Evidence map›Paper›PMID 41563441›Full record

ArticleDiabetes2026

Optimizing Single-Cell Long-Read Sequencing for Enhanced Isoform Detection in Pancreatic Islets.

Maria S Hansen, Christopher J Hill, Lori Sussel, Kristen L Wells

Abstract read
In one paragraph

Article in Diabetes, 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

5 · Who and what money

Authors and funding

4 authors.

Maria S HansenBarbara Davis Center, University of Colorado Anschutz Medical Campus, Aurora, CO.
Christopher J HillBarbara Davis Center, University of Colorado Anschutz Medical Campus, Aurora, CO.
Lori SusselBarbara Davis Center, University of Colorado Anschutz Medical Campus, Aurora, CO.
Kristen L WellsBarbara Davis Center, University of Colorado Anschutz Medical Campus, Aurora, CO.ORCID 0000-0002-7466-8164

Funding

University of Colorado Anschutz Medical Campus DRCP30DK116073 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI LORI SUSSEL · 2020 to 2026
$10.8M
Regulation of Pancreatic Islet Cell FateR01DK082590 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI LORI SUSSEL · 2009 to 2026
$7.3M
Alternative RNA splicing events contribute to the onset of islet dysfunction in T1DU01DK127505 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI NAKAYASU, ERNESTO SATOSHI, SUSSEL, LORI · 2020 to 2023
$2.9M
NIDDK NIH HHS P30DK116073NIDDK NIH HHS R01 DK082590NIDDK NIH HHS U01 DK127505
6 · The paper itself

Abstract

Alternative splicing is an essential mechanism for generating protein diversity by producing distinct isoforms from a single gene. Dysregulation of splicing that affects pancreatic function and immune tolerance has been linked to both types 1 and 2 diabetes. Next-generation sequencing technologies, with their short read lengths, are limited in their ability to accurately detect splice variants. Long-read sequencing technologies offer the potential to overcome these limitations by providing full-length transcript information; however, their application in single-cell RNA sequencing has been hindered by technical challenges, including insufficient read lengths and higher error rates. Furthermore, cell types that produce high levels of a single transcript, such as islet endocrine cells, can obscure identification of lower-abundance transcripts. In this study, we optimized a protocol for single-cell long-read sequencing in pancreatic islets to improve read length and transcript detection. Our findings demonstrate that 5' library preparation protocols outperform 3' protocols, resulting in better transcript identification. Furthermore, we show that targeted depletion of insulin transcripts enhances the detection of informative reads, highlighting the utility of transcript-depletion strategies. This optimized protocol enables isoform-specific gene expression analysis and reveals differential transcript usage across the various cell types in pancreatic islets. By leveraging this approach, we gain deeper insights into the transcriptomic complexity and cellular heterogeneity within pancreatic islets. ARTICLE HIGHLIGHTS: This study addresses the limitations of current single-cell long-read RNA sequencing technologies in detecting full-length transcripts and isoform diversity, particularly in pancreatic islets. We demonstrate that optimizing single-cell library preparation protocols reproducibly enhances read length and transcript identification in pancreatic islets. Combined with targeted insulin depletion and extended reverse transcription, 5' capture methods significantly improved read length and isoform detection compared with standard protocols, while maximizing the number of informative reads. These improvements yield longer reads in single-cell experiments, substantially enhancing transcript identification and enabling more accurate analysis of isoform diversity.

Indexed as

Alternative SplicingIslets of LangerhansSingle-Cell Gene Expression AnalysisAnimalsFemaleGene LibraryGlucagon-Secreting CellsInsulin-Secreting CellsMiceMice, Inbred C57BLRNA IsoformsRNA Isoforms

Identifiers

PMID41563441
PMCPMC13007207

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.