A ratio-based framework using Quartet reference materials for integrating long- and short-read RNA-seq Article Swipe
Yang Xu
,
Yuanbang Mai
,
Shumeng Duan
,
Yaqing Liu
,
Xiaojing Li
,
Hu Chen
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-8024543/v1
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-8024543/v1
Long-read RNA sequencing (lrRNA-seq) enables full-length transcript profiling but is confounded by technical batch effects that compromise quantification and prevent data integration across platforms, protocols, and laboratories. The lack of a transcriptome-wide biological ground truth has hindered objective benchmarking. To address these dual challenges, we leveraged certified Quartet reference materials to generate one of the largest multi-center lrRNA-seq resources to date: over one billion long reads from 144 libraries across four PacBio and Nanopore protocols in four independent laboratories. We first establish that ratio-based quantification against built-in reference samples effectively removes technical noise, revealing underlying biological signals. We then constructed the first ratio-based reference datasets for full-length transcripts—comprising 10,218 isoforms and 6,032 alternative splicing (AS) events—and orthogonally validated them with RT–qPCR. Finally, a comprehensive benchmark using these ground truths reveals that a hybrid strategy integrating long- and short-read data (hybrid-seq) achieves the highest quantification accuracy for both isoforms and AS events. Our work provides a foundational framework and resource for evaluating lrRNA-seq technologies and accelerating the standardization of full-length transcriptomics for research and clinical applications.
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- https://doi.org/10.21203/rs.3.rs-8024543/v1
- https://www.researchsquare.com/article/rs-8024543/latest.pdf
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https://doi.org/10.21203/rs.3.rs-8024543/v1Digital Object Identifier
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A ratio-based framework using Quartet reference materials for integrating long- and short-read RNA-seqWork title
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articleOpenAlex work type
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2025Year of publication
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2025-12-03Full publication date if available
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Yang Xu, Yuanbang Mai, Shumeng Duan, Yaqing Liu, Xiaojing Li, Hu ChenList of authors in order
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https://doi.org/10.21203/rs.3.rs-8024543/v1Publisher landing page
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https://www.researchsquare.com/article/rs-8024543/latest.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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0Total citation count in OpenAlex
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53Number of works referenced by this work
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