Timmermans, R. | Search bioRxiv

bioRxiv2026

Integrative optical genome mapping and long-read sequencing resolve constitutional complex rearrangements at nucleotide resolution

Complex rearrangements are one of the rarest types of structural variants (SVs) and can be divided into two categories: complex chromosomal rearrangements (CCRs) and complex genomic rearrangements (CGRs). CCRs include structural rearrangements that present at least three breakpoints and show exchange of genetic material between more than two chromosomes and CGRs are rearrangements that present more than one junction and/or more than one SV in cis. They are usually formed by one of the chromoanagenesis mechanisms, where a massive disruptive cellular event leads to multiple structural rearrangements. Classical cytogenomic techniques have been commonly applied for their characterization, but methodologies that involve longer DNA molecules, namely optical genome mapping (OGM) and long-read genome sequencing (lrGS), present a considerably higher SV detection resolution, revealing more details about the rearrangements, including precise breakpoint location. Here, we describe six patients with complex rearrangements investigated through a combination of different techniques: karyotyping, chromosomal microarray, and OGM were performed to characterize the rearrangements. Subsequently, lrGS was used to further resolve the alterations, refine their breakpoints' location, and sequence their junction points. Three patients presented CCRs involving three, four, and six chromosomes, while three exhibited CGRs involving one different chromosome each, providing a variety of complex SVs to show the importance of each technique and their combination in rearrangement resolution. In total, the complex rearrangements presented 127 breakpoints, 66 junction points and involved 14 of the 24 chromosomes. Higher-resolution techniques revealed additional complexity in all cases. Despite the advances provided by OGM and lrGS, conventional karyotyping remained indispensable for complete rearrangement resolution. In two patients, the findings supported a novel mechanism combining features of the different chromoanagenesis processes. Furthermore, evidence of inherited alterations was identified, and the comprehensive characterization of the rearrangements enabled more accurate genotype-phenotype correlations. Our findings indicate that an integrated approach combining karyotyping, OGM, and lrGS can completely resolve SVs, including complex rearrangements.

genomics↗

bioRxiv2024

Pushing the limits of single molecule transcript sequencing to uncover the largest disease-associated transcript isoforms in the human neural retina

Sequencing technologies have long limited the comprehensive investigation of large transcripts associated with inherited retinal diseases (IRDs) like Usher syndrome, which involves 11 associated genes with transcripts up to 19.6 kb. To address this, we used PacBio long-read mRNA isoform sequencing (Iso-Seq) following standard library preparation and an optimized workflow to enrich for long transcripts in the human neural retina. While our workflow achieved sequencing of transcripts up to 15 kb, this was insufficient for Usher syndrome-associated genes USH2A and ADGRV1, with transcripts of 18.9 kb and 19.6 kb, respectively. To overcome this, we employed the Samplix Xdrop System for indirect target enrichment of cDNA, a technique typically used for genomic DNA capture. This method facilitated the successful capture and sequencing of ADGRV1 transcripts as well as the full-length 18.9 kb USH2A transcripts. By combining algorithmic analysis with detailed manual curation of sequenced reads, we identified novel isoforms and alternative splicing events across the 11 Usher syndrome-associated genes, with implications for diagnostics and therapy development. Our findings demonstrate the Xdrop systems adaptability for cDNA capture and the advantages of integrating computational and manual transcript analyses. The full neural retina sequencing dataset is available via EGA under identifier EGAD50000000720.

genetics↗