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

Author:

Yankovitz Gal1,Cohn Ofir1,Bacharach Eran1,Peshes-Yaloz Naama1,Steuerman Yael1,Iraqi Fuad A2,Gat-Viks Irit1

Affiliation:

1. The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel

2. Department of Clinical Microbiology and Immunology, Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel

Abstract

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.

Funder

Israel Science Foundation

European Research Council

Edmond J. Safra Center for Bioinformatics

Tel-Aviv University

Publisher

Oxford University Press (OUP)

Subject

Genetics

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Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. eQTL studies: from bulk tissues to single cells;Journal of Genetics and Genomics;2023-12

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