Population-specific adaptation in malaria-endemic regions of Asia
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 malar...
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sg-ntu-dr.10356-1534532022-01-01T20:12:09Z Population-specific adaptation in malaria-endemic regions of Asia Gusareva, Elena S. Lorenzini, Paolo Alberto Nurul Adilah Ramli Ghosh, Amit Gourav Kim, Hie Lim Asian School of the Environment GenomeAsia 100K Consortium Singapore Centre for Environmental Life Sciences and Engineering (SCELSE) Science::Biological sciences Social sciences::General Malaria Natural Selection Adaptive Genes Infectious Disease Nervous System Cerebral Malaria 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. Ministry of Education (MOE) Published version This research was supported by the Singapore Ministry of Education, Academic Research Fund Tier 1 (2017-T1-001-046). The computational work for this article was performed in part on resources of the National Supercomputing Centre, Singapore (https://www.nscc.sg) supported by Project 12000454. 2021-12-03T06:33:48Z 2021-12-03T06:33:48Z 2021 Journal Article 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 0219-7200 https://hdl.handle.net/10356/153453 10.1142/S0219720021400060 6 19 2140006 en 2017-T1-001-046 Journal of Bioinformatics and Computational Biology © 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. application/pdf |
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Science::Biological sciences Social sciences::General Malaria Natural Selection Adaptive Genes Infectious Disease Nervous System Cerebral Malaria Gusareva, Elena S. Lorenzini, Paolo Alberto Nurul Adilah Ramli Ghosh, Amit Gourav Kim, Hie Lim Population-specific adaptation in malaria-endemic regions of Asia |
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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. |
author2 |
Asian School of the Environment |
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Asian School of the Environment Gusareva, Elena S. Lorenzini, Paolo Alberto Nurul Adilah Ramli Ghosh, Amit Gourav Kim, Hie Lim |
format |
Article |
author |
Gusareva, Elena S. Lorenzini, Paolo Alberto Nurul Adilah Ramli Ghosh, Amit Gourav Kim, Hie Lim |
author_sort |
Gusareva, Elena S. |
title |
Population-specific adaptation in malaria-endemic regions of Asia |
title_short |
Population-specific adaptation in malaria-endemic regions of Asia |
title_full |
Population-specific adaptation in malaria-endemic regions of Asia |
title_fullStr |
Population-specific adaptation in malaria-endemic regions of Asia |
title_full_unstemmed |
Population-specific adaptation in malaria-endemic regions of Asia |
title_sort |
population-specific adaptation in malaria-endemic regions of asia |
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2021 |
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https://hdl.handle.net/10356/153453 |
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1722355362114306048 |