GENCODE 2025: Reference Gene Annotation for Human and Mouse
Author Information
Author(s): Mudge Jonathan M, Carbonell-Sala Sílvia, Diekhans Mark, Martinez Jose Gonzalez, Hunt Toby, Jungreis Irwin, Loveland Jane E, Arnan Carme, Barnes If, Bennett Ruth, Berry Andrew, Bignell Alexandra, Cerdán-Vélez Daniel, Cochran Kelly, Cortés Lucas T, Davidson Claire, Donaldson Sarah, Dursun Cagatay, Fatima Reham, Hardy Matthew, Hebbar Prajna, Hollis Zoe, James Benjamin T, Jiang Yunzhe, Johnson Rory, Kaur Gazaldeep, Kay Mike, Mangan Riley J, Maquedano Miguel, Gómez Laura Martínez, Mathlouthi Nourhen, Merritt Ryan, Ni Pengyu, Palumbo Emilio, Perteghella Tamara, Pozo Fernando, Raj Shriya, Sisu Cristina, Steed Emily, Sumathipala Dulika, Suner Marie-Marthe, Uszczynska-Ratajczak Barbara, Wass Elizabeth, Yang Yucheng T, Zhang Dingyao, Finn Robert D, Gerstein Mark, Guigó Roderic, Hubbard Tim J P, Kellis Manolis, Kundaje Anshul, Paten Benedict, Tress Michael L, Birney Ewan, Martin Fergal J, Frankish Adam
Conclusion
GENCODE continues to enhance gene annotation for human and mouse, integrating new technologies and methodologies to improve the accuracy and comprehensiveness of genomic data.
Supporting Evidence
- GENCODE has produced comprehensive reference gene annotations for human and mouse since 2005.
- The project has significantly improved the annotation process using advanced technologies like long-read sequencing.
- Over 140,000 novel lncRNA transcripts were added to human and mouse annotations in recent updates.
- GENCODE annotations are integrated with data from various genomic and proteomic studies.
- The project aims to provide a unified annotation workflow to handle the complexity of genomic data.
Takeaway
GENCODE helps scientists understand genes in humans and mice by constantly updating and improving the information about them, using new tools and methods.
Methodology
The project uses a combination of long-read transcriptome sequencing, proteomics, and multi-genome alignments to improve gene annotations.
Limitations
The increasing complexity of genomic data presents usability challenges for researchers.
Digital Object Identifier (DOI)
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