Σάββατο 30 Σεπτεμβρίου 2017

Deciphering signature of selection affecting beef quality traits in Angus cattle

Abstract

Artificial selection towards a desired phenotype/trait has modified the genomes of livestock dramatically that generated breeds that greatly differ in morphology, production and environmental adaptation traits. Angus cattle are among the famous cattle breeds developed for superior beef quality. This paper aimed at exploring genomic regions under selection in Angus cattle that are associated with meat quality traits and other associated phenotypes. The whole genome of 10 Angus cattle was compared with 11 Hanwoo (A-H) and 9 Jersey (A-J) cattle breeds using a cross-population composite likelihood ratio (XP-CLR) statistical method. The top 1% of the empirical distribution was taken as significant and annotated using UMD3.1. As a result, 255 and 210 genes were revealed under selection from A–H and A–J comparisons, respectively. The WebGestalt gene ontology analysis resulted in sixteen (A–H) and five (A–J) significantly enriched KEGG pathways. Several pathways associated with meat quality traits (insulin signaling, type II diabetes mellitus pathway, focal adhesion pathway, and ECM-receptor interaction), and feeding efficiency (olfactory transduction, tight junction, and metabolic pathways) were enriched. Genes affecting beef quality traits (e.g., FABP3, FTO, DGAT2, ACS, ACAA2, CPE, TNNI1), stature and body size (e.g., PLAG1, LYN, CHCHD7, RPS20), fertility and dystocia (e.g., ESR1, RPS20, PPP2R1A, GHRL, PLAG1), feeding efficiency (e.g., PIK3CD, DNAJC28, DNAJC3, GHRL, PLAG1), coat color (e.g., MC1-R) and genetic disorders (e.g., ITGB6, PLAG1) were found to be under positive selection in Angus cattle. The study identified genes and pathways that are related to meat quality traits and other phenotypes of Angus cattle. The findings in this study, after validation using additional or independent dataset, will provide useful information for the study of Angus cattle in particular and beef cattle in general.



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