PSVII-5 - Detection and characterization of copy number variation regions in three selection lines of Nellore cattle

Abstract: Copy number variations (CNV) can partially explain phenotypic variability in complex traits. Therefore, we aimed to identify and characterize CNV regions (CNVR) in Nellore cattle from three selection lines. These selection lines were established in 1981 and consist of a line selected based on higher postweaning weight (NeS, n = 245), a line selected based on higher postweaning weight and lower residual feeding Intake (NeT, n = 556), and a line selected based on average postweaning weight (NeC, n = 114). Genotypes (GGP Indicus HD and GGP Indicus 50K panel) of 928 animals were analyzed. The CNV identification was performed per SNP panel using the PennCNV software. After identifying the CNVs, quality control was performed and the following exclusion criteria were used: Log R ratio > 0.30, B allele frequency "drift” < 0.01, and guanine-cytosine wave factor < 0.05. CNVR were determined by grouping individual CNVs with at least one overlapping base pair. The exclusive regions present in at least 10% of the animals from each population were identified. The GALLO R package was used for the annotation of genes in these regions, and the WebGestaltR package was used for the Gene Ontology analyses. Eight-hundred-and-twenty-three CNVRs (143 losses, 650 gains, and 30 mixed), 1,493 CNVRs (327 losses, 1,113 gains, and 53 mixed), and 482 CNVRs (90 losses, 378 gains, and 14 mixed) were identified in the NeS, NeT, and NeC lines, respectively. The CNVRs covered 1.61%, 2.54%, and 0.94% of the cattle genome in NeS, NeT, and NeC, respectively. Only 32 CNVRs were identified in at least 10% of the animals in NeS, 33 in NeT, and 25 in NeC. Of these regions, 2 are NeS exclusive, 4 are NeT exclusive, and 6 are NeC exclusive. Eight candidate genes in NeS, 20 candidate genes in NeT, and 16 genes in NeC overlapped with the exclusive regions. We identified some important genes such as SLC15A1 in NeS herd that have functions associated to nutrient absorption, MAPK1 identified in the NeT population is involved in a wide variety of cellular processes such as proliferation, differentiation, transcription regulation and development, and IQCA1L in the NeC population is involved in ATP activity. The genes identified are involved in 5 biological processes, such as response to growth factor, in NeT, and in 1 biological process (response to endoplasmic reticulum stress) in NeC. The differences observed in CNVR improve our understanding of the genetic architecture of the three Nellore selection schemes, given that the identification of genes in the CNVR allows the identification of genomic regions and biological processes that could be associated with the phenotypic differences between selection lines.