SUMMARY The transcriptional response to drug exposure shapes the ability for a parasite to survive and grow during and after treatment. During the prior grant period, we developed multiple tools to identify the drivers of drug resistance. Single cell RNAseq of Plasmodium falciparum genetic crosses now enables rapid, robust estimation of single cell expression quantitative trait loci (SCeQTLs) across the parasite life cycle. Pseudo Bulk Segregant Analysis (pseudoBSA) now enables rapid linking of phenotypic variation to QTLs. We will use these tools to capture the dynamic response of resistant and sensitive parasites to drug treatment. In Specific Aim 1, we will define transcriptional networks associated with growth under drug exposure, and with rapid recovery after treatment. We will identify which loci in the parasite genomes drive drug resistance and recovery using pseudoBSA. We will identify SCeQTLs that link together drug response to growth and recovery. In concert with Core B, we will identify high confidence polymorphisms that regulate the transcriptional response to drug exposure and validate these with CRISPR/Cas9 gene editing. In Specific Aim 2, we will leverage this platform to identify compensatory mutations relieving the impact of resistance mutations on parasite fitness and understand their mechanism of action. This will involve novel genetic cross generation with Core A.