Decoding the interactions and functions of non-coding RNA with artificial intelligence
In addition to encoding proteins, mRNAs have context-specific regulatory roles that contribute to many cellular processes. However, uncovering new mRNA functions is constrained by limitations of traditional biochemical and computational methods. In this Roadmap, we highlight how artificial intellige...
Saved in:
| Published in: | Nature reviews. Molecular cell biology Vol. 26; no. 10; p. 797 |
|---|---|
| Main Authors: | , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
England
01.10.2025
|
| Subjects: | |
| ISSN: | 1471-0080, 1471-0080 |
| Online Access: | Get more information |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | In addition to encoding proteins, mRNAs have context-specific regulatory roles that contribute to many cellular processes. However, uncovering new mRNA functions is constrained by limitations of traditional biochemical and computational methods. In this Roadmap, we highlight how artificial intelligence can transform our understanding of RNA biology by fostering collaborations between RNA biologists and computational scientists to drive innovation in this fundamental field of research. We discuss how non-coding regions of the mRNA, including introns and 5' and 3' untranslated regions, regulate the metabolism and interactomes of mRNA, and the current challenges in characterizing these regions. We further discuss large language models, which can be used to learn biologically meaningful RNA sequence representations. We also provide a detailed roadmap for integrating large language models with graph neural networks to harness publicly available sequencing and knowledge data. Adopting this roadmap will allow us to predict RNA interactions with diverse molecules and the modelling of context-specific mRNA interactomes. |
|---|---|
| AbstractList | In addition to encoding proteins, mRNAs have context-specific regulatory roles that contribute to many cellular processes. However, uncovering new mRNA functions is constrained by limitations of traditional biochemical and computational methods. In this Roadmap, we highlight how artificial intelligence can transform our understanding of RNA biology by fostering collaborations between RNA biologists and computational scientists to drive innovation in this fundamental field of research. We discuss how non-coding regions of the mRNA, including introns and 5' and 3' untranslated regions, regulate the metabolism and interactomes of mRNA, and the current challenges in characterizing these regions. We further discuss large language models, which can be used to learn biologically meaningful RNA sequence representations. We also provide a detailed roadmap for integrating large language models with graph neural networks to harness publicly available sequencing and knowledge data. Adopting this roadmap will allow us to predict RNA interactions with diverse molecules and the modelling of context-specific mRNA interactomes.In addition to encoding proteins, mRNAs have context-specific regulatory roles that contribute to many cellular processes. However, uncovering new mRNA functions is constrained by limitations of traditional biochemical and computational methods. In this Roadmap, we highlight how artificial intelligence can transform our understanding of RNA biology by fostering collaborations between RNA biologists and computational scientists to drive innovation in this fundamental field of research. We discuss how non-coding regions of the mRNA, including introns and 5' and 3' untranslated regions, regulate the metabolism and interactomes of mRNA, and the current challenges in characterizing these regions. We further discuss large language models, which can be used to learn biologically meaningful RNA sequence representations. We also provide a detailed roadmap for integrating large language models with graph neural networks to harness publicly available sequencing and knowledge data. Adopting this roadmap will allow us to predict RNA interactions with diverse molecules and the modelling of context-specific mRNA interactomes. In addition to encoding proteins, mRNAs have context-specific regulatory roles that contribute to many cellular processes. However, uncovering new mRNA functions is constrained by limitations of traditional biochemical and computational methods. In this Roadmap, we highlight how artificial intelligence can transform our understanding of RNA biology by fostering collaborations between RNA biologists and computational scientists to drive innovation in this fundamental field of research. We discuss how non-coding regions of the mRNA, including introns and 5' and 3' untranslated regions, regulate the metabolism and interactomes of mRNA, and the current challenges in characterizing these regions. We further discuss large language models, which can be used to learn biologically meaningful RNA sequence representations. We also provide a detailed roadmap for integrating large language models with graph neural networks to harness publicly available sequencing and knowledge data. Adopting this roadmap will allow us to predict RNA interactions with diverse molecules and the modelling of context-specific mRNA interactomes. |
| Author | Jung, Vincent Xu, Zhi Ming Saadat, Ali Tumescheit, Charlotte Darsinou, Marousa Tsantoulis, Petros Riccio, Antonella Fellay, Jacques Wang, Yiran Michielin, Olivier Patani, Rickie Vincent-Cuaz, Cédric Luisier, Raphaëlle Hastings, Janna Fournier, Lisa van der Plas, Lonneke Ramos, Andres Frossard, Pascal |
| Author_xml | – sequence: 1 givenname: Vincent orcidid: 0009-0005-6731-1553 surname: Jung fullname: Jung, Vincent organization: Signal Processing Laboratory (LTS4), School of Engineering, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland – sequence: 2 givenname: Cédric orcidid: 0009-0004-5056-7977 surname: Vincent-Cuaz fullname: Vincent-Cuaz, Cédric organization: Signal Processing Laboratory (LTS4), School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland – sequence: 3 givenname: Charlotte surname: Tumescheit fullname: Tumescheit, Charlotte organization: Swiss Institute of Bioinformatics, Lausanne, Switzerland – sequence: 4 givenname: Lisa orcidid: 0009-0000-8453-2888 surname: Fournier fullname: Fournier, Lisa organization: School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland – sequence: 5 givenname: Marousa surname: Darsinou fullname: Darsinou, Marousa organization: UCL Laboratory for Molecular Cell Biology, University College London, London, UK – sequence: 6 givenname: Zhi Ming surname: Xu fullname: Xu, Zhi Ming organization: Swiss Institute of Bioinformatics, Lausanne, Switzerland – sequence: 7 givenname: Ali orcidid: 0000-0002-1479-1304 surname: Saadat fullname: Saadat, Ali organization: School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland – sequence: 8 givenname: Yiran surname: Wang fullname: Wang, Yiran organization: Department of Neuromuscular Diseases, University College London, London, UK – sequence: 9 givenname: Petros orcidid: 0000-0003-3613-6682 surname: Tsantoulis fullname: Tsantoulis, Petros organization: Institute of Structural and Molecular Biology, University College London, London, UK – sequence: 10 givenname: Olivier surname: Michielin fullname: Michielin, Olivier organization: Swiss Institute of Bioinformatics, Lausanne, Switzerland – sequence: 11 givenname: Jacques orcidid: 0000-0002-8240-939X surname: Fellay fullname: Fellay, Jacques organization: School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland – sequence: 12 givenname: Rickie orcidid: 0000-0002-3825-7675 surname: Patani fullname: Patani, Rickie organization: Department of Neuromuscular Diseases, University College London, London, UK – sequence: 13 givenname: Andres surname: Ramos fullname: Ramos, Andres organization: Research Department of Structural and Molecular Biology, University College London, London, UK – sequence: 14 givenname: Pascal surname: Frossard fullname: Frossard, Pascal organization: Signal Processing Laboratory (LTS4), School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland – sequence: 15 givenname: Janna surname: Hastings fullname: Hastings, Janna organization: School of Medicine, University of St. Gallen, St. Gallen, Switzerland – sequence: 16 givenname: Antonella surname: Riccio fullname: Riccio, Antonella organization: UCL Laboratory for Molecular Cell Biology, University College London, London, UK – sequence: 17 givenname: Lonneke surname: van der Plas fullname: van der Plas, Lonneke organization: Faculty of Communication, Culture and Society and Faculty of Informatics, Università della Svizzera italiana USI, Lugano, Switzerland – sequence: 18 givenname: Raphaëlle orcidid: 0000-0002-5657-2943 surname: Luisier fullname: Luisier, Raphaëlle email: raphaelle.luisier@gmail.com, raphaelle.luisier@gmail.com organization: Swiss Institute of Bioinformatics, Lausanne, Switzerland. raphaelle.luisier@gmail.com |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/40537558$$D View this record in MEDLINE/PubMed |
| BookMark | eNpNkMtKxDAUQIOMOA_9AReSpZtqkjZNuhzGJ4iCqNuSx81MpJOOTcrg31u1gqt7D5z7nKNJaAMgdErJBSW5vIwF5ZJkhPGMEMlFtj9AM1oI-o1k8i-fonmM74TQkgp-hKYF4bngXM7Q2xWY1vqwxmkD2IcEnTLJtyFiFSx2fRipdXgYn43y8-MS733aYNUl77zxqvkpbhq_hmDgGB061UQ4GeMCvd5cv6zusoen2_vV8iEzuRAps8ZJLbS2YApLRUVUAZUohDDDfcAqw0rutNOCSVUqnldODKgqqrk1EjRboPPfvruu_eghpnrroxnWUAHaPtY5Y6zMq1KWg3o2qr3egq13nd-q7rP--wX7AmaNZL8 |
| CitedBy_id | crossref_primary_10_1016_j_fochms_2025_100294 |
| ContentType | Journal Article |
| Copyright | 2025. Springer Nature Limited. |
| Copyright_xml | – notice: 2025. Springer Nature Limited. |
| DBID | CGR CUY CVF ECM EIF NPM 7X8 |
| DOI | 10.1038/s41580-025-00857-w |
| DatabaseName | Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic |
| DatabaseTitle | MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic MEDLINE |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database |
| DeliveryMethod | no_fulltext_linktorsrc |
| Discipline | Biology |
| EISSN | 1471-0080 |
| ExternalDocumentID | 40537558 |
| Genre | Journal Article Review |
| GroupedDBID | --- .55 0R~ 123 29M 36B 39C 4.4 53G 70F 7RV 7X7 88E 8AO 8C1 8CJ 8FE 8FH 8FI 8FJ 8R4 8R5 AARCD AAWYQ ABDBF ABFSG ABJNI ABLJU ABUWG ACGFS ACIWK ACPRK ACSTC ACUHS ADBBV AENEX AEUYN AEZWR AFANA AFBBN AFFHD AFFNX AFHIU AFKRA AFRAH AFSHS AGAYW AGSTI AHBCP AHMBA AHOSX AHSBF AHWEU AIBTJ AIXLP ALFFA ALMA_UNASSIGNED_HOLDINGS ALPWD ARMCB ASPBG ATHPR AVWKF AXYYD AZFZN B0M BBNVY BENPR BHPHI BKEYQ BKKNO BKSAR BPHCQ BVXVI CCPQU CGR CS3 CUY CVF D0L D1J DB5 DU5 EAD EAP EBC EBD EBS ECM EE. EIF EJD EMB EMK EMOBN EPL ESX EX3 EXGXG F5P FEDTE FQGFK FSGXE FYUFA HCIFZ HMCUK HVGLF HZ~ IAO IGS IHR INH INR ISR ITC LK8 M1P M7P N9A NAPCQ NFIDA NNMJJ NPM O9- ODYON PCBAR PHGZM PHGZT PJZUB PPXIY PQGLB PQQKQ PROAC PSQYO Q2X RNR RNS RNT RNTTT SHXYY SIXXV SNYQT SOJ SV3 TAOOD TBHMF TDRGL TSG TUS UKHRP WOW X7M ~8M 7X8 AAYZH |
| ID | FETCH-LOGICAL-c377t-dcf8b7bbdec4d1790a4e97477c038e29c265fbfb728a6a539f7fbfa91b5dc8eb2 |
| IEDL.DBID | 7X8 |
| ISICitedReferencesCount | 2 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001511725600001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1471-0080 |
| IngestDate | Thu Oct 02 22:33:23 EDT 2025 Sat Nov 15 01:41:50 EST 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 10 |
| Language | English |
| License | 2025. Springer Nature Limited. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c377t-dcf8b7bbdec4d1790a4e97477c038e29c265fbfb728a6a539f7fbfa91b5dc8eb2 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 |
| ORCID | 0009-0005-6731-1553 0000-0003-3613-6682 0000-0002-1479-1304 0000-0002-5657-2943 0000-0002-3825-7675 0000-0002-8240-939X 0009-0000-8453-2888 0009-0004-5056-7977 |
| PMID | 40537558 |
| PQID | 3222639686 |
| PQPubID | 23479 |
| ParticipantIDs | proquest_miscellaneous_3222639686 pubmed_primary_40537558 |
| PublicationCentury | 2000 |
| PublicationDate | 2025-10-01 |
| PublicationDateYYYYMMDD | 2025-10-01 |
| PublicationDate_xml | – month: 10 year: 2025 text: 2025-10-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England |
| PublicationTitle | Nature reviews. Molecular cell biology |
| PublicationTitleAlternate | Nat Rev Mol Cell Biol |
| PublicationYear | 2025 |
| SSID | ssj0016175 |
| Score | 2.5019302 |
| SecondaryResourceType | review_article |
| Snippet | In addition to encoding proteins, mRNAs have context-specific regulatory roles that contribute to many cellular processes. However, uncovering new mRNA... |
| SourceID | proquest pubmed |
| SourceType | Aggregation Database Index Database |
| StartPage | 797 |
| SubjectTerms | Animals Artificial Intelligence Humans Large Language Models RNA, Messenger - genetics RNA, Messenger - metabolism RNA, Untranslated - genetics RNA, Untranslated - metabolism Sequence Analysis, RNA - methods |
| Title | Decoding the interactions and functions of non-coding RNA with artificial intelligence |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/40537558 https://www.proquest.com/docview/3222639686 |
| Volume | 26 |
| WOSCitedRecordID | wos001511725600001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8QwEA7qKnjx_VhfRPAatjbNoydZ1MWLZRGVvZU8wUu7blfFf-8k7bInQfBSCDQQJpN8M5mZbxC6AkyS19xyQq0HBwUwFI6UpATc60RLq5nVKjabEEUhJ5N83D24NV1a5eJOjBe1rU14Ix-EiACgKZf8ZvpOQteoEF3tWmisoh4FUyakdInJMooA6MxidZEAlxlMo65oJqFy0ABwyYSEZq6R5J18_W5iRqgZbf93kTtoqzMy8bDVil204qo9tNG2nfzeR6934HMGzMJg_eFAGDFryxsarCqLA9S1o9rjqq5I9_NTMcTh2RYHbWuJJ-LkBaPnAXoZ3T_fPpCuvwIxVIg5scZLLbS2zmQ2MHWpzAX3QhiQkEtzk3LmtdcilYorRnMvYKjya9hBI8ElP0RrsAp3jLATTGljtGCaZdRRTW1GJcu5s0Jwn_TR5UJgJehvCEqoytUfTbkUWR8dtVIvpy3RRpkFshnG5MkfZp-izTTsZsyzO0M9D6fXnaN18zl_a2YXUTHgW4wffwBAuMNF |
| linkProvider | ProQuest |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Decoding+the+interactions+and+functions+of+non-coding+RNA+with+artificial+intelligence&rft.jtitle=Nature+reviews.+Molecular+cell+biology&rft.au=Jung%2C+Vincent&rft.au=Vincent-Cuaz%2C+C%C3%A9dric&rft.au=Tumescheit%2C+Charlotte&rft.au=Fournier%2C+Lisa&rft.date=2025-10-01&rft.issn=1471-0080&rft.eissn=1471-0080&rft_id=info:doi/10.1038%2Fs41580-025-00857-w&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1471-0080&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1471-0080&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1471-0080&client=summon |