Systematic Analysis of Actively Transcribed Core Matrisome Genes Across Tissues and Cell Phenotypes.
cap analysis gene expression
clustermaps
matrisome
promoter-level expression
tissue level analysis
Journal
Matrix biology : journal of the International Society for Matrix Biology
ISSN: 1569-1802
Titre abrégé: Matrix Biol
Pays: Netherlands
ID NLM: 9432592
Informations de publication
Date de publication:
08 2022
08 2022
Historique:
received:
31
01
2022
revised:
20
05
2022
accepted:
13
06
2022
pubmed:
18
6
2022
medline:
9
9
2022
entrez:
17
6
2022
Statut:
ppublish
Résumé
The extracellular matrix (ECM) is a highly dynamic, well-organized acellular network of tissue-specific biomolecules, that can be divided into structural or core ECM proteins and ECM-associated proteins. The ECM serves as a blueprint for organ development and function and, when structurally altered through mutation, altered expression, or degradation, can lead to debilitating syndromes that often affect one tissue more than another. Cross-referencing the FANTOM5 SSTAR (Semantic catalog of Samples, Transcription initiation And Regulators) and the defined catalog of core matrisome ECM (glyco)proteins, we conducted a comprehensive analysis of 511 different human samples to annotate the context-specific transcription of the individual components of the defined matrisome. Relative log expression normalized SSTAR cap analysis gene expression peak data files were downloaded from the FANTOM5 online database and filtered to exclude all cell lines and diseased tissues. Promoter-level expression values were categorized further into eight core tissue systems and three major ECM categories: proteoglycans, glycoproteins, and collagens. Hierarchical clustering and correlation analyses were conducted to identify complex relationships in promoter-driven gene expression activity. Integration of the core matrisome and curated FANTOM5 SSTAR data creates a unique tool that provides insight into the promoter-level expression of ECM-encoding genes in a tissue- and cell-specific manner. Unbiased clustering of cap analysis gene expression peak data reveals unique ECM signatures within defined tissue systems. Correlation analysis among tissue systems exposes both positive and negative correlation of ECM promoters with varying levels of significance. This tool can be used to provide new insight into the relationships between ECM components and tissues and can inform future research on the ECM in human disease and development. We invite the matrix biology community to continue to explore and discuss this dataset as part of a larger and continuing conversation about the human ECM. An interactive web tool can be found at matrixpromoterome.github.io along with additional resources that can be found at dx.doi.org/10.6084/m9.figshare.19794481 (figures) and https://figshare.com/s/e18ecbc3ae5aaf919b78 (python notebook).
Identifiants
pubmed: 35714875
pii: S0945-053X(22)00083-X
doi: 10.1016/j.matbio.2022.06.003
pii:
doi:
Substances chimiques
Extracellular Matrix Proteins
0
Proteoglycans
0
Collagen
9007-34-5
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
95-107Subventions
Organisme : NIDCR NIH HHS
ID : R01 DE022969
Pays : United States
Organisme : NIDCR NIH HHS
ID : R56 DE026530
Pays : United States
Informations de copyright
Copyright © 2022 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Conflict of Interest The authors, T.V.T., M.D., V.A.A., D.S., A.N. and M.C.F-C., declare no conflicts of interest.