Evidence map›Paper›PMID 42219495›Full record

ArticleGenome biology2026

Hybrid untargeted short-read and targeted long-read RNA sequencing facilitates genotype-phenotype associations at single-cell resolution.

Jiayi Wang, Maria Constanza Maldifassi, Anna Bratus-Neuenschwander, Qin Zhang, Felix Beuschlein, David Penton, Mark D Robinson

Abstract read
PubMed Full text at PMC Publisher
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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jiayi WangDepartment of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Maria Constanza MaldifassiInstituto de Fisiología, Facultad de Ciencias, Universidad de Valparaíso, Valparaíso, Chile.
Anna Bratus-NeuenschwanderFunctional Genomics Center Zurich, ETH Zurich and University of Zurich, Zurich, 8057, Switzerland.
Qin ZhangFunctional Genomics Center Zurich, ETH Zurich and University of Zurich, Zurich, 8057, Switzerland.
Felix BeuschleinDepartment of Endocrinology, Diabetology and Clinical Nutrition, University Hospital Zurich (USZ), 8091, Zurich, Switzerland.
David PentonElectrophysiology Facility, University of Zurich, Zurich, Switzerland.
Mark D RobinsonDepartment of Molecular Life Sciences, University of Zurich, Zurich, Switzerland. mark.robinson@mls.uzh.ch.

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung CRSII_222773
6 · The paper itself

Abstract

Long-read single-cell RNA sequencing enables simultaneous and unbiased detection of transcriptomic variants and gene expression, but its application is limited by low read coverage, restricting genotype-phenotype analyses at single-cell resolution. We systematically evaluate short-read whole-transcriptome amplification (SR-WTA), long-read whole-transcriptome amplification (LR-WTA), and long-read targeted sequencing (LR-Twist). Based on these comparisons, we develop a hybrid strategy combining SR-WTA and LR-Twist within a Snakemake pipeline to leverage the strengths of both approaches. SR-WTA provides broad transcriptome coverage, while LR-Twist enriches a 50-gene panel for deeper variant detection. This approach improves the power to link mutational profiles with transcriptional programs at single-cell resolution.

Indexed as

Genetic Association StudiesSequence Analysis, RNASingle-Cell AnalysisAnimalsGenotypeHumansPhenotypeSingle-Cell Gene Expression AnalysisTranscriptomeCell typingGenotype–phenotype integrationHybrid strategyLong-read scRNA-seqShort-read scRNA-seqTargeted sequencingVariant calling

Identifiers

PMID42219495
PMCPMC13617763

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.