Multiple methods to detect copy number variants (CNV) relying on different types of data have been developed and CNV have been shown to have an impact on phenotypes of numerous traits of economic importance in cattle, such as reproduction and immunity. Further improvements in CNV detection are still needed in regard to the trade-off between high-true and low-false positive variant identification rates. Instead of improving single CNV detection methods, variants can be identified in silico with high confidence when multiple methods and datasets are combined. Here, CNV were identified from whole-genome sequences (WGS) and genotype array (GEN) data on 96 Holstein animals. After CNV detection, two sets of high confidence CNV regions (CNVR) were created that contained variants found in both WGS and GEN data following an animal-based (n = 52) and a population-based (n = 36) pipeline. Furthermore, the change in false positive CNV identification rates using different GEN marker densities was evaluated. The population-based approach characterized CNVR, which were more often shared among animals (average 40% more samples per CNVR) and were more often linked to putative functions (48 vs 56% of CNVR) than CNV identified with the animal-based approach. Moreover, false positive identification rates up to 22% were estimated on GEN information. Further research using larger datasets should use a population-wide approach to identify high confidence CNVR. Dairy cattle genetics has made great advances since the effects of single nucleotide polymorphisms (SNP) have been recognized on a wide range of mono or polygenic traits economically important for the dairy industry 1-5. Genomic variation, however, is not only caused by SNP. Recent studies have shown that structural variants (SV) also have an important impact on phenotypes of a multitude of traits, such as milk production, reproduction, health, and feed efficiency 6-8. Types of SV include translocations, inversions and copy number variation 9. Copy number variants (CNV) form the most common class of SV in the human, plant and animal genome and can be identified as two types of event: copy number loss (CNL) or copy number gain (CNG). As the amount of DNA changes between samples with or without multiple copies of a segment, CNV are a type of the unbalanced structural variations 9. Although the number of bovine CNV described in the literature is lower than the number of SNP, the fact that they have multiple alleles makes them highly informative 10. The CNV can affect both monogenic traits, such as the coat color of cattle 11 , and polygenic traits such as feed efficiency, production traits, and reproduction traits of cattle 12,13. For instance, a study by Liu et al. 14 showed associations between CNV and production traits specifically in Holstein dairy cattle. Identifying CNV is challenging and no consensus on the best method of identification has been reached because multiple factors, starting with the source of information on which the CNV are identified, influence the results. Mo...

Background Copy number variants (CNVs) contribute to genetic diversity and phenotypic variation. We aimed to discover CNVs in taurine cattle using a large collection of whole-genome sequences and to provide an interactive database of the identified CNV regions (CNVRs) that includes visualizations of sequence read alignments, CNV boundaries, and genome annotations. Results CNVs were identified in each of 4 whole-genome sequencing datasets, which together represent >500 bulls from 17 breeds, using a popular multi-sample read-depth−based algorithm, cn.MOPS. Quality control and CNVR construction, performed dataset-wise to avoid batch effects, resulted in 26,223 CNVRs covering 107.75 unique Mb (4.05%) of the bovine genome. Hierarchical clustering of samples by CNVR genotypes indicated clear separation by breeds. An interactive HTML database was created that allows data filtering options, provides graphical and tabular data summaries including Hardy-Weinberg equilibrium tests on genotype proportions, and displays genes and quantitative trait loci at each CNVR. Notably, the database provides sequence read alignments at each CNVR genotype and the boundaries of constituent CNVs in individual samples. Besides numerous novel discoveries, we corroborated the genotypes reported for a CNVR at the KIT locus known to be associated with the piebald coat colour phenotype in Hereford and some Simmental cattle. Conclusions We present a large comprehensive collection of taurine cattle CNVs in a novel interactive visual database that displays CNV boundaries, read depths, and genome features for individual CNVRs, thus providing users with a powerful means to explore and scrutinize CNVRs of interest more thoroughly.

Imputation of high-density genotypes to whole-genome sequences (WGS) is a cost-effective method to increase the density of available markers within a population. Imputed genotypes have been successfully used for genomic selection and discovery of variants associated with traits of interest for the population. To allow for the use of imputed genotypes for genomic analyses, accuracy of imputation must be high. Accuracy of imputation is influenced by multiple factors, such as size and composition of the reference group, and the allele frequency of variants included. Understanding the use of imputed WGSs prior to the generation of the reference population is important, as accurate imputation might be more focused, for instance, on common or on rare variants. The aim of this study was to present and evaluate new methods to select animals for sequencing relying on a previously genotyped population. The Genetic Diversity Index method optimizes the number of unique haplotypes in the future reference population, while the Highly Segregating Haplotype selection method targets haplotype alleles found throughout the majority of the population of interest. First the WGSs of a dairy cattle population were simulated. The simulated sequences mimicked the linkage disequilibrium level and the variants’ frequency distribution observed in currently available Holstein sequences. Then, reference populations of different sizes, in which animals were selected using both novel methods proposed here as well as two other methods presented in previous studies, were created. Finally, accuracies of imputation obtained with different reference populations were compared against each other. The novel methods were found to have overall accuracies of imputation of more than 0.85. Accuracies of imputation of rare variants reached values above 0.50. In conclusion, if imputed sequences are to be used for discovery of novel associations between variants and traits of interest in the population, animals carrying novel information should be selected and, consequently, the Genetic Diversity Index method proposed here may be used. If sequences are to be used to impute the overall genotyped population, a reference population consisting of common haplotypes carriers selected using the proposed Highly Segregating Haplotype method is recommended.

Genome-wide association studies based on SNP have been completed for multiple traits in dairy cattle; however, copy number variants (CNV) could add genomic information that has yet to be harnessed. The objectives of this study were to identify CNV in genotyped Holstein animals and assess their association with hoof health traits using deregressed estimated breeding values as pseudophenotypes. A total of 23,256 CNV comprising 1,645 genomic regions were identified in 5,845 animals. Fourteen genomic regions harboring structural variations, including 9 deletions and 5 duplications, were associated with at least 1 of the studied hoof health traits. This group of traits included digital dermatitis, interdigital dermatitis, heel horn erosion, sole ulcer, white line lesion, sole hemorrhage, and interdigital hyperplasia; no regions were associated with toe ulcer. Twenty candidate genes overlapped with the regions associated with these traits including SCART1, NRXN2, KIF26A, GPHN, and OR7A17. In this study, an effect on infectious hoof lesions could be attributed to the PRAME (Preferentially Expressed Antigen in Melanoma) gene. Almost all genes detected in association with noninfectious hoof lesions could be linked to known metabolic disorders. The knowledge obtained considering information of associated CNV to the traits of interest in this study could improve the accuracy of estimated breeding values. This may further increase the genetic gain for these traits in the Canadian Holstein population, thus reducing the involuntary animal losses due to lameness.

Supernumerary teats (SNT) are any abnormal teats found on a calf in addition to the usual and functional 4 teats. The presence of SNT has also been termed "hyperthelia" since the end of the 19th century. Supernumerary teats can act as an incubator for bacteria, infecting the whole udder, and can interfere with the positioning of the milking machine, and consequently, have economic relevance. Different types of SNT are observed at different positions on the udder. Caudal teats are in the rear, ramal teats are attached to another teat, and intercalary teats are found between 2 regular teats. Not all teats are equally developed; some are completely functional but most are rudimentary and not attached to any mammary gland tissue. Recently, different studies showed the poly/oligogenic character of these malformations in cattle as well as in other mammalian species. The objective of this study was to analyze the genetic architecture and incidence of hyperthelia in Swiss Brown Swiss cattle using both traditional genetic evaluation as well as imputed whole genome sequence variant information. First, phenotypes collected over the last 20 yr were used together with pedigree information for estimation of genetic variance. Second, breeding values of Brown Swiss bulls were estimated applying the BLUP algorithm. The BLUP-EBV were deregressed and used as phenotypes in genome-wide association studies. The gene LGR5 on chromosome 5 was identified as a candidate for the presence of SNT. Using alternative trait coding, genomic regions on chromosome 17 and 20 were also identified as being involved in the development of SNT with their own supernumerary mammary gland tissue. Implementing knowledge gained in this study as a routine application allows a more accurate evaluation of the trait and reduction of SNT prevalence in the Swiss Brown Swiss cattle population.