Literature DB >> 29471369

Genome-wide association study of Stayability and Heifer Pregnancy in Red Angus cattle.

S E Speidel1, B A Buckley2, R J Boldt1, R M Enns1, J Lee3, M L Spangler3, M G Thomas1.   

Abstract

Reproductive performance is the most important component of cattle production from the standpoint of economic sustainability of commercial beef enterprises. Heifer Pregnancy (HPG) and Stayability (STAY) genetic predictions are 2 selection tools published by the Red Angus Association of America (RAAA) to assist with improvements in reproductive performance. Given the importance of HPG and STAY to the profitability of commercial beef enterprises, the objective of this study was to identify QTL associated with both HPG and STAY in Red Angus cattle. A genome-wide association study (GWAS) was performed using deregressed HPG and STAY EBV, calculated using a single-trait animal model and a 3-generation pedigree with data from the Spring 2015 RAAA National Cattle Evaluation. Each individual animal possessed 74,659 SNP genotypes. Individual animals with a deregressed EBV reliability > 0.05 were merged with the genotype file and marker quality control was performed. Criteria for sifting genotypes consisted of removing those markers where any of the following were found: average call rate less than 0.85, minor allele frequency < 0.01, lack of Hardy-Weinberg equilibrium (P < 0.0001), or extreme linkage disequilibrium (r2 > 0.99). These criteria resulted in 2,664 animals with 62,807 SNP available for GWAS. Association studies were performed using a Bayes Cπ model in the BOLT software package. Marker significance was calculated as the posterior probability of inclusion (PPI), or the number of instances a specific marker was sampled divided by the total number of samples retained from the Markov chain Monte Carlo chains. Nine markers, with a PPI ≥ 3% were identified as QTL associated with HPG on BTA 1, 11, 13, 23, and 29. Twelve markers, with a PPI ≥ 75% were identified as QTL associated with STAY on BTA 6, 8, 9, 12, 15, 18, 22, and 23.

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Year:  2018        PMID: 29471369      PMCID: PMC6093520          DOI: 10.1093/jas/sky041

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  24 in total

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2.  The impact of training strategies on the accuracy of genomic predictors in United States Red Angus cattle.

Authors:  J Lee; S D Kachman; M L Spangler
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8.  Analyzes of genome-wide association follow-up study for calving traits in dairy cattle.

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Authors:  Aleksey V Zimin; Arthur L Delcher; Liliana Florea; David R Kelley; Michael C Schatz; Daniela Puiu; Finnian Hanrahan; Geo Pertea; Curtis P Van Tassell; Tad S Sonstegard; Guillaume Marçais; Michael Roberts; Poorani Subramanian; James A Yorke; Steven L Salzberg
Journal:  Genome Biol       Date:  2009-04-24       Impact factor: 13.583

10.  Sequence to Medical Phenotypes: A Framework for Interpretation of Human Whole Genome DNA Sequence Data.

Authors:  Frederick E Dewey; Megan E Grove; James R Priest; Daryl Waggott; Prag Batra; Clint L Miller; Matthew Wheeler; Amin Zia; Cuiping Pan; Konrad J Karzcewski; Christina Miyake; Michelle Whirl-Carrillo; Teri E Klein; Somalee Datta; Russ B Altman; Michael Snyder; Thomas Quertermous; Euan A Ashley
Journal:  PLoS Genet       Date:  2015-10-08       Impact factor: 5.917

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Journal:  Genes (Basel)       Date:  2019-11-06       Impact factor: 4.096

  1 in total

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