tWhEEL: a transcript-aware workflow for quantifying CRISPR knockout feasibility using transcriptome assembly
- 1Hiroshima University
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.
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BibTeX
@misc{nakamae2026twheel,
title = {{tWhEEL: a transcript-aware workflow for quantifying CRISPR knockout feasibility using transcriptome assembly}},
author = {K. Nakamae and H. Bono},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.27.762389},
url = {https://www.biorxiv.org/content/10.64898/2026.10.27.762389v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - tWhEEL: a transcript-aware workflow for quantifying CRISPR knockout feasibility using transcriptome assembly
AU - K. Nakamae
AU - H. Bono
PY - 2026
DA - 2026/10/27
PB - bioRxiv
DO - 10.64898/2026.10.27.762389
UR - https://www.biorxiv.org/content/10.64898/2026.10.27.762389v1
AB - 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.
ER -