Abstract：
Copy number variations (CNVs) are key structural variations in the genome and may contribute to phenotypic differences. In this study, we used a F2 chicken population created from reciprocal crossing between fast-growing Arian broiler line and Urmia native chickens. The chickens were genotyped by 60 K SNP BeadChip, and PennCNV algorithm was used to detect genome-wide CNVs. The growth curve parameters of W0, k, L, Wf, Wi, ti and average GR were used as phenotypic data. The association between CNV and growth curve parameters was carried out using the CNVRanger R/Bioconductor package. Five CNV regions (CNVRs) were chosen for the validation experiment using qPCR. Gene enrichment analysis was done using WebGestalt. The STRING database was used to search for significant pathways. The results identified 966 CNVs and 600 CNVRs including 468 gains, 67 losses, and 65 both events on autosomal chromosomes. Validation of the CNVRs obtained from the qPCR assay were 79 % consistent with the prediction by PennCNV. A total of 43 significant CNVs were obtained for the seven growth curve parameters. The 416 genes annotated for significant CNVs. Six genes out of 416 genes were most related to growth curve parameters. These genes were LCP2, Dock2, CD80, CYFIP1, NIPA1 and NIPA2. Some of these genes in their biological process were associated with the growth, reproduction and development of cells or organs that ultimately lead to the growth of the body. The results of the study could pave the way for better understanding the molecular process of CNVs and growth curve parameters in birds.
摘要：
拷贝数变异（CNV）是基因组中的关键结构变异，可能导致表型差异。在这项研究中,我们使用了由快速生长的Arian肉鸡品系和Urmia本地鸡之间的相互杂交产生的F2鸡种群。通过60KSNPBeadChip对鸡进行基因分型，PennCNV算法用于检测全基因组CNV。生长曲线参数W0，k，L,Wf,Wi,ti和平均GR用作表型数据。CNV和生长曲线参数之间的关联使用CNVRangerR/Bioconductor包进行。选择五个CNV区(CNVR)用于使用qPCR的验证实验。使用WebGestalt进行基因富集分析。STRING数据库用于搜索重要途径。结果确定了966个CNVs和600个CNVRs，包括468个增益，67损失，常染色体上有65个事件。从qPCR测定获得的CNVR的验证与PennCNV的预测是79%一致。对于七个生长曲线参数,总共获得43个显著的CNV。416个基因注释了显著的CNVs。416个基因中的6个基因与生长曲线参数最相关。这些基因是LCP2、Dock2、CD80、CYFIP1、NIPA1和NIPA2。其中一些基因在其生物过程中与生长有关，最终导致身体生长的细胞或器官的繁殖和发育。研究结果可为更好地理解CNV的分子过程和鸟类的生长曲线参数铺平道路。
