Suppr超能文献

对两个因腹脂含量而被 divergent 选择的鸡品系进行全基因组拷贝数变异检测。 (注:这里“divergent”直译为“发散的、分歧的”,结合语境推测可能是“定向差异选择”之类意思,但按要求不添加解释,保留英文)

Detection of genome-wide copy number variations in two chicken lines divergently selected for abdominal fat content.

作者信息

Zhang Hui, Du Zhi-Qiang, Dong Jia-Qiang, Wang Hai-Xia, Shi Hong-Yan, Wang Ning, Wang Shou-Zhi, Li Hui

机构信息

Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture, Harbin 150030, P,R China.

出版信息

BMC Genomics. 2014 Jun 24;15:517. doi: 10.1186/1471-2164-15-517.

Abstract

BACKGROUND

The chicken (Gallus gallus) is an important model organism that bridges the evolutionary gap between mammals and other vertebrates. Copy number variations (CNVs) are a form of genomic structural variation widely distributed in the genome. CNV analysis has recently gained greater attention and momentum, as the identification of CNVs can contribute to a better understanding of traits important 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 60 K SNP array, which is a high-throughput 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 all of them were 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 roles in a number of biological processes. Integrating the 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 and ZPAX) may be important for abdominal fat deposition in the chicken.

CONCLUSIONS

Our study provided a genome-wide CNVR map of the chicken genome, thereby contributing to our understanding of genomic structural variations and their potential roles in abdominal fat content in the chicken.

摘要

背景

鸡(原鸡)是一种重要的模式生物,它填补了哺乳动物与其他脊椎动物之间的进化差距。拷贝数变异(CNV)是基因组结构变异的一种形式,广泛分布于基因组中。由于CNV的鉴定有助于更好地理解对人类和其他动物都很重要的性状,因此CNV分析最近受到了更多的关注并得到了进一步发展。为了检测鸡的CNV,我们使用鸡60K SNP芯片对来自两个因腹脂含量而被 divergent 选择的肉鸡品系的475只动物进行了基因分型,这是一种在鸡基因组学研究中广泛使用的高通量方法。

结果

使用PennCNV算法,我们在瘦肉系和脂肪系中分别检测到438个和291个CNV,分别对应于271个和188个CNV区域(CNVR),这些区域是通过合并重叠的CNV获得的。在这些CNVR中,99%也被CNVPartition程序所证实。这些CNVR在瘦肉系和脂肪系中分别覆盖了鸡基因组的40.26 Mb和30.60 Mb。此外,瘦肉系中的CNVR包括176个缺失、68个增加和27个两者皆有(即同一区域内的缺失和增加)事件,脂肪系中的CNVR包括143个缺失、25个增加和20个两者皆有事件。选择了10个CNVR使用qPCR方法进行验证实验,并且所有这些CNVR在至少一次qPCR检测中都得到了证实。我们总共发现了886个位于这些CNVR内的基因,基因本体论(GO)和京都基因与基因组百科全书(KEGG)通路分析表明它们可能在许多生物学过程中发挥各种作用。整合CNVR、已知数量性状位点(QTL)和腹脂含量的选择清除结果表明,一些基因(包括SLC9A3、GNAL、SPOCK3、ANXA10、HELIOS、MYLK、CCDC14、SPAG9、SOX5、VSNL1、SMC6、GEN1、MSGN1和ZPAX)可能对鸡的腹脂沉积很重要。

结论

我们的研究提供了鸡基因组的全基因组CNVR图谱,从而有助于我们理解基因组结构变异及其在鸡腹脂含量中的潜在作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ade3/4092215/70d781ab07d3/12864_2013_6209_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验