Characterization of the nuclear and cytosolic transcriptomes in human brain tissue reveals new insights into the subcellular distribution of RNA transcripts.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
18 02 2021
Historique:
received: 24 04 2020
accepted: 20 01 2021
entrez: 19 2 2021
pubmed: 20 2 2021
medline: 15 12 2021
Statut: epublish

Résumé

Transcriptome analysis has mainly relied on analyzing RNA sequencing data from whole cells, overlooking the impact of subcellular RNA localization and its influence on our understanding of gene function, and interpretation of gene expression signatures in cells. Here, we separated cytosolic and nuclear RNA from human fetal and adult brain samples and performed a comprehensive analysis of cytosolic and nuclear transcriptomes. There are significant differences in RNA expression for protein-coding and lncRNA genes between cytosol and nucleus. We show that transcripts encoding the nuclear-encoded mitochondrial proteins are significantly enriched in the cytosol compared to the rest of protein-coding genes. Differential expression analysis between fetal and adult frontal cortex show that results obtained from the cytosolic RNA differ from results using nuclear RNA both at the level of transcript types and the number of differentially expressed genes. Our data provide a resource for the subcellular localization of thousands of RNA transcripts in the human brain and highlight differences in using the cytosolic or the nuclear transcriptomes for expression analysis.

Identifiants

pubmed: 33603054
doi: 10.1038/s41598-021-83541-1
pii: 10.1038/s41598-021-83541-1
pmc: PMC7893067
doi:

Substances chimiques

RNA, Long Noncoding 0
RNA, Nuclear 0
RNA 63231-63-0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

4076

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Auteurs

Ammar Zaghlool (A)

Department of Immunology, Genetics and Pathology, Uppsala University, BMC B11:4, Box 815, 751 08, Uppsala, Sweden. ammar.zaghlool@igp.uu.se.
Science for Life Laboratory in Uppsala, Uppsala University, Uppsala, Sweden. ammar.zaghlool@igp.uu.se.

Adnan Niazi (A)

Department of Immunology, Genetics and Pathology, Uppsala University, BMC B11:4, Box 815, 751 08, Uppsala, Sweden.
Science for Life Laboratory in Uppsala, Uppsala University, Uppsala, Sweden.

Åsa K Björklund (ÅK)

Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Husargatan 3, 752 37, Uppsala, Sweden.

Jakub Orzechowski Westholm (JO)

Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Stockholm University, Box 1031, 17121, Solna, Sweden.

Adam Ameur (A)

Department of Immunology, Genetics and Pathology, Uppsala University, BMC B11:4, Box 815, 751 08, Uppsala, Sweden.
Science for Life Laboratory in Uppsala, Uppsala University, Uppsala, Sweden.

Lars Feuk (L)

Department of Immunology, Genetics and Pathology, Uppsala University, BMC B11:4, Box 815, 751 08, Uppsala, Sweden. lars.feuk@igp.uu.se.
Science for Life Laboratory in Uppsala, Uppsala University, Uppsala, Sweden. lars.feuk@igp.uu.se.

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Classifications MeSH