RESOURCE DEVELOPMENT FACILITATING BOVINE GENOME SEQUENCE USE TO IMPROVE CATTLE PRODUCTION EFFICIENCY, PRODUCT QUALITY & ENVIRONMENTAL IMPACT
Location: Genetics, Breeding, & Animal Health
Title: Selection for genetic markers in beef cattle reveals complex associations of thyroglobulin and casein1-S1 with carcass and meat traits
Submitted to: Journal of Animal Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 16, 2012
Publication Date: February 1, 2013
Citation: Bennett, G.L., Shackelford, S.D., Wheeler, T.L., King, D.A., Casas, E., Smith, T.P. 2013. Selection for genetic markers in beef cattle reveals complex associations of thyroglobulin and casein1-S1 with carcass and meat traits. Journal of Animal Science. 91(2):565-571.
Interpretive Summary: Whether genetic markers have simple or complicated associations with beef cattle traits determines how genetic markers are best used. However, it is often difficult to determine if genetic markers have simple associations. All three genotypes (two copies of one form of the marker, two of the other form, or one of each form) are needed for accurate estimation but there are usually few animals with one of the genotypes. Two genetic markers that had been previously associated with carcass fatness were selected for two years to increase the frequencies of the rarer forms of each marker. This resulted in a more balanced distribution of genotypes for both markers and better estimates of their associations with growth, carcass, and meat traits. These genotypes were not associated with growth and most carcass traits measured. The markers did have complicated associations with fat depth and tenderness of meat as predicted at harvest by light reflectance. Although these types of complex associations would contribute little to within-herd selection response, they could be important for cattle management based on marker-predicted performance or for selection schemes based on crossbred performance.
Genetic markers in casein (CSN1S1) and thyroglobulin (TG) genes have previously been associated with fat distribution in cattle. Determining the nature of these genetic associations (additive, recessive, or dominant) has been difficult because both markers have small minor allele frequencies in most beef cattle populations. This results in few animals homozygous for the minor alleles. Selection to increase the frequencies of the minor alleles for two single nucleotide polymorphisms (SNP) markers in these genes was undertaken in a composite population. The objective was to obtain better estimates of genetic effects associated with these markers and to determine if there were epistatic interactions. Selection increased the frequencies of minor alleles for both SNP to 0.45 from less than 0.30. Bulls (n = 24) heterozygous for both SNP were used in 3 years to produce 204 steer progeny harvested at an average age of 474 d. The combined effect of the 9 CSN1S1 x TG genotypes was associated with carcass adjusted fat thickness (P = 0.06) and meat tenderness predicted at the abattoir by visible and near-infrared reflectance spectroscopy (P = 0.04). Genotype did not affect weights from birth through harvest, ribeye area, marbling score, slice shear force, or image based yield grade. Additive, dominance, and epistatic SNP association effects were estimated from genotypic effects for adjusted fat thickness and predicted meat tenderness. Adjusted fat thickness showed a dominance association with the TG SNP (P = 0.06) and an epistatic additive CSN1S1 x additive TG association (P = 0.03). For predicted meat tenderness, heterozygous TG meat was more tender than meat from either homozygote (P = 0.002). Dominance and epistatic associations can result in different SNP allele substitution effects in populations where SNP have the same linkage disequilibrium with causal mutations but have different frequencies. Although the complex associations estimated in this study would contribute little to within-population selection response, they could be important for marker-assisted management or for reciprocal selection schemes.