Functional analysis of cis-regulatory evolution in humans and other primates


Meeting Abstract

56.2  Jan. 6  Functional analysis of cis-regulatory evolution in humans and other primates BABBITT, Courtney C.*; WRAY, Gregory A.; Center for Evolutionary Genomics, Institute for Genome Science and Policy, Duke University; Center for Evolutionary Genomics, Institute for Genome Science and Policy, Duke University courtney.babbitt@duke.edu

Due to the extensive similarities in coding regions between humans and chimpanzees, it has been proposed that the genomic basis underlying uniquely human traits is due, in large part, to changes in gene expression. However, to date, few specific changes in primate cis-regulatory evolution have been well characterized. Our framework for investigating these changes is to identify and functionally explore instances of positive selection on cis-regulatory regions in the primate lineage, and specifically on the branch leading to humans. The aim of this study is to identify and characterize functional changes in cis-regulatory sequences, specifically those that may have played a role in the evolution of cognitive traits. We are approaching this in two ways: 1) examining candidate genes with known promoter polymorphisms that are statistically associated with affective and developmental disorders in humans; and 2) testing genes showing a high signature of positive selection in the human lineage, as determined by a bioinformatics screen also done in our lab. The 5� flanking regions from multiple humans and representatives of three non-human primate species have been cloned into luciferase reporter constructs. We are transiently transfecting these constructs into appropriate human cell lines, then measuring changes in expression levels using a dual luciferase assay. After identifying the genes with significant functional differences within the human lineage, we plan to test a subset of genes with additional constructs or by association analyses with specific cognitive traits. Combined, these data may identify changes within specific cis-regulatory regions in which the evolution of gene regulation has led to uniquely human traits.

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