Evidence map›Paper›PMID 39273072›Full record

ArticleCells2024

Importance of Transcript Variants in Transcriptome Analyses.

Kevin Vo, Yashica Sharma, Anohita Paul, Ryan Mohamadi, Amelia Mohamadi, Patrick E Fields, M A Karim Rumi

Abstract read
In one paragraph

Article in Cells, 2024. 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. Article
  2. Article
  3. mRNA Isoforms and Variants in Health and Disease.International journal of molecular sciences · 2025
    Review
  4. Article
  5. Review
  6. mRNA Transcript Variants Expressed in Mammalian Cells.International journal of molecular sciences · 2025
    Review
  7. Article
  8. 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.

Kevin VoDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.
Yashica SharmaDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.
Anohita PaulDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.
Ryan MohamadiDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.
Amelia MohamadiDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.
Patrick E FieldsDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.ORCID 0000-0002-6797-4139
M A Karim RumiDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA sequencing (RNA-Seq) has become a widely adopted technique for studying gene expression. However, conventional RNA-Seq analyses rely on gene expression (GE) values that aggregate all the transcripts produced under a single gene identifier, overlooking the complexity of transcript variants arising from different transcription start sites or alternative splicing. Transcript variants may encode proteins with diverse functional domains, or noncoding RNAs. This study explored the implications of neglecting transcript variants in RNA-Seq analyses. Among the 1334 transcription factor (TF) genes expressed in mouse embryonic stem (ES) or trophoblast stem (TS) cells, 652 were differentially expressed in TS cells based on GE values (365 upregulated and 287 downregulated, ≥absolute 2-fold changes, false discovery rate (FDR)

Indexed as

Gene Expression ProfilingTranscriptomeAlternative SplicingAnimalsGene Expression RegulationMiceMouse Embryonic Stem CellsRNA, MessengerSequence Analysis, RNATranscription FactorsTrophoblastsRNA, MessengerTranscription Factorsdifferential expression of genesdifferential expression of transcript variantsembryonic stem cellsRNA sequencingtranscript variantstrophoblast stem cells

Identifiers

PMID39273072
PMCPMC11394320

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.