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mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis
We introduce mirTarRnaSeq, an R/Bioconductor package for quantitative assessment of miRNA-mRNA relationships within sample cohorts. mirTarRnaSeq is a statistical package to explore predicted or pre-hypothesized miRNA-mRNA relationships following target prediction. We present two use cases applying m...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9191533/ https://www.ncbi.nlm.nih.gov/pubmed/35698050 http://dx.doi.org/10.1186/s12864-022-08558-w |
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author | Movassagh, Mercedeh Morton, Sarah U. Hehnly, Christine Smith, Jasmine Doan, Trang T. Irizarry, Rafael Broach, James R. Schiff, Steven J. Bailey, Jeffrey A. Paulson, Joseph N. |
author_facet | Movassagh, Mercedeh Morton, Sarah U. Hehnly, Christine Smith, Jasmine Doan, Trang T. Irizarry, Rafael Broach, James R. Schiff, Steven J. Bailey, Jeffrey A. Paulson, Joseph N. |
author_sort | Movassagh, Mercedeh |
collection | PubMed |
description | We introduce mirTarRnaSeq, an R/Bioconductor package for quantitative assessment of miRNA-mRNA relationships within sample cohorts. mirTarRnaSeq is a statistical package to explore predicted or pre-hypothesized miRNA-mRNA relationships following target prediction. We present two use cases applying mirTarRnaSeq. First, to identify miRNA targets, we examined EBV miRNAs for interaction with human and virus transcriptomes of stomach adenocarcinoma. This revealed enrichment of mRNA targets highly expressed in CD105+ endothelial cells, monocytes, CD4+ T cells, NK cells, CD19+ B cells, and CD34 cells. Next, to investigate miRNA-mRNA relationships in SARS-CoV-2 (COVID-19) infection across time, we used paired miRNA and RNA sequenced datasets of SARS-CoV-2 infected lung epithelial cells across three time points (4, 12, and 24 hours post-infection). mirTarRnaSeq identified evidence for human miRNAs targeting cytokine signaling and neutrophil regulation immune pathways from 4 to 24 hours after SARS-CoV-2 infection. Confirming the clinical relevance of these predictions, three of the immune specific mRNA-miRNA relationships identified in human lung epithelial cells after SARS-CoV-2 infection were also observed to be differentially expressed in blood from patients with COVID-19. Overall, mirTarRnaSeq is a robust tool that can address a wide-range of biological questions providing improved prediction of miRNA-mRNA interactions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08558-w. |
format | Online Article Text |
id | pubmed-9191533 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-91915332022-06-15 mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis Movassagh, Mercedeh Morton, Sarah U. Hehnly, Christine Smith, Jasmine Doan, Trang T. Irizarry, Rafael Broach, James R. Schiff, Steven J. Bailey, Jeffrey A. Paulson, Joseph N. BMC Genomics Research Article We introduce mirTarRnaSeq, an R/Bioconductor package for quantitative assessment of miRNA-mRNA relationships within sample cohorts. mirTarRnaSeq is a statistical package to explore predicted or pre-hypothesized miRNA-mRNA relationships following target prediction. We present two use cases applying mirTarRnaSeq. First, to identify miRNA targets, we examined EBV miRNAs for interaction with human and virus transcriptomes of stomach adenocarcinoma. This revealed enrichment of mRNA targets highly expressed in CD105+ endothelial cells, monocytes, CD4+ T cells, NK cells, CD19+ B cells, and CD34 cells. Next, to investigate miRNA-mRNA relationships in SARS-CoV-2 (COVID-19) infection across time, we used paired miRNA and RNA sequenced datasets of SARS-CoV-2 infected lung epithelial cells across three time points (4, 12, and 24 hours post-infection). mirTarRnaSeq identified evidence for human miRNAs targeting cytokine signaling and neutrophil regulation immune pathways from 4 to 24 hours after SARS-CoV-2 infection. Confirming the clinical relevance of these predictions, three of the immune specific mRNA-miRNA relationships identified in human lung epithelial cells after SARS-CoV-2 infection were also observed to be differentially expressed in blood from patients with COVID-19. Overall, mirTarRnaSeq is a robust tool that can address a wide-range of biological questions providing improved prediction of miRNA-mRNA interactions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08558-w. BioMed Central 2022-06-13 /pmc/articles/PMC9191533/ /pubmed/35698050 http://dx.doi.org/10.1186/s12864-022-08558-w Text en © The Author(s) 2022 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 Article Movassagh, Mercedeh Morton, Sarah U. Hehnly, Christine Smith, Jasmine Doan, Trang T. Irizarry, Rafael Broach, James R. Schiff, Steven J. Bailey, Jeffrey A. Paulson, Joseph N. mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis |
title | mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis |
title_full | mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis |
title_fullStr | mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis |
title_full_unstemmed | mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis |
title_short | mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis |
title_sort | mirtarrnaseq: an r/bioconductor statistical package for mirna-mrna target identification and interaction analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9191533/ https://www.ncbi.nlm.nih.gov/pubmed/35698050 http://dx.doi.org/10.1186/s12864-022-08558-w |
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