Identific tion of quantitative trait loci and associated candidate genes for pregnancy success in Angus–Brahman crossbred heifers

Background In beef cattle, more than 50% of the energy input to produce a unit of beef is consumed by the female that produced the calf. Development of genomic tools to identify females with high genetic merit for reproductive function could increase the profitability and sustainability of beef production.Results Genome-wide association studies(GWAS) were performed using a single-step genomic best linear unbiased prediction approach on pregnancy outcome traits from a population of Angus–Brahman crossbred heifers. Furthermore, a validation GWAS was performed using data from another farm. Heifers were genotyped with the Bovine GGP F250 array that contains 221,077 SNPs. In the discovery population, heifers were bred in winter breeding seasons involving a single round of timed artificial insemination(AI) followed by natural mating for 3 months. Two phenotypes were analyzed: pregnancy outcome to first-service AI(PAI;n = 1,481) and pregnancy status at the end of the breeding season(PEBS;n = 1,725). The heritability was estimated as 0.149 and 0.122 for PAI and PEBS, respectively. In the PAI model, one quantitative trait locus(QTL), located between 52.3 and 52.5 Mb on BTA7, explained about 3% of the genetic variation, in a region containing a cluster of γ-protocadherin genes and SLC25A2. Other QTLs explaining between 0.5% and 1% of the genetic variation were found on BTA12 and 25. In the PEBS model, a large QTL on BTA7 was synonymous with the QTL for PAI, with minor QTLs located on BTA5, 9, 10, 11, 19, and 20. The validation population for pregnancy status at the end of the breeding season were Angus–Brahman crossbred heifers bred by natural mating. In concordance with the discovery population, the large QTL on BTA7 and QTLs on BTA10 and 12 were identified.Conclusions In summary, QTLs and candidate SNPs identified were associated with pregnancy outcomes in beef heifers, including a large QTL associated with a group of protocadherin genes. Confirmation of these associations with larger populations could lead to the development of genomic predictions of reproductive function in beef cattle. Moreover, additional research is warranted to study the function of candidate genes associated with QTLs.

Comparison of methods for deriving phenotypes from incomplete observation data with an application to age at puberty in dairy cattle

Background Many phenotypes in animal breeding are derived from incomplete measures,especially if they are challenging or expensive to measure precisely.Examples include time-dependent traits such as reproductive status,or lifespan.Incomplete measures for these traits result in phenotypes that are subject to left-,interval-and rightcensoring,where phenotypes are only known to fall below an upper bound,between a lower and upper bound,or above a lower bound respectively.Here we compare three methods for deriving phenotypes from incomplete data using age at first elevation(>1 ng/mL)in blood plasma progesterone(AGEP4),which generally coincides with onset of puberty,as an example trait.Methods We produced AGEP4 phenotypes from three blood samples collected at about 30-day intervals from approximately 5,000 Holstein–Friesian or Holstein–Friesian×Jersey cross-bred dairy heifers managed in 54 seasonal-calving,pasture-based herds in New Zealand.We used these actual data to simulate 7 different visit scenarios,increasing the extent of censoring by disregarding data from one or two of the three visits.Three methods for deriving phenotypes from these data were explored:1)ordinal categorical variables which were analysed using categorical threshold analysis;2)continuous variables,with a penalty of 31 d assigned to right-censored phenotypes;and 3)continuous variables,sampled from within a lower and upper bound using a data augmentation approach.Results Credibility intervals for heritability estimations overlapped across all methods and visit scenarios,but estimated heritabilities tended to be higher when left censoring was reduced.For sires with at least 5 daughters,the correlations between estimated breeding values(EBVs)from our three-visit scenario and each reduced data scenario varied by method,ranging from 0.65 to 0.95.The estimated breed effects also varied by method,but breed differences were smaller as phenotype censoring increased.Conclusion Our results indicate that using some methods,phenotypes derived from one observation per offspring for a time-dependent trait such as AGEP4 may provide comparable sire rankings to three observations per offspring.This has implications for the design of large-scale phenotyping initiatives where animal breeders aim to estimate variance parameters and estimated breeding values(EBVs)for phenotypes that are challenging to measure or prohibitively expensive.