ReviewWiley interdisciplinary reviews. Developmental biology
Identifying transcriptional cis-regulatory modules in animal genomes.
Review in Wiley interdisciplinary reviews. Developmental biology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 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
43 citing papers in PubMed, 67 citations in OpenAlex.
- UnlockingNAR genomics and bioinformatics · 2026Article
- Deep learning enabled prediction of nuclear lamina-associated chromatin.Patterns (New York, N.Y.) · 2026Article
- Expanding the fly eye gene regulatory network: From Drosophila to the hoverfly Episyrphus balteatus.PLoS genetics · 2026Article
- EnhancerMatcher: comparing cell-type-specific enhancer activity of DNA sequences using deep convolutional neural networks and explainable AI.NAR genomics and bioinformatics · 2025Article
- Prediction of target genes and functional types of cis-regulatory modules in the human genome reveals their distinct properties.BMC biology · 2025Article
- Article
- Conserved and novel enhancers in the Aedes aegypti single-minded locus recapitulate embryonic ventral midline gene expression.PLoS genetics · 2024Article
- Article
- Evolution of Microglia.Advances in neurobiology · 2024Article
- Towards a comprehensive regulatory map of Mammalian Genomes.Research square · 2023Article
- A novel role for trithorax in the gene regulatory network for a rapidly evolving fruit fly pigmentation trait.PLoS genetics · 2023Article
- Bibliometric review of ATAC-Seq and its application in gene expression.Briefings in bioinformatics · 2022Review
- Global patterns of enhancer activity during sea urchin embryogenesis assessed by eRNA profiling.Genome research · 2021Article
- ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation.PLoS computational biology · 2021Article
- Identification of new Anopheles gambiae transcriptional enhancers using a cross-species prediction approach.Insect molecular biology · 2021Article
- Annotating the Insect Regulatory Genome.Insects · 2021Review
- Base-resolution models of transcription-factor binding reveal soft motif syntax.Nature genetics · 2021Article
- The mole genome reveals regulatory rearrangements associated with adaptive intersexuality.Science (New York, N.Y.) · 2020Article
- Speciation in North AmericanSystematic entomology · 2020Article
- Functional effects of variation in transcription factor binding highlight long-range gene regulation by epromoters.Nucleic acids research · 2020Article
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
Abstract
unlabelledGene expression is regulated through the activity of transcription factors (TFs) and chromatin-modifying proteins acting on specific DNA sequences, referred to as cis-regulatory elements. These include promoters, located at the transcription initiation sites of genes, and a variety of distal cis-regulatory modules (CRMs), the most common of which are transcriptional enhancers. Because regulated gene expression is fundamental to cell differentiation and acquisition of new cell fates, identifying, characterizing, and understanding the mechanisms of action of CRMs is critical for understanding development. CRM discovery has historically been challenging, as CRMs can be located far from the genes they regulate, have few readily identifiable sequence characteristics, and for many years were not amenable to high-throughput discovery methods. However, the recent availability of complete genome sequences and the development of next-generation sequencing methods have led to an explosion of both computational and empirical methods for CRM discovery in model and nonmodel organisms alike. Experimentally, CRMs can be identified through chromatin immunoprecipitation directed against TFs or histone post-translational modifications, identification of nucleosome-depleted 'open' chromatin regions, or sequencing-based high-throughput functional screening. Computational methods include comparative genomics, clustering of known or predicted TF-binding sites, and supervised machine-learning approaches trained on known CRMs. All of these methods have proven effective for CRM discovery, but each has its own considerations and limitations, and each is subject to a greater or lesser number of false-positive identifications. Experimental confirmation of predictions is essential, although shortcomings in current methods suggest that additional means of validation need to be developed. For further resources related to this article, please visit the WIREs website. CONFLICT OF INTEREST: The authors have declared no conflicts of interest for this article.
Indexed as
Identifiers
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.