{
  "abstract": "Gene redundancy can complicate loss-of-function experiments (knockout), and its extent varies among organisms and biological functions. Relating variation in gene redundancy to the availability of genome-editing targets can help researchers select tractable biological functions and experimental organisms. Here, we present the transcript-aware Whole-genomic Evaluation for Editing Locus (tWhEEL), a pipeline that infers redundancy in silico from transcript information and cross-references it with specific guide RNA designs. tWhEEL integrates CRISPR-Cas9 guide design with Gene Ontology (GO) and pathway annotations to compute a knockout feasibility index (KFI) for individual genes and functional categories. Interactive HTML reports link GO-associated KFI and pathway-associated KFI summaries to the contributing groups, genes, and guide candidates with links to QuickGO or WikiPathways. By linking sequence-level guide candidates to functional-level targetability, tWhEEL can support the selection of biological functions and organisms for reverse-genetic experiments. Applications to model and nonmodel datasets revealed distinct targetability profiles, including high full targetability in yeast and query-protein-set dependence in zebrafish. A zebrafish Fanconi anemia case study recovered 14 of 19 published target-site designs. By connecting sequence-level guide candidates with function-level experimental planning, tWhEEL provides a framework for comparing reverse genetic tractability and prioritizing biological functions and organisms for further study.",
  "abstract_shown": true,
  "affiliations": [
    "Hiroshima University"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "name": "K. Nakamae"
    },
    {
      "affs": [
        0
      ],
      "name": "H. Bono"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cwg7tfvv94e6j.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.27.762389",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.27.762389v1.full",
  "id": "cwg7tfvv94e6j",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.27.762389v1",
  "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/10.64898/2026.10.27.762389v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-27",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/cwg7tfvv94e6j.ris",
  "sources": [
    {
      "first_seen": "2026-11-01T12:20:58Z",
      "native_id": "10.64898/2026.10.27.762389",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.27.762389v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "tWhEEL: a transcript-aware workflow for quantifying CRISPR knockout feasibility using transcriptome assembly",
  "title_text": "tWhEEL: a transcript-aware workflow for quantifying CRISPR knockout feasibility using transcriptome assembly",
  "type": "preprint",
  "updated_at": "2026-11-02T00:21:21Z",
  "url": "https://research.draconitic.com/paper/cwg7tfvv94e6j",
  "venue": "bioRxiv",
  "versions": []
}