Abstract
The mechanistic target of rapamycin (MTOR) pathway regulates cell growth, energy homeostasis, apoptosis, and immune response. The regulatory associated protein of MTOR encoded by the RPTOR gene is a key component of this pathway. A previous survey of candidate genes found that RPTOR contains multiple SNPs with strong correlations between allele frequencies and climate variables, consistent with the action of selective pressures that vary across environments. Using data from a recent genome scan for selection signals, we honed in on a SNP (rs11868112) 26 kb upstream to the transcription start site of RPTOR that exhibits the strongest association with temperature variables. Transcription factor motif scanning and mining of recently mapped transcription factor binding sites identified a binding site for POU class 2 homeobox 1 (POU2F1) spanning the SNP and an adjacent retinoid acid receptor (RAR) binding site. Using expression quantification, chromatin immunoprecipitation (ChIP), and reporter gene assays, we demonstrate that POU2F1 and RARA do bind upstream of the RPTOR gene to regulate its expression in response to retinoids; this regulation is affected by the allele status at rs11868112 with the derived allele resulting in lower expression levels. We propose a model in which the derived allele influences thermogenesis or immune response by altering MTOR pathway activity and thereby increasing fitness in colder climates. Our results show that signatures of genetic adaptations can identify variants with functional effects, consistent with the idea that selection signals may be used for SNP annotation.
Highlights
A major goal of human genetics is to identify functional genomic regions, especially those containing variants that influence common disease susceptibility or disease-related phenotypes
Refining the location of the selection target To refine the location of the polymorphism targeted by climaterelated selective pressures, we mined the results of a recent genome-wide scan for signals of allele frequency correlation with climate variables (Hancock and Di Rienzo, personal communication)
The evidence for the action of selective pressures related to climate was assessed by means of a Bayesian method that yields a Bayes factor (BF), which is a measure of the support for a model in which a SNP allele frequency distribution is linearly dependent on a climate variable in addition to population structure, relative to a model in which the allele frequency distribution is dependent on population structure alone [27]
Summary
A major goal of human genetics is to identify functional genomic regions, especially those containing variants that influence common disease susceptibility or disease-related phenotypes. One approach to the detection of local adaptations searches for correlations between allele frequencies and environmental variables, e.g. latitude or temperature; this approach assumes that the intensity of selection varies across environments and that the variables correlated with allele frequencies are good proxies for the true selective pressure (e.g. temperature is a proxy for cold or heat stress) This approach may be informative for human populations who originated in Sub-Saharan Africa and migrated out of Africa 60–100k years ago to occupy most of the earth landmass [6,7]. During this dispersal, human populations have been exposed to extremely diverse environments, which differ in terms of climate, including temperature, day length, UV radiation, pathogen diversity and other factors. It was recently shown that polymorphisms in candidate genes for metabolic disorders [13], salt homeostasis [14,15], response to stress [16,17], and circadian signaling [18], are strongly correlated with climate variables, providing a possible genetic mechanism for the observed distribution of human phenotypes across populations
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