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Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

  • FANTOM consortium
  • Institut de Biologie Computationnelle, Montpellier, France
  • Université de Montpellier
  • Sanofi-Aventis
  • RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
  • RIKEN
  • National Institute of Advanced Industrial Science and Technology
  • The University of Tokyo
  • Waseda University
  • University of Edinburgh
  • European Molecular Biology Laboratory
  • Wellcome Trust
  • King Abdullah University of Science and Technology
  • Centre of Genomics and Policy, McGill University and Génome Québec Innovation Centre, Montreal, QC, H3A 0G4, Canada
  • University of New South Wales
  • University of Western Australia
  • Columbia University
  • University of Copenhagen
  • Department of Emergency and Disaster Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
  • University of California at Berkeley
  • Karolinska Institutet
  • Charité – Universitätsmedizin Berlin
  • Jackson Laboratory
  • Agency for Science, Technology and Research, Singapore
  • Stanford University
  • University of Queensland

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.
Original languageEnglish
Article number3297
JournalNature communications
Volume12
Issue number1
DOIs
Publication statusPublished - 1 Dec 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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