Cellular Heterogeneity–Adjusted cLonal Methylation (CHALM) improves prediction of gene expression

Jianfeng Xu, Jiejun Shi, Xiaodong Cui, Ya Cui, Jingyi Jessica Li, Ajay Goel, Xi Chen, Jean-Pierre Issa (), Jianzhong Su () and Wei Li ()
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Jianfeng Xu: University of California
Jiejun Shi: University of California
Xiaodong Cui: Baylor College of Medicine
Ya Cui: University of California
Jingyi Jessica Li: University of California
Ajay Goel: Beckman Research Institute of City of Hope
Xi Chen: Baylor College of Medicine
Jean-Pierre Issa: The Coriell Institute for Medical Research
Jianzhong Su: Baylor College of Medicine
Wei Li: University of California

Nature Communications, 2021, vol. 12, issue 1, 1-9

Abstract: Abstract Promoter DNA methylation is a well-established mechanism of transcription repression, though its global correlation with gene expression is weak. This weak correlation can be attributed to the failure of current methylation quantification methods to consider the heterogeneity among sequenced bulk cells. Here, we introduce Cell Heterogeneity–Adjusted cLonal Methylation (CHALM) as a methylation quantification method. CHALM improves understanding of the functional consequences of DNA methylation, including its correlations with gene expression and H3K4me3. When applied to different methylation datasets, the CHALM method enables detection of differentially methylated genes that exhibit distinct biological functions supporting underlying mechanisms.

Date: 2021
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DOI: 10.1038/s41467-020-20492-7

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