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London School of Hygiene & Tropical Medicine Malaria Centre

Malaria research in parasite biology

Using next-generation sequencing technologies to identify Plasmodium falciparum genomic variation.

LSHTM investigators:
Nuno SepĂșlveda, Mark Preston, Colin Sutherland, David Conway & Taane Clark.
External collaborators:
Samuel Assefa, Susana Campino & Dominic Kwiatkowski (Wellcome Trust Sanger Institute, UK)
Funding body:
Bill & Melinda Gates Foundation.

Structural variations (SVs), such as copy number variations (CNVs), in the Plasmodium falciparum (Pf) genome have been associated with important health-related phenotypes, including anti-malarial drug resistance.

Therefore, there is a great interest for human health in detecting and cataloguing SVs across the Pf genome. Genotyping array platforms, such as comparative genomic hybridization (CGH), have been widely used but could only detect a limited set of SVs. With the advent of next-generation sequencing technologies (NGTs), there is now the full capacity to characterise many types of SVs across the whole genome using the same data. NGTs yield many millions of short sequences per sample, and data from hundreds of isolates are publically available.    

We developed novel statistical methods in order to identify SVs using paired-end mapped sequence alignments and the resulting genomic coverage. These new approaches have the advantage of dealing with the high AT-content of Pf genome that usually affects the analysis due to uneven genomic coverage. We applied these methods to 6 well-characterised laboratory strains from different geographical origins and compared the results with the literature.

We confirmed several loci identified by CGH technologies, including a large amplification at the PfMDR1 locus in the Thailand-origin Dd2 strain and another at the GTP cyclohydrolase I locus across different strains but comprising different length. We also found other SVs that were not detected by previous technologies. These await for experimental validation.  

Ongoing work aims extending the analysis to a large collection of field isolates, complemented by experimental validation, and the development of a web-based exploratory tool for the research community.