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Overlapping cell population expression profiling and regulatory inference in C. elegans

BACKGROUND: Understanding gene expression across the diverse metazoan cell types during development is critical to understanding their function and regulation. However, most cell types have not been assayed for expression genome-wide. RESULTS: We applied a novel approach we term “Profiling of Overla...

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Autores principales: Burdick, Joshua, Walton, Travis, Preston, Elicia, Zacharias, Amanda, Raj, Arjun, Murray, John Isaac
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4772325/
https://www.ncbi.nlm.nih.gov/pubmed/26926147
http://dx.doi.org/10.1186/s12864-016-2482-z
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author Burdick, Joshua
Walton, Travis
Preston, Elicia
Zacharias, Amanda
Raj, Arjun
Murray, John Isaac
author_facet Burdick, Joshua
Walton, Travis
Preston, Elicia
Zacharias, Amanda
Raj, Arjun
Murray, John Isaac
author_sort Burdick, Joshua
collection PubMed
description BACKGROUND: Understanding gene expression across the diverse metazoan cell types during development is critical to understanding their function and regulation. However, most cell types have not been assayed for expression genome-wide. RESULTS: We applied a novel approach we term “Profiling of Overlapping Populations of cells (POP-Seq)” to assay differential expression across all embryonic cells in the nematode Caenorhabditis elegans. In this approach, we use RNA-seq to define the transcriptome of diverse partially overlapping FACS-sorted cell populations. This identified thousands of transcripts differentially expressed across embryonic cells. Hierarchical clustering analysis identified over 100 sets of coexpressed genes corresponding to distinct patterns of cell type specific expression. We identified thousands of candidate regulators of these clusters based on enrichment of transcription factor motifs and experimentally determined binding sites. CONCLUSIONS: Our analysis provides new insight into embryonic gene regulation, and provides a resource for improving our knowledge of tissue-specific expression and its regulation throughout C. elegans development. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2482-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-47723252016-03-02 Overlapping cell population expression profiling and regulatory inference in C. elegans Burdick, Joshua Walton, Travis Preston, Elicia Zacharias, Amanda Raj, Arjun Murray, John Isaac BMC Genomics Research Article BACKGROUND: Understanding gene expression across the diverse metazoan cell types during development is critical to understanding their function and regulation. However, most cell types have not been assayed for expression genome-wide. RESULTS: We applied a novel approach we term “Profiling of Overlapping Populations of cells (POP-Seq)” to assay differential expression across all embryonic cells in the nematode Caenorhabditis elegans. In this approach, we use RNA-seq to define the transcriptome of diverse partially overlapping FACS-sorted cell populations. This identified thousands of transcripts differentially expressed across embryonic cells. Hierarchical clustering analysis identified over 100 sets of coexpressed genes corresponding to distinct patterns of cell type specific expression. We identified thousands of candidate regulators of these clusters based on enrichment of transcription factor motifs and experimentally determined binding sites. CONCLUSIONS: Our analysis provides new insight into embryonic gene regulation, and provides a resource for improving our knowledge of tissue-specific expression and its regulation throughout C. elegans development. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2482-z) contains supplementary material, which is available to authorized users. BioMed Central 2016-02-29 /pmc/articles/PMC4772325/ /pubmed/26926147 http://dx.doi.org/10.1186/s12864-016-2482-z Text en © Burdick et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Burdick, Joshua
Walton, Travis
Preston, Elicia
Zacharias, Amanda
Raj, Arjun
Murray, John Isaac
Overlapping cell population expression profiling and regulatory inference in C. elegans
title Overlapping cell population expression profiling and regulatory inference in C. elegans
title_full Overlapping cell population expression profiling and regulatory inference in C. elegans
title_fullStr Overlapping cell population expression profiling and regulatory inference in C. elegans
title_full_unstemmed Overlapping cell population expression profiling and regulatory inference in C. elegans
title_short Overlapping cell population expression profiling and regulatory inference in C. elegans
title_sort overlapping cell population expression profiling and regulatory inference in c. elegans
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4772325/
https://www.ncbi.nlm.nih.gov/pubmed/26926147
http://dx.doi.org/10.1186/s12864-016-2482-z
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