» Articles » PMID: 38849569

Systematic Assessment of Long-read RNA-seq Methods for Transcript Identification and Quantification

Overview
Journal Nat Methods
Date 2024 Jun 7
PMID 38849569
Authors
Affiliations
Soon will be listed here.
Abstract

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Citing Articles

A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines.

Chen Y, Davidson N, Kei Wan Y, Yao F, Su Y, Gamaarachchi H Nat Methods. 2025; .

PMID: 40082608 DOI: 10.1038/s41592-025-02623-4.


Novel mRNA isoforms in human microglia refine genetic associations with neurodegeneration.

Nat Genet. 2025; 57(3):492-493.

PMID: 40055481 DOI: 10.1038/s41588-025-02112-6.


Discovery of Novel Protein-Coding and Long Non-coding Transcripts in Distinct Regions of the Human Brain.

Santucci K, Cheng Y, Xu S, Gao Y, Lindner G, Takenaka K J Mol Neurosci. 2025; 75(1):30.

PMID: 40048072 PMC: 11885362. DOI: 10.1007/s12031-025-02316-9.


Systematic review and meta-analysis of bulk RNAseq studies in human Alzheimer's disease brain tissue.

Heberle B, Fox K, Libermann L, Xavier S, Dallarosa G, Santos R Alzheimers Dement. 2025; 21(3):e70025.

PMID: 40042520 PMC: 11881636. DOI: 10.1002/alz.70025.


Long-read RNA sequencing atlas of human microglia isoforms elucidates disease-associated genetic regulation of splicing.

Humphrey J, Brophy E, Kosoy R, Zeng B, Coccia E, Mattei D Nat Genet. 2025; 57(3):604-615.

PMID: 40033057 DOI: 10.1038/s41588-025-02099-0.


References
1.
Carbonell-Sala S, Perteghella T, Lagarde J, Nishiyori H, Palumbo E, Arnan C . CapTrap-seq: a platform-agnostic and quantitative approach for high-fidelity full-length RNA sequencing. Nat Commun. 2024; 15(1):5278. PMC: 11211341. DOI: 10.1038/s41467-024-49523-3. View

2.
Nassar L, Barber G, Benet-Pages A, Casper J, Clawson H, Diekhans M . The UCSC Genome Browser database: 2023 update. Nucleic Acids Res. 2022; 51(D1):D1188-D1195. PMC: 9825520. DOI: 10.1093/nar/gkac1072. View

3.
Frankish A, Diekhans M, Jungreis I, Lagarde J, Loveland J, Mudge J . GENCODE 2021. Nucleic Acids Res. 2020; 49(D1):D916-D923. PMC: 7778937. DOI: 10.1093/nar/gkaa1087. View

4.
Raney B, Dreszer T, Barber G, Clawson H, Fujita P, Wang T . Track data hubs enable visualization of user-defined genome-wide annotations on the UCSC Genome Browser. Bioinformatics. 2013; 30(7):1003-5. PMC: 3967101. DOI: 10.1093/bioinformatics/btt637. View

5.
Kuo R, Cheng Y, Zhang R, Brown J, Smith J, Archibald A . Illuminating the dark side of the human transcriptome with long read transcript sequencing. BMC Genomics. 2020; 21(1):751. PMC: 7596999. DOI: 10.1186/s12864-020-07123-7. View