Biology Department, University of Puerto Rico at Mayaguez, Mayaguez 00681, Puerto Rico.
Philos Trans R Soc Lond B Biol Sci. 2010 Jan 12;365(1537):185-205. doi: 10.1098/rstb.2009.0219.
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 (F(ST)), 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.
检测最近选择的“基因组足迹”直接适用于疾病基因的发现,也适用于推断塑造现代人口遗传结构的形成事件。历史选择/适应事件在人类和动物基因组中留下的印记,可以帮助我们解释现代和祖先基因的起源和变化。目前,在全基因组选择扫描(GWSS)中应用的揭示选择区域的方法可分为八大类:(I)系统发育足迹分析,(II)检测功能突变率的增加,(III)评估分歧与多态性,(IV)检测连锁不平衡的扩展片段,(V)评估遗传变异的局部减少,(VI)检测遗传变异频率分布(频谱)形状的变化,(VII)评估种群之间的分化(F(ST)),以及(VIII)检测一个种群的混合贡献是否过多或过少。在这里,我们使用现有的人类全基因组数据集来回顾和比较这些方法,以提供不同方法和不同人群发现的区域的独立验证(或不验证)。从 GWSS 中吸取的经验教训将应用于确定其他具有新兴基因组序列的物种中基因和基因区域的历史选择压力的基因组特征。这将为功能、发育和进化背景下的基因组注释提供巨大的潜力。