Research Article: Genome-Wide Scan for Signatures of Human Population Differentiation and Their Relationship with Natural Selection, Functional Pathways and Diseases

Date Published: November 20, 2009

Publisher: Public Library of Science

Author(s): Roberto Amato, Michele Pinelli, Antonella Monticelli, Davide Marino, Gennaro Miele, Sergio Cocozza, Jason E. Stajich.

Abstract: 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 FST. We performed a genome-wide estimation of FST on about 4 millions of SNPs from HapMap project data. We demonstrated a heterogeneous distribution of FST values between autosomes and heterochromosomes. When we compared the FST 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 FST, while several pathways related to cell signalling, growth and morphogenesis showed high FST 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.

Partial Text: Genetic differences are present in humans at both individual and population level. Human genetic variations are studied for their evolutionary relevance and for their potential medical applications. This studies can help scientists in understanding ancient human population migrations as well as how selective forces act on the human being [1], [2].

Using FST, we estimated populations differentiation for 3,917,301 SNPs in population samples from the International HapMap Project data (Public release 27, merged II + III). To retain the largest number of SNPs broadly reflecting a continental subdivision, we used data from Yoruba (Africa), Japanese (Asia), Han Chinese (Asia) and CEPH (European descendant) individuals. Combining data from these populations we were able to compare the largest set of genotyped SNPs up to now available. We pooled Japanese and Han Chinese samples due to their geographical closeness. Furthermore, this pooling allowed us to compare our data with previous studies [20], [11]. FST was estimated according to Weir and Cockerham [18], [21].

The study of the evolutionary forces acting in diseases and physiological traits is an exciting field that may drive further researches and, in the future, public health policies. The study of population genetic differentiation could help the understanding of human evolution, demographic history and disease susceptibility [26]. To study population differentiation we performed a genome-wide FST calculation using the latest available data release from the HapMap. Using this release we were able to increase both the number of SNPs and the number of individuals analysed in comparison to recent analogous studies [15]. We focused on samples from three different continents (Africa, Asia, Europe) to obtain a broad but sound measure of populations differentiation.



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