Evidence map›Paper›PMID 40634599›Full record

ReviewNature reviews. Genetics2025

The evolutionary foundations of transcriptional regulation in animals.

Maxwell C Coyle, Nicole King

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. bioRxiv : the preprint server for biology · 2026
    Article
  4. Review
  5. Article
  6. 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.

Maxwell C CoyleDepartment of Molecular and Cell Biology and Howard Hughes Medical Institute, University of California, Berkeley, CA, USA. mcoyle@fas.harvard.edu.ORCID http://orcid.org/0009-0009-8874-4699
Nicole KingDepartment of Molecular and Cell Biology and Howard Hughes Medical Institute, University of California, Berkeley, CA, USA.ORCID http://orcid.org/0000-0002-6409-1111

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of a single-celled zygote into a complex, multicellular animal is directed by transcription factors and regulatory RNAs that coordinate spatio-temporal gene expression patterns. Given the morphological complexity of animals, some prior work has hypothesized that the origin of animals required the evolution of unique and markedly complex transcriptional regulatory mechanisms. Such postulated animal innovations include the evolution of greater numbers of transcription factors, new transcription factor families, distal enhancers and the emergence of long non-coding RNAs. Here, we revisit these explanations in light of new genomic and functional data from diverse early-branching animals and close relatives of animals, which provide essential phylogenetic context for reconstructing the origin of animals. These experimental models also offer examples of how some animal developmental pathways were built from core mechanisms inherited from their protistan ancestors. These new data provide fresh perspectives on whether animal origins entailed fundamental innovations in transcriptional regulation or whether, alternatively, a gradual accumulation of smaller changes sufficed to generate the complex developmental and cell differentiation mechanisms of early animals.

Indexed as

Biological EvolutionEvolution, MolecularGene Expression RegulationGene Expression Regulation, DevelopmentalTranscription, GeneticAnimalsPhylogenyRNA, Long NoncodingTranscription FactorsRNA, Long NoncodingTranscription Factors

Identifiers

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.