Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2013 Jul;23(7):1089-96.
doi: 10.1101/gr.152710.112. Epub 2013 Mar 28.

Gene expression drives local adaptation in humans

Hunter B Fraser  1
Affiliations

Gene expression drives local adaptation in humans

Hunter B Fraser. Genome Res. 2013 Jul.

Abstract

The molecular basis of adaptation--and, in particular, the relative roles of protein-coding versus gene expression changes--has long been the subject of speculation and debate. Recently, the genotyping of diverse human populations has led to the identification of many putative "local adaptations" that differ between populations. Here I show that these local adaptations are over 10-fold more likely to affect gene expression than amino acid sequence. In addition, a novel framework for identifying polygenic local adaptations detects recent positive selection on the expression levels of genes involved in UV radiation response, immune cell proliferation, and diabetes-related pathways. These results provide the first examples of polygenic gene expression adaptation in humans, as well as the first genome-scale support for the hypothesis that changes in gene expression have driven human adaptation.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
(A) Outline of the data sets integrated to identify putative local adaptations (Hancock et al. 2011) and to assess the relative importance of cis-regulatory variants compared with nonsynonymous variants among these adaptations. (B) The estimated number of putative local adaptations associated with each of nine climate/geographic variables that are explicable by either a nonsynonymous SNP (green), eSNP (red), CRE SNP (blue), or combined eSNP/CRE SNP (purple). Error bars indicate the standard deviations when randomly sampling negative control SNPs (see Methods). Various controls are shown in Supplemental Figures 1–5.
Figure 2.
Figure 2.
(A) Venn diagram showing DNA damage response as the most highly enriched functional category in the intersection between skin eSNPs and summer shortwave radiation (sunlight)–associated local-adaptation SNPs. The seven DNA damage response genes in this intersection are listed, with eSNPs that affect their expression levels in skin. Circles and overlap are not to scale. (B) The derived allele frequencies of one SNP in the skin eSNP/summer sunlight–associated SNP intersection (rs10458216) plotted against summer shortwave radiation flux in 58 worldwide human populations, split into four geographic regions. The derived allele is associated with lower expression of EEF1E1 (also known as AIMP3) (a tumor-suppressor gene that activates the DNA damage response in response to UV exposure and other DNA-damaging agents) (Kwon et al. 2011) in skin. Population names and additional data are shown in Supplemental Figure 6.
Figure 3.
Figure 3.
(A) Outline of the approach for identifying polygenic gene expression adaptations. (B–D) The three gene sets with significant associations (after correction for multiple tests; see Methods). Plots show their expression scores in each population versus the most strongly associated variable. Points are colored according to geographical regions listed in the insets; the two green points in each plot represent populations from Oceania. (B) Expression scores for the “UV down-regulation” gene set compared with absolute latitude. (C) Expression scores for the “Diabetes pathways” gene set compared with absolute latitude. (D) Expression scores for the “Positive regulation of cell proliferation” gene set (of which most eSNP target genes were immune-related) (Supplemental Table 2) compared with latitude.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Akey JM 2009. Constructing genomic maps of positive selection in humans: Where do we go from here? Genome Res 19: 711–722 - PMC - PubMed
    1. Barker D, Dixon K, Medrano EE, Smalara D, Im S, Mitchell D, Babcock G, Abdel-Malek ZA 1995. Comparison of the responses of human melanocytes with different melanin contents to ultraviolet B irradiation. Cancer Res 55: 4041–4046 - PubMed
    1. Chen R, Corona E, Sikora M, Dudley JT, Morgan AA, Moreno-Estrada A, Nilsen GB, Ruau D, Lincoln SE, Bustamante CD, et al. 2012. Type 2 diabetes risk alleles demonstrate extreme directional differentiation among human populations, compared to other diseases. PLoS Genet 8: e1002621. - PMC - PubMed
    1. Cheung VG, Spielman RS 2009. Genetics of human gene expression: Mapping DNA variants that influence gene expression. Nat Rev Genet 10: 595–604 - PMC - PubMed
    1. Ding J, Gudjonsson JE, Liang L, Stuart PE, Li Y, Chen W, Weichenthal M, Ellinghaus E, Franke A, Cookson W, et al. 2010. Gene expression in skin and lymphoblastoid cells: Refined statistical method reveals extensive overlap in cis-eQTL signals. Am J Hum Genet 87: 779–789 - PMC - PubMed

Publication types