1
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Yang L, Yin H, Bai L, Yao W, Tao T, Zhao Q, Gao Y, Teng J, Xu Z, Lin Q, Diao S, Pan Z, Guan D, Li B, Zhou H, Zhou Z, Zhao F, Wang Q, Pan Y, Zhang Z, Li K, Fang L, Liu GE. Mapping and functional characterization of structural variation in 1060 pig genomes. Genome Biol 2024; 25:116. [PMID: 38715020 PMCID: PMC11075355 DOI: 10.1186/s13059-024-03253-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Accepted: 04/19/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Structural variations (SVs) have significant impacts on complex phenotypes by rearranging large amounts of DNA sequence. RESULTS We present a comprehensive SV catalog based on the whole-genome sequence of 1060 pigs (Sus scrofa) representing 101 breeds, covering 9.6% of the pig genome. This catalog includes 42,487 deletions, 37,913 mobile element insertions, 3308 duplications, 1664 inversions, and 45,184 break ends. Estimates of breed ancestry and hybridization using genotyped SVs align well with those from single nucleotide polymorphisms. Geographically stratified deletions are observed, along with known duplications of the KIT gene, responsible for white coat color in European pigs. Additionally, we identify a recent SINE element insertion in MYO5A transcripts of European pigs, potentially influencing alternative splicing patterns and coat color alterations. Furthermore, a Yorkshire-specific copy number gain within ABCG2 is found, impacting chromatin interactions and gene expression across multiple tissues over a stretch of genomic region of ~200 kb. Preliminary investigations into SV's impact on gene expression and traits using the Pig Genotype-Tissue Expression (PigGTEx) data reveal SV associations with regulatory variants and gene-trait pairs. For instance, a 51-bp deletion is linked to the lead eQTL of the lipid metabolism regulating gene FADS3, whose expression in embryo may affect loin muscle area, as revealed by our transcriptome-wide association studies. CONCLUSIONS This SV catalog serves as a valuable resource for studying diversity, evolutionary history, and functional shaping of the pig genome by processes like domestication, trait-based breeding, and adaptive evolution.
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Affiliation(s)
- Liu Yang
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Hongwei Yin
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Lijing Bai
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Wenye Yao
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Tan Tao
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Qianyi Zhao
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Jinyan Teng
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Zhiting Xu
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Qing Lin
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Shuqi Diao
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Zhangyuan Pan
- Department of Animal Science, University of California-Davis, Davis, CA, USA
| | - Dailu Guan
- Department of Animal Science, University of California-Davis, Davis, CA, USA
| | - Bingjie Li
- Animal and Veterinary Sciences, Scotland's Rural College (SRUC), Roslin Institute Building, Easter Bush, Midlothian, EH25 9RG, United Kingdom
| | - Huaijun Zhou
- Department of Animal Science, University of California-Davis, Davis, CA, USA
| | - Zhongyin Zhou
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Fuping Zhao
- Key Laboratory of Animal Genetics, Breeding and Reproduction (Poultry) of Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Qishan Wang
- Department of Animal Science, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yuchun Pan
- Department of Animal Science, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Zhe Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Kui Li
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China.
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA.
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Sun J, Xie F, Wang J, Luo J, Chen T, Jiang Q, Xi Q, Liu GE, Zhang Y. Integrated meta-omics reveals the regulatory landscape involved in lipid metabolism between pig breeds. Microbiome 2024; 12:33. [PMID: 38374121 PMCID: PMC10877772 DOI: 10.1186/s40168-023-01743-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Accepted: 12/19/2023] [Indexed: 02/21/2024]
Abstract
BACKGROUND Domesticated pigs serve as an ideal animal model for biomedical research and also provide the majority of meat for human consumption in China. Porcine intramuscular fat content associates with human health and diseases and is essential in pork quality. The molecular mechanisms controlling lipid metabolism and intramuscular fat accretion across tissues in pigs, and how these changes in response to pig breeds, remain largely unknown. RESULTS We surveyed the tissue-resident cell types of the porcine jejunum, colon, liver, and longissimus dorsi muscle between Lantang and Landrace breeds by single-cell RNA sequencing. Combining lipidomics and metagenomics approaches, we also characterized gene signatures and determined key discriminating markers of lipid digestibility, absorption, conversion, and deposition across tissues in two pig breeds. In Landrace, lean-meat swine mainly exhibited breed-specific advantages in lipid absorption and oxidation for energy supply in small and large intestinal epitheliums, nascent high-density lipoprotein synthesis for reverse cholesterol transport in enterocytes and hepatocytes, bile acid formation, and secretion for fat emulsification in hepatocytes, as well as intestinal-microbiota gene expression involved in lipid accumulation product. In Lantang, obese-meat swine showed a higher synthesis capacity of chylomicrons responsible for high serum triacylglycerol levels in small intestinal epitheliums, the predominant characteristics of lipid absorption in muscle tissue, and greater intramuscular adipcytogenesis potentials from muscular fibro-adipogenic progenitor subpopulation. CONCLUSIONS The findings enhanced our understanding of the cellular biology of lipid metabolism and opened new avenues to improve animal production and human diseases. Video Abstract.
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Affiliation(s)
- Jiajie Sun
- Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China
| | - Fang Xie
- Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China
| | - Jing Wang
- Institute of Animal Husbandry and Veterinary Medicine, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China
| | - Junyi Luo
- Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China
| | - Ting Chen
- Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China
| | - Qingyan Jiang
- Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China
| | - Qianyun Xi
- Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, USDA-ARS, BARC-East, Beltsville, MD, 20705, USA.
| | - Yongliang Zhang
- Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China.
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3
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Sun X, Guo J, Li R, Zhang H, Zhang Y, Liu GE, Emu Q, Zhang H. Whole-Genome Resequencing Reveals Genetic Diversity and Wool Trait-Related Genes in Liangshan Semi-Fine-Wool Sheep. Animals (Basel) 2024; 14:444. [PMID: 38338087 PMCID: PMC10854784 DOI: 10.3390/ani14030444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Revised: 01/12/2024] [Accepted: 01/25/2024] [Indexed: 02/12/2024] Open
Abstract
Understanding the genetic makeup of local sheep breeds is essential for their scientific conservation and sustainable utilization. The Liangshan semi-fine-wool sheep (LSS), a Chinese semi-fine-wool breed renowned for its soft wool, was analyzed using whole-genome sequencing data including 35 LSS, 84 sheep from other domestic breeds, and 20 Asiatic mouflons. We investigated the genetic composition of LSS by conducting analyses of the population structure, runs of homozygosity, genomic inbreeding coefficients, and selection signature. Our findings indicated that LSS shares greater genetic similarity with Border Leicester and Romney sheep than with Tibetan (TIB), Yunnan (YNS), and Chinese Merino sheep. Genomic analysis indicated low to moderate inbreeding coefficients, ranging from 0.014 to 0.154. In identifying selection signals across the LSS genome, we pinpointed 195 candidate regions housing 74 annotated genes (e.g., IRF2BP2, BVES, and ALOX5). We also found the overlaps between the candidate regions and several known quantitative trait loci related to wool traits, such as the wool staple length and wool fiber diameter. A selective sweep region, marked by the highest value of cross-population extended haplotype homozygosity, encompassed IRF2BP2-an influential candidate gene affecting fleece fiber traits. Furthermore, notable differences in genotype frequency at a mutation site (c.1051 + 46T > C, Chr25: 6,784,190 bp) within IRF2BP2 were observed between LSS and TIB and YNS sheep (Fisher's exact test, p < 2.2 × 10-16). Taken together, these findings offer insights crucial for the conservation and breeding enhancement of LSS.
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Affiliation(s)
- Xueliang Sun
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (X.S.); (J.G.)
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
| | - Jiazhong Guo
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (X.S.); (J.G.)
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
| | - Ran Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Huanhuan Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yifei Zhang
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (X.S.); (J.G.)
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Quzhe Emu
- Animal Genetics and Breeding Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, No. 7, Niusha Road, Chengdu 610066, China
| | - Hongping Zhang
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (X.S.); (J.G.)
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
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4
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Teng J, Gao Y, Yin H, Bai Z, Liu S, Zeng H, Bai L, Cai Z, Zhao B, Li X, Xu Z, Lin Q, Pan Z, Yang W, Yu X, Guan D, Hou Y, Keel BN, Rohrer GA, Lindholm-Perry AK, Oliver WT, Ballester M, Crespo-Piazuelo D, Quintanilla R, Canela-Xandri O, Rawlik K, Xia C, Yao Y, Zhao Q, Yao W, Yang L, Li H, Zhang H, Liao W, Chen T, Karlskov-Mortensen P, Fredholm M, Amills M, Clop A, Giuffra E, Wu J, Cai X, Diao S, Pan X, Wei C, Li J, Cheng H, Wang S, Su G, Sahana G, Lund MS, Dekkers JCM, Kramer L, Tuggle CK, Corbett R, Groenen MAM, Madsen O, Gòdia M, Rocha D, Charles M, Li CJ, Pausch H, Hu X, Frantz L, Luo Y, Lin L, Zhou Z, Zhang Z, Chen Z, Cui L, Xiang R, Shen X, Li P, Huang R, Tang G, Li M, Zhao Y, Yi G, Tang Z, Jiang J, Zhao F, Yuan X, Liu X, Chen Y, Xu X, Zhao S, Zhao P, Haley C, Zhou H, Wang Q, Pan Y, Ding X, Ma L, Li J, Navarro P, Zhang Q, Li B, Tenesa A, Li K, Liu GE, Zhang Z, Fang L. A compendium of genetic regulatory effects across pig tissues. Nat Genet 2024; 56:112-123. [PMID: 38177344 PMCID: PMC10786720 DOI: 10.1038/s41588-023-01585-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 10/13/2023] [Indexed: 01/06/2024]
Abstract
The Farm Animal Genotype-Tissue Expression (FarmGTEx) project has been established to develop a public resource of genetic regulatory variants in livestock, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biological discovery and exploitation in animal breeding and human biomedicine. Here we show results from the pilot phase of PigGTEx by processing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples passing quality control from pigs. We build a pig genotype imputation panel and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We evaluate tissue specificity of regulatory effects and elucidate molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying 207 pig complex phenotypes and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, supporting the importance of pigs as a human biomedical model.
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Affiliation(s)
- Jinyan Teng
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University (SCAU), Guangzhou, China
| | - Yahui Gao
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University (SCAU), Guangzhou, China
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service (ARS), U.S. Department of Agriculture (USDA), Beltsville, MD, USA
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, USA
| | - Hongwei Yin
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Zhonghao Bai
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Shuli Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service (ARS), U.S. Department of Agriculture (USDA), Beltsville, MD, USA
- School of Life Sciences, Westlake University, Hangzhou, China
| | - Haonan Zeng
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University (SCAU), Guangzhou, China
| | - Lijing Bai
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Zexi Cai
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Bingru Zhao
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Xiujin Li
- Guangdong Provincial Key Laboratory of Waterfowl Healthy Breeding, College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, China
| | - Zhiting Xu
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University (SCAU), Guangzhou, China
| | - Qing Lin
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University (SCAU), Guangzhou, China
| | - Zhangyuan Pan
- Department of Animal Science, University of California, Davis, Davis, CA, USA
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Wenjing Yang
- College of Animal Science and Technology, China Agricultural University, Beijing, China
- Department of Animal Science, University of California, Davis, Davis, CA, USA
| | - Xiaoshan Yu
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Dailu Guan
- Department of Animal Science, University of California, Davis, Davis, CA, USA
| | - Yali Hou
- Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Brittney N Keel
- ARS, USDA, U.S. Meat Animal Research Center, Clay Center, NE, USA
| | - Gary A Rohrer
- ARS, USDA, U.S. Meat Animal Research Center, Clay Center, NE, USA
| | | | - William T Oliver
- ARS, USDA, U.S. Meat Animal Research Center, Clay Center, NE, USA
| | - Maria Ballester
- Animal Breeding and Genetics Programme, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Torre Marimon, Caldes de Montbui, Spain
| | - Daniel Crespo-Piazuelo
- Animal Breeding and Genetics Programme, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Torre Marimon, Caldes de Montbui, Spain
| | - Raquel Quintanilla
- Animal Breeding and Genetics Programme, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Torre Marimon, Caldes de Montbui, Spain
| | - Oriol Canela-Xandri
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Konrad Rawlik
- Baillie Gifford Pandemic Science Hub, University of Edinburgh, Edinburgh, UK
| | - Charley Xia
- Lothian Birth Cohort studies, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Yuelin Yao
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
- School of Informatics, The University of Edinburgh, Edinburgh, UK
| | - Qianyi Zhao
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Wenye Yao
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Liu Yang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Houcheng Li
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Huicong Zhang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Wang Liao
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Tianshuo Chen
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Peter Karlskov-Mortensen
- Animal Genetics, Bioinformatics and Breeding, Department of Veterinary and Animal Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Merete Fredholm
- Animal Genetics, Bioinformatics and Breeding, Department of Veterinary and Animal Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marcel Amills
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus de la Universitat Autònoma de Barcelona, Bellaterra, Spain
- Departament de Ciència Animal i dels Aliments, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Alex Clop
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus de la Universitat Autònoma de Barcelona, Bellaterra, Spain
- Consejo Superior de Investigaciones Científicas, Barcelona, Spain
| | - Elisabetta Giuffra
- Paris-Saclay University, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France
| | - Jun Wu
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University (SCAU), Guangzhou, China
| | - Xiaodian Cai
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University (SCAU), Guangzhou, China
| | - Shuqi Diao
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University (SCAU), Guangzhou, China
| | - Xiangchun Pan
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University (SCAU), Guangzhou, China
| | - Chen Wei
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University (SCAU), Guangzhou, China
| | - Jinghui Li
- Department of Animal Science, University of California, Davis, Davis, CA, USA
| | - Hao Cheng
- Department of Animal Science, University of California, Davis, Davis, CA, USA
| | - Sheng Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Guosheng Su
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Goutam Sahana
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Mogens Sandø Lund
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Jack C M Dekkers
- Department of Animal Science, Iowa State University, Ames, IA, USA
| | - Luke Kramer
- Department of Animal Science, Iowa State University, Ames, IA, USA
| | | | - Ryan Corbett
- Department of Animal Science, Iowa State University, Ames, IA, USA
| | - Martien A M Groenen
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Ole Madsen
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Marta Gòdia
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus de la Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Dominique Rocha
- Paris-Saclay University, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France
| | - Mathieu Charles
- Paris-Saclay University, INRAE, AgroParisTech, GABI, SIGENAE, Jouy-en-Josas, France
| | - Cong-Jun Li
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service (ARS), U.S. Department of Agriculture (USDA), Beltsville, MD, USA
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, Zurich, Switzerland
| | - Xiaoxiang Hu
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Laurent Frantz
- Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, Munich, Germany
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - Yonglun Luo
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
- Lars Bolund Institute of Regenerative Medicine, Qingdao-Europe Advanced Institute for Life Sciences, BGI-Research, Qingdao, China
| | - Lin Lin
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
| | - Zhongyin Zhou
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Zhe Zhang
- Department of Animal Science, College of Animal Sciences, Zhejiang University, Hangzhou, China
| | - Zitao Chen
- Department of Animal Science, College of Animal Sciences, Zhejiang University, Hangzhou, China
| | - Leilei Cui
- School of Life Sciences, Nanchang University, Nanchang, China
- Human Aging Research Institute and School of Life Science, Nanchang University, and Jiangxi Key Laboratory of Human Aging, Jiangxi, China
- UCL Genetics Institute, University College London, London, UK
| | - Ruidong Xiang
- Faculty of Veterinary and Agricultural Science, The University of Melbourne, Parkville, Victoria, Australia
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, Victoria, Australia
| | - Xia Shen
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine, Fudan University, Guangzhou, China
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Pinghua Li
- Institute of Swine Science, Nanjing Agricultural University, Nanjing, China
| | - Ruihua Huang
- Institute of Swine Science, Nanjing Agricultural University, Nanjing, China
| | - Guoqing Tang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Mingzhou Li
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Yunxiang Zhao
- College of Animal Science and Technology, Guangxi University, Nanning, China
| | - Guoqiang Yi
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Zhonglin Tang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Jicai Jiang
- Department of Animal Science, North Carolina State University, Raleigh, NC, USA
| | - Fuping Zhao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xiaolong Yuan
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University (SCAU), Guangzhou, China
| | - Xiaohong Liu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Yaosheng Chen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Xuewen Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education and College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Shuhong Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education and College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Pengju Zhao
- Hainan Institute, Zhejiang University, Yongyou Industry Park, Yazhou Bay Sci-Tech City, Sanya, China
| | - Chris Haley
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, UK
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, Davis, CA, USA
| | - Qishan Wang
- Department of Animal Science, College of Animal Sciences, Zhejiang University, Hangzhou, China
| | - Yuchun Pan
- Department of Animal Science, College of Animal Sciences, Zhejiang University, Hangzhou, China
| | - Xiangdong Ding
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, USA
| | - Jiaqi Li
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University (SCAU), Guangzhou, China
| | - Pau Navarro
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, UK
| | - Qin Zhang
- College of Animal Science and Technology, Shandong Agricultural University, Tai'an, China
| | - Bingjie Li
- Scotland's Rural College (SRUC), Roslin Institute Building, Midlothian, UK
| | - Albert Tenesa
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK.
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, UK.
| | - Kui Li
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service (ARS), U.S. Department of Agriculture (USDA), Beltsville, MD, USA.
| | - Zhe Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University (SCAU), Guangzhou, China.
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK.
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5
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Hu Z, Boschiero C, Li CJ, Connor EE, Baldwin RL, Liu GE. Unraveling the Genetic Basis of Feed Efficiency in Cattle through Integrated DNA Methylation and CattleGTEx Analysis. Genes (Basel) 2023; 14:2121. [PMID: 38136943 PMCID: PMC10742843 DOI: 10.3390/genes14122121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 11/21/2023] [Accepted: 11/22/2023] [Indexed: 12/24/2023] Open
Abstract
Feed costs can amount to 75 percent of the total overhead cost of raising cows for milk production. Meanwhile, the livestock industry is considered a significant contributor to global climate change due to the production of greenhouse gas emissions, such as methane. Indeed, the genetic basis of feed efficiency (FE) is of great interest to the animal research community. Here, we explore the epigenetic basis of FE to provide base knowledge for the development of genomic tools to improve FE in cattle. The methylation level of 37,554 CpG sites was quantified using a mammalian methylation array (HorvathMammalMethylChip40) for 48 Holstein cows with extreme residual feed intake (RFI). We identified 421 CpG sites related to 287 genes that were associated with RFI, several of which were previously associated with feeding or digestion issues. Activator of transcription and developmental regulation (AUTS2) is associated with digestive disorders in humans, while glycerol-3-phosphate dehydrogenase 2 (GPD2) encodes a protein on the inner mitochondrial membrane, which can regulate glucose utilization and fatty acid and triglyceride synthesis. The extensive expression and co-expression of these genes across diverse tissues indicate the complex regulation of FE in cattle. Our study provides insight into the epigenetic basis of RFI and gene targets to improve FE in dairy cattle.
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Affiliation(s)
- Zhenbin Hu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD 20705, USA
| | - Clarissa Boschiero
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD 20705, USA
| | - Cong-Jun Li
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD 20705, USA
| | - Erin E. Connor
- Department of Animal and Food Sciences, University of Delaware, Newark, DE 19716, USA
| | - Ransom L. Baldwin
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD 20705, USA
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD 20705, USA
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6
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Liu M, Cheng J, Chen Y, Yang L, Raza SHA, Huang Y, Lei C, Liu GE, Lan X, Chen H. Distribution of DGAT1 copy number variation in Chinese goats and its associations with milk production traits. Anim Biotechnol 2023; 34:980-985. [PMID: 34854798 DOI: 10.1080/10495398.2021.2007118] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Goat is an important sector for meat and dairy products. Diacylglycerol O-acyltransferase 1 (DGAT1), which is a key gene in milk production, has been recently detected to overlap with a novel copy number variation (CNV) in goats. CNVs could be genetic markers providing new insights into the genetic basis of phenotypic variation. Up to now, there are no reports on the DGAT1-related CNV (DGAT1 CNV) in Chinese goats. This study first detected the distribution of the DGAT1 CNV in Chinese seven goat breeds, finding substantial differences among dairy, meat, and fiber goats (P < 0.01). The association analysis between the DGAT1 CNV and milk production traits revealed significant associations: Xinong Sannen (XS) dairy goat with copy number loss type had higher freezing point depression (FPD) (P < 0.01) and milk solids-not-fat (SNF) content (P < 0.05). Overall, our study unraveled the distribution of DGAT1 CNV in Chinese goats for the first time and found the potential role of this CNV in the marker-assisted selection of dairy goat breeding.
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Affiliation(s)
- Mei Liu
- Animal Nutritional Genome and Germplasm Innovation Research Center, College of Animal Science and Technology, Hunan Agricultural University, Changsha, Hunan, China
- College of Animal Science and Technology, Northwest A & F University, Shaanxi Key Laboratory of Molecular Biology for Agriculture, Yangling, Shaanxi, China
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, Maryland, USA
| | - Jie Cheng
- College of Animal Science and Technology, Northwest A & F University, Shaanxi Key Laboratory of Molecular Biology for Agriculture, Yangling, Shaanxi, China
| | - Yuhan Chen
- Animal Nutritional Genome and Germplasm Innovation Research Center, College of Animal Science and Technology, Hunan Agricultural University, Changsha, Hunan, China
| | - Long Yang
- Animal Nutritional Genome and Germplasm Innovation Research Center, College of Animal Science and Technology, Hunan Agricultural University, Changsha, Hunan, China
| | - Sayed Haidar Abbas Raza
- College of Animal Science and Technology, Northwest A & F University, Shaanxi Key Laboratory of Molecular Biology for Agriculture, Yangling, Shaanxi, China
| | - Yongzhen Huang
- College of Animal Science and Technology, Northwest A & F University, Shaanxi Key Laboratory of Molecular Biology for Agriculture, Yangling, Shaanxi, China
| | - Chuzhao Lei
- College of Animal Science and Technology, Northwest A & F University, Shaanxi Key Laboratory of Molecular Biology for Agriculture, Yangling, Shaanxi, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, Maryland, USA
| | - Xianyong Lan
- College of Animal Science and Technology, Northwest A & F University, Shaanxi Key Laboratory of Molecular Biology for Agriculture, Yangling, Shaanxi, China
| | - Hong Chen
- College of Animal Science and Technology, Northwest A & F University, Shaanxi Key Laboratory of Molecular Biology for Agriculture, Yangling, Shaanxi, China
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7
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Gao Y, Marceau A, Iqbal V, Torres-Vázquez JA, Neupane M, Jiang J, Liu GE, Ma L. Genome-wide association analysis of heifer livability and early first calving in Holstein cattle. BMC Genomics 2023; 24:628. [PMID: 37865759 PMCID: PMC10590504 DOI: 10.1186/s12864-023-09736-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 10/12/2023] [Indexed: 10/23/2023] Open
Abstract
BACKGROUND The survival and fertility of heifers are critical factors for the success of dairy farms. The mortality of heifers poses a significant challenge to the management and profitability of the dairy industry. In dairy farming, achieving early first calving of heifers is also essential for optimal productivity and sustainability. Recently, Council on Dairy Cattle Breeding (CDCB) and USDA have developed new evaluations of heifer health and fertility traits. However, the genetic basis of these traits has yet to be thoroughly studied. RESULTS Leveraging the extensive U.S dairy genomic database maintained at CDCB, we conducted large-scale GWAS analyses of two heifer traits, livability and early first calving. Despite the large sample size, we found no major QTL for heifer livability. However, we identified a major QTL in the bovine MHC region associated with early first calving. Our GO analysis based on nearby genes detected 91 significant GO terms with a large proportion related to the immune system. This QTL in the MHC region was also confirmed in the analysis of 27 K bull with imputed sequence variants. Since these traits have few major QTL, we evaluated the genome-wide distribution of GWAS signals across different functional genomics categories. For heifer livability, we observed significant enrichment in promotor and enhancer-related regions. For early calving, we found more associations in active TSS, active Elements, and Insulator. We also identified significant enrichment of CDS and conserved variants in the GWAS results of both traits. By linking GWAS results and transcriptome data from the CattleGTEx project via TWAS, we detected four and 23 significant gene-trait association pairs for heifer livability and early calving, respectively. Interestingly, we discovered six genes for early calving in the Bovine MHC region, including two genes in lymph node tissue and one gene each in blood, adipose, hypothalamus, and leukocyte. CONCLUSION Our large-scale GWAS analyses of two heifer traits identified a major QTL in the bovine MHC region for early first calving. Additional functional enrichment and TWAS analyses confirmed the MHC QTL with relevant biological evidence. Our results revealed the complex genetic basis of heifer health and fertility traits and indicated a potential connection between the immune system and reproduction in cattle.
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Affiliation(s)
- Yahui Gao
- Department of Animal and Avian Sciences, University of Maryland, Room 2123, 8127 Regents Drive, College Park, MD, 20742, USA
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, 20705, USA
| | - Alexis Marceau
- Department of Animal and Avian Sciences, University of Maryland, Room 2123, 8127 Regents Drive, College Park, MD, 20742, USA
| | - Victoria Iqbal
- Department of Animal and Avian Sciences, University of Maryland, Room 2123, 8127 Regents Drive, College Park, MD, 20742, USA
| | - Jose Antonio Torres-Vázquez
- Department of Animal and Avian Sciences, University of Maryland, Room 2123, 8127 Regents Drive, College Park, MD, 20742, USA
| | - Mahesh Neupane
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, 20705, USA
| | - Jicai Jiang
- Department of Animal Science, North Carolina State University, Raleigh, 27695, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, 20705, USA
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, Room 2123, 8127 Regents Drive, College Park, MD, 20742, USA.
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8
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Peng L, Zhang X, Du Y, Li F, Han J, Liu O, Dai S, Zhang X, Liu GE, Yang L, Zhou Y. New insights into transcriptome variation during cattle adipocyte adipogenesis by direct RNA sequencing. iScience 2023; 26:107753. [PMID: 37692285 PMCID: PMC10492216 DOI: 10.1016/j.isci.2023.107753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 07/31/2023] [Accepted: 08/24/2023] [Indexed: 09/12/2023] Open
Abstract
We performed direct RNA sequencing (DRS) together with PCR-amplified cDNA long and short read sequencing for cattle adipocyte at different stages. We proved that the DRS was with advantages to avoid artificial transcripts and questionable exitrons. Totally, we obtained 68,124 transcripts with information of alternative splicing, poly (A) length and mRNA modification. The number of transcripts for adipogenesis was expanded by alternative splicing, which lead regulation mechanisms far more complex than ever known. We detected 891 differentially expressed genes (DEGs). However, 62.78% transcripts of DEGs were not significantly differentially expressed, and 248 transcripts showed opposite changing directions with their genes. The poly (A) tail became globally shorter in differentiated adipocyte than in primary adipocyte, and had a weak negative correlation with gene/transcript expression. Moreover, the study of different mRNA modifications implied their potential roles in gene expression and alternative splicing. Overall, our study promoted better understanding of adipogenesis mechanisms in cattle adipocytes.
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Affiliation(s)
- Lingwei Peng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiaolian Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Yuqin Du
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Fan Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Jiazheng Han
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Oujin Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Shoulu Dai
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiang Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD 20705, USA
| | - Liguo Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
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9
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Xiang R, Fang L, Liu S, Macleod IM, Liu Z, Breen EJ, Gao Y, Liu GE, Tenesa A, Mason BA, Chamberlain AJ, Wray NR, Goddard ME. Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle. Cell Genom 2023; 3:100385. [PMID: 37868035 PMCID: PMC10589627 DOI: 10.1016/j.xgen.2023.100385] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 08/10/2022] [Accepted: 07/26/2023] [Indexed: 10/24/2023]
Abstract
Many quantitative trait loci (QTLs) are in non-coding regions. Therefore, QTLs are assumed to affect gene regulation. Gene expression and RNA splicing are primary steps of transcription, so DNA variants changing gene expression (eVariants) or RNA splicing (sVariants) are expected to significantly affect phenotypes. We quantify the contribution of eVariants and sVariants detected from 16 tissues (n = 4,725) to 37 traits of ∼120,000 cattle (average magnitude of genetic correlation between traits = 0.13). Analyzed in Bayesian mixture models, averaged across 37 traits, cis and trans eVariants and sVariants detected from 16 tissues jointly explain 69.2% (SE = 0.5%) of heritability, 44% more than expected from the same number of random variants. This 69.2% includes an average of 24% from trans e-/sVariants (14% more than expected). Averaged across 56 lipidomic traits, multi-tissue cis and trans e-/sVariants also explain 71.5% (SE = 0.3%) of heritability, demonstrating the essential role of proximal and distal regulatory variants in shaping mammalian phenotypes.
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Affiliation(s)
- Ruidong Xiang
- Faculty of Veterinary & Agricultural Science, the University of Melbourne, Parkville, VIC 3052, Australia
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
- Cambridge-Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
| | - Lingzhao Fang
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, the University of Edinburgh, Edinburgh, UK
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Shuli Liu
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Iona M. Macleod
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
| | - Zhiqian Liu
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
| | - Edmond J. Breen
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Albert Tenesa
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, the University of Edinburgh, Edinburgh, UK
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, the University of Edinburgh, Midlothian EH25 9RG, UK
| | - CattleGTEx Consortium
- Faculty of Veterinary & Agricultural Science, the University of Melbourne, Parkville, VIC 3052, Australia
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
- Cambridge-Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, the University of Edinburgh, Edinburgh, UK
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, the University of Edinburgh, Midlothian EH25 9RG, UK
- Institute for Molecular Bioscience, the University of Queensland, Brisbane, QLD 4072, Australia
- Queensland Brain Institute, the University of Queensland, Brisbane, QLD 4072, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
| | - Brett A. Mason
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
| | - Amanda J. Chamberlain
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
| | - Naomi R. Wray
- Institute for Molecular Bioscience, the University of Queensland, Brisbane, QLD 4072, Australia
- Queensland Brain Institute, the University of Queensland, Brisbane, QLD 4072, Australia
| | - Michael E. Goddard
- Faculty of Veterinary & Agricultural Science, the University of Melbourne, Parkville, VIC 3052, Australia
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
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10
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Marceau A, Wang J, Iqbal V, Jiang J, Liu GE, Ma L. Investigation of lncRNA in Bos taurus Mammary Tissue during Dry and Lactation Periods. Genes (Basel) 2023; 14:1789. [PMID: 37761929 PMCID: PMC10531232 DOI: 10.3390/genes14091789] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 09/01/2023] [Accepted: 09/08/2023] [Indexed: 09/29/2023] Open
Abstract
This study aims to collect RNA-Seq data from Bos taurus samples representing dry and lactating mammary tissue, identify lncRNA transcripts, and analyze findings for their features and functional annotation. This allows for connections to be drawn between lncRNA and the lactation process. RNA-Seq data from 103 samples of Bos taurus mammary tissue were gathered from publicly available databases (60 dry, 43 lactating). The samples were filtered to reveal 214 dry mammary lncRNA transcripts and 517 lactating mammary lncRNA transcripts. The lncRNAs met common lncRNA characteristics such as shorter length, fewer exons, lower expression levels, and less sequence conservation when compared to the genome. Interestingly, several lncRNAs showed sequence similarity to genes associated with strong hair keratin intermediate filaments. Human breast cancer research has associated strong hair keratin filaments with mammary tissue cellular resilience. The lncRNAs were also associated with several genes/proteins that linked to pregnancy using expression correlation and gene ontology. Such findings indicate that there are crucial relationships between the lncRNAs found in mammary tissue and the development of the tissue, to meet both the animal's needs and our own production needs; these relationships should be further investigated to ensure that we continue to breed the most resilient, efficient dairy cattle.
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Affiliation(s)
- Alexis Marceau
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA; (A.M.); (V.I.)
| | - Junjian Wang
- Department of Animal Science, North Carlonina State University, Raleigh, NC 27695, USA; (J.W.); (J.J.)
| | - Victoria Iqbal
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA; (A.M.); (V.I.)
| | - Jicai Jiang
- Department of Animal Science, North Carlonina State University, Raleigh, NC 27695, USA; (J.W.); (J.J.)
| | - George E. Liu
- Animal Genomics and Improvemennt Laboratory, BARC, USDA-ARS, Beltsville, MD 20705, USA;
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA; (A.M.); (V.I.)
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11
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Zhao P, Gu L, Gao Y, Pan Z, Liu L, Li X, Zhou H, Yu D, Han X, Qian L, Liu GE, Fang L, Wang Z. Young SINEs in pig genomes impact gene regulation, genetic diversity, and complex traits. Commun Biol 2023; 6:894. [PMID: 37652983 PMCID: PMC10471783 DOI: 10.1038/s42003-023-05234-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 08/09/2023] [Indexed: 09/02/2023] Open
Abstract
Transposable elements (TEs) are a major source of genetic polymorphisms and play a role in chromatin architecture, gene regulatory networks, and genomic evolution. However, their functional role in pigs and contributions to complex traits are largely unknown. We created a catalog of TEs (n = 3,087,929) in pigs and found that young SINEs were predominantly silenced by histone modifications, DNA methylation, and decreased accessibility. However, some transcripts from active young SINEs showed high tissue-specificity, as confirmed by analyzing 3570 RNA-seq samples. We also detected 211,067 dimorphic SINEs in 374 individuals, including 340 population-specific ones associated with local adaptation. Mapping these dimorphic SINEs to genome-wide associations of 97 complex traits in pigs, we found 54 candidate genes (e.g., ANK2 and VRTN) that might be mediated by TEs. Our findings highlight the important roles of young SINEs and provide a supplement for genotype-to-phenotype associations and modern breeding in pigs.
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Affiliation(s)
- Pengju Zhao
- Hainan Institute, Zhejiang University, Yongyou Industry Park, Yazhou Bay Sci-Tech City, Sanya, 572000, China
- College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Lihong Gu
- Institute of Animal Science & Veterinary Medicine, Hainan Academy of Agricultural Sciences, No. 14 Xingdan Road, Haikou, 571100, China
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Zhangyuan Pan
- Department of Animal Science, University of California, Davis, CA, 95616, USA
| | - Lei Liu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China
| | - Xingzheng Li
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, CA, 95616, USA
| | - Dongyou Yu
- Hainan Institute, Zhejiang University, Yongyou Industry Park, Yazhou Bay Sci-Tech City, Sanya, 572000, China
- College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Xinyan Han
- Hainan Institute, Zhejiang University, Yongyou Industry Park, Yazhou Bay Sci-Tech City, Sanya, 572000, China
- College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Lichun Qian
- Hainan Institute, Zhejiang University, Yongyou Industry Park, Yazhou Bay Sci-Tech City, Sanya, 572000, China
- College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA.
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, 8000, Denmark.
| | - Zhengguang Wang
- Hainan Institute, Zhejiang University, Yongyou Industry Park, Yazhou Bay Sci-Tech City, Sanya, 572000, China.
- College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China.
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12
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Wang X, Gao Y, Li CJ, Fang L, Liu GE, Zhao X, Zhang Y, Cai G, Xue G, Liu Y, Wang L, Zhang F, Wang K, Zhang M, Li R, Gao Y, Li J. The single-cell transcriptome and chromatin accessibility datasets of peripheral blood mononuclear cells in Chinese holstein cattle. BMC Genom Data 2023; 24:39. [PMID: 37550629 PMCID: PMC10408222 DOI: 10.1186/s12863-023-01139-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Accepted: 06/30/2023] [Indexed: 08/09/2023] Open
Abstract
OBJECTIVES This study was performed in the frame of a more extensive study dedicated to the integrated analysis of the single-cell transcriptome and chromatin accessibility datasets of peripheral blood mononuclear cells (PBMCs) with a large-scale GWAS of 45 complex traits in Chinese Holstein cattle. Lipopolysaccharide (LPS) is a crucial mediator of chronic inflammation to modulate immune responses. PBMCs include primary T and B cells, natural killer (NK) cells, monocytes (Mono), and dendritic cells (DC). How LPS stimulates PBMCs at the single-cell level in dairy cattle remains largely unknown. DATA DESCRIPTION We sequenced 30,756 estimated single cells and mapped 26,141 of them (96.05%) with approximately 60,075 mapped reads per cell after quality control for four whole-blood treatments (no, 2 h, 4 h, and 8 h LPS) by single-cell RNA sequencing (scRNA-seq) and single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq). Finally, 7,107 (no), 9,174 (2 h), 6,741 (4 h), and 3,119 (8 h) cells were generated with ~ 15,000 total genes in the whole population. Therefore, the single-cell transcriptome and chromatin accessibility datasets in this study enable a further understanding of the cell types and functions of PBMCs and their responses to LPS stimulation in vitro.
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Affiliation(s)
- Xiao Wang
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Cong-Jun Li
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, 8000, Denmark
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Xiuxin Zhao
- Shandong OX Livestock Breeding Co., Ltd, Jinan, 250100, China
| | - Yuanpei Zhang
- Shandong OX Livestock Breeding Co., Ltd, Jinan, 250100, China
| | - Gaozhan Cai
- Shandong OX Livestock Breeding Co., Ltd, Jinan, 250100, China
| | - Guanghui Xue
- Shandong OX Livestock Breeding Co., Ltd, Jinan, 250100, China
| | - Yan Liu
- Shandong OX Livestock Breeding Co., Ltd, Jinan, 250100, China
| | - Lingling Wang
- Shandong OX Livestock Breeding Co., Ltd, Jinan, 250100, China
| | - Fan Zhang
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Kun Wang
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Miao Zhang
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Rongling Li
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Yundong Gao
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
| | - Jianbin Li
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
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13
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Wang X, Li W, Feng X, Li J, Liu GE, Fang L, Yu Y. Correction: Harnessing male germline epigenomics for the genetic improvement in cattle. J Anim Sci Biotechnol 2023; 14:110. [PMID: 37528452 PMCID: PMC10394826 DOI: 10.1186/s40104-023-00917-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/03/2023] Open
Affiliation(s)
- Xiao Wang
- Laboratory of Animal Genetics and Breeding, Ministry of Agriculture and Rural Affairs of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
- Konge Larsen ApS, 2800, Kongens Lyngby, Denmark
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Wenlong Li
- Laboratory of Animal Genetics and Breeding, Ministry of Agriculture and Rural Affairs of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Xia Feng
- Laboratory of Animal Genetics and Breeding, Ministry of Agriculture and Rural Affairs of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Jianbin Li
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, Henry A. Wallace Beltsville Agricultural Research Center, USDA, Beltsville, MD, 20705, USA
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, 8000, Aarhus, Denmark.
| | - Ying Yu
- Laboratory of Animal Genetics and Breeding, Ministry of Agriculture and Rural Affairs of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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14
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Zhao P, Peng C, Fang L, Wang Z, Liu GE. Taming transposable elements in livestock and poultry: a review of their roles and applications. Genet Sel Evol 2023; 55:50. [PMID: 37479995 PMCID: PMC10362595 DOI: 10.1186/s12711-023-00821-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 06/30/2023] [Indexed: 07/23/2023] Open
Abstract
Livestock and poultry play a significant role in human nutrition by converting agricultural by-products into high-quality proteins. To meet the growing demand for safe animal protein, genetic improvement of livestock must be done sustainably while minimizing negative environmental impacts. Transposable elements (TE) are important components of livestock and poultry genomes, contributing to their genetic diversity, chromatin states, gene regulatory networks, and complex traits of economic value. However, compared to other species, research on TE in livestock and poultry is still in its early stages. In this review, we analyze 72 studies published in the past 20 years, summarize the TE composition in livestock and poultry genomes, and focus on their potential roles in functional genomics. We also discuss bioinformatic tools and strategies for integrating multi-omics data with TE, and explore future directions, feasibility, and challenges of TE research in livestock and poultry. In addition, we suggest strategies to apply TE in basic biological research and animal breeding. Our goal is to provide a new perspective on the importance of TE in livestock and poultry genomes.
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Affiliation(s)
- Pengju Zhao
- Hainan Institute of Zhejiang University, Hainan Sanya, 572000, China
- College of Animal Sciences, Zhejiang University, Zhejiang, Hangzhou, People's Republic of China
| | - Chen Peng
- Hainan Institute of Zhejiang University, Hainan Sanya, 572000, China
- College of Animal Sciences, Zhejiang University, Zhejiang, Hangzhou, People's Republic of China
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, 8000, Aarhus, Denmark.
| | - Zhengguang Wang
- Hainan Institute of Zhejiang University, Hainan Sanya, 572000, China.
- College of Animal Sciences, Zhejiang University, Zhejiang, Hangzhou, People's Republic of China.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA.
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15
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Kang X, Li C, Liu S, Baldwin RL, Liu GE, Li CJ. Genome-Wide Acetylation Modification of H3K27ac in Bovine Rumen Cell Following Butyrate Exposure. Biomolecules 2023; 13:1137. [PMID: 37509173 PMCID: PMC10377523 DOI: 10.3390/biom13071137] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/12/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
Butyrate contributes epigenetically to the changes in cellular function and tissue development of the rumen in ruminant animals, which might be achieved by its genetic or epigenetic regulation of gene expression. To explore the role of butyrate on bovine rumen epithelial function and development, this study characterized genome-wide H3K27ac modification changes and super-enhancer profiles in rumen epithelial primary cells (REPC) induced with butyrate by ChIP-seq, and analyzed its effects on gene expression and functional pathways by integrating RNA-seq data. The results showed that genome-wide acetylation modification was observed in the REPC with 94,675 and 48,688 peaks in the butyrate treatment and control group, respectively. A total of 9750 and 5020 genes with increased modification (H3K27ac-gain) and decreased modification (H3K27ac-loss) were detected in the treatment group. The super-enhancer associated genes in the butyrate-induction group were involved in the AMPK signaling pathway, MAPK signaling pathway, and ECM-receptor interaction. Finally, the up-regulated genes (PLCG1, CLEC3B, IGSF23, OTOP3, ADTRP) with H3K27ac gain modification by butyrate were involved in cholesterol metabolism, lysosome, cell adhesion molecules, and the PI3K-Akt signaling pathway. Butyrate treatment has the role of genome-wide H3K27ac acetylation on bovine REPC, and affects the changes in gene expression. The effect of butyrate on gene expression correlates with the acetylation of the H3K27ac level. Identifying genome-wide acetylation modifications and expressed genes of butyrate in bovine REPC cells will expand the understanding of the biological role of butyrate and its acetylation.
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Affiliation(s)
- Xiaolong Kang
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
- Key Laboratory of Ruminant Molecular and Cellular Breeding, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China
| | - Chenglong Li
- Key Laboratory of Ruminant Molecular and Cellular Breeding, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China
| | - Shuli Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
| | - Ransom L Baldwin
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
| | - Cong-Jun Li
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
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Wang X, Li W, Feng X, Li J, Liu GE, Fang L, Yu Y. Harnessing male germline epigenomics for the genetic improvement in cattle. J Anim Sci Biotechnol 2023; 14:76. [PMID: 37277852 PMCID: PMC10242889 DOI: 10.1186/s40104-023-00874-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 04/02/2023] [Indexed: 06/07/2023] Open
Abstract
Sperm is essential for successful artificial insemination in dairy cattle, and its quality can be influenced by both epigenetic modification and epigenetic inheritance. The bovine germline differentiation is characterized by epigenetic reprogramming, while intergenerational and transgenerational epigenetic inheritance can influence the offspring's development through the transmission of epigenetic features to the offspring via the germline. Therefore, the selection of bulls with superior sperm quality for the production and fertility traits requires a better understanding of the epigenetic mechanism and more accurate identifications of epigenetic biomarkers. We have comprehensively reviewed the current progress in the studies of bovine sperm epigenome in terms of both resources and biological discovery in order to provide perspectives on how to harness this valuable information for genetic improvement in the cattle breeding industry.
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Affiliation(s)
- Xiao Wang
- Laboratory of Animal Genetics and Breeding, Ministry of Agriculture and Rural Affairs of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
- Konge Larsen ApS, Kongens Lyngby, 2800, Denmark
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Wenlong Li
- Laboratory of Animal Genetics and Breeding, Ministry of Agriculture and Rural Affairs of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Xia Feng
- Laboratory of Animal Genetics and Breeding, Ministry of Agriculture and Rural Affairs of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Jianbing Li
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, Henry A. Wallace Beltsville Agricultural Research Center, USDA, Beltsville, MD, 20705, USA
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, 8000, Denmark.
| | - Ying Yu
- Laboratory of Animal Genetics and Breeding, Ministry of Agriculture and Rural Affairs of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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17
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Marceau A, Gao Y, Baldwin RL, Li CJ, Jiang J, Liu GE, Ma L. Investigation of rumen long noncoding RNA before and after weaning in cattle. BMC Genomics 2022; 23:531. [PMID: 35869425 PMCID: PMC9308236 DOI: 10.1186/s12864-022-08758-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 07/12/2022] [Indexed: 11/10/2022] Open
Abstract
Background This study aimed to identify long non-coding RNA (lncRNA) from the rumen tissue in dairy cattle, explore their features including expression and conservation levels, and reveal potential links between lncRNA and complex traits that may indicate important functional impacts of rumen lncRNA during the transition to the weaning period. Results A total of six cattle rumen samples were taken with three replicates from before and after weaning periods, respectively. Total RNAs were extracted and sequenced with lncRNA discovered based on size, coding potential, sequence homology, and known protein domains. As a result, 404 and 234 rumen lncRNAs were identified before and after weaning, respectively. However, only nine of them were shared under two conditions, with 395 lncRNAs found only in pre-weaning tissues and 225 only in post-weaning samples. Interestingly, none of the nine common lncRNAs were differentially expressed between the two weaning conditions. LncRNA averaged shorter length, lower expression, and lower conservation scores than the genome overall, which is consistent with general lncRNA characteristics. By integrating rumen lncRNA before and after weaning with large-scale GWAS results in cattle, we reported significant enrichment of both pre- and after-weaning lncRNA with traits of economic importance including production, reproduction, health, and body conformation phenotypes. Conclusions The majority of rumen lncRNAs are uniquely expressed in one of the two weaning conditions, indicating a functional role of lncRNA in rumen development and transition of weaning. Notably, both pre- and post-weaning lncRNA showed significant enrichment with a variety of complex traits in dairy cattle, suggesting the importance of rumen lncRNA for cattle performance in the adult stage. These relationships should be further investigated to better understand the specific roles lncRNAs are playing in rumen development and cow performance. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08758-4.
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18
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Boschiero C, Gao Y, Vi RB, Liu GE, Li C. PSVIII-B-5 Dynamic of Accessible Chromatin Regions in Cattle Rumen Epithelial Tissue During Weaning. J Anim Sci 2022. [DOI: 10.1093/jas/skac247.566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Weaning in ruminants is characterized by the transition from a milk-based diet to a solid diet which drives a critical gastrointestinal tract transformation. Identifying regulatory control of this transformation during weaning can help identify strategies to improve rumen health. This study aimed to identify regions of accessible chromatin in rumen epithelial tissue in pre- and post-weaning calves and investigate differentially accessible regions (DARs) to uncover regulatory elements in cattle rumen development using the ATAC-seq approach. A total of 126,071 peaks were identified, covering 1.15% of the cattle genome. From these accessible regions, 2,766 DARs were discovered. Gene ontology enrichment resulted in GO terms related to cell adhesion, anchoring junction, growth, cell migration, motility, and morphogenesis. In addition, putative regulatory canonical pathways were identified (TGFβ, Integrin-linked kinase, Integrin signaling, and regulation of the epithelial-mesenchymal transition). Canonical pathways integrated with co-expression results showed that TGFβ and ILK signaling pathways play essential roles in rumen development through the regulation of cellular adhesions. In this study, DARs during weaning have been identified, revealing enhancers, transcription factors, and candidate target genes that represent potential biomarkers for the bovine rumen development which will serve as a molecular tool for rumen development studies.
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Boschiero C, Gao Y, Baldwin RL, Ma L, Li CJ, Liu GE. Butyrate Induces Modifications of the CTCF-Binding Landscape in Cattle Cells. Biomolecules 2022; 12:biom12091177. [PMID: 36139015 PMCID: PMC9496099 DOI: 10.3390/biom12091177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 08/19/2022] [Accepted: 08/23/2022] [Indexed: 11/24/2022] Open
Abstract
Butyrate is produced in the rumen from microbial fermentation and is related to several functions, including cell differentiation and proliferation. Butyrate supplementation in calves can accelerate rumen development. DNA-protein interactions, such as the CCCTC-binding factor (CTCF), play essential roles in chromatin organization and gene expression regulation. Although CTCF-binding sites have been identified recently in cattle, a deeper characterization, including differentially CTCF-binding sites (DCBS), is vital for a better understanding of butyrate’s role in the chromatin landscape. This study aimed to identify CTCF-binding regions and DCBS under a butyrate-induced condition using ChIP-seq in bovine cells; 61,915 CTCF peaks were identified in the butyrate and 51,347 in the control. From these regions, 2265 DCBS were obtained for the butyrate vs. control comparison, comprising ~90% of induced sites. Most of the butyrate DCBS were in distal intergenic regions, showing a potential role as insulators. Gene ontology enrichment showed crucial terms for the induced DCBS, mainly related to cellular proliferation, cell adhesion, and growth regulation. Interestingly, the ECM-receptor interaction pathway was observed for the induced DCBS. Motif enrichment analysis further identified transcription factors, including CTCF, BORIS, TGIF2, and ZIC3. When DCBS was integrated with RNA-seq data, putative genes were identified for the repressed DCBS, including GATA4. Our study revealed promising candidate genes in bovine cells by a butyrate-induced condition that might be related to the regulation of rumen development, such as integrins, keratins, and collagens. These results provide a better understanding of the function of butyrate in cattle rumen development and chromatin landscape regulation.
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Affiliation(s)
- Clarissa Boschiero
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Ransom L. Baldwin
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Cong-jun Li
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
- Correspondence: (C.-j.L.); (G.E.L.); Tel.: +1-301-504-7216 (C.-j.L.); +1-301-504-9843 (G.E.L.); Fax: +1-301-504-8414 (C.-j.L. & G.E.L.)
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
- Correspondence: (C.-j.L.); (G.E.L.); Tel.: +1-301-504-7216 (C.-j.L.); +1-301-504-9843 (G.E.L.); Fax: +1-301-504-8414 (C.-j.L. & G.E.L.)
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20
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Yao Y, Liu S, Xia C, Gao Y, Pan Z, Canela-Xandri O, Khamseh A, Rawlik K, Wang S, Li B, Zhang Y, Pairo-Castineira E, D’Mellow K, Li X, Yan Z, Li CJ, Yu Y, Zhang S, Ma L, Cole JB, Ross PJ, Zhou H, Haley C, Liu GE, Fang L, Tenesa A. Comparative transcriptome in large-scale human and cattle populations. Genome Biol 2022; 23:176. [PMID: 35996157 PMCID: PMC9394047 DOI: 10.1186/s13059-022-02745-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 08/09/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Cross-species comparison of transcriptomes is important for elucidating evolutionary molecular mechanisms underpinning phenotypic variation between and within species, yet to date it has been essentially limited to model organisms with relatively small sample sizes. RESULTS Here, we systematically analyze and compare 10,830 and 4866 publicly available RNA-seq samples in humans and cattle, respectively, representing 20 common tissues. Focusing on 17,315 orthologous genes, we demonstrate that mean/median gene expression, inter-individual variation of expression, expression quantitative trait loci, and gene co-expression networks are generally conserved between humans and cattle. By examining large-scale genome-wide association studies for 46 human traits (average n = 327,973) and 45 cattle traits (average n = 24,635), we reveal that the heritability of complex traits in both species is significantly more enriched in transcriptionally conserved than diverged genes across tissues. CONCLUSIONS In summary, our study provides a comprehensive comparison of transcriptomes between humans and cattle, which might help decipher the genetic and evolutionary basis of complex traits in both species.
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Affiliation(s)
- Yuelin Yao
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, EH4 2XU Edinburgh, UK
- School of Informatics, The University of Edinburgh, Edinburgh, EH8 9AB UK
| | - Shuli Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705 USA
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Charley Xia
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG UK
- Department of Psychology, 7 George Square, The University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705 USA
- Department of Animal and Avian Sciences, University of Maryland, College Park, MA 20742 USA
| | - Zhangyuan Pan
- Department of Animal Science, University of California, Davis, CA 95616 USA
- Present address: Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Oriol Canela-Xandri
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, EH4 2XU Edinburgh, UK
| | - Ava Khamseh
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, EH4 2XU Edinburgh, UK
- School of Informatics, The University of Edinburgh, Edinburgh, EH8 9AB UK
| | - Konrad Rawlik
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG UK
| | - Sheng Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223 Yunnan China
| | - Bingjie Li
- Scotland’s Rural College (SRUC), Roslin Institute Building, Midlothian, EH25 9RG UK
| | - Yi Zhang
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Erola Pairo-Castineira
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, EH4 2XU Edinburgh, UK
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG UK
| | - Kenton D’Mellow
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, EH4 2XU Edinburgh, UK
| | - Xiujin Li
- Guangdong Provincial Key Laboratory of Waterfowl Healthy Breeding, College of Animal Science & Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, 510225 Guangdong China
| | - Ze Yan
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Cong-jun Li
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705 USA
| | - Ying Yu
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Shengli Zhang
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MA 20742 USA
| | - John B. Cole
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705 USA
| | - Pablo J. Ross
- Department of Animal Science, University of California, Davis, CA 95616 USA
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, CA 95616 USA
| | - Chris Haley
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, EH4 2XU Edinburgh, UK
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG UK
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705 USA
| | - Lingzhao Fang
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, EH4 2XU Edinburgh, UK
- Present address: Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Albert Tenesa
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, EH4 2XU Edinburgh, UK
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG UK
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21
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Zhou Y, Yang L, Han X, Han J, Hu Y, Li F, Xia H, Peng L, Boschiero C, Rosen BD, Bickhart DM, Zhang S, Guo A, Van Tassell CP, Smith TPL, Yang L, Liu GE. Assembly of a pangenome for global cattle reveals missing sequences and novel structural variations, providing new insights into their diversity and evolutionary history. Genome Res 2022; 32:gr.276550.122. [PMID: 35977842 PMCID: PMC9435747 DOI: 10.1101/gr.276550.122] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 07/21/2022] [Indexed: 02/03/2023]
Abstract
A cattle pangenome representation was created based on the genome sequences of 898 cattle representing 57 breeds. The pangenome identified 83 Mb of sequence not found in the cattle reference genome, representing 3.1% novel sequence compared with the 2.71-Gb reference. A catalog of structural variants developed from this cattle population identified 3.3 million deletions, 0.12 million inversions, and 0.18 million duplications. Estimates of breed ancestry and hybridization between cattle breeds using insertion/deletions as markers were similar to those produced by single nucleotide polymorphism-based analysis. Hundreds of deletions were observed to have stratification based on subspecies and breed. For example, an insertion of a Bov-tA1 repeat element was identified in the first intron of the APPL2 gene and correlated with cattle breed geographic distribution. This insertion falls within a segment overlapping predicted enhancer and promoter regions of the gene, and could affect important traits such as immune response, olfactory functions, cell proliferation, and glucose metabolism in muscle. The results indicate that pangenomes are a valuable resource for studying diversity and evolutionary history, and help to delineate how domestication, trait-based breeding, and adaptive introgression have shaped the cattle genome.
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Affiliation(s)
- Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Lv Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiaotao Han
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Jiazheng Han
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Yan Hu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Fan Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Han Xia
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Lingwei Peng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Clarissa Boschiero
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland 20705, USA
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland 20705, USA
| | - Derek M Bickhart
- Dairy Forage Research Center, ARS USDA, Madison, Wisconsin 53706, USA
| | - Shujun Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Aizhen Guo
- The State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, China
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland 20705, USA
| | - Timothy P L Smith
- U.S. Meat Animal Research Center, ARS USDA, Clay Center, Nebraska 68933, USA
| | - Liguo Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland 20705, USA
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22
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Boschiero C, Gao Y, Baldwin RL, Ma L, Li CJ, Liu GE. Differentially CTCF-Binding Sites in Cattle Rumen Tissue during Weaning. Int J Mol Sci 2022; 23:ijms23169070. [PMID: 36012336 PMCID: PMC9408924 DOI: 10.3390/ijms23169070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 08/09/2022] [Accepted: 08/11/2022] [Indexed: 11/17/2022] Open
Abstract
The weaning transition in calves is characterized by major structural changes such as an increase in the rumen capacity and surface area due to diet changes. Studies evaluating rumen development in calves are vital to identify genetic mechanisms affected by weaning. This study aimed to provide a genome-wide characterization of CTCF-binding sites and differentially CTCF-binding sites (DCBS) in rumen tissue during the weaning transition of four Holstein calves to uncover regulatory elements in rumen epithelial tissue using ChIP-seq. Our study generated 67,280 CTCF peaks for the before weaning (BW) and 39,891 for after weaning (AW). Then, 7401 DCBS were identified for the AW vs. BW comparison representing 0.15% of the cattle genome, comprising ~54% of induced DCBS and ~46% of repressed DCBS. Most of the induced and repressed DCBS were in distal intergenic regions, showing a potential role as insulators. Gene ontology enrichment revealed many shared GO terms for the induced and the repressed DCBS, mainly related to cellular migration, proliferation, growth, differentiation, cellular adhesion, digestive tract morphogenesis, and response to TGFβ. In addition, shared KEGG pathways were obtained for adherens junction and focal adhesion. Interestingly, other relevant KEGG pathways were observed for the induced DCBS like gastric acid secretion, salivary secretion, bacterial invasion of epithelial cells, apelin signaling, and mucin-type O-glycan biosynthesis. IPA analysis further revealed pathways with potential roles in rumen development during weaning, including TGFβ, Integrin-linked kinase, and Integrin signaling. When DCBS were further integrated with RNA-seq data, 36 putative target genes were identified for the repressed DCBS, including KRT84, COL9A2, MATN3, TSPAN1, and AJM1. This study successfully identified DCBS in cattle rumen tissue after weaning on a genome-wide scale and revealed several candidate target genes that may have a role in rumen development, such as TGFβ, integrins, keratins, and SMADs. The information generated in this preliminary study provides new insights into bovine genome regulation and chromatin landscape.
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Affiliation(s)
- Clarissa Boschiero
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Ransom L. Baldwin
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Cong-jun Li
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
- Correspondence: (C.-j.L.); (G.E.L.); Tel.: +1-301-504-7216 (C.-j.L.); +1-301-504-9843 (G.E.L.); Fax: +1-301-504-8414 (C.-j.L. & G.E.L.)
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
- Correspondence: (C.-j.L.); (G.E.L.); Tel.: +1-301-504-7216 (C.-j.L.); +1-301-504-9843 (G.E.L.); Fax: +1-301-504-8414 (C.-j.L. & G.E.L.)
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23
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Liu S, Gao Y, Canela-Xandri O, Wang S, Yu Y, Cai W, Li B, Xiang R, Chamberlain AJ, Pairo-Castineira E, D'Mellow K, Rawlik K, Xia C, Yao Y, Navarro P, Rocha D, Li X, Yan Z, Li C, Rosen BD, Van Tassell CP, Vanraden PM, Zhang S, Ma L, Cole JB, Liu GE, Tenesa A, Fang L. A multi-tissue atlas of regulatory variants in cattle. Nat Genet 2022; 54:1438-1447. [PMID: 35953587 PMCID: PMC7613894 DOI: 10.1038/s41588-022-01153-5] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 07/07/2022] [Indexed: 12/12/2022]
Abstract
Characterization of genetic regulatory variants acting on livestock gene expression is essential for interpreting the molecular mechanisms underlying traits of economic value and for increasing the rate of genetic gain through artificial selection. Here we build a Cattle Genotype-Tissue Expression atlas (CattleGTEx) as part of the pilot phase of the Farm animal GTEx (FarmGTEx) project for the research community based on 7,180 publicly available RNA-sequencing (RNA-seq) samples. We describe the transcriptomic landscape of more than 100 tissues/cell types and report hundreds of thousands of genetic associations with gene expression and alternative splicing for 23 distinct tissues. We evaluate the tissue-sharing patterns of these genetic regulatory effects, and functionally annotate them using multiomics data. Finally, we link gene expression in different tissues to 43 economically important traits using both transcriptome-wide association and colocalization analyses to decipher the molecular regulatory mechanisms underpinning such agronomic traits in cattle.
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Affiliation(s)
- Shuli Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, USA.,National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China.,School of Life Sciences, Westlake University, Hangzhou, China
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, USA.,Department of Animal and Avian Sciences, University of Maryland, College Park, MD, USA
| | - Oriol Canela-Xandri
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Sheng Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Ying Yu
- National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Wentao Cai
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, China
| | - Bingjie Li
- Scotland's Rural College (SRUC), Roslin Institute Building, Midlothian, UK
| | - Ruidong Xiang
- Faculty of Veterinary & Agricultural Science, The University of Melbourne, Parkville, Victoria, Australia.,Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, Victoria, Australia
| | - Amanda J Chamberlain
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, Victoria, Australia
| | - Erola Pairo-Castineira
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK.,The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, UK
| | - Kenton D'Mellow
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Konrad Rawlik
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, UK
| | - Charley Xia
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, UK
| | - Yuelin Yao
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Pau Navarro
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Dominique Rocha
- INRAE, AgroParisTech, GABI, Université Paris-Saclay, Jouy-en-Josas, France
| | - Xiujin Li
- Guangdong Provincial Key Laboratory of Waterfowl Healthy Breeding, College of Animal Science & Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, China
| | - Ze Yan
- National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Congjun Li
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, USA
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, USA
| | - Paul M Vanraden
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, USA
| | - Shengli Zhang
- National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, USA
| | - John B Cole
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, USA.
| | - Albert Tenesa
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK. .,The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, UK.
| | - Lingzhao Fang
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, USA. .,MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK. .,Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.
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24
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Ibeagha-Awemu EM, Kiefer H, McKay S, Liu GE. Editorial: Epigenetic Variation Influences on Livestock Production and Disease Traits. Front Genet 2022; 13:942747. [PMID: 35783264 PMCID: PMC9241065 DOI: 10.3389/fgene.2022.942747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 05/16/2022] [Indexed: 11/22/2022] Open
Affiliation(s)
- Eveline M. Ibeagha-Awemu
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC, Canada
- *Correspondence: Eveline M. Ibeagha-Awemu,
| | - Hélène Kiefer
- Université Paris-Saclay, UVSQ, INRAE, BREED, Jouy-en-Josas, France
- Ecole Nationale Vétérinaire d’Alfort, BREED, Maisons-Alfort, France
| | - Stephanie McKay
- Department of Animal and Veterinary Sciences, University of Vermont, Burlington, VT, United States
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, United States
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25
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Guo J, Sun X, Mao A, Liu H, Zhan S, Li L, Zhong T, Wang L, Cao J, Liu GE, Zhang H. A 13.42-kb tandem duplication at the ASIP locus is strongly associated with the depigmentation phenotype of non-classic Swiss markings in goats. BMC Genomics 2022; 23:437. [PMID: 35698044 PMCID: PMC9190080 DOI: 10.1186/s12864-022-08672-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 05/27/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The pigmentation phenotype diversity is rich in domestic goats, and identification of the genetic loci affecting coat color in goats has long been of interest. Via the detections of selection signatures, a duplication upstream ASIP was previously reported to be a variant affecting the Swiss markings depigmentation phenotype in goats. RESULTS We conducted a genome-wide association study using whole-genome sequencing (WGS) data to identify the genetic loci and causal variants affecting the pigmentation phenotype in 65 Jintang black (JT) goats (i.e., 48 solid black vs. 17 non-classic Swiss markings). Although a single association peak harboring the ASIP gene at 52,619,845-72,176,538 bp on chromosome 13 was obtained using a linear mixed model approach, all the SNPs and indels in this region were excluded as causal variants for the pigmentation phenotype. We then found that all 17 individuals with non-classic Swiss markings carried a 13,420-bp duplication (CHI13:63,129,198-63,142,617 bp) nearly 101 kb upstream of ASIP, and this variant was strongly associated (P = 1.48 × 10- 12) with the coat color in the 65 JT goats. The copy numbers obtained from the WGS data also showed that the duplication was present in all 53 goats from three European breeds with Swiss markings and absent in 45 of 51 non-Swiss markings goats from four other breeds and 21 Bezoars, which was further validated in 314 samples from seven populations based on PCR amplification. The copy numbers of the duplication vary in different goat breeds with Swiss markings, indicating a threshold effect instead of a dose-response effect at the molecular level. Furthermore, breakpoint flanking repeat analysis revealed that the duplication was likely to be a result of the Bov-B-mediated nonallelic homologous recombination. CONCLUSION We confirmed that a genomic region harboring the ASIP gene is a major locus affecting the coat color phenotype of Swiss markings in goats. Although the molecular genetic mechanisms remain unsolved, the 13,420-bp duplication upstream of ASIP is a necessary but not sufficient condition for this phenotype in goats. Moreover, the variations in the copy number of the duplication across different goat breeds do not lead to phenotypic heterogeneity.
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Affiliation(s)
- Jiazhong Guo
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Xueliang Sun
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Ayi Mao
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Haifeng Liu
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Siyuan Zhan
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Li Li
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Tao Zhong
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Linjie Wang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jiaxue Cao
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA.
| | - Hongping Zhang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China.
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26
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Zhang T, Wang T, Niu Q, Zheng X, Li H, Gao X, Chen Y, Gao H, Zhang L, Liu GE, Li J, Xu L. Comparative transcriptomic analysis reveals region-specific expression patterns in different beef cuts. BMC Genomics 2022; 23:387. [PMID: 35596128 PMCID: PMC9123670 DOI: 10.1186/s12864-022-08527-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Accepted: 03/30/2022] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Beef cuts in different regions of the carcass have different meat quality due to their distinct physiological function. The objective of this study was to characterize the region-specific expression differences using comparative transcriptomics analysis among five representative beef cuts (tenderloin, longissimus lumborum, rump, neck, chuck). RESULTS We obtained 15,701 expressed genes in 30 muscle samples across five regions from carcass meat. We identified a total of 80 region-specific genes (RSGs), ranging from three (identified in the rump cut) to thirty (identified in the longissimus lumborum cut), and detected 25 transcription factors (TFs) for RSGs. Using a co-expression network analysis, we detected seven region-specific modules, including three positively correlated modules and four negatively correlated modules. We finally obtained 91 candidate genes related to meat quality, and the functional enrichment analyses showed that these genes were mainly involved in muscle fiber structure (e.g., TNNI1, TNNT1), fatty acids (e.g., SCD, LPL), amino acids (ALDH2, IVD, ACADS), ion channel binding (PHPT1, SNTA1, SUMO1, CNBP), protein processing (e.g., CDC37, GAPDH, NRBP1), as well as energy production and conversion (e.g., ATP8, COX8B, NDUFB6). Moreover, four candidate genes (ALDH2, CANX, IVD, PHPT1) were validated using RT-qPCR analyses which further supported our RNA-seq results. CONCLUSIONS Our results provide valuable insights into understanding the transcriptome regulation of meat quality in different beef cuts, and these findings may further help to improve the selection for health-beneficial meat in beef cattle.
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Affiliation(s)
- Tianliu Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road 2#, Haidian District, Beijing, 100193, China
| | - Tianzhen Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road 2#, Haidian District, Beijing, 100193, China
| | - Qunhao Niu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road 2#, Haidian District, Beijing, 100193, China
| | - Xu Zheng
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road 2#, Haidian District, Beijing, 100193, China
| | - Haipeng Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road 2#, Haidian District, Beijing, 100193, China
| | - Xue Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road 2#, Haidian District, Beijing, 100193, China
| | - Yan Chen
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road 2#, Haidian District, Beijing, 100193, China
| | - Huijiang Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road 2#, Haidian District, Beijing, 100193, China
| | - Lupei Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road 2#, Haidian District, Beijing, 100193, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture-Agricultural Research Services, Beltsville, MD, 20705, USA
| | - Junya Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road 2#, Haidian District, Beijing, 100193, China.
| | - Lingyang Xu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road 2#, Haidian District, Beijing, 100193, China.
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27
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Gao Y, Ma L, Liu GE. Initial Analysis of Structural Variation Detections in Cattle Using Long-Read Sequencing Methods. Genes (Basel) 2022; 13:genes13050828. [PMID: 35627213 PMCID: PMC9142105 DOI: 10.3390/genes13050828] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 05/01/2022] [Accepted: 05/04/2022] [Indexed: 02/01/2023] Open
Abstract
Structural variations (SVs), as a great source of genetic variation, are widely distributed in the genome. SVs involve longer genomic sequences and potentially have stronger effects than SNPs, but they are not well captured by short-read sequencing owing to their size and relevance to repeats. Improved characterization of SVs can provide more advanced insight into complex traits. With the availability of long-read sequencing, it has become feasible to uncover the full range of SVs. Here, we sequenced one cattle individual using 10× Genomics (10 × G) linked read, Pacific Biosciences (PacBio) continuous long reads (CLR) and circular consensus sequencing (CCS), as well as Oxford Nanopore Technologies (ONT) PromethION. We evaluated the ability of various methods for SV detection. We identified 21,164 SVs, which amount to 186 Mb covering 7.07% of the whole genome. The number of SVs inferred from long-read-based inferences was greater than that from short reads. The PacBio CLR identified the most of large SVs and covered the most genomes. SVs called with PacBio CCS and ONT data showed high uniformity. The one with the most overlap with the results obtained by short-read data was PB CCS. Together, we found that long reads outperformed short reads in terms of SV detections.
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Affiliation(s)
- Yahui Gao
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA;
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA;
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA;
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA;
- Correspondence: ; Tel.: +1-301-504-9843
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28
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Gao Y, Li J, Cai G, Wang Y, Yang W, Li Y, Zhao X, Li R, Gao Y, Tuo W, Baldwin RL, Li CJ, Fang L, Liu GE. Single-cell transcriptomic and chromatin accessibility analyses of dairy cattle peripheral blood mononuclear cells and their responses to lipopolysaccharide. BMC Genomics 2022; 23:338. [PMID: 35501711 PMCID: PMC9063233 DOI: 10.1186/s12864-022-08562-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 04/13/2022] [Indexed: 11/24/2022] Open
Abstract
Background Gram-negative bacteria are important pathogens in cattle, causing severe infectious diseases, including mastitis. Lipopolysaccharides (LPS) are components of the outer membrane of Gram-negative bacteria and crucial mediators of chronic inflammation in cattle. LPS modulations of bovine immune responses have been studied before. However, the single-cell transcriptomic and chromatin accessibility analyses of bovine peripheral blood mononuclear cells (PBMCs) and their responses to LPS stimulation were never reported. Results We performed single-cell RNA sequencing (scRNA-seq) and single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) in bovine PBMCs before and after LPS treatment and demonstrated that seven major cell types, which included CD4 T cells, CD8 T cells, and B cells, monocytes, natural killer cells, innate lymphoid cells, and dendritic cells. Bioinformatic analyses indicated that LPS could increase PBMC cell cycle progression, cellular differentiation, and chromatin accessibility. Gene analyses further showed significant changes in differential expression, transcription factor binding site, gene ontology, and regulatory interactions during the PBMC responses to LPS. Consistent with the findings of previous studies, LPS induced activation of monocytes and dendritic cells, likely through their upregulated TLR4 receptor. NF-κB was observed to be activated by LPS and an increased transcription of an array of pro-inflammatory cytokines, in agreement that NF-κB is an LPS-responsive regulator of innate immune responses. In addition, by integrating LPS-induced differentially expressed genes (DEGs) with large-scale GWAS of 45 complex traits in Holstein, we detected trait-relevant cell types. We found that selected DEGs were significantly associated with immune-relevant health, milk production, and body conformation traits. Conclusion This study provided the first scRNAseq and scATAC-seq data for cattle PBMCs and their responses to the LPS stimulation to the best of our knowledge. These results should also serve as valuable resources for the future study of the bovine immune system and open the door for discoveries about immune cell roles in complex traits like mastitis at single-cell resolution. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08562-0.
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Affiliation(s)
- Yahui Gao
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, No.202, Gongyebei Road, Jinan, 250100, China.,Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, 20705, USA
| | - Jianbin Li
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, No.202, Gongyebei Road, Jinan, 250100, China.
| | - Gaozhan Cai
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, No.202, Gongyebei Road, Jinan, 250100, China.,Shandong Ox Livestock Breeding Co., Ltd, Jinan, 250100, China
| | - Yujiao Wang
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, No.202, Gongyebei Road, Jinan, 250100, China
| | - Wenjing Yang
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Yanqin Li
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, No.202, Gongyebei Road, Jinan, 250100, China
| | - Xiuxin Zhao
- Shandong Ox Livestock Breeding Co., Ltd, Jinan, 250100, China
| | - Rongling Li
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, No.202, Gongyebei Road, Jinan, 250100, China
| | - Yundong Gao
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, No.202, Gongyebei Road, Jinan, 250100, China
| | - Wenbin Tuo
- Animal Parasitic Diseases Laboratory, BARC, USDA-ARS, Beltsville, MD, 20705, USA
| | - Ransom L Baldwin
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, 20705, USA
| | - Cong-Jun Li
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, 20705, USA.
| | - Lingzhao Fang
- MRC Human Genetics Unit at the Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, 20705, USA.
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Zhang T, Wang T, Niu Q, Xu L, Chen Y, Gao X, Gao H, Zhang L, Liu GE, Li J, Xu L. Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle. BMC Biol 2022; 20:79. [PMID: 35351103 PMCID: PMC8966188 DOI: 10.1186/s12915-022-01269-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Accepted: 03/03/2022] [Indexed: 11/12/2022] Open
Abstract
Background A comprehensive analysis of gene expression profiling across tissues can provide necessary information for an in-depth understanding of their biological functions. We performed a large-scale gene expression analysis and generated a high-resolution atlas of the transcriptome in beef cattle. Results Our transcriptome atlas was generated from 135 bovine tissues in adult beef cattle, covering 51 tissue types of major organ systems (e.g., muscular system, digestive system, immune system, reproductive system). Approximately 94.76% of sequencing reads were successfully mapped to the reference genome assembly ARS-UCD1.2. We detected a total of 60,488 transcripts, and 32% of them were not reported before. We identified 2654 housekeeping genes (HKGs) and 477 tissue-specific genes (TSGs) across tissues. Using weighted gene co-expression network analysis, we obtained 24 modules with 237 hub genes (HUBGs). Functional enrichment analysis showed that HKGs mainly maintain the basic biological activities of cells, while TSGs were involved in tissue differentiation and specific physiological processes. HKGs in bovine tissues were more conserved in terms of expression pattern as compared to TSGs and HUBGs among multiple species. Finally, we obtained a subset of tissue-specific differentially expressed genes (DEGs) between beef and dairy cattle and several functional pathways, which may be involved in production and health traits. Conclusions We generated a large-scale gene expression atlas across the major tissues in beef cattle, providing valuable information for enhancing genome assembly and annotation. HKGs, TSGs, and HUBGs further contribute to better understanding the biology and evolution of multiple tissues in cattle. DEGs between beef and dairy cattle also fill in the knowledge gaps about differential transcriptome regulation of bovine tissues underlying economically important traits. Supplementary Information The online version contains supplementary material available at 10.1186/s12915-022-01269-4.
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Affiliation(s)
- Tianliu Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China
| | - Tianzhen Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China
| | - Qunhao Niu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China
| | - Lei Xu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China
| | - Yan Chen
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China
| | - Xue Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China
| | - Huijiang Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China
| | - Lupei Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, 20705, USA
| | - Junya Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China.
| | - Lingyang Xu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China.
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30
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Yang L, Gao Y, Oswalt A, Fang L, Boschiero C, Neupane M, Sattler CG, Li CJ, Seroussi E, Xu L, Yang L, Li L, Zhang H, Rosen BD, Van Tassell CP, Zhou Y, Ma L, Liu GE. Towards the detection of copy number variation from single sperm sequencing in cattle. BMC Genomics 2022; 23:215. [PMID: 35300589 PMCID: PMC8928590 DOI: 10.1186/s12864-022-08441-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 10/15/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Copy number variation (CNV) has been routinely studied using bulk-cell sequencing. However, CNV is not well studied on the single-cell level except for humans and a few model organisms. RESULTS We sequenced 143 single sperms of two Holstein bulls, from which we predicted CNV events using 14 single sperms with deep sequencing. We then compared the CNV results derived from single sperms with the bulk-cell sequencing of one bull's family trio of diploid genomes. As a known CNV hotspot, segmental duplications were also predicted using the bovine ARS-UCD1.2 genome. Although the trio CNVs validated only some single sperm CNVs, they still showed a distal chromosomal distribution pattern and significant associations with segmental duplications and satellite repeats. CONCLUSION Our preliminary results pointed out future research directions and highlighted the importance of uniform whole genome amplification, deep sequence coverage, and dedicated software pipelines for CNV detection using single cell sequencing data.
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Affiliation(s)
- Liu Yang
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA.,College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA.,Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Adam Oswalt
- Select Sires Inc, 11740 U.S. 42 North, Plain City, OH, 43064, USA
| | - Lingzhao Fang
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Clarissa Boschiero
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Mahesh Neupane
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | | | - Cong-Jun Li
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Eyal Seroussi
- Agricultural Research Organization (ARO), Institute of Animal Science, HaMaccabim Road, P.O.B 15159, 7528809, Volcani CenterRishon LeTsiyon, Israel
| | - Lingyang Xu
- Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Lv Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Li Li
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Hongping Zhang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA.
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31
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Yang L, Gao Y, Li M, Park KE, Liu S, Kang X, Liu M, Oswalt A, Fang L, Telugu BP, Sattler CG, Li CJ, Cole JB, Seroussi E, Xu L, Yang L, Zhou Y, Li L, Zhang H, Rosen BD, Van Tassell CP, Ma L, Liu GE. Genome-wide recombination map construction from single sperm sequencing in cattle. BMC Genomics 2022; 23:181. [PMID: 35247961 PMCID: PMC8898482 DOI: 10.1186/s12864-022-08415-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 02/24/2022] [Indexed: 11/30/2022] Open
Abstract
Background Meiotic recombination is one of the important phenomena contributing to gamete genome diversity. However, except for human and a few model organisms, it is not well studied in livestock, including cattle. Results To investigate their distributions in the cattle sperm genome, we sequenced 143 single sperms from two Holstein bulls. We mapped meiotic recombination events at high resolution based on phased heterozygous single nucleotide polymorphism (SNP). In the absence of evolutionary selection pressure in fertilization and survival, recombination events in sperm are enriched near distal chromosomal ends, revealing that such a pattern is intrinsic to the molecular mechanism of meiosis. Furthermore, we further validated these findings in single sperms with results derived from sequencing its family trio of diploid genomes and our previous studies of recombination in cattle. Conclusions To our knowledge, this is the first large-scale single sperm whole-genome sequencing effort in livestock, which provided useful information for future studies of recombination, genome instability, and male infertility. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08415-w.
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Guo J, Jiang R, Mao A, Liu GE, Zhan S, Li L, Zhong T, Wang L, Cao J, Chen Y, Zhang G, Zhang H. Correction to: Genome-wide association study reveals 14 new SNPs and confirms two structural variants highly associated with the horned/polled phenotype in goats. BMC Genomics 2022; 23:117. [PMID: 35144538 PMCID: PMC8832681 DOI: 10.1186/s12864-022-08361-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- Jiazhong Guo
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Rui Jiang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Ayi Mao
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Siyuan Zhan
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Li Li
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Tao Zhong
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Linjie Wang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jiaxue Cao
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yu Chen
- Nanjiang Yellow Goat Scientific Research Institute, Bazhong, 635600, China
| | - Guojun Zhang
- Nanjiang Yellow Goat Scientific Research Institute, Bazhong, 635600, China
| | - Hongping Zhang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China.
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Zhang T, Niu Q, Wang T, Zheng X, Li H, Gao X, Chen Y, Gao H, Zhang L, Liu GE, Li J, Xu L. Comparative Transcriptomic Analysis Reveals Diverse Expression Pattern Underlying Fatty Acid Composition among Different Beef Cuts. Foods 2022; 11:foods11010117. [PMID: 35010243 PMCID: PMC8750426 DOI: 10.3390/foods11010117] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 12/23/2021] [Accepted: 12/27/2021] [Indexed: 01/21/2023] Open
Abstract
Beef is an important dietary source of quality animal proteins and amino acids in human nutrition. The fatty acid composition is one of the indispensable indicators affecting nutritional value of beef. However, a comprehensive understanding of the expression changes underlying fatty acid composition in representative beef cuts is needed in cattle. This study aimed to characterize the dynamics of fatty acid composition using comparative transcriptomic analysis in five different type of beef cuts. We identified 7545 differentially expressed genes (DEGs) among 10 pair-wise comparisons. Co-expression gene network analysis identified two modules, which were significantly correlated with 2 and 20 fatty acid composition, respectively. We also identified 38 candidate genes, and functional enrichment showed that these genes were involved in fatty acid biosynthetic process and degradation, PPAR, and AMPK signaling pathway. Moreover, we observed a cluster of DEGs (e.g., SCD, LPL, FABP3, and PPARD) which were involved in the regulation of lipid metabolism and adipocyte differentiation. Our results provide some valuable insights into understanding the transcriptome regulation of candidate genes on fatty acid composition of beef cuts, and our findings may facilitate the designs of genetic selection program for beneficial fatty acid composition in beef cattle.
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Affiliation(s)
- Tianliu Zhang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (T.Z.); (Q.N.); (T.W.); (X.Z.); (H.L.); (X.G.); (Y.C.); (H.G.); (L.Z.); (J.L.)
| | - Qunhao Niu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (T.Z.); (Q.N.); (T.W.); (X.Z.); (H.L.); (X.G.); (Y.C.); (H.G.); (L.Z.); (J.L.)
| | - Tianzhen Wang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (T.Z.); (Q.N.); (T.W.); (X.Z.); (H.L.); (X.G.); (Y.C.); (H.G.); (L.Z.); (J.L.)
| | - Xu Zheng
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (T.Z.); (Q.N.); (T.W.); (X.Z.); (H.L.); (X.G.); (Y.C.); (H.G.); (L.Z.); (J.L.)
| | - Haipeng Li
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (T.Z.); (Q.N.); (T.W.); (X.Z.); (H.L.); (X.G.); (Y.C.); (H.G.); (L.Z.); (J.L.)
| | - Xue Gao
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (T.Z.); (Q.N.); (T.W.); (X.Z.); (H.L.); (X.G.); (Y.C.); (H.G.); (L.Z.); (J.L.)
| | - Yan Chen
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (T.Z.); (Q.N.); (T.W.); (X.Z.); (H.L.); (X.G.); (Y.C.); (H.G.); (L.Z.); (J.L.)
| | - Huijiang Gao
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (T.Z.); (Q.N.); (T.W.); (X.Z.); (H.L.); (X.G.); (Y.C.); (H.G.); (L.Z.); (J.L.)
| | - Lupei Zhang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (T.Z.); (Q.N.); (T.W.); (X.Z.); (H.L.); (X.G.); (Y.C.); (H.G.); (L.Z.); (J.L.)
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture-Agricultural Research Services, Beltsville, MD 20705, USA;
| | - Junya Li
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (T.Z.); (Q.N.); (T.W.); (X.Z.); (H.L.); (X.G.); (Y.C.); (H.G.); (L.Z.); (J.L.)
| | - Lingyang Xu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (T.Z.); (Q.N.); (T.W.); (X.Z.); (H.L.); (X.G.); (Y.C.); (H.G.); (L.Z.); (J.L.)
- Correspondence:
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Guo J, Jiang R, Mao A, Liu GE, Zhan S, Li L, Zhong T, Wang L, Cao J, Chen Y, Zhang G, Zhang H. Genome-wide association study reveals 14 new SNPs and confirms two structural variants highly associated with the horned/polled phenotype in goats. BMC Genomics 2021; 22:769. [PMID: 34706644 PMCID: PMC8555091 DOI: 10.1186/s12864-021-08089-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 10/14/2021] [Indexed: 12/01/2022] Open
Abstract
Background There is a long-term interest in investigating the genetic basis of the horned/polled phenotype in domestic goats. Here, we report a genome-wide association study (GWAS) to detect the genetic loci affecting the polled phenotype in goats. Results We obtained a total of 13,980,209 biallelic SNPs, using the genotyping-by-sequencing data from 45 Jintang Black (JT) goats, which included 32 female and nine male goats, and four individuals with the polled intersex syndrome (PIS). Using a mixed-model based GWAS, we identified two association signals, which were located at 150,334,857–150,817,260 bp (P = 5.15 × 10− 119) and 128,286,704–131,306,537 bp (P = 2.74 × 10− 15) on chromosome 1. The genotype distributions of the 14 most significantly associated SNPs were completely correlated with horn status in goats, based on the whole-genome sequencing (WGS) data from JT and two other Chinese horned breeds. However, variant annotation suggested that none of the detected SNPs within the associated regions were plausible causal mutations. Via additional read-depth analyses and visual inspections of WGS data, we found a 10.1-kb deletion (CHI1:g. 129424781_129434939del) and a 480-kb duplication (CHI1:150,334,286–150,818,098 bp) encompassing two genes KCNJ15 and ERG in the associated regions of polled and PIS-affected goats. Notably, the 10.1-kb deletion also served as the insertion site for the 480-kb duplication, as validated by PCR and Sanger sequencing. Our WGS genotyping showed that all horned goats were homozygous for the reference alleles without either the structural variants (SVs), whereas the PIS-affected goats were homozygous for both the SVs. We also demonstrated that horned, polled, and PIS-affected individuals among 333 goats from JT and three other Chinese horned breeds can be accurately classified via PCR amplification and agarose gel electrophoresis of two fragments in both SVs. Conclusion Our results revealed that two genomic regions on chromosome 1 are major loci affecting the polled phenotypes in goats. We provided a diagnostic PCR to accurately classify horned, polled, and PIS-affected goats, which will enable a reliable genetic test for the early-in-life prediction of horn status in goats. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-08089-w.
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Affiliation(s)
- Jiazhong Guo
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Rui Jiang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Ayi Mao
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Siyuan Zhan
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Li Li
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Tao Zhong
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Linjie Wang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jiaxue Cao
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yu Chen
- Nanjiang Yellow Goat Scientific Research Institute, Bazhong, 635600, China
| | - Guojun Zhang
- Nanjiang Yellow Goat Scientific Research Institute, Bazhong, 635600, China
| | - Hongping Zhang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China.
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Baldwin RL, Connor EE, Ramsay TG, Liu GE, Li CJ. PSVIII-25 Transcriptional reprogramming in rumen epithelium during the developmental transition of pre-ruminant to the ruminant in cattle. J Anim Sci 2021. [DOI: 10.1093/jas/skab235.652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
The rumen is a critical organ mediating nutrient uptake and use in cattle. Healthy rumen development is essential to ensure animal feed efficiency. In this work, we present an analysis of transcriptomic dynamics in rumen epithelium during the transition from pre-rumination to rumination in cattle-fed hay or concentrated diets at weaning (eighteen Holstein bull calves, 3 X 6 groups). These two distinct phases of rumen development and function in cattle are tightly regulated by a series of signaling events and clusters of effectors on key pathways. Our analysis identifies putative signaling events and effectors. Gene activity shifts indicated the transcriptomic reprogramming required to induce developmental changes in ruminal epithelium and functional transitions. A principal component analysis distinguished the temporal expression patterns that clustered separately between pre- and post-weaning groups. A GO-term enrichment analysis reflected functional (physical and metabolic) development of ruminal epithelium and revealed the greatest number of DEGs were enriched in biological processes related to energy metabolism. Canonical pathway and upstream regulator analyses revealed transcription reprogramming with clusters of critical pathways and upstream regulators controlling functional and developmental transitions with no significant differences between hay- and concentrate-fed groups at weaning. The most highly activated transcription factors expressed during the weaning transition were PPARGC1A, INSR, NFE2L2, MYC, MYCN, and PPARA. Overall, the dietary shift from liquid to solid feeds prompted transcriptional reprogramming in rumen epithelial tissue reflecting critical nutrient-gene interactions occurring during the developmental progression of ruminant digestion.
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Zhao P, Zheng X, Yu Y, Hou Z, Diao C, Wang H, Kang H, Ning C, Li J, Feng W, Wang W, Liu GE, Li B, Smith J, Chamba Y, Liu JF. Mining Unknown Porcine Protein Isoforms by Tissue-based Map of Proteome Enhances Pig Genome Annotation. Genomics Proteomics Bioinformatics 2021; 19:772-786. [PMID: 33631433 PMCID: PMC9170766 DOI: 10.1016/j.gpb.2021.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 09/05/2019] [Accepted: 11/29/2019] [Indexed: 11/29/2022]
Abstract
A lack of the complete pig proteome has left a gap in our knowledge of the pig genome and has restricted the feasibility of using pigs as a biomedical model. In this study, we developed a tissue-based proteome map using 34 major normal pig tissues. A total of 5841 unknown protein isoforms were identified and systematically characterized, including 2225 novel protein isoforms, 669 protein isoforms from 460 genes symbolized beginning with LOC, and 2947 protein isoforms without clear NCBI annotation in the current pig reference genome. These newly identified protein isoforms were functionally annotated through profiling the pig transcriptome with high-throughput RNA sequencing of the same pig tissues, further improving the genome annotation of the corresponding protein-coding genes. Combining the well-annotated genes that have parallel expression pattern and subcellular witness, we predicted the tissue-related subcellularlocations and potential functions for these unknown proteins. Finally, we mined 3081 orthologous genes for 52.7% of unknown protein isoforms across multiple species, referring to 68 KEGG pathways as well as 23 disease signaling pathways. These findings provide valuable insights and a rich resource for enhancing studies of pig genomics and biology, as well as biomedical model application to human medicine.
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Affiliation(s)
- Pengju Zhao
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xianrui Zheng
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Ying Yu
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Zhuocheng Hou
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Chenguang Diao
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Haifei Wang
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Huimin Kang
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Chao Ning
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Junhui Li
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Wen Feng
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Wen Wang
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an 710072, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, U.S. Department of Agriculture, Beltsville, MD 20705, USA
| | - Bugao Li
- Department of Animal Sciences and Veterinary Medicine, Shanxi Agricultural University, Taigu 030801, China
| | - Jacqueline Smith
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK
| | - Yangzom Chamba
- Tibet Agriculture and Animal Husbandry College, Linzhi 860000, China
| | - Jian-Feng Liu
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.
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Zhao B, Luo H, He J, Huang X, Chen S, Fu X, Zeng W, Tian Y, Liu S, Li CJ, Liu GE, Fang L, Zhang S, Tian K. Comprehensive transcriptome and methylome analysis delineates the biological basis of hair follicle development and wool-related traits in Merino sheep. BMC Biol 2021; 19:197. [PMID: 34503498 PMCID: PMC8427949 DOI: 10.1186/s12915-021-01127-9] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 08/18/2021] [Indexed: 12/13/2022] Open
Abstract
Background Characterization of the molecular mechanisms underlying hair follicle development is of paramount importance in the genetic improvement of wool-related traits in sheep and skin-related traits in humans. The Merino is the most important breed of fine-wooled sheep in the world. In this study, we systematically investigated the complexity of sheep hair follicle development by integrating transcriptome and methylome datasets from Merino sheep skin. Results We analysed 72 sequence datasets, including DNA methylome and the whole transcriptome of four gene types, i.e. protein-coding genes (PCGs), lncRNAs, circRNAs, and miRNAs, across four embryonic days (E65, E85, E105, and E135) and two postnatal days (P7 and P30) from the skin tissue of 18 Merino sheep. We revealed distinct expression profiles of these four gene types across six hair follicle developmental stages, and demonstrated their complex interactions with DNA methylation. PCGs with stage-specific expression or regulated by stage-specific lncRNAs, circRNAs, and miRNAs were significantly enriched in epithelial differentiation and hair follicle morphogenesis. Regulatory network and gene co-expression analyses identified key transcripts controlling hair follicle development. We further predicted transcriptional factors (e.g. KLF4, LEF1, HOXC13, RBPJ, VDR, RARA, and STAT3) with stage-specific involvement in hair follicle morphogenesis. Through integrating these stage-specific genomic features with results from genome-wide association studies (GWAS) of five wool-related traits in 7135 Merino sheep, we detected developmental stages and genes that were relevant with wool-related traits in sheep. For instance, genes that were specifically upregulated at E105 were significantly associated with most of wool-related traits. A phenome-wide association study (PheWAS) demonstrated that candidate genes of wool-related traits (e.g. SPHK1, GHR, PPP1R27, CSRP2, EEF1A2, and PTPN1) in sheep were also significantly associated with dermatological, metabolic, and immune traits in humans. Conclusions Our study provides novel insights into the molecular basis of hair follicle morphogenesis and will serve as a foundation to improve breeding for wool traits in sheep. It also indicates the importance of studying gene expression in the normal development of organs in understanding the genetic architecture of economically important traits in livestock. The datasets generated here are useful resources for functionally annotating the sheep genome, and for elucidating early skin development in mammals, including humans. Supplementary Information The online version contains supplementary material available at 10.1186/s12915-021-01127-9.
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Affiliation(s)
- Bingru Zhao
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding, and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Hanpeng Luo
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding, and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Junmin He
- Key Laboratory of Genetics Breeding and Reproduction of the Fine Wool Sheep & Cashmere Goat in Xinjiang, Institute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi, China
| | - Xixia Huang
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Siqian Chen
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding, and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Xuefeng Fu
- Key Laboratory of Genetics Breeding and Reproduction of the Fine Wool Sheep & Cashmere Goat in Xinjiang, Institute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi, China
| | - Weidan Zeng
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Yuezhen Tian
- Key Laboratory of Genetics Breeding and Reproduction of the Fine Wool Sheep & Cashmere Goat in Xinjiang, Institute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi, China
| | - Shuli Liu
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding, and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Cong-Jun Li
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, Agricultural Research Service, USDA, Beltsville, Maryland, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, Agricultural Research Service, USDA, Beltsville, Maryland, USA
| | - Lingzhao Fang
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
| | - Shengli Zhang
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding, and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China.
| | - Kechuan Tian
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, China.
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Zhao P, Du H, Jiang L, Zheng X, Feng W, Diao C, Zhou L, Liu GE, Zhang H, Chamba Y, Zhang Q, Li B, Liu JF. PRE-1 Revealed Previous Unknown Introgression Events in Eurasian Boars during the Middle Pleistocene. Genome Biol Evol 2021; 12:1751-1764. [PMID: 33151306 PMCID: PMC7643367 DOI: 10.1093/gbe/evaa142] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/03/2020] [Indexed: 12/22/2022] Open
Abstract
Introgression events and population admixture occurred among Sus species across the Eurasian mainland in the Middle Pleistocene, which reflects the local adaption of different populations and contributes to evolutionary novelty. Previous findings on these population introgressions were largely based on extensive genome-wide single-nucleotide polymorphism information, ignoring structural variants (SVs) as an important alternative resource of genetic variations. Here, we profiled the genome-wide SVs and explored the formation of pattern-related SVs, indicating that PRE1-SS is a recently active subfamily that was strongly associated with introgression events in multiple Asian and European pig populations. As reflected by the three different combination haplotypes from two specific patterns and known phylogenetic relationships in Eurasian boars, we identified the Asian Northern wild pigs as having experienced introgression from European wild boars around 0.5–0.2 Ma and having received latitude-related selection. During further exploration of the influence of pattern-related SVs on gene functions, we found substantial sequence changes in 199 intron regions of 54 genes and 3 exon regions of 3 genes (HDX, TRO, and SMIM1), implying that the pattern-related SVs were highly related to positive selection and adaption of pigs. Our findings revealed novel introgression events in Eurasian wild boars, providing a timeline of population admixture and divergence across the Eurasian mainland in the Middle Pleistocene.
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Affiliation(s)
- Pengju Zhao
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Heng Du
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Lin Jiang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Xianrui Zheng
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Wen Feng
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Chenguang Diao
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Lei Zhou
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Maryland
| | - Hao Zhang
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yangzom Chamba
- College of Animal Science and Technology, Tibet Agriculture and Animal Husbandry College, Linzhi, Tibet, China
| | - Qin Zhang
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, China.,College of Animal Science and Technology, Shandong Agricultural University, Taian, Shandong, PR China
| | - Bugao Li
- Department of Animal Sciences and Veterinary Medicine, Shanxi Agricultural University, Taigu, China
| | - Jian-Feng Liu
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, China
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Shen B, Freebern E, Jiang J, Maltecca C, Cole JB, Liu GE, Ma L. Effect of Temperature and Maternal Age on Recombination Rate in Cattle. Front Genet 2021; 12:682718. [PMID: 34354736 PMCID: PMC8329537 DOI: 10.3389/fgene.2021.682718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 06/28/2021] [Indexed: 11/16/2022] Open
Abstract
Meiotic recombination is a fundamental biological process that facilitates meiotic division and promotes genetic diversity. Recombination is phenotypically plastic and affected by both intrinsic and extrinsic factors. The effect of maternal age on recombination rates has been characterized in a wide range of species, but the effect’s direction remains inconclusive. Additionally, the characterization of temperature effects on recombination has been limited to model organisms. Here we seek to comprehensively determine the impact of genetic and environmental factors on recombination rate in dairy cattle. Using a large cattle pedigree, we identified maternal recombination events within 305,545 three-generation families. By comparing recombination rate between parents of different ages, we found a quadratic trend between maternal age and recombination rate in cattle. In contrast to either an increasing or decreasing trend in humans, cattle recombination rate decreased with maternal age until 65 months and then increased afterward. Combining recombination data with temperature information from public databases, we found a positive correlation between environmental temperature during fetal development of offspring and recombination rate in female parents. Finally, we fitted a full recombination rate model on all related factors, including genetics, maternal age, and environmental temperatures. Based on the final model, we confirmed the effect of maternal age and environmental temperature during fetal development of offspring on recombination rate with an estimated heritability of 10% (SE = 0.03) in cattle. Collectively, we characterized the maternal age and temperature effects on recombination rate and suggested the adaptation of meiotic recombination to environmental stimuli in cattle. Our results provided first-hand information regarding the plastic nature of meiotic recombination in a mammalian species.
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Affiliation(s)
- Botong Shen
- Department of Animal and Avian Sciences, University of Maryland, College Park, College Park, MD, United States
| | - Ellen Freebern
- Department of Animal and Avian Sciences, University of Maryland, College Park, College Park, MD, United States
| | - Jicai Jiang
- Department of Animal and Avian Sciences, University of Maryland, College Park, College Park, MD, United States.,Department of Animal Science, North Carolina State University, Raleigh, NC, United States
| | - Christian Maltecca
- Department of Animal Science, North Carolina State University, Raleigh, NC, United States
| | - John B Cole
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, United States
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, United States
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, College Park, MD, United States
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Zhao B, Luo H, Huang X, Wei C, Di J, Tian Y, Fu X, Li B, Liu GE, Fang L, Zhang S, Tian K. Integration of a single-step genome-wide association study with a multi-tissue transcriptome analysis provides novel insights into the genetic basis of wool and weight traits in sheep. Genet Sel Evol 2021; 53:56. [PMID: 34193030 PMCID: PMC8247193 DOI: 10.1186/s12711-021-00649-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 06/22/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Genetic improvement of wool and growth traits is a major goal in the sheep industry, but their underlying genetic architecture remains elusive. To improve our understanding of these mechanisms, we conducted a weighted single-step genome-wide association study (WssGWAS) and then integrated the results with large-scale transcriptome data for five wool traits and one growth trait in Merino sheep: mean fibre diameter (MFD), coefficient of variation of the fibre diameter (CVFD), crimp number (CN), mean staple length (MSL), greasy fleece weight (GFW), and live weight (LW). RESULTS Our dataset comprised 7135 individuals with phenotype data, among which 1217 had high-density (HD) genotype data (n = 372,534). The genotypes of 707 of these animals were imputed from the Illumina Ovine single nucleotide polymorphism (SNP) 54 BeadChip to the HD Array. The heritability of these traits ranged from 0.05 (CVFD) to 0.36 (MFD), and between-trait genetic correlations ranged from - 0.44 (CN vs. LW) to 0.77 (GFW vs. LW). By integrating the GWAS signals with RNA-seq data from 500 samples (representing 87 tissue types from 16 animals), we detected tissues that were relevant to each of the six traits, e.g. liver, muscle and the gastrointestinal (GI) tract were the most relevant tissues for LW, and leukocytes and macrophages were the most relevant cells for CN. For the six traits, 54 quantitative trait loci (QTL) were identified covering 81 candidate genes on 21 ovine autosomes. Multiple candidate genes showed strong tissue-specific expression, e.g. BNC1 (associated with MFD) and CHRNB1 (LW) were specifically expressed in skin and muscle, respectively. By conducting phenome-wide association studies (PheWAS) in humans, we found that orthologues of several of these candidate genes were significantly (FDR < 0.05) associated with similar traits in humans, e.g. BNC1 was significantly associated with MFD in sheep and with hair colour in humans, and CHRNB1 was significantly associated with LW in sheep and with body mass index in humans. CONCLUSIONS Our findings provide novel insights into the biological and genetic mechanisms underlying wool and growth traits, and thus will contribute to the genetic improvement and gene mapping of complex traits in sheep.
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Affiliation(s)
- Bingru Zhao
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding, and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Hanpeng Luo
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding, and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Xixia Huang
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Chen Wei
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Jiang Di
- Key Laboratory of Genetics Breeding and Reproduction of the Fine Wool Sheep & Cashmere Goat in Xinjiang, Institute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi, China
| | - Yuezhen Tian
- Key Laboratory of Genetics Breeding and Reproduction of the Fine Wool Sheep & Cashmere Goat in Xinjiang, Institute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi, China
| | - Xuefeng Fu
- Key Laboratory of Genetics Breeding and Reproduction of the Fine Wool Sheep & Cashmere Goat in Xinjiang, Institute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi, China
| | - Bingjie Li
- Scotland's Rural College (SRUC), Roslin Institute Building, Midlothian, EH25 9RG, UK
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, Agricultural Research Service, USDA, Beltsville, MD, USA
| | - Lingzhao Fang
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
| | - Shengli Zhang
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding, and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China.
| | - Kechuan Tian
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, China.
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Nandolo W, Mészáros G, Wurzinger M, Banda LJ, Gondwe TN, Mulindwa HA, Nakimbugwe HN, Clark EL, Woodward-Greene MJ, Liu M, Liu GE, Van Tassell CP, Rosen BD, Sölkner J. Detection of copy number variants in African goats using whole genome sequence data. BMC Genomics 2021; 22:398. [PMID: 34051743 PMCID: PMC8164248 DOI: 10.1186/s12864-021-07703-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 05/11/2021] [Indexed: 12/21/2022] Open
Abstract
Background Copy number variations (CNV) are a significant source of variation in the genome and are therefore essential to the understanding of genetic characterization. The aim of this study was to develop a fine-scaled copy number variation map for African goats. We used sequence data from multiple breeds and from multiple African countries. Results A total of 253,553 CNV (244,876 deletions and 8677 duplications) were identified, corresponding to an overall average of 1393 CNV per animal. The mean CNV length was 3.3 kb, with a median of 1.3 kb. There was substantial differentiation between the populations for some CNV, suggestive of the effect of population-specific selective pressures. A total of 6231 global CNV regions (CNVR) were found across all animals, representing 59.2 Mb (2.4%) of the goat genome. About 1.6% of the CNVR were present in all 34 breeds and 28.7% were present in all 5 geographical areas across Africa, where animals had been sampled. The CNVR had genes that were highly enriched in important biological functions, molecular functions, and cellular components including retrograde endocannabinoid signaling, glutamatergic synapse and circadian entrainment. Conclusions This study presents the first fine CNV map of African goat based on WGS data and adds to the growing body of knowledge on the genetic characterization of goats. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07703-1.
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Affiliation(s)
- Wilson Nandolo
- University of Natural Resources and Life Sciences, Vienna, Austria.,Lilongwe University of Agriculture and Natural Resources, Lilongwe, Malawi
| | - Gábor Mészáros
- University of Natural Resources and Life Sciences, Vienna, Austria
| | - Maria Wurzinger
- University of Natural Resources and Life Sciences, Vienna, Austria
| | - Liveness J Banda
- Lilongwe University of Agriculture and Natural Resources, Lilongwe, Malawi
| | - Timothy N Gondwe
- Lilongwe University of Agriculture and Natural Resources, Lilongwe, Malawi
| | | | | | - Emily L Clark
- The Roslin Institute, University of Edinburgh, Edinburgh, Scotland, UK
| | - M Jennifer Woodward-Greene
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, USA.,National Agricultural Library, USDA-ARS, Beltsville, MD, USA
| | - Mei Liu
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, USA
| | | | - George E Liu
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, USA
| | | | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, USA.
| | - Johann Sölkner
- University of Natural Resources and Life Sciences, Vienna, Austria
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Liu GE, Cai W, Liu H, Jiang HH, Yi Bi Y, Wang H. Malignancy is a risk factor for higher COVID-19 severity:A meta-analysis. Turk J Med Sci 2021. [PMID: 34022777 DOI: 10.3906/sag-2101-192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Accepted: 05/22/2021] [Indexed: 11/03/2022] Open
Abstract
BACKGROUND The outbreak of coronavirus disease 2019 (COVID-19) has been an almost global pandemic with significant public health impacts. The increasing prevalence of malignancy has become a leading cause of human mortality. However, conflicting findings have been published on the association between malignancy and COVID-19 severity. This study aims to assess the pooled proportion of malignancy amongst 2019-nCov patients and to investigate the association between malignancy and COVID-19 severity. METHODS Correlative studies were identi?ed by systematically searching electronic databases (PubMed, Web of Sciences and Embase) up to September 2, 2020. All data analyses were carried out using Stata 15.0. RESULTS Twenty-nine studies consisting of 9475 confirmed COVID-19 patients (median age 54.4 years [IQR 49-62], 54.0% men) were included. The overall proportion of malignancy was 2.5% (95% CI 1.6%-3.4%). The proportion of malignancy was higher in patients with severe/critical 2019-nCoV than those in non-severe/non-critical group (3.9% [95% CI 2.0-6.3] vs 1.4% [95% CI 0.8-2.2]). Furthermore, pre-existing malignancy was associated with more than twofold higher risk of severe/critical patients with COVID-19 (OR 2.25, 95% CI 1.65-3.06 I2 = 0.0%). CONCLUSION Malignancy was associated with up to 2.3-fold higher risk of severe/critical COVID-19 and may serve as a clinical predictor for adverse outcomes.
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43
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Gao Y, Fang L, Baldwin RL, Connor EE, Cole JB, Van Tassell CP, Ma L, Li CJ, Liu GE. Single-cell transcriptomic analyses of dairy cattle ruminal epithelial cells during weaning. Genomics 2021; 113:2045-2055. [PMID: 33933592 DOI: 10.1016/j.ygeno.2021.04.039] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 03/20/2021] [Accepted: 04/27/2021] [Indexed: 11/30/2022]
Abstract
Using the 10× Genomics Chromium Controller, we obtained scRNA-seq data of 5064 and 1372 individual cells from two Holstein calf ruminal epithelial tissues before and after weaning, respectively. We detected six distinct cell clusters, designated their cell types, and reported their marker genes. We then examined these clusters' underlining cell types and relationships by performing cell cycle, pseudotime trajectory, regulatory network, weighted gene co-expression network and gene ontology analyses. By integrating these cell marker genes with Holstein GWAS signals, we found they were enriched for animal production and body conformation traits. Finally, we confirmed their cell identities by comparing them with human and mouse stomach epithelial cells. This study presents an initial effort to implement single-cell transcriptomic analysis in cattle, and demonstrates ruminal tissue epithelial cell types and their developments during weaning, opening the door for new discoveries about tissue/cell type roles in complex traits at single-cell resolution.
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Affiliation(s)
- Yahui Gao
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD 20705, USA; Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA.
| | - Lingzhao Fang
- MRC Human Genetics Unit at the Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom.
| | - Ransom L Baldwin
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD 20705, USA.
| | - Erin E Connor
- Department of Animal and Food Sciences, University of Delaware, Newark, DE 19716, USA.
| | - John B Cole
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD 20705, USA.
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD 20705, USA.
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA.
| | - Cong-Jun Li
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD 20705, USA.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD 20705, USA.
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Liang D, Zhao P, Si J, Fang L, Pairo-Castineira E, Hu X, Xu Q, Hou Y, Gong Y, Liang Z, Tian B, Mao H, Yindee M, Faruque MO, Kongvongxay S, Khamphoumee S, Liu GE, Wu DD, Barker JSF, Han J, Zhang Y. Genomic Analysis Revealed a Convergent Evolution of LINE-1 in Coat Color: A Case Study in Water Buffaloes (Bubalus bubalis). Mol Biol Evol 2021; 38:1122-1136. [PMID: 33212507 PMCID: PMC7947781 DOI: 10.1093/molbev/msaa279] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Visible pigmentation phenotypes can be used to explore the regulation of gene expression and the evolution of coat color patterns in animals. Here, we performed whole-genome and RNA sequencing and applied genome-wide association study, comparative population genomics and biological experiments to show that the 2,809-bp-long LINE-1 insertion in the ASIP (agouti signaling protein) gene is the causative mutation for the white coat phenotype in swamp buffalo (Bubalus bubalis). This LINE-1 insertion (3' truncated and containing only 5' UTR) functions as a strong proximal promoter that leads to a 10-fold increase in the transcription of ASIP in white buffalo skin. The 165 bp of 5' UTR transcribed from the LINE-1 is spliced into the first coding exon of ASIP, resulting in a chimeric transcript. The increased expression of ASIP prevents melanocyte maturation, leading to the absence of pigment in white buffalo skin and hairs. Phylogenetic analyses indicate that the white buffalo-specific ASIP allele originated from a recent genetic transposition event in swamp buffalo. Interestingly, as a similar LINE-1 insertion has been identified in the cattle ASIP gene, we discuss the convergent mechanism of coat color evolution in the Bovini tribe.
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Affiliation(s)
- Dong Liang
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics and Breeding and Reproduction of MOAR, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Pengju Zhao
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics and Breeding and Reproduction of MOAR, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jingfang Si
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics and Breeding and Reproduction of MOAR, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Lingzhao Fang
- Medical Research Council Human Genetics Unit at the Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Erola Pairo-Castineira
- Medical Research Council Human Genetics Unit at the Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Xiaoxiang Hu
- State Key Laboratory of AgroBiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Qing Xu
- College of Life Sciences and Bioengineering, Beijing Jiaotong University, Beijing, China
| | - Yali Hou
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Yu Gong
- Guizhou Domestic Animal Genetic Resources Management Station, Guiyang, China
| | - Zhengwen Liang
- Agriculture and Rural Affairs Bureau of Fenggang County, Zunyi, China
| | - Bing Tian
- Animal Disease Prevention and Control Station of Zunyi City, Zunyi, China
| | - Huaming Mao
- College of Animal Science and Technology, Yunnan Agricultural University, Kunming, China
| | - Marnoch Yindee
- Akkhararatchakumari Veterinary College (AVC), Walailak University, Nakorn Si Thammarat, Thailand
| | - Md Omar Faruque
- Department of Animal Breeding and Genetics, Bangladesh Agricultural University, Mymensingh, Bangladesh
| | - Siton Kongvongxay
- Livestock Research Center, National Agriculture and Forestry Research Institute, Ministry of Agriculture and Forestry, Vientiane, Lao PDR
| | - Souksamlane Khamphoumee
- Livestock Research Center, National Agriculture and Forestry Research Institute, Ministry of Agriculture and Forestry, Vientiane, Lao PDR
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD
| | - Dong-Dong Wu
- Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - James Stuart F Barker
- School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia
| | - Jianlin Han
- International Livestock Research Institute (ILRI), Nairobi, Kenya
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Yi Zhang
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics and Breeding and Reproduction of MOAR, College of Animal Science and Technology, China Agricultural University, Beijing, China
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Yang L, Niu Q, Zhang T, Zhao G, Zhu B, Chen Y, Zhang L, Gao X, Gao H, Liu GE, Li J, Xu L. Genomic sequencing analysis reveals copy number variations and their associations with economically important traits in beef cattle. Genomics 2020; 113:812-820. [PMID: 33080318 DOI: 10.1016/j.ygeno.2020.10.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 09/21/2020] [Accepted: 10/05/2020] [Indexed: 11/25/2022]
Abstract
Copy number variation (CNV) represents a major source of genetic variation, which may have potentially large effects, including alternating gene regulation and dosage, as well as contributing to gene expression and risk for normal phenotypic variability. We carried out a comprehensive analysis of CNV based on whole genome sequencing in Chinese Simmental beef cattle. Totally, we found 9313 deletion and 234 duplication events, covering 147.5 Mb autosomal regions. Within them, 257 deletion events of high frequency overlapped with 193 known RefGenes. Among these genes, we observed several genes were related to economically important traits, like residual feed intake, immune responding, pregnancy rate and muscle differentiation. Using a locus-based analysis, we identified 11 deletions and 1 duplication, which were significantly associated with three traits including carcass weight, tenderloin and longissimus muscle area. Our sequencing-based study provided important insights into investigating the association of CNVs with important traits in beef cattle.
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Affiliation(s)
- Liu Yang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
| | - Qunhao Niu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Tianliu Zhang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Guoyao Zhao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Bo Zhu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Yan Chen
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Lupei Zhang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Xue Gao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Huijiang Gao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture-Agricultural Research Service, Beltsville, MD 20705, USA.
| | - Junya Li
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Lingyang Xu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
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Hu Y, Xia H, Li M, Xu C, Ye X, Su R, Zhang M, Nash O, Sonstegard TS, Yang L, Liu GE, Zhou Y. Comparative analyses of copy number variations between Bos taurus and Bos indicus. BMC Genomics 2020; 21:682. [PMID: 33004001 PMCID: PMC7528262 DOI: 10.1186/s12864-020-07097-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 09/23/2020] [Indexed: 12/15/2022] Open
Abstract
Background Bos taurus and Bos indicus are two main sub-species of cattle. However, the differential copy number variations (CNVs) between them are not yet well studied. Results Based on the new high-quality cattle reference genome ARS-UCD1.2, we identified 13,234 non-redundant CNV regions (CNVRs) from 73 animals of 10 cattle breeds (4 Bos taurus and 6 Bos indicus), by integrating three detection strategies. While 6990 CNVRs (52.82%) were shared by Bos taurus and Bos indicus, large CNV differences were discovered between them and these differences could be used to successfully separate animals into two subspecies. We found that 2212 and 538 genes uniquely overlapped with either indicine-specific CNVRs and or taurine-specific CNVRs, respectively. Based on FST, we detected 16 candidate lineage-differential CNV segments (top 0.1%) under selection, which overlapped with eight genes (CTNNA1, ENSBTAG00000004415, PKN2, BMPER, PDE1C, DNAJC18, MUSK, and PLCXD3). Moreover, we obtained 1.74 Mbp indicine-specific sequences, which could only be mapped on the Bos indicus reference genome UOA_Brahman_1. We found these sequences and their associated genes were related to heat resistance, lipid and ATP metabolic process, and muscle development under selection. We further analyzed and validated the top significant lineage-differential CNV. This CNV overlapped genes related to muscle cell differentiation, which might be generated from a retropseudogene of CTH but was deleted along Bos indicus lineage. Conclusions This study presents a genome wide CNV comparison between Bos taurus and Bos indicus. It supplied essential genome diversity information for understanding of adaptation and phenotype differences between the Bos taurus and Bos indicus populations.
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Affiliation(s)
- Yan Hu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Han Xia
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Mingxun Li
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA.,College of Animal Science and Technology, Yangzhou University, Yangzhou, 225009, China
| | - Chang Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Xiaowei Ye
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Ruixue Su
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Mai Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Oyekanmi Nash
- Centre for Genomics Research and Innovation, National Biotechnology Development Agency, Abuja, Nigeria
| | | | - Liguo Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA.
| | - Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.
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47
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Kang X, Li M, Liu M, Liu S, Pan MG, Wiggans GR, Rosen BD, Liu GE. Copy number variation analysis reveals variants associated with milk production traits in dairy goats. Genomics 2020; 112:4934-4937. [PMID: 32898641 DOI: 10.1016/j.ygeno.2020.09.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2019] [Revised: 07/29/2020] [Accepted: 09/03/2020] [Indexed: 11/29/2022]
Abstract
Copy number variation (CNV) is a major type of genomic structural variation. We investigated their impacts on goat dairy traits using the CaprineSNP50 array. From 120 samples of five dairy goat breeds, we totally identified 42 CNVs ranging from 56,044 bp to 4,337,625 bp. We found significant associations between two CNVs (CNV5 and CNV25) and two milk production traits (mean of milk fat yield and mean of milk protein yield) after false discovery rate (FDR) correction (P < 0.05). CNV5 overlaps the ADAMTS20 gene, which is involved in the differentiation of mammary cell and plays a crucial role in lactogenic activity of bovine mammary epithelial cells. CNV25 overlaps with PAPPA2, which has been found to be associated with bovine reproduction and milk production traits. Our results revealed that CNVs overlapped with ADAMTS20 and PAPPA2 could be involved in goat dairy traits and function as candidate markers for further genetic selection.
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Affiliation(s)
- Xiaolong Kang
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, USA; College of Agriculture, Ningxia University, Yinchuan, China
| | - Mingxun Li
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, USA; College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Mei Liu
- Animal Nutritional Genome and Germplasm Innovation Research Center, College of Animal Science and Technology, Hunan Agricultural University, Changsha, China
| | - Shuli Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, USA; College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Michael G Pan
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, USA
| | | | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, USA.
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48
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Yan Z, Huang H, Freebern E, Santos DJA, Dai D, Si J, Ma C, Cao J, Guo G, Liu GE, Ma L, Fang L, Zhang Y. Integrating RNA-Seq with GWAS reveals novel insights into the molecular mechanism underpinning ketosis in cattle. BMC Genomics 2020; 21:489. [PMID: 32680461 PMCID: PMC7367229 DOI: 10.1186/s12864-020-06909-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Accepted: 07/13/2020] [Indexed: 01/12/2023] Open
Abstract
Background Ketosis is a common metabolic disease during the transition period in dairy cattle, resulting in long-term economic loss to the dairy industry worldwide. While genetic selection of resistance to ketosis has been adopted by many countries, the genetic and biological basis underlying ketosis is poorly understood. Results We collected a total of 24 blood samples from 12 Holstein cows, including 4 healthy and 8 ketosis-diagnosed ones, before (2 weeks) and after (5 days) calving, respectively. We then generated RNA-Sequencing (RNA-Seq) data and seven blood biochemical indicators (bio-indicators) from leukocytes and plasma in each of these samples, respectively. By employing a weighted gene co-expression network analysis (WGCNA), we detected that 4 out of 16 gene-modules, which were significantly engaged in lipid metabolism and immune responses, were transcriptionally (FDR < 0.05) correlated with postpartum ketosis and several bio-indicators (e.g., high-density lipoprotein and low-density lipoprotein). By conducting genome-wide association signal (GWAS) enrichment analysis among six common health traits (ketosis, mastitis, displaced abomasum, metritis, hypocalcemia and livability), we found that 4 out of 16 modules were genetically (FDR < 0.05) associated with ketosis, among which three were correlated with postpartum ketosis based on WGCNA. We further identified five candidate genes for ketosis, including GRINA, MAF1, MAFA, C14H8orf82 and RECQL4. Our phenome-wide association analysis (Phe-WAS) demonstrated that human orthologues of these candidate genes were also significantly associated with many metabolic, endocrine, and immune traits in humans. For instance, MAFA, which is involved in insulin secretion, glucose response, and transcriptional regulation, showed a significantly higher association with metabolic and endocrine traits compared to other types of traits in humans. Conclusions In summary, our study provides novel insights into the molecular mechanism underlying ketosis in cattle, and highlights that an integrative analysis of omics data and cross-species mapping are promising for illustrating the genetic architecture underpinning complex traits.
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Affiliation(s)
- Ze Yan
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Hetian Huang
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.,College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450002, China
| | - Ellen Freebern
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Daniel J A Santos
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Dongmei Dai
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Jingfang Si
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Chong Ma
- Department of Clinical Veterinary Medicine, College of Veterinary Medicine, China Agricultural University, Beijing, 100193, China
| | - Jie Cao
- Department of Clinical Veterinary Medicine, College of Veterinary Medicine, China Agricultural University, Beijing, 100193, China
| | - Gang Guo
- Beijing Sunlon Livestock Development Co Ltd., Beijing, 100076, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
| | - Lingzhao Fang
- MRC Human Genetics Unit at the Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
| | - Yi Zhang
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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49
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Zhou Y, Liu S, Hu Y, Fang L, Gao Y, Xia H, Schroeder SG, Rosen BD, Connor EE, Li CJ, Baldwin RL, Cole JB, Van Tassell CP, Yang L, Ma L, Liu GE. Comparative whole genome DNA methylation profiling across cattle tissues reveals global and tissue-specific methylation patterns. BMC Biol 2020; 18:85. [PMID: 32631327 PMCID: PMC7339546 DOI: 10.1186/s12915-020-00793-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 05/12/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Efforts to improve animal health, and understand genetic bases for production, may benefit from a comprehensive analysis of animal genomes and epigenomes. Although DNA methylation has been well studied in humans and other model species, its distribution patterns and regulatory impacts in cattle are still largely unknown. Here, we present the largest collection of cattle DNA methylation epigenomic data to date. RESULTS Using Holstein cattle, we generated 29 whole genome bisulfite sequencing (WGBS) datasets for 16 tissues, 47 corresponding RNA-seq datasets, and 2 whole genome sequencing datasets. We did read mapping and DNA methylation calling based on two different cattle assemblies, demonstrating the high quality of the long-read-based assembly markedly improved DNA methylation results. We observed large differences across cattle tissues in the methylation patterns of global CpG sites, partially methylated domains (PMDs), hypomethylated regions (HMRs), CG islands (CGIs), and common repeats. We detected that each tissue had a distinct set of PMDs, which showed tissue-specific patterns. Similar to human PMD, cattle PMDs were often linked to a general decrease of gene expression and a decrease in active histone marks and related to long-range chromatin organizations, like topologically associated domains (TADs). We tested a classification of the HMRs based on their distributions relative to transcription start sites (TSSs) and detected tissue-specific TSS-HMRs and genes that showed strong tissue effects. When performing cross-species comparisons of paired genes (two opposite strand genes with their TSS located in the same HMR), we found out they were more consistently co-expressed among human, mouse, sheep, goat, yak, pig, and chicken, but showed lower consistent ratios in more divergent species. We further used these WGBS data to detect 50,023 experimentally supported CGIs across bovine tissues and found that they might function as a guard against C-to-T mutations for TSS-HMRs. Although common repeats were often heavily methylated, some young Bov-A2 repeats were hypomethylated in sperm and could affect the promoter structures by exposing potential transcription factor binding sites. CONCLUSIONS This study provides a comprehensive resource for bovine epigenomic research and enables new discoveries about DNA methylation and its role in complex traits.
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Affiliation(s)
- Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
| | - Shuli Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Yan Hu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
| | - Lingzhao Fang
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Han Xia
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
| | - Steven G. Schroeder
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Benjamin D. Rosen
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Erin E. Connor
- Department of Animal and Food Sciences, University of Delaware, Newark, DE 19716 USA
| | - Cong-jun Li
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Ransom L. Baldwin
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - John B. Cole
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Curtis P. Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Liguo Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742 USA
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
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50
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Liu S, Yu Y, Zhang S, Cole JB, Tenesa A, Wang T, McDaneld TG, Ma L, Liu GE, Fang L. Epigenomics and genotype-phenotype association analyses reveal conserved genetic architecture of complex traits in cattle and human. BMC Biol 2020; 18:80. [PMID: 32620158 PMCID: PMC7334855 DOI: 10.1186/s12915-020-00792-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 05/12/2020] [Indexed: 02/01/2023] Open
Abstract
Background Lack of comprehensive functional annotations across a wide range of tissues and cell types severely hinders the biological interpretations of phenotypic variation, adaptive evolution, and domestication in livestock. Here we used a combination of comparative epigenomics, genome-wide association study (GWAS), and selection signature analysis, to shed light on potential adaptive evolution in cattle. Results We cross-mapped 8 histone marks of 1300 samples from human to cattle, covering 178 unique tissues/cell types. By uniformly analyzing 723 RNA-seq and 40 whole genome bisulfite sequencing (WGBS) datasets in cattle, we validated that cross-mapped histone marks captured tissue-specific expression and methylation, reflecting tissue-relevant biology. Through integrating cross-mapped tissue-specific histone marks with large-scale GWAS and selection signature results, we for the first time detected relevant tissues and cell types for 45 economically important traits and artificial selection in cattle. For instance, immune tissues are significantly associated with health and reproduction traits, multiple tissues for milk production and body conformation traits (reflecting their highly polygenic architecture), and thyroid for the different selection between beef and dairy cattle. Similarly, we detected relevant tissues for 58 complex traits and diseases in humans and observed that immune and fertility traits in humans significantly correlated with those in cattle in terms of relevant tissues, which facilitated the identification of causal genes for such traits. For instance, PIK3CG, a gene highly specifically expressed in mononuclear cells, was significantly associated with both age-at-menopause in human and daughter-still-birth in cattle. ICAM, a T cell-specific gene, was significantly associated with both allergic diseases in human and metritis in cattle. Conclusion Collectively, our results highlighted that comparative epigenomics in conjunction with GWAS and selection signature analyses could provide biological insights into the phenotypic variation and adaptive evolution. Cattle may serve as a model for human complex traits, by providing additional information beyond laboratory model organisms, particularly when more novel phenotypes become available in the near future.
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Affiliation(s)
- Shuli Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, BARC-East, Beltsville, MD, 20705, USA.,College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Ying Yu
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Shengli Zhang
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - John B Cole
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, BARC-East, Beltsville, MD, 20705, USA
| | - Albert Tenesa
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,The Roslin Institute, University of Edinburgh, Edinburgh, EH25 9RG, UK
| | - Ting Wang
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Tara G McDaneld
- US Meat Animal Research Center, Agricultural Research Service, USDA, Clay Center, NE, 68933, USA
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, BARC-East, Beltsville, MD, 20705, USA.
| | - Lingzhao Fang
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, BARC-East, Beltsville, MD, 20705, USA. .,MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK. .,Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
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