Biology subjects

van der Sanden, B.

Publications and source records attributed to van der Sanden, B..

5 recordsLinked to original sources

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↗

bioRxiv2026

Oncolytic measles virus reprograms the tumor microenvironment in a vascularized mesothelioma-on-chip model

Pleural mesothelioma (PM) is a rare, aggressive cancer primarily caused by asbestos exposure and remains resistant to conventional chemotherapy. Although dual immune checkpoint inhibition (anti-PD-1/anti-CTLA-4) is now approved as first-line therapy, clinical benefit is limited to a small subset of patients, necessitating the need for alternative strategies. Oncolytic viruses (OVs) represent a promising approach as they selectively infect and lyse tumor cells while reprogramming the immunosuppressive tumor microenvironment (TME) into an immunostimulatory state. In PM, we previously showed that the attenuated Schwarz strain of measles virus (MV) oncolytic activity is mainly dependent on alterations in the type I interferon (IFN-I) pathway, rendering tumor cells sensitive to infection. Recently, we showed that monocytes/macrophages exposed to MV produce IFN-I, which protects PM cells via paracrine IFNAR signaling. This underscores the necessity of modeling the TME to accurately evaluate OV efficacy. Conventional rodent models are non-permissive to MV, and availability of fresh human PM tissue is scarce. We therefore developed a humanized 3D "vascularized mesothelioma-on-chip" (VMOC) model using microfluidic chips. It comprises two perfusable endothelial-lined parental vessels flanking a central secondary microvascular network (MVN), generated using human umbilical vein endothelial cells (HUVECs) embedded in fibrin and co-cultured alongside PM cells and primary human lung fibroblasts (hLFs). We characterized the integrity and functionality of the endothelial compartment as well as the cellular heterogeneity in VMOC using single-cell RNA sequencing. After administration of MV via the endothelial network, we observed infection and death of PM cells in addition to a strong activation of the type I interferon pathway and production of multiple inflammatory mediators. The VMOC model enables in vitro study of both MV infection and TME reprogramming, paving the way for a better understanding of the role of the TME in the response to treatment and for supporting the development of more personalized, targeted therapies for PM.

cancer biology↗

bioRxiv2024

TRGT-denovo: accurate detection of de novo tandem repeat mutations

MotivationIdentifying de novo tandem repeat (TR) mutations on a genome-wide scale is essential for understanding genetic variability and its implications in rare diseases. While PacBio HiFi sequencing data enhances the accessibility of the genomes TR regions for genotyping, simple de novo calling strategies often generate an excess of likely false positives, which can obscure true positive findings, particularly as the number of surveyed genomic regions increases. ResultsWe developed TRGT-denovo, a computational method designed to accurately identify all types of de novo TR mutations--including expansions, contractions, and compositional changes-- within family trios. TRGT-denovo directly interrogates read evidence, allowing for the detection of subtle variations often overlooked in variant call format (VCF) files. TRGT-denovo improves the precision and specificity of de novo mutation (DNM) identification, reducing the number of de novo candidates by an order of magnitude compared to genotype-based approaches. In our experiments involving eight rare disease trios previously studied TRGT-denovo correctly reclassified all false positive DNM candidates as true negatives. Using an expanded repeat catalog, it identified new candidates, of which 95% (19/20) were experimentally validated, demonstrating its effectiveness in minimizing likely false positives while maintaining high sensitivity for true discoveries. Availability and implementationBuilt in Rust, TRGT-denovo is available as source code and a pre-compiled Linux binary along with a user guide at: https://github.com/PacificBiosciences/trgt-denovo.

bioinformatics↗

bioRxiv2024

Optical genome mapping enables accurate repeat expansion testing

Short tandem repeats (STRs) are amongst the most abundant class of variations in human genomes and are meiotically and mitotically unstable which leads to expansions and contractions. STR expansions are frequently associated with genetic disorders, with the size of expansions often correlating with the severity and age of onset. Therefore, being able to accurately detect the total repeat expansion length and to identify potential somatic repeat instability is important. Current standard of care (SOC) diagnostic assays include laborious repeat-primed PCR-based tests as well as Southern blotting, which are unable to precisely determine long repeat expansions and/or require a separate set-up for each locus. Sequencing-based assays have proven their potential for the genome-wide detection of repeat expansions but have not yet replaced these diagnostic assays due to their inaccuracy to detect long repeat expansions (short-read sequencing) and their costs (long-read sequencing). Here, we tested whether optical genome mapping (OGM) can efficiently and accurately identify the STR length and assess the stability of known repeat expansions. We performed OGM for 85 samples with known clinically relevant repeat expansions in DMPK, CNBP and RFC1, causing myotonic dystrophy type 1 and 2 and cerebellar ataxia, neuropathy and vestibular areflexia syndrome (CANVAS), respectively. After performing OGM, we applied three different repeat expansion detection workflows, i.e. manual de novo assembly, local guided assembly (local-GA) and molecule distance script of which the latter two were developed as part of this study. The first two workflows estimated the repeat size for each of the two alleles, while the third workflow was used to detect potential somatic instability. The estimated repeat sizes were compared to the repeat sizes reported after the SOC and concordance between the results was determined. All except one known repeat expansions above the pathogenic repeat size threshold were detected by OGM, and allelic differences were distinguishable, either between wildtype and expanded alleles, or two expanded alleles for recessive cases. An apparent strength of OGM over current SOC methods was the more accurate length measurement, especially for very long repeat expansion alleles, with no upper size limit. In addition, OGM enabled the detection of somatic repeat instability, which was detected in 9/30 DMPK, 23/25 CNBP and 4/30 RFC1 samples, leveraging the analysis of intact, native DNA molecules. In conclusion, for tandem repeat expansions larger than [~]300 bp, OGM provides an efficient method to identify exact repeat lengths and somatic repeat instability with high confidence across multiple loci simultaneously, enabling the potential to provide a significantly improved and generic genome-wide assay for repeat expansion disorders.

genomics↗

bioRxiv2021

DeNovoCNN: A deep learning approach to de novo variant calling in next generation sequencing data

De novo mutations (DNMs) are an important cause of genetic disorders. The accurate identification of DNMs from sequencing data is therefore fundamental to rare disease research and diagnostics. Unfortunately, identifying reliable DNMs remains a major challenge due to sequence errors, uneven coverage, and mapping artifacts. Here, we developed a deep convolutional neural network (CNN) DNM caller (DeNovoCNN), that encodes the alignment of sequence reads for a trio as 160x164 resolution images. DeNovoCNN was trained on DNMs of 5,616 whole exome sequencing (WES) trios achieving total 96.74% recall and 96.55% precision on the test dataset. We find that DeNovoCNN has increased recall/sensitivity and precision compared to existing DNM calling approaches (GATK, DeNovoGear, DeepTrio, Samtools) based on the Genome in a Bottle reference dataset and independent WES and WGS trios. Validations of DNMs based on Sanger and PacBio HiFi sequencing confirm that DeNovoCNN outperforms existing methods. Most importantly, our results suggest that DeNovoCNN is likely robust against different exome sequencing and analyses approaches, thereby allowing the application on other datasets. DeNovoCNN is freely available as a Docker container and can be run on existing alignment (BAM/CRAM) and variant calling (VCF) files from WES and WGS without a need for variant recalling.

bioinformatics↗