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Genetic determination and linkage mapping of Plasmodium falciparum malaria related traits in Senegal.

PloS one | 2008

Plasmodium falciparum malaria episodes may vary considerably in their severity and clinical manifestations. There is good evidence that host genetic factors contribute to this variability. To date, most genetic studies aiming at the identification of these genes have used a case/control study design for severe malaria, exploring specific candidate genes. Here, we performed a family-based genetic study of falciparum malaria related phenotypes in two independent longitudinal survey cohorts, as a first step towards the identification of genes and mechanisms involved in the outcome of infection. We studied two Senegalese villages, Dielmo and Ndiop that differ in ethnicity, malaria transmission and endemicity. We performed genome-scan linkage analysis of several malaria-related phenotypes both during clinical attacks and asymptomatic infection. We show evidence for a strong genetic contribution to both the number of clinical falciparum malaria attacks and the asymptomatic parasite density. The asymptomatic parasite density showed linkage to chromosome 5q31 (LOD = 2.26, empirical p = 0.0014, Dielmo), confirming previous findings in other studies. Suggestive linkage values were also obtained at three additional chromosome regions: the number of clinical malaria attacks on chromosome 5p15 (LOD = 2.57, empirical p = 0.001, Dielmo) and 13q13 (LOD = 2.37, empirical p = 0.0014 Dielmo), and the maximum parasite density during asymptomatic infection on chromosome 12q21 (LOD = 3.1, empirical p<10(-4), Ndiop). While regions of linkage show little overlap with genes known to be involved in severe malaria, the four regions appear to overlap with regions linked to asthma or atopy related traits, suggesting that common immune related pathways may be involved.

Pubmed ID: 18431485 RIS Download

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MERLIN (tool)

RRID:SCR_009289

Software application that carries out single-point and multipoint analyses of pedigree data, including IBD and kinship calculations, nonparametric and variance component linkage analyses, error detection and information content mapping. For multipoint analyses in dense maps, Merlin allows the user to impose constraints on the number of recombinants between consecutive markers. Merlin estimates haplotypes by finding the most likely path of gene flow or by sampling paths of gene flow at all markers jointly. It can also list all possible nonrecombinant haplotypes within short regions. Finally, Merlin provides swap-file support for handling very large numbers of markers as well as gene-dropping simulations for estimating empirical significance levels. (entry from Genetic Analysis Software)

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