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Copy Number Variations (CNVs) are DNA sequences of 50 bp up to several Mb long, which can vary in number of copies in comparison with a reference genome. CNVs can be used in association studies to disclose genetic basis of quantitative traits phenotypic variation. Up to date, no genome-wide association study (GWAS) with CNVs and quantitative traits in such a large Brown Swiss population (i.e. with 1116 samples) has been described. The purpose of this study was to perform a GWAS using CNVs with functional, health and productive traits and to asses the impact on farming and breeding practices. The CNV – association studies were performed with the Golden Helix SVS 8.4.4 software using a correlation-trend test model. Genes within significant associated CNVs for each trait were annotated with a GO analysis using the DAVID Bioinformatics Resources 6.7. A total of 56 CNVs were significantly associated with one or more of the eight evaluated traits. The greatest association signals were given by three CNVs on chromosome 12 for the fat yield trait and on BTA23 for udder traits. The associated CNVs overlap with 23 different genes annotated on the Bos taurus genome assembly (UMD3.1).

Detecting genetic variation such as Copy Number Variants (CNVs) in cattle provides the opportunity to study their association with quantitative traits. CNVs are DNA sequences of 50 bp up to several Mb long, which can vary in copy number in comparison with a reference genome. The aim of this study was to investigate CNVs in 1410 samples of the Brown Swiss cattle breed using Illumina Bovine HD SNP chip information, which includes 777,962 SNPs. After stringent quality control, CNVs were called with the Golden Helix SVS 8.3.1 (SVS) and PennCNV software and were summarized to CNV regions (CNVRs) at a population level (i.e. overlapping CNVs), using BEDTools. Additionally, common CNVRs between the two software were set as consensus regions. Genes within consensus CNVRs were annotated with a GO analysis using the DAVID Bioinformatics Resources 6.7. In order to validate these results, quantitative PCRs were executed on 15 selected CNVRs. The SVS software identified 25,030 CNVs summarized to 398 CNVRs, which comprised 30 gains, 344 losses and 24 complex CNVRs (i.e. containing both losses and gains), covering 3.92% of the bovine genome. The PennCNV software identified 62,341 CNVs summarized to 5578 CNVRs, which comprised 2638 gains, 2404 losses and 537 complex CNVRs, covering 7.68% of the bovine genome. The length of these CNVRs ranged from 1244 bp to 1,381,355 bp. A total of 563 consensus CNVRs were found covering 2.29% of the UMD 3.1 bovine genome assembly. Of these, 24 were gains, 300 were losses and 239 were complex CNVRs. A total of 775 official gene IDs were annotated in the consensus CNVRs. Among the 537 genes with functional information, the GO and pathway analysis was reported for those who clustered with a p-value