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<p>Inherited retinal dystrophies (IRDs) are a genetically diverse group of vision loss disorders with over 360 implicated genes. However, 30-50% of cases remain unresolved after panel-based clinical testing and may benefit from exome or genome sequencing for a genetic diagnosis. To manage the extensive and analytically demanding datasets generated by genome sequencing, we developed ReDGAP (Retinal Degeneration Genome Analysis Pipeline), a phenotype-guided, semi-automated genome analysis pipeline that integrates clinical phenotyping with flexible variant scoring to prioritize variants of interest (<a href="https://github.com/vincentlab-la/ReDGAP">https://github.com/vincentlab-la/ReDGAP</a>). The pipeline supports the joint analysis of multiple variant classes, using an evidence-weighted scoring system informed by in silico predictors. Validation in eleven previously solved IRD cases achieved a 100% re-identification rate. Application to five unsolved cases yielded diagnoses in four (80%), including intronic variants in <i>CRB1</i> and <i>HGSNAT</i>, a tandem duplication in <i>OAT</i>, and a 5′UTR deletion affecting a retina-specific promoter of <i>RPGRIP1</i>. Functional validation confirmed transcript-level disruptions in three variants, while computational analysis demonstrated regulatory impact in the fourth. Integrating phenotypic data with broad variant analysis offers a tailored model for improving IRD diagnostics, enabling timely molecular diagnoses and informing eligibility for emerging gene-targeted therapies. This positions ReDGAP as a tailored, clinically relevant model for investigating rare diseases within the evolving landscape of precision health.</p>

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A novel phenotype-guided genome analysis pipeline for variant discovery

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月28日

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  • Layla Ahmed,
  • Erika Tavares,
  • Janice Min Li,
  • Kashif Ahmed,
  • Maanik Mehta,
  • Christabel Eileen,
  • Genevieve Ah-Sen,
  • Rahma Osman,
  • Kit Green-Sanderson,
  • Anna Dvaladze,
  • Graeme Nimmo,
  • Ashish R. Deshwar,
  • Tara Paton,
  • Guillermo Casallo,
  • Christian R. Marshall,
  • Elise Heon,
  • Ajoy Vincent

摘要

Inherited retinal dystrophies (IRDs) are a genetically diverse group of vision loss disorders with over 360 implicated genes. However, 30-50% of cases remain unresolved after panel-based clinical testing and may benefit from exome or genome sequencing for a genetic diagnosis. To manage the extensive and analytically demanding datasets generated by genome sequencing, we developed ReDGAP (Retinal Degeneration Genome Analysis Pipeline), a phenotype-guided, semi-automated genome analysis pipeline that integrates clinical phenotyping with flexible variant scoring to prioritize variants of interest (https://github.com/vincentlab-la/ReDGAP). The pipeline supports the joint analysis of multiple variant classes, using an evidence-weighted scoring system informed by in silico predictors. Validation in eleven previously solved IRD cases achieved a 100% re-identification rate. Application to five unsolved cases yielded diagnoses in four (80%), including intronic variants in CRB1 and HGSNAT, a tandem duplication in OAT, and a 5′UTR deletion affecting a retina-specific promoter of RPGRIP1. Functional validation confirmed transcript-level disruptions in three variants, while computational analysis demonstrated regulatory impact in the fourth. Integrating phenotypic data with broad variant analysis offers a tailored model for improving IRD diagnostics, enabling timely molecular diagnoses and informing eligibility for emerging gene-targeted therapies. This positions ReDGAP as a tailored, clinically relevant model for investigating rare diseases within the evolving landscape of precision health.