Evolutionary genetics of skin pigmentation in African populations

Abstract

Skin color is a highly heritable human trait, and global variation in skin pigmentation has been shaped by natural selection, migration and admixture. Ethnically diverse African populations harbor extremely high levels of genetic and phenotypic diversity, and skin pigmentation varies widely across Africa. Recent genome-wide genetic studies of skin pigmentation in African populations have advanced our understanding of pigmentation biology and human evolutionary history. For example, novel roles in skin pigmentation for loci near MFSD12 and DDB1 have recently been identified in African populations. However, due to an underrepresentation of Africans in human genetic studies, there is still much to learn about the evolutionary genetics of skin pigmentation. Here, we summarize recent progress in skin pigmentation genetics in Africans and discuss the importance of including more ethnically diverse African populations in future genetic studies. In addition, we discuss methods for functional validation of adaptive variants related to skin pigmentation.

Figure 1

Methods of detecting adaptive variants related to skin pigmentation. (1) Genome-wide selection scans identify genomic signatures of natural selection, and some are near pigmentation genes. (2) GWAS localizes variants associated with pigmentation. (3) Overlapping GWAS variants with signatures of natural selection reveals candidate adaptive pigmentation loci.

Figure 2

An integrative functional genomics approach for evolutionary studies. During the dispersal of modern humans, admixture between different populations, archaic introgression and natural selection have shaped the allele frequencies in human populations. The functional alleles (arising de novo or from standing variation) influence an individual’s phenotype (morphological or physiological) and fitness by modulating gene expression (noncoding variants) or changing the protein function (coding variants). The individuals with adaptive variants have a higher probability of survival or reproduction in certain environments (adaptation). The selection signals could be detected by genomic scans of selection and the causal variants could be identified and validated with experimental methods. GWAS could link the potential causal variants with phenotypes and eQTLs could be used to link variants with their target genes. However, both GWAS and eQTL analyses only indicate that association (dashed lines) and experimental validations are necessary for identifying causal variants.