Cold exposure impacts DNA methylation patterns in cattle sperm.

DNA methylation is influenced by various exogenous factors such as nutrition, temperature, toxicants, and stress. Bulls from the Pacific Northwest region of the United States and other northern areas are exposed to extreme cold temperatures during winter. However, the effects of cold exposure on the methylation patterns of bovine sperm remain unclear. To address, DNA methylation profiles of sperm collected during late spring and winter from the same bulls were analyzed using whole genome bisulfite sequencing (WGBS). Bismark (0.22.3) were used for mapping the WGBS reads and R Bioconductor package DSS was used for differential methylation analysis. Cold exposure induced 3,163 differentially methylated cytosines (DMCs) with methylation difference ≥10% and a q-value < 0.05. We identified 438 differentially methylated regions (DMRs) with q-value < 0.05, which overlapped with 186 unique genes. We also identified eight unique differentially methylated genes (DMGs) (Pax6, Macf1, Mest, Ubqln1, Smg9, Ctnnb1, Lsm4, and Peg10) involved in embryonic development, and nine unique DMGs (Prmt6, Nipal1, C21h15orf40, Slc37a3, Fam210a, Raly, Rgs3, Lmbr1, and Gan) involved in osteogenesis. Peg10 and Mest, two paternally expressed imprinted genes, exhibited >50% higher methylation. The differential methylation patterns of six distinct DMRs: Peg10, Smg9 and Mest related to embryonic development and Lmbr1, C21h15orf40 and Prtm6 related to osteogenesis, were assessed by methylation-specific PCR (MS-PCR), which confirmed the existence of variable methylation patterns in those locations across the two seasons. In summary, cold exposure induces differential DNA methylation patterns in genes that appear to affect embryonic development and osteogenesis in the offspring. Our findings suggest the importance of replicating the results of the current study with a larger sample size and exploring the potential of these changes in affecting offspring development.

Genome wide association study of passive immunity and disease traits in beef-suckler and dairy calves on Irish farms.

Calves with lower concentrations of immunoglobulin G (IgG) in their blood, have a greater risk of developing diseases. There is a lack of knowledge on genetic markers known to be associated with immunological variability or disease resistance. Therefore, the objective of this study was to identify SNP markers associated with passive immunity measures (serum IgG, serum protein, albumin, globulin and total protein concentrations, total solids Brix percentage, zinc sulphate turbidity units) and disease (pneumonia, diarrhoea, crude illness) traits in Irish commercial beef-suckler and dairy calves through genome wide association studies (GWAS). Genotyping was performed on DNA samples from beef-suckler (n = 698) and dairy (n = 1178) calves, using the IDBv3 chip. Heritability of passive immunity associated traits (range 0.02-0.22) and the disease traits (range 0.03-0.20) were low-to-moderate. Twenty-five and fifteen SNPs approached genome wide significance (P < 5 × 10-5) for the passive immunity and the disease traits, respectively. One SNP "ARS-BFGL-BAC-27914" reached Bonferroni genome wide significance (P < 1.15 × 10-6) for an association with serum IgG concentration in beef calves. Further work will evaluate these SNPs in larger cattle populations and assess their contribution to genomic selection breeding strategies, aimed towards producing more disease resistant livestock.

Analysis of a large dataset reveals haplotypes carrying putatively recessive lethal and semi-lethal alleles with pleiotropic effects on economically important traits in beef cattle.

BACKGROUND: In livestock, deleterious recessive alleles can result in reduced economic performance of homozygous individuals in multiple ways, e.g. early embryonic death, death soon after birth, or semi-lethality with incomplete penetrance causing reduced viability. While death is an easy phenotype to score, reduced viability is not as easy to identify. However, it can sometimes be observed as reduced conception rates, longer calving intervals, or lower survival for live born animals. METHODS: In this paper, we searched for haplotypes that carry putatively recessive lethal or semi-lethal alleles in 132,725 genotyped Irish beef cattle from five breeds: Aberdeen Angus, Charolais, Hereford, Limousin, and Simmental. We phased the genotypes in sliding windows along the genome and used five tests to identify haplotypes with absence of or reduced homozygosity. Then, we associated the identified haplotypes with 44,351 insemination records that indicated early embryonic death, and postnatal survival records. Finally, we assessed haplotype pleiotropy by estimating substitution effects on estimates of breeding value for 15 economically important traits in beef production. RESULTS: We found support for one haplotype that carries a putatively recessive lethal (chromosome 16 in Simmental) and two haplotypes that carry semi-lethal alleles (chromosome 14 in Aberdeen Angus and chromosome 19 in Charolais), with population frequencies of 8.8, 15.2, and 14.4%, respectively. These three haplotypes showed pleiotropic effects on economically important traits for beef production. Their allele substitution effects are €2.30, €3.42, and €1.47 for the terminal index and €1.03, - €3.11, and - €0.88 for the replacement index, where the standard deviations for the terminal index are €22.52, €18.65, and €22.70 and for the replacement index they are €31.35, €29.82, and €35.79. We identified ZFAT as the candidate gene for semi-lethality in Aberdeen Angus, several candidate genes for the lethal Simmental haplotype, and no candidate genes for the semi-lethal Charolais haplotype. CONCLUSIONS: We analysed genotype, reproduction, survival, and production data to detect haplotypes that carry putatively recessive lethal or semi-lethal alleles in Irish beef cattle and identified one lethal and two semi-lethal haplotypes, which have pleiotropic effects on economically important traits in beef production.

GWAS and eQTL analysis identifies a SNP associated with both residual feed intake and GFRA2 expression in beef cattle.

Residual feed intake (RFI), a measure of feed efficiency, is an important economic and environmental trait in beef production. Selection of low RFI (feed efficient) cattle could maintain levels of production, while decreasing feed costs and methane emissions. However, RFI is a difficult and expensive trait to measure. Identification of single nucleotide polymorphisms (SNPs) associated with RFI may enable rapid, cost effective genomic selection of feed efficient cattle. Genome-wide association studies (GWAS) were conducted in multiple breeds followed by meta-analysis to identify genetic variants associated with RFI and component traits (average daily gain (ADG) and feed intake (FI)) in Irish beef cattle (n = 1492). Expression quantitative trait loci (eQTL) analysis was conducted to identify functional effects of GWAS-identified variants. Twenty-four SNPs were associated (P < 5 × 10-5) with RFI, ADG or FI. The variant rs43555985 exhibited strongest association for RFI (P = 8.28E-06). An eQTL was identified between this variant and GFRA2 (P = 0.0038) where the allele negatively correlated with RFI was associated with increased GFRA2 expression in liver. GFRA2 influences basal metabolic rates, suggesting a mechanism by which genetic variation may contribute to RFI. This study identified SNPs that may be useful both for genomic selection of RFI and for understanding the biology of feed efficiency.

SNP Data Quality Control in a National Beef and Dairy Cattle System and Highly Accurate SNP Based Parentage Verification and Identification.

A major use of genetic data is parentage verification and identification as inaccurate pedigrees negatively affect genetic gain. Since 2012 the international standard for single nucleotide polymorphism (SNP) verification in Bos taurus cattle has been the ISAG SNP panels. While these ISAG panels provide an increased level of parentage accuracy over microsatellite markers (MS), they can validate the wrong parent at ≤1% misconcordance rate levels, indicating that more SNP are needed if a more accurate pedigree is required. With rapidly increasing numbers of cattle being genotyped in Ireland that represent 61 B. taurus breeds from a wide range of farm types: beef/dairy, AI/pedigree/commercial, purebred/crossbred, and large to small herd size the Irish Cattle Breeding Federation (ICBF) analyzed different SNP densities to determine that at a minimum ≥500 SNP are needed to consistently predict only one set of parents at a ≤1% misconcordance rate. For parentage validation and prediction ICBF uses 800 SNP (ICBF800) selected based on SNP clustering quality, ISAG200 inclusion, call rate (CR), and minor allele frequency (MAF) in the Irish cattle population. Large datasets require sample and SNP quality control (QC). Most publications only deal with SNP QC via CR, MAF, parent-progeny conflicts, and Hardy-Weinberg deviation, but not sample QC. We report here parentage, SNP QC, and a genomic sample QC pipelines to deal with the unique challenges of >1 million genotypes from a national herd such as SNP genotype errors from mis-tagging of animals, lab errors, farm errors, and multiple other issues that can arise. We divide the pipeline into two parts: a Genotype QC and an Animal QC pipeline. The Genotype QC identifies samples with low call rate, missing or mixed genotype classes (no BB genotype or ABTG alleles present), and low genotype frequencies. The Animal QC handles situations where the genotype might not belong to the listed individual by identifying: >1 non-matching genotypes per animal, SNP duplicates, sex and breed prediction mismatches, parentage and progeny validation results, and other situations. The Animal QC pipeline make use of ICBF800 SNP set where appropriate to identify errors in a computationally efficient yet still highly accurate method.

Genome-wide association study and ancestral origins of the slick-hair coat in tropically adapted cattle.

The slick hair coat (SLICK) is a dominantly inherited trait typically associated with tropically adapted cattle that are from Criollo descent through Spanish colonization of cattle into the New World. The trait is of interest relative to climate change, due to its association with improved thermo-tolerance and subsequent increased productivity. Previous studies localized the SLICK locus to a 4 cM region on chromosome (BTA) 20 and identified signatures of selection in this region derived from Senepol cattle. The current study compares three slick-haired Criollo-derived breeds including Senepol, Carora, and Romosinuano and three additional slick-haired cross-bred lineages to non-slick ancestral breeds. Genome-wide association (GWA), haplotype analysis, signatures of selection, runs of homozygosity (ROH), and identity by state (IBS) calculations were used to identify a 0.8 Mb (37.7-38.5 Mb) consensus region for the SLICK locus on BTA20 in which contains SKP2 and SPEF2 as possible candidate genes. Three specific haplotype patterns are identified in slick individuals, all with zero frequency in non-slick individuals. Admixture analysis identified common genetic patterns between the three slick breeds at the SLICK locus. Principal component analysis (PCA) and admixture results show Senepol and Romosinuano sharing a higher degree of genetic similarity to one another with a much lesser degree of similarity to Carora. Variation in GWA, haplotype analysis, and IBS calculations with accompanying population structure information supports potentially two mutations, one common to Senepol and Romosinuano and another in Carora, effecting genes contained within our refined location for the SLICK locus.

Bovine exome sequence analysis and targeted SNP genotyping of recessive fertility defects BH1, HH2, and HH3 reveal a putative causative mutation in SMC2 for HH3.

The recent discovery of bovine haplotypes with negative effects on fertility in the Brown Swiss, Holstein, and Jersey breeds has allowed producers to identify carrier animals using commercial single nucleotide polymorphism (SNP) genotyping assays. This study was devised to identify the causative mutations underlying defective bovine embryo development contained within three of these haplotypes (Brown Swiss haplotype 1 and Holstein haplotypes 2 and 3) by combining exome capture with next generation sequencing. Of the 68,476,640 sequence variations (SV) identified, only 1,311 genome-wide SNP were concordant with the haplotype status of 21 sequenced carriers. Validation genotyping of 36 candidate SNP identified only 1 variant that was concordant to Holstein haplotype 3 (HH3), while no variants located within the refined intervals for HH2 or BH1 were concordant. The variant strictly associated with HH3 is a non-synonymous SNP (T/C) within exon 24 of the Structural Maintenance of Chromosomes 2 (SMC2) on Chromosome 8 at position 95,410,507 (UMD3.1). This polymorphism changes amino acid 1135 from phenylalanine to serine and causes a non-neutral, non-tolerated, and evolutionarily unlikely substitution within the NTPase domain of the encoded protein. Because only exome capture sequencing was used, we could not rule out the possibility that the true causative mutation for HH3 might lie in a non-exonic genomic location. Given the essential role of SMC2 in DNA repair, chromosome condensation and segregation during cell division, our findings strongly support the non-synonymous SNP (T/C) in SMC2 as the likely causative mutation. The absence of concordant variations for HH2 or BH1 suggests either the underlying causative mutations lie within a non-exomic region or in exome regions not covered by the capture array.

Imputation of microsatellite alleles from dense SNP genotypes for parentage verification across multiple Bos taurus and Bos indicus breeds.

To assist cattle producers transition from microsatellite (MS) to single nucleotide polymorphism (SNP) genotyping for parental verification we previously devised an effective and inexpensive method to impute MS alleles from SNP haplotypes. While the reported method was verified with only a limited data set (N = 479) from Brown Swiss, Guernsey, Holstein, and Jersey cattle, some of the MS-SNP haplotype associations were concordant across these phylogenetically diverse breeds. This implied that some haplotypes predate modern breed formation and remain in strong linkage disequilibrium. To expand the utility of MS allele imputation across breeds, MS and SNP data from more than 8000 animals representing 39 breeds (Bos taurus and B. indicus) were used to predict 9410 SNP haplotypes, incorporating an average of 73 SNPs per haplotype, for which alleles from 12 MS markers could be accurately be imputed. Approximately 25% of the MS-SNP haplotypes were present in multiple breeds (N = 2 to 36 breeds). These shared haplotypes allowed for MS imputation in breeds that were not represented in the reference population with only a small increase in Mendelian inheritance inconsistancies. Our reported reference haplotypes can be used for any cattle breed and the reported methods can be applied to any species to aid the transition from MS to SNP genetic markers. While ~91% of the animals with imputed alleles for 12 MS markers had ≤1 Mendelian inheritance conflicts with their parents' reported MS genotypes, this figure was 96% for our reference animals, indicating potential errors in the reported MS genotypes. The workflow we suggest autocorrects for genotyping errors and rare haplotypes, by MS genotyping animals whose imputed MS alleles fail parentage verification, and then incorporating those animals into the reference dataset.

Identification of a nonsense mutation in CWC15 associated with decreased reproductive efficiency in Jersey cattle.

With the recent advent of genomic tools for cattle, several recessive conditions affecting fertility have been identified and selected against, such as deficiency of uridine monophosphate synthase, complex vertebral malformation, and brachyspina. The current report refines the location of a recessive haplotype affecting fertility in Jersey cattle using crossover haplotypes, discovers the causative mutation using whole genome sequencing, and examines the gene's role in embryo loss. In an attempt to identify unknown recessive lethal alleles in the current dairy population, a search using deep Mendelian sampling of 5,288 Jersey cattle was conducted for high-frequency haplotypes that have a deficit of homozygotes at the population level. This search led to the discovery of a putative recessive lethal in Jersey cattle on Bos taurus autosome 15. The haplotype, denoted JH1, was associated with reduced fertility, and further investigation identified one highly-influential Jersey bull as the putative source ancestor. By combining SNP analysis of whole-genome sequences aligned to the JH1 interval and subsequent SNP validation a nonsense mutation in CWC15 was identified as the likely causative mutation underlying the fertility phenotype. No homozygous recessive individuals were found in 749 genotyped animals, whereas all known carriers and carrier haplotypes possessed one copy of the mutant allele. This newly identified lethal has been responsible for a substantial number of spontaneous abortions in Jersey dairy cattle throughout the past half-century. With the mutation identified, selection against the deleterious allele in breeding schemes will aid in reducing the incidence of this defect in the population. These results also show that carrier status can be imputed with high accuracy. Whole-genome resequencing proved to be a powerful strategy to rapidly identify a previously mapped deleterious mutation in a known carrier of a recessive lethal allele.

A novel analytical method, Birth Date Selection Mapping, detects response of the Angus (Bos taurus) genome to selection on complex traits.

BACKGROUND: Several methods have recently been developed to identify regions of the genome that have been exposed to strong selection. However, recent theoretical and empirical work suggests that polygenic models are required to identify the genomic regions that are more moderately responding to ongoing selection on complex traits. We examine the effects of multi-trait selection on the genome of a population of US registered Angus beef cattle born over a 50-year period representing approximately 10 generations of selection. We present results from the application of a quantitative genetic model, called Birth Date Selection Mapping, to identify signatures of recent ongoing selection. RESULTS: We show that US Angus cattle have been systematically selected to alter their mean additive genetic merit for most of the 16 production traits routinely recorded by breeders. Using Birth Date Selection Mapping, we estimate the time-dependency of allele frequency for 44,817 SNP loci using genomic best linear unbiased prediction, generalized least squares, and BayesCπ analyses. Finally, we reconstruct the primary phenotypes that have historically been exposed to selection from a genome-wide analysis of the 16 production traits and gene ontology enrichment analysis. CONCLUSIONS: We demonstrate that Birth Date Selection Mapping utilizing mixed models corrects for time-dependent pedigree sampling effects that lead to spurious SNP associations and reveals genomic signatures of ongoing selection on complex traits. Because multiple traits have historically been selected in concert and most quantitative trait loci have small effects, selection has incrementally altered allele frequencies throughout the genome. Two quantitative trait loci of large effect were not the most strongly selected of the loci due to their antagonistic pleiotropic effects on strongly selected phenotypes. Birth Date Selection Mapping may readily be extended to temporally-stratified human or model organism populations.

Impact of reduced marker set estimation of genomic relationship matrices on genomic selection for feed efficiency in Angus cattle.

BACKGROUND: Molecular estimates of breeding value are expected to increase selection response due to improvements in the accuracy of selection and a reduction in generation interval, particularly for traits that are difficult or expensive to record or are measured late in life. Several statistical methods for incorporating molecular data into breeding value estimation have been proposed, however, most studies have utilized simulated data in which the generated linkage disequilibrium may not represent the targeted livestock population. A genomic relationship matrix was developed for 698 Angus steers and 1,707 Angus sires using 41,028 single nucleotide polymorphisms and breeding values were estimated using feed efficiency phenotypes (average daily feed intake, residual feed intake, and average daily gain) recorded on the steers. The number of SNPs needed to accurately estimate a genomic relationship matrix was evaluated in this population. RESULTS: Results were compared to estimates produced from pedigree-based mixed model analysis of 862 Angus steers with 34,864 identified paternal relatives but no female ancestors. Estimates of additive genetic variance and breeding value accuracies were similar for AFI and RFI using the numerator and genomic relationship matrices despite fewer animals in the genomic analysis. Bootstrap analyses indicated that 2,500-10,000 markers are required for robust estimation of genomic relationship matrices in cattle. CONCLUSIONS: This research shows that breeding values and their accuracies may be estimated for commercially important sires for traits recorded in experimental populations without the need for pedigree data to establish identity by descent between members of the commercial and experimental populations when at least 2,500 SNPs are available for the generation of a genomic relationship matrix.

Resolving the evolution of extant and extinct ruminants with high-throughput phylogenomics.

The Pecorans (higher ruminants) are believed to have rapidly speciated in the Mid-Eocene, resulting in five distinct extant families: Antilocapridae, Giraffidae, Moschidae, Cervidae, and Bovidae. Due to the rapid radiation, the Pecoran phylogeny has proven difficult to resolve, and 11 of the 15 possible rooted phylogenies describing ancestral relationships among the Antilocapridae, Giraffidae, Cervidae, and Bovidae have each been argued as representations of the true phylogeny. Here we demonstrate that a genome-wide single nucleotide polymorphism (SNP) genotyping platform designed for one species can be used to genotype ancient DNA from an extinct species and DNA from species diverged up to 29 million years ago and that the produced genotypes can be used to resolve the phylogeny for this rapidly radiated infraorder. We used a high-throughput assay with 54,693 SNP loci developed for Bos taurus taurus to rapidly genotype 678 individuals representing 61 Pecoran species. We produced a highly resolved phylogeny for this diverse group based upon 40,843 genome-wide SNP, which is five times as many informative characters as have previously been analyzed. We also establish a method to amplify and screen genomic information from extinct species, and place Bison priscus within the Bovidae. The quality of genotype calls and the placement of samples within a well-supported phylogeny may provide an important test for validating the fidelity and integrity of ancient samples. Finally, we constructed a phylogenomic network to accurately describe the relationships between 48 cattle breeds and facilitate inferences concerning the history of domestication and breed formation.

Assessment of DNA extracted from FTA cards for use on the Illumina iSelect BeadChip.

BACKGROUND: As FTA cards provide an ideal medium for the field collection of DNA we sought to assess the quality of genomic DNA extracted from this source for use on the Illumina BovineSNP50 iSelect BeadChip which requires unbound, relatively intact (fragment sizes >or= 2 kb), and high-quality DNA. Bovine blood and nasal swab samples collected on FTA cards were extracted using the commercially available GenSolve kit with a minor modification. The call rate and concordance of genotypes from each sample were compared to those obtained from whole blood samples extracted by standard PCI extraction. FINDINGS: An ANOVA analysis indicated no significant difference (P > 0.72) in BovineSNP50 genotype call rate between DNA extracted from FTA cards by the GenSolve kit or extracted from whole blood by PCI. Two sample t-tests demonstrated that the DNA extracted from the FTA cards produced genotype call and concordance rates that were not different to those produced by assaying DNA samples extracted by PCI from whole blood. CONCLUSION: We conclude that DNA extracted from FTA cards by the GenSolve kit is of sufficiently high quality to produce results comparable to those obtained from DNA extracted from whole blood when assayed by the Illumina iSelect technology. Additionally, we validate the use of nasal swabs as an alternative to venous blood or buccal samples from animal subjects for reliably producing high quality genotypes on this platform.