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Abstract Background The trading of individual animal genotype information often involves only the exchange of the called genotypes and not necessarily the additional information required to effectively call structural variants. The main aim here was to determine if it is possible to impute copy number variants (CNVs) using the flanking single nucleotide polymorphism (SNP) haplotype structure in cattle. While this objective was achieved using high-density genotype panels (i.e., 713,162 SNPs), a secondary objective investigated the concordance of CNVs called with this high-density genotype panel compared to CNVs called from a medium-density panel (i.e., 45,677 SNPs in the present study). This is the first study to compare CNVs called from high-density and medium-density SNP genotypes from the same animals. High (and medium-density) genotypes were available on 991 Holstein-Friesian, 1015 Charolais, and 1394 Limousin bulls. The concordance between CNVs called from the medium-density and high-density genotypes were calculated separately for each animal. A subset of CNVs which were called from the high-density genotypes was selected for imputation. Imputation was carried out separately for each breed using a set of high-density SNPs flanking the midpoint of each CNV. A CNV was deemed to be imputed correctly when the called copy number matched the imputed copy number. Results For 97.0% of CNVs called from the high-density genotypes, the corresponding genomic position on the medium-density of the animal did not contain a called CNV. The average accuracy of imputation for CNV deletions was 0.281, with a standard deviation of 0.286. The average accuracy of imputation of the CNV normal state, i.e. the absence of a CNV, was 0.982 with a standard deviation of 0.022. Two CNV duplications were imputed in the Charolais, a single CNV duplication in the Limousins, and a single CNV duplication in the Holstein-Friesians; in all cases the CNV duplications were incorrectly imputed. Conclusion The vast majority of CNVs called from the high-density genotypes were not detected using the medium-density genotypes. Furthermore, CNVs cannot be accurately predicted from flanking SNP haplotypes, at least based on the imputation algorithms routinely used in cattle, and using the SNPs currently available on the high-density genotype panel.

Background: The trading of individual animal genotype information often involves only the exchange of the called genotypes and not necessarily the additional information required to effectively call structural variants. The main aim here was to determine if it is possible to impute copy number variants (CNVs) using the flanking single nucleotide polymorphism (SNP) haplotype structure in cattle. While this objective was achieved using high-density genotype panels (i.e., 713,162 SNPs), a secondary objective investigated the concordance of CNVs called with this high-density genotype panel compared to CNVs called from a medium-density panel (i.e., 45,677 SNPs in the present study). This is the first study to compare CNVs called from high-density and medium-density SNP genotypes from the same animals. High (and medium-density) genotypes were available on 991 Holstein-Friesian, 1015 Charolais, and 1394 Limousin bulls. The concordance between CNVs called from the medium-density and high-density genotypes were calculated separately for each animal. A subset of CNVs which were called from the high-density genotypes was selected for imputation. Imputation was carried out separately for each breed using a set of high-density SNPs flanking the midpoint of each CNV. A CNV was deemed to be imputed correctly when the called copy number matched the imputed copy number. Results: For 97.0% of CNVs called from the high-density genotypes, the corresponding genomic position on the medium-density of the animal did not contain a called CNV. The average accuracy of imputation for CNV deletions was 0.281, with a standard deviation of 0.286. The average accuracy of imputation of the CNV normal state, i.e. the absence of a CNV, was 0.982 with a standard deviation of 0.022. Two CNV duplications were imputed in the Charolais, a single CNV duplication in the Limousins, and a single CNV duplication in the Holstein-Friesians; in all cases the CNV duplications were incorrectly imputed. Conclusion: The vast majority of CNVs called from the high-density genotypes were not detected using the medium-density genotypes. Furthermore, CNVs cannot be accurately predicted from flanking SNP haplotypes, at least based on the imputation algorithms routinely used in cattle, and using the SNPs currently available on the high-density genotype panel. [ABSTRACT FROM AUTHOR]

Copy number variants (CNVs) are a form of genomic variation that changes the structure of the genome through deletion or duplication of stretches of DNA. The objective of the present study was to characterize CNVs in a large multibreed population of beef and dairy bulls. The CNVs were called on the autosomes of 5,551 cattle from 22 different beef and dairy breeds, using 2 freely available software suites, QuantiSNP and PennCNV. All CNVs were classified into either deletions or duplications. The median concordance between PennCNV and QuantiSNP, per animal, was 18.5% for deletions and 0% for duplications. The low concordance rate between PennCNV and QuantiSNP indicated that neither algorithm, by itself, could identify all CNVs in the population. In total, PennCNV and QuantiSNP collectively identified 747,129 deletions and 432,523 duplications; 80.2% of all duplications and 69.1% of all deletions were present only once in the population. Only 0.154% of all CNVs identified were present in more than 50 animals in the population. The distribution of the percentage of the autosomes that were composed of deletions, per animal, was positively skewed, as was the distribution for the percentage of the autosomes that were composed of duplications, per animal. The first quartile, median, and third quartile of the distribution of the percentage of the autosomes that were composed of deletions were 0.019%, 0.037%, and 0.201%, respectively. The first quartile, median, and third quartile of the distribution of the percentage of the autosomes that were composed of duplications were 0.013%, 0.028%, and 0.076%, respectively. The distributions of the number of deletions and duplications per animal were both positively skewed. The interquartile range for the number of deletions per animal in the population was between 16 and 117, whereas for duplications it was between 8 and 23. Per animal, there tended to be twice as many deletions as duplications. The distribution of the length of deletions was positively skewed, as was the distribution of the length of duplications. The interquartile range for the length of deletions in the population was between 25 and 101 kb, and for duplications the interquartile range was between 46 and 235 kb. Per animal, duplications tended to be twice as long as deletions. This study provides a description of the characteristics and distribution of CNVs in a large multibreed population of beef and dairy cattle. [ABSTRACT FROM AUTHOR]

Background Obesity, excess fat tissue in the body, can underlie a variety of medical complaints including heart disease, stroke and cancer. The pig is an excellent model organism for the study of various human disorders, including obesity, as well as being the foremost agricultural species. In order to identify genetic variants associated with fatness, we used a selective genomic approach sampling DNA from animals at the extreme ends of the fat and lean spectrum using estimated breeding values derived from a total population size of over 70,000 animals. DNA from 3 breeds (Sire Line Large White, Duroc and a white Pietrain composite line (Titan)) was used to interrogate the Illumina Porcine SNP60 Genotyping Beadchip in order to identify significant associations in terms of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs). Results By sampling animals at each end of the fat/lean EBV (estimate breeding value) spectrum the whole population could be assessed using less than 300 animals, without losing statistical power. Indeed, several significant SNPs (at the 5% genome wide significance level) were discovered, 4 of these linked to genes with ontologies that had previously been correlated with fatness (NTS, FABP6, SST and NR3C2). Quantitative analysis of the data identified putative CNV regions containing genes whose ontology suggested fatness related functions (MCHR1, PPARα, SLC5A1 and SLC5A4). Conclusions Selective genotyping of EBVs at either end of the phenotypic spectrum proved to be a cost effective means of identifying SNPs and CNVs associated with fatness and with estimated major effects in a large population of animals. [ABSTRACT FROM AUTHOR]