ArticleCell genomics2025
Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage.
Article in Cell genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- dubTAGs enable on-demand stabilization for tunable and reversible control of endogenous protein levels.bioRxiv : the preprint server for biology · 2026Article
- Motif-Cluster: Motif driven prioritization of transcription factor binding clusters.PLoS computational biology · 2026Article
- Lentiviral single-cell MPRA of synthetic enhancers reveals motif affinity-based encoding of cell state specificity.Genome biology · 2026Article
- Redefining cellular reprogramming with advanced genomic technologies.Nature reviews. Genetics · 2026Review
- Transposable Elements Seed Transcription Factor Binding Sites to Sequence-Specific Double-Stranded DNA Binding TF Networks Contributing to Governance of Primate Brain Evolution.Journal of molecular evolution · 2026Article
- Parameter-efficient fine-tuning enables scalable transfer of regulatory sequence models to novel contexts.Genome biology · 2026Article
- Review
- The craniofacial shape of modern humans embodies genomic signatures of evolution, diversity, and clinical conditions.bioRxiv : the preprint server for biology · 2026Article
- Cooperation of transposable elements to endow global networks of initiators of hybrid assembly pathways of endogenous multiprotein complexes.Frontiers in cellular and infection microbiology · 2026Article
- Synthetic tunable promoters for flexible control of multi-gene expression in mammalian cells.Journal of advanced research · 2025Article
- Widespread low-affinity motifs enhance chromatin accessibility and regulatory potential in mESCs.bioRxiv : the preprint server for biology · 2025Article
- Predicting gene expression from DNA sequence using deep learning models.Nature reviews. Genetics · 2025Review
- Transcriptional regulation as a dose-dependent process: insights from transcription factor tuning.Open biology · 2025Review
- An automated ATAC-seq method reveals sequence determinants of transcription factor dose response in the open chromatin.bioRxiv : the preprint server for biology · 2025Article
- Post-translational modification of transcription factors: perspectives in vascular medicine.Cell death & disease · 2025Review
- Article
- Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage.Cell genomics · 2025Article
- ChromBPNet: bias factorized, base-resolution deep learning models of chromatin accessibility reveal cis-regulatory sequence syntax, transcription factor footprints and regulatory variants.bioRxiv : the preprint server for biology · 2025Article
- Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage.bioRxiv : the preprint server for biology · 2024Article
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Authors and funding
7 authors.
Funding
Abstract
Deep learning models have advanced our ability to predict cell-type-specific chromatin patterns from transcription factor (TF) binding motifs, but their application to perturbed contexts remains limited. We applied transfer learning to predict how concentrations of the dosage-sensitive TFs TWIST1 and SOX9 affect regulatory element (RE) chromatin accessibility in facial progenitor cells, achieving near-experimental accuracy. High-affinity motifs that allow for heterotypic TF co-binding and are concentrated at the center of REs buffer against quantitative changes in TF dosage and predict unperturbed accessibility. Conversely, low-affinity or homotypic binding motifs distributed throughout REs drive sensitive responses with minimal impact on unperturbed accessibility. Both buffering and sensitizing features display purifying selection signatures. We validated these sequence features through reporter assays and demonstrated that TF-nucleosome competition can explain low-affinity motifs' sensitizing effects. This combination of transfer learning and quantitative chromatin response measurements provides a novel approach for uncovering additional layers of the cis-regulatory code.
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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 Socratic graph.