Due to partial isolation of human populations during history, their genetic variation is geographically diverted. Positive natural selection, i.e. the force that drives the increase in prevalence of advantageous traits, has played a central role in human evolution. Genetic differences between human populations are most pronounced in tissues, such as the skin, the intestinal tract or the immune system, that are directly affected by the environment. This led not only to obvious differences in skin color among the populations, but also in different resistance to diseases and diversity in dietary intake, such as the ability to digest milk sugar (lactose). The genetic basis of the variation of human populations and individuals has recently been studied and catalogued by large consortia, such as the HapMap Project and the 1000 Genomes Project. They obtained data via genome-wide genotyping and whole genome sequencing of 2504 subjects and thus allow the study and analysis of the relation of human genomic variation and disease risk.
In this chapter, we will briefly describe the genetic adaption of the anatomically modern human to new geographic and climatic environments in Asia and Europe and the challenges provided by the shift from hunters and gatherers to farmers (Chap. 4). We will discuss how complex phenotypic traits influence the risk to develop diseases, such a T2D and CVD (Chaps. 10 and 11). Each complex disease is based on dozens to hundreds of gene variants, such as single nucleotide polymorphisms (SNPs) and structural variants, such as copy number variations (CNVs). We will describe how the HapMap Project and the 1000 Genomes Project map these genetic variants in different human populations. In this context, we will discuss how whole genome sequencing can result in the identification of rare SNPs that significantly contribute to complex traits and diseases.
KeywordsHuman evolution Human populations Single nucleotide variants Copy number variants Haplotype blocks Next-generation sequencing HapMap Project Genome-wide association studies 1000 Genomes Project
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