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Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.

Authors :
Pardo-Palacios FJ
Wang D
Reese F
Diekhans M
Carbonell-Sala S
Williams B
Loveland JE
De María M
Adams MS
Balderrama-Gutierrez G
Behera AK
Gonzalez JM
Hunt T
Lagarde J
Liang CE
Li H
Jerryd Meade M
Moraga Amador DA
Prjibelski AD
Birol I
Bostan H
Brooks AM
Hasan Çelik M
Chen Y
Du MRM
Felton C
Göke J
Hafezqorani S
Herwig R
Kawaji H
Lee J
Liang Li J
Lienhard M
Mikheenko A
Mulligan D
Ming Nip K
Pertea M
Ritchie ME
Sim AD
Tang AD
Kei Wan Y
Wang C
Wong BY
Yang C
Barnes I
Berry A
Capella S
Dhillon N
Fernandez-Gonzalez JM
Ferrández-Peral L
Garcia-Reyero N
Goetz S
Hernández-Ferrer C
Kondratova L
Liu T
Martinez-Martin A
Menor C
Mestre-Tomás J
Mudge JM
Panayotova NG
Paniagua A
Repchevsky D
Rouchka E
Saint-John B
Sapena E
Sheynkman L
Laird Smith M
Suner MM
Takahashi H
Youngworth IA
Carninci P
Denslow ND
Guigó R
Hunter ME
Tilgner HU
Wold BJ
Vollmers C
Frankish A
Fai Au K
Sheynkman GM
Mortazavi A
Conesa A
Brooks AN
Source :
BioRxiv : the preprint server for biology [bioRxiv] 2023 Jul 27. Date of Electronic Publication: 2023 Jul 27.
Publication Year :
2023

Abstract

The Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. 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. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.<br />Competing Interests: Competing Interests Design of the project was discussed with Oxford Nanopore Technologies (ONT), Pacific Biosciences, and Lexogen. ONT provided partial support for flow cells and reagents. S.C-S and A.N.B. have received reimbursement for travel, accommodation, and conference fees to speak at events organized by ONT. A.N.B. is a consultant for Remix Therapeutics, Inc.

Details

Language :
English
ISSN :
2692-8205
Database :
MEDLINE
Journal :
BioRxiv : the preprint server for biology
Accession number :
37546854
Full Text :
https://doi.org/10.1101/2023.07.25.550582