Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/153453
Title: Population-specific adaptation in malaria-endemic regions of Asia
Authors: Gusareva, Elena S.
Lorenzini, Paolo Alberto
Nurul Adilah Ramli
Ghosh, Amit Gourav
Kim, Hie Lim
Keywords: Science::Biological sciences
Social sciences::General
Issue Date: 2021
Source: Gusareva, E. S., Lorenzini, P. A., Nurul Adilah Ramli, Ghosh, A. G. & Kim, H. L. (2021). Population-specific adaptation in malaria-endemic regions of Asia. Journal of Bioinformatics and Computational Biology, 19(6), 2140006-. https://dx.doi.org/10.1142/S0219720021400060
Project: 2017-T1-001-046 
Journal: Journal of Bioinformatics and Computational Biology 
Abstract: Evolutionary mechanisms of adaptation to malaria are understudied in Asian endemic regions despite a high prevalence of malaria in the region. In our research, we performed genome-wide screening for footprints of natural selection against malaria by comparing eight Asian population groups from malaria-endemic regions with two non-endemic population groups from Europe and Mongolia. We identified 285 adaptive genes showing robust selection signals across three statistical methods, iHS, XP-EHH, and PBS. Interestingly, most of the identified genes (82%) were found to be under selection in a single population group, while adaptive genes shared across populations were rare. This is likely due to the independent adaptation history in different endemic populations. The gene ontology analysis for the 285 adaptive genes highlighted their functional processes linked to neuronal organizations or nervous system development. These genes could be related to cerebral malaria and may reduce the inflammatory response and the severity of malaria symptoms. Remarkably, our novel population genomic approach identified population-specific adaptive genes potentially against malaria infection without the need for patient samples or individual medical records.
URI: https://hdl.handle.net/10356/153453
ISSN: 0219-7200
DOI: 10.1142/S0219720021400060
Rights: © 2021 The Author(s). This is an Open Access article published by World Scienti ̄c Publishing Company. It is distributed underthe terms of the Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC) License which permitsuse, distribution and reproduction in any medium, provided that the original work is properly cited and isused for non-commercial purposes.
Fulltext Permission: open
Fulltext Availability: With Fulltext
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SCELSE Journal Articles

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