Inferring single-cell and spatial microRNA activity from transcriptomics data
Abstract The activity of miRNA varies across different cell populations and systems, as part of the mechanisms that distinguish cell types and roles in living organisms and in human health and disease. Typically, miRNA regulation drives changes in the composition and levels of protein-coding RNA and...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Communications Biology |
| Online Access: | https://doi.org/10.1038/s42003-025-07454-9 |
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| author | Efrat Herbst Yael Mandel-Gutfreund Zohar Yakhini Hadas Biran |
| author_facet | Efrat Herbst Yael Mandel-Gutfreund Zohar Yakhini Hadas Biran |
| author_sort | Efrat Herbst |
| collection | DOAJ |
| description | Abstract The activity of miRNA varies across different cell populations and systems, as part of the mechanisms that distinguish cell types and roles in living organisms and in human health and disease. Typically, miRNA regulation drives changes in the composition and levels of protein-coding RNA and of lncRNA, with targets being down-regulated when miRNAs are active. The term “miRNA activity" is used to refer to this transcriptional effect of miRNAs. This study introduces miTEA-HiRes, a method designed to facilitate the evaluation of miRNA activity at high resolution. The method applies to single-cell transcriptomics, type-specific single-cell populations, and spatial transcriptomics data. By comparing different conditions, differential miRNA activity is inferred. For instance, miTEA-HiRes analysis of peripheral blood mononuclear cells comparing Multiple Sclerosis patients to control groups revealed differential activity of miR-20a-5p and others, consistent with the literature on miRNA underexpression in Multiple Sclerosis. We also show miR-519a-3p differential activity in specific cell populations. |
| format | Article |
| id | doaj-art-f57d9df8690645c4a6fee23c18bb97e6 |
| institution | Kabale University |
| issn | 2399-3642 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Biology |
| spelling | doaj-art-f57d9df8690645c4a6fee23c18bb97e62025-01-19T12:35:42ZengNature PortfolioCommunications Biology2399-36422025-01-018111810.1038/s42003-025-07454-9Inferring single-cell and spatial microRNA activity from transcriptomics dataEfrat Herbst0Yael Mandel-Gutfreund1Zohar Yakhini2Hadas Biran3Arazi School of Computer Science, Reichman UniversityComputer Science Department, Technion - Israel Institute of TechnologyArazi School of Computer Science, Reichman UniversityComputer Science Department, Technion - Israel Institute of TechnologyAbstract The activity of miRNA varies across different cell populations and systems, as part of the mechanisms that distinguish cell types and roles in living organisms and in human health and disease. Typically, miRNA regulation drives changes in the composition and levels of protein-coding RNA and of lncRNA, with targets being down-regulated when miRNAs are active. The term “miRNA activity" is used to refer to this transcriptional effect of miRNAs. This study introduces miTEA-HiRes, a method designed to facilitate the evaluation of miRNA activity at high resolution. The method applies to single-cell transcriptomics, type-specific single-cell populations, and spatial transcriptomics data. By comparing different conditions, differential miRNA activity is inferred. For instance, miTEA-HiRes analysis of peripheral blood mononuclear cells comparing Multiple Sclerosis patients to control groups revealed differential activity of miR-20a-5p and others, consistent with the literature on miRNA underexpression in Multiple Sclerosis. We also show miR-519a-3p differential activity in specific cell populations.https://doi.org/10.1038/s42003-025-07454-9 |
| spellingShingle | Efrat Herbst Yael Mandel-Gutfreund Zohar Yakhini Hadas Biran Inferring single-cell and spatial microRNA activity from transcriptomics data Communications Biology |
| title | Inferring single-cell and spatial microRNA activity from transcriptomics data |
| title_full | Inferring single-cell and spatial microRNA activity from transcriptomics data |
| title_fullStr | Inferring single-cell and spatial microRNA activity from transcriptomics data |
| title_full_unstemmed | Inferring single-cell and spatial microRNA activity from transcriptomics data |
| title_short | Inferring single-cell and spatial microRNA activity from transcriptomics data |
| title_sort | inferring single cell and spatial microrna activity from transcriptomics data |
| url | https://doi.org/10.1038/s42003-025-07454-9 |
| work_keys_str_mv | AT efratherbst inferringsinglecellandspatialmicrornaactivityfromtranscriptomicsdata AT yaelmandelgutfreund inferringsinglecellandspatialmicrornaactivityfromtranscriptomicsdata AT zoharyakhini inferringsinglecellandspatialmicrornaactivityfromtranscriptomicsdata AT hadasbiran inferringsinglecellandspatialmicrornaactivityfromtranscriptomicsdata |