{
  "abstract": "Cardiomyocyte hypertrophy is a leading clinical predictor of heart failure, yet newly identified candidate genes often remain disconnected from the signaling mechanisms that govern cardiomyocyte growth. We developed a computational-experimental pipeline that integrates genome-scale mouse knockout phenotypes with a logic-based differential equation model of hypertrophic signaling. Among 9,605 genes evaluated by the International Mouse Phenotyping Consortium, 939 knockout lines induced abnormal heart morphology. Directional curation of hypertrophy-related sub-phenotypes followed by interaction-based network expansion mapped 37 genes to the signaling model. Virtual knockdown screening identified five candidates with concordant in vivo and in silico effects: LRIG1 and CBL as predicted negative regulators and VAV2, RASA1, and LEPR as predicted positive regulators. Mechanistic subnetwork analysis linked these candidates to distinct receptor-proximal, Ras, PI3K-AKT, and MAPK signaling axes. In neonatal rat cardiomyocytes, siRNA-mediated depletion of VAV2, RASA1, or LEPR reduced phenylephrine-induced cell growth, supporting their cell-autonomous contribution to hypertrophy. Quantitative phenotyping further validated the predicted decreased cardiac hypertrophy for VAV2 and LEPR knockouts but identified potential age-dependent mechanisms for RASA1 knockout. Overall, this study establishes the application of network models to translate from in vivo phenotypic screens into pathway mechanisms.",
  "abstract_shown": true,
  "affiliations": [
    "University of Virginia"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "name": "L. D. Watkins"
    },
    {
      "affs": [
        0
      ],
      "name": "J. J. Saucerman"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4yf9cwym1ba0f.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.24.754086",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.24.754086v1.full",
  "id": "4yf9cwym1ba0f",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.24.754086v1",
  "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",
      "systems biology"
    ],
    [
      "openalex",
      "1312|Gene Regulatory Network Analysis"
    ]
  ],
  "openalex": "W7214733374",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.24.754086v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-24",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/4yf9cwym1ba0f.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:17Z",
      "native_id": "10.64898/2026.09.24.754086",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.24.754086v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:systems biology",
      "subfield": "systems-synthetic"
    }
  ],
  "title": "Mapping a genome-scale in vivo knockout screen to a mechanistic network model identifies VAV2, RASA1, and LEPR as regulators of cardiomyocyte hypertrophy",
  "title_text": "Mapping a genome-scale in vivo knockout screen to a mechanistic network model identifies VAV2, RASA1, and LEPR as regulators of cardiomyocyte hypertrophy",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:17Z",
  "url": "https://research.draconitic.com/paper/4yf9cwym1ba0f",
  "venue": "bioRxiv",
  "versions": []
}