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Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics
Methods for single-cell genome and transcriptome sequencing have contributed to our understanding of cellular heterogeneity, whereas methods for single-cell epigenomics are much less established. Here, we describe a whole-genome bisulfite sequencing (WGBS) assay that enables DNA methylation mapping...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cell Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4542311/ https://www.ncbi.nlm.nih.gov/pubmed/25732828 http://dx.doi.org/10.1016/j.celrep.2015.02.001 |
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author | Farlik, Matthias Sheffield, Nathan C. Nuzzo, Angelo Datlinger, Paul Schönegger, Andreas Klughammer, Johanna Bock, Christoph |
author_facet | Farlik, Matthias Sheffield, Nathan C. Nuzzo, Angelo Datlinger, Paul Schönegger, Andreas Klughammer, Johanna Bock, Christoph |
author_sort | Farlik, Matthias |
collection | PubMed |
description | Methods for single-cell genome and transcriptome sequencing have contributed to our understanding of cellular heterogeneity, whereas methods for single-cell epigenomics are much less established. Here, we describe a whole-genome bisulfite sequencing (WGBS) assay that enables DNA methylation mapping in very small cell populations (μWGBS) and single cells (scWGBS). Our assay is optimized for profiling many samples at low coverage, and we describe a bioinformatic method that analyzes collections of single-cell methylomes to infer cell-state dynamics. Using these technological advances, we studied epigenomic cell-state dynamics in three in vitro models of cellular differentiation and pluripotency, where we observed characteristic patterns of epigenome remodeling and cell-to-cell heterogeneity. The described method enables single-cell analysis of DNA methylation in a broad range of biological systems, including embryonic development, stem cell differentiation, and cancer. It can also be used to establish composite methylomes that account for cell-to-cell heterogeneity in complex tissue samples. |
format | Online Article Text |
id | pubmed-4542311 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Cell Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-45423112015-09-22 Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics Farlik, Matthias Sheffield, Nathan C. Nuzzo, Angelo Datlinger, Paul Schönegger, Andreas Klughammer, Johanna Bock, Christoph Cell Rep Resource Methods for single-cell genome and transcriptome sequencing have contributed to our understanding of cellular heterogeneity, whereas methods for single-cell epigenomics are much less established. Here, we describe a whole-genome bisulfite sequencing (WGBS) assay that enables DNA methylation mapping in very small cell populations (μWGBS) and single cells (scWGBS). Our assay is optimized for profiling many samples at low coverage, and we describe a bioinformatic method that analyzes collections of single-cell methylomes to infer cell-state dynamics. Using these technological advances, we studied epigenomic cell-state dynamics in three in vitro models of cellular differentiation and pluripotency, where we observed characteristic patterns of epigenome remodeling and cell-to-cell heterogeneity. The described method enables single-cell analysis of DNA methylation in a broad range of biological systems, including embryonic development, stem cell differentiation, and cancer. It can also be used to establish composite methylomes that account for cell-to-cell heterogeneity in complex tissue samples. Cell Press 2015-02-26 /pmc/articles/PMC4542311/ /pubmed/25732828 http://dx.doi.org/10.1016/j.celrep.2015.02.001 Text en © 2015 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Resource Farlik, Matthias Sheffield, Nathan C. Nuzzo, Angelo Datlinger, Paul Schönegger, Andreas Klughammer, Johanna Bock, Christoph Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics |
title | Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics |
title_full | Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics |
title_fullStr | Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics |
title_full_unstemmed | Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics |
title_short | Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics |
title_sort | single-cell dna methylome sequencing and bioinformatic inference of epigenomic cell-state dynamics |
topic | Resource |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4542311/ https://www.ncbi.nlm.nih.gov/pubmed/25732828 http://dx.doi.org/10.1016/j.celrep.2015.02.001 |
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