Going global by adapting local: A review of recent human adaptation

Short stature

One distinctive phenotype thought to be adaptive to a tropical rainforest environment is short stature (commonly referred to as a “pygmy” phenotype), which is defined as an average height of <150 cm in adult males. The short stature trait is an example of convergent evolution in rainforest hunter-gatherer (RFHG) populations across Africa, Asia, and South America. Selection for small body size may be due to limited food resources, resistance to heat stress, immune response, and/or a trade-off between early onset of reproduction and cessation of growth (14, 15). Perturbations in the GH1-IGF1 pathway have been implicated to play a role in short stature in RFHG populations in central Africa and southeast Asia (16).

In central African RFHG populations where admixture with neighboring populations is common, short stature is significantly correlated with ancestry and is highly heritable (14). Central African RFHG–specific genomic adaptations were identified through comparisons with other African populations by using methods such as locus-specific branch length (LSBL) (17) and XP-EHH (3) tests, which have high power to detect population-specific positive selection (Fig. 3B). These tests identified a 15-Mb region on chromosome 3 that shows signatures of strong positive selection (14). Several genes in this region are associated with short stature in Pygmies, including DOCK3, which is associated with height variation in non-Africans, and CISH, which is important in immune response but also inhibits human growth hormone receptor activity, indicating that short stature could be a product of selection acting on pleiotropic loci (14). A subsequent study discovered a ~200-kb haplotype containing HESX1 at high frequency in central African RFHGs but low frequency in other African populations; HESX1 is involved in the development of the anterior pituitary, where growth hormone is produced (18). This haplotype was not tagged in previous genotyping arrays, demonstrating the importance of including ethnically diverse populations in whole-genome sequencing studies (18). However, RFHG and neighboring agriculturalist populations in Uganda exhibit a distinct set of loci associated with short stature, which raises the possibility of convergent evolution of this trait across the RFHGs in Africa (15).

The studies discussed above suggest that short stature in central African RFHG is mostly driven by strong selection affecting a relatively small number of loci of moderate to strong effect. In contrast, hundreds of loci are associated with European height variation (19, 20). Detecting selection on a polygenic trait such as height is difficult because the causative variants can be ancient polymorphisms each of relatively small effect. Several recent methods use GWAS to identify trait-associated variants then test for allele frequency shifts between populations [either unweighted (20) or weighted by effect size (21)] greater than expected from neutral drift. Polygenic selection tests using GWAS data (Fig. 2C) have suggested weak selection influencing average height differences among European populations, with Northern Europeans generally being taller than Southern Europeans (20, 21). A recent aDNA analysis of Neolithic European populations suggests that the North-South European height gradient may reflect selection for shorter height in Early Neolithic migrants into southern Europe and admixture of taller steppe populations with northern Europeans (11). Although analysis of aDNA holds great promise for revealing human phenotypic history, this approach faces challenges for studies of indigenous populations such as RFHG because DNA is not well-preserved in tropical climates, and large-scale GWAS are not available.

Adaptation to endemic pathogens

Pathogenic environments are an important driver of local adaptation in humans (22), and nowhere is the challenge of survival from pathogens greater than in tropical rainforests. In particular, malaria, a mosquito-borne protozoan parasitic infection, is a major cause of mortality in sub-Saharan Africa. The most lethal malarial species, Plasmodium falciparum, causes >1 million child deaths in Africa each year (23). Tropical populations have long been known to have genetic variants that confer resistance to malaria, including the sickle cell, α⁺- and β⁺-thalassemia–causing alleles at the hemoglobin loci, as well as variants at ABO, GYPA, GYPB, GYPE, and G6PD [reviewed in (23)]. These variants are likely adaptive, as initially evidenced by the strong correlation between allele frequency and prevalence of malaria infection. However, several malaria-protective variants also cause common Mendelian diseases in hemi- or homozygotes [such as sickle cell anemia, G6PD deficiency, and thalassemia (23)] and are maintained through balancing selection.

Another example of adaptation to pathogens resulting in high frequencies of genetic variants associated with disease is at the APOL1 locus. The “G1” and “G2” genetic variants in the last exon of APOL1 are associated with chronic kidney disease, which is disproportionately common among individuals of African descent (24). These variants also confer resistance to human African trypanosomes (causing “African sleeping sickness”) by modifying the protein to lyse Trypanosoma brucei rhodesiense, a parasitic protozoa transmitted by the tsetse fly. The region flanking the G1 and G2 variants appear to be under recent positive selection, as indicated by extended haplotype homozygosity (25). G1 and G2 are common in some western African populations, but T.b. rhodesiense is currently common only in eastern and southern Africa, which raises questions about the evolutionary history of the APOL1 locus and the pleiotropic effects of G1 and G2 (25).

Unearthing human adaptation with aDNA

aDNA sequencing provides a direct historical record of genomic variation and provides new possibilities for inferring recent human evolutionary history of modern phenotypes. Studies based on comparison of modern human with Neandertal and Denisovan genomes have found evidence of adaptive archaic haplotypes in genes related to innate immune response, metabolism, and skin phenotypes in ethnically diverse modern human populations [reviewed in (1)]. Future studies of aDNA will be informative for reconstructing the origin of functional variants and inferring the strength of selection based on direct observation of changes in allele frequencies over time (37). However, current understanding of ancient adaptation events is limited by sparse aDNA data over broad geographic and temporal scales. Moreover, methods for studying ancient genotype variation tend to focus on ascertained variants in specific populations, particularly Europeans (1).

Adaptive potential of structural variation

Structural variants (SVs)—including duplications, copy number variants, deletions, insertions, and inversions—encompass a much larger fraction of the genome than single-nucleotide polymorphisms (SNPs) [~4.1 million to 5.0 million base pairs for SNPs compared with ~20 million base pairs for SVs (38)] and may consequently have substantial contributions to human adaptive evolution (39). For example, Perry et al. (40) observed higher copy numbers of AMY1, an enzyme that breaks down starches, in populations with high-starch diets. Further, a common inversion polymorphism at chromosome 17q21.31 is hypothesized to be under positive selection in Europeans because of increased fecundity of women carrying the inverted haplotype (41). However, SVs are extremely challenging to detect by using short-read sequencing technologies. The development of cost-effective high-throughput methods for obtaining long-sequence reads and novel computational approaches will facilitate identification and characterization of SVs in the future (42).

Challenges to detecting selection

Although numerous methods for detecting selection have been developed, there is a known lack of concordance across methods (43), partly because of the different selection time scales each method is capable of detecting (44). Strong positive selection on a de novo (newly arising) mutation is the classic process that many methods have been devised to detect, in which the haplotype containing the beneficial variant rapidly rises in frequency in the population, resulting in long stretches of identical haplotypes around the selected variant within the population (Figs. 2 and 3). There is some debate over the fraction of the human genome affected by selective sweeps within the past ~250,000 years, in part owing to complexities in accounting for background selection that purges deleterious genetic variation (45, 46) and the difficulty in detecting simultaneous selection on multiple beneficial haplotypes at a locus (“soft sweeps”) (Fig. 2B) (47). Although recent methods have increased the power to scan for soft sweeps (48, 49), their detection is still limited because of relatively weak genomic signals (50) and because regions flanking a hard sweep (the “shoulders”) can mimic a soft sweep (51, 52). Development of machine-learning methods, which can effectively “learn” the appropriate signals within complex data when given training examples, may be effective for detecting hard and soft selective sweeps (53).

Perhaps the largest challenge to detecting selection is the fact that most traits are polygenic. It is difficult to distinguish small frequency shifts over large numbers of independent loci (Fig. 2C) from neutral drift without knowing a priori which trait is under selection and the genetic variants that influence the trait. Incorporating the results of GWAS into selection tests (20, 21) is one promising avenue to identify cases of polygenic adaptation, although such integration will have to overcome issues common to genetic association tests, including ascertainment bias in the set of genotyped variants, population stratification, and a lack of observed heritability (“missing heritability”).

Integration of genetic, phenotypic, and functional data into adaptation studies

The best-characterized human adaptive variants are those related to Mendelian, or near Mendelian, traits for which the adaptive phenotype can be easily distinguished (for example, LP and skin pigmentation). Characterizing the functional variants that affect nonobvious or intermediate phenotypes—such as blood metabolite levels, gene expression across cell types, and epigenetic modifications—motivates the need for detailed phenotyping of global populations based on “-omics” profiling (such as transcriptomics, metabolomics, or epigenomics). Additionally, integration of genome-wide selection scans with GWAS helps improve the power of genotype-phenotype association analyses by localizing putative regions with a functional impact. This is particularly important in studies of indigenous populations, in which obtaining large sample sizes is challenging. Lastly, functional experiments in model organisms can directly establish the link between candidate adaptive variants and phenotypes. For example, a derived allele at the EDAR locus (EDAR370A) is significantly associated with hair thickness and dental morphology [reviewed in (27)] and is a target of recent strong positive selection in Asian populations (3, 54). Development of humanized mice containing EDAR370A replicated the hair thickness phenotype and also identified previously unknown phenotypic impact on mammary and eccrine glands (55). With the development of in vitro and in vivo technologies, such as tissue-specific cell lines, genome/RNA-editing (such as CRISPR technology), and induced pluripotent stem cells, it is increasingly possible to validate the function of adaptive variants in humans.