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<p>Frameshift mutations, responsible for &gt;20% of Mendelian inherited diseases, pose substantial therapeutic challenges. Here we developed Template-Independent Genome Editing for Restoration (TIGER), a platform for the efficient and precise correction of frameshift mutations across various models. By identifying reproducible nucleotide-level factors that influence therapeutic efficacy across cells and tissues, we developed a scoring system for guide RNA (gRNA)–Cas9 outcomes. Approximately 75% of deletion and 50% of insertion mutations produced ≥30% in-frame products, sufficient for phenotypic restoration, with 38% and 65% achieving wild-type correction, respectively. To expand the applicability of TIGER across species and genome wide, we retrained the inDelphi algorithm to predict therapeutic gRNAs for single-nucleotide frameshifts. In a mouse model of deafness, delivery of <i>Sp</i>Cas9 and optimal gRNA via dual adeno-associated virus restored hearing thresholds to wild-type levels, with ~90% of in-frame edits being wild type. TIGER provides a robust and broadly applicable strategy for in vivo correction of inherited frameshift diseases.</p>

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Template-independent genome editing and restoration for correcting frameshift disorders

  • 期刊论文

  • 发表日期：

    2026年3月23日

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  • Shiwei Qiu,
  • Lian Liu,
  • Bin Xiang,
  • Ziqin Jin,
  • Yahong Li,
  • Dong Li,
  • Hanqing Hou,
  • Kuan Li,
  • Gege Wei,
  • Jiangping Xie,
  • Shang Li,
  • Shuang Liu,
  • Chunlai Chen,
  • Xin Liang,
  • Qianwen Sun,
  • Wei Xiong

摘要

Frameshift mutations, responsible for >20% of Mendelian inherited diseases, pose substantial therapeutic challenges. Here we developed Template-Independent Genome Editing for Restoration (TIGER), a platform for the efficient and precise correction of frameshift mutations across various models. By identifying reproducible nucleotide-level factors that influence therapeutic efficacy across cells and tissues, we developed a scoring system for guide RNA (gRNA)–Cas9 outcomes. Approximately 75% of deletion and 50% of insertion mutations produced ≥30% in-frame products, sufficient for phenotypic restoration, with 38% and 65% achieving wild-type correction, respectively. To expand the applicability of TIGER across species and genome wide, we retrained the inDelphi algorithm to predict therapeutic gRNAs for single-nucleotide frameshifts. In a mouse model of deafness, delivery of SpCas9 and optimal gRNA via dual adeno-associated virus restored hearing thresholds to wild-type levels, with ~90% of in-frame edits being wild type. TIGER provides a robust and broadly applicable strategy for in vivo correction of inherited frameshift diseases.