Premium
Genome‐wide copy number profiling using high‐density SNP array in chickens
Author(s) -
Yi G.,
Qu L.,
Chen S.,
Xu G.,
Yang N.
Publication year - 2015
Publication title -
animal genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.756
H-Index - 81
eISSN - 1365-2052
pISSN - 0268-9146
DOI - 10.1111/age.12267
Subject(s) - biology , molecular inversion probe , snp array , profiling (computer programming) , genetics , snp , computational biology , genome , copy number variation , snp genotyping , single nucleotide polymorphism , gene , genotype , computer science , operating system
Summary Phenotypic diversity is a direct consequence resulting mainly from the impact of underlying genetic variation, and recent studies have shown that copy number variation ( CNV ) is emerging as an important contributor to both phenotypic variability and disease susceptibility. Herein, we performed a genome‐wide CNV scan in 96 chickens from 12 diversified breeds, benefiting from the high‐density Affymetrix 600 K SNP arrays. We identified a total of 231 autosomal CNV regions ( CNVR s) encompassing 5.41 Mb of the chicken genome and corresponding to 0.59% of the autosomal sequence. The length of these CNVR s ranged from 2.6 to 586.2 kb with an average of 23.4 kb, including 130 gain, 93 loss and eight both gain and loss events. These CNVR s, especially deletions, had lower GC content and were located particularly in gene deserts. In particular, 102 CNVR s harbored 128 chicken genes, most of which were enriched in immune responses. We obtained 221 autosomal CNVR s after converting probe coordinates to Galgal3, and comparative analysis with previous studies illustrated that 153 of these CNVR s were regarded as novel events. Furthermore, qPCR assays were designed for 11 novel CNVR s, and eight (72.73%) were validated successfully. In this study, we demonstrated that the high‐density 600 K SNP array can capture CNV s with higher efficiency and accuracy and highlighted the necessity of integrating multiple technologies and algorithms. Our findings provide a pioneering exploration of chicken CNV s based on a high‐density SNP array, which contributes to a more comprehensive understanding of genetic variation in the chicken genome and is beneficial to unearthing potential CNV s underlying important traits of chickens.