Tamara Perteghella1,2,*, Gazaldeep Kaur1,*, Sílvia Carbonell-Sala1,3,*, Jose Gonzalez-Martinez4,*, Toby Hunt4,*, Tomasz Mądry5, Irwin Jungreis6,7, Fabien Degalez1,8, Carme Arnan1, Silvia González-López1,2, Ramil Nurtdinov1, Julien Lagarde1, Beatrice Borsari9,10,11, Yunzhe Jiang9,10, Sebastien Auber1, Ruth Bennett4, Andrew Berry4, Marta Blangiewicz5, Daniel Cerdán-Vélez12, Kelly Cochran13, Claire Davidson4, Sarah Donaldson4, Cagatay Dursun9,10, Stefan Ernst Seemann14, Veerendra P. Gadekar14,15, Sasti Gopal Das5, Roderic Guigó-Corominas16, Guillem Guigó i Corominas3,17, Matthew Hardy4, Zoe Hollis4, Mike Kay4, Kathryn Lawrence18, Daniel Nachun19, José Carlos Montañés20,21, Pengyu Ni9,10, Vasilis F. Ntasis1,20, Emilio Palumbo1, Carlos Pulido-Quetglas22,23, Cristina Sisu24, Marie-Marthe Suner4, Covadonga Vara20, Xuezhu Yu9,10, Dingyao Zhang9,10, Francois Aguet7, Kristin Ardlie7, Stephen B. Montgomery18,19,25, M. Mar Albà20,26, Jan Gorodkin14, John R. Prensner27,28, Jane E. Loveland4, Mark Diekhans29,30, Andrea Tanzer31, Jonathan M. Mudge4,32, Paul Flicek33,34, Fergal J Martin4, Anshul Kundaje13,18, Benedict Paten29, Mark Gerstein9,10,35,36,37, Manolis Kellis6,7, Michael L. Tress12, Rory Johnson38,39,40, Barbara Uszczynska-Ratajczak5, Adam Frankish4, Roderic Guigó1,2
1. Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Catalonia, Spain.
2. Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra (UPF).
3. Facultat de Ciències, Tecnologia i Enginyeries, Universitat de Vic-Universitat Central de Catalunya, Catalonia.
4. European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
5. Department of Computational Biology of Noncoding RNA, Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland.
6. Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA.
7. The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA.
8. PEGASE, INRAE, Institut Agro, 35590, Saint Gilles, France
9. Program in Computational Biology and Biomedical informatics, Yale University, New Haven, Connecticut 06520, USA.
10. Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA.
11. Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona (UB), Barcelona, 08028, Spain
12. Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Calle Melchor Fernandez Almagro, 3, 28029 Madrid, Spain.
13. Department of Computer Science, Stanford University, Stanford, CA, USA.
14. Center for non-coding RNA in Technology and Health, Section for Health Data Science and AI, Department of Public Health, University of Copenhagen, Denmark
15. Centre for Integrative Biology and Systems Medicine, IIT Madras, Chennai, India
16. Department of Mathematics, Harvard University, Cambridge MA 02138
17. eXIT research group, Universitat de Girona, Catalonia
18. Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
19. Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
20. Hospital del Mar Research Institute, Dr. Aiguader 88, Barcelona 08003, Spain.
21. Molecular Biology Core, Biomedical Diagnostic Centre, Hospital Clínic de Barcelona, Barcelona, Spain.
22. Department of Computational Biology, University of Lausanne, Lausanne, CH-1015, Switzerland
23. School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, D04 V1W8, Ireland.
24. Department of Life Sciences, Brunel University London, Uxbridge, London, UB8 3PH, UK.
25. Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
26. Catalan Institute for Research and Advanced Studies (ICREA), Barcelona, Spain.
27. Department of Pediatrics, Division of Pediatric Hematology/Oncology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
28. Department of Biological Chemistry, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
29. UC Santa Cruz Genomics Institute, 2300 Delaware Avenue, University of California, Santa Cruz, CA 95060, USA.
30. Tricode Genomics, Santa Cruz, CA, USA
31. University of Vienna, Max Perutz Labs, Vienna, Austria
32. Institute of Cancer Research, London SW3 6JB, UK
33. Institute for Systems Genomics, University of Connecticut, Storrs, CT 06269, USA.
34. Department of Genetics and Genome Sciences, University of Connecticut School of Medicine, 400 Farmington Ave, Farmington, CT 06030, USA.
35. Department of Statistics & Data Science, Yale University, New Haven, Connecticut 06520, USA.
36. Department of Computer Science, Yale University, New Haven, Connecticut 06520, USA.
37. Department of Biomedical Informatics & Data Science, Yale University, New Haven, Connecticut 06520, USA.
38. School of Medicine, University College Dublin, Dublin, Ireland.
39. Systems Biology Ireland, School of Medicine, University College Dublin, Dublin, Ireland.
40. Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland.
* Equal contribution
Correspondence should be addressed to R.G. (roderic.guigo@crg.cat)
GENCODE is a 20-year international project focused on producing high-quality annotations for human and mouse genomes, crucial for understanding gene function. While the human gene catalog for protein-coding genes is nearly complete, long non-coding RNA (lncRNA) annotations have remained inconsistent across different catalogs. To address this, GENCODE used targeted RNA sequencing to unify and expand lncRNA annotations in human and mouse, employing full-length sequencing across diverse tissues. This effort resulted in 16,817 new human genes and 22,210 new mouse genes, significantly increasing the lncRNA catalog and improving orthology mapping between species. These new annotations enhance the functional interpretation of genome data, linking previously unannotated regions to biological functions.
In this repository:
Summary of the steps taken to process long-read data, upon sequencing but prior to LyRic. Measures undertaken to assess the quality of the data prior to downstream processing are also detailed here.
List of the files used in this work, complemented with descriptions of the steps taken to generate them, links to direct download, and detailed information about formats and tags.
Datasets used in this work, complemented with useful information regarding the files and their processing prior to analysis.
Codes used in various downstream analyses.