|Thallman, Richard - Mark|
Submitted to: Journal of Animal Science Supplement
Publication Type: Abstract only
Publication Acceptance Date: 3/2/2013
Publication Date: 7/20/2013
Citation: Snelling, W.M., Bennett, G.L., Thallman, R.M., Lindholm-Perry, A.K., Kuehn, L.A., McDaneld, T.G., Kachman, S.D., Spangler, M.L., Koshinsky, H., Kalbfleisch, T.S., Pollak, E.J. 2013. Prioritizing sequence polymorphisms for potential association with phenotype [abstract]. Journal of Animal Science. 91(E-Supplement 2):74-75. Interpretive Summary:
Technical Abstract: The millions of SNP, insertions and deletions revealed by next generation sequencing (NGS), are certain to include polymorphisms responsible for phenotypic variation. Distinguishing causal from benign variants may allow genomic predictions that are robust across populations. While variants underlying phenotypic variation may never be known with certainty, classifying NGS variants according to expected effects on gene function may reveal likely candidates. Associations between phenotypes and available genotypes of markers flanking each variant may further indicate those likely to affect phenotype through altered gene function. Low-coverage NGS of 96 sires used in a 7-breed population of crossbred beef cattle revealed 10,028,578 variants. 1,309 were classified as having a high impact on protein coding genes, and 1,503 occurred in non-coding RNA, which may regulate protein coding genes. Potential impact of these variants on birth weight was assessed using 2,940 birth weight records from the 7-breed population, 3,812 records from a somewhat related 16-breed population, and imputed high-density SNP genotypes for both populations. Genomic heritability estimates (SE) in the 7-breed population were 0.38 (0.03) with 3,810 SNP flanking the high-impact and non-coding RNA variants, 0.25 (0.02) with 291 SNP surrounding 217 variants with the largest flanking SNP effects, 0.64 (0.03) with the full set of high-density SNP, and 0.38 (0.05) for the 300 high-density SNP with the largest effects. Genetic correlations between 16-breed birth weights and genomic EBV predicted from 7-breed SNP effects were 0.42 (0.05) for the 3,810 SNP and 0.58 (0.05) for the 291 SNP around selected variants. Estimated birth weight-genomic EBV genetic correlations were 0.51 (0.04) for all high-density SNP and 0.48 (0.05) for the top 300. Genomic predictions with SNP flanking variants affecting gene function may be more robust than predictions based only on associations with phenotype. Further assessment of direct genotypes for the functional variants is needed.