...
【24h】

Genome-wide scans for footprints of natural selection

机译:全基因组扫描自然选择的足迹

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Detecting recent selected ‘genomic footprints’ applies directly to the discovery of disease genes and in the imputation of the formative events that molded modern population genetic structure. The imprints of historic selection/adaptation episodes left in human and animal genomes allow one to interpret modern and ancestral gene origins and modifications. Current approaches to reveal selected regions applied in genome-wide selection scans (GWSSs) fall into eight principal categories: (I) phylogenetic footprinting, (II) detecting increased rates of functional mutations, (III) evaluating divergence versus polymorphism, (IV) detecting extended segments of linkage disequilibrium, (V) evaluating local reduction in genetic variation, (VI) detecting changes in the shape of the frequency distribution (spectrum) of genetic variation, (VII) assessing differentiating between populations (FST), and (VIII) detecting excess or decrease in admixture contribution from one population. Here, we review and compare these approaches using available human genome-wide datasets to provide independent verification (or not) of regions found by different methods and using different populations. The lessons learned from GWSSs will be applied to identify genome signatures of historic selective pressures on genes and gene regions in other species with emerging genome sequences. This would offer considerable potential for genome annotation in functional, developmental and evolutionary contexts.
机译:检测最近选定的“基因组足迹”直接适用于疾病基因的发现以及归因于塑造现代人群遗传结构的形成性事件。人类和动物基因组中留下的历史性选择/适应事件的印记使人们能够解释现代和祖先的基因起源和修饰。当前揭示用于全基因组选择扫描(GWSS)的选定区域的方法可分为八个主要类别:(I)系统发育足迹,(II)检测功能突变的发生率,(III)评估差异与多态性,(IV)检测连锁不平衡的延伸部分,(V)评估遗传变异的局部减少,(VI)检测遗传变异的频率分布(频谱)形状的变化,(VII)评估种群之间的差异(FST),以及(VIII)从一个人群中检测出混合料贡献的增加或减少。在这里,我们使用可用的人类全基因组数据集来审查和比较这些方法,以提供对使用不同方法和使用不同人群发现的区域的独立验证(或不提供)。从GWSS获得的经验教训将被用于确定具有新的基因组序列的其他物种的基因和基因区域对历史选择性压力的基因组特征。这将为功能,发展和进化背景下的基因组注释提供巨大潜力。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号