Dataset Information

Identification of copy number variants in horses.

ABSTRACT: Copy number variants (CNVs) represent a substantial source of genetic variation in mammals. However, the occurrence of CNVs in horses and their subsequent impact on phenotypic variation is unknown. We performed a study to identify CNVs in 16 horses representing 15 distinct breeds (Equus caballus) and an individual gray donkey (Equus asinus) using a whole-exome tiling array and the array comparative genomic hybridization methodology. We identified 2368 CNVs ranging in size from 197 bp to 3.5 Mb. Merging identical CNVs from each animal yielded 775 CNV regions (CNVRs), involving 1707 protein- and RNA-coding genes. The number of CNVs per animal ranged from 55 to 347, with median and mean sizes of CNVs of 5.3 kb and 99.4 kb, respectively. Approximately 6% of the genes investigated were affected by a CNV. Biological process enrichment analysis indicated CNVs primarily affected genes involved in sensory perception, signal transduction, and metabolism. CNVs also were identified in genes regulating blood group antigens, coat color, fecundity, lactation, keratin formation, neuronal homeostasis, and height in other species. Collectively, these data are the first report of copy number variation in horses and suggest that CNVs are common in the horse genome and may modulate biological processes underlying different traits observed among horses and horse breeds.

SUBMITTER: Doan R

PROVIDER: S-EPMC3337435 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

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Identification of copy number variants in horses.

Doan Ryan R Cohen Noah N Harrington Jessica J Veazey Kylee K Juras Rytis R Cothran Gus G McCue Molly E ME Skow Loren L Dindot Scott V SV

Genome research 20120301 5

Copy number variants (CNVs) represent a substantial source of genetic variation in mammals. However, the occurrence of CNVs in horses and their subsequent impact on phenotypic variation is unknown. We performed a study to identify CNVs in 16 horses representing 15 distinct breeds (Equus caballus) and an individual gray donkey (Equus asinus) using a whole-exome tiling array and the array comparative genomic hybridization methodology. We identified 2368 CNVs ranging in size from 197 bp to 3.5 Mb. ...[more]

PMID: 22383489

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Project description:BACKGROUND: Algorithms and software for CNV detection have been developed, but they detect the CNV regions sample-by-sample with individual-specific breakpoints, while common CNV regions are likely to occur at the same genomic locations across different individuals in a homogenous population. Current algorithms to detect common CNV regions do not account for the varying reliability of the individual CNVs, typically reported as confidence scores by SNP-based CNV detection algorithms. General methodologies for identifying these recurrent regions, especially those directed at SNP arrays, are still needed. RESULTS: In this paper, we describe two new approaches for identifying common CNV regions based on (i) the frequency of occurrence of reliable CNVs, where reliability is determined by high confidence scores, and (ii) a weighted frequency of occurrence of CNVs, where the weights are determined by the confidence scores. In addition, motivated by the fact that we often observe partially overlapping CNV regions as a mixture of two or more distinct subregions, regions identified using the two approaches can be fine-tuned to smaller sub-regions using a clustering algorithm. We compared the performance of the methods with sequencing-based results in terms of discordance rates, rates of departure from Hardy-Weinberg equilibrium (HWE) and average frequency and size of the identified regions. The discordance rates as well as the rates of departure from HWE decrease when we select CNVs with higher confidence scores. We also performed comparisons with two previously published methods, STAC and GISTIC, and showed that the methods we consider are better at identifying low-frequency but high-confidence CNV regions. CONCLUSIONS: The proposed methods for identifying common CNV regions in multiple individuals perform well compared to existing methods. The identified common regions can be used for downstream analyses such as group comparisons in association studies.

Dataset Information

Identification of copy number variants in horses.

Publications

Identification of copy number variants in horses.

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