ReviewChromosoma2015
Variation in transcriptome size: are we getting the message?
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.
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.
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.
Who cites it
38 citing papers in PubMed, 81 citations in OpenAlex.
- Cell-free genomics reveals fundamental regulatory principles of the Mycobacterium tuberculosis transcription cycle.Molecular cell · 2026Article
- Genome-scale transcriptome augmentation during Arabidopsis thaliana photomorphogenesis.Nature communications · 2025Article
- DNA gains and losses in gigantic genomes do not track differences in transposable element-host silencing interactions.Communications biology · 2025Article
- Cell type-specific weighting-factors to solve solid organs-specific limitations of single cell RNA-sequencing.PLoS genetics · 2024Article
- Unifying framework explaining how parental regulatory divergence can drive gene expression in hybrids and allopolyploids.Nature communications · 2024Article
- Chromatin Accessibility and Gene Expression Vary Between a New and Evolved Autopolyploid of Arabidopsis arenosa.Molecular biology and evolution · 2024Article
- Metatranscriptomic response of deep ocean microbial populations to infusions of oil and/or synthetic chemical dispersant.Applied and environmental microbiology · 2024Article
- The immediate metabolomic effects of whole-genome duplication in the greater duckweed, Spirodela polyrhiza.American journal of botany · 2024Article
- Review
- Human B Cell Receptor Repertoire Sequencing.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Deciphering a global source of non-genetic heterogeneity in cancer cells.Nucleic acids research · 2023Article
- An Emerging Animal Model for Querying the Role of Whole Genome Duplication in Development, Evolution, and Disease.Journal of developmental biology · 2023Review
- Telomere Transcription inBiomedicines · 2023Article
- Biomolecule-Based Optical Metamaterials: Design and Applications.Biosensors · 2022Review
- Experimental and computational workflow for the analysis of tRNA pools from eukaryotic cells by mim-tRNAseq.STAR protocols · 2022Article
- The accuracy of absolute differential abundance analysis from relative count data.PLoS computational biology · 2022Article
- Normalization of gene expression data revisited: the three viewpoints of the transcriptome in human skeletal muscle undergoing load-induced hypertrophy and why they matter.BMC bioinformatics · 2022Article
- Transcriptional Shift and Metabolic Adaptations duringMicroorganisms · 2022Article
- DNA Methylome and LncRNAome Analysis Provide Insights Into Mechanisms of Genome-Dosage Effects in Autotetraploid Cassava.Frontiers in plant science · 2022Article
- Anti-bias training for (sc)RNA-seq: experimental and computational approaches to improve precision.Briefings in bioinformatics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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What OpenQuestion holds
Registered trials
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.