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Updated: Jul 13, 2025
Author Spotlight: Identifying Compensatory Pathways in Malaria Parasites Containing Hypomorphic Allele of Essential Protein Kinases
Published on: November 22, 2024
MalariaSED: a deep learning framework to decipher the regulatory contributions of noncoding variants in malaria
Chengqi Wang1, Yibo Dong2,3, Chang Li2
1Center for Global Health and Infectious Diseases Research and USF Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA. chengqi@usf.edu.
Abstract:
Malaria remains one of the deadliest infectious diseases. Transcriptional regulation effects of noncoding variants in this unusual genome of malaria parasites remain elusive. We developed a sequence-based, ab initio deep learning framework, MalariaSED, for predicting chromatin profiles in malaria parasites. The MalariaSED performance was validated by published ChIP-qPCR and TF motifs results. Applying MalariaSED to ~ 1.3 million variants shows that geographically differentiated noncoding variants are associated with parasite invasion and drug resistance. Further analysis reveals chromatin accessibility changes at Plasmodium falciparum rings are partly associated with artemisinin resistance. MalariaSED illuminates the potential functional roles of noncoding variants in malaria parasites.
