{
  "abstract": "Steady-state molecular profiles incompletely capture the regulatory programs through which genetic variation influences complex disease, particularly programs that emerge only when cells are perturbed. Here, we introduce Perturbscape, a computational framework that learns multiscale gene programs for individual perturbations in a CRISPR Perturb-seq screen using linear and nonlinear contrastive approaches alongside complementary program-learning methods, and integrates them with human genetics to prioritize disease-relevant genes, perturbations and downstream regulatory pathways. Across 15,859 perturbation-by-context profiles from 7 Perturb-seq systems and 53 complex diseases and traits (mean GWAS N=291K), perturbation-induced programs showed up to 4.3-fold higher heritability informativeness than analogous steady-state multi-tissue gene prioritization, and retained significant conditional heritability informativeness across all 34 matched cell system-trait comparisons after accounting for steady-state prioritization. Preserving perturbation-specific programs further yielded 2.5-5.3-fold higher trait relevance scores than programs derived from control cells, pooled perturbations or differential-expression summaries. In K562, Perturbscape-prioritized genes showed stronger enrichment for rare-variant burden genes than steady-state prioritization and were supported by orthogonal enhancer CRISPRi screens. In HepG2, LDL cholesterol-associated perturbation-induced programs specifically revealed statin-responsive pathways not significantly enriched by steady-state PoPS prioritization, supported by pharmacological transcriptional responses and population plasma proteomics. Perturbscape also recovered blood-related trait-conditioned trans-regulatory relationships that were specifically supported by population trans-eQTLs in IFN-gamma-stimulated monocytes (OR = 1.30, P=1.6e-05). Perturbscape further revealed developmental-stage-specific convergence between monogenic diabetes regulators and polygenic T2D risk during pancreatic islet differentiation, and neuronal-subclass-specific autism-associated regulatory programs in vivo. Together, these findings establish perturbation-induced gene programs as a complementary layer of disease-relevant regulatory information, revealing genetically informative pathways and context-specific regulatory relationships incompletely represented by steady-state molecular atlases.",
  "abstract_shown": true,
  "affiliations": [
    "Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Physiology, Biophysics and Syst"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 11,
  "authors": [
    {
      "name": "B. Turhan"
    },
    {
      "name": "H. Lee"
    },
    {
      "name": "D. Liu"
    },
    {
      "name": "A. Le"
    },
    {
      "name": "A. Ghosh"
    },
    {
      "name": "D. Nandi"
    },
    {
      "name": "R. Mazumder"
    },
    {
      "name": "J. M. Engreitz"
    },
    {
      "name": "X. Jin"
    },
    {
      "name": "D. Huangfu"
    },
    {
      "affs": [
        0
      ],
      "name": "K. K. Dey"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7aeqrk4gndnv7.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.11.03.762080",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.11.03.762080v1.full",
  "id": "7aeqrk4gndnv7",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.11.03.762080v1",
  "language": null,
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "genetics"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.11.03.762080v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-03",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7aeqrk4gndnv7.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T12:21:08Z",
      "native_id": "10.64898/2026.11.03.762080",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.11.03.762080v2"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:genetics",
      "subfield": "genetics-genomics"
    }
  ],
  "title": "Perturbation-induced gene programs map the hidden regulatory architecture of complex diseases",
  "title_text": "Perturbation-induced gene programs map the hidden regulatory architecture of complex diseases",
  "type": "preprint",
  "updated_at": "2026-11-06T00:21:48Z",
  "url": "https://research.draconitic.com/paper/7aeqrk4gndnv7",
  "venue": "bioRxiv",
  "versions": []
}