Accounting for genomic pre-selection in national BLUP evaluations in dairy cattle

<p>Abstract</p> <p>Background</p> <p>In future Best Linear Unbiased Prediction (BLUP) evaluations of dairy cattle, genomic selection of young sires will cause evaluation biases and loss of accuracy once the selected ones get progeny.</p> <p>Methods</p> <p>To avoid such bias in the estimation of breeding values, we propose to include information on all genotyped bulls, including the culled ones, in BLUP evaluations. Estimated breeding values based on genomic information were converted into genomic pseudo-performances and then analyzed simultaneously with actual performances. Using simulations based on actual data from the French Holstein population, bias and accuracy of BLUP evaluations were computed for young sires undergoing progeny testing or genomic pre-selection. For bulls pre-selected based on their genomic profile, three different types of information can be included in the BLUP evaluations: (1) data from pre-selected genotyped candidate bulls with actual performances on their daughters, (2) data from bulls with both actual and genomic pseudo-performances, or (3) data from all the genotyped candidates with genomic pseudo-performances. The effects of different levels of heritability, genomic pre-selection intensity and accuracy of genomic evaluation were considered.</p> <p>Results</p> <p>Including information from all the genotyped candidates, i.e. genomic pseudo-performances for both selected and culled candidates, removed bias from genetic evaluation and increased accuracy. This approach was effective regardless of the magnitude of the initial bias and as long as the accuracy of the genomic evaluations was sufficiently high.</p> <p>Conclusions</p> <p>The proposed method can be easily and quickly implemented in BLUP evaluations at the national level, although some improvement is necessary to more accurately propagate genomic information from genotyped to non-genotyped animals. In addition, it is a convenient method to combine direct genomic, phenotypic and pedigree-based information in a multiple-step procedure.</p

A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation

<p>Abstract</p> <p>Background</p> <p>Efficient, robust, and accurate genotype imputation algorithms make large-scale application of genomic selection cost effective. An algorithm that imputes alleles or allele probabilities for all animals in the pedigree and for all genotyped single nucleotide polymorphisms (SNP) provides a framework to combine all pedigree, genomic, and phenotypic information into a single-stage genomic evaluation.</p> <p>Methods</p> <p>An algorithm was developed for imputation of genotypes in pedigreed populations that allows imputation for completely ungenotyped animals and for low-density genotyped animals, accommodates a wide variety of pedigree structures for genotyped animals, imputes unmapped SNP, and works for large datasets. The method involves simple phasing rules, long-range phasing and haplotype library imputation and segregation analysis.</p> <p>Results</p> <p>Imputation accuracy was high and computational cost was feasible for datasets with pedigrees of up to 25 000 animals. The resulting single-stage genomic evaluation increased the accuracy of estimated genomic breeding values compared to a scenario in which phenotypes on relatives that were not genotyped were ignored.</p> <p>Conclusions</p> <p>The developed imputation algorithm and software and the resulting single-stage genomic evaluation method provide powerful new ways to exploit imputation and to obtain more accurate genetic evaluations.</p

Lambs with Scrapie Susceptible Genotypes Have Higher Postnatal Survival

BACKGROUND: Prion protein (PrP) alleles associated with scrapie susceptibility persist in many sheep populations even with high frequencies despite centuries of selection against them. This suggests that scrapie susceptibility alleles have a pleiotropic effect or are associated with fitness or other traits that have been subject to selection. METHODOLOGY/PRINCIPAL FINDINGS: We genotyped all lambs in two scrapie-free Scottish Blackface sheep flocks for polymorphisms at codons 136, 154 and 171 of the PrP gene. We tested potential associations of the PrP genotype with lamb viability at birth and postnatal survival using a complementary log-log link function and a Weibull proportional hazard model, respectively. Here we show there is an association between PrP genotype, as defined by polymorphisms at codons 154 ad 171, and postnatal lamb survival in the absence of scrapie. Sheep carrying the wild-type ARQ allele have higher postnatal survival rates than sheep carrying the more scrapie-resistant alleles (ARR or AHQ). CONCLUSION: The PrP genotypes associated with higher susceptibility to scrapie are associated with improved postnatal survival in the absence of the disease. This association helps to explain the existence, and in many instances the high frequency, of the ARQ allele in sheep populations