ArticlePLoS computational biology2018
Prediction of gene regulatory enhancers across species reveals evolutionarily conserved sequence properties.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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59 citing papers in PubMed, 105 citations in OpenAlex.
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- Cross-species prediction reveals chromatin regions with increased accessibility in humans.Science advances · 2026Article
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- In silico genome transplants and the cis-regulatory basis of biodiversity.Trends in genetics : TIG · 2026Review
- Deciphering the regulatory landscape of enhancer RNAs in health and disease.Signal transduction and targeted therapy · 2026Review
- Cross-species prediction of histone modifications in plants via deep learning.Genome biology · 2026Article
- EnhancerMatcher: comparing cell-type-specific enhancer activity of DNA sequences using deep convolutional neural networks and explainable AI.NAR genomics and bioinformatics · 2025Article
- Motif-based models accurately predict cell type-specific distal regulatory elements.Nature communications · 2025Article
- Challenges in Predicting Chromatin Accessibility Differences between Species.bioRxiv : the preprint server for biology · 2025Article
- Predicting gene expression from DNA sequence using deep learning models.Nature reviews. Genetics · 2025Review
- "Frustratingly easy" domain adaptation for cross-species transcription factor binding prediction.bioRxiv : the preprint server for biology · 2025Article
- Mediator complex: update of key insights into transcriptional regulation of ancestral framework and its role in cardiovascular diseases.European journal of medical research · 2025Review
- Inhibition of triglyceride metabolism-associated enhancers alters lipid deposition during adipocyte differentiation.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025Article
- Characterization of Single-Cell Cis-regulatory Elements Informs Implications for Cell Differentiation.Genome biology and evolution · 2024Article
- Cross-Species Prediction of Transcription Factor Binding by Adversarial Training of a Novel Nucleotide-Level Deep Neural Network.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Gapped-kmer sequence modeling robustly identifies regulatory vocabularies and distal enhancers conserved between evolutionarily distant mammals.Nature communications · 2024Article
- Large-scale genomic analysis of the domestic dog informs biological discovery.Genome research · 2024Review
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3 authors at 1 institution in 1 country.
Funding
Abstract
Genomic regions with gene regulatory enhancer activity turnover rapidly across mammals. In contrast, gene expression patterns and transcription factor binding preferences are largely conserved between mammalian species. Based on this conservation, we hypothesized that enhancers active in different mammals would exhibit conserved sequence patterns in spite of their different genomic locations. To investigate this hypothesis, we evaluated the extent to which sequence patterns that are predictive of enhancers in one species are predictive of enhancers in other mammalian species by training and testing two types of machine learning models. We trained support vector machine (SVM) and convolutional neural network (CNN) classifiers to distinguish enhancers defined by histone marks from the genomic background based on DNA sequence patterns in human, macaque, mouse, dog, cow, and opossum. The classifiers accurately identified many adult liver, developing limb, and developing brain enhancers, and the CNNs outperformed the SVMs. Furthermore, classifiers trained in one species and tested in another performed nearly as well as classifiers trained and tested on the same species. We observed similar cross-species conservation when applying the models to human and mouse enhancers validated in transgenic assays. This indicates that many short sequence patterns predictive of enhancers are largely conserved. The sequence patterns most predictive of enhancers in each species matched the binding motifs for a common set of TFs enriched for expression in relevant tissues, supporting the biological relevance of the learned features. Thus, despite the rapid change of active enhancer locations between mammals, cross-species enhancer prediction is often possible. Our results suggest that short sequence patterns encoding enhancer activity have been maintained across more than 180 million years of mammalian evolution.
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