TY - JOUR
T1 - The geography of malaria genetics in the Democratic Republic of Congo
T2 - A complex and fragmented landscape
AU - Carrel, Margaret
AU - Patel, Jaymin
AU - Taylor, Steve M.
AU - Janko, Mark
AU - Mwandagalirwa, Melchior Kashamuka
AU - Tshefu, Antoinette K.
AU - Escalante, Ananias A.
AU - McCollum, Andrea
AU - Alam, Md Tauqeer
AU - Udhayakumar, Venkatachalam
AU - Meshnick, Steven
AU - Emch, Michael
N1 - Funding Information:
This project was supported by grants from the NSF , the Gillings Innovative Laboratory Fund and the NIH . MC and ME are supported by NSF under award number BCS-1339949 . JP and SM are supported by NIH award number 1R56AI097609-01 . SMT is supported by the National Institute of Allergy and Infectious Diseases of the NIH under award number K08AI100924 . We thank Dr. Augustin Okenge (Programme National de Lutte Contre le SIDA, Kinshasa, DRC), Dr. Jeremie Mwonga (Laboratoire National de Reference SIDA et IST, Kinshasa, DRC), and Ann Way, Mohamed Ayad, and Martin Vaessen (all of MeasureDHS, Calverton, MD) for help in obtaining access to the dried blood spots.
Publisher Copyright:
© 2014 Elsevier Ltd.
PY - 2015/5/1
Y1 - 2015/5/1
N2 - Understanding how malaria parasites move between populations is important, particularly given the potential for malaria to be reintroduced into areas where it was previously eliminated. We examine the distribution of malaria genetics across seven sites within the Democratic Republic of Congo (DRC) and two nearby countries, Ghana and Kenya, in order to understand how the relatedness of malaria parasites varies across space, and whether there are barriers to the flow of malaria parasites within the DRC or across borders. Parasite DNA was retrieved from dried blood spots from 7 Demographic and Health Survey sample clusters in the DRC. Malaria genetic characteristics of parasites from Ghana and Kenya were also obtained. For each of 9 geographic sites (7 DRC, 1 Ghana and 1 Kenya), a pair-wise RST statistic was calculated, indicating the genetic distance between malaria parasites found in those locations. Mapping genetics across the spatial extent of the study area indicates a complex genetic landscape, where relatedness between two proximal sites may be relatively high (RST0.64) or low (RST<0.05), and where distal sites also exhibit both high and low genetic similarity. Mantel's tests suggest that malaria genetics differ as geographic distances increase. Principal Coordinate Analysis suggests that genetically related samples are not co-located. Barrier analysis reveals no significant barriers to gene flow between locations. Malaria genetics in the DRC have a complex and fragmented landscape. Limited exchange of genes across space is reflected in greater genetic distance between malaria parasites isolated at greater geographic distances. There is, however, evidence for close genetic ties between distally located sample locations, indicating that movement of malaria parasites and flow of genes is being driven by factors other than distance decay. This research demonstrates the contributions that spatial disease ecology and landscape genetics can make to understanding the evolutionary dynamics of infectious diseases.
AB - Understanding how malaria parasites move between populations is important, particularly given the potential for malaria to be reintroduced into areas where it was previously eliminated. We examine the distribution of malaria genetics across seven sites within the Democratic Republic of Congo (DRC) and two nearby countries, Ghana and Kenya, in order to understand how the relatedness of malaria parasites varies across space, and whether there are barriers to the flow of malaria parasites within the DRC or across borders. Parasite DNA was retrieved from dried blood spots from 7 Demographic and Health Survey sample clusters in the DRC. Malaria genetic characteristics of parasites from Ghana and Kenya were also obtained. For each of 9 geographic sites (7 DRC, 1 Ghana and 1 Kenya), a pair-wise RST statistic was calculated, indicating the genetic distance between malaria parasites found in those locations. Mapping genetics across the spatial extent of the study area indicates a complex genetic landscape, where relatedness between two proximal sites may be relatively high (RST0.64) or low (RST<0.05), and where distal sites also exhibit both high and low genetic similarity. Mantel's tests suggest that malaria genetics differ as geographic distances increase. Principal Coordinate Analysis suggests that genetically related samples are not co-located. Barrier analysis reveals no significant barriers to gene flow between locations. Malaria genetics in the DRC have a complex and fragmented landscape. Limited exchange of genes across space is reflected in greater genetic distance between malaria parasites isolated at greater geographic distances. There is, however, evidence for close genetic ties between distally located sample locations, indicating that movement of malaria parasites and flow of genes is being driven by factors other than distance decay. This research demonstrates the contributions that spatial disease ecology and landscape genetics can make to understanding the evolutionary dynamics of infectious diseases.
KW - Democratic Republic of Congo
KW - Disease ecology
KW - Landscape genetics
KW - Malaria
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U2 - 10.1016/j.socscimed.2014.10.037
DO - 10.1016/j.socscimed.2014.10.037
M3 - Article
AN - SCOPUS:84928124958
SN - 0277-9536
VL - 133
SP - 233
EP - 241
JO - Social Science and Medicine
JF - Social Science and Medicine
ER -