Comparing Methods to Select Candidates for Re-Genotyping to Impute Higher-Density Genotype Data in a Japanese Black Cattle Population: A Case Study.

As optimization methods to identify the best animals for dense genotyping to construct a reference population for genotype imputation, the MCA and MCG methods, which use the pedigree-based additive genetic relationship matrix (A matrix) and the genomic relationship matrix (G matrix), respectively, have been proposed. We assessed the performance of MCA and MCG methods using 575 Japanese Black cows. Pedigree data were provided to trace back up to five generations to construct the A matrix with changing the pedigree depth from 1 to 5 (five MCA methods). Genotype information on 36,426 single-nucleotide polymorphisms was used to calculate the G matrix based on VanRaden's methods 1 and 2 (two MCG methods). The MCG always selected one cow per iteration, while MCA sometimes selected multiple cows. The number of commonly selected cows between the MCA and MCG methods was generally lower than that between different MCA methods or between different MCG methods. For the studied population, MCG appeared to be more reasonable than MCA in selecting cows as a reference population for higher-density genotype imputation to perform genomic prediction and a genome-wide association study.

Single-Step Genomic Prediction of Superovulatory Response Traits in Japanese Black Donor Cows.

We assessed the performance of single-step genomic prediction of breeding values for superovulatory response traits in Japanese Black donor cows. A total of 25,332 records of the total number of embryos and oocytes (TNE) and the number of good embryos (NGE) per flush for 1874 Japanese Black donor cows were collected during 2008 and 2022. Genotype information on 36,426 autosomal single-nucleotide polymorphisms (SNPs) for 575 out of the 1,874 cows was used. Breeding values were predicted exploiting a two-trait repeatability animal model. Two genetic relationship matrices were used, one based on pedigree information (A matrix) and the other considering both pedigree and SNP marker genotype information (H matrix). Estimated heritabilities of TNE and NGE were 0.18 and 0.11, respectively, when using the H matrix, which were both slightly lower than when using the A matrix (0.26 for TNE and 0.16 for NGE). Estimated genetic correlations between the traits were 0.61 and 0.66 when using H and A matrices, respectively. When the variance components were the same in breeding value prediction, the mean reliability was greater when using the H matrix than when using the A matrix. This advantage seems more prominent for cows with low reliability when using the A matrix. The results imply that introducing single-step genomic prediction could boost the rate of genetic improvement of superovulatory response traits, but efforts should be made to maintain genetic diversity when performing selection.

Bayesian estimation of genetic parameters for superovulatory response traits in Japanese Black donor cows using count data models.

We estimated genetic parameters for two in vivo embryo production-related superovulatory response traits-total number of embryos and oocytes (TNE) and number of good embryos (NGE)-in Japanese Black donor cows through Bayesian count regression analysis. We used 20,257 records of superovulation treatments from 1546 Japanese Black cows, with 1102 (5.4%) zero-count records for TNE and 3533 (17.4%) for NGE. Two generalized mixed linear models (MLMs; repeatability animal models)-Poisson (POI) and zero-inflated Poisson (ZIP) regression models-were fitted to the untransformed phenotypic records. A Gaussian MLM was also fitted to untransformed phenotypic records (GAU), natural log-transformed records (LOG), and records with Anscombe's variance stabilizing transformation (ANS). The estimated heritabilities and repeatabilities of TNE were 0.30 and 0.43 by POI, 0.35 and 0.47 by ZIP, 0.27 and 0.36 by GAU, 0.21 and 0.31 by LOG, and 0.24 and 0.35 by ANS, respectively. Those of NGE were 0.29 and 0.36 by POI, 0.31 and 0.40 by ZIP, 0.18 and 0.25 by GAU, 0.19 and 0.24 by LOG, and 0.20 and 0.25 by ANS, respectively. Under the ZIP, the estimated heritabilities and repeatabilities of the probability of zero counts were 0.43 and 0.71 for TNE and 0.42 and 0.51 for NGE, respectively, and the rank correlations between estimated breeding values of the 1546 donor cows for superovulation response and those for the probability of zero count were around -0.40 for TNE and -0.50 for NGE.

Genetic relationship between superovulatory response traits and carcass traits in Japanese Black cattle.

We estimated the genetic correlations between superovulatory response traits and carcass traits in Japanese Black cattle. As regards the superovulatory response traits in cows, we analyzed the phenotypic records of the total number of embryos and oocytes (TNE) and the number of good embryos (NGE) collected from 1532 donors between 2008 and 2018. As regards the carcass traits in fattened animals, we analyzed the phenotypic records for cold carcass weight, rib eye area, rib thickness, subcutaneous fat thickness, estimated yield percent, and marbling score for 1448 progenies derived from 596 donors and slaughtered between 2004 and 2020. Variance components were estimated using single-trait and two-trait animal models and the restricted maximum likelihood approach. The estimated genetic correlations with the carcass traits ranged from -0.05 to 0.04 for TNE and from -0.14 to 0.04 for NGE, and their standard errors ranged from 0.10 to 0.14. These results imply that the genetic relationship between the superovulatory response traits in Japanese Black donor cows and the carcass traits in their fattened progenies was weak to negligible. Therefore, we concluded that selecting donors with superior genetic ability for superovulatory responses would not have antagonistic effects on carcass performance in their fattened progenies.