Comprehensive identification of pathogenic variants in retinoblastoma by long- and short-read sequencing
<p>Retinoblastoma (RB) is the most common intraocular malignancy in childhood. The causal variants in RB are mostly characterized by previously used short-read sequencing (SRS) analysis, which has technical limitations in identifying structural variants (SVs) and phasing information. Long-read sequencing (LRS) technology has significant advantages over SRS in detecting SVs, phased genetic variants, and methylation. In this study, we comprehensively characterized the genetic landscape of RB using combinatorial LRS and SRS of 16 RB tumors and 16 matched blood samples. We detected a total of 232 somatic SVs, with an average of 14.5 SVs per sample across the cohort. We identified 20 distinct pathogenic variants, including <span>three</span> novel small variants and <span>five</span> <span>somatic</span> SVs. Furthermore, our analysis shows that the vast majority (93.8%) of <em>RB1</em>-disrupted patients fit the two-hit hypothesis through diverse types, including the biallelic hypermethylated promoter as well as small and large compound heterozygous mutations which were missing in SRS analysis. By constructing the evolutionary history of all genetic variants, we reveal the evolution trends that <em>RB1</em> disruption early and followed by copy number changes, including amplifications of Chr2p, and deletions of Chr16q, during RB tumorigenesis. Altogether, we characterize the comprehensive genetic landscape of RB, providing novel insights into the genetic alterations and mechanisms contributing to RB initiation and development. Our work also establishes a framework to analyze genomic landscape of cancers based on LRS data. <br><br>We took IGV screenshots of SV and SNV/indels. The IGV naming conventions for SV is: sample name, chromosome 1, start, chromosome 2, end, SV type, SV length, SV breakpoint. The IGV naming convention for SNV/indels is: sample name, chromosome, position, reference allele, alternate allele.</p>
ShareScore
36/100
Overall dataset sharing score
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These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0