MalariaSED: a deep learning framework to decipher the regulatory contributions of noncoding variants in malaria parasites

Chengqi Wang; Yibo Dong; Chang Li; Jenna Oberstaller; Min Zhang; Justin Gibbons; Camilla Valente Pires; Mianli Xiao; Lei Zhu; Rays H. Y. Jiang; Kami Kim; Jun Miao; Thomas D. Otto; Liwang Cui; John H. Adams; Xiaoming Liu

doi:10.1186/s13059-023-03063-z

Genome Biology (Oct 2023)

MalariaSED: a deep learning framework to decipher the regulatory contributions of noncoding variants in malaria parasites

Chengqi Wang,
Yibo Dong,
Chang Li,
Jenna Oberstaller,
Min Zhang,
Justin Gibbons,
Camilla Valente Pires,
Mianli Xiao,
Lei Zhu,
Rays H. Y. Jiang,
Kami Kim,
Jun Miao,
Thomas D. Otto,
Liwang Cui,
John H. Adams,
Xiaoming Liu

Affiliations

Chengqi Wang: Center for Global Health and Infectious Diseases Research and USF Genomics Program, College of Public Health, University of South Florida
Yibo Dong: Center for Global Health and Infectious Diseases Research and USF Genomics Program, College of Public Health, University of South Florida
Chang Li: Center for Global Health and Infectious Diseases Research and USF Genomics Program, College of Public Health, University of South Florida
Jenna Oberstaller: Center for Global Health and Infectious Diseases Research and USF Genomics Program, College of Public Health, University of South Florida
Min Zhang: Center for Global Health and Infectious Diseases Research and USF Genomics Program, College of Public Health, University of South Florida
Justin Gibbons: Center for Global Health and Infectious Diseases Research and USF Genomics Program, College of Public Health, University of South Florida
Camilla Valente Pires: Center for Global Health and Infectious Diseases Research and USF Genomics Program, College of Public Health, University of South Florida
Mianli Xiao: Center for Global Health and Infectious Diseases Research and USF Genomics Program, College of Public Health, University of South Florida
Lei Zhu: School of Biological Sciences, Nanyang Technological University
Rays H. Y. Jiang: Center for Global Health and Infectious Diseases Research and USF Genomics Program, College of Public Health, University of South Florida
Kami Kim: Department of Internal Medicine, Morsani College of Medicine
Jun Miao: Department of Internal Medicine, Morsani College of Medicine
Thomas D. Otto: School of Infection & Immunity, MVLS, University of Glasgow
Liwang Cui: Department of Internal Medicine, Morsani College of Medicine
John H. Adams: Center for Global Health and Infectious Diseases Research and USF Genomics Program, College of Public Health, University of South Florida
Xiaoming Liu: Center for Global Health and Infectious Diseases Research and USF Genomics Program, College of Public Health, University of South Florida

DOI: https://doi.org/10.1186/s13059-023-03063-z
Journal volume & issue: Vol. 24, no. 1
pp. 1 – 20

Abstract

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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.

Published in Genome Biology

ISSN: 1474-760X (Online)
Publisher: BMC
Country of publisher: United Kingdom
LCC subjects: Science: Biology (General): Genetics
Website: https://genomebiology.biomedcentral.com/

About the journal