Cell-type-specific resolution epigenetics without the need for cell sorting or single-cell biology

Elior Rahmani*, Regev Schweiger, Brooke Rhead, Lindsey A. Criswell, Lisa F. Barcellos, Eleazar Eskin, Saharon Rosset, Sriram Sankararaman, Eran Halperin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

75 Scopus citations


High costs and technical limitations of cell sorting and single-cell techniques currently restrict the collection of large-scale, cell-type-specific DNA methylation data. This, in turn, impedes our ability to tackle key biological questions that pertain to variation within a population, such as identification of disease-associated genes at a cell-type-specific resolution. Here, we show mathematically and empirically that cell-type-specific methylation levels of an individual can be learned from its tissue-level bulk data, conceptually emulating the case where the individual has been profiled with a single-cell resolution and then signals were aggregated in each cell population separately. Provided with this unprecedented way to perform powerful large-scale epigenetic studies with cell-type-specific resolution, we revisit previous studies with tissue-level bulk methylation and reveal novel associations with leukocyte composition in blood and with rheumatoid arthritis. For the latter, we further show consistency with validation data collected from sorted leukocyte sub-types.

Original languageEnglish
Article number3417
JournalNature Communications
Issue number1
StatePublished - 1 Dec 2019


FundersFunder number
University of California–Stanford Arthritis Center of Excellence
National Science Foundation1705197
National Institutes of Health1R01MH115979
National Institute of General Medical SciencesR35GM125055
Alfred P. Sloan Foundation
Arthritis Foundation
Edmond J. Safra Center for Ethics, Harvard UniversityIII-1705121, R00GM111744
Rheumatology Research Foundation
Israel Science Foundation1425/13
Okawa Foundation for Information and Telecommunications


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