Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Cap analysis of gene expression (CAGE) sequencing reveals alternative promoter usage in complex disease

Sonal Dahale, View ORCID ProfileJorge Ruiz-Orera, View ORCID ProfileJan Silhavy, Norbert Hubner, View ORCID ProfileSebastiaan van Heesch, Michal Pravenec, View ORCID ProfileSantosh S Atanur
doi: https://doi.org/10.1101/2021.08.28.458014
Sonal Dahale
1Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
2Department of Microbial Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jorge Ruiz-Orera
3Cardiovascular and Metabolic Sciences, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 13125 Berlin, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jorge Ruiz-Orera
Jan Silhavy
4Institute of Physiology of the Czech Academy of Sciences, 142 00, Prague 4, Czech Republic
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jan Silhavy
Norbert Hubner
3Cardiovascular and Metabolic Sciences, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 13125 Berlin, Germany
5Charité -Universitätsmedizin, 10117 Berlin, Germany
6DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, 13347 Berlin, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sebastiaan van Heesch
7Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584 CS, Utrecht, the Netherlands
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Sebastiaan van Heesch
Michal Pravenec
4Institute of Physiology of the Czech Academy of Sciences, 142 00, Prague 4, Czech Republic
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Santosh S Atanur
1Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
8NIHR Imperial Biomedical Research Centre, ITMAT Data Science Group, Imperial College London, London, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Santosh S Atanur
  • For correspondence: santosh.atanur@imperial.ac.uk
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

The role of alternative promoter usage in tissue specific gene expression has been well established, however, its role in complex diseases is poorly understood. We performed cap analysis of gene expression (CAGE) tag sequencing from the left ventricle (LV) of a rat model of hypertension, the spontaneously hypertensive rat (SHR), and a normotensive strain, the Brown Norway (BN) to understand role of alternative promoter usage in complex disease. We identified 26,560 CAGE-defined transcription start sites (TSS) in the rat LV, including 1,970 novel cardiac TSS resulting in new transcripts. We identified 27 genes with alternative promoter usage between SHR and BN which could lead to protein isoforms differing at the amino terminus between two strains. Additionally, we identified 475 promoter switching events where a shift in TSS usage was within 100bp between SHR and BN, altering length of the 5’ UTR. Genomic variants located in the shifting promoter regions showed significant allelic imbalance in F1 crosses, confirming promoter shift. We found that the insulin receptor gene (Insr) showed a switch in promoter usage between SHR and BN in heart and liver. The Insr promoter shift was significantly associated with insulin levels and blood pressure within a panel of BXH/HXB recombinant inbred (RI) rat strains. This suggests that the hyperinsulinemia due to insulin resistance might lead to hypertension in SHR. Our study provides a preliminary evidence of alternative promoter usage in complex diseases.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted August 28, 2021.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Cap analysis of gene expression (CAGE) sequencing reveals alternative promoter usage in complex disease
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Cap analysis of gene expression (CAGE) sequencing reveals alternative promoter usage in complex disease
Sonal Dahale, Jorge Ruiz-Orera, Jan Silhavy, Norbert Hubner, Sebastiaan van Heesch, Michal Pravenec, Santosh S Atanur
bioRxiv 2021.08.28.458014; doi: https://doi.org/10.1101/2021.08.28.458014
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Cap analysis of gene expression (CAGE) sequencing reveals alternative promoter usage in complex disease
Sonal Dahale, Jorge Ruiz-Orera, Jan Silhavy, Norbert Hubner, Sebastiaan van Heesch, Michal Pravenec, Santosh S Atanur
bioRxiv 2021.08.28.458014; doi: https://doi.org/10.1101/2021.08.28.458014

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (3686)
  • Biochemistry (7774)
  • Bioengineering (5668)
  • Bioinformatics (21245)
  • Biophysics (10563)
  • Cancer Biology (8162)
  • Cell Biology (11915)
  • Clinical Trials (138)
  • Developmental Biology (6738)
  • Ecology (10388)
  • Epidemiology (2065)
  • Evolutionary Biology (13843)
  • Genetics (9694)
  • Genomics (13056)
  • Immunology (8123)
  • Microbiology (19956)
  • Molecular Biology (7833)
  • Neuroscience (42973)
  • Paleontology (318)
  • Pathology (1276)
  • Pharmacology and Toxicology (2256)
  • Physiology (3350)
  • Plant Biology (7208)
  • Scientific Communication and Education (1309)
  • Synthetic Biology (1999)
  • Systems Biology (5528)
  • Zoology (1126)