Integrative analysis of single-cell expression data reveals distinct regulatory states in bidirectional promoters.

Autor: Behjati Ardakani F; Excellence Cluster for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Campus E1 7, Saarbrücken, 66123, Germany.; Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics, Campus E 4, Saarbrücken, 66123, Germany.; Graduate School of Computer Science, Saarland University, Campus E1 3, Saarbrücken, 66123, Germany., Kattler K; Department of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany., Nordström K; Department of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany., Gasparoni N; Department of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany., Gasparoni G; Department of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany., Fuchs S; Department of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany., Sinha A; Institute of Clinical Molecular Biology, Christian-Albrechts-University, Rosalind-Franklin-Str. 12, Kiel, 24105, Germany., Barann M; Institute of Clinical Molecular Biology, Christian-Albrechts-University, Rosalind-Franklin-Str. 12, Kiel, 24105, Germany., Ebert P; Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics, Campus E 4, Saarbrücken, 66123, Germany.; Graduate School of Computer Science, Saarland University, Campus E1 3, Saarbrücken, 66123, Germany., Fischer J; Excellence Cluster for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Campus E1 7, Saarbrücken, 66123, Germany.; Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics, Campus E 4, Saarbrücken, 66123, Germany.; Graduate School of Computer Science, Saarland University, Campus E1 3, Saarbrücken, 66123, Germany., Hutter B; Applied Bioinformatics, Deutsches Krebsforschungszentrum, Berliner-Str. 41, Heidelberg, 69120, Germany., Zipprich G; Data Management and Genomics IT, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Heidelberg, 69120, Germany., Imbusch CD; Applied Bioinformatics, Deutsches Krebsforschungszentrum, Berliner-Str. 41, Heidelberg, 69120, Germany., Felder B; Data Management and Genomics IT, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Heidelberg, 69120, Germany., Eils J; Data Management and Genomics IT, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Heidelberg, 69120, Germany., Brors B; Applied Bioinformatics, Deutsches Krebsforschungszentrum, Berliner-Str. 41, Heidelberg, 69120, Germany., Lengauer T; Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics, Campus E 4, Saarbrücken, 66123, Germany., Manke T; Max Planck Institute of Immunobiology and Epigenetics, Stübeweg 51, Freiburg, 79108, Germany., Rosenstiel P; Institute of Clinical Molecular Biology, Christian-Albrechts-University, Rosalind-Franklin-Str. 12, Kiel, 24105, Germany., Walter J; Department of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany., Schulz MH; Excellence Cluster for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Campus E1 7, Saarbrücken, 66123, Germany. marcel.schulz@em.uni-frankfurt.de.; Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics, Campus E 4, Saarbrücken, 66123, Germany. marcel.schulz@em.uni-frankfurt.de.; Institute for Cardiovascular Regeneration, Goethe University, Theodor-Stern-Kai 7, Frankfurt am Main, 60590, Germany. marcel.schulz@em.uni-frankfurt.de.; German Center for Cardiovascular Research, Partner site Rhein-Main, Frankfurt am Main, 60590, Germany. marcel.schulz@em.uni-frankfurt.de.
Jazyk: angličtina
Zdroj: Epigenetics & chromatin [Epigenetics Chromatin] 2018 Nov 10; Vol. 11 (1), pp. 66. Date of Electronic Publication: 2018 Nov 10.
DOI: 10.1186/s13072-018-0236-7
Abstrakt: Background: 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.
Results: 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.
Conclusions: 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.
Databáze: MEDLINE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje