Evidence map›Paper›PMID 41742281›Full record

ArticleGenome biology2026

A systematic benchmark of high-accuracy PacBio long-read RNA sequencing for transcript-level quantification.

David Wissel, Madison M Mehlferber, Khue M Nguyen, Vasilii Pavelko, Elizabeth Tseng, Mark D Robinson, Gloria M Sheynkman

Abstract read
In one paragraph

Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Long-Read Sequencing Reveals RNA Splicing Complexity in Human Diseases.Computational and structural biotechnology journal · 2026
    Review
  8. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

David Wissel *Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Madison M Mehlferber *Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Khue M NguyenCenter for Digital Health, Berlin Institute of Health (BIH) at Charité - Universitätsmedizin, Berlin, Germany.
Vasilii PavelkoDepartment of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA.
Elizabeth TsengPacific Biosciences, Menlo Park, CA, USA.
Mark D RobinsonDepartment of Molecular Life Sciences, University of Zurich, Zurich, Switzerland. mark.robinson@mls.uzh.ch.
Gloria M SheynkmanDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA. gs9yr@virginia.edu.

Funding

Uncovering the functional diversification mechanisms of transcription factor isoforms involved in stem cell differentiationR35GM142647 · NIGMS · UNIVERSITY OF VIRGINIA · PI SHEYNKMAN, GLORIA · 2021 to 2025
$2.1M
NIGMS NIH HHS R35GM142647Robert M. Berne Cardiovascular Research Center Training Program T32HL007284Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 204869Wagner Fellowship MMM
6 · The paper itself

Abstract

backgroundThe assembly of fragmented RNA-sequencing reads into complete transcripts is error-prone, particularly for genes with complex splicing, resulting in ambiguity in transcript discovery and quantification. PacBio long-read RNA sequencing resolves transcripts with greater clarity than short-read technologies. PacBio Kinnex employs a cDNA concatenation approach that increases read yield on average by 8-fold relative to previous protocols. However, its quantitative performance remains under-evaluated at scale.

resultsHere, we benchmark the high-throughput PacBio Kinnex platform against Illumina short-read RNA-seq using matched, deeply sequenced datasets across a time course of endothelial cell differentiation. Compared to Illumina, Kinnex achieves comparable gene-level quantification and more accurate transcript discovery and transcript quantification. While Illumina detects more transcripts overall, many reflect potentially unstable or ambiguous estimates in complex genes. Kinnex largely avoids these issues, producing more reliable differential transcript expression calls, despite a mild bias against short transcripts (shorter than 1.25 kb). When correcting Illumina for inferential variability, Kinnex and Illumina quantifications are highly concordant, demonstrating equivalent performance. We also benchmark long-read tools, nominating Oarfish as the most efficient for our Kinnex data.

conclusionsTogether, our results establish Kinnex as a reliable platform for full-length transcript quantification.

Indexed as

High-Throughput Nucleotide SequencingSequence Analysis, RNAAnimalsBenchmarkingGene Expression ProfilingHumansEndothelial cellsLong-read RNA-seqPacBioQuantification

Identifiers

PMID41742281
PMCPMC13040695

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.