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Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data
BACKGROUND: Existing computational methods for studying miRNA regulation are mostly based on bulk miRNA and mRNA expression data. However, bulk data only allows the analysis of miRNA regulation regarding a group of cells, rather than the miRNA regulation unique to individual cells. Recent advance in...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8641245/ https://www.ncbi.nlm.nih.gov/pubmed/34856921 http://dx.doi.org/10.1186/s12859-021-04498-6 |
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author | Zhang, Junpeng Liu, Lin Xu, Taosheng Zhang, Wu Zhao, Chunwen Li, Sijing Li, Jiuyong Rao, Nini Le, Thuc Duy |
author_facet | Zhang, Junpeng Liu, Lin Xu, Taosheng Zhang, Wu Zhao, Chunwen Li, Sijing Li, Jiuyong Rao, Nini Le, Thuc Duy |
author_sort | Zhang, Junpeng |
collection | PubMed |
description | BACKGROUND: Existing computational methods for studying miRNA regulation are mostly based on bulk miRNA and mRNA expression data. However, bulk data only allows the analysis of miRNA regulation regarding a group of cells, rather than the miRNA regulation unique to individual cells. Recent advance in single-cell miRNA-mRNA co-sequencing technology has opened a way for investigating miRNA regulation at single-cell level. However, as currently single-cell miRNA-mRNA co-sequencing data is just emerging and only available at small-scale, there is a strong need of novel methods to exploit existing single-cell data for the study of cell-specific miRNA regulation. RESULTS: In this work, we propose a new method, CSmiR (Cell-Specific miRNA regulation) to combine single-cell miRNA-mRNA co-sequencing data and putative miRNA-mRNA binding information to identify miRNA regulatory networks at the resolution of individual cells. We apply CSmiR to the miRNA-mRNA co-sequencing data in 19 K562 single-cells to identify cell-specific miRNA-mRNA regulatory networks for understanding miRNA regulation in each K562 single-cell. By analyzing the obtained cell-specific miRNA-mRNA regulatory networks, we observe that the miRNA regulation in each K562 single-cell is unique. Moreover, we conduct detailed analysis on the cell-specific miRNA regulation associated with the miR-17/92 family as a case study. The comparison results indicate that CSmiR is effective in predicting cell-specific miRNA targets. Finally, through exploring cell–cell similarity matrix characterized by cell-specific miRNA regulation, CSmiR provides a novel strategy for clustering single-cells and helps to understand cell–cell crosstalk. CONCLUSIONS: To the best of our knowledge, CSmiR is the first method to explore miRNA regulation at a single-cell resolution level, and we believe that it can be a useful method to enhance the understanding of cell-specific miRNA regulation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04498-6. |
format | Online Article Text |
id | pubmed-8641245 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-86412452021-12-06 Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data Zhang, Junpeng Liu, Lin Xu, Taosheng Zhang, Wu Zhao, Chunwen Li, Sijing Li, Jiuyong Rao, Nini Le, Thuc Duy BMC Bioinformatics Research BACKGROUND: Existing computational methods for studying miRNA regulation are mostly based on bulk miRNA and mRNA expression data. However, bulk data only allows the analysis of miRNA regulation regarding a group of cells, rather than the miRNA regulation unique to individual cells. Recent advance in single-cell miRNA-mRNA co-sequencing technology has opened a way for investigating miRNA regulation at single-cell level. However, as currently single-cell miRNA-mRNA co-sequencing data is just emerging and only available at small-scale, there is a strong need of novel methods to exploit existing single-cell data for the study of cell-specific miRNA regulation. RESULTS: In this work, we propose a new method, CSmiR (Cell-Specific miRNA regulation) to combine single-cell miRNA-mRNA co-sequencing data and putative miRNA-mRNA binding information to identify miRNA regulatory networks at the resolution of individual cells. We apply CSmiR to the miRNA-mRNA co-sequencing data in 19 K562 single-cells to identify cell-specific miRNA-mRNA regulatory networks for understanding miRNA regulation in each K562 single-cell. By analyzing the obtained cell-specific miRNA-mRNA regulatory networks, we observe that the miRNA regulation in each K562 single-cell is unique. Moreover, we conduct detailed analysis on the cell-specific miRNA regulation associated with the miR-17/92 family as a case study. The comparison results indicate that CSmiR is effective in predicting cell-specific miRNA targets. Finally, through exploring cell–cell similarity matrix characterized by cell-specific miRNA regulation, CSmiR provides a novel strategy for clustering single-cells and helps to understand cell–cell crosstalk. CONCLUSIONS: To the best of our knowledge, CSmiR is the first method to explore miRNA regulation at a single-cell resolution level, and we believe that it can be a useful method to enhance the understanding of cell-specific miRNA regulation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04498-6. BioMed Central 2021-12-02 /pmc/articles/PMC8641245/ /pubmed/34856921 http://dx.doi.org/10.1186/s12859-021-04498-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Zhang, Junpeng Liu, Lin Xu, Taosheng Zhang, Wu Zhao, Chunwen Li, Sijing Li, Jiuyong Rao, Nini Le, Thuc Duy Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data |
title | Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data |
title_full | Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data |
title_fullStr | Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data |
title_full_unstemmed | Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data |
title_short | Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data |
title_sort | exploring cell-specific mirna regulation with single-cell mirna-mrna co-sequencing data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8641245/ https://www.ncbi.nlm.nih.gov/pubmed/34856921 http://dx.doi.org/10.1186/s12859-021-04498-6 |
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