Peaks to genes: Fine mapping of QTLs and functional analysis
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PROJECT SUMMARY Linkage mapping using genetic crosses results in identification of quantitative trait locus (QTL) regions that may contain tens to hundreds of genes. Identification of the causative genes therefore requires careful prioritization of candidate loci, followed by gene manipulation studies to validate the best candidates, and ultimately to determine the causative mutations. Core B will play a critical role in this program project, interfacing with RP01-03 for QTL location, candidate gene prioritization and candidate validation phases of each project. Bulk segregant analysis for QTL location. In the first funding period, we refined methods for rapid mapping of genes underlying QTL using Bulk Segregant Approaches (BSA) that utilize deep sequencing of F2 progeny populations. Core B will sequence and analyze BSA experiments conducted by RP01, RP02 and RP03 to determine the QTLs underlying traits of interest. QTL mapping of P. falciparum typically maps reads to the 3D7 reference sequence, but this limits our ability to localize QTLs to core genome regions. We will generate long-read (nanopore) reference sequences for the parental parasites, which allows accurate mapping across the whole genome. Candidate gene prioritization: Identifying the genes and mutations that underlie traits of interest is a central issue in QTL mapping. Core B will develop and implement bioinformatic and experimental approaches to prioritize candidate genes. We will utilize information from genomic analyses of P. falciparum populations, computation predictions of SNP functionality, as well as information from P. falciparum piggyBac mutagenesis libraries, and rodent malaria (P. berghei) knockout studies. We will also utilize information from expression QTL (eQTL) analyses (RP03), and use nanopore long read sequences to investigate structural variants that may underly phenotypes of interest. Candidate gene validation: We will deploy systematic CRISPR/Cas9 gene editing to determine the loci and specific mutations underlying parasite phenotypes. This will initially use SNP editing to determine causative mutations. We can also use conditional knockouts or conditional protein mislocalization (knock sideways) strategies to examine the role of candidate resistance loci. Where haplotypes contain several causative mutations, we will edit these individually or in combination to examine whether SNPs act additively or epistatically to determine phenotype. These validation experiments will be conducted in close collaboration with projects RP01, RP02 and RP03: Core B will generate the edited parasites, while the projects will conduct the phenotyping experiments to examine links between phenotype and genotype. These studies will (a) develop efficient computational and experimental approaches for rapid identification of genes and causative mutations following QTL location (peaks to genes) and (b) generate gene edited parasite lines, sequence data and bioinformatic tools that will be shared with the community.
