학술논문
Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network.
Document Type
Academic Journal
Author
Grapotte M; Institut de Biologie Computationnelle, Montpellier, France.; Institut de Génétique Moléculaire de Montpellier, University of Montpellier, CNRS, Montpellier, France.; SANOFI R&D, Translational Sciences, Chilly Mazarin, France.; Saraswat M; Institut de Biologie Computationnelle, Montpellier, France.; Institut de Génétique Moléculaire de Montpellier, University of Montpellier, CNRS, Montpellier, France.; Bessière C; Institut de Biologie Computationnelle, Montpellier, France.; Institut de Génétique Moléculaire de Montpellier, University of Montpellier, CNRS, Montpellier, France.; Menichelli C; Institut de Biologie Computationnelle, Montpellier, France.; LIRMM, Univ Montpellier, CNRS, Montpellier, France.; Ramilowski JA; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.; Severin J; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.; Hayashizaki Y; RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama, Japan.; Itoh M; RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama, Japan.; Tagami M; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.; Murata M; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.; Kojima-Ishiyama M; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.; Noma S; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.; Noguchi S; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.; Kasukawa T; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.; Hasegawa A; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.; Suzuki H; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.; Nishiyori-Sueki H; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.; Frith MC; Artificial Intelligence Research Center, AIST, Tokyo, Japan.; Graduate School of Frontier Sciences, University of Tokyo, Chiba, Japan.; AIST-Waseda University CBBD-OIL, AIST, Tokyo, Japan.; Chatelain C; SANOFI R&D, Translational Sciences, Chilly Mazarin, France.; Carninci P; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.; de Hoon MJL; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.; Wasserman WW; Centre for Molecular Medicine and Therapeutics at the Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada.; Bréhélin L; Institut de Biologie Computationnelle, Montpellier, France. brehelin@lirmm.fr.; LIRMM, Univ Montpellier, CNRS, Montpellier, France. brehelin@lirmm.fr.; Lecellier CH; Institut de Biologie Computationnelle, Montpellier, France. charles.lecellier@igmm.cnrs.fr.; Institut de Génétique Moléculaire de Montpellier, University of Montpellier, CNRS, Montpellier, France. charles.lecellier@igmm.cnrs.fr.; LIRMM, Univ Montpellier, CNRS, Montpellier, France. charles.lecellier@igmm.cnrs.fr.
Source
Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE
Subject
Language
English
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.