# Systems genetics of artemisinin resistance

> **NIH NIH P01** · UNIVERSITY OF NOTRE DAME · 2021 · $438,154

## Abstract

ABSTRACT
The ability to conduct experimental genetic crosses in malaria using humanized mice provides exciting
opportunities for genetic analysis of Plasmodium falciparum. Systems genetics approaches can complement
these efforts, because transcription of RNA, translation into proteins and metabolism of these proteins, provide
the critical intermediate steps that link genotype and phenotype. We will characterize the transcriptional,
proteomic and metabolomic signatures of both parental parasites and progeny from three genetic crosses
generated by Core A (Experimental Genetic Crosses). To generate the material needed, we will grow and
harvest tightly synchronized parasite cultures (2 replicates) at 6 hr intervals throughout the parasites lifecycle for
extraction of mRNA, proteins and metabolites: RNAseq, proteomic and metabolomic characterization will then
be conducted by Core C (Genomics). The systems datasets generated will be used to ask both applied and
fundamental questions about parasite biology: (i) We hypothesis that `omic' data collected will provide key
insights into the mechanism of resistance, the metabolic networks involved in resistance and cost of resistance.
Systems genetic analyses in a linkage mapping framework will show how additional loci impact artemisinin
resistance, and the reasons that kelch13 alleles vary in level of resistance observed. (ii) we hypothesize that the
systems biology paradigms emerging from studies of model organism will fit poorly for malaria. P. falciparum is
fundamentally different from models organism in having just-in-time cascades of mRNA production across the
lifecycle and few encoded transcription factors. We will conduct genome wide QTL analyses of mRNA, proteins
and metabolites to investigate the interplay and feedback between genes, mRNA, proteins and metabolites to
test this hypothesis. These analyses will explore the level at which protein abundance is regulated, and the
relative importance of SNPs, microsatellites and copy number variation in driving regulatory evolution. These
analyses will involve strong collaboration with Core B (Data Integration and Analysis Core) and RP02 (Drug
Resistance Profiling and QTL mapping) in Notre Dame. The RNAseq, proteomics and metabolomics data will
be made publically available for use by the malaria research community.

## Key facts

- **NIH application ID:** 10216649
- **Project number:** 5P01AI127338-05
- **Recipient organization:** UNIVERSITY OF NOTRE DAME
- **Principal Investigator:** Tim J Anderson
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $438,154
- **Award type:** 5
- **Project period:** 2017-08-01 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10216649

## Citation

> US National Institutes of Health, RePORTER application 10216649, Systems genetics of artemisinin resistance (5P01AI127338-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10216649. Licensed CC0.

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