This study investigated the reliability of genomic estimated breeding values (GEBV) in the Danish Holstein population. The data in the analysis included 3,330 bulls with both published conventional EBV and single nucleotide polymorphism (SNP) markers. After data editing, 38,134 SNP markers were available. In the analysis, all SNP were fitted simultaneously as random effects in a Bayesian variable selection model, which allows heterogeneous variances for different SNP markers. The response variables were the official EBV. Direct GEBV were calculated as the sum of individual SNP effects. Initial analyses of 4 index traits were carried out to compare models with different intensities of shrinkage for SNP effects; that is, mixture prior distributions of scaling factors (standard deviation of SNP effects) assuming 5, 10, 20, or 50% of SNP having large effects and the others having very small or no effects, and a single prior distribution common for all SNP. It was found that, in general, the model with a common prior distribution of scaling factors had better predictive ability than any mixture prior models. Therefore, a common prior model was used to estimate SNP effects and breeding values for all 18 index traits. Reliability of GEBV was assessed by squared correlation between GEBV and conventional EBV (r(2)(GEBV, EBV)), and expected reliability was obtained from prediction error variance using a 5-fold cross validation. Squared correlations between GEBV and published EBV (without any adjustment) ranged from 0.252 to 0.700, with an average of 0.418. Expected reliabilities ranged from 0.494 to 0.733, with an average of 0.546. Averaged over 18 traits, r(2)(GEBV, EBV) was 0.13 higher and expected reliability was 0.26 higher than reliability of conventional parent average. The results indicate that genomic selection can greatly improve the accuracy of preselection for young bulls compared with traditional selection based on parent average information.

The European bison (Bison bonasus) has recovered successfully after a severe bottleneck about 90 years ago but has been left with low genetic variability that may substantially hinder parentage and identity analysis. According to pedigree analysis, over 80% of the genes in the contemporary population descend from just two founder animals and inbreeding coefficients averaged almost 0.5, whereas microsatellite heterozygosity does not exceed 0.3. We present a comparison of the effectiveness of 17 microsatellite and 960 single nucleotide polymorphism (SNP) markers for paternity and identity analysis in the European bison. Microsatellite-based paternity and identity analysis was unsuccessful because of low marker heterozygosity and is not a practical approach in this species. Simulations using SNP markers suggest that 80-90 randomly selected loci, or just 50-60 of the most heterozygous loci, would be sufficient to ensure successful paternity and identity analysis in this species. For the purpose of standardizing future analysis, a panel of 50-60 bovine SNPs characterized by high heterozygosity and an even distribution in the genome could be selected. This panel of markers could be typed using VeraCode (Illumina) or similar SNP genotyping systems. The low cost of these SNP genotyping methods compared with a 16 locus microsatellite survey means that off-the-shelf SNP genotyping systems developed for domestic species represent powerful tools for genetic analysis in related species, and can be effective even in bottlenecked species in which heterozygosity of other markers such as microsatellites may be very low.

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BackgroundOver the last few years, continuous development of high-throughput sequencing platforms and sequence analysis tools has facilitated reliable identification and characterization of genetic variants in many cattle breeds. Deep sequencing of entire genomes within a cattle breed that has not been thoroughly investigated would be imagined to discover functional variants that are underlying phenotypic differences. Here, we sequenced to a high coverage the Danish Holstein cattle breed to detect and characterize single nucleotide polymorphisms (SNPs), insertion/deletions (Indels), and loss-of-function (LoF) variants in protein-coding genes in order to provide a comprehensive resource for subsequent detection of causal variants for recessive traits.ResultsWe sequenced four genetically unrelated Danish Holstein cows with a mean coverage of 27X using an Illumina Hiseq 2000. Multi-sample SNP calling identified 10,796,794 SNPs and 1,295,036 indels whereof 482,835 (4.5 %) SNPs and 231,359 (17.9 %) indels were novel. A comparison between sequencing-derived SNPs and genotyping from the BovineHD BeadChip revealed a concordance rate of 99.6–99.8 % for homozygous SNPs and 93.3–96.5 % for heterozygous SNPs. Annotation of the SNPs discovered 74,886 SNPs and 1937 indels affecting coding sequences with 2145 being LoF mutations. The frequency of LoF variants differed greatly across the genome, a hot spot with a strikingly high density was observed in a 6 Mb region on BTA18. LoF affected genes were enriched for functional categories related to olfactory reception and underrepresented for genes related to key cellular constituents and cellular and biological process regulation. Filtering using sequence derived genotype data for 288 Holstein animals from the 1000 bull genomes project removing variants containing homozygous individuals retained 345 of the LoF variants as putatively deleterious. A substantial number of the putative deleterious LoF variants had a minor allele frequency >0.05 in the 1000 bull genomes data set.ConclusionsDeep sequencing of Danish Holstein genomes enabled us to identify 12.1 million variants. An investigation into LoF variants discovered a set of variants predicted to disrupt protein-coding genes. This catalog of variants will be a resource for future studies to understand variation underlying important phenotypes, particularly recessively inherited lethal phenotypes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2249-y) contains supplementary material, which is available to authorized users.

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