Leveraging the cell lineage to predict cell-type specificity of regulatory variation from bulk genomics

Gal Yankovitz, Ofir Cohn, Eran Bacharach, Naama Peshes-Yaloz, Yael Steuerman, Fuad A. Iraqi, Irit Gat-Viks

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Recent computational methods have enabled the inference of the cell-type-specificity of eQTLs based on bulk transcriptomes from highly heterogeneous tissues. However, these methods are limited in their scalability to highly heterogeneous tissues and limited in their broad applicability to any cell-type specificity of eQTLs. Here we present and demonstrate Cell Lineage Genetics (CeL-Gen), a novel computational approach that allows inference of eQTLs together with the subsets of cell types in which they have an effect, from bulk transcriptome data. To obtain improved scalability and broader applicability, CeL-Gen takes as input the known cell lineage tree and relies on the observation that dynamic changes in genetic effects occur relatively infrequently during cell differentiation. CeL-Gen can therefore be used not only to tease apart genetic effects derived from different cell types but also to infer the particular differentiation steps in which genetic effects are altered.

Original languageEnglish
Article numberiyab016
JournalGenetics
Volume217
Issue number4
DOIs
StatePublished - 1 Apr 2021
Externally publishedYes

Keywords

  • cell lineage
  • cell type
  • eQTL

ASJC Scopus subject areas

  • General Medicine

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