title: Functional Genomic Insights into Regulatory Mechanisms of High-Altitude Adaptation.
abstract: Recent studies of indigenous human populations at high altitude have provided proof-of-principle that genome scans of DNA polymorphism can be used to identify candidate loci for hypoxia adaptation. When integrated with experimental analyses of physiological phenotypes, genome-wide surveys of DNA polymorphism and tissue-specific transcriptional profiles can provide insights into actual mechanisms of adaptation. It has been suggested that adaptive phenotypic evolution is largely mediated by cis-regulatory changes in genes that are located at integrative control points in regulatory networks. This hypothesis can be tested by conducting transcriptomic analyses of hypoxic signaling pathways in conjunction with experimental measures of vascular oxygen supply and metabolic pathway flux. Such studies may reveal whether the architecture of gene regulatory networks can be used to predict which loci (and which types of loci) are likely to be "hot spots" for adaptive physiological evolution. Functional genomic studies of deer mice (Peromyscus maniculatus) demonstrate how the integrated analysis of variation in tissue-specific transcriptomes, whole-animal physiological performance, and various subordinate traits can yield insights into the mechanistic underpinnings of high-altitude adaptation.
authors.affiliation: School of Biological Sciences, University of Nebraska, Lincoln, NE, USA. jstorz2@unl.edu.
authors.forename: Jay F
authors.initials: JF
authors.lastname: Storz
authors.affiliation: Division of Biological Sciences, University of Montana, Missoula, MT, USA.
authors.forename: Zachary A
authors.initials: ZA
authors.lastname: Cheviron
mesh_terms: D000222:Adaptation, Physiological / Q000235:genetics*; D000531:Altitude; D000818:Animals; D005786:Gene Expression Regulation; D014644:Genetic Variation; D023281:Genomics; D006801:Humans; D014158:Transcription, Genetic
keywords: Functional genomics; Hypoxia; Peromyscus; Population genomics; Systems genetics; Transcriptomics