Genome-Wide Scan for Signatures of Human Population Differentiation and Their Relationship with Natural Selection, Functional Pathways and Diseases
Genome-Wide Scan for Signatures of Human Population Differentiation and Their Relationship with Natural Selection, Functional Pathways and Diseases
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DOI：
10.1371/journal.pone.0007927
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发表时间：
2009-11-20
期刊：
影响因子：
3.7
通讯作者：
Cocozza, Sergio
中科院分区：
文献类型：
--
作者：
Amato, Roberto;Pinelli, Michele;Cocozza, Sergio
个体和群体之间的遗传差异研究其进化相关性和潜在的医学应用。大多数种群间的遗传分化是由随机漂变引起的，随机漂变会以类似的方式影响基因组中的所有位点。当一个基因座表现出极高或极低的种群分化水平时，这可以被解释为自然选择的证据。最常用的群体分化指标是由Wright设计的，称为固定指数，或F-ST。我们对来自HapMap项目数据的约400万个SNP进行了全基因组F-ST估计。我们证明了F-ST值在常染色体和异染色体之间的不均匀分布。当我们比较的F-ST值在这项研究中获得的另一种进化措施通过比较种间的方法，我们发现，正选择下的基因似乎表现出低水平的群体分化。我们采用了基因集的方法，广泛用于微阵列数据分析，检测功能的选择下的途径。我们发现，一个与抗原加工和呈递相关的途径显示出低水平的F-ST，而与细胞信号传导、生长和形态发生相关的几个途径显示出高F-ST值。最后，我们在与人类复杂疾病相关的基因中检测到了选择的特征。这些结果有助于确定人类进化和适应不同环境的过程。他们还支持这样一种假设，即常见疾病可能具有由人类进化形成的遗传背景。
Genetic differences both between individuals and populations are studied for their evolutionary relevance and for their potential medical applications. Most of the genetic differentiation among populations are caused by random drift that should affect all loci across the genome in a similar manner. When a locus shows extraordinary high or low levels of population differentiation, this may be interpreted as evidence for natural selection. The most used measure of population differentiation was devised by Wright and is known as fixation index, or F-ST. We performed a genome-wide estimation of F-ST on about 4 millions of SNPs from HapMap project data. We demonstrated a heterogeneous distribution of F-ST values between autosomes and heterochromosomes. When we compared the F-ST values obtained in this study with another evolutionary measure obtained by comparative interspecific approach, we found that genes under positive selection appeared to show low levels of population differentiation. We applied a gene set approach, widely used for microarray data analysis, to detect functional pathways under selection. We found that one pathway related to antigen processing and presentation showed low levels of F-ST, while several pathways related to cell signalling, growth and morphogenesis showed high F-ST values. Finally, we detected a signature of selection within genes associated with human complex diseases. These results can help to identify which process occurred during human evolution and adaptation to different environments. They also support the hypothesis that common diseases could have a genetic background shaped by human evolution.