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.

Human and Hummingbird Hemoglobin Concentrations and MetabolicRhythms at Altitude Determined with Statistical Modeling

“…Functional amino acid substitutions in hemoglobin also occur in many other altitude vertebrates who live at high altitudes [22]. However, there is no good evidence to date that any of those variants enhance respiratory function at altitude or provide a fitness advantage under any circumstances [16].…”

“…This phenotypic convergence is remarkable considering the contrasting evolutionary histories of these two taxa at altitude. Humans colonized high altitude thousands of years ago and maintained gene flow between high and low altitude populations [15] in contrast, several lineages within the hummingbird clade colonized altitude millions of years ago and gave rise to numerous high-altitude specialist species that long ago stopped exchanging genes with lowland relatives [16].…”

Global variation in gene expression and the value of diverse sampling

“…To understand inter-population gene expression variation in a native tissue, Hughes et al [23] studied placental samples from four American ethnic groups (see Table 1), estimating that 7.8% of variation in gene expression was between-groups. Genes with significant between-group expression variance were found to be enriched for functions related to immune response, cell signaling, and metabolism, which are all phenotypes that can have adaptive significance [24,25]. …”

Inferences of African evolutionary history from genomic data

“…F ST , LSBL, PSB, XPCLR) (reviewed in Scheinfeldt and Tishkoff [44] and Fan et al . [45]). If these targets of selection fall within a genomic region associated with a putative function, the adaptive phenotype can potentially be inferred.…”