By: Oliver Billker, Wellcome Trust Sanger Institute, UK

Title: Functional genoms profiling of a malaria parasite by simultaneous in vivo phenotyping of thousands of barcoded mutants

More than a decade after the completion of the first Plasmodium genome, around a third of that genome remains annotated as hypothetical genes with no known function. While experimental genetics has made a major contribution to understanding gene function in the intervening years, the combined research effort of the malaria community has so far targeted only roughly 600 genes, leaving nearly >85% of the genome unexplored. The technical difficulties associated with modifying the AT and repeat-rich genomes of important Plasmodium species has prompted us to develop new methods to scale up experimental genetics in P. berghei, a malaria parasite infecting rodents. We created an open access project, called PlasmoGEM to generate a genome scale resource of individually barcoded gene targeting vectors. We have now used these to phenotype 2571 P. berghei mutants for their competitive fitness during asexually replicating blood stages by barcode counting on a next generation sequencer. We show that two thirds of parasite genes are required for full competitive fitness of just a single life cycle stage, an unexpectedly large proportion when compared to the much smaller essentialomes of cultured yeast or human cells. Genes with 1:1 orthologs in distant eukaryotes were enriched for essentiality, while in contrast, the vast majority of genes whose expression peaks in sexual stages were readily disrupted without growth phenotype. In a major step towards the systematic experimental prioritisation of drug targets, the relative importance in vivo of many parasite biochemical pathways can now be predicted from the fitness phenotypes of their corresponding genes. A substantial number of P. berghei genes have previously remained unstudied because they lack annotated domains or conserved orthologs outside Plasmodium. We find these genes are no less important and most likely account for a large quantity of unknown but important biology.