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Azam S, Sahu A, Pandey NK, Neupane M, Van Tassell CP, Rosen BD, Gandham RK, Rath SN, Majumdar SS. Constructing a draft Indian cattle pangenome using short-read sequencing. Commun Biol 2025; 8:605. [PMID: 40223124 PMCID: PMC11994783 DOI: 10.1038/s42003-025-07978-0] [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: 09/20/2024] [Accepted: 03/21/2025] [Indexed: 04/15/2025] Open
Abstract
Indian desi cattle, known for their adaptability and phenotypic diversity, represent a valuable genetic resource. However, a single reference genome often fails to capture the full extent of their genetic variation. To address this, we construct a pangenome for desi cattle by identifying and characterizing non-reference novel sequences (NRNS). We sequence 68 genomes from seven breeds, generating 48.35 billion short reads. Using the PanGenome Analysis (PanGA) pipeline, we identify 13,065 NRNS (~41 Mbp), with substantial variation across the population. Most NRNS were unique to desi cattle, with minimal overlap (4.1%) with the Chinese indicine pangenome. Approximately 40% of NRNS exhibited ancestral origins within the Bos genus and were enriched in genic regions, suggesting functional roles. These sequences are linked to quantitative trait loci for traits such as milk production. The pangenome approach enhances read mapping accuracy, reduces spurious single nucleotide polymorphism calls, and uncovers novel genetic variants, offering a deeper understanding of desi cattle genomics.
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Affiliation(s)
- Sarwar Azam
- National Institute of Animal Biotechnology, Hyderabad, India
- Indian Institute of Technology Hyderabad, Sangareddy, India
| | - Abhisek Sahu
- National Institute of Animal Biotechnology, Hyderabad, India
| | | | - Mahesh Neupane
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, USA
| | | | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, USA.
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Xu S, Akhatayeva Z, Liu J, Feng X, Yu Y, Badaoui B, Esmailizadeh A, Kantanen J, Amills M, Lenstra JA, Johansson AM, Coltman DW, Liu GE, Curik I, Orozco-terWengel P, Paiva SR, Zinovieva NA, Zhang L, Yang J, Liu Z, Wang Y, Yu Y, Li M. Genetic advancements and future directions in ruminant livestock breeding: from reference genomes to multiomics innovations. SCIENCE CHINA. LIFE SCIENCES 2025; 68:934-960. [PMID: 39609363 DOI: 10.1007/s11427-024-2744-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Accepted: 09/24/2024] [Indexed: 11/30/2024]
Abstract
Ruminant livestock provide a rich source of products, such as meat, milk, and wool, and play a critical role in global food security and nutrition. Over the past few decades, genomic studies of ruminant livestock have provided valuable insights into their domestication and the genetic basis of economically important traits, facilitating the breeding of elite varieties. In this review, we summarize the main advancements for domestic ruminants in reference genome assemblies, population genomics, and the identification of functional genes or variants for phenotypic traits. These traits include meat and carcass quality, reproduction, milk production, feed efficiency, wool and cashmere yield, horn development, tail type, coat color, environmental adaptation, and disease resistance. Functional genomic research is entering a new era with the advancements of graphical pangenomics and telomere-to-telomere (T2T) gap-free genome assembly. These advancements promise to improve our understanding of domestication and the molecular mechanisms underlying economically important traits in ruminant livestock. Finally, we provide new perspectives and future directions for genomic research on ruminant genomes. We suggest how ever-increasing multiomics datasets will facilitate future studies and molecular breeding in livestock, including the potential to uncover novel genetic mechanisms underlying phenotypic traits, to enable more accurate genomic prediction models, and to accelerate genetic improvement programs.
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Affiliation(s)
- Songsong Xu
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Zhanerke Akhatayeva
- Institute of Grassland Research, Chinese Academy of Agricultural Sciences, Hohhot, 010010, China
| | - Jiaxin Liu
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Xueyan Feng
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Yi Yu
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Bouabid Badaoui
- Laboratory of Biodiversity, Ecology and Genome, Department of Biology, Faculty of Sciences Rabat, Mohammed V University, Rabat, 10106, Morocco
| | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, 76169-133, Iran
| | - Juha Kantanen
- Production Systems, Natural Resources Institute Finland (Luke), Jokioinen, FI-31600, Finland
| | - Marcel Amills
- Department of Animal Genetics, Center for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus de la Universitat Autónoma de Barcelona, Bellaterra, 08193, Spain
- Departament de Ciència Animal i dels Aliments, Universitat Autónoma de Barcelona, Bellaterra, 08193, Spain
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, 3584, The Netherlands
| | - Anna M Johansson
- Department of Animal Breeding and Genetics, Faculty of Veterinary Medicine and Animal Science, Swedish University of Agricultural Sciences, Uppsala, 75007, Sweden
| | - David W Coltman
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9, Canada
- Department of Biology, Western University, London, Ontario, N6A 5B7, Canada
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, 20705, USA
| | - Ino Curik
- Department of Animal Science, Faculty of Agriculture, University of Zagreb, Zagreb, 10000, Croatia
- Institute of Animal Sciences, Hungarian University of Agriculture and Life Sciences (MATE), Kaposvár, 7400, Hungary
| | | | - Samuel R Paiva
- Embrapa Genetic Resources and Biotechnology, Laboratory of Animal Genetics, Brasília, Federal District, 70770917, Brazil
| | - Natalia A Zinovieva
- L.K. Ernst Federal Science Center for Animal Husbandry, Moscow Region, Podolsk, 142132, Russian Federation
| | - Linwei Zhang
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Ji Yang
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Zhihong Liu
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Yachun Wang
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Ying Yu
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Menghua Li
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
- Sanya Institute of China Agricultural University, Sanya, 572024, China.
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Wang Q, Lu Y, Li M, Gao Z, Li D, Gao Y, Deng W, Wu J. Leveraging Whole-Genome Resequencing to Uncover Genetic Diversity and Promote Conservation Strategies for Ruminants in Asia. Animals (Basel) 2025; 15:831. [PMID: 40150358 PMCID: PMC11939356 DOI: 10.3390/ani15060831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2025] [Revised: 02/28/2025] [Accepted: 03/12/2025] [Indexed: 03/29/2025] Open
Abstract
Whole-genome resequencing (WGRS) is a critical branch of whole-genome sequencing (WGS), primarily targeting species with existing reference genomes. By aligning sequencing data to the reference genome, WGRS enables precise detection of genetic variations in individuals or populations. As a core technology in genomic research, WGS holds profound significance in ruminant studies. It not only reveals the intricate structure of ruminant genomes but also provides essential data for deciphering gene function, variation patterns, and evolutionary processes, thereby advancing the exploration of ruminant genetic mechanisms. However, WGS still faces several challenges, such as incomplete and inaccurate genome assembly, as well as the incomplete annotation of numerous unknown genes or gene functions. Although WGS can identify a vast number of genomic variations, the specific relationships between these variations and phenotypes often remain unclear, which limits its potential in functional studies and breeding applications. By performing WGRS on multiple samples, these assembly challenges can be effectively addressed, particularly in regions with high repeat content or complex structural variations. WGRS can accurately identify subtle variations among different individuals or populations and further elucidate their associations with specific traits, thereby overcoming the limitations of WGS and providing more precise genetic information for functional research and breeding applications. This review systematically summarizes the latest applications of WGRS in the analysis of ruminant genetic structures, genetic diversity, economic traits, and adaptive traits, while also discussing the challenges faced by this technology. It aims to provide a scientific foundation for the improvement and conservation of ruminant genetic resources.
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Affiliation(s)
| | | | | | | | | | | | - Weidong Deng
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China (Y.L.); (M.L.); (Z.G.); (D.L.); (Y.G.)
| | - Jiao Wu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China (Y.L.); (M.L.); (Z.G.); (D.L.); (Y.G.)
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Azam S, Sahu A, Pandey NK, Neupane M, Van Tassell CP, Rosen BD, Gandham RK, Rath SN, Majumdar SS. Advancing the Indian cattle pangenome: characterizing non-reference sequences in Bos indicus. J Anim Sci Biotechnol 2025; 16:21. [PMID: 39915889 PMCID: PMC11804092 DOI: 10.1186/s40104-024-01133-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2024] [Accepted: 11/26/2024] [Indexed: 02/09/2025] Open
Abstract
BACKGROUND India harbors the world's largest cattle population, encompassing over 50 distinct Bos indicus breeds. This rich genetic diversity underscores the inadequacy of a single reference genome to fully capture the genomic landscape of Indian cattle. To comprehensively characterize the genomic variation within Bos indicus and, specifically, dairy breeds, we aim to identify non-reference sequences and construct a comprehensive pangenome. RESULTS Five representative genomes of prominent dairy breeds, including Gir, Kankrej, Tharparkar, Sahiwal, and Red Sindhi, were sequenced using 10X Genomics 'linked-read' technology. Assemblies generated from these linked-reads ranged from 2.70 Gb to 2.77 Gb, comparable to the Bos indicus Brahman reference genome. A pangenome of Bos indicus cattle was constructed by comparing the newly assembled genomes with the reference using alignment and graph-based methods, revealing 8 Mb and 17.7 Mb of novel sequence respectively. A confident set of 6,844 Non-reference Unique Insertions (NUIs) spanning 7.57 Mb was identified through both methods, representing the pangenome of Indian Bos indicus breeds. Comparative analysis with previously published pangenomes unveiled 2.8 Mb (37%) commonality with the Chinese indicine pangenome and only 1% commonality with the Bos taurus pangenome. Among these, 2,312 NUIs encompassing ~ 2 Mb, were commonly found in 98 samples of the 5 breeds and designated as Bos indicus Common Insertions (BICIs) in the population. Furthermore, 926 BICIs were identified within 682 protein-coding genes, 54 long non-coding RNAs (lncRNA), and 18 pseudogenes. These protein-coding genes were enriched for functions such as chemical synaptic transmission, cell junction organization, cell-cell adhesion, and cell morphogenesis. The protein-coding genes were found in various prominent quantitative trait locus (QTL) regions, suggesting potential roles of BICIs in traits related to milk production, reproduction, exterior, health, meat, and carcass. Notably, 63.21% of the bases within the BICIs call set contained interspersed repeats, predominantly Long Interspersed Nuclear Elements (LINEs). Additionally, 70.28% of BICIs are shared with other domesticated and wild species, highlighting their evolutionary significance. CONCLUSIONS This is the first report unveiling a robust set of NUIs defining the pangenome of Bos indicus breeds of India. The analyses contribute valuable insights into the genomic landscape of desi cattle breeds.
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Affiliation(s)
- Sarwar Azam
- National Institute of Animal Biotechnology, Hyderabad, India
- Indian Institute of Technology Hyderabad, Sangareddy, India
| | - Abhisek Sahu
- National Institute of Animal Biotechnology, Hyderabad, India
| | | | - Mahesh Neupane
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, 20705, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, 20705, USA
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, 20705, USA.
| | - Ravi Kumar Gandham
- National Institute of Animal Biotechnology, Hyderabad, India.
- Animal Biotechnology, ICAR-NBAGR, Karnal, Haryana, India.
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Si J, Dai D, Gorkhali NA, Wang M, Wang S, Sapkota S, Kadel RC, Sadaula A, Dhakal A, Faruque MO, Omar AI, Sari EM, Ashari H, Dagong MIA, Yindee M, Rushdi HE, Elregalaty H, Amin A, Radwan MA, Pham LD, Hulugalla WMMP, Silva GLLP, Zheng W, Mansoor S, Ali MB, Vahidi F, Al-Bayatti SA, Pauciullo A, Lenstra JA, Barker JSF, Fang L, Wu DD, Han J, Zhang Y. Complete Genomic Landscape Reveals Hidden Evolutionary History and Selection Signature in Asian Water Buffaloes (Bubalus bubalis). ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2407615. [PMID: 39630943 DOI: 10.1002/advs.202407615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2024] [Revised: 10/18/2024] [Indexed: 12/07/2024]
Abstract
To identify the genetic determinants of domestication and productivity of Asian water buffaloes (Bubalus bubalis), 470 genomes of domesticated river and swamp buffaloes along with their putative ancestors, the wild water buffaloes (Bubalus arnee) are sequenced and integrated. The swamp buffaloes inherit the morphology of the wild buffaloes. In contrast, most river buffaloes are unique in their morphology, but their genomes cluster with the wild buffaloes. The levels of genomic diversity in Italian river and Indonesian swamp buffaloes decrease at opposite extremes of their distribution range. Purifying selection prevented the accumulation of harmful loss-of-function variants in the Indonesian buffaloes. Genes that evolved rapidly (e.g., GKAP1) following differential selections in the river and swamp buffaloes are involved in their reproduction. Genes related to milk production (e.g., CSN2) and coat color (e.g., MC1R) underwent strong selections in the dairy river buffaloes via soft and hard selective sweeps, respectively. The selective sweeps and single-cell RNA-seq data revealed the luminal cells as the key cell type in response to artificial selection for milk production of the dairy buffaloes. These findings show how artificial selection has been driving the evolutionary divergence and genetic differentiation in morphology and productivity of Asian water buffaloes.
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Affiliation(s)
- Jingfang Si
- State Key Laboratory of Animal Biotech Breeding, 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
| | - Dongmei Dai
- State Key Laboratory of Animal Biotech Breeding, 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
| | - Neena Amatya Gorkhali
- National Animal Breeding and Genetics Research Centre, National Animal Science Research Institute, Nepal Agriculture Research Council, Khumaltar, Lalitpur, Nepal
| | - Mingshan Wang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650023, China
| | - Sheng Wang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650023, China
| | - Saroj Sapkota
- National Animal Breeding and Genetics Research Centre, National Animal Science Research Institute, Nepal Agriculture Research Council, Khumaltar, Lalitpur, Nepal
| | - Ram Chandra Kadel
- Ministry of Industry, Tourism, Forests and Environment, Government of Gandaki Province, Pokhara, Nepal
| | - Amir Sadaula
- National Trust for Nature Conservation- Biodiversity Conservation Center, Sauraha, Chitwan, Nepal
| | - Aashish Dhakal
- State Key Laboratory of Animal Biotech Breeding, 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
| | - Md Omar Faruque
- Department of Animal Breeding and Genetics, Bangladesh Agricultural University, Mymensingh, 2202, Bangladesh
| | - Abdullah Ibne Omar
- State Key Laboratory of Animal Biotech Breeding, 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
| | - Eka Meutia Sari
- Department of Animal Science, Faculty of Agriculture, Syiah Kuala University, Darussalam-Banda Aceh, 23111, Indonesia
| | - Hidayat Ashari
- Department of Animal Science, Faculty of Agriculture, Syiah Kuala University, Darussalam-Banda Aceh, 23111, Indonesia
| | | | - Marnoch Yindee
- Akkhraratchakumari Veterinary College, Walailak University, Thaiburi, 222, Thailand
| | - Hossam E Rushdi
- Department of Animal Production, Faculty of Agriculture, Cairo University, Algammaa Street, Giza, 12613, Egypt
| | - Hussein Elregalaty
- Animal Production Research Institute, Agricultural Research Center, Dokki, Giza, Egypt
| | - Ahmed Amin
- Department of Animal Production, Faculty of Agriculture, Cairo University, Algammaa Street, Giza, 12613, Egypt
| | - Mohamed A Radwan
- Department of Animal Production, Faculty of Agriculture, Cairo University, Algammaa Street, Giza, 12613, Egypt
| | - Lan Doan Pham
- Key Laboratory of Animal Cell Technology, National Institute of Animal Sciences, Tu Liem, Hanoi, 100000, Vietnam
| | - W M M P Hulugalla
- Department of Animal Science, Faculty of Agriculture, University of Peradeniya, Sri Lanka
| | - G L L Pradeepa Silva
- Department of Animal Science, Faculty of Agriculture, University of Peradeniya, Sri Lanka
| | - Wei Zheng
- Guangxi Key Laboratory of Buffalo Genetics, Reproduction and Breeding, Guangxi Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning, 530001, China
| | - Shahid Mansoor
- National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Pakistan
- Jamil ur Rehman Center for Genome Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, Pakistan
| | - Muhammad Basil Ali
- National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Pakistan
| | - Farhad Vahidi
- Department of Genomics, Agricultural Biotechnology Research Institute of Iran-North Branch (ABRII), Rasht, Iran
| | - Sahar Ahmed Al-Bayatti
- Medical Laboratory Techniques Department, Al-Farabi University College, Ministry of Higher Education and Scientific Research, Baghdad, Iraq
| | - Alfredo Pauciullo
- Department of Agricultural, Forest and Food Sciences, University of Turin, Grugliasco (TO), 10095, Italy
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Yalelaan 104, Utrecht CM, 3584, The Netherlands
| | - J Stuart F Barker
- School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia
| | - Lingzhao Fang
- The Center for Quantitative Genetics and Genomics (QGG), Aarhus University, Aarhus, 8000, Denmark
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650023, China
| | - Jianlin Han
- Yazhouwan National Laboratory, Sanya, 572024, China
| | - Yi Zhang
- State Key Laboratory of Animal Biotech Breeding, 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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Dhakal A, Si J, Sapkota S, Pauciullo A, Han J, Gorkhali NA, Zhao X, Zhang Y. Whole-genome sequencing reveals genetic structure and adaptive genes in Nepalese buffalo breeds. BMC Genomics 2024; 25:1082. [PMID: 39543523 PMCID: PMC11566569 DOI: 10.1186/s12864-024-10993-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 11/05/2024] [Indexed: 11/17/2024] Open
Abstract
BACKGROUND Indigenous buffaloes, as the important livestock species contributing to economy of the country, are the lifeline of livelihood in Nepal. They are distributed across diverse geographical regions of the country and have adapted to various feeding, breeding, and management conditions. The larger group of these native buffalo breeds are present in narrow and stiff hilly terrains. Their dispersal indicates a possible environmental adaptation mechanism, which is crucial for the conservation of these breeds. RESULTS We utilized whole-genome sequencing (WGS) to investigate the genetic diversity, population structure, and selection signatures of Nepalese indigenous buffaloes. We compared 66 whole-genome sequences with 118 publicly available sequences from six river and five swamp buffalo breeds. Genomic diversity parameters indicated genetic variability level in the Nepalese buffaloes comparable to those of Indian breeds, and population genetic structure revealed distinct geography-mediated genetic differentiation among these breeds. We used locus-specific branch length analysis (LSBL) for genome-wide scan, which revealed a list of potentially selected genes in Lime and Parkote breeds that inhabit the hilly region. A gene ontology (GO) analysis discovered that many GO terms were associated with cardiac function regulation. Furthermore, complementary analyses of local selection signatures, tissue expression profiles, and haplotype differences identified candidate genes, including KCNE1, CSF1R, and PDGFRB, related to the regulation of cardiac and pulmonary functions. CONCLUSIONS This study is a comprehensive WGS-based genetic analysis of the native Nepalese buffalo breeds. Our study suggested that the Nepalese "hilly" buffaloes, especially the Lime and Parkote breeds, have undergone some characteristic genetic changes and evolved increased cardiac and pulmonary function for their adaptation to the steep hilly terrains of the country.
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Affiliation(s)
- Aashish Dhakal
- State Key Laboratory of Animal Biotech Breeding, 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
- State Key Laboratory of Animal Biotech Breeding, 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
| | - Saroj Sapkota
- National Animal Breeding and Genetics Research Centre, Nepal Agricultural Research Council, Lalitpur, Nepal
| | - Alfredo Pauciullo
- Department of Agricultural, Forest and Food Sciences, University of Torino, Grugliasco, 10095, Italy
| | - Jianlin Han
- Yazhouwan National Laboratory, Sanya, 572024, China
| | - Neena Amatya Gorkhali
- National Animal Breeding and Genetics Research Centre, Nepal Agricultural Research Council, Lalitpur, Nepal.
| | - Xingbo Zhao
- State Key Laboratory of Animal Biotech Breeding, 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.
| | - Yi Zhang
- State Key Laboratory of Animal Biotech Breeding, 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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Dai D, Sari EM, Si J, Ashari H, Dagong MIA, Pauciullo A, Lenstra JA, Han J, Zhang Y. Genomic analysis reveals the association of KIT and MITF variants with the white spotting in swamp buffaloes. BMC Genomics 2024; 25:713. [PMID: 39048931 PMCID: PMC11267946 DOI: 10.1186/s12864-024-10634-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2024] [Accepted: 07/18/2024] [Indexed: 07/27/2024] Open
Abstract
BACKGROUND Swamp-type buffaloes with varying degrees of white spotting are found exclusively in Tana Toraja, South Sulawesi, Indonesia, where spotted buffalo bulls are highly valued in accordance with the Torajan customs. The white spotting depigmentation is caused by the absence of melanocytes. However, the genetic variants that cause this phenotype have not been fully characterized. The objective of this study was to identify the genomic regions and variants responsible for this unique coat-color pattern. RESULTS Genome-wide association study (GWAS) and selection signature analysis identified MITF as a key gene based on the whole-genome sequencing data of 28 solid and 39 spotted buffaloes, while KIT was also found to be involved in the development of this phenotype by a candidate gene approach. Alternative candidate mutations included, in addition to the previously reported nonsense mutation c.649 C > T (p.Arg217*) and splice donor mutation c.1179 + 2T > A in MITF, a nonsense mutation c.2028T > A (p.Tyr676*) in KIT. All these three mutations were located in the genomic regions that were highly conserved exclusively in Indonesian swamp buffaloes and they accounted largely (95%) for the manifestation of white spotting. Last but not the least, ADAMTS20 and TWIST2 may also contribute to the diversification of this coat-color pattern. CONCLUSIONS The alternative mutations identified in this study affect, at least partially and independently, the development of melanocytes. The presence and persistence of such mutations may be explained by significant financial and social value of spotted buffaloes used in historical Rambu Solo ceremony in Tana Toraja, Indonesia. Several de novo spontaneous mutations have therefore been favored by traditional breeding for the spotted buffaloes.
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Affiliation(s)
- Dongmei Dai
- State Key Laboratory of Animal Biotech Breeding, 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
| | - Eka Meutia Sari
- Department of Animal Science, Agriculture Faculty, Universitas Syiah Kuala (USK), Banda Aceh, 23111, Indonesia.
| | - Jingfang Si
- State Key Laboratory of Animal Biotech Breeding, 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
| | - Hidayat Ashari
- Research Center for Biosystematics and Evolution, National Research and Innovation Agency (BRIN), Cibinong, 16911, Indonesia
| | - Muhammad Ihsan Andi Dagong
- Animal Production Department, Faculty of Animal Science, Hasanuddin University, Makassar, 90245, Indonesia
| | - Alfredo Pauciullo
- Department of Agricultural, Forest and Food Sciences, University of Turin, Grugliasco (TO), 10095, Italy
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Yalelaan 104, 3584 CM, Utrecht, The Netherlands
| | - Jianlin Han
- Yazhouwan National Laboratory, Sanya, 572024, China
| | - Yi Zhang
- State Key Laboratory of Animal Biotech Breeding, 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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Talenti A, Wilkinson T, Cook EA, Hemmink JD, Paxton E, Mutinda M, Ngulu SD, Jayaraman S, Bishop RP, Obara I, Hourlier T, Garcia Giron C, Martin FJ, Labuschagne M, Atimnedi P, Nanteza A, Keyyu JD, Mramba F, Caron A, Cornelis D, Chardonnet P, Fyumagwa R, Lembo T, Auty HK, Michaux J, Smitz N, Toye P, Robert C, Prendergast JGD, Morrison LJ. Continent-wide genomic analysis of the African buffalo (Syncerus caffer). Commun Biol 2024; 7:792. [PMID: 38951693 PMCID: PMC11217449 DOI: 10.1038/s42003-024-06481-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 06/21/2024] [Indexed: 07/03/2024] Open
Abstract
The African buffalo (Syncerus caffer) is a wild bovid with a historical distribution across much of sub-Saharan Africa. Genomic analysis can provide insights into the evolutionary history of the species, and the key selective pressures shaping populations, including assessment of population level differentiation, population fragmentation, and population genetic structure. In this study we generated the highest quality de novo genome assembly (2.65 Gb, scaffold N50 69.17 Mb) of African buffalo to date, and sequenced a further 195 genomes from across the species distribution. Principal component and admixture analyses provided little support for the currently described four subspecies. Estimating Effective Migration Surfaces analysis suggested that geographical barriers have played a significant role in shaping gene flow and the population structure. Estimated effective population sizes indicated a substantial drop occurring in all populations 5-10,000 years ago, coinciding with the increase in human populations. Finally, signatures of selection were enriched for key genes associated with the immune response, suggesting infectious disease exert a substantial selective pressure upon the African buffalo. These findings have important implications for understanding bovid evolution, buffalo conservation and population management.
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Affiliation(s)
- Andrea Talenti
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, EH25 9RG, United Kingdom
- Centre for Tropical Livestock Genetics and Health (CTLGH), Roslin Institute, University of Edinburgh, Easter Bush Campus, Roslin, EH25 9RG, United Kingdom
| | - Toby Wilkinson
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, EH25 9RG, United Kingdom
- Centre for Tropical Livestock Genetics and Health (CTLGH), Roslin Institute, University of Edinburgh, Easter Bush Campus, Roslin, EH25 9RG, United Kingdom
| | - Elizabeth A Cook
- International Livestock Research Institute, P.O. Box 30709, Nairobi, 00100, Kenya
- Centre for Tropical Livestock Genetics and Health (CTLGH), ILRI Kenya, P.O. Box 30709, Nairobi, 00100, Kenya
| | - Johanneke D Hemmink
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, EH25 9RG, United Kingdom
- Centre for Tropical Livestock Genetics and Health (CTLGH), Roslin Institute, University of Edinburgh, Easter Bush Campus, Roslin, EH25 9RG, United Kingdom
- International Livestock Research Institute, P.O. Box 30709, Nairobi, 00100, Kenya
- Centre for Tropical Livestock Genetics and Health (CTLGH), ILRI Kenya, P.O. Box 30709, Nairobi, 00100, Kenya
| | - Edith Paxton
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, EH25 9RG, United Kingdom
| | - Matthew Mutinda
- Kenya Wildlife Service, P.O. Box 40241, Nairobi, 00100, Kenya
| | | | - Siddharth Jayaraman
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, EH25 9RG, United Kingdom
| | - Richard P Bishop
- International Livestock Research Institute, P.O. Box 30709, Nairobi, 00100, Kenya
| | - Isaiah Obara
- Institute for Parasitology and Tropical Veterinary Medicine, Freie Universität Berlin, Robert-von-Ostertag-Str. 7-13, 14163, Berlin, Germany
| | - Thibaut Hourlier
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, United Kingdom
| | - Carlos Garcia Giron
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, United Kingdom
| | - Fergal J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, United Kingdom
| | | | | | - Anne Nanteza
- College of Veterinary Medicine, Animal Resources and Biosecurity, Makerere University, Kampala, Uganda
| | - Julius D Keyyu
- Tanzania Wildlife Research Institute, Box 661, Arusha, Tanzania
| | - Furaha Mramba
- Vector and Vector-Borne Diseases Institute, Tanga, Tanzania
| | - Alexandre Caron
- ASTRE, University of Montpellier (UMR), CIRAD, 34090, Montpellier, France
- CIRAD, UMR ASTRE, RP-PCP, Maputo, 01009, Mozambique
- Faculdade Veterinaria, Universidade Eduardo Mondlan, Maputo, Mozambique
| | - Daniel Cornelis
- CIRAD, Forêts et Sociétés, 34398, Montpellier, France
- Forêts et Sociétés, University of Montpellier, CIRAD, 34090, Montpellier, France
| | | | - Robert Fyumagwa
- Tanzania Wildlife Research Institute, Box 661, Arusha, Tanzania
| | - Tiziana Lembo
- School of Biodiversity, One Health and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Harriet K Auty
- School of Biodiversity, One Health and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Johan Michaux
- Laboratoire de Génétique de la Conservation, Institut de Botanique (Bat. 22), Université de Liège (Sart Tilman), Chemin de la Vallée 4, B4000, Liège, Belgium
| | - Nathalie Smitz
- Royal Museum for Central Africa (BopCo), Leuvensesteenweg 13, 3080, Tervuren, Belgium
| | - Philip Toye
- International Livestock Research Institute, P.O. Box 30709, Nairobi, 00100, Kenya
- Centre for Tropical Livestock Genetics and Health (CTLGH), ILRI Kenya, P.O. Box 30709, Nairobi, 00100, Kenya
| | - Christelle Robert
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, EH25 9RG, United Kingdom
- Centre for Tropical Livestock Genetics and Health (CTLGH), Roslin Institute, University of Edinburgh, Easter Bush Campus, Roslin, EH25 9RG, United Kingdom
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, United Kingdom
| | - James G D Prendergast
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, EH25 9RG, United Kingdom
- Centre for Tropical Livestock Genetics and Health (CTLGH), Roslin Institute, University of Edinburgh, Easter Bush Campus, Roslin, EH25 9RG, United Kingdom
| | - Liam J Morrison
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, EH25 9RG, United Kingdom.
- Centre for Tropical Livestock Genetics and Health (CTLGH), Roslin Institute, University of Edinburgh, Easter Bush Campus, Roslin, EH25 9RG, United Kingdom.
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Melo TP, Zwirtes AK, Silva AA, Lázaro SF, Oliveira HR, Silveira KR, Santos JCG, Andrade WBF, Kluska S, Evangelho LA, Oliveira HN, Tonhati H. Unknown parent groups and truncated pedigree in single-step genomic evaluations of Murrah buffaloes. J Dairy Sci 2024:S0022-0302(24)00847-6. [PMID: 38825116 DOI: 10.3168/jds.2023-24608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 04/16/2024] [Indexed: 06/04/2024]
Abstract
Missing pedigree may produce bias in genomic evaluations. Thus, strategies to deal with this problem have been proposed as using unknown parent groups (UPG) or truncated pedigrees. The aim of this study was to investigate the impact of modeling missing pedigree under ssGBLUP evaluations for productive and reproductive traits in dairy buffalos using different approaches: 1) traditional BLUP without UPG (BLUP), 2) traditional BLUP including UPG (BLUP/UPG), 3) ssGBLUP without UPG (ssGBLUP), 4) ssGBLUP including UPG in the A and A22 matrices (ssGBLUP/A_UPG), 5) ssGBLUP including UPG in all elements of the H matrix (ssGBLUP/H_UPG), 6) BLUP with pedigree truncation for the last 3 generations (BLUP/truncated), and 7) ssGBLUP with pedigree truncation for the last 3 generations (ssGBLUP/ truncated). UPGs were not used in the scenarios with truncated pedigree. A total of 3,717, 4,126 and 3,823 records of the first lactation for accumulated 305 d milk yield (MY), age at first calving (AFC) and lactation length (LL), respectively were used. Accuracies ranged from 0.27 for LL (BLUP) to 0.46 for MY (BLUP), bias ranged from -0.62 for MY (ssGBLUP) to 0.0002 for AFC (BLUP/truncated), and dispersion ranged from 0.88 for MY (BLUP/ A_UPG) to 1.13 for LL (BLUP). Genetic trend showed genetic gains for all traits across 20 years of selection and the impact of including either genomic information, UPG or pedigree truncation under GEBV accuracies ranged among the evaluated traits. Overall, methods using UPGs, truncation pedigree and genomic information exhibited potential to improve GEBV accuracies, bias and dispersion for all traits compared with other methods. Truncated scenarios promoted high genetic gains. In small populations with few genotyped animals, combining truncated pedigree or UPG with genomic information is a feasible approach to deal with missing pedigrees.
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Affiliation(s)
- T P Melo
- Departament of Animal Science, Federal University of Santa Maria (UFSM), Santa Maria, 97105-900, Rio Grande do Sul, Brazil.
| | - A K Zwirtes
- Departament of Animal Science, Federal University of Santa Maria (UFSM), Santa Maria, 97105-900, Rio Grande do Sul, Brazil
| | - A A Silva
- Departament of Animal Science, Sao Paulo State University (UNESP), Jaboticabal 14884-900, Sao Paulo, Brazil
| | - S F Lázaro
- Department of Animal Biosciences, University of Guelph, Guelph, N1G 1Y2, Ontario, Canada
| | - H R Oliveira
- Departament of Animal Sciences, Purdue University, West Lafayette, 47906, Indiana, USA
| | - K R Silveira
- Departament of Animal Science, Sao Paulo State University (UNESP), Jaboticabal 14884-900, Sao Paulo, Brazil
| | - J C G Santos
- Departament of Animal Science, Sao Paulo State University (UNESP), Jaboticabal 14884-900, Sao Paulo, Brazil
| | - W B F Andrade
- Departament of Animal Science, Sao Paulo State University (UNESP), Jaboticabal 14884-900, Sao Paulo, Brazil
| | - S Kluska
- Brazilian Association of Girolando Breeder's
| | - L A Evangelho
- Departament of Animal Science, Federal University of Santa Maria (UFSM), Santa Maria, 97105-900, Rio Grande do Sul, Brazil
| | - H N Oliveira
- Departament of Animal Science, Sao Paulo State University (UNESP), Jaboticabal 14884-900, Sao Paulo, Brazil
| | - H Tonhati
- Departament of Animal Science, Sao Paulo State University (UNESP), Jaboticabal 14884-900, Sao Paulo, Brazil
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10
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Pauciullo A, Gaspa G, Zhang Y, Liu Q, Cosenza G. CSN1S1, CSN3 and LPL: Three Validated Gene Polymorphisms Useful for More Sustainable Dairy Production in the Mediterranean River Buffalo. Animals (Basel) 2024; 14:1414. [PMID: 38791632 PMCID: PMC11117199 DOI: 10.3390/ani14101414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 05/06/2024] [Accepted: 05/07/2024] [Indexed: 05/26/2024] Open
Abstract
The search for DNA polymorphisms useful for the genetic improvement of dairy farm animals has spanned more than 40 years, yielding relevant findings in cattle for milk traits, where the best combination of alleles for dairy processing has been found in casein genes and in DGAT1. Nowadays, similar results have not yet been reached in river buffaloes, despite the availability of advanced genomic technologies and accurate phenotype records. The aim of the present study was to investigate and validate the effect of four single nucleotide polymorphisms (SNP) in the CSN1S1, CSN3, SCD and LPL genes on seven milk traits in a larger buffalo population. These SNPs have previously been reported to be associated with, or affect, dairy traits in smaller populations often belonging to one farm. A total of 800 buffaloes were genotyped. The following traits were individually recorded, monthly, throughout each whole lactation period from 2010 to 2021: daily milk yield (dMY, kg), protein yield (dPY, kg) and fat yield (dFY, kg), fat and protein contents (dFP, % and dPP, %), somatic cell count (SCC, 103 cell/mL) and urea (mg/dL). A total of 15,742 individual milk test day records (2496 lactations) were available for 680 buffalo cows, with 3.6 ± 1.7 parities (from 1 to 13) and an average of 6.1 ± 1.2 test day records per lactation. Three out four SNPs in the CSN1S1, CSN3 and LPL genes were associated with at least one of analyzed traits. In particular, the CSN1S1 (AJ005430:c.578C>T) gave favorable associations with all yield traits (dMY, p = 0.022; dPY, p = 0.014; dFY, p = 0.029) and somatic cell score (SCS, p = 0.032). The CSN3 (HQ677596: c.536C>T) was positively associated with SCS (p = 0.005) and milk urea (p = 0.04). Favorable effects on daily milk yield (dMY, p = 0.028), fat (dFP, p = 0.027) and protein (dPP, p = 0.050) percentages were observed for the LPL. Conversely, the SCD did not show any association with milk traits. This is the first example of a confirmation study carried out in the Mediterranean river buffalo for genes of economic interest in the dairy field, and it represents a very important indication for the preselection of young bulls destined for breeding programs aimed at more sustainable dairy production.
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Affiliation(s)
- Alfredo Pauciullo
- Department of Agricultural, Forest and Food Sciences, University of Turin, 10095 Grugliasco, Italy
| | - Giustino Gaspa
- Department of Agricultural, Forest and Food Sciences, University of Turin, 10095 Grugliasco, Italy
| | - Yi Zhang
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Qingyou Liu
- School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Gianfranco Cosenza
- Department of Agriculture, University of Naples Federico II, 80055 Portici, Italy
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11
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He K, Liang C, Ma S, Liu H, Zhu Y. Copy number and selection of MHC genes in ruminants are related to habitat, average life span and diet. Gene 2024; 904:148179. [PMID: 38242373 DOI: 10.1016/j.gene.2024.148179] [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: 09/18/2023] [Revised: 12/26/2023] [Accepted: 01/16/2024] [Indexed: 01/21/2024]
Abstract
The ruminants, as the main group of livestock, have been extensively studied in terms of their physiology, endocrinology, biochemistry, genetics, and nutrition. Despite the wide geographic distribution and habitat diversity of animals in this group, their ecology and evolution remain poorly understood. In this study, we analyzed the gene copy number, selection, and ecological and evolutionary processes that have affected the evolution of major histocompatibility complex (MHC) genes across ruminant lineages based on available genomic data. The 51 species analyzed represented all six families of ruminants. Our finding indicated that the architecture of the MHC region is conserved in ruminants, but with variable copy numbers of MHC-I, MHC-IIA, and MHC-IIB genes. No lineage-specific gene duplication was observed in the MHC genes. The phylogenetic generalized least squares regression (PGLS) model revealed association between ecological and biological factors (habitat and lifespan) and gene duplication in DQA and DQB, but not in DRB. The selection pressure of DQA and DQB were related with lifespan, diet, and the ratio of genetic repeat elements. These results suggest that the MHC evolution in ruminants, including copy number and selection, has been influenced by genetic repeat elements, pathogen exposure risk, and intrinsic cost of possessing multiple MHC genes.
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Affiliation(s)
- Ke He
- College of Animal Science and Technology, College of Veterinary Medicine, Zhejiang Agriculture and Forestry University, Key Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Hangzhou, China
| | - Chunhong Liang
- College of Animal Science and Technology, College of Veterinary Medicine, Zhejiang Agriculture and Forestry University, Key Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Hangzhou, China
| | - Shujuan Ma
- Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, China
| | - Hongyi Liu
- College of Biology and the Environment, Nanjing Forestry University, Nanjing, China
| | - Ying Zhu
- Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, China.
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12
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Du X, Sun Y, Fu T, Gao T, Zhang T. Research Progress and Applications of Bovine Genome in the Tribe Bovini. Genes (Basel) 2024; 15:509. [PMID: 38674443 PMCID: PMC11050176 DOI: 10.3390/genes15040509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 04/16/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
Various bovine species have been domesticated and bred for thousands of years, and they provide adequate animal-derived products, including meat, milk, and leather, to meet human requirements. Despite the review studies on economic traits in cattle, the genetic basis of traits has only been partially explained by phenotype and pedigree breeding methods, due to the complexity of genomic regulation during animal development and growth. With the advent of next-generation sequencing technology, genomics projects, such as the 1000 Bull Genomes Project, Functional Annotation of Animal Genomes project, and Bovine Pangenome Consortium, have advanced bovine genomic research. These large-scale genomics projects gave us a comprehensive concept, technology, and public resources. In this review, we summarize the genomics research progress of the main bovine species during the past decade, including cattle (Bos taurus), yak (Bos grunniens), water buffalo (Bubalus bubalis), zebu (Bos indicus), and gayal (Bos frontalis). We mainly discuss the development of genome sequencing and functional annotation, focusing on how genomic analysis reveals genetic variation and its impact on phenotypes in several bovine species.
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Affiliation(s)
- Xingjie Du
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Yu Sun
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Tong Fu
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Tengyun Gao
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Tianliu Zhang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
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13
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Liu X, Zheng J, Ding J, Wu J, Zuo F, Zhang G. When Livestock Genomes Meet Third-Generation Sequencing Technology: From Opportunities to Applications. Genes (Basel) 2024; 15:245. [PMID: 38397234 PMCID: PMC10888458 DOI: 10.3390/genes15020245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 01/30/2024] [Accepted: 02/10/2024] [Indexed: 02/25/2024] Open
Abstract
Third-generation sequencing technology has found widespread application in the genomic, transcriptomic, and epigenetic research of both human and livestock genetics. This technology offers significant advantages in the sequencing of complex genomic regions, the identification of intricate structural variations, and the production of high-quality genomes. Its attributes, including long sequencing reads, obviation of PCR amplification, and direct determination of DNA/RNA, contribute to its efficacy. This review presents a comprehensive overview of third-generation sequencing technologies, exemplified by single-molecule real-time sequencing (SMRT) and Oxford Nanopore Technology (ONT). Emphasizing the research advancements in livestock genomics, the review delves into genome assembly, structural variation detection, transcriptome sequencing, and epigenetic investigations enabled by third-generation sequencing. A comprehensive analysis is conducted on the application and potential challenges of third-generation sequencing technology for genome detection in livestock. Beyond providing valuable insights into genome structure analysis and the identification of rare genes in livestock, the review ventures into an exploration of the genetic mechanisms underpinning exemplary traits. This review not only contributes to our understanding of the genomic landscape in livestock but also provides fresh perspectives for the advancement of research in this domain.
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Affiliation(s)
- Xinyue Liu
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Junyuan Zheng
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Jialan Ding
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Jiaxin Wu
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Fuyuan Zuo
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
- Beef Cattle Engineering and Technology Research Center of Chongqing, Southwest University, Rongchang, Chongqing 402460, China
| | - Gongwei Zhang
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
- Beef Cattle Engineering and Technology Research Center of Chongqing, Southwest University, Rongchang, Chongqing 402460, China
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14
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Lázaro SF, Tonhati H, Oliveira HR, Silva AA, Scalez DCB, Nascimento AV, Santos DJA, Stefani G, Carvalho IS, Sandoval AF, Brito LF. Genetic parameters and genome-wide association studies for mozzarella and milk production traits, lactation length, and lactation persistency in Murrah buffaloes. J Dairy Sci 2024; 107:992-1021. [PMID: 37730179 DOI: 10.3168/jds.2023-23284] [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: 01/18/2023] [Accepted: 08/30/2023] [Indexed: 09/22/2023]
Abstract
Genetic and genomic analyses of longitudinal traits related to milk production efficiency are paramount for optimizing water buffaloes breeding schemes. Therefore, this study aimed to (1) compare single-trait random regression models under a single-step genomic BLUP setting based on alternative covariance functions (i.e., Wood, Wilmink, and Ali and Schaeffer) to describe milk (MY), fat (FY), protein (PY), and mozzarella (MZY) yields, fat-to-protein ratio (FPR), somatic cell score (SCS), lactation length (LL), and lactation persistency (LP) in Murrah dairy buffaloes (Bubalus bubalis); (2) combine the best functions for each trait under a multiple-trait framework; (3) estimate time-dependent SNP effects for all the studied longitudinal traits; and (4) identify the most likely candidate genes associated with the traits. A total of 323,140 test-day records from the first lactation of 4,588 Murrah buffaloes were made available for the study. The model included the average curve of the population nested within herd-year-season of calving, systematic effects of number of milkings per day, and age at first calving as linear and quadratic covariates, and additive genetic, permanent environment, and residual as random effects. The Wood model had the best goodness of fit based on the deviance information criterion and posterior model probabilities for all traits. Moderate heritabilities were estimated over time for most traits (0.30 ± 0.02 for MY; 0.26 ± 0.03 for FY; 0.45 ± 0.04 for PY; 0.28 ± 0.05 for MZY; 0.13 ± 0.02 for FPR; and 0.15 ± 0.03 for SCS). The heritability estimates for LP ranged from 0.38 ± 0.02 to 0.65 ± 0.03 depending on the trait definition used. Similarly, heritabilities estimated for LL ranged from 0.10 ± 0.01 to 0.14 ± 0.03. The genetic correlation estimates across days in milk (DIM) for all traits ranged from -0.06 (186-215 DIM for MY-SCS) to 0.78 (66-95 DIM for PY-MZY). The SNP effects calculated for the random regression model coefficients were used to estimate the SNP effects throughout the lactation curve (from 5 to 305 d). Numerous relevant genomic regions and candidate genes were identified for all traits, confirming their polygenic nature. The candidate genes identified contribute to a better understanding of the genetic background of milk-related traits in Murrah buffaloes and reinforce the value of incorporating genomic information in their breeding programs.
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Affiliation(s)
- Sirlene F Lázaro
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907; Department of Animal Science, College of Agricultural and Veterinary Sciences, São Paulo State University (UNESP), Jaboticabal, 14884-900, SP, Brazil
| | - Humberto Tonhati
- Department of Animal Science, College of Agricultural and Veterinary Sciences, São Paulo State University (UNESP), Jaboticabal, 14884-900, SP, Brazil
| | - Hinayah R Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907; Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - Alessandra A Silva
- Department of Animal Science, College of Agricultural and Veterinary Sciences, São Paulo State University (UNESP), Jaboticabal, 14884-900, SP, Brazil
| | - Daiane C B Scalez
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - André V Nascimento
- Department of Animal Science, College of Agricultural and Veterinary Sciences, São Paulo State University (UNESP), Jaboticabal, 14884-900, SP, Brazil
| | | | - Gabriela Stefani
- Department of Animal Science, College of Agricultural and Veterinary Sciences, São Paulo State University (UNESP), Jaboticabal, 14884-900, SP, Brazil
| | - Isabella S Carvalho
- Department of Animal Science, College of Agricultural and Veterinary Sciences, São Paulo State University (UNESP), Jaboticabal, 14884-900, SP, Brazil
| | - Amanda F Sandoval
- Department of Animal Science, College of Agricultural and Veterinary Sciences, São Paulo State University (UNESP), Jaboticabal, 14884-900, SP, Brazil
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907.
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15
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Pineda PS, Flores EB, Villamor LP, Parac CJM, Khatkar MS, Thu HT, Smith TPL, Rosen BD, Ajmone-Marsan P, Colli L, Williams JL, Low WY. Disentangling river and swamp buffalo genetic diversity: initial insights from the 1000 Buffalo Genomes Project. Gigascience 2024; 13:giae053. [PMID: 39250077 PMCID: PMC11382405 DOI: 10.1093/gigascience/giae053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 06/04/2024] [Accepted: 07/12/2024] [Indexed: 09/10/2024] Open
Abstract
More people in the world depend on water buffalo for their livelihoods than on any other domesticated animals, but its genetics is still not extensively explored. The 1000 Buffalo Genomes Project (1000BGP) provides genetic resources for global buffalo population study and tools to breed more sustainable and productive buffaloes. Here we report the most contiguous swamp buffalo genome assembly (PCC_UOA_SB_1v2) with substantial resolution of telomeric and centromeric repeats, ∼4-fold more contiguous than the existing reference river buffalo assembly and exceeding a recently published male swamp buffalo genome. This assembly was used along with the current reference to align 140 water buffalo short-read sequences and produce a public genetic resource with an average of ∼41 million single nucleotide polymorphisms per swamp and river buffalo genome. Comparison of the swamp and river buffalo sequences showed ∼1.5% genetic differences, and estimated divergence time occurred 3.1 million years ago (95% CI, 2.6-4.9). The open science model employed in the 1000BGP provides a key genomic resource and tools for a species with global economic relevance.
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Affiliation(s)
- Paulene S Pineda
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA 5371, Australia
- Philippine Carabao Center National Headquarters and Genepool, Science City of Muñoz, Nueva Ecija 3120, Philippines
| | - Ester B Flores
- Philippine Carabao Center National Headquarters and Genepool, Science City of Muñoz, Nueva Ecija 3120, Philippines
| | - Lilian P Villamor
- Philippine Carabao Center National Headquarters and Genepool, Science City of Muñoz, Nueva Ecija 3120, Philippines
| | - Connie Joyce M Parac
- Philippine Carabao Center National Headquarters and Genepool, Science City of Muñoz, Nueva Ecija 3120, Philippines
| | - Mehar S Khatkar
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA 5371, Australia
| | - Hien To Thu
- Norwegian University of Life Sciences: NMBU, Universitetstunet 3, 1430 Ås, Norway
| | - Timothy P L Smith
- U.S. Meat Animal Research Center, USDA-ARS, Clay Center, NE 68933, USA
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD 20705, USA
| | - Paolo Ajmone-Marsan
- Department of Animal Science, Food and Nutrition, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy
| | - Licia Colli
- Department of Animal Science, Food and Nutrition, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy
| | - John L Williams
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA 5371, Australia
- Department of Animal Science, Food and Nutrition, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy
| | - Wai Yee Low
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA 5371, Australia
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16
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Kwon D, Park N, Wy S, Lee D, Chai HH, Cho IC, Lee J, Kwon K, Kim H, Moon Y, Kim J, Park W, Kim J. A chromosome-level genome assembly of the Korean crossbred pig Nanchukmacdon (Sus scrofa). Sci Data 2023; 10:761. [PMID: 37923776 PMCID: PMC10624824 DOI: 10.1038/s41597-023-02661-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 10/17/2023] [Indexed: 11/06/2023] Open
Abstract
As plentiful high-quality genome assemblies have been accumulated, reference-guided genome assembly can be a good approach to reconstruct a high-quality assembly. Here, we present a chromosome-level genome assembly of the Korean crossbred pig called Nanchukmacdon (the NCMD assembly) using the reference-guided assembly approach with short and long reads. The NCMD assembly contains 20 chromosome-level scaffolds with a total size of 2.38 Gbp (N50: 138.77 Mbp). Its BUSCO score is 93.1%, which is comparable to the pig reference assembly, and a total of 20,588 protein-coding genes, 8,651 non-coding genes, and 996.14 Mbp of repetitive elements are annotated. The NCMD assembly was also used to close many gaps in the pig reference assembly. This NCMD assembly and annotation provide foundational resources for the genomic analyses of pig and related species.
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Affiliation(s)
- Daehong Kwon
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Nayoung Park
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Suyeon Wy
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Daehwan Lee
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Han-Ha Chai
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju, 55365, Republic of Korea
| | - In-Cheol Cho
- Subtropical Livestock Research Institute, National Institute of Animal Science, RDA, Jeju, 63242, Republic of Korea
| | - Jongin Lee
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Kisang Kwon
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Heesun Kim
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Youngbeen Moon
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Juyeon Kim
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Woncheoul Park
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju, 55365, Republic of Korea.
| | - Jaebum Kim
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea.
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17
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Saravanan KA, Panigrahi M, Kumar H, Nayak SS, Rajawat D, Bhushan B, Dutt T. Progress and future perspectives of livestock genomics in India: a mini review. Anim Biotechnol 2023; 34:1979-1987. [PMID: 35369840 DOI: 10.1080/10495398.2022.2056046] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
The field of genetics has evolved a lot after the emergence of molecular and advanced genomic technologies. The advent of Next Generation Sequencing, SNP genotyping platforms and simultaneous reduction in the cost of sequencing had opened the door to genomic research in farm animals. There are various applications of genomics in livestock, such as the use of genomic data: (i) to investigate genetic diversity and breed composition/population structure (ii) to identify genetic variants and QTLs related to economically important and ecological traits, genome-wide association studies (GWAS) and genomic signatures of selection; (iii) to enhance breeding programs by genomic selection. Compared to traditional methods, genomic selection is expected to improve selection response by increasing selection accuracy and reducing the generation interval due to early selection. Genomic selection (GS) in developed countries has led to rapid genetic gains, especially in dairy cattle, due to a well-established genetic evaluation system. Indian livestock system is still lagging behind developed nations in adopting these technologies. This review discusses the current status, challenges, and future perspectives of livestock genomics in India.
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Affiliation(s)
- K A Saravanan
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, UP, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, UP, India
| | - Harshit Kumar
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, UP, India
| | - Sonali Sonejita Nayak
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, UP, India
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, UP, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, UP, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Bareilly, UP, India
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18
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Li TT, Xia T, Wu JQ, Hong H, Sun ZL, Wang M, Ding FR, Wang J, Jiang S, Li J, Pan J, Yang G, Feng JN, Dai YP, Zhang XM, Zhou T, Li T. De novo genome assembly depicts the immune genomic characteristics of cattle. Nat Commun 2023; 14:6601. [PMID: 37857610 PMCID: PMC10587341 DOI: 10.1038/s41467-023-42161-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 09/30/2023] [Indexed: 10/21/2023] Open
Abstract
Immunogenomic loci remain poorly understood because of their genetic complexity and size. Here, we report the de novo assembly of a cattle genome and provide a detailed annotation of the immunogenomic loci. The assembled genome contains 143 contigs (N50 ~ 74.0 Mb). In contrast to the current reference genome (ARS-UCD1.2), 156 gaps are closed and 467 scaffolds are located in our assembly. Importantly, the immunogenomic regions, including three immunoglobulin (IG) loci, four T-cell receptor (TR) loci, and the major histocompatibility complex (MHC) locus, are seamlessly assembled and precisely annotated. With the characterization of 258 IG genes and 657 TR genes distributed across seven genomic loci, we present a detailed depiction of immune gene diversity in cattle. Moreover, the MHC gene structures are integrally revealed with properly phased haplotypes. Together, our work describes a more complete cattle genome, and provides a comprehensive view of its complex immune-genome.
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Affiliation(s)
- Ting-Ting Li
- Nanhu Laboratory, National Center of Biomedical Analysis, Beijing, 100850, China
| | - Tian Xia
- Nanhu Laboratory, National Center of Biomedical Analysis, Beijing, 100850, China
| | - Jia-Qi Wu
- Nanhu Laboratory, National Center of Biomedical Analysis, Beijing, 100850, China
| | - Hao Hong
- Nanhu Laboratory, National Center of Biomedical Analysis, Beijing, 100850, China
| | - Zhao-Lin Sun
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing, 100850, China
| | - Ming Wang
- State Key Laboratories for Agrobiotechnology, College of Biological Sciences, China Agricultural University, No.2 Yuanmingyuan Xilu, Beijing, 100193, China
- College of Animal Science and Technology, China Agricultural University, No.2 Yuanmingyuan Xilu, Beijing, 100193, China
| | - Fang-Rong Ding
- State Key Laboratories for Agrobiotechnology, College of Biological Sciences, China Agricultural University, No.2 Yuanmingyuan Xilu, Beijing, 100193, China
| | - Jing Wang
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing, 100850, China
| | - Shuai Jiang
- Nanhu Laboratory, National Center of Biomedical Analysis, Beijing, 100850, China
| | - Jin Li
- Nanhu Laboratory, National Center of Biomedical Analysis, Beijing, 100850, China
| | - Jie Pan
- Nanhu Laboratory, National Center of Biomedical Analysis, Beijing, 100850, China
| | - Guang Yang
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing, 100850, China
| | - Jian-Nan Feng
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing, 100850, China
| | - Yun-Ping Dai
- State Key Laboratories for Agrobiotechnology, College of Biological Sciences, China Agricultural University, No.2 Yuanmingyuan Xilu, Beijing, 100193, China
| | - Xue-Min Zhang
- Nanhu Laboratory, National Center of Biomedical Analysis, Beijing, 100850, China
- School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China
| | - Tao Zhou
- Nanhu Laboratory, National Center of Biomedical Analysis, Beijing, 100850, China.
| | - Tao Li
- Nanhu Laboratory, National Center of Biomedical Analysis, Beijing, 100850, China.
- School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China.
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19
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Triant DA, Walsh AT, Hartley GA, Petry B, Stegemiller MR, Nelson BM, McKendrick MM, Fuller EP, Cockett NE, Koltes JE, McKay SD, Green JA, Murdoch BM, Hagen DE, Elsik CG. AgAnimalGenomes: browsers for viewing and manually annotating farm animal genomes. Mamm Genome 2023; 34:418-436. [PMID: 37460664 PMCID: PMC10382368 DOI: 10.1007/s00335-023-10008-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 06/29/2023] [Indexed: 07/30/2023]
Abstract
Current genome sequencing technologies have made it possible to generate highly contiguous genome assemblies for non-model animal species. Despite advances in genome assembly methods, there is still room for improvement in the delineation of specific gene features in the genomes. Here we present genome visualization and annotation tools to support seven livestock species (bovine, chicken, goat, horse, pig, sheep, and water buffalo), available in a new resource called AgAnimalGenomes. In addition to supporting the manual refinement of gene models, these browsers provide visualization tracks for hundreds of RNAseq experiments, as well as data generated by the Functional Annotation of Animal Genomes (FAANG) Consortium. For species with predicted gene sets from both Ensembl and RefSeq, the browsers provide special tracks showing the thousands of protein-coding genes that disagree across the two gene sources, serving as a valuable resource to alert researchers to gene model issues that may affect data interpretation. We describe the data and search methods available in the new genome browsers and how to use the provided tools to edit and create new gene models.
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Affiliation(s)
- Deborah A Triant
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA
| | - Amy T Walsh
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA
| | - Gabrielle A Hartley
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, 06269, USA
| | - Bruna Petry
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - Morgan R Stegemiller
- Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, ID, 83844, USA
| | - Benjamin M Nelson
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA
| | - Makenna M McKendrick
- Department of Animal and Food Sciences, Oklahoma State University, Stillwater, OK, 74078, USA
| | - Emily P Fuller
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, 06269, USA
| | - Noelle E Cockett
- Department of Animal, Dairy, and Veterinary Sciences, Utah State University, Logan, UT, 84322, USA
| | - James E Koltes
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - Stephanie D McKay
- Department of Animal and Veterinary Sciences, University of Vermont, Burlington, VT, 05405, USA
| | - Jonathan A Green
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA
| | - Brenda M Murdoch
- Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, ID, 83844, USA
| | - Darren E Hagen
- Department of Animal and Food Sciences, Oklahoma State University, Stillwater, OK, 74078, USA
| | - Christine G Elsik
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA.
- Division of Plant Science & Technology, University of Missouri, Columbia, MO, 65211, USA.
- Institute for Data Science & Informatics, University of Missouri, Columbia, MO, 65211, USA.
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20
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Marcotuli I, Mandrone M, Chiocchio I, Poli F, Gadaleta A, Ferrara G. Metabolomics and genetics of reproductive bud development in Ficus carica var. sativa (edible fig) and in Ficus carica var. caprificus (caprifig): similarities and differences. FRONTIERS IN PLANT SCIENCE 2023; 14:1192350. [PMID: 37360723 PMCID: PMC10285451 DOI: 10.3389/fpls.2023.1192350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 04/28/2023] [Indexed: 06/28/2023]
Abstract
In figs, reproductive biology comprises cultivars requiring or not pollination, with female trees (edible fig) and male trees (caprifig) bearing different types of fruits. Metabolomic and genetic studies may clarify bud differentiation mechanisms behind the different fruits. We used a targeted metabolomic analysis and genetic investigation through RNA sequence and candidate gene investigation to perform a deep analysis of buds of two fig cultivars, 'Petrelli' (San Pedro type) and 'Dottato' (Common type), and one caprifig. In this work, proton nuclear magnetic resonance (1H NMR-based metabolomics) has been used to analyze and compare buds of the caprifig and the two fig cultivars collected at different times of the season. Metabolomic data of buds collected on the caprifig, 'Petrelli', and 'Dottato' were treated individually, building three separate orthogonal partial least squared (OPLS) models, using the "y" variable as the sampling time to allow the identification of the correlations among metabolomic profiles of buds. The sampling times revealed different patterns between caprifig and the two edible fig cultivars. A significant amount of glucose and fructose was found in 'Petrelli', differently from 'Dottato', in the buds in June, suggesting that these sugars not only are used by the ripening brebas of 'Petrelli' but also are directed toward the developing buds on the current year shoot for either a main crop (fruit in the current season) or a breba (fruit in the successive season). Genetic characterization through the RNA-seq of buds and comparison with the literature allowed the identification of 473 downregulated genes, with 22 only in profichi, and 391 upregulated genes, with 21 only in mammoni.
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Affiliation(s)
- Ilaria Marcotuli
- Department of Soil, Plant and Food Sciences, University of Bari “Aldo Moro”, Bari, Italy
| | - Manuela Mandrone
- Dipartimento di Farmacia e Biotecnologie, Alma Mater Studiorum - Università di Bologna, Bologna, Italy
| | - Ilaria Chiocchio
- Dipartimento di Farmacia e Biotecnologie, Alma Mater Studiorum - Università di Bologna, Bologna, Italy
| | - Ferruccio Poli
- Dipartimento di Farmacia e Biotecnologie, Alma Mater Studiorum - Università di Bologna, Bologna, Italy
| | - Agata Gadaleta
- Department of Soil, Plant and Food Sciences, University of Bari “Aldo Moro”, Bari, Italy
| | - Giuseppe Ferrara
- Department of Soil, Plant and Food Sciences, University of Bari “Aldo Moro”, Bari, Italy
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21
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Galbraith JD, Hayward A. The influence of transposable elements on animal colouration. Trends Genet 2023:S0168-9525(23)00091-4. [PMID: 37183153 DOI: 10.1016/j.tig.2023.04.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 04/17/2023] [Accepted: 04/19/2023] [Indexed: 05/16/2023]
Abstract
Transposable elements (TEs) are mobile genetic sequences present within host genomes. TEs can contribute to the evolution of host traits, since transposition is mutagenic and TEs often contain host regulatory and protein coding sequences. We review cases where TEs influence animal colouration, reporting major patterns and outstanding questions. TE-induced colouration phenotypes typically arise via introduction of novel regulatory sequences and splice sites, affecting pigment cell development or pigment synthesis. We discuss if particular TE types may be more frequently involved in the evolution of colour variation in animals, given that examples involving long terminal repeat (LTR) elements appear to dominate. Currently, examples of TE-induced colouration phenotypes in animals mainly concern model and domesticated insect and mammal species. However, several influential recent examples, coupled with increases in genome sequencing, suggest cases reported from wild species will increase considerably.
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Affiliation(s)
- James D Galbraith
- Faculty of Environment, Science and Economy, University of Exeter, Cornwall TR10 9FE, UK.
| | - Alexander Hayward
- Faculty of Environment, Science and Economy, University of Exeter, Cornwall TR10 9FE, UK.
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22
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Si J, Dai D, Li K, Fang L, Zhang Y. A Multi-Tissue Gene Expression Atlas of Water Buffalo ( Bubalus bubalis) Reveals Transcriptome Conservation between Buffalo and Cattle. Genes (Basel) 2023; 14:890. [PMID: 37107649 PMCID: PMC10137413 DOI: 10.3390/genes14040890] [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: 03/22/2023] [Revised: 04/04/2023] [Accepted: 04/07/2023] [Indexed: 04/29/2023] Open
Abstract
We generated 73 transcriptomic data of water buffalo, which were integrated with publicly available data in this species, yielding a large dataset of 355 samples representing 20 major tissue categories. We established a multi-tissue gene expression atlas of water buffalo. Furthermore, by comparing them with 4866 cattle transcriptomic data from the cattle genotype-tissue expression atlas (CattleGTEx), we found that the transcriptomes of the two species exhibited conservation in their overall gene expression patterns, tissue-specific gene expression and house-keeping gene expression. We further identified conserved and divergent expression genes between the two species, with the largest number of differentially expressed genes found in the skin, which may be related to structural and functional differences in the skin of the two species. This work provides a source of functional annotation of the buffalo genome and lays the foundations for future genetic and evolutionary studies in water buffalo.
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Affiliation(s)
- Jingfang Si
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (J.S.); (D.D.); (K.L.)
| | - Dongmei Dai
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (J.S.); (D.D.); (K.L.)
| | - Kun Li
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (J.S.); (D.D.); (K.L.)
| | - Lingzhao Fang
- The Center for Quantitative Genetics and Genomics (QGG), Aarhus University, 11, 8000 Aarhus, Denmark
| | - Yi Zhang
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (J.S.); (D.D.); (K.L.)
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23
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Yang L, Han J, Deng T, Li F, Han X, Xia H, Quan F, Hua G, Yang L, Zhou Y. Comparative analyses of copy number variations between swamp buffaloes and river buffaloes. Anim Genet 2023; 54:199-206. [PMID: 36683294 DOI: 10.1111/age.13288] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 11/24/2022] [Accepted: 12/12/2022] [Indexed: 01/24/2023]
Abstract
As an important source of genomic variation, copy number variation (CNV) contributes to environmental adaptation in worldwide buffaloes. Despite this importance, CNV divergence between swamp buffaloes and river buffaloes has not been studied previously. Here, we report 21 152 CNV regions (CNVRs) in 141 buffaloes of 20 breeds detected through multiple CNV calling strategies. Only 248 CNVRs were shared between river buffalo and swamp buffalo, reflecting great variation of CNVRs between the two subspecies. Population structure analysis based on CNVs successfully separated the two buffalo subspecies. We further assessed CNV divergence by calculating FST for genome-wide CNVs. Totally, we identified 110 significantly divergent CNV segments and 44 putatively selected genes between river buffaloes and swamp buffaloes. In particular, LALBA, a key gene controlling milk production in cattle, presented a highly differentiated CNV in the promoter region, which makes it a strong functional candidate gene for differences between swamp buffaloes and river buffaloes in traits related to milk production. Our study provides useful information of CNVs in buffaloes, which may help explain the genetic differences between the two subspecies.
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Affiliation(s)
- Lv Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China.,National Center for International Research on Animal Genetics, Breeding and Reproduction (NCIRAGBR), Frontiers Science Center for Animal Breeding and Sustainable Production, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Jiazheng Han
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China.,National Center for International Research on Animal Genetics, Breeding and Reproduction (NCIRAGBR), Frontiers Science Center for Animal Breeding and Sustainable Production, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Tingxian Deng
- Guangxi Provincial Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning, China
| | - Fan Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China.,National Center for International Research on Animal Genetics, Breeding and Reproduction (NCIRAGBR), Frontiers Science Center for Animal Breeding and Sustainable Production, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Xiaotao Han
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China.,National Center for International Research on Animal Genetics, Breeding and Reproduction (NCIRAGBR), Frontiers Science Center for Animal Breeding and Sustainable Production, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Han Xia
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China.,National Center for International Research on Animal Genetics, Breeding and Reproduction (NCIRAGBR), Frontiers Science Center for Animal Breeding and Sustainable Production, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Fanfan Quan
- Livestock and Poultry Breeding Center of Hubei Province, Wuhan, China
| | - Guohua Hua
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China.,National Center for International Research on Animal Genetics, Breeding and Reproduction (NCIRAGBR), Frontiers Science Center for Animal Breeding and Sustainable Production, Huazhong Agricultural University, Wuhan, Hubei, China.,Hubei Province's Engineering Research Center in Buffalo Breeding and Products, Wuhan, China
| | - Liguo Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China.,National Center for International Research on Animal Genetics, Breeding and Reproduction (NCIRAGBR), Frontiers Science Center for Animal Breeding and Sustainable Production, Huazhong Agricultural University, Wuhan, Hubei, China.,Hubei Province's Engineering Research Center in Buffalo Breeding and Products, Wuhan, China
| | - Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China.,National Center for International Research on Animal Genetics, Breeding and Reproduction (NCIRAGBR), Frontiers Science Center for Animal Breeding and Sustainable Production, Huazhong Agricultural University, Wuhan, Hubei, China.,Hubei Province's Engineering Research Center in Buffalo Breeding and Products, Wuhan, China
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24
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Jiang YF, Wang S, Wang CL, Xu RH, Wang WW, Jiang Y, Wang MS, Jiang L, Dai LH, Wang JR, Chu XH, Zeng YQ, Fang LZ, Wu DD, Zhang Q, Ding XD. Pangenome obtained by long-read sequencing of 11 genomes reveal hidden functional structural variants in pigs. iScience 2023; 26:106119. [PMID: 36852268 PMCID: PMC9958381 DOI: 10.1016/j.isci.2023.106119] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 12/21/2022] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
Long-read sequencing (LRS) facilitates both the genome assembly and the discovery of structural variants (SVs). Here, we built a graph-based pig pangenome by incorporating 11 LRS genomes with an average of 94.01% BUSCO completeness score, revealing 206-Mb novel sequences. We discovered 183,352 nonredundant SVs (63% novel), representing 12.12% of the reference genome. By genotyping SVs in an additional 196 short-read sequencing samples, we identified thousands of population stratified SVs. Particularly, we detected 7,568 Tibetan specific SVs, some of which demonstrate significant population differentiation between Tibetan and low-altitude pigs, which might be associated with the high-altitude hypoxia adaptation in Tibetan pigs. Further integrating functional genomic data, the most promising candidate genes within the SVs that might contribute to the high-altitude hypoxia adaptation were discovered. Overall, our study generates a benchmark pangenome resource for illustrating the important roles of SVs in adaptive evolution, domestication, and genetic improvement of agronomic traits in pigs.
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Affiliation(s)
- Yi-Fan Jiang
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Sheng Wang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Chong-Long Wang
- Key Laboratory of Pig Molecular Quantitative Genetics of Anhui Academy of Agricultural Sciences, Anhui Provincial Key Laboratory of Livestock and Poultry Product Safety Engineering, Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei 230031, China
| | - Ru-Hai Xu
- Key Laboratory of Animal Genetics and Breeding of Zhejiang Province, Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
| | - Wen-Wen Wang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Taian 271001, China
| | - Yao Jiang
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
- Key Laboratory of Pig Molecular Quantitative Genetics of Anhui Academy of Agricultural Sciences, Anhui Provincial Key Laboratory of Livestock and Poultry Product Safety Engineering, Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei 230031, China
| | - Ming-Shan Wang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Li Jiang
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Li-He Dai
- Key Laboratory of Animal Genetics and Breeding of Zhejiang Province, Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
| | - Jie-Ru Wang
- Key Laboratory of Pig Molecular Quantitative Genetics of Anhui Academy of Agricultural Sciences, Anhui Provincial Key Laboratory of Livestock and Poultry Product Safety Engineering, Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei 230031, China
| | - Xiao-Hong Chu
- Key Laboratory of Animal Genetics and Breeding of Zhejiang Province, Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
| | - Yong-Qing Zeng
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Taian 271001, China
| | - Ling-Zhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, 8000, Denmark
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Qin Zhang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Taian 271001, China
| | - Xiang-Dong Ding
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
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25
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Wang X, Li Z, Feng T, Luo X, Xue L, Mao C, Cui K, Li H, Huang J, Huang K, Rehman SU, Shi D, Wu D, Ruan J, Liu Q. Chromosome-level genome and recombination map of the male buffalo. Gigascience 2022; 12:giad063. [PMID: 37589307 PMCID: PMC10433102 DOI: 10.1093/gigascience/giad063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 03/20/2023] [Accepted: 07/13/2023] [Indexed: 08/18/2023] Open
Abstract
BACKGROUND The swamp buffalo (Bubalus bubalis carabanesis) is an economically important livestock supplying milk, meat, leather, and draft power. Several female buffalo genomes have been available, but the lack of high-quality male genomes hinders studies on chromosome evolution, especially Y, as well as meiotic recombination. RESULTS Here, a chromosome-level genome with a contig N50 of 72.2 Mb and a fine-scale recombination map of male buffalo were reported. We found that transposable elements (TEs) and structural variants (SVs) may contribute to buffalo evolution by influencing adjacent gene expression. We further found that the pseudoautosomal region (PAR) of the Y chromosome is subject to stronger purification selection. The meiotic recombination map showed that there were 2 obvious recombination hotspots on chromosome 8, and the genes around them were mainly related to tooth development, which may have helped to enhance the adaption of buffalo to inferior feed. Among several genomic features, TE density has the strongest correlation with recombination rates. Moreover, the TE subfamily, SINE/tRNA, is likely to play a role in driving recombination into SVs. CONCLUSIONS The male genome and sperm sequencing will facilitate the understanding of the buffalo genomic evolution and functional research.
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Affiliation(s)
- Xiaobo Wang
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
- 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 518120, China
| | - Zhipeng Li
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Tong Feng
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Xier Luo
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Lintao Xue
- Reproductive Medical and Genetic Center, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi 530021, China
| | - Chonghui Mao
- 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 518120, China
| | - Kuiqing Cui
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Hui Li
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Jieping Huang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Kongwei Huang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Saif-ur Rehman
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Deshun Shi
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Dongdong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Jue Ruan
- 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 518120, China
| | - Qingyou Liu
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
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26
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Karimi K, Do DN, Wang J, Easley J, Borzouie S, Sargolzaei M, Plastow G, Wang Z, Miar Y. A chromosome-level genome assembly reveals genomic characteristics of the American mink (Neogale vison). Commun Biol 2022; 5:1381. [PMID: 36526733 PMCID: PMC9757699 DOI: 10.1038/s42003-022-04341-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 12/05/2022] [Indexed: 12/23/2022] Open
Abstract
Availability of a contiguous chromosome-level genome assembly is the foundational step to develop genome-based studies in American mink (Neogale vison). The main objective of this study was to provide a high quality chromosome-level genome assembly for American mink. An initial draft of the genome assembly was generated using 2,884,047 PacBio long reads. Integration of Hi-C data into the initial draft led to an assembly with 183 scaffolds and scaffold N50 of 220 Mb. This gap-free genome assembly of American mink (ASM_NN_V1) had a length of 2.68 Gb in which about 98.6% of the whole genome was covered by 15 chromosomes. In total, 25,377 genes were predicted across the American mink genome using the NCBI Eukaryotic Genome Annotation Pipeline. In addition, gene orthology, demographic history, synteny blocks, and phylogenetic relationships were studied in connection with the genomes of other related Carnivora. Furthermore, population-based statistics of 100 sequenced mink were presented using the newly assembled genome. Remarkable improvements were observed in genome contiguity, the number of scaffolds, and annotation compared to the first draft of mink genome assembly (NNQGG.v01). This high-quality genome assembly will support the development of efficient breeding strategies as well as conservation programs for American mink.
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Affiliation(s)
- Karim Karimi
- grid.55602.340000 0004 1936 8200Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS Canada
| | - Duy Ngoc Do
- grid.55602.340000 0004 1936 8200Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS Canada
| | - Jingy Wang
- grid.55602.340000 0004 1936 8200Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS Canada
| | - John Easley
- Joint Mink Research Committee, Fur Commission USA, Preston, ID USA ,Mink Veterinary Consulting and Research Service, Plymouth, WI USA
| | - Shima Borzouie
- grid.55602.340000 0004 1936 8200Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS Canada
| | - Mehdi Sargolzaei
- grid.34429.380000 0004 1936 8198Department of Pathobiology, University of Guelph, Guelph, ON Canada ,Select Sires Inc., Plain City, OH USA
| | - Graham Plastow
- grid.17089.370000 0001 2190 316XLivestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB Canada
| | - Zhiquan Wang
- grid.17089.370000 0001 2190 316XLivestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB Canada
| | - Younes Miar
- grid.55602.340000 0004 1936 8200Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS Canada
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27
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Xiaobo W, Hassan FU, Liu S, Yang S, Ahmad M, Ahmed I, Huang K, Iqbal HMN, Yu H, Liu Q, Rehman SU. De Novo Transcriptome Dataset Generation of the Swamp Buffalo Brain and Non-Brain Tissues. BIOMED RESEARCH INTERNATIONAL 2022; 2022:4472940. [PMID: 36408285 PMCID: PMC9668446 DOI: 10.1155/2022/4472940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 09/23/2022] [Indexed: 12/02/2022]
Abstract
The sequenced data availability opened new horizons related to buffalo genetic control of economic traits and genomic diversity. The visceral organs (brain, liver, etc.) significantly involved in energy metabolism, docility, or social interactions. We performed swamp buffalo transcriptomic profiling of 24 different tissues (brain and non-brain) to identify novel transcripts and analyzed the differentially expressed genes (DEGs) of brain vs. non-brain tissues with their functional annotation. We obtained 178.57 Gb clean transcriptomic data with GC contents 52.77%, reference genome alignment 95.36%, exonic coverage 88.49%. Totally, 26363 mRNAs transcripts including 5574 novel genes were obtained. Further, 7194 transcripts were detected as DEGs by comparing brain vs. non-brain tissues group, of which 3,999 were upregulated and 3,195 downregulated. These DEGs were functionally associated with cellular metabolic activities, signal transduction, cytoprotection, and structural and binding activities. The related functional pathways included cancer pathway, PI3k-Akt signaling, axon guidance, JAK-STAT signaling, basic cellular metabolism, thermogenesis, and oxidative phosphorylation. Our study provides an in-depth understanding of swamp buffalo transcriptomic data including DEGs potentially involved in basic cellular activities and development that helped to maintain their working capacity and social interaction with humans, and also, helpful to disclose the genetic architecture of different phenotypic traits and their gene expression regulation.
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Affiliation(s)
- Wang Xiaobo
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Faiz-ul Hassan
- Institute of Animal and Dairy Sciences, Faculty of Animal Husbandry, University of Agriculture, Faisalabad 38040, Pakistan
| | - Sheng Liu
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Shuli Yang
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Muhammad Ahmad
- Faculty of Veterinary Sciences, Shaheed Benazir Bhutto University of Veterinary and Animal Sciences (SBBUVAS), Sakrand 67210, Pakistan
| | - Ishtiaq Ahmed
- Department of Regional Science Operations, La Trobe Rural Health School, Albury-Wodonga, Victoria 3690, Australia
| | - Kongwei Huang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Hafiz M. N. Iqbal
- Tecnológico de Monterrey, School of Engineering and Sciences, Monterrey 64849, Mexico
| | - Hui Yu
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Qingyou Liu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Saif ur Rehman
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
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28
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Zhao R, Talenti A, Fang L, Liu S, Liu G, Chue Hong NP, Tenesa A, Hassan M, Prendergast JGD. The conservation of human functional variants and their effects across livestock species. Commun Biol 2022; 5:1003. [PMID: 36131008 PMCID: PMC9492664 DOI: 10.1038/s42003-022-03961-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 09/07/2022] [Indexed: 11/24/2022] Open
Abstract
Despite the clear potential of livestock models of human functional variants to provide important insights into the biological mechanisms driving human diseases and traits, their use to date has been limited. Generating such models via genome editing is costly and time consuming, and it is unclear which variants will have conserved effects across species. In this study we address these issues by studying naturally occurring livestock models of human functional variants. We show that orthologues of over 1.6 million human variants are already segregating in domesticated mammalian species, including several hundred previously directly linked to human traits and diseases. Models of variants linked to particular phenotypes, including metabolomic disorders and height, are preferentially shared across species, meaning studying the genetic basis of these phenotypes is particularly tractable in livestock. Using machine learning we demonstrate it is possible to identify human variants that are more likely to have an existing livestock orthologue, and, importantly, we show that the effects of functional variants are often conserved in livestock, acting on orthologous genes with the same direction of effect. Consequently, this work demonstrates the substantial potential of naturally occurring livestock carriers of orthologues of human functional variants to disentangle their functional impacts. An investigation of genetic variants that exist across human and livestock species supports the clear potential of livestock models in providing insights into the mechanisms driving human diseases and traits.
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Affiliation(s)
- Rongrong Zhao
- The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - Andrea Talenti
- The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - Lingzhao Fang
- The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - Shuli Liu
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, 310024, China
| | - George Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, Agricultural Research Service, USDA, Beltsville, Maryland, 20705, USA
| | | | - Albert Tenesa
- The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - Musa Hassan
- The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - James G D Prendergast
- The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK.
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29
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Porrelli S, Gerbault-Seureau M, Rozzi R, Chikhi R, Curaudeau M, Ropiquet A, Hassanin A. Draft genome of the lowland anoa ( Bubalus depressicornis) and comparison with buffalo genome assemblies (Bovidae, Bubalina). G3 GENES|GENOMES|GENETICS 2022; 12:6701968. [PMID: 36111873 PMCID: PMC9635665 DOI: 10.1093/g3journal/jkac234] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 08/11/2022] [Indexed: 11/24/2022]
Abstract
Genomic data for wild species of the genus Bubalus (Asian buffaloes) are still lacking while several whole genomes are currently available for domestic water buffaloes. To address this, we sequenced the genome of a wild endangered dwarf buffalo, the lowland anoa (Bubalus depressicornis), produced a draft genome assembly and made comparison to published buffalo genomes. The lowland anoa genome assembly was 2.56 Gbp long and contained 103,135 contigs, the longest contig being 337.39 kbp long. N50 and L50 values were 38.73 and 19.83 kbp, respectively, mean coverage was 44× and GC content was 41.74%. Two strategies were adopted to evaluate genome completeness: (1) determination of genomic features with de novo and homology-based predictions using annotations of chromosome-level genome assembly of the river buffalo and (2) employment of benchmarking against universal single-copy orthologs (BUSCO). Homology-based predictions identified 94.51% complete and 3.65% partial genomic features. De novo gene predictions identified 32,393 genes, representing 97.14% of the reference’s annotated genes, whilst BUSCO search against the mammalian orthologs database identified 71.1% complete, 11.7% fragmented, and 17.2% missing orthologs, indicating a good level of completeness for downstream analyses. Repeat analyses indicated that the lowland anoa genome contains 42.12% of repetitive regions. The genome assembly of the lowland anoa is expected to contribute to comparative genome analyses among bovid species.
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Affiliation(s)
- Stefano Porrelli
- Department of Natural Sciences, Faculty of Science and Technology, Middlesex University , London NW4 4BT, UK
| | - Michèle Gerbault-Seureau
- Institut Systématique Evolution Biodiversité (ISYEB), Sorbonne Université, MNHN, CNRS, EPHE , UA, 75005 Paris, France
| | - Roberto Rozzi
- Museum für Naturkunde, Leibniz-Institut für Evolutions- und Biodiversitätsforschung , 10115 Berlin, Germany
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig , Germany
| | - Rayan Chikhi
- Institut Pasteur, Université Paris Cité, Sequence Bioinformatics , 75015 Paris, France
| | - Manon Curaudeau
- Institut Systématique Evolution Biodiversité (ISYEB), Sorbonne Université, MNHN, CNRS, EPHE , UA, 75005 Paris, France
| | - Anne Ropiquet
- Department of Natural Sciences, Faculty of Science and Technology, Middlesex University , London NW4 4BT, UK
| | - Alexandre Hassanin
- Institut Systématique Evolution Biodiversité (ISYEB), Sorbonne Université, MNHN, CNRS, EPHE , UA, 75005 Paris, France
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30
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Long read genome assemblies complemented by single cell RNA-sequencing reveal genetic and cellular mechanisms underlying the adaptive evolution of yak. Nat Commun 2022; 13:4887. [PMID: 36068211 PMCID: PMC9448747 DOI: 10.1038/s41467-022-32164-9] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 07/20/2022] [Indexed: 12/04/2022] Open
Abstract
Wild yak (Bos mutus) and domestic yak (Bos grunniens) are adapted to high altitude environment and have ecological, economic, and cultural significances on the Qinghai-Tibetan Plateau (QTP). Currently, the genetic and cellular bases underlying adaptations of yak to extreme conditions remains elusive. In the present study, we assembled two chromosome-level genomes, one each for wild yak and domestic yak, and screened structural variants (SVs) through the long-read data of yak and taurine cattle. The results revealed that 6733 genes contained high-FST SVs. 127 genes carrying special type of SVs were differentially expressed in lungs of the taurine cattle and yak. We then constructed the first single-cell gene expression atlas of yak and taurine cattle lung tissues and identified a yak-specific endothelial cell subtype. By integrating SVs and single-cell transcriptome data, we revealed that the endothelial cells expressed the highest proportion of marker genes carrying high-FST SVs in taurine cattle lungs. Furthermore, we identified pathways which were related to the medial thickness and formation of elastic fibers in yak lungs. These findings provide new insights into the high-altitude adaptation of yak and have important implications for understanding the physiological and pathological responses of large mammals and humans to hypoxia. The genetic bases of yak adaptations to extreme conditions remains elusive. This study compares yak and cattle at a genomic and transcriptomic level, revealing a new type of endothelial cell and candidate genes related with elastic fiber formation in yak lungs that might contribute to high altitude adaptation.
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31
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Xiang Z, Li J, Lu D, Wei X, Xu X. Advances in multi-omics research on viral hepatitis. Front Microbiol 2022; 13:987324. [PMID: 36118247 PMCID: PMC9478034 DOI: 10.3389/fmicb.2022.987324] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 08/11/2022] [Indexed: 11/13/2022] Open
Abstract
Viral hepatitis is a major global public health problem that affects hundreds of millions of people and is associated with significant morbidity and mortality. Five biologically unrelated hepatotropic viruses account for the majority of the global burden of viral hepatitis, including hepatitis A virus (HAV), hepatitis B virus (HBV), hepatitis C virus (HCV), hepatitis D virus (HDV), and hepatitis E virus (HEV). Omics is defined as the comprehensive study of the functions, relationships and roles of various types of molecules in biological cells. The multi-omics analysis has been proposed and considered key to advancing clinical precision medicine, mainly including genomics, transcriptomics and proteomics, metabolomics. Overall, the applications of multi-omics can show the origin of hepatitis viruses, explore the diagnostic and prognostics biomarkers and screen out the therapeutic targets for viral hepatitis and related diseases. To better understand the pathogenesis of viral hepatitis and related diseases, comprehensive multi-omics analysis has been widely carried out. This review mainly summarizes the applications of multi-omics in different types of viral hepatitis and related diseases, aiming to provide new insight into these diseases.
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Affiliation(s)
- Ze Xiang
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiayuan Li
- Zhejiang University School of Medicine, Hangzhou, China
| | - Di Lu
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
- NHC Key Laboratory of Combined Multi-Organ Transplantation, Hangzhou, China
- Institute of Organ Transplantation, Zhejiang University, Hangzhou, China
| | - Xuyong Wei
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
- NHC Key Laboratory of Combined Multi-Organ Transplantation, Hangzhou, China
- Institute of Organ Transplantation, Zhejiang University, Hangzhou, China
| | - Xiao Xu
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
- NHC Key Laboratory of Combined Multi-Organ Transplantation, Hangzhou, China
- Institute of Organ Transplantation, Zhejiang University, Hangzhou, China
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32
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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; 32:1585-1601. [PMID: 35977842 PMCID: PMC9435747 DOI: 10.1101/gr.276550.122] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [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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Panigrahi M, Kumar H, Saravanan KA, Rajawat D, Sonejita Nayak S, Ghildiyal K, Kaisa K, Parida S, Bhushan B, Dutt T. Trajectory of livestock genomics in South Asia: A comprehensive review. Gene 2022; 843:146808. [PMID: 35973570 DOI: 10.1016/j.gene.2022.146808] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 08/08/2022] [Accepted: 08/10/2022] [Indexed: 02/07/2023]
Abstract
Livestock plays a central role in sustaining human livelihood in South Asia. There are numerous and distinct livestock species in South Asian countries. Several of them have experienced genetic development in recent years due to the application of genomic technologies and effective breeding programs. This review discusses genomic studies on cattle, buffalo, sheep, goat, pig, horse, camel, yak, mithun, and poultry. The frontiers covered in this review are genetic diversity, admixture studies, selection signature research, QTL discovery, genome-wide association studies (GWAS), and genomic selection. The review concludes with recommendations for South Asian livestock systems to increasingly leverage genomic technologies, based on the lessons learned from the numerous case studies. This paper aims to present a comprehensive analysis of the dichotomy in the South Asian livestock sector and argues that a realistic approach to genomics in livestock can ensure long-term genetic advancements.
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Affiliation(s)
- Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India.
| | - Harshit Kumar
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - K A Saravanan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Sonali Sonejita Nayak
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Kanika Ghildiyal
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Kaiho Kaisa
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Subhashree Parida
- Division of Pharmacology & Toxicology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
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Zhang X, Chen N, Chen H, Lei C, Sun T. Comparative analyses of copy number variations between swamp and river buffalo. Gene X 2022; 830:146509. [PMID: 35460806 DOI: 10.1016/j.gene.2022.146509] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 04/08/2022] [Accepted: 04/14/2022] [Indexed: 11/30/2022] Open
Abstract
Domestic buffalo is an important livestock in the tropical and sub-tropical region, including two types: swamp and river buffalo. The swamp buffalo is mainly used as draft animal, while the river buffalo is raised for milk production. In this study, based on the new high-quality buffalo reference genome UOA_WB_1, we firstly investigated the copy number variants in buffalo using whole-genome Illumina sequencing. A total of 3,734 CNV regions (CNVRs) were detected in 106 buffalo population with a total length of 23,429,066 bp, corresponding to ∼ 0.88% of the water buffalo genome (UOA_WB_1). Our results revealed a clear population differentiation in CNV between swamp and river buffalo. In addition, a total of 667 highly differentiated CNVRs (covering 886 genes) were detected between river and swamp buffalo population. We detected a set of CNVR-overlapping genes associated with exercise, immunity, nerve, and milk trait which exhibited different copy numbers between swamp and river buffalo population. This study provides valuable genome variation resources for buffalo and would contribute to understanding the genetic differences between swamp and river buffalo.
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Affiliation(s)
- Xianfu Zhang
- Key Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Laboratory for Animal Health Inspection and Internet Technology, College of Animal Science and Technology, College of Veterinary Medicine, Zhejiang A & F University, Hangzhou, Zhejiang 311300, China.
| | - Ningbo Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Hong Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Chuzhao Lei
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Ting Sun
- College of Life Sciences, Shaanxi Normal University, Xi'an 710062, China.
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Xing X, Ai C, Wang T, Li Y, Liu H, Hu P, Wang G, Liu H, Wang H, Zhang R, Zheng J, Wang X, Wang L, Chang Y, Qian Q, Yu J, Tang L, Wu S, Shao X, Li A, Cui P, Zhan W, Zhao S, Wu Z, Shao X, Dong Y, Rong M, Tan Y, Cui X, Chang S, Song X, Yang T, Sun L, Ju Y, Zhao P, Fan H, Liu Y, Wang X, Yang W, Yang M, Wei T, Song S, Xu J, Yue Z, Liang Q, Li C, Ruan J, Yang F. The first high-quality reference genome of sika deer provides insights for high-tannin adaptation. GENOMICS, PROTEOMICS & BIOINFORMATICS 2022:S1672-0229(22)00075-4. [PMID: 35718271 PMCID: PMC10372904 DOI: 10.1016/j.gpb.2022.05.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 03/07/2022] [Accepted: 05/08/2022] [Indexed: 10/18/2022]
Abstract
Sika deer are known to prefer oak leaves, which are rich in tannins and toxic to most mammals; however, the genetic mechanisms underlying their unique ability to adapt to living in the jungle are still unclear. In identifying the mechanism responsible for the tolerance of a highly toxic diet, we have made a major advancement by explaining the genomics of sika deer. We generated the first high-quality, chromosome-level genome assembly of sika deer and measured the correlation between tannin intake and RNA expression in 15 tissues through 180 experiments. Comparative genome analyses showed that the UGT and CYP gene families are functionally involved in the adaptation of sika deer to high-tannin food, especially the expansion of the UGT family 2 subfamily B of UGT genes. The first chromosome-level assembly and genetic characterization of the tolerance to a highly toxic diet suggest that the sika deer genome may serve as an essential resource for understanding evolutionary events and tannin adaptation. Our study provides a paradigm of comparative expressive genomics that can be applied to the study of unique biological features in non-model animals.
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Affiliation(s)
- Xiumei Xing
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China.
| | - Cheng Ai
- 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 518120, China
| | - Tianjiao Wang
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Yang Li
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Huitao Liu
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Pengfei Hu
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Guiwu Wang
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Huamiao Liu
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Hongliang Wang
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Ranran Zhang
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Junjun Zheng
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Xiaobo Wang
- 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 518120, China
| | - Lei Wang
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Yuxiao Chang
- 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 518120, China
| | - Qian Qian
- 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 518120, China
| | - Jinghua Yu
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
| | - Lixin Tang
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Shigang Wu
- 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 518120, China
| | - Xiujuan Shao
- 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 518120, China
| | - Alun 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 518120, China
| | - Peng Cui
- 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 518120, China
| | - Wei Zhan
- Annoroad Gene Technology (Beijing) Co., Ltd, Beijing 100176, China
| | - Sheng Zhao
- 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 518120, China
| | - Zhichao Wu
- 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 518120, China
| | - Xiqun Shao
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Yimeng Dong
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Min Rong
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Yihong Tan
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
| | - Xuezhe Cui
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Shuzhuo Chang
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Xingchao Song
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Tongao Yang
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Limin Sun
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Yan Ju
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Pei Zhao
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Huanhuan Fan
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Ying Liu
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Xinhui Wang
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Wanyun Yang
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Min Yang
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Tao Wei
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Shanshan Song
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Jiaping Xu
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Zhigang Yue
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Qiqi Liang
- Novogene Bioinformatics Institute, Beijing 100083, China.
| | - Chunyi Li
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China.
| | - Jue Ruan
- 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 518120, China.
| | - Fuhe Yang
- Key Laboratory of Genetics, Breeding and Reproduction of Special Economic Animals, Ministry of Agriculture and Rural Affairs, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China.
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Low WY, Rosen BD, Ren Y, Bickhart DM, To TH, Martin FJ, Billis K, Sonstegard TS, Sullivan ST, Hiendleder S, Williams JL, Heaton MP, Smith TPL. Gaur genome reveals expansion of sperm odorant receptors in domesticated cattle. BMC Genomics 2022; 23:344. [PMID: 35508966 PMCID: PMC9069736 DOI: 10.1186/s12864-022-08561-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 04/13/2022] [Indexed: 02/08/2023] Open
Abstract
Background The gaur (Bos gaurus) is the largest extant wild bovine species, native to South and Southeast Asia, with unique traits, and is listed as vulnerable by the International Union for Conservation of Nature (IUCN). Results We report the first gaur reference genome and identify three biological pathways including lysozyme activity, proton transmembrane transporter activity, and oxygen transport with significant changes in gene copy number in gaur compared to other mammals. These may reflect adaptation to challenges related to climate and nutrition. Comparative analyses with domesticated indicine (Bos indicus) and taurine (Bos taurus) cattle revealed genomic signatures of artificial selection, including the expansion of sperm odorant receptor genes in domesticated cattle, which may have important implications for understanding selection for male fertility. Conclusions Apart from aiding dissection of economically important traits, the gaur genome will also provide the foundation to conserve the species. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08561-1.
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Affiliation(s)
- Wai Yee Low
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, 5371, Australia.
| | - Benjamin D Rosen
- Animal Genomics and Improvement LaboratoryARS USDA, Beltsville, MD, USA
| | - Yan Ren
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, 5371, Australia
| | | | - Thu-Hien To
- Norwegian University of Life Sciences: NMBU, Universitetstunet 3, 1430, Ås, Norway
| | - Fergal J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Konstantinos Billis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | | | - Shawn T Sullivan
- Phase Genomics, 4000 Mason Road, Suite 225, Seattle, WA, 98195, USA
| | - Stefan Hiendleder
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, 5371, Australia
| | - John L Williams
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, 5371, Australia.,Department of Animal Science, Food and Nutrition, Università Cattolica del Sacro Cuore, 29122, Piacenza, Italy
| | - Michael P Heaton
- U.S. Department of Agriculture, Agricultural Research Service, U.S. Meat Animal Research Center, Clay Center, Nebraska, USA
| | - Timothy P L Smith
- U.S. Department of Agriculture, Agricultural Research Service, U.S. Meat Animal Research Center, Clay Center, Nebraska, USA.
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Chen Y, Zhang T, Xian M, Zhang R, Yang W, Su B, Yang G, Sun L, Xu W, Xu S, Gao H, Xu L, Gao X, Li J. A draft genome of Drung cattle reveals clues to its chromosomal fusion and environmental adaptation. Commun Biol 2022; 5:353. [PMID: 35418663 PMCID: PMC9008013 DOI: 10.1038/s42003-022-03298-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 03/21/2022] [Indexed: 12/02/2022] Open
Abstract
Drung cattle (Bos frontalis) have 58 chromosomes, differing from the Bos taurus 2n = 60 karyotype. To date, its origin and evolution history have not been proven conclusively, and the mechanisms of chromosome fusion and environmental adaptation have not been clearly elucidated. Here, we assembled a high integrity and good contiguity genome of Drung cattle with 13.7-fold contig N50 and 4.1-fold scaffold N50 improvements over the recently published Indian mithun assembly, respectively. Speciation time estimation and phylogenetic analysis showed that Drung cattle diverged from Bos taurus into an independent evolutionary clade. Sequence evidence of centromere regions provides clues to the breakpoints in BTA2 and BTA28 centromere satellites. We furthermore integrated a circulation and contraction-related biological process involving 43 evolutionary genes that participated in pathways associated with the evolution of the cardiovascular system. These findings may have important implications for understanding the molecular mechanisms of chromosome fusion, alpine valleys adaptability and cardiovascular function.
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Affiliation(s)
- Yan Chen
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, 100193, Beijing, P.R. China
| | - Tianliu Zhang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, 100193, Beijing, P.R. China
| | - Ming Xian
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, 100193, Beijing, P.R. China
| | - Rui Zhang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, 100193, Beijing, P.R. China
| | - Weifei Yang
- 1 Gene Co., Ltd, 310051, Hangzhou, P.R. China
- Annoroad Gene Technology (Beijing) Co., Ltd, 100176, Beijing, P.R. China
| | - Baqi Su
- Drung Cattle Conservation Farm in Jiudang Wood, Drung and Nu Minority Autonomous County, Gongshan, 673500, Kunming, Yunnan, P.R. China
| | - Guoqiang Yang
- Livestock and Poultry Breed Improvement Center, Nujiang Lisu Minority Autonomous Prefecture, 673199, Kunming, Yunnan, P.R. China
| | - Limin Sun
- Yunnan Animal Husbandry Service, 650224, Kunming, Yunnan, P.R. China
| | - Wenkun Xu
- Yunnan Animal Husbandry Service, 650224, Kunming, Yunnan, P.R. China
| | - Shangzhong Xu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, 100193, Beijing, P.R. China
| | - Huijiang Gao
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, 100193, Beijing, P.R. China
| | - Lingyang Xu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, 100193, Beijing, P.R. China
| | - Xue Gao
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, 100193, Beijing, P.R. China.
| | - Junya Li
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, 100193, Beijing, P.R. China.
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38
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Immunity and lifespan: answering long-standing questions with comparative genomics. Trends Genet 2022; 38:650-661. [DOI: 10.1016/j.tig.2022.02.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 01/14/2022] [Accepted: 02/28/2022] [Indexed: 10/18/2022]
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Liu SH, Ma XY, Hassan FU, Gao TY, Deng TX. Genome-wide analysis of runs of homozygosity in Italian Mediterranean buffalo. J Dairy Sci 2022; 105:4324-4334. [PMID: 35307184 DOI: 10.3168/jds.2021-21543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Accepted: 02/07/2022] [Indexed: 11/19/2022]
Abstract
Runs of homozygosity (ROH) are a powerful tool to explore patterns of genomic inbreeding in animal populations and detect signatures of selection. The present study used ROH analysis to evaluate the genome-wide patterns of homozygosity, inbreeding levels, and distribution of ROH islands using the SNP data sets from 899 Mediterranean buffaloes. A total of 42,433 ROH segments were identified, with an average of 47.20 segments per individual. The ROH comprising mostly shorter segments (1-4 Mb) accounted for approximately 72.29% of all ROH. In contrast, the larger ROH (>8 Mb) class accounted for only 7.97% of all ROH segments. Estimated inbreeding coefficients from ROH (FROH) ranged from 0.0201 to 0.0371. Pearson correlations between FROH and genomic relationship matrix increased with the increase of ROH length. We identified ROH hotspots in 12 genomic regions, located on chromosomes 1, 2, 3, 5, 17, and 19, harboring a total of 122 genes. Protein-protein interaction (PPI) analysis revealed the clustering of these genes into 7 PPI networks. Many genes located in these regions were associated with different production traits. In addition, 5 ROH islands overlapped with cattle quantitative trait loci that were mainly associated with milk traits. These findings revealed the genome-wide autozygosity patterns and inbreeding levels in Mediterranean buffalo. Our study identified many candidate genes related to production traits that could be used to assist in selective breeding for genetic improvement of buffalo.
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Affiliation(s)
- Shen-He Liu
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China.
| | - Xiao-Ya Ma
- Guangxi Provincial Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China
| | - Faiz-Ul Hassan
- Institute of Animal and Dairy Sciences, University of Agriculture, Faisalabad 38040, Pakistan
| | - Teng-Yun Gao
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Ting-Xian Deng
- Guangxi Provincial Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China.
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Cristina R, Viviana G, Domenico I, Filomena M, Angela P, Alfredo P. State of the art on the physical mapping of the Y-chromosome in the <i>Bovidae</i> and comparison with other species. Anim Biosci 2022; 35:1289-1302. [PMID: 35240029 PMCID: PMC9449390 DOI: 10.5713/ab.21.0480] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 02/01/2022] [Indexed: 11/27/2022] Open
Abstract
The next generation sequencing has significantly contributed to clarify the genome structure of many species of zootechnical interest. However, to date, some portions of the genome, especially those linked to a heterogametic nature such as the Y chromosome, are difficult to assemble and many gaps are still present. It is well known that the fluorescence in situ hybridization (FISH) is an excellent tool for identifying genes unequivocably mapped on chromosomes. Therefore, FISH can contribute to the localization of unplaced genome sequences, as well as to correct assembly errors generated by comparative bioinformatics. To this end, it is necessary to have starting points; therefore, in this study, we reviewed the physically mapped genes on the Y chromosome of cattle, buffalo, sheep, goats, pigs, horses and alpacas. A total of 208 loci were currently mapped by FISH. 89 were located in the male-specific region of the Y chromosome (MSY) and 119 were identified in the pseudoautosomal region (PAR). The loci reported in MSY and PAR were respectively: 18 and 25 in Bos taurus, 5 and 7 in Bubalus bubalis, 5 and 24 in Ovis aries, 5 and 19 in Capra hircus, 10 and 16 in Sus scrofa, 46 and 18 in Equus caballus. While in Vicugna pacos only 10 loci are reported in the PAR region. The correct knowledge and assembly of all genome sequences, including those of genes mapped on the Y chromosome, will help to elucidate their biological processes, as well as to discover and exploit potentially epistasis effects useful for selection breeding programs.
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Talenti A, Powell J, Hemmink JD, Cook EAJ, Wragg D, Jayaraman S, Paxton E, Ezeasor C, Obishakin ET, Agusi ER, Tijjani A, Amanyire W, Muhanguzi D, Marshall K, Fisch A, Ferreira BR, Qasim A, Chaudhry U, Wiener P, Toye P, Morrison LJ, Connelley T, Prendergast JGD. A cattle graph genome incorporating global breed diversity. Nat Commun 2022; 13:910. [PMID: 35177600 PMCID: PMC8854726 DOI: 10.1038/s41467-022-28605-0] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 01/20/2022] [Indexed: 11/28/2022] Open
Abstract
Despite only 8% of cattle being found in Europe, European breeds dominate current genetic resources. This adversely impacts cattle research in other important global cattle breeds, especially those from Africa for which genomic resources are particularly limited, despite their disproportionate importance to the continent's economies. To mitigate this issue, we have generated assemblies of African breeds, which have been integrated with genomic data for 294 diverse cattle into a graph genome that incorporates global cattle diversity. We illustrate how this more representative reference assembly contains an extra 116.1 Mb (4.2%) of sequence absent from the current Hereford sequence and consequently inaccessible to current studies. We further demonstrate how using this graph genome increases read mapping rates, reduces allelic biases and improves the agreement of structural variant calling with independent optical mapping data. Consequently, we present an improved, more representative, reference assembly that will improve global cattle research.
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Affiliation(s)
- A Talenti
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK.
| | - J Powell
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - J D Hemmink
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
- The International Livestock Research Institute, PO Box 30709, Nairobi, Kenya
- Centre for Tropical Livestock Genetics and Health, Easter Bush, Midlothian, EH25 9RG, UK
- Centre for Tropical Livestock Genetics and Health, ILRI Kenya, Nairobi, 30709-00100, Kenya
| | - E A J Cook
- The International Livestock Research Institute, PO Box 30709, Nairobi, Kenya
- Centre for Tropical Livestock Genetics and Health, ILRI Kenya, Nairobi, 30709-00100, Kenya
| | - D Wragg
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
- Centre for Tropical Livestock Genetics and Health, Easter Bush, Midlothian, EH25 9RG, UK
| | - S Jayaraman
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - E Paxton
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - C Ezeasor
- Department of Veterinary Pathology and Microbiology, University of Nigeria, Nsukka, Enugu State, Nigeria
| | - E T Obishakin
- Biotechnology Division, National Veterinary Research Institute, Vom, Plateau State, Nigeria
- Biomedical Research Centre, Ghent University Global Campus, Songdo, Incheon, South Korea
| | - E R Agusi
- Biotechnology Division, National Veterinary Research Institute, Vom, Plateau State, Nigeria
- Biomedical Research Centre, Ghent University Global Campus, Songdo, Incheon, South Korea
| | - A Tijjani
- International Livestock Research Institute (ILRI) PO, 5689, Addis Ababa, Ethiopia
- Centre for Tropical Livestock Genetics and Health (CTLGH), ILRI Ethiopia, PO Box 5689, Addis Ababa, Ethiopia
| | - W Amanyire
- School of Biosecurity, Biotechnology and Laboratory Sciences (SBLS), College of Veterinary Medicine, Animal Resources and Biosecurity, Makerere University, P.O Box 7062, Kampala, Uganda
| | - D Muhanguzi
- School of Biosecurity, Biotechnology and Laboratory Sciences (SBLS), College of Veterinary Medicine, Animal Resources and Biosecurity, Makerere University, P.O Box 7062, Kampala, Uganda
| | - K Marshall
- The International Livestock Research Institute, PO Box 30709, Nairobi, Kenya
- Centre for Tropical Livestock Genetics and Health, ILRI Kenya, Nairobi, 30709-00100, Kenya
| | - A Fisch
- Ribeirão Preto College of Nursing, University of Sao Paulo, Ribeirão Preto, SP, Brazil
| | - B R Ferreira
- Ribeirão Preto College of Nursing, University of Sao Paulo, Ribeirão Preto, SP, Brazil
| | - A Qasim
- Faculty of Veterinary and Animal Sciences, Gomal University, Dera Ismail Khan, Pakistan
| | - U Chaudhry
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - P Wiener
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - P Toye
- The International Livestock Research Institute, PO Box 30709, Nairobi, Kenya
- Centre for Tropical Livestock Genetics and Health, ILRI Kenya, Nairobi, 30709-00100, Kenya
| | - L J Morrison
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
- Centre for Tropical Livestock Genetics and Health, Easter Bush, Midlothian, EH25 9RG, UK
| | - T Connelley
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
- Centre for Tropical Livestock Genetics and Health, Easter Bush, Midlothian, EH25 9RG, UK
| | - J G D Prendergast
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK.
- Centre for Tropical Livestock Genetics and Health, Easter Bush, Midlothian, EH25 9RG, UK.
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Abdel-Shafy H, Deng T, Zhou Y, Low WY, Hua G. Editorial: Buffalo Genetics and Genomics. Front Genet 2022; 12:820627. [PMID: 35154263 PMCID: PMC8832542 DOI: 10.3389/fgene.2021.820627] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 12/16/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Hamdy Abdel-Shafy
- Department of Animal Production, Faculty of Agriculture, Cairo University, Giza, Egypt
- *Correspondence: Hamdy Abdel-Shafy,
| | - Tingxian Deng
- Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning, China
| | - 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, China
| | - Wai Yee Low
- The Davies Livestock Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Adelaide, Australia
| | - Guohua Hua
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
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de Araujo Neto FR, dos Santos JCG, da Silva Arce CD, Borquis RRA, dos Santos DJA, Guimarães KC, do Nascimento AV, de Oliveira HN, Tonhati H. Genomic study of the resilience of buffalo cows to a negative energy balance. J Appl Genet 2022; 63:379-388. [DOI: 10.1007/s13353-021-00680-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 11/15/2021] [Accepted: 12/23/2021] [Indexed: 11/27/2022]
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Zhang J, Huang L, Zhang P, Huang X, Yang W, Liu R, Sun Q, Lu Y, Zhang M, Fu Q. Genomic Identification, Evolution, and Expression Analysis of Bromodomain Genes Family in Buffalo. Genes (Basel) 2022; 13:genes13010103. [PMID: 35052443 PMCID: PMC8774554 DOI: 10.3390/genes13010103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/22/2021] [Accepted: 12/28/2021] [Indexed: 02/05/2023] Open
Abstract
Bromodomain (BRD) is an evolutionarily conserved protein-protein interaction module that is critical in gene regulation, cellular homeostasis, and epigenetics. This study aimed to conduct an identification, evolution, and expression analysis of the BRD gene family in the swamp buffalo (Bubalus bubalis). A total of 101 BRD protein sequences deduced from 22 BRD genes were found in the buffalo genome. The BRD proteins were classified into six groups based on phylogenetic relationships, conserved motifs, and conserved domains. The BRD genes were irregularly distributed in 13 chromosomes. Collinearity analysis revealed 20 BRD gene pairs that had remarkable homologous relationships between the buffalo and cattle, although no tandem or segmental duplication event was found in the buffalo BRD genes. Comparative transcriptomics using a 10x sequencing platform analysis showed that 22 BRD genes were identified in the Sertoli cells (SCs) at different developmental stages of buffalo. Further, the mRNA expression levels of bromodomain and the extraterminal (BET) family in SCs at the pubertal stage were higher than that at the prepubertal stage of buffalo. However, the SMARCA2, PHIP, BRD9, and TAF1 genes exhibited the opposite trend. The maturation process of SCs may be regulated by the BRD family members expressed differentially in SCs at different developmental stages of buffalo. In summary, our findings provide an understanding of the evolutionary, structural, and functional properties of the buffalo BRD family members, and further characterize the function of the BRD family in the maturation of SCs. It also provides a theoretical basis for further understanding in the future of the mechanism of SCs regulating spermatogenesis.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Qiang Fu
- Correspondence: ; Tel.: +86-771-3237124
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45
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Deng TX, Ma XY, Lu XR, Duan AQ, Shokrollahi B, Shang JH. Signatures of selection reveal candidate genes involved in production traits in Chinese crossbred buffaloes. J Dairy Sci 2021; 105:1327-1337. [PMID: 34955275 DOI: 10.3168/jds.2021-21102] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 11/03/2021] [Indexed: 12/11/2022]
Abstract
Identification of selection signature is important for a better understanding of genetic mechanisms that affect phenotypic differentiation in livestock. However, the genome-wide selection responses have not been investigated for the production traits of Chinese crossbred buffaloes. In this study, an SNP data set of 133 buffaloes (Chinese crossbred buffalo, n = 45; Chinese local swamp buffalo, n = 88) was collected from the Dryad Digital Repository database (https://datadryad.org/stash/). Population genetics analysis showed that these buffaloes were divided into the following 2 groups: crossbred buffalo and swamp buffalo. The crossbred group had higher genetic diversity than the swamp group. Using 3 complementary statistical methods (integrated haplotype score, cross population extended haplotype homozygosity, and composite likelihood ratio), a total of 31 candidate selection regions were identified in the Chinese crossbred population. Here, within these candidate regions, 25 genes were under the putative selection. Among them, several candidate genes were reported to be associated with production traits. In addition, we identified 13 selection regions that overlapped with bovine QTLs that were mainly involved in milk production and composition traits. These results can provide useful insights regarding the selection response for production traits of Chinese crossbred buffalo, as identified candidate genes influence production performance.
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Affiliation(s)
- T X Deng
- Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China.
| | - X Y Ma
- Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China
| | - X R Lu
- Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China
| | - A Q Duan
- Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China
| | - Borhan Shokrollahi
- Department of Animal Science, Faculty of Agriculture, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran 5595-73919
| | - J H Shang
- Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China.
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46
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Stervander M, Cresko WA. A highly contiguous nuclear genome assembly of the mandarinfish Synchiropus splendidus (Syngnathiformes: Callionymidae). G3 (BETHESDA, MD.) 2021; 11:jkab306. [PMID: 34849773 PMCID: PMC8664458 DOI: 10.1093/g3journal/jkab306] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Accepted: 08/23/2021] [Indexed: 12/21/2022]
Abstract
The fish order Syngnathiformes has been referred to as a collection of misfit fishes, comprising commercially important fish such as red mullets as well as the highly diverse seahorses, pipefishes, and seadragons-the well-known family Syngnathidae, with their unique adaptations including male pregnancy. Another ornate member of this order is the species mandarinfish. No less than two types of chromatophores have been discovered in the spectacularly colored mandarinfish: the cyanophore (producing blue color) and the dichromatic cyano-erythrophore (producing blue and red). The phylogenetic position of mandarinfish in Syngnathiformes, and their promise of additional genetic discoveries beyond the chromatophores, made mandarinfish an appealing target for whole-genome sequencing. We used linked sequences to create synthetic long reads, producing a highly contiguous genome assembly for the mandarinfish. The genome assembly comprises 483 Mbp (longest scaffold 29 Mbp), has an N50 of 12 Mbp, and an L50 of 14 scaffolds. The assembly completeness is also high, with 92.6% complete, 4.4% fragmented, and 2.9% missing out of 4584 BUSCO genes found in ray-finned fishes. Outside the family Syngnathidae, the mandarinfish represents one of the most contiguous syngnathiform genome assemblies to date. The mandarinfish genomic resource will likely serve as a high-quality outgroup to syngnathid fish, and furthermore for research on the genomic underpinnings of the evolution of novel pigmentation.
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Affiliation(s)
- Martin Stervander
- Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403-5289, USA
| | - William A Cresko
- Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403-5289, USA
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47
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Tyagi SK, Mehrotra A, Singh A, Kumar A, Dutt T, Mishra BP, Pandey AK. Comparative Signatures of Selection Analyses Identify Loci Under Positive Selection in the Murrah Buffalo of India. Front Genet 2021; 12:673697. [PMID: 34737760 PMCID: PMC8560740 DOI: 10.3389/fgene.2021.673697] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 09/17/2021] [Indexed: 12/18/2022] Open
Abstract
India is home to a large and diverse buffalo population. The Murrah breed of North India is known for its milk production, and it has been used in breeding programs in several countries. Selection signature analysis yield valuable information about how the natural and artificial selective pressures have shaped the genomic landscape of modern-day livestock species. Genotype information was generated on six buffalo breeds of India, namely, Murrah, Bhadawari, Mehsana, Pandharpuri, Surti, and Toda using ddRAD sequencing protocol. Initially, the genotypes were used to carry out population diversity and structure analysis among the six breeds, followed by pair-wise comparisons of Murrah with the other five breeds through XP-EHH and F ST methodologies to identify regions under selection in Murrah. Admixture results showed significant levels of Murrah inheritance in all the breeds except Pandharpuri. The selection signature analysis revealed six regions in Murrah, which were identified in more than one pair-wise comparison through both XP-EHH and F ST analyses. The significant regions overlapped with QTLs for milk production, immunity, and body development traits. Genes present in these regions included SLC37A1, PDE9A, PPBP, CXCL6, RASSF6, AFM, AFP, ALB, ANKRD17, CNTNAP2, GPC5, MYLK3, and GPT2. These genes emerged as candidates for future polymorphism studies of adaptability and performance traits in buffaloes. The results also suggested ddRAD sequencing as a useful cost-effective alternative for whole-genome sequencing to carry out diversity analysis and discover selection signatures in Indian buffalo breeds.
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Affiliation(s)
- Shiv K Tyagi
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnangar, Bareilly, India
| | - Arnav Mehrotra
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnangar, Bareilly, India
| | - Akansha Singh
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnangar, Bareilly, India
| | - Amit Kumar
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnangar, Bareilly, India
| | - Triveni Dutt
- Livestock Production and Management, Indian Council of Agricultural Research (ICAR)-Indian Veterinary Research Institute, Bareilly, India
| | - Bishnu P Mishra
- Animal Biotechnology, Indian Council of Agricultural Research (ICAR)-Indian Veterinary Research Institute, Bareilly, India
| | - Ashwni K Pandey
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnangar, Bareilly, India
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48
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Johnson LK, Sahasrabudhe R, Gill JA, Roach JL, Froenicke L, Brown CT, Whitehead A. Draft genome assemblies using sequencing reads from Oxford Nanopore Technology and Illumina platforms for four species of North American Fundulus killifish. Gigascience 2021; 9:5859380. [PMID: 32556169 PMCID: PMC7301629 DOI: 10.1093/gigascience/giaa067] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Revised: 04/16/2020] [Accepted: 05/27/2020] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Whole-genome sequencing data from wild-caught individuals of closely related North American killifish species (Fundulus xenicus, Fundulus catenatus, Fundulus nottii, and Fundulus olivaceus) were obtained using long-read Oxford Nanopore Technology (ONT) PromethION and short-read Illumina platforms. FINDINGS Draft de novo reference genome assemblies were generated using a combination of long and short sequencing reads. For each species, the PromethION platform was used to generate 30-45× sequence coverage, and the Illumina platform was used to generate 50-160× sequence coverage. Illumina-only assemblies were fragmented with high numbers of contigs, while ONT-only assemblies were error prone with low BUSCO scores. The highest N50 values, ranging from 0.4 to 2.7 Mb, were from assemblies generated using a combination of short- and long-read data. BUSCO scores were consistently >90% complete using the Eukaryota database. CONCLUSIONS High-quality genomes can be obtained from a combination of using short-read Illumina data to polish assemblies generated with long-read ONT data. Draft assemblies and raw sequencing data are available for public use. We encourage use and reuse of these data for assembly benchmarking and other analyses.
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Affiliation(s)
- Lisa K Johnson
- Department of Environmental Toxicology, University of California. 1 Shields Avenue, Davis, CA 95616, Davis, CA, USA
- Department of Population Health & Reproduction, School of Veterinary Medicine, University of California. 1 Shields Avenue, Davis, CA 95616, Davis, CA, USA
| | - Ruta Sahasrabudhe
- DNA Technologies Core, Genome Center, University of California, 1 Shields Avenue, Davis, CA 95616
| | - James Anthony Gill
- Department of Environmental Toxicology, University of California. 1 Shields Avenue, Davis, CA 95616, Davis, CA, USA
| | - Jennifer L Roach
- Department of Environmental Toxicology, University of California. 1 Shields Avenue, Davis, CA 95616, Davis, CA, USA
| | - Lutz Froenicke
- DNA Technologies Core, Genome Center, University of California, 1 Shields Avenue, Davis, CA 95616
| | - C Titus Brown
- Department of Population Health & Reproduction, School of Veterinary Medicine, University of California. 1 Shields Avenue, Davis, CA 95616, Davis, CA, USA
| | - Andrew Whitehead
- Correspondence address. Andrew Whitehead, Department of Environmental Toxicology, University of California. 1 Shields Avenue, Davis, CA 95616, USA, Davis, CA, USA. E-mail:
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49
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Freire R, Weisweiler M, Guerreiro R, Baig N, Hüttel B, Obeng-Hinneh E, Renner J, Hartje S, Muders K, Truberg B, Rosen A, Prigge V, Bruckmüller J, Lübeck J, Stich B. Chromosome-scale reference genome assembly of a diploid potato clone derived from an elite variety. G3-GENES GENOMES GENETICS 2021; 11:6371871. [PMID: 34534288 PMCID: PMC8664475 DOI: 10.1093/g3journal/jkab330] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 09/08/2021] [Indexed: 01/27/2023]
Abstract
Potato (Solanum tuberosum L.) is one of the most important crops with a worldwide production of 370 million metric tons. The objectives of this study were (1) to create a high-quality consensus sequence across the two haplotypes of a diploid clone derived from a tetraploid elite variety and assess the sequence divergence from the available potato genome assemblies, as well as among the two haplotypes; (2) to evaluate the new assembly’s usefulness for various genomic methods; and (3) to assess the performance of phasing in diploid and tetraploid clones, using linked-read sequencing technology. We used PacBio long reads coupled with 10x Genomics reads and proximity ligation scaffolding to create the dAg1_v1.0 reference genome sequence. With a final assembly size of 812 Mb, where 750 Mb are anchored to 12 chromosomes, our assembly is larger than other available potato reference sequences and high proportions of properly paired reads were observed for clones unrelated by pedigree to dAg1. Comparisons of the new dAg1_v1.0 sequence to other potato genome sequences point out the high divergence between the different potato varieties and illustrate the potential of using dAg1_v1.0 sequence in breeding applications.
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Affiliation(s)
- Ruth Freire
- Institute for Quantitative Genetics and Genomics of Plants, Universitätsstraße 1, 40225 Düsseldorf, Germany
| | - Marius Weisweiler
- Institute for Quantitative Genetics and Genomics of Plants, Universitätsstraße 1, 40225 Düsseldorf, Germany
| | - Ricardo Guerreiro
- Institute for Quantitative Genetics and Genomics of Plants, Universitätsstraße 1, 40225 Düsseldorf, Germany
| | - Nadia Baig
- Institute for Quantitative Genetics and Genomics of Plants, Universitätsstraße 1, 40225 Düsseldorf, Germany
| | - Bruno Hüttel
- Max Planck-Genome-centre Cologne, Max Planck Institute for Plant Breeding, Carl-von-Linne-Weg 10, 50829 Köln, Germany
| | - Evelyn Obeng-Hinneh
- Böhm-Nordkartoffel Agrarproduktion GmbH & Co. OHG, Strehlow 19, 17111 Hohenmocker, Germany
| | - Juliane Renner
- Böhm-Nordkartoffel Agrarproduktion GmbH & Co. OHG, Strehlow 19, 17111 Hohenmocker, Germany
| | - Stefanie Hartje
- Böhm-Nordkartoffel Agrarproduktion GmbH & Co. OHG, Strehlow 19, 17111 Hohenmocker, Germany
| | - Katja Muders
- Nordring- Kartoffelzucht- und Vermehrungs- GmbH, Parkweg 4, 18190 Sanitz, Germany
| | - Bernd Truberg
- Nordring- Kartoffelzucht- und Vermehrungs- GmbH, Parkweg 4, 18190 Sanitz, Germany
| | - Arne Rosen
- Nordring- Kartoffelzucht- und Vermehrungs- GmbH, Parkweg 4, 18190 Sanitz, Germany
| | - Vanessa Prigge
- SaKa Pflanzenzucht GmbH & Co. KG, Zuchtstation Windeby, Eichenallee 9, 24340 Windeby, Germany
| | | | - Jens Lübeck
- Solana Research GmbH, Eichenallee 9, 24340 Windeby, Germany
| | - Benjamin Stich
- Institute for Quantitative Genetics and Genomics of Plants, Universitätsstraße 1, 40225 Düsseldorf, Germany.,Cluster of Excellence on Plant Sciences, From Complex Traits towards Synthetic Modules, Universitätsstraße 1, 40225 Düsseldorf, Germany
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Sarwalia P, Raza M, Soni A, Dubey P, Chandel R, Kumar R, Kumaresan A, Onteru SK, Pal A, Singh K, Iquebal MA, Jaiswal S, Kumar D, Datta TK. Establishment of Repertoire of Placentome-Associated MicroRNAs and Their Appearance in Blood Plasma Could Identify Early Establishment of Pregnancy in Buffalo ( Bubalus bubalis). Front Cell Dev Biol 2021; 9:673765. [PMID: 34513824 PMCID: PMC8427669 DOI: 10.3389/fcell.2021.673765] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 07/27/2021] [Indexed: 01/05/2023] Open
Abstract
Precise early pregnancy diagnosis in dairy animals is of utmost importance for an efficient dairy production system. Not detecting a dairy animal pregnant sufficiently early after the breeding results to extending the unproductive time of their milk production cycle and causes substantial economic loss for a dairy producer. At present, the most conventional and authentic pregnancy confirmation practice in cows and buffaloes is rectal palpation of the reproductive organs at Days 35–40 after insemination, which sometime leads to considering an animal as false pregnant. Other alternative methods available for early pregnancy diagnosis lack either accuracy or reproducibility or require elaborate instrumentation and laboratory setup not feasible to practice at farmers’ doorstep. The present study was aimed at establishment of the microRNA (miRNA) repertoire of the placentome in buffaloes, which could capture the event of the cross talk between a growing embryo and a dam, through fetal cotyledons and maternal caruncles, and thus could hint at the early pregnancy establishment event in ruminants. Total RNA was isolated from buffalo placentome tissues during early stages of pregnancy (at Day < 25 and Days 30–35), and global small RNA analysis was performed by using Illumina single-end read chemistry and Bubalus bubalis genome. A total of 2,199 miRNAs comprising 1,620 conserved and 579 non-conserved miRNAs were identified. Stringent functional miRNA selection criteria could predict 20 miRNAs worth evaluating for their abundance in the plasma of pregnant, non-pregnant, cyclic non-bred, and non-cyclic prepubertal animals. Eight of them (viz., miR-195-5p, miR-708-3p, miR-379-5p, miR-XX1, miR-XX2, miR-130a-3p, miR-200a-3p, and miR-27) displayed typical abundance patterns in the plasma samples of the animals on Day 19 as well as Day 25 post-insemination, thus making them ambiguous candidates for early pregnancy detection. Similarly, higher abundance of miR-200a-3p and miR130a-3p in non-pregnant animals was indicative of their utility for detecting the animals as not pregnant. Most interestingly, miR-XX1 and miR-XX2 were very characteristically abundant only in pregnant animals. In silico target prediction analysis confirmed that these two miRNAs are important regulators of cyclooxygenase-2 (COX-2) and cell adhesion molecule-2 (CADM-2), both of which play a significant role in the implantation process during feto-maternal cross talk. We interpret that circulatory miR-XX1 and miR-XX2 in blood plasma could be the potential biomarkers for early pregnancy detection in buffaloes.
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Affiliation(s)
- Parul Sarwalia
- Animal Genomics Laboratory, Animal Biotechnology Centre, National Dairy Research Institute, Karnal, India
| | - Mustafa Raza
- Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Apoorva Soni
- Animal Genomics Laboratory, Animal Biotechnology Centre, National Dairy Research Institute, Karnal, India
| | - Pratiksha Dubey
- Animal Genomics Laboratory, Animal Biotechnology Centre, National Dairy Research Institute, Karnal, India.,Biological Science Laboratory, Indian Institute of Science Education and Research, Mohali, India
| | - Rajeev Chandel
- Animal Biochemistry Division, National Dairy Research Institute, Karnal, India
| | - Rakesh Kumar
- Animal Genomics Laboratory, Animal Biotechnology Centre, National Dairy Research Institute, Karnal, India
| | - A Kumaresan
- Theriogenology Laboratory, SRS of National Dairy Research Institute, Bengaluru, India
| | - Suneel Kumar Onteru
- Animal Biochemistry Division, National Dairy Research Institute, Karnal, India
| | - Ankit Pal
- Animal Genomics Laboratory, Animal Biotechnology Centre, National Dairy Research Institute, Karnal, India
| | - Kalpana Singh
- Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Mir Asif Iquebal
- Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Sarika Jaiswal
- Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Dinesh Kumar
- Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, New Delhi, India
| | - T K Datta
- Animal Genomics Laboratory, Animal Biotechnology Centre, National Dairy Research Institute, Karnal, India
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