Journal Article

On Characterizing Adaptive Events Unique to Modern Humans

Jessica L. Crisci, Alex Wong, Jeffrey M. Good and Jeffrey D. Jensen

in Genome Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 3, issue , pages 791-798
Published in print January 2011 |
Published online July 2011 | e-ISSN: 1759-6653 | DOI:

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  • Bioinformatics and Computational Biology
  • Evolutionary Biology
  • Genetics and Genomics


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Ever since the first draft of the human genome was completed in 2001, there has been increased interest in identifying genetic changes that are uniquely human, which could account for our distinct morphological and cognitive capabilities with respect to other apes. Recently, draft sequences of two extinct hominin genomes, a Neanderthal and Denisovan, have been released. These two genomes provide a much greater resolution to identify human-specific genetic differences than the chimpanzee, our closest extant relative. The Neanderthal genome paper presented a list of regions putatively targeted by positive selection around the time of the human–Neanderthal split. We here seek to characterize the evolutionary history of these candidate regions—examining evidence for selective sweeps in modern human populations as well as for accelerated adaptive evolution across apes. Results indicate that 3 of the top 20 candidate regions show evidence of selection in at least one modern human population (P < 5 × 105). Additionally, four genes within the top 20 regions show accelerated amino acid substitutions across multiple apes (P < 0.01), suggesting importance across deeper evolutionary time. These results highlight the importance of evaluating evolutionary processes across both recent and ancient evolutionary timescales and intriguingly suggest a list of candidate genes that may have been uniquely important around the time of the human–Neanderthal split.

Keywords: adaptation; Neanderthal genomics; selective sweeps

Journal Article.  5022 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology ; Evolutionary Biology ; Genetics and Genomics

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