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Genome-scale detection of positive selection in nine primates predicts human-virus evolutionary conflicts

Authors :
van der Lee, Robin
Wiel, Laurens
van Dam, Teunis J P
Huynen, Martijn A
Sub Bioinformatics
Theoretical Biology and Bioinformatics
Sub Bioinformatics
Theoretical Biology and Bioinformatics
Source :
Nucleic Acids Research, 45(18), 10634. Oxford University Press, Nucleic Acids Research, gkx704, pp. 10634-10648, Nucleic Acids Research, gkx704, 10634-10648, Nucleic Acids Research
Publication Year :
2017

Abstract

Hotspots of rapid genome evolution hold clues about human adaptation. We present a comparative analysis of nine whole-genome sequenced primates to identify high-confidence targets of positive selection. We find strong statistical evidence for positive selection in 331 protein-coding genes (3%), pinpointing 934 adaptively evolving codons (0.014%). Our new procedure is stringent and reveals substantial artefacts (20% of initial predictions) that have inflated previous estimates. The final 331 positively selected genes (PSG) are strongly enriched for innate and adaptive immunity, secreted and cell membrane proteins (e.g. pattern recognition, complement, cytokines, immune receptors, MHC, Siglecs). We also find evidence for positive selection in reproduction and chromosome segregation (e.g. centromere-associated CENPO, CENPT), apolipoproteins, smell/taste receptors and mitochondrial proteins. Focusing on the virus–host interaction, we retrieve most evolutionary conflicts known to influence antiviral activity (e.g. TRIM5, MAVS, SAMHD1, tetherin) and predict 70 novel cases through integration with virus–human interaction data. Protein structure analysis further identifies positive selection in the interaction interfaces between viruses and their cellular receptors (CD4-HIV; CD46-measles, adenoviruses; CD55-picornaviruses). Finally, primate PSG consistently show high sequence variation in human exomes, suggesting ongoing evolution. Our curated dataset of positive selection is a rich source for studying the genetics underlying human (antiviral) phenotypes. Procedures and data are available at https://github.com/robinvanderlee/positive-selection.

Details

Language :
English
ISSN :
03051048
Database :
OpenAIRE
Journal :
Nucleic Acids Research, 45(18), 10634. Oxford University Press, Nucleic Acids Research, gkx704, pp. 10634-10648, Nucleic Acids Research, gkx704, 10634-10648, Nucleic Acids Research
Accession number :
edsair.doi.dedup.....dba36e4f5cd533b14534588ca9944b5a