Genomic analysis informs malaria evolution

Updated analysis of Plasmodium falciparum malaria reveals markers of antimalarial resistance Detailed comparisons of DNA sequences shared between individuals or groups can allow the inference of relatedness among current members of a species and estimate when they may have been part of the same inte...

Full description

Saved in:
Bibliographic Details
Published in:Science (American Association for the Advancement of Science) 2019-08, Vol.365 (6455), p.752-753
Main Author: Sibley, Carol Hopkins
Format: Article
Language:English
Subjects:
Biological evolution
Deoxyribonucleic acid
DNA
Evolutionary genetics
Gene sequencing
Genetics
Genomes
Genomic analysis
Local population
Malaria
Nucleotide sequence
Parasites
PERSPECTIVES
Plasmodium falciparum
Population genetics
Vector-borne diseases
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c301t-22f6e066f7da887e1f4dcf84f55a830bda06a284756578e095715134459271753
container_end_page 753
container_issue 6455
container_start_page 752
container_title Science (American Association for the Advancement of Science)
container_volume 365
creator Sibley, Carol Hopkins
description Updated analysis of Plasmodium falciparum malaria reveals markers of antimalarial resistance Detailed comparisons of DNA sequences shared between individuals or groups can allow the inference of relatedness among current members of a species and estimate when they may have been part of the same interbreeding population. These approaches have been applied intensively to humans, and they support a detailed model of the origins and relatedness of humans, joining the threads of our common evolutionary history ( 1 ). On page 813 of this issue, Amambua-Ngwa et al. ( 2 ) apply these powerful population genetics techniques to several thousand genomes of Plasmodium falciparum , the deadliest malaria parasite, from a wide range of sites in 15 African countries. Their findings update the evolutionary history of this African parasite and enhance the foundation on which to examine recent selection pressures on local populations. Moreover, they identify genomic signatures that indicate recent selection by current antimalarial drugs.
doi_str_mv 10.1126/science.aay0988
format article
fullrecord <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_2282454568</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>26782239</jstor_id><sourcerecordid>26782239</sourcerecordid><originalsourceid>FETCH-LOGICAL-c301t-22f6e066f7da887e1f4dcf84f55a830bda06a284756578e095715134459271753</originalsourceid><addsrcrecordid>eNpdkE1Lw0AQhhdRbK2ePSkBLyKknf3ePUrRKhS86Dlsk13YkmTrbiL035vS2IOnObzPvMw8CN1imGNMxCKV3ralnRuzB63UGZpi0DzXBOg5mgJQkSuQfIKuUtoCDJmml2hCMaNaKjxFTyvbhsaXmWlNvU8-Zb51ITYpa0xtojeZ_Ql13_nQXqMLZ-pkb8Y5Q1-vL5_Lt3z9sXpfPq_zkgLuckKcsCCEk5VRSlrsWFU6xRznRlHYVAaEIYpJLrhUdjhJYo4pY1wTiSWnM_R47N3F8N3b1BWNT6Wta9Pa0KeCEEUYZ1yoAX34h25DH4dPDpRUwIFhOlCLI1XGkFK0rthF35i4LzAUB43FqLEYNQ4b92Nvv2lsdeL_vA3A3RHYpi7EU06EVIRQTX8Bx_V3Gw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2278050413</pqid></control><display><type>article</type><title>Genomic analysis informs malaria evolution</title><source>Alma/SFX Local Collection</source><source>Science Online科学在线</source><creator>Sibley, Carol Hopkins</creator><creatorcontrib>Sibley, Carol Hopkins</creatorcontrib><description>Updated analysis of Plasmodium falciparum malaria reveals markers of antimalarial resistance Detailed comparisons of DNA sequences shared between individuals or groups can allow the inference of relatedness among current members of a species and estimate when they may have been part of the same interbreeding population. These approaches have been applied intensively to humans, and they support a detailed model of the origins and relatedness of humans, joining the threads of our common evolutionary history ( 1 ). On page 813 of this issue, Amambua-Ngwa et al. ( 2 ) apply these powerful population genetics techniques to several thousand genomes of Plasmodium falciparum , the deadliest malaria parasite, from a wide range of sites in 15 African countries. Their findings update the evolutionary history of this African parasite and enhance the foundation on which to examine recent selection pressures on local populations. Moreover, they identify genomic signatures that indicate recent selection by current antimalarial drugs.</description><identifier>ISSN: 0036-8075</identifier><identifier>EISSN: 1095-9203</identifier><identifier>DOI: 10.1126/science.aay0988</identifier><identifier>PMID: 31439781</identifier><language>eng</language><publisher>United States: American Association for the Advancement of Science</publisher><subject>Biological evolution ; Deoxyribonucleic acid ; DNA ; Evolutionary genetics ; Gene sequencing ; Genetics ; Genomes ; Genomic analysis ; Local population ; Malaria ; Nucleotide sequence ; Parasites ; PERSPECTIVES ; Plasmodium falciparum ; Population genetics ; Vector-borne diseases</subject><ispartof>Science (American Association for the Advancement of Science), 2019-08, Vol.365 (6455), p.752-753</ispartof><rights>Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c301t-22f6e066f7da887e1f4dcf84f55a830bda06a284756578e095715134459271753</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,2871,2872,27905,27906</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31439781$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sibley, Carol Hopkins</creatorcontrib><title>Genomic analysis informs malaria evolution</title><title>Science (American Association for the Advancement of Science)</title><addtitle>Science</addtitle><description>Updated analysis of Plasmodium falciparum malaria reveals markers of antimalarial resistance Detailed comparisons of DNA sequences shared between individuals or groups can allow the inference of relatedness among current members of a species and estimate when they may have been part of the same interbreeding population. These approaches have been applied intensively to humans, and they support a detailed model of the origins and relatedness of humans, joining the threads of our common evolutionary history ( 1 ). On page 813 of this issue, Amambua-Ngwa et al. ( 2 ) apply these powerful population genetics techniques to several thousand genomes of Plasmodium falciparum , the deadliest malaria parasite, from a wide range of sites in 15 African countries. Their findings update the evolutionary history of this African parasite and enhance the foundation on which to examine recent selection pressures on local populations. Moreover, they identify genomic signatures that indicate recent selection by current antimalarial drugs.</description><subject>Biological evolution</subject><subject>Deoxyribonucleic acid</subject><subject>DNA</subject><subject>Evolutionary genetics</subject><subject>Gene sequencing</subject><subject>Genetics</subject><subject>Genomes</subject><subject>Genomic analysis</subject><subject>Local population</subject><subject>Malaria</subject><subject>Nucleotide sequence</subject><subject>Parasites</subject><subject>PERSPECTIVES</subject><subject>Plasmodium falciparum</subject><subject>Population genetics</subject><subject>Vector-borne diseases</subject><issn>0036-8075</issn><issn>1095-9203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNpdkE1Lw0AQhhdRbK2ePSkBLyKknf3ePUrRKhS86Dlsk13YkmTrbiL035vS2IOnObzPvMw8CN1imGNMxCKV3ralnRuzB63UGZpi0DzXBOg5mgJQkSuQfIKuUtoCDJmml2hCMaNaKjxFTyvbhsaXmWlNvU8-Zb51ITYpa0xtojeZ_Ql13_nQXqMLZ-pkb8Y5Q1-vL5_Lt3z9sXpfPq_zkgLuckKcsCCEk5VRSlrsWFU6xRznRlHYVAaEIYpJLrhUdjhJYo4pY1wTiSWnM_R47N3F8N3b1BWNT6Wta9Pa0KeCEEUYZ1yoAX34h25DH4dPDpRUwIFhOlCLI1XGkFK0rthF35i4LzAUB43FqLEYNQ4b92Nvv2lsdeL_vA3A3RHYpi7EU06EVIRQTX8Bx_V3Gw</recordid><startdate>20190823</startdate><enddate>20190823</enddate><creator>Sibley, Carol Hopkins</creator><general>American Association for the Advancement of Science</general><general>The American Association for the Advancement of Science</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QG</scope><scope>7QL</scope><scope>7QP</scope><scope>7QQ</scope><scope>7QR</scope><scope>7SC</scope><scope>7SE</scope><scope>7SN</scope><scope>7SP</scope><scope>7SR</scope><scope>7SS</scope><scope>7T7</scope><scope>7TA</scope><scope>7TB</scope><scope>7TK</scope><scope>7TM</scope><scope>7U5</scope><scope>7U9</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>H94</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20190823</creationdate><title>Genomic analysis informs malaria evolution</title><author>Sibley, Carol Hopkins</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c301t-22f6e066f7da887e1f4dcf84f55a830bda06a284756578e095715134459271753</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Biological evolution</topic><topic>Deoxyribonucleic acid</topic><topic>DNA</topic><topic>Evolutionary genetics</topic><topic>Gene sequencing</topic><topic>Genetics</topic><topic>Genomes</topic><topic>Genomic analysis</topic><topic>Local population</topic><topic>Malaria</topic><topic>Nucleotide sequence</topic><topic>Parasites</topic><topic>PERSPECTIVES</topic><topic>Plasmodium falciparum</topic><topic>Population genetics</topic><topic>Vector-borne diseases</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sibley, Carol Hopkins</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Calcium &amp; Calcified Tissue Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Ecology Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Materials Business File</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Science (American Association for the Advancement of Science)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sibley, Carol Hopkins</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genomic analysis informs malaria evolution</atitle><jtitle>Science (American Association for the Advancement of Science)</jtitle><addtitle>Science</addtitle><date>2019-08-23</date><risdate>2019</risdate><volume>365</volume><issue>6455</issue><spage>752</spage><epage>753</epage><pages>752-753</pages><issn>0036-8075</issn><eissn>1095-9203</eissn><abstract>Updated analysis of Plasmodium falciparum malaria reveals markers of antimalarial resistance Detailed comparisons of DNA sequences shared between individuals or groups can allow the inference of relatedness among current members of a species and estimate when they may have been part of the same interbreeding population. These approaches have been applied intensively to humans, and they support a detailed model of the origins and relatedness of humans, joining the threads of our common evolutionary history ( 1 ). On page 813 of this issue, Amambua-Ngwa et al. ( 2 ) apply these powerful population genetics techniques to several thousand genomes of Plasmodium falciparum , the deadliest malaria parasite, from a wide range of sites in 15 African countries. Their findings update the evolutionary history of this African parasite and enhance the foundation on which to examine recent selection pressures on local populations. Moreover, they identify genomic signatures that indicate recent selection by current antimalarial drugs.</abstract><cop>United States</cop><pub>American Association for the Advancement of Science</pub><pmid>31439781</pmid><doi>10.1126/science.aay0988</doi><tpages>2</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0036-8075
ispartof Science (American Association for the Advancement of Science), 2019-08, Vol.365 (6455), p.752-753
issn 0036-8075
1095-9203
language eng
recordid cdi_proquest_miscellaneous_2282454568
source Alma/SFX Local Collection; Science Online科学在线
subjects Biological evolution
Deoxyribonucleic acid
DNA
Evolutionary genetics
Gene sequencing
Genetics
Genomes
Genomic analysis
Local population
Malaria
Nucleotide sequence
Parasites
PERSPECTIVES
Plasmodium falciparum
Population genetics
Vector-borne diseases
title Genomic analysis informs malaria evolution
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T05%3A44%3A25IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Genomic%20analysis%20informs%20malaria%20evolution&rft.jtitle=Science%20(American%20Association%20for%20the%20Advancement%20of%20Science)&rft.au=Sibley,%20Carol%20Hopkins&rft.date=2019-08-23&rft.volume=365&rft.issue=6455&rft.spage=752&rft.epage=753&rft.pages=752-753&rft.issn=0036-8075&rft.eissn=1095-9203&rft_id=info:doi/10.1126/science.aay0988&rft_dat=%3Cjstor_proqu%3E26782239%3C/jstor_proqu%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c301t-22f6e066f7da887e1f4dcf84f55a830bda06a284756578e095715134459271753%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2278050413&rft_id=info:pmid/31439781&rft_jstor_id=26782239&rfr_iscdi=true