4.7 Article Data Paper

Multi omics analysis of fibrotic kidneys in two mouse models

Journal

SCIENTIFIC DATA
Volume 6, Issue -, Pages -

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/s41597-019-0095-5

Keywords

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Funding

  1. Deutsche Forschungsgemeinschaft
  2. NIH [P50-GM107618, U54-HL127365]
  3. Outstanding New Environmental Sciences award from NIH/NIEHS [ES017543]
  4. Burroughs Wellcome Fund [BWF-1012518]
  5. Biogen [A24378]
  6. Molecular Biology Core Facilities at Dana-Farber Cancer Institute
  7. Thermo Fisher Center for Multiplexed Proteomics at the Harvard Medical School
  8. Harvard Medical School Tools and Technology Committee
  9. Harvard Catalyst\The Harvard Clinical and Translational Science Center (National Center for Advancing Translational Sciences, National Institutes of Health Award) [UL1 TR001102]
  10. Harvard University

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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.

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