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

Gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

View ORCID ProfileJan Zrimec, Filip Buric, Azam Sheikh Muhammad, Rhongzen Chen, Vilhelm Verendel, Mats Töpel, View ORCID ProfileAleksej Zelezniak
doi: https://doi.org/10.1101/792531
Jan Zrimec
1Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-412 96, Gothenburg, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jan Zrimec
Filip Buric
1Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-412 96, Gothenburg, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Azam Sheikh Muhammad
2Computer Science and Engineering, Chalmers University of Technology, Rännvägen 6B, SE-412 96, Gothenburg, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rhongzen Chen
2Computer Science and Engineering, Chalmers University of Technology, Rännvägen 6B, SE-412 96, Gothenburg, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Vilhelm Verendel
2Computer Science and Engineering, Chalmers University of Technology, Rännvägen 6B, SE-412 96, Gothenburg, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mats Töpel
3Department of Marine Sciences, University of Gothenburg, Box 461, SE-405 30, Gothenburg, Sweden
4Gothenburg Global Biodiversity Center (GGBC), Box 461, 40530 Gothenburg, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Aleksej Zelezniak
1Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-412 96, Gothenburg, Sweden
5Science for Life Laboratory, Tomtebodavägen 23a, SE-171 65, Stockholm, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Aleksej Zelezniak
  • For correspondence: aleksej.zelezniak@chalmers.se
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Understanding the genetic regulatory code that governs gene expression is a primary, yet challenging aspiration in molecular biology that opens up possibilities to cure human diseases and solve biotechnology problems. However, the fundamental question of how each of the individual coding and non-coding regions of the gene regulatory structure interact and contribute to the mRNA expression levels remains unanswered. Considering that all the information for gene expression regulation is already present in living cells, here we applied deep learning on over 20,000 mRNA datasets in 7 model organisms ranging from bacteria to Human. We show that in all organisms, mRNA abundance can be predicted directly from the DNA sequence with high accuracy, demonstrating that up to 82% of the variation of gene expression levels is encoded in the gene regulatory structure. Coding and non-coding regions carry both overlapping and orthogonal information and additively contribute to gene expression levels. By searching for DNA regulatory motifs present across the whole gene regulatory structure, we discover that motif interactions can regulate gene expression levels in a range of over three orders of magnitude. The uncovered co-evolution of coding and non-coding regions challenges the current paradigm that single motifs or regions are solely responsible for gene expression levels. Instead, we show that the correct combination of all regulatory regions must be established in order to accurately control gene expression levels. Therefore, the holistic system that spans the entire gene regulatory structure is required to analyse, understand, and design any future gene expression systems.

Footnotes

  • A chapter was added to the results section as well as figure 5. Text was updated in all sections and references added. Mistakes were fixed in text and figures 1,2 and 4.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted October 23, 2019.
Download PDF

Supplementary Material

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.
Gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
(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
Gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
Jan Zrimec, Filip Buric, Azam Sheikh Muhammad, Rhongzen Chen, Vilhelm Verendel, Mats Töpel, Aleksej Zelezniak
bioRxiv 792531; doi: https://doi.org/10.1101/792531
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
Jan Zrimec, Filip Buric, Azam Sheikh Muhammad, Rhongzen Chen, Vilhelm Verendel, Mats Töpel, Aleksej Zelezniak
bioRxiv 792531; doi: https://doi.org/10.1101/792531

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

  • Systems Biology
  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (3583)
  • Biochemistry (7537)
  • Bioengineering (5491)
  • Bioinformatics (20715)
  • Biophysics (10272)
  • Cancer Biology (7944)
  • Cell Biology (11604)
  • Clinical Trials (138)
  • Developmental Biology (6577)
  • Ecology (10155)
  • Epidemiology (2065)
  • Evolutionary Biology (13565)
  • Genetics (9509)
  • Genomics (12806)
  • Immunology (7899)
  • Microbiology (19487)
  • Molecular Biology (7631)
  • Neuroscience (41957)
  • Paleontology (307)
  • Pathology (1253)
  • Pharmacology and Toxicology (2188)
  • Physiology (3255)
  • Plant Biology (7017)
  • Scientific Communication and Education (1292)
  • Synthetic Biology (1945)
  • Systems Biology (5415)
  • Zoology (1110)