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

Pardo-Palacios, Francisco J.; Wang, Dingjie; Reese, Fairlie; Diekhans, Mark; Sala, Sílvia Carbonell; Williams, Brian A.; Loveland, Jane; María, Maite De; Adams, Matthew S.; Balderrama-Gutierrez, Gabriela; Behera, Amit K.; González, José M.; Hunt, Toby; Lagarde, Julien; Liang, Cindy; Li, Haoran; Meade, Marcus J.; Amador, David A. Moraga; Prjibelski, Andrey D.; Birol, İnanç; Bostan, Hamed; Brooks, Ashley M.; Çelik, Muhammed Hasan; Chen, Ying; Du, Mei R. M.; Felton, Colette; Göke, Jonathan; Hafezqorani, Saber; Herwig, Ralf; Kawaji, Hideya; Lee, Joseph; Li, Jian‐Liang; Lienhard, Matthias; Mikheenko, Alla; Mulligan, Dennis; Nip, Ka Ming; Pertea, Mihaela; Ritchie, Matthew E.; Sim, Andre; Tang, Alison D.; Wan, Yuk Kei; Wang, Changqing; Wong, Brandon; Yang, Chen; Barnes, If; Berry, Andrew; Capella-Gutiérrez, Salvador; Cousineau, Alyssa; Dhillon, Namrita; Fernández, José M.; Ferrández-Peral, Luis; Garcia-Reyero, Natàlia; Götz, Stefan; Hernandéz-Ferrer, Carles; Kondratova, Liudmyla; Liu, Tianyuan; Martinez-Martin, Alessandra; Menor, Carlos; Mestre‐Tomás, Jorge; Mudge, Jonathan M.; Panayotova, Nedka G.; Paniagua, Alejandro; Repchevsky, Dmitry; Ren, Xingjie; Rouchka, Eric C.; Saint-John, Brandon; Sapena, Enrique; Sheynkman, Leon; Smith, Melissa; Suner, Marie‐Marthe; Takahashi, Hazuki; Youngworth, Ingrid; Carninci, Piero; Denslow, Nancy D.; Guigó, Roderic; Hunter, Margaret E.; Maehr, René; Shen, Yin; Tilgner, Hagen; Wold, B; Vollmers, Christopher; Frankish, Adam; Au, Kin Fai; Sheynkman, Gloria; Mortazavi, A; Conesa, Ana; Brooks, Angela N.

doi:10.1038/s41592-024-02298-3

articleNature MethodsJun 7, 2024HYBRID OA

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

FJFrancisco J. Pardo-Palacios DWDingjie Wang FRFairlie Reese MDMark Diekhans SCSílvia Carbonell Sala

Consejo Superior de Investigaciones Científicas · Institute for Integrative Systems Biology · +42 more institutions

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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…

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Topics & keywords

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Keywords

Computational biology
Annotation
Benchmark (surveying)
Replicate
Identification (biology)
Computer science
Transcriptome
Genome

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