Overcoming Limitations to Deep Learning in Domesticated Animals with TrioTrain.

Variant calling across diverse species remains challenging as most bioinformatics tools default to assumptions based on human genomes. DeepVariant (DV) excels without joint genotyping while offering fewer implementation barriers. However, the growing appeal of a "universal" algorithm has magnified the unknown impacts when used with non-human genomes. Here, we use bovine genomes to assess the limits of human-genome-trained models in other species. We introduce the first multi-species DV model that achieves a lower Mendelian Inheritance Error (MIE) rate during single-sample genotyping. Our novel approach, TrioTrain, automates extending DV for species without Genome In A Bottle (GIAB) resources and uses region shuffling to mitigate barriers for SLURM-based clusters. To offset imperfect truth labels for animal genomes, we remove Mendelian discordant variants before training, where models are tuned to genotype the offspring correctly. With TrioTrain, we use cattle, yak, and bison trios to build 30 model iterations across five phases. We observe remarkable performance across phases when testing the GIAB human trios with a mean SNP F1 score >0.990. In HG002, our phase 4 bovine model identifies more variants at a lower MIE rate than DeepTrio. In bovine F1-hybrid genomes, our model substantially reduces inheritance errors with a mean MIE rate of 0.03 percent. Although constrained by imperfect labels, we find that multi-species, trio-based training produces a robust variant calling model. Our research demonstrates that exclusively training with human genomes restricts the application of deep-learning approaches for comparative genomics.

Uncovering the architecture of selection in two Bos taurus cattle breeds.

Directional selection alters the genome via hard sweeps, soft sweeps, and polygenic selection. However, mapping polygenic selection is difficult because it does not leave clear signatures on the genome like a selective sweep. In populations with temporally stratified genotypes, the Generation Proxy Selection Mapping (GPSM) method identifies variants associated with generation number (or appropriate proxy) and thus variants undergoing directional allele frequency changes. Here, we use GPSM on two large datasets of beef cattle to detect associations between an animal's generation and 11 million imputed SNPs. Using these datasets with high power and dense mapping resolution, GPSM detected a total of 294 unique loci actively under selection in two cattle breeds. We observed that GPSM has a high power to detect selection in the very recent past (<10 years), even when allele frequency changes are small. Variants identified by GPSM reside in genomic regions associated with known breed-specific selection objectives, such as fertility and maternal ability in Red Angus, and carcass merit and coat color in Simmental. Over 60% of the selected loci reside in or near (<50 kb) annotated genes. Using haplotype-based and composite selective sweep statistics, we identify hundreds of putative selective sweeps that likely occurred earlier in the evolution of these breeds; however, these sweeps have little overlap with recent polygenic selection. This makes GPSM a complementary approach to sweep detection methods when temporal genotype data are available. The selected loci that we identify across methods demonstrate the complex architecture of selection in domesticated cattle.

Genomic loci involved in sensing environmental cues and metabolism affect seasonal coat shedding in Bos taurus and Bos indicus cattle.

Seasonal shedding of winter hair at the start of summer is well studied in wild and domesticated populations. However, the genetic influences on this trait and their interactions are poorly understood. We use data from 13,364 cattle with 36,899 repeated phenotypes to investigate the relationship between hair shedding and environmental variables, single nucleotide polymorphisms, and their interactions to understand quantitative differences in seasonal shedding. Using deregressed estimated breeding values from a repeated records model in a genome-wide association analysis (GWAA) and meta-analysis of year-specific GWAA gave remarkably similar results. These GWAA identified hundreds of variants associated with seasonal hair shedding. There were especially strong associations between chromosomes 5 and 23. Genotype-by-environment interaction GWAA identified 1,040 day length-by-genotype interaction associations and 17 apparent temperature-by-genotype interaction associations with hair shedding, highlighting the importance of day length on hair shedding. Accurate genomic predictions of hair shedding were created for the entire dataset, Angus, Hereford, Brangus, and multibreed datasets. Loci related to metabolism and light-sensing have a large influence on seasonal hair shedding. This is one of the largest genetic analyses of a phenological trait and provides insight into both agriculture production and basic science.

The Bovine Pangenome Consortium: democratizing production and accessibility of genome assemblies for global cattle breeds and other bovine species.

The Bovine Pangenome Consortium (BPC) is an international collaboration dedicated to the assembly of cattle genomes to develop a more complete representation of cattle genomic diversity. The goal of the BPC is to provide genome assemblies and a community-agreed pangenome representation to replace breed-specific reference assemblies for cattle genomics. The BPC invites partners sharing our vision to participate in the production of these assemblies and the development of a common, community-approved, pangenome reference as a public resource for the research community ( https://bovinepangenome.github.io/ ). This community-driven resource will provide the context for comparison between studies and the future foundation for cattle genomic selection.

Genome-wide association and genotype by environment interactions for growth traits in U.S. Red Angus cattle.

BACKGROUND: Genotypic information produced from single nucleotide polymorphism (SNP) arrays has routinely been used to identify genomic regions associated with complex traits in beef and dairy cattle. Herein, we assembled a dataset consisting of 15,815 Red Angus beef cattle distributed across the continental U.S. and a union set of 836,118 imputed SNPs to conduct genome-wide association analyses (GWAA) for growth traits using univariate linear mixed models (LMM); including birth weight, weaning weight, and yearling weight. Genomic relationship matrix heritability estimates were produced for all growth traits, and genotype-by-environment (GxE) interactions were investigated. RESULTS: Moderate to high heritabilities with small standard errors were estimated for birth weight (0.51 ± 0.01), weaning weight (0.25 ± 0.01), and yearling weight (0.42 ± 0.01). GWAA revealed 12 pleiotropic QTL (BTA6, BTA14, BTA20) influencing Red Angus birth weight, weaning weight, and yearling weight which met a nominal significance threshold (P ≤ 1e-05) for polygenic traits using 836K imputed SNPs. Moreover, positional candidate genes associated with Red Angus growth traits in this study (i.e., LCORL, LOC782905, NCAPG, HERC6, FAM184B, SLIT2, MMRN1, KCNIP4, CCSER1, GRID2, ARRDC3, PLAG1, IMPAD1, NSMAF, PENK, LOC112449660, MOS, SH3PXD2B, STC2, CPEB4) were also previously associated with feed efficiency, growth, and carcass traits in beef cattle. Collectively, 14 significant GxE interactions were also detected, but were less consistent among the investigated traits at a nominal significance threshold (P ≤ 1e-05); with one pleiotropic GxE interaction detected on BTA28 (24 Mb) for Red Angus weaning weight and yearling weight. CONCLUSIONS: Sixteen well-supported QTL regions detected from the GWAA and GxE GWAA for growth traits (birth weight, weaning weight, yearling weight) in U.S. Red Angus cattle were found to be pleiotropic. Twelve of these pleiotropic QTL were also identified in previous studies focusing on feed efficiency and growth traits in multiple beef breeds and/or their composites. In agreement with other beef cattle GxE studies our results implicate the role of vasodilation, metabolism, and the nervous system in the genetic sensitivity to environmental stress.

Evidence of rare misassemblies in the bovine reference genome revealed by population genetic metrics.

Creation of the bovine reference assembly paved the way to develop the high-throughput genotyping arrays of the single nucleotide polymorphisms (SNPs) based on the available map coordinates that facilitated major advances in gene mapping and selection programs. The assembly flaws, however, may cause false results in the downstream gene mapping studies. The most recent bovine reference genome (ARS-UCD1.2) is built on the long-read sequences that provides improved quality and continuity. By applying population genetic metrics in this study, we aimed to evaluate the map coordinates to which SNP markers were assigned. We employed a three-step approach by combining the recombination and linkage disequilibrium analyses to test if the markers fit into the assigned physical map coordinates. We applied the method to the bovine 50k array in a large pedigree of Holstein cattle and revealed a panel of 65 candidate markers, most of which were re-located either on a different chromosome or re-mapped as far as several million base pairs away on the same chromosome. This list of candidates accounts for 0.1% of the SNPs in the widely used 50k genotyping array and we foresee a reasonably larger set of markers being misplaced in the BovineHD 700K BeadChip. We suggest pre-removal of the candidate misplaced markers to reduce false signals in association mapping studies.

A Non-Synonymous Point Mutation in a WD-40 Domain Repeat of EML5 Leads to Decreased Bovine Sperm Quality and Fertility.

This study is part of a concerted effort to identify and phenotype rare, deleterious mutations that adversely affect sperm quality, or convey high developmental and fertility potential to embryos and ensuing progeny. A rare, homozygous mutation in EML5 (EML5 R1654W ), which encodes a microtubule-associated protein with high expression in testis and brain was identified in an Angus bull used extensively in artificial insemination (AI) for its outstanding progeny production traits. The bull's fertility was low in cross-breeding timed AI (TAI) (Pregnancy/TAI = 25.2%; n = 222) and, in general, AI breeding to Nellore cows (41%; n = 822). A search of the 1,000 Bull Genomes Run9 database revealed an additional 74 heterozygous animals and 8 homozygous animals harboring this exact mutation across several different breeds (0.7% frequency within the 6,191 sequenced animals). Phenotypically, spermatozoa from the homozygous Angus bull displayed prominent piriform and tapered heads, and outwardly protruding knobbed acrosomes. Additionally, an increased retention of EML5 was also observed in the sperm head of both homozygous and heterozygous Angus bulls compared to wild-type animals. This non-synonymous point mutation is located within a WD40 signaling domain repeat of EML5 and is predicted to be detrimental to overall protein function by genomic single nucleotide polymorphism (SNP) analysis and protein modeling. Future work will examine how this rare mutation affects field AI fertility and will characterize the role of EML5 in spermatogenesis.

Exploring genetic variation and population structure in a threatened species, Noturus placidus, with whole-genome sequence data.

The Neosho madtom (Noturus placidus) is a small catfish, generally less than 3 inches in length, unique to the Neosho-Spring River system within the Arkansas River Basin. It was federally listed as threatened in 1990, largely due to habitat loss. For conservation efforts, we generated whole-genome sequence data from 10 Neosho madtom individuals originating from 3 geographically separated populations to evaluate genetic diversity and population structure. A Neosho madtom genome was de novo assembled, and genome size and content were assessed. Single nucleotide polymorphisms were assessed from de Bruijn graphs, and via reference alignment with both the channel catfish (Ictalurus punctatus) reference genome and Neosho madtom reference genome. Principal component analysis and structure analysis indicated weak population structure, suggesting fish from the 3 locations represent a single population. Using a novel method, genome-wide conservation and divergence between the Neosho madtom, channel catfish, and zebrafish (Danio rerio) was assessed by pairwise contig alignment, which demonstrated that genes important to embryonic development frequently had conserved sequences. This research in a threatened species with no previously published genomic resources provides novel genetic information to guide current and future conservation efforts and demonstrates that using whole-genome sequencing provides detailed information of population structure and demography using only a limited number of rare and valuable samples.

Taurine and Indicine Haplotype Representation in Advanced Generation Individuals From Three American Breeds.

Development of the American Breeds of beef cattle began in the 1920s as breeders and U. S. Experiment Station researchers began to create Bos taurus taurus × Bos taurus indicus hybrids using Brahman as the B. t. indicus source. By 1954, U.S. Breed Associations had been formed for Brangus (5/8 Angus × 3/8 Brahman), Beefmaster (½ Brahman × » Shorthorn × » Hereford), and Santa Gertrudis (5/8 Shorthorn × 3/8 Brahman). While these breeds were developed using mating designs expected to create base generation animals with the required genome contributions from progenitor breeds, each association has now registered advanced generation animals in which selection or drift may have caused the realized genome compositions to differ from initial expected proportions. The availability of high-density SNP genotypes for 9,161 Brangus, 3,762 Beefmaster, and 1,942 Santa Gertrudis animals allowed us to compare the realized genomic architectures of breed members to the base generation expectations. We used RFMix to estimate local ancestry and identify genomic regions in which the proportion of Brahman ancestry differed significantly from a priori expectations. For all three breeds, lower than expected levels of Brahman composition were found genome-wide, particularly in early-generation animals where we demonstrate that selection on beef production traits was likely responsible for the taurine enrichment. Using a proxy for generation number, we also contrasted the genomes of early- and advanced-generation animals and found that the indicine composition of the genome has increased with generation number likely due to selection on adaptive traits. Many of the most-highly differentiated genomic regions were breed specific, suggesting that differences in breeding objectives and selection intensities exist between the breeds. Global ancestry estimation is commonly performed in admixed animals to control for stratification in association studies. However, local ancestry estimation provides the opportunity to investigate the evolution of specific chromosomal segments and estimate haplotype effects on trait variation in admixed individuals. Investigating the genomic architecture of the American Breeds not only allows the estimation of indicine and taurine genome proportions genome-wide, but also the locations within the genome where either taurine or indicine alleles confer a selective advantage.

Powerful detection of polygenic selection and evidence of environmental adaptation in US beef cattle.

Selection on complex traits can rapidly drive evolution, especially in stressful environments. This polygenic selection does not leave intense sweep signatures on the genome, rather many loci experience small allele frequency shifts, resulting in large cumulative phenotypic changes. Directional selection and local adaptation are changing populations; but, identifying loci underlying polygenic or environmental selection has been difficult. We use genomic data on tens of thousands of cattle from three populations, distributed over time and landscapes, in linear mixed models with novel dependent variables to map signatures of selection on complex traits and local adaptation. We identify 207 genomic loci associated with an animal's birth date, representing ongoing selection for monogenic and polygenic traits. Additionally, hundreds of additional loci are associated with continuous and discrete environments, providing evidence for historical local adaptation. These candidate loci highlight the nervous system's possible role in local adaptation. While advanced technologies have increased the rate of directional selection in cattle, it has likely been at the expense of historically generated local adaptation, which is especially problematic in changing climates. When applied to large, diverse cattle datasets, these selection mapping methods provide an insight into how selection on complex traits continually shapes the genome. Further, understanding the genomic loci implicated in adaptation may help us breed more adapted and efficient cattle, and begin to understand the basis for mammalian adaptation, especially in changing climates. These selection mapping approaches help clarify selective forces and loci in evolutionary, model, and agricultural contexts.

Genome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattle.

Understanding genotype-by-environment interactions (G × E) is crucial to understand environmental adaptation in mammals and improve the sustainability of agricultural production. Here, we present an extensive study investigating the interaction of genome-wide SNP markers with a vast assortment of environmental variables and searching for SNPs controlling phenotypic variance (vQTL) using a large beef cattle dataset. We showed that G × E contribute 10.1%, 3.8%, and 2.8% of the phenotypic variance of birth weight, weaning weight, and yearling weight, respectively. G × E genome-wide association analysis (GWAA) detected a large number of G × E loci affecting growth traits, which the traditional GWAA did not detect, showing that functional loci may have non-additive genetic effects regardless of differences in genotypic means. Further, variance-heterogeneity GWAA detected loci enriched with G × E effects without requiring prior knowledge of the interacting environmental factors. Functional annotation and pathway analysis of G × E genes revealed biological mechanisms by which cattle respond to changes in their environment, such as neurotransmitter activity, hypoxia-induced processes, keratinization, hormone, thermogenic and immune pathways. We unraveled the relevance and complexity of the genetic basis of G × E underlying growth traits, providing new insights into how different environmental conditions interact with specific genes influencing adaptation and productivity in beef cattle and potentially across mammals.

Introgression, admixture, and selection facilitate genetic adaptation to high-altitude environments in cattle.

Domestication and subsequent selection of cattle to form breeds and biological types that can adapt to different environments partitioned ancestral genetic diversity into distinct modern lineages. Genome-wide selection particularly for adaptation to extreme environments left detectable signatures genome-wide. We used high-density genotype data for 42 cattle breeds and identified the influence of Bos grunniens and Bos javanicus on the formation of Chinese indicine breeds that led to their divergence from India-origin zebu. We also found evidence for introgression, admixture, and migration in most of the Chinese breeds. Selection signature analyses between high-altitude (≥1800 m) and low-altitude adapted breeds (<1500 m) revealed candidate genes (ACSS2, ALDOC, EPAS1, EGLN1, NUCB2) and pathways that are putatively involved in hypoxia adaptation. Immunohistochemical, real-time PCR and CRISPR/cas9 ACSS2-knockout analyses suggest that the up-regulation of ACSS2 expression in the liver promotes the metabolic adaptation of cells to hypoxia via the hypoxia-inducible factor pathway. High altitude adaptation involved the introgression of alleles from high-altitude adapted yaks into Chinese Bos taurus taurus prior to their formation into recognized breeds and followed by selection. In addition to selection, adaptation to high altitude environments has been facilitated by admixture and introgression with locally adapted cattle populations.

Spliced genes in muscle from Nelore Cattle and their association with carcass and meat quality.

Transcript data obtained by RNA-Seq were used to identify differentially expressed alternatively spliced genes in ribeye muscle tissue between Nelore cattle that differed in their ribeye area (REA) or intramuscular fat content (IF). A total of 166 alternatively spliced transcripts from 125 genes were significantly differentially expressed in ribeye muscle between the highest and lowest REA groups (p ≤ 0.05). For animals selected on their IF content, 269 alternatively spliced transcripts from 219 genes were differentially expressed in ribeye muscle between the highest and lowest IF animals. Cassette exons and alternative 3' splice sites were the most frequently found alternatively spliced transcripts for REA and IF content. For both traits, some differentially expressed alternatively spliced transcripts belonged to myosin and myotilin gene families. The hub transcripts were identified for REA (LRRFIP1, RCAN1 and RHOBTB1) and IF (TRIP12, HSPE1 and MAP2K6) have an important role to play in muscle cell degradation, development and motility. In general, transcripts were found for both traits with biological process GO terms that were involved in pathways related to protein ubiquitination, muscle differentiation, lipids and hormonal systems. Our results reinforce the biological importance of these known processes but also reveal new insights into the complexity of the whole cell muscle mRNA of Nelore cattle.

De novo assembly of the cattle reference genome with single-molecule sequencing.

BACKGROUND: Major advances in selection progress for cattle have been made following the introduction of genomic tools over the past 10-12 years. These tools depend upon the Bos taurus reference genome (UMD3.1.1), which was created using now-outdated technologies and is hindered by a variety of deficiencies and inaccuracies. RESULTS: We present the new reference genome for cattle, ARS-UCD1.2, based on the same animal as the original to facilitate transfer and interpretation of results obtained from the earlier version, but applying a combination of modern technologies in a de novo assembly to increase continuity, accuracy, and completeness. The assembly includes 2.7 Gb and is >250× more continuous than the original assembly, with contig N50 >25 Mb and L50 of 32. We also greatly expanded supporting RNA-based data for annotation that identifies 30,396 total genes (21,039 protein coding). The new reference assembly is accessible in annotated form for public use. CONCLUSIONS: We demonstrate that improved continuity of assembled sequence warrants the adoption of ARS-UCD1.2 as the new cattle reference genome and that increased assembly accuracy will benefit future research on this species.

A multi-breed reference panel and additional rare variants maximize imputation accuracy in cattle.

BACKGROUND: During 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. RESULTS: We 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. CONCLUSIONS: Using 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.

Genome-wide association and genotype by environment interactions for growth traits in U.S. Gelbvieh cattle.

BACKGROUND: Single nucleotide polymorphism (SNP) arrays have facilitated discovery of genetic markers associated with complex traits in domestic cattle; thereby enabling modern breeding and selection programs. Genome-wide association analyses (GWAA) for growth traits were conducted on 10,837 geographically diverse U.S. Gelbvieh cattle using a union set of 856,527 imputed SNPs. Birth weight (BW), weaning weight (WW), and yearling weight (YW) were analyzed using GEMMA and EMMAX (via imputed genotypes). Genotype-by-environment (GxE) interactions were also investigated. RESULTS: GEMMA and EMMAX produced moderate marker-based heritability estimates that were similar for BW (0.36-0.37, SE = 0.02-0.06), WW (0.27-0.29, SE = 0.01), and YW (0.39-0.41, SE = 0.01-0.02). GWAA using 856K imputed SNPs (GEMMA; EMMAX) revealed common positional candidate genes underlying pleiotropic QTL for Gelbvieh growth traits on BTA6, BTA7, BTA14, and BTA20. The estimated proportion of phenotypic variance explained (PVE) by the lead SNP defining these QTL (EMMAX) was larger and most similar for BW and YW, and smaller for WW. Collectively, GWAAs (GEMMA; EMMAX) produced a highly concordant set of BW, WW, and YW QTL that met a nominal significance level (P ≤ 1e-05), with prioritization of common positional candidate genes; including genes previously associated with stature, feed efficiency, and growth traits (i.e., PLAG1, NCAPG, LCORL, ARRDC3, STC2). Genotype-by-environment QTL were not consistent among traits at the nominal significance threshold (P ≤ 1e-05); although some shared QTL were apparent at less stringent significance thresholds (i.e., P ≤ 2e-05). CONCLUSIONS: Pleiotropic QTL for growth traits were detected on BTA6, BTA7, BTA14, and BTA20 for U.S. Gelbvieh beef cattle. Seven QTL detected for Gelbvieh growth traits were also recently detected for feed efficiency and growth traits in U.S. Angus, SimAngus, and Hereford cattle. Marker-based heritability estimates and the detection of pleiotropic QTL segregating in multiple breeds support the implementation of multiple-breed genomic selection.

Neuronal ceroid lipofuscinosis in a German Shorthaired Pointer associated with a previously reported CLN8 nonsense variant.

Two littermate German Shorthaired Pointers, a male and a female, were adopted as puppies from an animal shelter. Both puppies developed normally until approximately 11 months of age when the male began to exhibit neurological signs including ataxia, vision loss, and behavioral changes indicative of cognitive decline. These signs increased in severity over time. The female remained neurologically normal and healthy. The affected dog was euthanized at approximately 21 months of age. Autofluorescent cytoplasmic storage bodies were detected in neurons in unstained tissue sections from the cerebellum, the cerebrum, and the retina. Electron micrographs of these storage bodies showed that they were membrane bound and that most contained tightly packed aggregates of membranous whorls along with a variety of other ultrastructural features. This ultrastructure, along with the autofluorescence and the clinical signs supported a diagnosis of neuronal ceroid lipofuscinosis (NCL). Unlike earlier investigated forms of canine NCL with causal alleles in ATP13A2, TPP1, MFSD8 and CLN5 that had autofluorescent cytoplasmic storage bodies in cardiac muscle, no autofluorescence was detected in cardiac muscle from the affected German Shorthaired Pointer. A 39-fold average coverage whole genome sequence indicated that the affected German Shorthaired Pointer was homozygous for the A allele of a G > A transversion at position 30,895,648 chromosome 37. This 37:30895648G > A mutation created a CLN8 termination codon that had been previously reported to cause NCL in a mixed breed dog with Australian Shepherd and Australian Cattle Dog ancestry. This nonsense allele was heterozygous in the clinically normal female sibling, while archived DNA samples from 512 other German Shorthaired Pointers were all homozygous for the reference allele. The affected German Shorthaired Pointer and the previously diagnosed mixed breed dog with the same nonsense mutation shaired an identical homozygous haplotype that extended for 4.41 Mb at the telomeric end of chromosome 37, indicating the both dogs inherited the nonsense mutation from a common ancestor.

Identification of bovine CpG SNPs as potential targets for epigenetic regulation via DNA methylation.

Methylation patterns established and maintained at CpG sites may be altered by single nucleotide polymorphisms (SNPs) within these sites and may affect the regulation of nearby genes. Our aims were to: 1) identify and generate a database of SNPs potentially subject to epigenetic control by DNA methylation via their involvement in creating, removing or displacing CpG sites (meSNPs), and; 2) investigate the association of these meSNPs with CpG islands (CGIs), and with methylation profiles of DNA extracted from tissues from cattle with divergent feed efficiencies detected using MIRA-Seq. Using the variant annotation for 56,969,697 SNPs identified in Run5 of the 1000 Bull Genomes Project and the UMD3.1.1 bovine reference genome sequence assembly, we identified and classified 12,836,763 meSNPs according to the nature of variation created at CpGs. The majority of the meSNPs were located in intergenic regions (68%) or introns (26.3%). We found an enrichment (p<0.01) of meSNPs located in CGIs relative to the genome as a whole, and also in differentially methylated sequences in tissues from animals divergent for feed efficiency. Seven meSNPs, located in differentially methylated regions, were fixed for methylation site creating (MSC) or destroying (MSD) alleles in the differentially methylated genomic sequences of animals differing in feed efficiency. These meSNPs may be mechanistically responsible for creating or deleting methylation targets responsible for the differential expression of genes underlying differences in feed efficiency. Our methyl SNP database (dbmeSNP) is useful for identifying potentially functional "epigenetic polymorphisms" underlying variation in bovine phenotypes.

CRUMBLER: A tool for the prediction of ancestry in cattle.

In many beef and some dairy production systems, crossbreeding is used to take advantage of breed complementarity and heterosis. Admixed animals are frequently identified by their coat color and body conformation phenotypes, however, without pedigree information it is not possible to identify the expected breed composition of an admixed animal and in the presence of selection, the actual composition may differ from expectation. As the roles of DNA and genotype data become more pervasive in animal agriculture, a systematic method for estimating the breed composition (the proportions of an animal's genome originating from ancestral pure breeds) has utility for a variety of downstream analyses including the estimation of genomic breeding values for crossbred animals, the estimation of quantitative trait locus effects, and heterosis and heterosis retention in advanced generation composite animals. Currently, there is no automated or semi-automated ancestry estimation platform for cattle and the objective of this study was to evaluate the utility of extant public software for ancestry estimation and determine the effects of reference population size and composition and number of utilized single nucleotide polymorphism loci on ancestry estimation. We also sought to develop an analysis pipeline that would simplify this process for members of the livestock genomics research community. We developed and tested a tool, "CRUMBLER", to estimate the global ancestry of cattle using ADMIXTURE and SNPweights based on a defined reference panel. CRUMBLER, was developed and evaluated in cattle, but is a species agnostic pipeline that facilitates the streamlined estimation of breed composition for individuals with potentially complex ancestries using publicly available global ancestry software and a specified reference population SNP dataset. We developed the reference panel from a large cattle genotype data set and breed association pedigree information using iterative analyses to identify purebred individuals that were representative of each breed. We also evaluated the numbers of markers necessary for breed composition estimation and simulated genotypes for advanced generation composite animals to evaluate the precision of the developed tool. The developed CRUMBLER pipeline extracts a specified subset of genotypes that is common to all current commercially available genotyping platforms, processes these into the file formats required for the analysis software, and predicts admixture proportions using the specified reference population allele frequencies.

QTL-mapping and genomic prediction for bovine respiratory disease in U.S. Holsteins using sequence imputation and feature selection.

BACKGROUND: National genetic evaluations for disease resistance do not exist, precluding the genetic improvement of cattle for these traits. We imputed BovineHD genotypes to whole genome sequence for 2703 Holsteins that were cases or controls for Bovine Respiratory Disease and sampled from either California or New Mexico to construct and compare genomic prediction models. The sequence variation reference dataset comprised variants called for 1578 animals from Run 5 of the 1000 Bull Genomes Project, including 450 Holsteins and 29 animals sequenced from this study population. Genotypes for 9,282,726 variants with minor allele frequencies ≥5% were imputed and used to obtain genomic predictions in GEMMA using a Bayesian Sparse Linear Mixed Model. RESULTS: Variation explained by markers increased from 13.6% using BovineHD data to 14.4% using imputed whole genome sequence data and the resolution of genomic regions detected as harbouring QTL substantially increased. Explained variation in the analysis of the combined California and New Mexico data was less than when data for each state were separately analysed and the estimated genetic correlation between risk of Bovine Respiratory Disease in California and New Mexico Holsteins was - 0.36. Consequently, genomic predictions trained using the data from one state did not accurately predict disease risk in the other state. To determine if a prediction model could be developed with utility in both states, we selected variants within genomic regions harbouring: 1) genes involved in the normal immune response to infection by pathogens responsible for Bovine Respiratory Disease detected by RNA-Seq analysis, and/or 2) QTL identified in the association analysis of the imputed sequence variants. The model based on QTL selected variants is biased but when trained in one state generated BRD risk predictions with positive accuracies in the other state. CONCLUSIONS: We demonstrate the utility of sequence-based and biology-driven model development for genomic selection. Disease phenotypes cannot be routinely recorded in most livestock species and the observed phenotypes may vary in their genomic architecture due to variation in the pathogen composition across environments. Elucidation of trait biology and genetic architecture may guide the development of prediction models with utility across breeds and environments.