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

Abstract

The spread of modern humans across the globe has led to genetic adaptations to diverse local environments. Recent developments in genomic technologies, statistical analyses, and expanded sampled populations have led to improved identification and fine-mapping of genetic variants associated with adaptations to regional living conditions and dietary practices. Ongoing efforts in sequencing genomes of indigenous populations, accompanied by the growing availability of "-omics" and ancient DNA data, promises a new era in our understanding of recent human evolution and the origins of variable traits and disease risks.

Fig. 1. Examples of human local adaptations, each labeled by the phenotype and/or selection pressure, and the genetic loci under selection

[Adapted from (13)]

Fig. 2. Genomic signatures of local adaptation

(A) A hard sweep. (B) A soft sweep acting on (i) multiple de novo beneficial mutations and (ii) standing variation. (C) Polygenic adaptation. (D) Adaptive introgression. Each horizontal bar represents a haplotype (a sequence of genetic variants on the same chromosome). The orange segment is graded to indicate the strength of linkage disequilibrium between beneficial (stars) and neutral (dots) variants.

Fig. 3. Illustrations of basic concepts of population genetics and methods for detecting recent positive selection

(A) Population genetics terminology. (i) A genetic variant (A/T, red) on the diploid chromosomes of an individual. (ii) The allele frequency of a variant in a population is the fraction of chromosomes containing the variant. In this case, allele frequency of variant T (red) = 0.4. (iii) F_ST measures proportion of genetic differentiation between populations. F_ST = 0 means the two populations have equal allele frequencies. F_ST =1 means the two populations are completely differentiated. (iv) Haplotype homozygosity is the shared stretches of variants between pairs of sampled haplotypes, typically measured around a focal variant (red square) and extending out to flanking variants (light blue). (B) Means of detecting positive selection. (i) Changes in the allele frequency spectrum. Positive selection (red) drives the alleles under selection and the hitchhiking alleles to high frequencies; at the same time, new mutations arise, creating an excess of rare alleles. (ii) F_ST along the genome. High F_ST values indicate loci enriched for targets of selection, with a cutoff (red dashed line) arbitrarily set to be the top 1%. (iii) LSBL, which quantifies branch lengths of a phylogenetic tree with three or more populations by using pairwise F_ST (17). At a locus, long branch length for one population (red) indicates a population-specific divergence. A similar statistic is the PBS. (iv) Haplotype homozygosity statistics [extended haplotype homozygosity (EHH) and integrated haplotype score (iHS)]. Overabundance of a long haplotype (H1, red) surrounding a focal variant indicates positive selection at the locus. The EHH statistic has also been extended to identify population-specific selective sweeps through cross-population comparisons (XP-EHH). (v) Results from GWAS, which identify genetic variants significantly associated with a specific trait (such as height), indicated by red dots on the Manhattan plot (left). Shifts in the frequency distribution of alleles associated with the trait (right) in specific populations (red) compared with the expectation under neutrality (blue) indicates that the trait is under selection. [Part of Fig. 3B is adapted from (27)]