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Iterative epigenomic analyses in the same single cell

Gene expression in individual cells is epigenetically regulated by DNA modifications, histone modifications, transcription factors, and other DNA-binding proteins. It has been shown that multiple histone modifications can predict gene expression and reflect future responses of bulk cells to extracel...

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Autores principales: Ohnuki, Hidetaka, Venzon, David J., Lobanov, Alexei, Tosato, Giovanna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494233/
https://www.ncbi.nlm.nih.gov/pubmed/33627472
http://dx.doi.org/10.1101/gr.269068.120
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author Ohnuki, Hidetaka
Venzon, David J.
Lobanov, Alexei
Tosato, Giovanna
author_facet Ohnuki, Hidetaka
Venzon, David J.
Lobanov, Alexei
Tosato, Giovanna
author_sort Ohnuki, Hidetaka
collection PubMed
description Gene expression in individual cells is epigenetically regulated by DNA modifications, histone modifications, transcription factors, and other DNA-binding proteins. It has been shown that multiple histone modifications can predict gene expression and reflect future responses of bulk cells to extracellular cues. However, the predictive ability of epigenomic analysis is still limited for mechanistic research at a single cell level. To overcome this limitation, it would be useful to acquire reliable signals from multiple epigenetic marks in the same single cell. Here, we propose a new approach and a new method for analysis of several components of the epigenome in the same single cell. The new method allows reanalysis of the same single cell. We found that reanalysis of the same single cell is feasible, provides confirmation of the epigenetic signals, and allows application of statistical analysis to identify reproduced reads using data sets generated only from the single cell. Reanalysis of the same single cell is also useful to acquire multiple epigenetic marks from the same single cells. The method can acquire at least five epigenetic marks: H3K27ac, H3K27me3, mediator complex subunit 1, a DNA modification, and a DNA-interacting protein. We can predict active signaling pathways in K562 single cells using the epigenetic data and confirm that the predicted results strongly correlate with actual active signaling pathways identified by RNA-seq results. These results suggest that the new method provides mechanistic insights for cellular phenotypes through multilayered epigenome analysis in the same single cells.
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spelling pubmed-84942332022-04-01 Iterative epigenomic analyses in the same single cell Ohnuki, Hidetaka Venzon, David J. Lobanov, Alexei Tosato, Giovanna Genome Res Method Gene expression in individual cells is epigenetically regulated by DNA modifications, histone modifications, transcription factors, and other DNA-binding proteins. It has been shown that multiple histone modifications can predict gene expression and reflect future responses of bulk cells to extracellular cues. However, the predictive ability of epigenomic analysis is still limited for mechanistic research at a single cell level. To overcome this limitation, it would be useful to acquire reliable signals from multiple epigenetic marks in the same single cell. Here, we propose a new approach and a new method for analysis of several components of the epigenome in the same single cell. The new method allows reanalysis of the same single cell. We found that reanalysis of the same single cell is feasible, provides confirmation of the epigenetic signals, and allows application of statistical analysis to identify reproduced reads using data sets generated only from the single cell. Reanalysis of the same single cell is also useful to acquire multiple epigenetic marks from the same single cells. The method can acquire at least five epigenetic marks: H3K27ac, H3K27me3, mediator complex subunit 1, a DNA modification, and a DNA-interacting protein. We can predict active signaling pathways in K562 single cells using the epigenetic data and confirm that the predicted results strongly correlate with actual active signaling pathways identified by RNA-seq results. These results suggest that the new method provides mechanistic insights for cellular phenotypes through multilayered epigenome analysis in the same single cells. Cold Spring Harbor Laboratory Press 2021-10 /pmc/articles/PMC8494233/ /pubmed/33627472 http://dx.doi.org/10.1101/gr.269068.120 Text en Published by Cold Spring Harbor Laboratory Press https://creativecommons.org/licenses/by-nc/4.0/This is a work of the US Government.
spellingShingle Method
Ohnuki, Hidetaka
Venzon, David J.
Lobanov, Alexei
Tosato, Giovanna
Iterative epigenomic analyses in the same single cell
title Iterative epigenomic analyses in the same single cell
title_full Iterative epigenomic analyses in the same single cell
title_fullStr Iterative epigenomic analyses in the same single cell
title_full_unstemmed Iterative epigenomic analyses in the same single cell
title_short Iterative epigenomic analyses in the same single cell
title_sort iterative epigenomic analyses in the same single cell
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494233/
https://www.ncbi.nlm.nih.gov/pubmed/33627472
http://dx.doi.org/10.1101/gr.269068.120
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