Genome and chromosome wide association studies for growth traits in Simmental and Simbrah cattle
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Objective: The objective of this study was to perform genome (genome wide association studies [GWAS]) and chromosome (CWAS) wide association analyses to identify single nucleotide polymorphisms (SNPs) associated with growth traits in registered Simmental and Simbrah cattle. Methods: The phenotypes were deregressed BLUP EBVs for birth weight, weaning weight direct, weaning weight maternal, and yearling weight. The genotyping was performed with the GGP Bovine 150k chip. After the quality control analysis, 105,129 autosomal SNP from 967 animals (473 Simmental and 494 Simbrah) were used to carry out genotype association tests. The two association analyses were performed per breed and using combined information of the two breeds. The SNP associated with growth traits were mapped to their corresponding genes at 100 kb on either side. Results: A difference in magnitude of posterior probabilities was found across breeds between genome and chromosome wide association analyses. A total of 110, 143, and 302 SNP were associated with GWAS and CWAS for growth traits in the Simmental-, Simbrahand joint -data analyses, respectively. It stands out from the enrichment analysis of the pathways for RNA polymerase (POLR2G, POLR3E) and GABAergic synapse (GABRR1, GABRR3) for Simmental cattle and p53 signaling pathway (BID, SERPINB5) for Simbrah cattle. Conclusion: Only 6,265% of the markers associated with growth traits were found using CWAS and GWAS. The associated markers using the CWAS analysis, which were not associated using the GWAS, represents information that due to the model and priors was not associated with the traits.
Abstract
Objective: The objective of this study was to perform genome (genome wide association studies [GWAS]) and chromosome (CWAS) wide association analyses to identify single nucleotide polymorphisms (SNPs) associated with growth traits in registered Simmental and Simbrah cattle. Methods: The phenotypes were deregressed BLUP EBVs for birth weight, weaning weight direct, weaning weight maternal, and yearling weight. The genotyping was performed with the GGP Bovine 150k chip. After the quality control analysis, 105,129 autosomal SNP from 967 animals (473 Simmental and 494 Simbrah) were used to carry out genotype association tests. The two association analyses were performed per breed and using combined information of the two breeds. The SNP associated with growth traits were mapped to their corresponding genes at 100 kb on either side. Results: A difference in magnitude of posterior probabilities was found across breeds between genome and chromosome wide association analyses. A total of 110, 143, and 302 SNP were associated with GWAS and CWAS for growth traits in the Simmental-, Simbrahand joint -data analyses, respectively. It stands out from the enrichment analysis of the pathways for RNA polymerase (POLR2G, POLR3E) and GABAergic synapse (GABRR1, GABRR3) for Simmental cattle and p53 signaling pathway (BID, SERPINB5) for Simbrah cattle. Conclusion: Only 6,265% of the markers associated with growth traits were found using CWAS and GWAS. The associated markers using the CWAS analysis, which were not associated using the GWAS, represents information that due to the model and priors was not associated with the traits.
참고문헌 (45)
- Barwick SA, "Development successes and issues for the future in deriving and applying selection indexes for beef breeding", Aust J Exp Agric, 45, pp.923~933 (2005)[DOI]
- Buzanskas ME, "Genome-wide association for growth traits in Canchim beef cattle", PLoS One, 9, pp.e94802~ (2014)[DOI]
- Buzanskas ME, "Genetic associations between stayability and reproductive and growth traits in Canchim beef cattle", Livest Sci, 132, pp.107~112 (2010)[DOI]
- Baldi F, "Random regression models on Legendre polynomials to estimate genetic parameters for weights from birth to adult age in Canchim cattle", J Anim Breed Genet, 127, pp.289~299 (2010)[DOI]
- Terakado APN, "Genomewide association study for growth traits in Nelore cattle", Animal, 12, pp.1358~1362 (2018)[DOI]
- Biegelmeyer P, "Linkage disequilibrium, persistence of phase and effective population size estimates in Hereford and Braford cattle", BMC Genet, 17, pp.32~ (2016)[DOI]
- Prakapenka D, "A large-scale genome-wide association study of epistasis effects of production traits and daughter pregnancy rate in u. S. Holstein cattle", Genes(Basel), 12, pp.1089~ (2021)[DOI]
- Garrick DJ, "Deregressing estimated breeding values and weighting information for genomic regression analyses", Genet Sel Evol, 41, pp.55~ (2009)[DOI]
- Brooks SP, "General methods for monitoring convergence of iterative simulations", J Comput Graph Stat, 7, pp.434~455 (1998)[DOI]
- Akanno EC, "Genome-wide association scan for heterotic quantitative trait loci in multibreed and crossbred beef cattle", Genet Sel Evol, 50, pp.48~ (2018)[DOI]
- Wilson MA, "Bayesian model search and multilevel inference for SNP association studies", Ann Appl Stat, 4, pp.1342~1364 (2010)[DOI]
- Villa-Angulo R, "High-resolution haplotype block structure in the cattle genome", BMC Genet, 10, pp.19~ (2009)[DOI]
- Gibbs RA, "Genome-wide survey of SNP variation uncovers the genetic structure of cattle breeds", Science, 324, pp.528~532 (2009)[DOI]
- Porto-Neto LR, "The extent of linkage disequilibrium in beef cattle breeds using high-density SNP genotypes", Genet Sel Evol, 46, pp.22~ (2014)[DOI]
- Cañas-Álvarez JJ, "Linkage disequilibrium, persistence of phase, and effective population size in Spanish local beef cattle breeds assessed through a high-density single nucleotide polymorphism chip", J Anim Sci, 94, pp.2779~2788 (2016)[DOI]
- den Berg S, "Significance testing and genomic inflation factor using high-density genotypes or whole-genome sequence data", J Anim Breed Genet, 136, pp.418~429 (2019)[DOI]
- Ball RD, "Methods in molecular biology Vol. 1019", pp.37~98 (2013), Humana Press Inc
- Clyde M, "Model uncertainty", Statist Sci, 19, pp.81~94 (2004)[DOI]
- Cheung SH, "Calculation of posterior probabilities for bayesian model class assessment and averaging from posterior samples based on dynamic system data", Comput Civ Infrastruct Eng, 25, pp.304~321 (2010)[DOI]
- Duggal P, "Establishing an adjusted p-value threshold to control the family-wide type 1 error in genome wide association studies", BMC Genomics, 9, pp.516~ (2008)[DOI]
- Nicodemus KK, "Comparison of type I error for multiple test corrections in large single-nucleotide polymorphism studies using principal components versus haplotype blocking algorithms", BMC Genet, 6, pp.S78~ (2005)[DOI]
- Paim TP, "Dynamics of genomic architecture during composite breed development in cattle", Anim Genet, 51, pp.224~234 (2020)[DOI]
- Tang J, "The genetic mechanism of high prolificacy in small tail han sheep by comparative proteomics of ovaries in the follicular and luteal stages", J Proteomics, 204, pp.103394~ (2019)[DOI]
- Peñagaricano F, "Maternal nutrition induces gene expression changes in fetal muscle and adipose tissues in sheep", BMC Genomics, 15, pp.1034~ (2014)[DOI]
- Zhang L, "Genome-wide association study of body weight traits in Inner Mongolia cashmere goats", Front Vet Sci, 8, pp.752746~ (2021)[DOI]
- Lee SH, "QTL and gene expression analyses identify genes affecting carcass weight and marbling on BTA14 in Hanwoo(Korean Cattle)", Mamm Genome, 22, pp.589~ (2011)[DOI]
- Iung LHS, "Genomic regions underlying uniformity of yearling weight in Nellore cattle evaluated under different response variables", BMC Genomics, 19, pp.619~ (2018)[DOI]
- Weng Z, "Genome-wide association study of growth and body composition traits in Brangus beef cattle", Livest Sci, 183, pp.4~11 (2016)[DOI]
- Londoño-Gil M, "Genome-wide association study for growth traits in blanco orejinero(bon)cattle from Colombia", Livest Sci, 243, pp.104366~ (2021)[DOI]
- Lau LY, "Gene regulation could be attributed to TCF3 and other key transcription factors in the muscle of pubertal heifers", Vet Med Sci, 6, pp.695~710 (2020)[DOI]
- Kireeva ML, "RNA polymerase structure, function, regulation, dynamics, fidelity, and roles in gene expression", Chem Rev, 113, pp.8325~8330 (2013)[DOI]
- Agrawal A, "Prepartal energy intake alters blood polymorphonuclear leukocyte transcriptome during the peripartal period in Holstein cows", Bioinform Biol Insights, 11, pp.1~17 (2017)[DOI]
- Fan H, "Pathway-based genome-wide association studies for two meat production traits in Simmental cattle", Sci Rep, 5, pp.18389~ (2016)[DOI]
- Seoane JR, "Effects of intraventricular injections of gamma-aminobutyric acid and related substances on feeding behavior in satiated sheep", Can J Physiol Pharmacol, 62, pp.1296~1299 (1984)[DOI]
- 윤준, "Multi-tissue observation of the long non-coding RNA effects on sexually biased gene expression in cattle", Animal Bioscience, 32(7), pp.1044~1051 (2019), 아세아·태평양축산학회[DOI]
- Sun Y, "Comparative proteomics of whey and milk fat globule membrane proteins of Guanzhong goat and Holstein cow mature milk", J Food Sci, 84, pp.244~253 (2019)[DOI]
- Zhang Z, "Identifying the complex genetic architecture of growth and fatness traits in a Duroc pig population", J Integr Agric, 20, pp.1607~1614 (2021)[DOI]
- Martínez R, "Genome-wide association study on growth traits in Colombian creole breeds and crossbreeds with Zebu cattle", Genet Mol Res, 13, pp.6420~6432 (2014)[DOI]
- Santana MHA, "Genomewide association study for feedlot average daily gain in Nellore cattle(Bos indicus)", J Anim Breed Genet, 131, pp.210~216 (2014)[DOI]
- Yang Y, "Proteasome activity and expression of mammalian target of rapamycin signaling factors in skeletal muscle of dairy cows supplemented with conjugated linoleic acids during early lactation", J Dairy Sci, 103, pp.2829~2846 (2020)[DOI]
- Saatchi M, "Large-effect pleiotropic or closely linked QTL segregate within and across ten US cattle breeds", BMC Genomics, 15, pp.442~ (2014)[DOI]
- Abi Habib W, "Genetic disruption of the oncogenic HMGA2–PLAG1–IGF2 pathway causes fetal growth restriction", Genet Med, 20, pp.250~258 (2018)[DOI]
- Lee SH, "Genome-Wide Association Study Identifies Major Loci for Carcass Weight on BTA14in Hanwoo(Korean Cattle)", PLoS One, 8, pp.e74677~ (2013)[DOI]
- Fortes MRS, "Association weight matrix for the genetic dissection of puberty in beef cattle", Proc Natl Acad Sci, 107, pp.13642~13647 (2010)[DOI]
- Morris CA, "Genetic parameters for growth, puberty, and beef cow reproductive traits in a puberty selection experiment", NZ J Agric Res, 43, pp.83~91 (2000)[DOI]
