Scholarlink

<p>Splice-disrupting variants are estimated to account for one-third of disease-causing variants, yet many remain underrepresented in clinical databases due to limitations in detecting splicing changes beyond canonical splice sites. Short-read RNA sequencing (RNA-seq) has proved to be a valuable complement in clinical practice to address this gap, however, the added value of long-read RNA-seq is unclear. We evaluated the potential of PacBio long-read RNA-seq to detect pathogenic splicing events in rare disorders, comparing its performance to short-read RNA-seq. Participants from the UK (<i>n</i> = 23) and the Netherlands (<i>n</i> = 2) with suspected splice-altering variants underwent long-read RNA-seq following the Kinnex full-length RNA protocol. HiFi reads from the Revio instrument were processed using the Read Segmentation and Iso-Seq workflow and then classified and filtered using Pigeon. Detection of disease genes was comparable with short reads, with fibroblast capturing more transcripts overall. Novel isoforms accounted for ~14% of detected transcripts in both tissues, increasing following cycloheximide treatment in fibroblasts and decreasing following globin depletion in blood. Transcript abundance estimates showed strong concordance between short- and long-read platforms (Pearson <i>r</i> = 0.86 and 0.61 in blood and fibroblasts, respectively). LRS captured 21 confirmed known events, and revealed additional transcript-level effects in eight cases. This included intron retention, multiple exon skipping, leaky splicing, variant phasing, and isoform switching. These results demonstrate that long-read RNA-seq enhances detection and interpretation of clinically relevant splicing events, supporting its integration into diagnostic workflows for rare diseases.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

HiFi long-read RNA sequencing enhances clinical diagnostics in rare disorders

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月10日

查看全文
  • Carolina Jaramillo Oquendo,
  • Federico Ferraro,
  • Htoo A. Wai,
  • Heather Ferrao,
  • Herma van der Linde,
  • Evita Karelioti,
  • Liz Tseng,
  • Harsharan Dhillon,
  • Sam Holt,
  • David J. Bunyan,
  • Laura Donker Kaat,
  • Marieke van Dooren,
  • Jeff Zhou,
  • Sarah Ennis,
  • John W. Holloway,
  • Tjakko J. van Ham,
  • Diana Baralle

摘要

Splice-disrupting variants are estimated to account for one-third of disease-causing variants, yet many remain underrepresented in clinical databases due to limitations in detecting splicing changes beyond canonical splice sites. Short-read RNA sequencing (RNA-seq) has proved to be a valuable complement in clinical practice to address this gap, however, the added value of long-read RNA-seq is unclear. We evaluated the potential of PacBio long-read RNA-seq to detect pathogenic splicing events in rare disorders, comparing its performance to short-read RNA-seq. Participants from the UK (n = 23) and the Netherlands (n = 2) with suspected splice-altering variants underwent long-read RNA-seq following the Kinnex full-length RNA protocol. HiFi reads from the Revio instrument were processed using the Read Segmentation and Iso-Seq workflow and then classified and filtered using Pigeon. Detection of disease genes was comparable with short reads, with fibroblast capturing more transcripts overall. Novel isoforms accounted for ~14% of detected transcripts in both tissues, increasing following cycloheximide treatment in fibroblasts and decreasing following globin depletion in blood. Transcript abundance estimates showed strong concordance between short- and long-read platforms (Pearson r = 0.86 and 0.61 in blood and fibroblasts, respectively). LRS captured 21 confirmed known events, and revealed additional transcript-level effects in eight cases. This included intron retention, multiple exon skipping, leaky splicing, variant phasing, and isoform switching. These results demonstrate that long-read RNA-seq enhances detection and interpretation of clinically relevant splicing events, supporting its integration into diagnostic workflows for rare diseases.