Genomic prediction of reproduction traits for Merino sheep

Economically important reproduction traits in sheep, such as number of lambs weaned and litter size, are expressed only in females and later in life after most selection decisions are made, which makes them ideal candidates for genomic selection. Accurate genomic predictions would lead to greater genetic gain for these traits by enabling accurate selection of young rams with high genetic merit. The aim of this study was to design and evaluate the accuracy of a genomic prediction method for female reproduction in sheep using daughter trait deviations (DTD) for sires and ewe phenotypes (when individual ewes were genotyped) for three reproduction traits: number of lambs born (NLB), litter size (LSIZE) and number of lambs weaned. Genomic best linear unbiased prediction (GBLUP), BayesR and pedigree BLUP analyses of the three reproduction traits measured on 5340 sheep (4503 ewes and 837 sires) with real and imputed genotypes for 510 174 SNPs were performed. The prediction of breeding values using both sire and ewe trait records was validated in Merino sheep. Prediction accuracy was evaluated by across sire family and random cross‐validations. Accuracies of genomic estimated breeding values (GEBVs) were assessed as the mean Pearson correlation adjusted by the accuracy of the input phenotypes. The addition of sire DTD into the prediction analysis resulted in higher accuracies compared with using only ewe records in genomic predictions or pedigree BLUP. Using GBLUP, the average accuracy based on the combined records (ewes and sire DTD) was 0.43 across traits, but the accuracies varied by trait and type of cross‐validations. The accuracies of GEBVs from random cross‐validations (range 0.17–0.61) were higher than were those from sire family cross‐validations (range 0.00–0.51). The GEBV accuracies of 0.41–0.54 for NLB and LSIZE based on the combined records were amongst the highest in the study. Although BayesR was not significantly different from GBLUP in prediction accuracy, it identified several candidate genes which are known to be associated with NLB and LSIZE. The approach provides a way to make use of all data available in genomic prediction for traits that have limited recording.     

Evidence for pleiotropism and recent selection in the PLAG1 region in Australian Beef cattle

A putative functional mutation (rs109231213) near PLAG1 (BTA14) associated with stature was studied in beef cattle. Data from 8199 Bos taurus, Bos indicus and Tropical Composite cattle were used to test the associations between rs109231213 and various phenotypes. Further, 23 496 SNPs located on BTA14 were tested for association with these phenotypes, both independently and fitted together with rs109231213. The C allele of rs109231213 significantly increased hip height, weight, net food intake, age at puberty in males and females and decreased IGF‐I concentration in blood and fat depth. When rs109231213 was fitted as a fixed effect in the model, there was an overall reduction in associations between other SNPs and these traits but some SNPs remained associated (P < 10^?4). Frequency of the mutant C allele of rs109231213 differed among B. indicus (0.52), B. taurus (0.96) and Tropical Composite (0.68). Most chromosomes carrying the C allele had the same surrounding 10 SNP haplotype, probably because the C allele was introgressed into Brahman from B. taurus cattle. A region of reduced heterozygosity surrounds the C allele; this is small in B. taurus but 20 Mb long in Brahmans, indicating recent and strong selection for the mutant allele. Thus, the C allele appears to mark a mutation that has been selected almost to fixation in the B. taurus breeds studied here and introduced into Brahman cattle during grading up and selected to a frequency of 0.52 despite its negative effects on fertility.