Evidence map›Paper›PMID 25297727›Full record

ReviewNature reviews. Genetics2014

Evolutionary dynamics of coding and non-coding transcriptomes.

Anamaria Necsulea, Henrik Kaessmann

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 135 papers.

0numbers the graph read from it
0cells of the map it votes in
135citing 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

135 citing papers in PubMed.

  1. Article
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  4. Article
  5. Review
  6. Article
  7. Remodeling ofScience advances · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. Article
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  13. In search of epigenetic hallmarks of different tissues: an integrative omics study of horse liver, lung, and heart.Mammalian genome : official journal of the International Mammalian Genome Society · 2024
    Article
  14. Oligodendrocyte-specific expression ofNon-coding RNA research · 2024
    Article
  15. Article
  16. The Role of Long Intergenic Noncoding RNA in Fetal Development.International journal of molecular sciences · 2024
    Review
  17. Gene Expression Divergence inPlants (Basel, Switzerland) · 2024
    Article
  18. Review
  19. Article
  20. Review

75 more citing papers are in PubMed but not listed here.

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.

Anamaria NecsuleaLaboratory of Developmental Genomics, School of Life Sciences, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
Henrik Kaessmann1] Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland. [2] Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene expression changes may underlie much of phenotypic evolution. The development of high-throughput RNA sequencing protocols has opened the door to unprecedented large-scale and cross-species transcriptome comparisons by allowing accurate and sensitive assessments of transcript sequences and expression levels. Here, we review the initial wave of the new generation of comparative transcriptomic studies in mammals and vertebrate outgroup species in the context of earlier work. Together with various large-scale genomic and epigenomic data, these studies have unveiled commonalities and differences in the dynamics of gene expression evolution for various types of coding and non-coding genes across mammalian lineages, organs, developmental stages, chromosomes and sexes. They have also provided intriguing new clues to the regulatory basis and phenotypic implications of evolutionary gene expression changes.

Indexed as

EpigenomicsEvolution, MolecularGenomicsAnimalsGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansMammalsPhenotypeRNARNA, UntranslatedSequence Analysis, DNASpecies SpecificityTranscriptomeVertebratesRNARNA, Untranslated

Identifiers

PMID25297727

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.