SynthesisGenome biology2015
Meta-analysis of RNA-seq expression data across species, tissues and studies.
Synthesis in Genome biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 2 of them syntheses that pooled it.
What it found
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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
73 citing papers in PubMed, 2 syntheses or guidelines pooled it, 148 citations in OpenAlex.
- Pooled it
- Pooled it
- Deep learning of 777 K bulk transcriptomes reveals human-mouse gene conservation beyond DNA sequence similarity.Communications biology · 2026Article
- Translation efficiency covariation identifies conserved coordination patterns across cell types.Nature biotechnology · 2026Article
- Evolutionary Divergence of mTOR-mediated Transcriptional Regulation BetweenbioRxiv : the preprint server for biology · 2026Article
- Integrative Multi-Omics Approaches for Identifying and Characterizing Biological Elements in Crop Traits: Current Progress and Future Prospects.International journal of molecular sciences · 2025Review
- Thermal variation influences the transcriptome of the major malaria vector Anopheles stephensi.Communications biology · 2025Article
- Understanding species-specific and conserved RNA-protein interactions in vivo and in vitro.Nature communications · 2024Article
- Transcriptomic analyses of differentially expressed human genes, micro RNAs and long-non-coding RNAs in severe, symptomatic and asymptomatic malaria infection.Scientific reports · 2024Article
- Article
- Understanding species-specific and conserved RNA-protein interactionsbioRxiv : the preprint server for biology · 2024Article
- Article
- CoSIA: an R Bioconductor package for CrOss Species Investigation and Analysis.Bioinformatics (Oxford, England) · 2023Article
- Unveiling the potential of proteomics in addressing food and feed safety challenges.EFSA journal. European Food Safety Authority · 2023Article
- JGI Plant Gene Atlas: an updateable transcriptome resource to improve functional gene descriptions across the plant kingdom.Nucleic acids research · 2023Article
- CoSIA: an R Bioconductor package for CrOss Species Investigation and Analysis.bioRxiv : the preprint server for biology · 2023Article
- Understanding the evolution of immune genes in jawed vertebrates.Journal of evolutionary biology · 2023Review
- Comparative three-dimensional genome architectures of adipose tissues provide insight into human-specific regulation of metabolic homeostasis.The Journal of biological chemistry · 2023Article
- Stochastic Modeling of Gene Expression Evolution Uncovers Tissue- and Sex-Specific Properties of Expression Evolution in theJournal of computational biology : a journal of computational molecular cell biology · 2023Article
- Tissue-specific impacts of aging and genetics on gene expression patterns in humans.Nature communications · 2022Article
13 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundDifferences in gene expression drive phenotypic differences between species, yet major organs and tissues generally have conserved gene expression programs. Several comparative transcriptomic studies have observed greater similarity in gene expression between homologous tissues from different vertebrate species than between diverse tissues of the same species. However, a recent study by Lin and colleagues reached the opposite conclusion. These studies differed in the species and tissues analyzed, and in technical details of library preparation, sequencing, read mapping, normalization, gene sets, and clustering methods.
resultsTo better understand gene expression evolution we reanalyzed data from four studies, including that of Lin, encompassing 6-13 tissues each from 11 vertebrate species using standardized mapping, normalization, and clustering methods. An analysis of independent data showed that the set of tissues chosen by Lin et al. were more similar to each other than those analyzed by previous studies. Comparing expression in five common tissues from the four studies, we observed that samples clustered exclusively by tissue rather than by species or study, supporting conservation of organ physiology in mammals. Furthermore, inter-study distances between homologous tissues were generally less than intra-study distances among different tissues, enabling informative meta-analyses. Notably, when comparing expression divergence of tissues over time to expression variation across 51 human GTEx tissues, we could accurately predict the clustering of expression for arbitrary pairs of tissues and species.
conclusionsThese results provide a framework for the design of future evolutionary studies of gene expression and demonstrate the utility of comparing RNA-seq data across studies.
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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.