Location: Genetics, Breeding, & Animal Health
Title: Selection enhanced estimates of µ-calpain, calpastatin, and diacylglycerol O-acyltransferase 1 genetic effects on pre-weaning performance, carcass quality traits, and residual variance of tenderness in composite ... cattle Authors
|Tait Jr, Richard|
Submitted to: World Congress of Genetics Applied in Livestock Production
Publication Type: Proceedings
Publication Acceptance Date: April 21, 2014
Publication Date: N/A
Interpretive Summary: Previous research has associated some genetic markers with beef carcass and meat tenderness traits. A population of cattle was selected to increase the frequencies of some less frequent markers. This allows better estimation of associations and a better determination of dominance and recessive modes of inheritance. Three marker systems were selected. Two marker systems (CAPN1 and CAST) have been associated with meat tenderness and one (DGAT1) with carcass fatness. CAPN1 and CAST verified previous associations showing additive differences in meat tenderness averages. CAST was also found to be associated with variation in meat tenderness. DGAT1 showed both dominant and additive genetic associations with carcass fat thickness and meat tenderness. A better understanding of genetic marker effects will be useful to breeders trying to change beef carcass and meat traits.
Technical Abstract: Selection of the composite MARC III population for markers allowed better estimates of effects and inheritance of markers for targeted carcass quality traits (n=254) and nontargeted traits and an evaluation of SNP specific residual variance models for tenderness. Genotypic effects of CAPN1 haplotypes (P=0.12) on LM slice shear force (SSF) were similar in direction and size to previous reports. Effects of divergent CAPN1 haplotypes (1.15 kg) and additive effects of CAST (0.90 kg; P=0.05) on SSF were large. Animals homozygous tender at both markers had 4.11 kg lower SSF than homozygous tough counterparts. The DGAT1 polymorphism affected fat thickness (P=0.02) and VISNIR predicted SSF (P<0.001), with both traits showing additive and dominance inheritance (P<0.05). Genotype specific residual variance models for CAST fit SSF better (P<0.001) than single residual variance models, with tougher genotypes having progressively larger residual (and hence phenotypic) variances.