Evidence map›Paper›PMID 25421950›Full record

ReviewChromosoma2015

Variation in transcriptome size: are we getting the message?

Jeremy E Coate, Jeff J Doyle

Abstract readReview
PubMed Publisher
In one paragraph

Review in Chromosoma, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
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

38 citing papers in PubMed, 81 citations in OpenAlex.

  1. Article
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  3. Article
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  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Human B Cell Receptor Repertoire Sequencing.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  11. Article
  12. Review
  13. Telomere Transcription inBiomedicines · 2023
    Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

2 authors at 2 institutions in 1 country.

Jeremy E CoateDepartment of Biology, Reed College, Portland, OR, 97206, USA, jcoate@reed.edu.
Jeff J Doyle
Cornell University · USReed College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The number of RNA molecules per cell (transcriptome size) is highly variable, differing among and within cell types depending on cell size, stage of the cell cycle, ploidy level, age, disease state, and growth condition. Such variation has been observed at the level of total RNA, ribosomal RNA, messenger RNA (mRNA), and the polyadenylated fraction of mRNA, and these distinct RNA species can also vary in abundance with respect to each other. This variation in transcriptome size has been largely ignored or overlooked, and in fact, standard data normalization procedures for transcript profiling experiments implicitly assume that mRNA transcriptome size is constant. Consequently, variation in transcriptome size has important technical implications for such experiments, as well as profound biological implications for the affected cells and underlying genomes. Here, we review what is known about transcriptome size variation, explore how ignoring this variation introduces systematic bias into standard expression profiling experiments, and present examples of how such biases have led to erroneous conclusions in expression studies of sex chromosome dosage compensation, cancer, Rett syndrome, embryonic development, aging, and polyploidy. We also discuss how quantifying transcriptome size will help to elucidate the selective forces underlying patterns of gene and genome evolution and review the evidence that cells exert tight control over transcriptome size in order to maintain cell size homeostasis and to optimize chemical reactions within the cell, such that loss of control over transcriptome size is associated with cancer and aging. Thus, transcriptome size is an important phenotype in its own right. Finally, we discuss strategies for quantifying transcriptome size and individual gene dosage responses in order to account for and better understand this important biological phenomenon.

Indexed as

TranscriptomeBacteriaDosage Compensation, GeneticEukaryotaEvolution, MolecularFemaleGene DosageGene Expression ProfilingHumansMalePolyploidy

Identifiers

PMID25421950
OpenAlexW1983064113

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.