Molecular value predictions: Associations with beef quality, carcass, production, behavior, and efficiency phenotypes in Brahman cattle1

Abstract

Data from 2 previously published experiments, New South Wales (NSW; n = 161) and Western Australia (WA; n = 135), were used to test molecular value predictions (MVP), generated from commercially available gene markers, on economically important traits of Bos indicus (Brahman) cattle. Favorable tenderness MVP scores were associated with reduced shear force values of strip loin (LM) steaks aged 7 d from Achilles-hung carcasses (P ≤ 0.06), as well as steaks aged 1 (P ≤ 0.08) or 7 d (P ≤ 0.07) from carcasses hung from the pelvis (tenderstretch). Favorable tenderness MVP scores were also associated with improved consumer tenderness ratings for strip loin steaks aged 7 d and either Achilles hung (P ≤ 0.006) or tenderstretched (P ≤ 0.07). Similar results were observed in NSW for rump (top butt; gluteus medius) steaks, with favorable tenderness MVP scores associated with more tender (P = 0.006) and acceptable (P = 0.008) beef. Favorable marbling MVP scores were associated with improved (P ≤ 0.021) marbling scores and intramuscular fat (IMF) content in the NSW experiment, despite low variation in marbling in the Brahman cattle. For the WA experiment, however, there were no (P ≥ 0.71) relationships between marbling MVP and marbling scores or IMF content. Although residual (net) feed intake (RFI) was not associated (P = 0.63) with the RFI (feed efficiency) MVP, the RFI MVP was adversely associated with LM tenderness and acceptability of 7-d-aged Achilles-hung carcasses in NSW (P ≤ 0.031) and WA (P ≤ 0.037). Some other relationships and trends were noted between the MVP and the other traits, but few reached statistical significance, and none were evident in both experiments. Results from this study provide evidence to support the use of the tenderness MVP. The value of the marbling MVP, which was associated with marbling in only 1 herd, warrants further evaluation; however, there appears to be no evidence to support use of the RFI MVP in Brahman cattle.

Integrating Genomics with Nutrition Models to Improve the Prediction of Cattle Performance and Carcass Composition under Feedlot Conditions

“…The stepwise regression of ΔADG HH or ΔADG CT on MBV and leptin genotypes yielded inconsistent relationships with little explanatory capacity, suggesting that either the CVDS model was not able to accurately predict ADG or there is little effect of the evaluated MBV and leptin genotype on ADG. The lack of correlation between ADG and MBV is consistent with previously reported values [ 20 ]. It seems that the MBV and leptin genotypes may influence the composition of the gain [ 47 ], not the ADG per se.…”

“…The MBV BTRFI had more significant correlations with input and output variables than the MBV AllRFI . Significant correlations between marbling MBV and marbling scores or intramuscular fat have been reported [ 20 ], suggesting that MBV scores can reliably be used to identify differences in carcass traits they were originally intended for. Thus, the correlations between MBV REA and model input and output variables are expected to hold across different scenarios of production.…”

“…Hence, the information of genetic predisposition for growth and development could be useful in improving the accuracy in determining the shrunk BW ( SBW ) at 28% empty body fat ( AFSBW ) for individuals. The use of commercial single nucleotide polymorphism ( SNP ) panels to predict animal performance and carcass traits have yielded promising, but yet yields variable, results [ 18 – 20 ]. It is possible that coefficients of complex model parameters may contain unexplained genetic variation [ 21 ]; thus, unbiased coefficients could be obtained if genetic variation is explicitly accounted for.…”

A post-transcriptional mechanism regulates calpastatin expression in bovine skeletal muscle1

“…The experiments were primarily designed to assess the effects of calpain-system gene markers (CAST,CAPN3, and molecular value predictions (MVP) on production and beef quality characteristics, as well as identify interactions of the gene markers with production (sex and hormonal growth promotant [HGP] implantation) and processing (carcass suspension, muscle, and duration of the postmortem aging period) effects in Brahman cattle (Cafe et al, 2010a;Robinson et al, 2012;Greenwood et al, 2013). Information on marker status was used to select Brahman cattle to achieve divergence in the number of favorable alleles for the CAST and CAPN3 markers, with the groups being as balanced as possible for the CAPN1-4751 marker.…”