Journal Article

DKFZ-2018-01996

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Integrative analysis of single-cell expression data reveals distinct regulatory states in bidirectional promoters.

Behjati Ardakani, F. ; Kattler, K. ; Nordström, K. ; Gasparoni, N. ; Gasparoni, G. ; Fuchs, S. ; Sinha, A. ; Barann, M. ; Ebert, P. ; Fischer, J. ; Hutter, B.DKFZ* ; Zipprich, G.DKFZ* ; Imbusch, C. D.DKFZ* ; Felder, B.DKFZ* ; Eils, J.DKFZ* ; Brors, B.DKFZ* ; Lengauer, T. ; Manke, T. ; Rosenstiel, P. ; Walter, J. ; Schulz, M. H.

2018
BioMed Central London

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Please use a persistent id in citations: doi:10.1186/s13072-018-0236-7

Abstract: Bidirectional promoters (BPs) are prevalent in eukaryotic genomes. However, it is poorly understood how the cell integrates different epigenomic information, such as transcription factor (TF) binding and chromatin marks, to drive gene expression at BPs. Single-cell sequencing technologies are revolutionizing the field of genome biology. Therefore, this study focuses on the integration of single-cell RNA-seq data with bulk ChIP-seq and other epigenetics data, for which single-cell technologies are not yet established, in the context of BPs.We performed integrative analyses of novel human single-cell RNA-seq (scRNA-seq) data with bulk ChIP-seq and other epigenetics data. scRNA-seq data revealed distinct transcription states of BPs that were previously not recognized. We find associations between these transcription states to distinct patterns in structural gene features, DNA accessibility, histone modification, DNA methylation and TF binding profiles.Our results suggest that a complex interplay of all of these elements is required to achieve BP-specific transcriptional output in this specialized promoter configuration. Further, our study implies that novel statistical methods can be developed to deconvolute masked subpopulations of cells measured with different bulk epigenomic assays using scRNA-seq data.

Note: Applied Bioinformatics, Deutsches Krebsforschungszentrum, Berliner-Str. 41,Heidelberg 69120, Germany. Data Management and Genomics IT, DeutschesKrebsforschungszentrum,

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Contributing Institute(s):

1. Angewandte Bioinformatik (G200)
2. Theoretische Bioinformatik (B080)

Research Program(s):

1. 317 - Translational cancer research (POF3-317) (POF3-317)

Appears in the scientific report 2018

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Database coverage:
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