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Abebe BK, Wang H, Li A, Zan L. A review of the role of transcription factors in regulating adipogenesis and lipogenesis in beef cattle. J Anim Breed Genet 2024; 141:235-256. [PMID: 38146089 DOI: 10.1111/jbg.12841] [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: 09/30/2023] [Revised: 11/25/2023] [Accepted: 11/30/2023] [Indexed: 12/27/2023]
Abstract
In the past few decades, genomic selection and other refined strategies have been used to increase the growth rate and lean meat production of beef cattle. Nevertheless, the fast growth rates of cattle breeds are often accompanied by a reduction in intramuscular fat (IMF) deposition, impairing meat quality. Transcription factors play vital roles in regulating adipogenesis and lipogenesis in beef cattle. Meanwhile, understanding the role of transcription factors in regulating adipogenesis and lipogenesis in beef cattle has gained significant attention to increase IMF deposition and meat quality. Therefore, the aim of this paper was to provide a comprehensive summary and valuable insight into the complex role of transcription factors in adipogenesis and lipogenesis in beef cattle. This review summarizes the contemporary studies in transcription factors in adipogenesis and lipogenesis, genome-wide analysis of transcription factors, epigenetic regulation of transcription factors, nutritional regulation of transcription factors, metabolic signalling pathways, functional genomics methods, transcriptomic profiling of adipose tissues, transcription factors and meat quality and comparative genomics with other livestock species. In conclusion, transcription factors play a crucial role in promoting adipocyte development and fatty acid biosynthesis in beef cattle. They control adipose tissue formation and metabolism, thereby improving meat quality and maintaining metabolic balance. Understanding the processes by which these transcription factors regulate adipose tissue deposition and lipid metabolism will simplify the development of marbling or IMF composition in beef cattle.
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Affiliation(s)
- Belete Kuraz Abebe
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
- Department of Animal Science, Werabe University, Werabe, Ethiopia
| | - Hongbao Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
| | - Anning Li
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
| | - Linsen Zan
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
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2
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Iqbal N, Liu X, Yang T, Huang Z, Hanif Q, Asif M, Khan QM, Mansoor S. Genomic variants identified from whole-genome resequencing of indicine cattle breeds from Pakistan. PLoS One 2019; 14:e0215065. [PMID: 30973947 PMCID: PMC6459497 DOI: 10.1371/journal.pone.0215065] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 03/26/2019] [Indexed: 12/30/2022] Open
Abstract
The primary goal of cattle genomics is the identification of genome-wide polymorphism associated with economically important traits. The bovine genome sequencing project was completed in 2009. Since then, using massively parallel sequencing technologies, a large number of Bos taurus cattle breeds have been resequenced and scanned for genome-wide polymorphisms. As a result, a substantial number of single nucleotide polymorphisms (SNPs) have been discovered across European Bos taurus genomes, whereas extremely less number of SNPs are cataloged for Bos indicus breeds. In this study, we performed whole-genome resequencing, reference-based mapping, functional annotation and gene enrichment analysis of 20 sires representing eleven important Bos indicus (indicine) breeds of Pakistan. The breeds sequenced here include: Sahiwal, Red Sindhi, Tharparkar and Cholistani (tropically adapted dairy and dual purpose breeds), Achai, Bhagnari, Dajal and Lohani (high altitude adapted dual and drought purpose breeds); Dhanni, Hisar Haryana and Gabrali (dairy and light drought purpose breeds). A total of 17.4 billion QC passed reads were produced using BGISEQ-500 next generation sequencing platform to generate 9 to 27-fold genome coverage (average ~16×) for each of the 20 sequenced sires. A total of 67,303,469 SNPs were identified, of which 3,850,365 were found novel and 1,083,842 insertions-deletions (InDels) were detected across the whole sequenced genomes (491,247 novel). Comparative analysis using coding region SNPs revealed a close relationship between the best milking indicine breeds; Red Sindhi and Sahiwal. On the other hand, Bhagnari and Tharparkar being popular for their adaptation to dry and extremely hot climates were found to share the highest number of SNPs. Functional annotation identified a total of 3,194 high-impact (disruptive) SNPs and 745 disruptive InDels (in 275 genes) that may possibly affect economically important dairy and beef traits. Functional enrichment analysis was performed and revealed that high or moderate impact variants in wingless-related integration site (Wnt) and vascular smooth muscle contraction (VSMC) signaling pathways were significantly over-represented in tropically adapted heat tolerant Pakistani-indicine breeds. On the other hand, vascular endothelial growth factor (VEGF) and hypoxia-inducible factor 1 (HIF-1) signaling pathways were found over-represented in highland adapted Pakistani-indicine breeds. Similarly, the ECM-receptor interaction and Jak-STAT signaling pathway were significantly enriched in dairy and beef purpose Pakistani-indicine cattle breeds. The Toll-like receptor signaling pathway was significantly enriched in most of the Pakistani-indicine cattle. Therefore, this study provides baseline data for further research to investigate the molecular mechanisms of major traits and to develop potential genomic markers associated with economically important breeding traits, particularly in indicine cattle.
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Affiliation(s)
- Naveed Iqbal
- National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Punjab, Pakistan
- Beijing Genomic Institute (BGI), Shenzhen, Guangdong, China
- Department of Biotechnology, Pakistan Institute of Engineering & Applied Sciences (PIEAS), Nilore, Islamabad, Pakistan
- Department of Biotechnology & Informatics, Faculty of life Sciences, Baluchistan University of Information Technology, Engineering and Management Sciences (BUITEMS), Quetta, Baluchistan, Pakistan
| | - Xin Liu
- Beijing Genomic Institute (BGI), Shenzhen, Guangdong, China
| | - Ting Yang
- Beijing Genomic Institute (BGI), Shenzhen, Guangdong, China
| | - Ziheng Huang
- Beijing Genomic Institute (BGI), Shenzhen, Guangdong, China
| | - Quratulain Hanif
- National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Punjab, Pakistan
- Department of Biotechnology, Pakistan Institute of Engineering & Applied Sciences (PIEAS), Nilore, Islamabad, Pakistan
| | - Muhammad Asif
- National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Punjab, Pakistan
- Department of Biotechnology, Pakistan Institute of Engineering & Applied Sciences (PIEAS), Nilore, Islamabad, Pakistan
| | - Qaiser Mahmood Khan
- National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Punjab, Pakistan
| | - Shahid Mansoor
- National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Punjab, Pakistan
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Zwane AA, Schnabel RD, Hoff J, Choudhury A, Makgahlela ML, Maiwashe A, Van Marle-Koster E, Taylor JF. Genome-Wide SNP Discovery in Indigenous Cattle Breeds of South Africa. Front Genet 2019; 10:273. [PMID: 30988672 PMCID: PMC6452414 DOI: 10.3389/fgene.2019.00273] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Accepted: 03/12/2019] [Indexed: 01/30/2023] Open
Abstract
Single nucleotide polymorphism arrays have created new possibilities for performing genome-wide studies to detect genomic regions harboring sequence variants that affect complex traits. However, the majority of validated SNPs for which allele frequencies have been estimated are limited primarily to European breeds. The objective of this study was to perform SNP discovery in three South African indigenous breeds (Afrikaner, Drakensberger, and Nguni) using whole genome sequencing. DNA was extracted from blood and hair samples, quantified and prepared at 50 ng/μl concentration for sequencing at the Agricultural Research Council Biotechnology Platform using an Illumina HiSeq 2500. The fastq files were used to call the variants using the Genome Analysis Tool Kit. A total of 1,678,360 were identified as novel using Run 6 of 1000 Bull Genomes Project. Annotation of the identified variants classified them into functional categories. Within the coding regions, about 30% of the SNPs were non-synonymous substitutions that encode for alternate amino acids. The study of distribution of SNP across the genome identified regions showing notable differences in the densities of SNPs among the breeds and highlighted many regions of functional significance. Gene ontology terms identified genes such as MLANA, SYT10, and CDC42EP5 that have been associated with coat color in mouse, and ADAMS3, DNAJC3, and PAG5 genes have been associated with fertility in cattle. Further analysis of the variants detected 688 candidate selective sweeps (ZHp Z-scores ≤ -4) across all three breeds, of which 223 regions were assigned as being putative selective sweeps (ZHp scores ≤-5). We also identified 96 regions with extremely low ZHp Z-scores (≤-6) in Afrikaner and Nguni. Genes such as KIT and MITF that have been associated with skin pigmentation in cattle and CACNA1C, which has been associated with biopolar disorder in human, were identified in these regions. This study provides the first analysis of sequence data to discover SNPs in indigenous South African cattle breeds. The information will play an important role in our efforts to understand the genetic history of our cattle and in designing appropriate breed improvement programmes.
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Affiliation(s)
- Avhashoni A. Zwane
- Department of Animal Breeding and Genetics, Agricultural Research Council-Animal Production, Irene, South Africa
- Department of Animal and Wildlife Sciences, University of Pretoria, Pretoria, South Africa
| | - Robert D. Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
- Informatics Institute, University of Missouri, Columbia, MO, United States
| | - Jesse Hoff
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | - Ananyo Choudhury
- Sydney Brenner Institute of Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa
| | - Mahlako Linah Makgahlela
- Department of Animal Breeding and Genetics, Agricultural Research Council-Animal Production, Irene, South Africa
- Department of Animal, Wildlife and Grassland Sciences, University of the Free State, Bloemfontein, South Africa
| | - Azwihangwisi Maiwashe
- Department of Animal Breeding and Genetics, Agricultural Research Council-Animal Production, Irene, South Africa
- Department of Animal, Wildlife and Grassland Sciences, University of the Free State, Bloemfontein, South Africa
| | - Este Van Marle-Koster
- Department of Animal and Wildlife Sciences, University of Pretoria, Pretoria, South Africa
| | - Jeremy F. Taylor
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
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Abstract
There is sustained growth in the number of tropical cattle, which represent more than half of all cattle worldwide. By and large, most research in tropical areas is still focused on breeds of cattle, their particular advantages or disadvantages in tropical areas, and the tropical forages or feeds that could be usefully fed to them. A consistent issue for adaptation to climate is the heat of tropical environments. Changing the external characteristics of the animal, such as color and coat characteristics, is one way to adapt, and there are several major genes for these traits. However, further improvement in heat tolerance and other adaptation traits will need to use the entire genome and all physical and physiological systems. Apart from the response to heat, climate forcing through methane emission identifies dry season weight loss as an important if somewhat neglected trait in climate adaptation of cattle. The use of genome-estimated breeding values in tropical areas is in its infancy and will be difficult to implement, but will be essential for rapid, coordinated genetic improvement. The difficulty of implementation cannot be exaggerated and may require major improvements in methodology.
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Affiliation(s)
- W Barendse
- CSIRO Agriculture, St. Lucia 4067, Australia.,School of Veterinary Science, University of Queensland, Gatton 4343, Australia;
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5
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Rosse IC, Assis JG, Oliveira FS, Leite LR, Araujo F, Zerlotini A, Volpini A, Dominitini AJ, Lopes BC, Arbex WA, Machado MA, Peixoto MGCD, Verneque RS, Martins MF, Coimbra RS, Silva MVGB, Oliveira G, Carvalho MRS. Whole genome sequencing of Guzerá cattle reveals genetic variants in candidate genes for production, disease resistance, and heat tolerance. Mamm Genome 2016; 28:66-80. [PMID: 27853861 DOI: 10.1007/s00335-016-9670-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Accepted: 10/24/2016] [Indexed: 01/08/2023]
Abstract
In bovines, artificial selection has produced a large number of breeds which differ in production, environmental adaptation, and health characteristics. To investigate the genetic basis of these phenotypical differences, several bovine breeds have been sequenced. Millions of new SNVs were described at every new breed sequenced, suggesting that every breed should be sequenced. Guzerat or Guzerá is an indicine breed resistant to drought and parasites that has been the base for some important breeds such as Brahman. Here, we describe the sequence of the Guzerá genome and the in silico functional analyses of intragenic breed-specific variations. Mate-paired libraries were generated using the ABI SOLiD system. Sequences were mapped to the Bos taurus reference genome (UMD 3.1) and 87% of the reference genome was covered at a 26X. Among the variants identified, 2,676,067 SNVs and 463,158 INDELs were homozygous, not found in any database searched, and may represent true differences between Guzerá and B. taurus. Functional analyses investigated with the NGS-SNP package focused on 1069 new, non-synonymous SNVs, splice-site variants (including acceptor and donor sites, and the conserved regions at both intron borders, referred to here as splice regions) and coding INDELs (NS/SS/I). These NS/SS/I map to 935 genes belonging to cell communication, environmental adaptation, signal transduction, sensory, and immune systems pathways. These pathways have been involved in phenotypes related to health, adaptation to the environment and behavior, and particularly, disease resistance and heat tolerance. Indeed, 105 of these genes are known QTLs for milk, meat and carcass, production, reproduction, and health traits. Therefore, in addition to describing new genetic variants, our approach provided groundwork for unraveling key candidate genes and mutations.
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Affiliation(s)
- Izinara C Rosse
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais - UFMG, Av. Antônio Carlos, 6627, Pampulha, Belo Horizonte, MG, 31901-207, Brazil
| | - Juliana G Assis
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais - UFMG, Av. Antônio Carlos, 6627, Pampulha, Belo Horizonte, MG, 31901-207, Brazil.,Grupo de Genômica e Biologia Computacional, Centro de Pesquisas René Rachou - FIOCRUZ-Minas, Belo Horizonte, MG, Brazil
| | - Francislon S Oliveira
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais - UFMG, Av. Antônio Carlos, 6627, Pampulha, Belo Horizonte, MG, 31901-207, Brazil.,Grupo de Genômica e Biologia Computacional, Centro de Pesquisas René Rachou - FIOCRUZ-Minas, Belo Horizonte, MG, Brazil
| | - Laura R Leite
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais - UFMG, Av. Antônio Carlos, 6627, Pampulha, Belo Horizonte, MG, 31901-207, Brazil.,Grupo de Genômica e Biologia Computacional, Centro de Pesquisas René Rachou - FIOCRUZ-Minas, Belo Horizonte, MG, Brazil
| | - Flávio Araujo
- Grupo de Genômica e Biologia Computacional, Centro de Pesquisas René Rachou - FIOCRUZ-Minas, Belo Horizonte, MG, Brazil
| | | | - Angela Volpini
- Grupo de Genômica e Biologia Computacional, Centro de Pesquisas René Rachou - FIOCRUZ-Minas, Belo Horizonte, MG, Brazil
| | - Anderson J Dominitini
- Grupo de Genômica e Biologia Computacional, Centro de Pesquisas René Rachou - FIOCRUZ-Minas, Belo Horizonte, MG, Brazil
| | | | | | | | | | | | | | - Roney S Coimbra
- Neurogenômica, Centro de Pesquisa René Rachou - FIOCRUZ-Minas, Belo Horizonte, MG, Brazil
| | | | - Guilherme Oliveira
- Grupo de Genômica e Biologia Computacional, Centro de Pesquisas René Rachou - FIOCRUZ-Minas, Belo Horizonte, MG, Brazil.,Vale Technology Institute, Belém, PA, Brazil
| | - Maria Raquel S Carvalho
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais - UFMG, Av. Antônio Carlos, 6627, Pampulha, Belo Horizonte, MG, 31901-207, Brazil.
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6
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Boussaha M, Esquerré D, Barbieri J, Djari A, Pinton A, Letaief R, Salin G, Escudié F, Roulet A, Fritz S, Samson F, Grohs C, Bernard M, Klopp C, Boichard D, Rocha D. Genome-Wide Study of Structural Variants in Bovine Holstein, Montbéliarde and Normande Dairy Breeds. PLoS One 2015; 10:e0135931. [PMID: 26317361 PMCID: PMC4552564 DOI: 10.1371/journal.pone.0135931] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2015] [Accepted: 07/28/2015] [Indexed: 11/26/2022] Open
Abstract
High-throughput sequencing technologies have offered in recent years new opportunities to study genome variations. These studies have mostly focused on single nucleotide polymorphisms, small insertions or deletions and on copy number variants. Other structural variants, such as large insertions or deletions, tandem duplications, translocations, and inversions are less well-studied, despite that some have an important impact on phenotypes. In the present study, we performed a large-scale survey of structural variants in cattle. We report the identification of 6,426 putative structural variants in cattle extracted from whole-genome sequence data of 62 bulls representing the three major French dairy breeds. These genomic variants affect DNA segments greater than 50 base pairs and correspond to deletions, inversions and tandem duplications. Out of these, we identified a total of 547 deletions and 410 tandem duplications which could potentially code for CNVs. Experimental validation was carried out on 331 structural variants using a novel high-throughput genotyping method. Out of these, 255 structural variants (77%) generated good quality genotypes and 191 (75%) of them were validated. Gene content analyses in structural variant regions revealed 941 large deletions removing completely one or several genes, including 10 single-copy genes. In addition, some of the structural variants are located within quantitative trait loci for dairy traits. This study is a pan-genome assessment of genomic variations in cattle and may provide a new glimpse into the bovine genome architecture. Our results may also help to study the effects of structural variants on gene expression and consequently their effect on certain phenotypes of interest.
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Affiliation(s)
- Mekki Boussaha
- INRA, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- AgroParisTech, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- * E-mail:
| | - Diane Esquerré
- INRA, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENSAT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENVT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Toulouse, France
| | - Johanna Barbieri
- INRA, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENSAT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENVT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Toulouse, France
| | - Anis Djari
- INRA, SIGENAE, UR 875, INRA Auzeville, BP 52627, Castanet-Tolosan, France
| | - Alain Pinton
- INRA, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENSAT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENVT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Toulouse, France
| | - Rabia Letaief
- INRA, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- AgroParisTech, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
| | - Gérald Salin
- INRA, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENSAT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENVT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Toulouse, France
| | - Frédéric Escudié
- INRA, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENSAT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENVT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Toulouse, France
| | - Alain Roulet
- INRA, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENSAT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENVT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Toulouse, France
| | - Sébastien Fritz
- INRA, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- AgroParisTech, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- Union Nationale des Coopératives Agricoles d’Elevage et d’Insémination Animale, Paris, France
| | - Franck Samson
- INRA, UR1077, Mathématique Informatique et Génome, Domaine de Vilvert, Jouy-en-Josas, France
| | - Cécile Grohs
- INRA, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- AgroParisTech, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
| | - Maria Bernard
- INRA, SIGENAE, UR 875, INRA Auzeville, BP 52627, Castanet-Tolosan, France
| | - Christophe Klopp
- INRA, SIGENAE, UR 875, INRA Auzeville, BP 52627, Castanet-Tolosan, France
| | - Didier Boichard
- INRA, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- AgroParisTech, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
| | - Dominique Rocha
- INRA, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- AgroParisTech, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
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7
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Liao X, Peng F, Forni S, McLaren D, Plastow G, Stothard P. Whole genome sequencing of Gir cattle for identifying polymorphisms and loci under selection. Genome 2013; 56:592-8. [DOI: 10.1139/gen-2013-0082] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Genetic variation in Gir cattle (Bos indicus) has so far not been well characterized. In this study, we used whole genome sequencing of three Gir bulls and a pooled sample from another 11 bulls to identify polymorphisms and loci under selection. A total of 9 990 733 single nucleotide polymorphisms (SNPs) and 604 308 insertion/deletions (indels) were discovered in Gir samples, of which 62.34% and 83.62%, respectively, are previously unknown. Moreover, we detected 79 putative selective sweeps using the sequence data of the pooled sample. One of the most striking sweeps harbours several genes belonging to the cathelicidin gene family, such as CAMP, CATHL1, CATHL2, and CATHL3, which are related to pathogen- and parasite-resistance. Another interesting region harbours genes encoding mitogen-activated protein kinases, which are involved in directing cellular responses to a variety of stimuli, such as osmotic stress and heat shock. These findings are particularly interesting because Gir is resistant to hot temperatures and tropical diseases. This initial selective sweep analysis of Gir cattle has revealed a number of loci that could be important for their adaptation to tropical climates.
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Affiliation(s)
- Xiaoping Liao
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G2P5, Canada
| | - Fred Peng
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G2P5, Canada
| | - Selma Forni
- Genus plc, 100 Bluegrass Commons Boulevard, Suite 2200, Hendersonville, TN 37075, USA
| | | | - Graham Plastow
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G2P5, Canada
| | - Paul Stothard
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G2P5, Canada
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8
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Genotyping-by-sequencing (GBS): a novel, efficient and cost-effective genotyping method for cattle using next-generation sequencing. PLoS One 2013; 8:e62137. [PMID: 23690931 PMCID: PMC3656875 DOI: 10.1371/journal.pone.0062137] [Citation(s) in RCA: 133] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2012] [Accepted: 03/19/2013] [Indexed: 12/21/2022] Open
Abstract
High-throughput genotyping methods have increased the analytical power to study complex traits but high cost has remained a barrier for large scale use in animal improvement. We have adapted genotyping-by-sequencing (GBS) used in plants for genotyping 47 animals representing 7 taurine and indicine breeds of cattle from the US and Africa. Genomic DNA was digested with different enzymes, ligated to adapters containing one of 48 unique bar codes and sequenced by the Illumina HiSeq 2000. PstI was the best enzyme producing 1.4 million unique reads per animal and initially identifying a total of 63,697 SNPs. After removal of SNPs with call rates of less than 70%, 51,414 SNPs were detected throughout all autosomes with an average distance of 48.1 kb, and 1,143 SNPs on the X chromosome at an average distance of 130.3 kb, as well as 191 on unmapped contigs. If we consider only the SNPs with call rates of 90% and over, we identified 39,751 on autosomes, 850 on the X chromosome and 124 on unmapped contigs. Of these SNPs, 28,843 were not tightly linked to other SNPs. Average marker density per autosome was highly correlated with chromosome size (coefficient of correlation = −0.798, r2 = 0.637) with higher density in smaller chromosomes. Average SNP call rate was 86.5% for all loci, with 53.0% of the loci having call rates >90% and the average minor allele frequency being 0.212. Average observed heterozygosity ranged from 0.046–0.294 among individuals, and from 0.064–0.197 among breeds, with Brangus showing the highest diversity as expected. GBS technique is novel, flexible, sufficiently high-throughput, and capable of providing acceptable marker density for genomic selection or genome-wide association studies at roughly one third of the cost of currently available genotyping technologies.
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9
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Harrison BE, Bunch RJ, McCulloch R, Williams P, Sim W, Corbet NJ, Barendse W. The structure of a cattle stud determined using a medium density single nucleotide polymorphism array. ANIMAL PRODUCTION SCIENCE 2012. [DOI: 10.1071/an11267] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Genetic progress depends on accurate knowledge of the genetic composition of a population or herd including level of inbreeding and parentage. However, in many circumstances, such as at an individual property level, the relationships between animals may be unknown, or at best, only partly known. In this study, we used DNA from 938 animals and genotypes from ~54 000 single nucleotide polymorphisms (SNP) to determine the genetic structure of a stud from Central Queensland. Animals on the study were bred using multi-sire mating in mobs of composite tropically adapted cattle of the Senepol, Belmont and Bonsmara breeds. Following genotyping using an array of 54 000 SNP, we were able to separate animals into breed groups using principal components and show that ~400 SNP were sufficient to separate animals into stable groups if the sample was genetically diverse. However, precise principal component values were only achieved when a few thousand SNP were used. We characterised the pedigree relationships between individuals using a genome relationship matrix. At least 3000 SNP were required to calculate accurate relationship coefficients between individuals. Around 19% of paired comparisons between animals showed similarity equivalent to sharing a great-grandparent or 1/64 shared ancestry. Approximately 8% of the individuals showed more than 10% inbreeding. To demonstrate the utility of calculating the relationship coefficients, we counted the tick burden on each animal at more than one time and then calculated the heritability of tick burden of h2 = 0.46 (±0.08). There was no significant genetic difference in tick burden between Belmont and Bonsmara cattle compared with Senepol on this property once a genetic relationship matrix was included to account for co-ancestry of individuals.
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