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Multi omics analysis of fibrotic kidneys in two mouse models
Kidney fibrosis represents an urgent unmet clinical need due to the lack of effective therapies and an inadequate understanding of the molecular pathogenesis. We have generated a comprehensive and combined multi-omics dataset (proteomics, mRNA and small RNA transcriptomics) of fibrotic kidneys that...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6570759/ https://www.ncbi.nlm.nih.gov/pubmed/31201317 http://dx.doi.org/10.1038/s41597-019-0095-5 |
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author | Pavkovic, Mira Pantano, Lorena Gerlach, Cory V. Brutus, Sergine Boswell, Sarah A. Everley, Robert A. Shah, Jagesh V. Sui, Shannan H. Vaidya, Vishal S. |
author_facet | Pavkovic, Mira Pantano, Lorena Gerlach, Cory V. Brutus, Sergine Boswell, Sarah A. Everley, Robert A. Shah, Jagesh V. Sui, Shannan H. Vaidya, Vishal S. |
author_sort | Pavkovic, Mira |
collection | PubMed |
description | Kidney fibrosis represents an urgent unmet clinical need due to the lack of effective therapies and an inadequate understanding of the molecular pathogenesis. We have generated a comprehensive and combined multi-omics dataset (proteomics, mRNA and small RNA transcriptomics) of fibrotic kidneys that is searchable through a user-friendly web application: http://hbcreports.med.harvard.edu/fmm/. Two commonly used mouse models were utilized: a reversible chemical-induced injury model (folic acid (FA) induced nephropathy) and an irreversible surgically-induced fibrosis model (unilateral ureteral obstruction (UUO)). mRNA and small RNA sequencing, as well as 10-plex tandem mass tag (TMT) proteomics were performed with kidney samples from different time points over the course of fibrosis development. The bioinformatics workflow used to process, technically validate, and combine the single omics data will be described. In summary, we present temporal multi-omics data from fibrotic mouse kidneys that are accessible through an interrogation tool (Mouse Kidney Fibromics browser) to provide a searchable transcriptome and proteome for kidney fibrosis researchers. |
format | Online Article Text |
id | pubmed-6570759 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65707592019-06-21 Multi omics analysis of fibrotic kidneys in two mouse models Pavkovic, Mira Pantano, Lorena Gerlach, Cory V. Brutus, Sergine Boswell, Sarah A. Everley, Robert A. Shah, Jagesh V. Sui, Shannan H. Vaidya, Vishal S. Sci Data Data Descriptor Kidney fibrosis represents an urgent unmet clinical need due to the lack of effective therapies and an inadequate understanding of the molecular pathogenesis. We have generated a comprehensive and combined multi-omics dataset (proteomics, mRNA and small RNA transcriptomics) of fibrotic kidneys that is searchable through a user-friendly web application: http://hbcreports.med.harvard.edu/fmm/. Two commonly used mouse models were utilized: a reversible chemical-induced injury model (folic acid (FA) induced nephropathy) and an irreversible surgically-induced fibrosis model (unilateral ureteral obstruction (UUO)). mRNA and small RNA sequencing, as well as 10-plex tandem mass tag (TMT) proteomics were performed with kidney samples from different time points over the course of fibrosis development. The bioinformatics workflow used to process, technically validate, and combine the single omics data will be described. In summary, we present temporal multi-omics data from fibrotic mouse kidneys that are accessible through an interrogation tool (Mouse Kidney Fibromics browser) to provide a searchable transcriptome and proteome for kidney fibrosis researchers. Nature Publishing Group UK 2019-06-14 /pmc/articles/PMC6570759/ /pubmed/31201317 http://dx.doi.org/10.1038/s41597-019-0095-5 Text en © The Author(s) 2019 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Pavkovic, Mira Pantano, Lorena Gerlach, Cory V. Brutus, Sergine Boswell, Sarah A. Everley, Robert A. Shah, Jagesh V. Sui, Shannan H. Vaidya, Vishal S. Multi omics analysis of fibrotic kidneys in two mouse models |
title | Multi omics analysis of fibrotic kidneys in two mouse models |
title_full | Multi omics analysis of fibrotic kidneys in two mouse models |
title_fullStr | Multi omics analysis of fibrotic kidneys in two mouse models |
title_full_unstemmed | Multi omics analysis of fibrotic kidneys in two mouse models |
title_short | Multi omics analysis of fibrotic kidneys in two mouse models |
title_sort | multi omics analysis of fibrotic kidneys in two mouse models |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6570759/ https://www.ncbi.nlm.nih.gov/pubmed/31201317 http://dx.doi.org/10.1038/s41597-019-0095-5 |
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