Network-level and population genetics analysis of the insulin/TOR signal transduction pathway across human populations

Abstract

Genes and proteins rarely act in isolation, but they rather operate as components of complex networks of interacting molecules. Therefore, for understanding their evolution, it may be helpful to take into account the interaction networks in which they participate. It has been shown that selective constraints acting on genes depend on the position that they occupy in the network. Less understood is how the impact of local adaptation at the intraspecific level is affected by the network structure. Here, we analyzed the patterns of molecular evolution of 67 genes involved in the insulin/target of rapamycin (TOR) signal transduction pathway. This well-characterized pathway plays a key role in fundamental processes such as energetic metabolism, growth, reproduction, and aging and is involved in metabolic disorders such as obesity, insulin resistance, and diabetes. For that purpose, we combined genotype data from worldwide human populations with current knowledge of the structure and function of the pathway. We identified the footprint of recent positive selection in nine of the studied genomic regions. Most of the adaptation signals were observed among Middle East and North African, European, and Central South Asian populations. We found that positive selection preferentially targets the most central elements in the pathway, in contrast to previous observations in the whole human interactome. This observation indicates that the impact of positive selection on genes involved in the insulin/TOR pathway is affected by the pathway structure.

This work was funded by grants BFU2010-19443 (subprogram BMC) awarded by Ministerio de Educación y Ciencia (Spain) and the Direcció General de Recerca, Generalitat de Catalunya (Grup de Recerca Consolidat 2009 SGR 1101). P.L. is supported by a PhD fellowship from "Acción Estratégica de Salud, en el marco del Plan Nacional de Investigación Científica, Desarrollo e Innovación Tecnológica 2008-2011" from Instituto de Salud Carlos III.