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Wu S, Dou T, Wang K, Yuan S, Yan S, Xu Z, Liu Y, Jian Z, Zhao J, Zhao R, Wu H, Gu D, Liu L, Li Q, Wu DD, Ge C, Su Z, Jia J. Artificial selection footprints in indigenous and commercial chicken genomes. BMC Genomics 2024; 25:428. [PMID: 38689225 PMCID: PMC11061962 DOI: 10.1186/s12864-024-10291-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 04/08/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND Although many studies have been done to reveal artificial selection signatures in commercial and indigenous chickens, a limited number of genes have been linked to specific traits. To identify more trait-related artificial selection signatures and genes, we re-sequenced a total of 85 individuals of five indigenous chicken breeds with distinct traits from Yunnan Province, China. RESULTS We found 30 million non-redundant single nucleotide variants and small indels (< 50 bp) in the indigenous chickens, of which 10 million were not seen in 60 broilers, 56 layers and 35 red jungle fowls (RJFs) that we compared with. The variants in each breed are enriched in non-coding regions, while those in coding regions are largely tolerant, suggesting that most variants might affect cis-regulatory sequences. Based on 27 million bi-allelic single nucleotide polymorphisms identified in the chickens, we found numerous selective sweeps and affected genes in each indigenous chicken breed and substantially larger numbers of selective sweeps and affected genes in the broilers and layers than previously reported using a rigorous statistical model. Consistent with the locations of the variants, the vast majority (~ 98.3%) of the identified selective sweeps overlap known quantitative trait loci (QTLs). Meanwhile, 74.2% known QTLs overlap our identified selective sweeps. We confirmed most of previously identified trait-related genes and identified many novel ones, some of which might be related to body size and high egg production traits. Using RT-qPCR, we validated differential expression of eight genes (GHR, GHRHR, IGF2BP1, OVALX, ELF2, MGARP, NOCT, SLC25A15) that might be related to body size and high egg production traits in relevant tissues of relevant breeds. CONCLUSION We identify 30 million single nucleotide variants and small indels in the five indigenous chicken breeds, 10 million of which are novel. We predict substantially more selective sweeps and affected genes than previously reported in both indigenous and commercial breeds. These variants and affected genes are good candidates for further experimental investigations of genotype-phenotype relationships and practical applications in chicken breeding programs.
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Affiliation(s)
- Siwen Wu
- Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - Tengfei Dou
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Kun Wang
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Sisi Yuan
- Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - Shixiong Yan
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Zhiqiang Xu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Yong Liu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Zonghui Jian
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Jingying Zhao
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Rouhan Zhao
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Hao Wu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Dahai Gu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Lixian Liu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Qihua Li
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Changrong Ge
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China.
| | - Zhengchang Su
- Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC, 28223, USA.
| | - Junjing Jia
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China.
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Xiong X, Liu J, Rao Y. Whole Genome Resequencing Helps Study Important Traits in Chickens. Genes (Basel) 2023; 14:1198. [PMID: 37372379 DOI: 10.3390/genes14061198] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 05/23/2023] [Accepted: 05/25/2023] [Indexed: 06/29/2023] Open
Abstract
The emergence of high-throughput sequencing technology promotes life science development, provides technical support to analyze many life mechanisms, and presents new solutions to previously unsolved problems in genomic research. Resequencing technology has been widely used for genome selection and research on chicken population structure, genetic diversity, evolutionary mechanisms, and important economic traits caused by genome sequence differences since the release of chicken genome sequence information. This article elaborates on the factors influencing whole genome resequencing and the differences between these factors and whole genome sequencing. It reviews the important research progress in chicken qualitative traits (e.g., frizzle feather and comb), quantitative traits (e.g., meat quality and growth traits), adaptability, and disease resistance, and provides a theoretical basis to study whole genome resequencing in chickens.
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Affiliation(s)
- Xinwei Xiong
- Key Laboratory for Genetic Improvement of Indigenous Chicken Breeds of Jiangxi Province, Nanchang Normal University, Nanchang 330032, China
| | - Jianxiang Liu
- Key Laboratory for Genetic Improvement of Indigenous Chicken Breeds of Jiangxi Province, Nanchang Normal University, Nanchang 330032, China
| | - Yousheng Rao
- Key Laboratory for Genetic Improvement of Indigenous Chicken Breeds of Jiangxi Province, Nanchang Normal University, Nanchang 330032, China
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Chen B, Xi S, El-Senousey HAK, Zhou M, Cheng D, Chen K, Wan L, Xiong T, Liao M, Liu S, Mao H. Deletion in KRT75L4 linked to frizzle feather in Xiushui Yellow Chickens. Anim Genet 2021; 53:101-107. [PMID: 34904261 DOI: 10.1111/age.13158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/17/2021] [Indexed: 11/30/2022]
Abstract
Bird feathers are the product of interactions between natural and artificial selection. Feather-related traits are important for chicken selection and breeding. Frizzle feather is characterized by the abnormally development of feathers in chickens. In the current study, frizzle feather characteristics were observed in a local breed called Xiushui Yellow Chicken in Jiangxi, China. To determine the molecular mechanisms that underlie frizzle feather in Xiushui Yellow Chicken, four populations of three breeds (Xiushui Yellow Chicken with frizzle feathers, Xiushui Yellow Chicken with normal feathers, Guangfeng White-Ear Yellow Chicken, and Ningdu Yellow Chicken) were selected for whole-genome resequencing. Using a comparative genome strategy and genome-wide association study, a missense mutation (g.5281494A>G) and a 15-bp deletion (g.5285437-5285451delGATGCCGGCAGGACG) in KRT75L4 were identified as candidate mutations associated with frizzle feather in Xiushui Yellow Chicken. Based on genotyping performed in a large Xiushui Yellow Chicken population, the g.5285437-5285451delGATGCCGGCAGGACG mutation in KRT75L4 was confirmed as the putative causative mutation of frizzle feather. These results deepen the understanding of the molecular mechanisms responsible for frizzle feather, as well as facilitating the molecular detection and selection of the feather phenotype in Xiushui Yellow Chickens.
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Affiliation(s)
- B Chen
- College of Animal Science and Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
| | - S Xi
- College of Animal Science and Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China.,Jiangxi Biotech Vocational College, Nanchang, Jiangxi, 330200, China
| | - H A K El-Senousey
- Department of Animal Production, Faculty of Agriculture, Cairo University, Giza, 12613, Egypt
| | - M Zhou
- College of Animal Science and Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
| | - D Cheng
- College of Animal Science and Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
| | - K Chen
- College of Animal Science and Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
| | - L Wan
- College of Animal Science and Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
| | - T Xiong
- College of Animal Science and Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
| | - M Liao
- School of Foreign Languages, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
| | - S Liu
- College of Animal Science and Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
| | - H Mao
- College of Animal Science and Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
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Wang YM, Khederzadeh S, Li SR, Otecko NO, Irwin DM, Thakur M, Ren XD, Wang MS, Wu DD, Zhang YP. Integrating Genomic and Transcriptomic Data to Reveal Genetic Mechanisms Underlying Piao Chicken Rumpless Trait. GENOMICS PROTEOMICS & BIOINFORMATICS 2021; 19:787-799. [PMID: 33631431 PMCID: PMC9170765 DOI: 10.1016/j.gpb.2020.06.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 04/14/2020] [Accepted: 06/10/2020] [Indexed: 11/19/2022]
Abstract
Piao chicken, a rare Chinese native poultry breed, lacks primary tail structures, such as pygostyle, caudal vertebra, uropygial gland, and tail feathers. So far, the molecular mechanisms underlying tail absence in this breed remain unclear. In this study, we comprehensively employed comparative transcriptomic and genomic analyses to unravel potential genetic underpinnings of rumplessness in Piao chicken. Our results reveal many biological factors involved in tail development and several genomic regions under strong positive selection in this breed. These regions contain candidate genes associated with rumplessness, including Irx4, Il18, Hspb2, and Cryab. Retrieval of quantitative trait loci (QTL) and gene functions implies that rumplessness might be consciously or unconsciously selected along with the high-yield traits in Piao chicken. We hypothesize that strong selection pressures on regulatory elements might lead to changes in gene activity in mesenchymal stem cells of the tail bud. The ectopic activity could eventually result in tail truncation by impeding differentiation and proliferation of the stem cells. Our study provides fundamental insights into early initiation and genetic basis of the rumpless phenotype in Piao chicken.
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Affiliation(s)
- Yun-Mei Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China; Center for Neurobiology and Brain Restoration, Skolkovo Institute of Science and Technology, Moscow 143026, Russia
| | - Saber Khederzadeh
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China
| | - Shi-Rong Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China
| | - Newton Otieno Otecko
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China
| | - David M Irwin
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto M5S 1A8, Canada
| | - Mukesh Thakur
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Zoological Survey of India, Kolkata 700053, India
| | - Xiao-Die Ren
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China
| | - Ming-Shan Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China.
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China.
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China.
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Gao Z, Ding R, Zhai X, Wang Y, Chen Y, Yang CX, Du ZQ. Common Gene Modules Identified for Chicken Adiposity by Network Construction and Comparison. Front Genet 2020; 11:537. [PMID: 32547600 PMCID: PMC7272656 DOI: 10.3389/fgene.2020.00537] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Accepted: 05/04/2020] [Indexed: 12/12/2022] Open
Abstract
Excessive fat deposition can cause chicken health problem, and affect production efficiency by causing great economic losses to the industry. However, the molecular underpinnings of the complex adiposity trait remain elusive. In the current study, we constructed and compared the gene co-expression networks on four transcriptome profiling datasets, from two chicken lines under divergent selection for abdominal fat contents, in an attempt to dissect network compositions underlying adipose tissue growth and development. After functional enrichment analysis, nine network modules important to adipogenesis were discovered to be involved in lipid metabolism, PPAR and insulin signaling pathways, and contained hub genes related to adipogenesis, cell cycle, inflammation, and protein synthesis. Moreover, after additional functional annotation and network module comparisons, common sub-modules of similar functionality for chicken fat deposition were identified for different chicken lines, apart from modules specific to each chicken line. We further validated the lysosome pathway, and found TFEB and its downstream target genes showed similar expression patterns along with chicken preadipocyte differentiation. Our findings could provide novel insights into the genetic basis of complex adiposity traits, as well as human obesity and related metabolic diseases.
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Affiliation(s)
- Zhuoran Gao
- College of Animal Science, Yangtze University, Jingzhou, China.,College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Ran Ding
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Xiangyun Zhai
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Yuhao Wang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Yaofeng Chen
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Cai-Xia Yang
- College of Animal Science, Yangtze University, Jingzhou, China.,College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Zhi-Qiang Du
- College of Animal Science, Yangtze University, Jingzhou, China.,College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
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Dong X, Li J, Zhang Y, Han D, Hua G, Wang J, Deng X, Wu C. Genomic Analysis Reveals Pleiotropic Alleles at EDN3 and BMP7 Involved in Chicken Comb Color and Egg Production. Front Genet 2019; 10:612. [PMID: 31316551 PMCID: PMC6611142 DOI: 10.3389/fgene.2019.00612] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Accepted: 06/12/2019] [Indexed: 12/20/2022] Open
Abstract
Artificial selection is often associated with numerous changes in seemingly unrelated phenotypic traits. The genetic mechanisms of correlated phenotypes probably involve pleiotropy or linkage of genes related to such phenotypes. Dongxiang blue-shelled chicken, an indigenous chicken breed of China, has segregated significantly for the dermal hyperpigmentation phenotype. Two lines of the chicken have been divergently selected with respect to comb color for over 20 generations. The red comb line chicken produces significantly higher number of eggs than the dark comb line chicken. The objective of this study was to explore potential mechanisms involved in the relationship between comb color and egg production among chickens. Based on the genome-wide association study results, we identified a genomic region on chromosome 20 involving EDN3 and BMP7, which is associated with hyperpigmentation of chicken comb. Further analyses by selection signatures in the two divergent lines revealed that several candidate genes, including EDN3, BMP7, BPIFB3, and PCK1, closely located on chromosome 20 are involved in the development of neural crest cell and reproductive system. The two genes EDN3 and BMP7 have known roles in regulating both ovarian function and melanogenesis, indicating the pleiotropic effect on hyperpigmentation and egg production in blue-shelled chickens. Association analysis for egg production confirmed the pleiotropic effect of selected loci identified by selection signatures. The study provides insights into phenotypic evolution due to genetic variation across the genome. The information might be useful in the current breeding efforts to develop improved breeds for egg production.
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Affiliation(s)
- Xianggui Dong
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture, China Agricultural University, Beijing, China
| | - Junying Li
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture, China Agricultural University, Beijing, China
| | - Yuanyuan Zhang
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture, China Agricultural University, Beijing, China
| | - Deping Han
- College of Veterinary Medicine, China Agricultural University, Beijing, China
| | - Guoying Hua
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture, China Agricultural University, Beijing, China
| | - Jiankui Wang
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture, China Agricultural University, Beijing, China
| | - Xuemei Deng
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture, China Agricultural University, Beijing, China
| | - Changxin Wu
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture, China Agricultural University, Beijing, China
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