Evidence map›Paper›PMID 39567235›Full record

ReviewGenome research2024

Understanding isoform expression by pairing long-read sequencing with single-cell and spatial transcriptomics.

Natan Belchikov, Justine Hsu, Xiang Jennie Li, Julien Jarroux, Wen Hu, Anoushka Joglekar, Hagen U Tilgner

Abstract readReview
In one paragraph

Review in Genome research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Long-Read Sequencing Reveals RNA Splicing Complexity in Human Diseases.Computational and structural biotechnology journal · 2026
    Review
  8. The Role of mRNA Alternative Processing in Mammalian Neurodevelopment.International journal of molecular sciences · 2025
    Review
  9. Review
  10. Article
  11. Review
  12. Review
  13. Article
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  16. Review
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.

Natan BelchikovFeil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10065, USA.ORCID 0000-0002-3816-7055
Justine HsuFeil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10065, USA.ORCID 0000-0003-2713-5119
Xiang Jennie LiFeil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10065, USA.ORCID 0000-0001-8829-3511
Julien JarrouxFeil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10065, USA.ORCID 0000-0002-7185-6960
Wen HuFeil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10065, USA.ORCID 0000-0002-0604-2119
Anoushka JoglekarNew York Genome Center, New York, New York 10013, USA.ORCID 0000-0002-7818-6867
Hagen U TilgnerFeil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10065, USA; hagen.u.tilgner@gmail.com.ORCID 0000-0002-7058-3606

Funding

Integrative Single Cell isoform and chromatin accessibility Mapping of Chronic Opioid Exposure in Cognitive Brain Areas in HIVU01DA053625 · NIDA · WEILL MEDICAL COLL OF CORNELL UNIV · PI MILNER, TERESA A, NDHLOVU, LISHOMWA C · 2021 to 2025
$4.0M
Tri-Institutional PhD Program in Computational Biology & MedicineT32GM132083 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI Doron Betel, Iman Hajirasouliha · 2020 to 2026
$3.6M
Multiome measurements connecting transcription start sites at single-nucleotide resolution, DNA methylation and open chromatin status to splicing outcome across single cells in health and diseaseR35GM152101 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI HAGEN ULRICH TILGNER · 2024 to 2026
$1.7M
Genetic and Environmental Influences on AddictionT32DA039080 · NIDA · WEILL MEDICAL COLL OF CORNELL UNIV · PI Teresa A Milner · 2017 to 2026
$1.4M
NIDA NIH HHS T32 DA039080NIDA NIH HHS U01 DA053625NIGMS NIH HHS R35 GM152101NIGMS NIH HHS T32 GM132083
6 · The paper itself

Abstract

RNA isoform diversity, produced via alternative splicing, and alternative usage of transcription start and poly(A) sites, results in varied transcripts being derived from the same gene. Distinct isoforms can play important biological roles, including by changing the sequences or expression levels of protein products. The first single-cell approaches to RNA sequencing-and later, spatial approaches-which are now widely used for the identification of differentially expressed genes, rely on short reads and offer the ability to transcriptomically compare different cell types but are limited in their ability to measure differential isoform expression. More recently, long-read sequencing methods have been combined with single-cell and spatial technologies in order to characterize isoform expression. In this review, we provide an overview of the emergence of single-cell and spatial long-read sequencing and discuss the challenges associated with the implementation of these technologies and interpretation of these data. We discuss the opportunities they offer for understanding the relationships between the distinct variable elements of transcript molecules and highlight some of the ways in which they have been used to characterize isoforms' roles in development and pathology. Single-nucleus long-read sequencing, a special case of the single-cell approach, is also discussed. We attempt to cover both the limitations of these technologies and their significant potential for expanding our still-limited understanding of the biological roles of RNA isoforms.

Indexed as

Alternative SplicingSequence Analysis, RNASingle-Cell AnalysisTranscriptomeAnimalsGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansProtein IsoformsRNA IsoformsProtein IsoformsRNA Isoforms

Identifiers

PMID39567235
PMCPMC11610585

What OpenQuestion holds

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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.