{
  "abstract": "How a common genome generates diverse human cell types may depend less on distinct cis-regulatory vocabularies than on context-dependent use of a shared one. We have developed CNN-CR, an interpretable neural network that learns regulatory motifs while predicting gene expression across 116 human biosamples. Promoter regulation proves highly compressible: dozens of recurrent motif families retain most of the predictive information of much larger cell-type-specific vocabularies and generalize to cellular contexts excluded from their discovery. These motifs are conserved at their binding sites and enriched at fine-mapped regulatory variants. Cellular context acts at two levels: chromatin state gates which motif instances are available for regulatory use, whereas reader identity determines how accessible motifs are interpreted. ChIP-seq data reveal frequent shifts in reader occupancy across cell types, and genome-scale perturbations support corresponding context-dependent reader functions. Thus, regulatory diversity can emerge through differential access to and interpretation of a compact shared DNA vocabulary.",
  "abstract_shown": true,
  "affiliations": [
    "University of California, San Diego"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "name": "S. Shen"
    },
    {
      "affs": [
        0
      ],
      "name": "W. Wang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2k84abg6wg7qy.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.11.01.763377",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.11.01.763377v1.full",
  "id": "2k84abg6wg7qy",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.11.01.763377v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioinformatics"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.11.01.763377v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-01",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/2k84abg6wg7qy.ris",
  "sources": [
    {
      "first_seen": "2026-11-03T12:21:11Z",
      "native_id": "10.64898/2026.11.01.763377",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.11.01.763377v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "A compact motif vocabulary is differentially interpreted across human cell types",
  "title_text": "A compact motif vocabulary is differentially interpreted across human cell types",
  "type": "preprint",
  "updated_at": "2026-11-05T00:20:38Z",
  "url": "https://research.draconitic.com/paper/2k84abg6wg7qy",
  "venue": "bioRxiv",
  "versions": []
}