Evidence map›Paper›PMID 33689769›Full record

ReviewDevelopmental cell2021

Enhancer grammar in development, evolution, and disease: dependencies and interplay.

Granton A Jindal, Emma K Farley

Abstract readReview
In one paragraph

Review in Developmental cell, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 94 papers.

0numbers the graph read from it
0cells of the map it votes in
94citing 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

94 citing papers in PubMed.

  1. Review
  2. UnlockingNAR genomics and bioinformatics · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
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  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article

34 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.

Granton A JindalDivision of Cardiology, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA; Division of Biological Sciences, Section of Molecular Biology, University of California San Diego, La Jolla, CA 92093, USA.
Emma K FarleyDivision of Cardiology, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA; Division of Biological Sciences, Section of Molecular Biology, University of California San Diego, La Jolla, CA 92093, USA. Electronic address: efarley@ucsd.edu.

Funding

Training In Cardiovascular Physiology & PharmacologyT32HL007444 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Ju Chen, Robert Scott Ross · 1985 to 2026
$11.1M
Deciphering the regulatory principles governing enhancer specificityDP2HG010013 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FARLEY, EMMA KIRSTEN · 2017 to 2021
$2.5M
American Heart Association-American Stroke Association 18POST34030077NHGRI NIH HHS DP2 HG010013NHLBI NIH HHS T32 HL007444
6 · The paper itself

Abstract

Each language has standard books describing that language's grammatical rules. Biologists have searched for similar, albeit more complex, principles relating enhancer sequence to gene expression. Here, we review the literature on enhancer grammar. We introduce dependency grammar, a model where enhancers encode information based on dependencies between enhancer features shaped by mechanistic, evolutionary, and biological constraints. Classifying enhancers based on the types of dependencies may identify unifying principles relating enhancer sequence to gene expression. Such rules would allow us to read the instructions for development within genomes and pinpoint causal enhancer variants underlying disease and evolutionary changes.

Indexed as

Enhancer Elements, GeneticEvolution, MolecularGene Expression Regulation, DevelopmentalDiseaseHumans

Identifiers

PMID33689769
PMCPMC8462829

What Socratic holds

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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 Socratic graph.