Tissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data

Abstract The extracellular matrix (ECM) has historically been explored through proteomic methods. Whether or not global transcriptomics can yield meaningful information on the human matrisome is unknown. Gene expression data from 17,382 samples across 52 tissues, were obtained from the Genotype-Tiss...

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Autores principales:	Tim O. Nieuwenhuis, Avi Z. Rosenberg, Matthew N. McCall, Marc K. Halushka
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/9d288ca36166428b8cedf93868f543b4
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spelling	oai:doaj.org-article:9d288ca36166428b8cedf93868f543b42021-11-08T10:52:41ZTissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data10.1038/s41598-021-00943-x2045-2322https://doaj.org/article/9d288ca36166428b8cedf93868f543b42021-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-00943-xhttps://doaj.org/toc/2045-2322Abstract The extracellular matrix (ECM) has historically been explored through proteomic methods. Whether or not global transcriptomics can yield meaningful information on the human matrisome is unknown. Gene expression data from 17,382 samples across 52 tissues, were obtained from the Genotype-Tissue Expression (GTEx) project. Additional datasets were obtained from The Cancer Genome Atlas (TCGA) program and the Gene Expression Omnibus for comparisons. Gene expression levels generally matched proteome-derived matrisome expression patterns. Further, matrisome gene expression properly clustered tissue types, with some matrisome genes including SERPIN family members having tissue-restricted expression patterns. Deeper analyses revealed 382 gene transcripts varied by age and 315 varied by sex in at least one tissue, with expression correlating with digitally imaged histologic tissue features. A comparison of TCGA tumor, TCGA adjacent normal and GTEx normal tissues demonstrated robustness of the GTEx samples as a generalized matrix control, while also determining a common primary tumor matrisome. Additionally, GTEx tissues served as a useful non-diseased control in a separate study of idiopathic pulmonary fibrosis (IPF) matrix changes, while identifying 22 matrix genes upregulated in IPF. Altogether, these findings indicate that the transcriptome, in general, and GTEx in particular, has value in understanding the state of organ ECM.Tim O. NieuwenhuisAvi Z. RosenbergMatthew N. McCallMarc K. HalushkaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tim O. Nieuwenhuis Avi Z. Rosenberg Matthew N. McCall Marc K. Halushka Tissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data
description	Abstract The extracellular matrix (ECM) has historically been explored through proteomic methods. Whether or not global transcriptomics can yield meaningful information on the human matrisome is unknown. Gene expression data from 17,382 samples across 52 tissues, were obtained from the Genotype-Tissue Expression (GTEx) project. Additional datasets were obtained from The Cancer Genome Atlas (TCGA) program and the Gene Expression Omnibus for comparisons. Gene expression levels generally matched proteome-derived matrisome expression patterns. Further, matrisome gene expression properly clustered tissue types, with some matrisome genes including SERPIN family members having tissue-restricted expression patterns. Deeper analyses revealed 382 gene transcripts varied by age and 315 varied by sex in at least one tissue, with expression correlating with digitally imaged histologic tissue features. A comparison of TCGA tumor, TCGA adjacent normal and GTEx normal tissues demonstrated robustness of the GTEx samples as a generalized matrix control, while also determining a common primary tumor matrisome. Additionally, GTEx tissues served as a useful non-diseased control in a separate study of idiopathic pulmonary fibrosis (IPF) matrix changes, while identifying 22 matrix genes upregulated in IPF. Altogether, these findings indicate that the transcriptome, in general, and GTEx in particular, has value in understanding the state of organ ECM.
format	article
author	Tim O. Nieuwenhuis Avi Z. Rosenberg Matthew N. McCall Marc K. Halushka
author_facet	Tim O. Nieuwenhuis Avi Z. Rosenberg Matthew N. McCall Marc K. Halushka
author_sort	Tim O. Nieuwenhuis
title	Tissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data
title_short	Tissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data
title_full	Tissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data
title_fullStr	Tissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data
title_full_unstemmed	Tissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data
title_sort	tissue, age, sex, and disease patterns of matrisome expression in gtex transcriptome data
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/9d288ca36166428b8cedf93868f543b4
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Tissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data

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