Stature is affected by many polymorphisms of small effect in humans . In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes. Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 × 10) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP-seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals.

BackgroundDuring the last decade, the use of common-variant array-based single nucleotide polymorphism (SNP) genotyping in the beef and dairy industries has produced an astounding amount of medium-to-low density genomic data. Although low-density assays work well in the context of genomic prediction, they are less useful for detecting and mapping causal variants and the effects of rare variants are not captured. The objective of this project was to maximize the accuracies of genotype imputation from medium- and low-density assays to the marker set obtained by combining two high-density research assays (~ 850,000 SNPs), the Illumina BovineHD and the GGP-F250 assays, which contains a large proportion of rare and potentially functional variants and for which the assay design is described here. This 850 K SNP set is useful for both imputation to sequence-level genotypes and direct downstream analysis.ResultsWe found that a large multi-breed composite imputation reference panel that includes 36,131 samples with either BovineHD and/or GGP-F250 genotypes significantly increased imputation accuracy compared with a within-breed reference panel, particularly at variants with low minor allele frequencies. Individual animal imputation accuracies were maximized when more genetically similar animals were represented in the composite reference panel, particularly with complete 850 K genotypes. The addition of rare variants from the GGP-F250 assay to our composite reference panel significantly increased the imputation accuracy of rare variants that are exclusively present on the BovineHD assay. In addition, we show that an assay marker density of 50 K SNPs balances cost and accuracy for imputation to 850 K.ConclusionsUsing high-density genotypes on all available individuals in a multi-breed reference panel maximized imputation accuracy for tested cattle populations. Admixed animals or those from breeds with a limited representation in the composite reference panel were still imputed at high accuracy, which is expected to further increase as the reference panel expands. We anticipate that the addition of rare variants from the GGP-F250 assay will increase the accuracy of imputation to sequence level.

BackgroundIf unmanaged, high rates of inbreeding in livestock populations adversely impact their reproductive fitness. In beef cattle, historical selection strategies have increased the frequency of several segregating fatal autosomal recessive polymorphisms. Selective breeding has also decreased the extent of haplotypic diversity genome-wide. By identifying haplotypes for which homozygotes are not observed but would be expected based on their frequency, candidates for developmentally lethal recessive loci can be localized. This analysis comes without the need for observation of the loss-associated phenotype (e.g., failure to implant, first trimester abortion, deformity at birth). In this study, haplotypes were estimated for 3961 registered Angus individuals using 52,545 SNP loci using findhap v2, which exploited the complex pedigree among the individuals in this population.ResultsSeven loci were detected to possess haplotypes that were not observed in homozygous form despite a sufficiently high frequency and pedigree-based expectation of homozygote occurrence. These haplotypes were identified as candidates for harboring autosomal recessive lethal alleles. Of the genotyped individuals, 109 were resequenced to an average 27X depth of coverage to identify putative loss-of-function alleles genome-wide and had variants called using a custom in-house developed pipeline. For the candidate lethal-harboring haplotypes present in these bulls, sequence-called genotypes were used to identify concordant variants. In addition, whole-genome sequence imputation of variants was performed into the set of 3961 genotyped animals using the 109 resequenced animals to identify candidate lethal recessive variants at the seven loci. Following the imputation, no variants were identified that were fully concordant with the marker-based diplotypes.ConclusionsSelective breeding programs could utilize the predicted lethal haplotypes associated with SNP genotypes. Sequencing and other methods for identifying the causal variants underlying these haplotypes can allow for more efficient methods of management such as gene editing. These two methods in total will reduce the negative impacts of inbreeding on fertility and maximize overall genetic gains.

Decreasing costs are making low coverage sequencing with imputation to a comprehensive reference panel an attractive alternative to obtain functional variant genotypes that can increase the accuracy of genomic prediction. To assess the potential of low-pass sequencing, genomic sequence of 77 steers sequenced to >10X coverage was downsampled to 1X and imputed to a reference of 946 cattle representing multiple Bos taurus and Bos indicus-influenced breeds. Genotypes for nearly 60 million variants detected in the reference were imputed from the downsampled sequence. The imputed genotypes strongly agreed with the SNP array genotypes (r¯=0.99) and the genotypes called from the transcript sequence (r¯=0.97). Effects of BovineSNP50 and GGP-F250 variants on birth weight, postweaning gain, and marbling were solved without the steers’ phenotypes and genotypes, then applied to their genotypes, to predict the molecular breeding values (MBV). The steers’ MBV were similar when using imputed and array genotypes. Replacing array variants with functional sequence variants might allow more robust MBV. Imputation from low coverage sequence offers a viable, low-cost approach to obtain functional variant genotypes that could improve genomic prediction.

Johne's disease is a contagious bacterial infection of cattle caused by ssp. (). A previous genome-wide association analysis (GWAA) in Holstein cattle identified QTL on BTA3 and BTA9 that were highly associated (P < 5 × 10) and on BTA1, BTA16, and BTA21 that were moderately associated (P < 5 × 10) with Map tissue infection. The objectives of this study were to validate previous GWAA results in Jersey cattle ( = 57), Holstein cattle from the Pacific Northwest (PNW, = 205) and a combined Holstein population from the PNW and the Northeast (PNW + NE, = 423), and also identify new loci associated with tissue infection. DNA was genotyped using the Illumina BovineSNP50 BeadChip, and the PNW + NE data was also imputed to whole genome sequence level using Run4 of the 1000 Bull Genomes project with Beagle v 4.1 and FImpute. Cases were ileocecal node positive and controls were negative for by quantitative PCR (qPCR). Individuals were removed for SNP call rate < 90%, and SNP were removed for genotype call rate < 90% or minor allele frequency < 1%. For the Jersey, PNW, and PNW + NE, GWAA were conducted using an allelic dosage model. For the PNW and the PNW + NE, an additional efficient mixed-model association eXpedited (EMMAX) analysis was performed using additive, dominance and recessive models. Seven QTL on BTA22 were identified in the Jersey population with the most significant ( = 4.45 × 10) located at 21.7 megabases (Mb). Six QTL were associated in the PNW and the PNW + NE analyses, including a QTL previously identified on BTA16 in the NE population. The most significant locus for the PNW was located on BTA21 at 61 Mb ( = 8.61 × 10) while the most significant locus for the PNW + NE was on BTA12 at 90 Mb ( = 2.33 × 10). No additional QTL were identified with the imputed GWAA. Putative positional candidate genes were identified within 50 kb 5' and 3' of each QTL. Two positional candidate genes were identified in Jersey cattle, 1 identified in the PNW and 8 in the PNW + NE populations. Many identified positional candidate genes are involved in signal transduction, have immunological functions, or have putative functional relevance in entry into host cells. This study supported 2 previously identified SNP within a QTL on BTA16 and identified 16 new QTL, including 2 found in the PNW and the PNW+NE, associated with tissue infection.