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

FANTOM Consortium

doi:10.1038/s41467-021-23143-7

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

FANTOM Consortium

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

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 language	English (US)
Article number	3297
Journal	Nature Communications
Volume	12
Issue number	1
DOIs	https://doi.org/10.1038/s41467-021-23143-7
State	Published - Dec 1 2021

Bibliographical note

Funding Information:
We thank Cédric Notredame, Anthony Mathelier, Oriol Fornes Crespo, Philip Richmond, Jean-Christophe Andrau, Diego Garrido Martin, Dimitri D. Pervouchine, Roderic Guigo, Charles Plessy, and Chung Hon for their help in analyzing the data and for insightful suggestions. We also thank Takahiro Arakawa for the preparation and provision of cell culture samples. We are indebted to the researchers around the globe who generated experimental data and made them freely available. C.-H.L. is grateful to Marc Piechaczyk and Edouard Bertrand for their continued support. The work was supported by funding from CNRS (International Associated Laboratory “miREGEN”), INSERM-ITMO Cancer project “LIONS” BIO2015-04, Plan d’Investissement d’Avenir #ANR-11-BINF-0002 Institut de Biologie Computationnelle (young investigator grant to C-H.L.) and GEM Flagship project funded from Labex NUMEV (ANR-10-LABX-0020). M.G. was supported by a Conventions Industrielles de Formation par la Recherche (CIFRE) PhD fellowship from SANOFI R&D. FANTOM5 was made possible by the following grants: Research Grant for RIKEN Omics Science Center from MEXT to Y.H.; Grant of the Innovative Cell Biology by Innovative Technology (Cell Innovation Program) from the MEXT to Y.H.; Research Grant from MEXT to the RIKEN Center for Life Science Technologies; Research Grant to RIKEN Preventive Medicine and Diagnosis Innovation Program from MEXT to Y.H. This work was further supported by a Research Grant from MEXT to the RIKEN Center for Integrative Medical Sciences.

Publisher Copyright:
© 2021, The Author(s).

ASJC Scopus subject areas

General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy

UN SDGs

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

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10.1038/s41467-021-23143-7

Cite this

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title = "Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network",

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.",

author = "{FANTOM Consortium} and Mathys Grapotte and Manu Saraswat and Chlo{\'e} Bessi{\`e}re and Christophe Menichelli and Ramilowski, {Jordan A.} and Jessica Severin and Yoshihide Hayashizaki and Masayoshi Itoh and Michihira Tagami and Mitsuyoshi Murata and Miki Kojima-Ishiyama and Shohei Noma and Shuhei Noguchi and Takeya Kasukawa and Akira Hasegawa and Harukazu Suzuki and Hiromi Nishiyori-Sueki and Frith, {Martin C.} and Imad Abugessaisa and Stuart Aitken and Aken, {Bronwen L.} and Intikhab Alam and Tanvir Alam and Rami Alasiri and Alhendi, {Ahmad M.N.} and Hamid Alinejad-Rokny and Alvarez, {Mariano J.} and Robin Andersson and Takahiro Arakawa and Marito Araki and Taly Arbel and John Archer and Archibald, {Alan L.} and Erik Arner and Peter Arner and Haitham Ashoor and Bajic, {Vladimir B.} and Salim Bougouffa and Brown, {James B.} and Cannistraci, {Carlo V.} and Yanal Ghosheh and Takashi Gojobori and Jankovic, {Boris R.} and Medvedeva, {Yulia A.} and Hiromasa Morikawa and Valerio Orlando and Timothy Ravasi and Alka Saxena and Sebastian Schmeier and Voolstra, {Christian R.}",

note = "Funding Information: We thank C{\'e}dric Notredame, Anthony Mathelier, Oriol Fornes Crespo, Philip Richmond, Jean-Christophe Andrau, Diego Garrido Martin, Dimitri D. Pervouchine, Roderic Guigo, Charles Plessy, and Chung Hon for their help in analyzing the data and for insightful suggestions. We also thank Takahiro Arakawa for the preparation and provision of cell culture samples. We are indebted to the researchers around the globe who generated experimental data and made them freely available. C.-H.L. is grateful to Marc Piechaczyk and Edouard Bertrand for their continued support. The work was supported by funding from CNRS (International Associated Laboratory “miREGEN”), INSERM-ITMO Cancer project “LIONS” BIO2015-04, Plan d{\textquoteright}Investissement d{\textquoteright}Avenir #ANR-11-BINF-0002 Institut de Biologie Computationnelle (young investigator grant to C-H.L.) and GEM Flagship project funded from Labex NUMEV (ANR-10-LABX-0020). M.G. was supported by a Conventions Industrielles de Formation par la Recherche (CIFRE) PhD fellowship from SANOFI R&D. FANTOM5 was made possible by the following grants: Research Grant for RIKEN Omics Science Center from MEXT to Y.H.; Grant of the Innovative Cell Biology by Innovative Technology (Cell Innovation Program) from the MEXT to Y.H.; Research Grant from MEXT to the RIKEN Center for Life Science Technologies; Research Grant to RIKEN Preventive Medicine and Diagnosis Innovation Program from MEXT to Y.H. This work was further supported by a Research Grant from MEXT to the RIKEN Center for Integrative Medical Sciences. Publisher Copyright: {\textcopyright} 2021, The Author(s).",

year = "2021",

month = dec,

day = "1",

doi = "10.1038/s41467-021-23143-7",

language = "English (US)",

volume = "12",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature Publishing Group",

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TY - JOUR

T1 - Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

AU - FANTOM Consortium

AU - Grapotte, Mathys

AU - Saraswat, Manu

AU - Bessière, Chloé

AU - Menichelli, Christophe

AU - Ramilowski, Jordan A.

AU - Severin, Jessica

AU - Hayashizaki, Yoshihide

AU - Itoh, Masayoshi

AU - Tagami, Michihira

AU - Murata, Mitsuyoshi

AU - Kojima-Ishiyama, Miki

AU - Noma, Shohei

AU - Noguchi, Shuhei

AU - Kasukawa, Takeya

AU - Hasegawa, Akira

AU - Suzuki, Harukazu

AU - Nishiyori-Sueki, Hiromi

AU - Frith, Martin C.

AU - Abugessaisa, Imad

AU - Aitken, Stuart

AU - Aken, Bronwen L.

AU - Alam, Intikhab

AU - Alam, Tanvir

AU - Alasiri, Rami

AU - Alhendi, Ahmad M.N.

AU - Alinejad-Rokny, Hamid

AU - Alvarez, Mariano J.

AU - Andersson, Robin

AU - Arakawa, Takahiro

AU - Araki, Marito

AU - Arbel, Taly

AU - Archer, John

AU - Archibald, Alan L.

AU - Arner, Erik

AU - Arner, Peter

AU - Ashoor, Haitham

AU - Bajic, Vladimir B.

AU - Bougouffa, Salim

AU - Brown, James B.

AU - Cannistraci, Carlo V.

AU - Ghosheh, Yanal

AU - Gojobori, Takashi

AU - Jankovic, Boris R.

AU - Medvedeva, Yulia A.

AU - Morikawa, Hiromasa

AU - Orlando, Valerio

AU - Ravasi, Timothy

AU - Saxena, Alka

AU - Schmeier, Sebastian

AU - Voolstra, Christian R.

N1 - Funding Information: We thank Cédric Notredame, Anthony Mathelier, Oriol Fornes Crespo, Philip Richmond, Jean-Christophe Andrau, Diego Garrido Martin, Dimitri D. Pervouchine, Roderic Guigo, Charles Plessy, and Chung Hon for their help in analyzing the data and for insightful suggestions. We also thank Takahiro Arakawa for the preparation and provision of cell culture samples. We are indebted to the researchers around the globe who generated experimental data and made them freely available. C.-H.L. is grateful to Marc Piechaczyk and Edouard Bertrand for their continued support. The work was supported by funding from CNRS (International Associated Laboratory “miREGEN”), INSERM-ITMO Cancer project “LIONS” BIO2015-04, Plan d’Investissement d’Avenir #ANR-11-BINF-0002 Institut de Biologie Computationnelle (young investigator grant to C-H.L.) and GEM Flagship project funded from Labex NUMEV (ANR-10-LABX-0020). M.G. was supported by a Conventions Industrielles de Formation par la Recherche (CIFRE) PhD fellowship from SANOFI R&D. FANTOM5 was made possible by the following grants: Research Grant for RIKEN Omics Science Center from MEXT to Y.H.; Grant of the Innovative Cell Biology by Innovative Technology (Cell Innovation Program) from the MEXT to Y.H.; Research Grant from MEXT to the RIKEN Center for Life Science Technologies; Research Grant to RIKEN Preventive Medicine and Diagnosis Innovation Program from MEXT to Y.H. This work was further supported by a Research Grant from MEXT to the RIKEN Center for Integrative Medical Sciences. Publisher Copyright: © 2021, The Author(s).

PY - 2021/12/1

Y1 - 2021/12/1

N2 - 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.

AB - 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.

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U2 - 10.1038/s41467-021-23143-7

DO - 10.1038/s41467-021-23143-7

M3 - Article

C2 - 34078885

AN - SCOPUS:85107388625

SN - 2041-1723

VL - 12

JO - Nature Communications

JF - Nature Communications

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

Abstract

Bibliographical note

ASJC Scopus subject areas

UN SDGs

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