Detection of genome-wide copynumber variations in two chicken lines divergently selected for abdomin

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  Background:The chicken(Gallus gallus)is an important model organism that bridges the evolutionary gap between mammals and other vertebrates.Copynumber variations(CNVs)are a form of genomic structural variation widely distributed in the genome.CNV analysis has recently gained greater attention and momentum,as theidentification of CNVs can contribute to a better understanding of traitsimportant to both humans and other animals.To detect chicken CNVs,we genotyped 475 animals derived from two broiler chicken lines divergently selected for abdominal fat content using chicken 60K SNP array,which is a highthroughput method widely used in chicken genomics studies.Results:Using PennCNV algorithm,we detected 438 and 291 CNVs in the lean and fat lines,respectively,corresponding to 271 and 188 CNV regions(CNVRs),which were obtained by merging overlapping CNVs.Out of these CNVRs,99%were confirmed also by the CNVPartition program.These CNVRs covered 40.26 and 30.60 Mb of the chicken genome in the lean and fat lines,respectively.Moreover,CNVRs included 176 loss,68 gain and 27 both(.i e.loss and gain within the same region)events in the lean line,and 143 loss,25 gain and 20 both events in the fat line.Ten CNVRs were chosen for the validation experiment using qPCR method,and allof themwere confirmed in at least one qPCR assay.We found a total of 886 genes located within these CNVRs,and Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analyses showed they could play various rolesin a number ofbiological processes.Integratingthe results of CNVRs,known quantitative trait loci(QTL)and selective sweeps for abdominal fat content suggested that some genes(including SLC9A3,GNAL,SPOCK3,ANXA10,HELIOS,MYLK,CCDC14,SPAG9,SOX5,VSNL1,SMC6,GEN1,MSGN1 andZPAX)may be important for abdominal fat deposition in the chicken.Conclusions:Our study provided a genome-wide CNVR map of the chicken genome,thereby contributingto our understanding of genomic structural variations and their potential roles in abdominal fat content in the chicken.
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