Carcass Phenotypes Research Articles

Evaluation of Simmental carcass EPD estimated using live and carcass data.

This study was conducted to compare carcass EPD predicted using yearling live animal data and/or progeny carcass data, and to quantify the association between the carcass phenotype of progeny and the sire EPD. The live data model (L) included scan weight, ultrasound fat thickness, longissimus muscle area, and percentage of intramuscular fat from yearling (369 d of age) Simmental bulls and heifers. The carcass data model (C) included hot carcass weight, fat thickness, longissimus muscle area, and marbling score from Simmental-sired steers and cull heifers (453 d of age). The combined data model (F) included live animal and carcass data as separate but correlated traits. All data and pedigree information on 39,566 animals were obtained from the American Simmental Association, and all EPD were predicted using animal model procedures. The genetic model included fixed effects of contemporary group and a linear covariate for age at measurement, and a random animal genetic effect. The EPD from L had smaller variance and range than those from either C or F. Further, EPD from F had highest average accuracy. Correlations indicated that evaluations from C and F were most similar, and L would significantly (P < 0.05) re-rank sires compared with models including carcass data. Progeny (n = 824) with carcass data collected subsequent to evaluation were used to quantify the association between progeny phenotype and sire EPD using a model including contemporary group, and linear regressions for age at slaughter and the appropriate sire EPD. The regression coefficient was generally improved for sire EPD from L when genetic regression was used to scale EPD to the appropriate carcass trait basis. The EPD from C and F had similar linear associations with progeny phenotype, although EPD from F may be considered optimal because of increased accuracy. These data suggest that carcass EPD based on a combination of live and carcass data predict differences in progeny phenotype at or near theoretical expectation.

Candidate gene analysis of GH1 for effects on growth and carcass composition of cattle.

We present an approach to evaluate the support for candidate genes as quantitative trait loci (QTLs) within the context of genome-wide map-based cloning strategies. To establish candidacy, a bacterial artificial chromosome (BAC) clone containing a putative candidate gene is physically assigned to an anchored linkage map to localise the gene relative to an identified QTL effect. Microsatellite loci derived from BAC clones containing an established candidate gene are integrated into the linkage map facilitating the evaluation by interval analysis of the statistical support for QTL identity. Permutation analysis is employed to determine experiment-wise statistical support. The approach is illustrated for the growth hormone 1 (GH1) gene and growth and carcass phenotypes in cattle. Polymerase chain reaction (PCR) primers which amplify a 441 bp fragment of GH1 were used to systematically screen a bovine BAC library comprising 60,000 clones and with a 95% probability of containing a single copy sequence. The presence of GH1 in BAC-110R2C3 was confirmed by sequence analysis of the PCR product from this clone and by the physical assignment of BAC110R2C3 to bovine chromosome 19 (BTA19) band 22 by fluorescence in situ hybridisation (FISH). Microsatellite KHGH1 was isolated from BAC110R2C3 and scored in 529 reciprocal backcross and F2 fullsib progeny from 41 resource families derived from Angus (Bos taurus) and Brahman (Bos indicus). The microsatellite KHGH1 was incorporated into a framework genetic map of BTA19 comprising 12 microsatellite loci, the erythrocyte antigen T and a GH1-TaqI restriction fragment length polymorphism (RFLP). Interval analysis localised effects of taurus vs. indicus alleles on subcutaneous fat and the percentage of either extractable fat from the Iongissimus dorsi muscle to the region of BTA19 harbouring GH1.