Evidence map›Paper›PMID 40149494›Full record

ReviewGenes2025

Detection of mRNA Transcript Variants.

Kevin Vo, Sharmin Shila, Yashica Sharma, Grace J Pei, Cinthia Y Rosales, Vinesh Dahiya, Patrick E Fields, M A Karim Rumi

Abstract readReview
In one paragraph

Review in Genes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Neurofibromin 1 (International journal of molecular sciences · 2026
    Article
  4. mRNA Isoforms and Variants in Health and Disease.International journal of molecular sciences · 2025
    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

8 authors.

Kevin VoDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.
Sharmin ShilaDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.ORCID 0009-0008-9704-5390
Yashica SharmaDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.
Grace J PeiDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.
Cinthia Y RosalesDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.
Vinesh DahiyaDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.ORCID 0000-0002-0698-4747
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

Most eukaryotic genes express more than one mature mRNA, defined as transcript variants. This complex phenomenon arises from various mechanisms, such as using alternative transcription start sites and alternative post-transcriptional processing events. The resulting transcript variants can lead to synthesizing proteins that possess distinct functional domains or may even generate noncoding RNAs, each with unique roles in cellular processes. The generation of these transcript variants is not merely a random occurrence; it is cell-type specific and varies with developmental stages, aging processes, or pathogenesis of diseases. This highlights the biological significance of transcript variants in regulating gene expression and their potential impact on cellular functionality. Despite the biological importance, investigating transcript variants has been hampered by challenges associated with detecting their expression. This review article addresses the advancements in molecular techniques in detecting transcript variants. Traditional methods such as RT-PCR and RT-qPCR can easily detect known transcript variants using primers that target unique exons associated with the variants. Other techniques like RACE-PCR and hybridization-based methods, including Northern blotting, RNase protection assays, and microarrays, have also been utilized to detect transcript variants. Nevertheless, RNA sequencing (RNA-Seq) has emerged as a powerful technique for identifying transcript variants, especially those with previously unknown sequences. The effectiveness of RNA sequencing in transcript variant detection depends on the specific sequencing approach and the precision of data analysis. By understanding the strengths and weaknesses of each laboratory technique, researchers can develop more effective strategies for detecting mRNA transcript variants. This ability will be crucial for our comprehensive understanding of gene regulation and the implications of transcript diversity in various biological contexts.

Indexed as

Alternative SplicingRNA, MessengerAnimalsGenetic VariationHumansSequence Analysis, RNARNA, Messengeranalyses of NGS datagene expressionmRNA transcript variantsRNA sequencingspatial transcriptomicsverification of NGS data

Identifiers

PMID40149494
PMCPMC11942493

What OpenQuestion holds

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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.