Biology subjects

van Roosmalen, M. J.

Publications and source records attributed to van Roosmalen, M. J..

7 recordsLinked to original sources

bioRxiv2026

Somatic variant detection using an individual-specific pangenome reference: a case study of a pediatric acute myeloid leukemia patient

Background: Reference bias can cause false or missed somatic variant calls, also in clinically relevant genes. Pangenomes aim to reduce this bias, but evidence of their diagnostic benefit is lacking. We tested how an individual-specific pangenome affects somatic variant calling in bulk samples and single cells. Results: We built an individual-specific pangenome from Nanopore assemblies of normal hematopoietic stem and progenitor cells of a child with acute myeloid leukemia. We aligned short-read whole-genome sequencing data of bulk and single-cell samples to hg38 and to the pangenome, and called somatic variants with standard downstream tools after anchoring pangenome alignments to hg38. Single nucleotide variants were mostly shared, while indel calls unique to the pangenome were fewer than those unique to hg38, mostly in repeats. Both approaches detected NUP98-NSD1 and FLT3 internal tandem duplication (FLT3-ITD) drivers. The pangenome-based phylogeny showed more parallel branching in comparison to hg38-based tree. The pangenome removed three false-positive PRSS1 variants and, in single cells, frameshift insertion calls next to polyG and polyC repeats. However, surjection to hg38 coordinates split a WT1 driver indel call in a low-complexity region into two separate calls. Validation showed that all somatic structural variant calls, except NUP98-NSD1 and FLT3-ITD, were germline variants or artifacts. Conclusions: The use of individual-specific pangenome led to fewer false-positive indel and driver calls, mainly in repeats and single cells, and changed the branching of the inferred phylogeny. However, surjection artifacts and false-positive somatic structural variants show that pangenome-based results need read-level inspection and validation before clinical use.

genomics↗

bioRxiv2025

Single-cell whole-genome sequencing reveals convergent evolution in Burkitt lymphoma

Burkitt lymphoma (BL) carries multiple oncogenic drivers yet arises predominantly in children, whose normal cells harbour few age-related mutations. To investigate this paradox, we sought to define the sequence and timing of mutational drivers underlying BL development. Here, we analysed single-cell whole-genome sequencing (WGS) data of 250 paired normal and malignant B-cells from BL patients and integrated this data with 21 bulk WGS samples and an existing dataset of 157 clonally expanded B-cells from healthy individuals. Phylogenetic reconstruction revealed an accelerated accumulation of mutations following the emergence of the most recent common ancestor, leading to the early establishment of extensive genetic intra-tumoral heterogeneity. We further provide evidence that convergent evolution shapes this diversity at both the point mutation- and copy number variation-levels. This in-depth characterisation further establishes BL as a paradigmatic model of tumorigenesis with implications for therapeutic intervention.

cancer biology↗

bioRxiv2024

Direct detection of 8-oxo-dG using nanopore sequencing

Genomic DNA is constantly subjected to oxidative damage, which is thought to be one of the major drivers of cancer and age-dependent decline. The most prominent consequence is the modification of guanine into 8-hydroxyguanine (8-oxo-dG), which has important mutagenic potential and plays a role in methylation-mediated gene regulation. Methods to simultaneously detect and quantify 8-oxo-dG within its genomic context have been lacking; mainly because these methods rely on indirect detection or are based on hydrolysis of the DNA. Nanopore sequencing has been deployed for the direct detection of base-modifications like cytosine methylation during sequencing. However, currently there is no model to detect 8-oxo-dG by nanopore sequencing due to the lack of training data. Here, we developed a strategy based on synthetic oligos to create long DNA molecules with context variability for effective deep learning and nanopore sequencing. Moreover, we showcase a training approach suitable to deal with the extreme scarceness of 8-oxo-dG compared to canonical G to enable specific 8-oxo-dG detection. Applied to an inducible tissue culture system for oxidative DNA damage, our approach reveals variable 8-oxo-dG distribution across the genome, a dissimilar context pattern to C>A mutations, and concurrent 5-mC depletion within a 2-kilobase window surrounding 8-oxo-dG sites. These findings not only underscore the potential of nanopore sequencing in epigenetic research, but also shed light on 8-oxo-dGs role in genomic regulation. By simultaneously measuring 5-mC and 8-oxo-dG at single molecule resolution, our study provides insights into the functional interplay between these DNA modifications. Moreover, our approach using synthetic oligos to generate a ground truth from machine learning modification calling could be applied to any other DNA modification. Overall, our work contributes to advancing the field of epigenetics and highlights nanopore sequencing as a powerful tool for studying DNA modifications.

bioinformatics↗

bioRxiv2023

Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole genome sequencing (WGS), but still generate hundreds of artefacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolkit (PTATO), to accurately detect single base substitutions, small insertions and deletions (indels) and structural variants in PTA-based WGS data. PTATO includes a machine learning approach to distinguish PTA-artefacts from true mutations with high sensitivity (up to 90% for base substitution and 95% for indels), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that many hematopoietic stem and progenitor cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS technologies, have normal somatic single base substitution burdens, but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.

genomics↗

bioRxiv2021

MutationalPatterns: The one stop shop for the analysis of mutational processes

BackgroundThe collective of somatic mutations in a genome represents a record of mutational processes that have been operative in a cell. These processes can be investigated by extracting relevant mutational patterns from sequencing data. ResultsHere, we present the next version of MutationalPatterns, an R/Bioconductor package, which allows in-depth mutational analysis of catalogues of single and double base substitutions as well as small insertions and deletions. Major features of the package include the possibility to perform regional mutation spectra analyses and the possibility to detect strand asymmetry phenomena, such as lesion segregation. On top of this, the package also contains functions to determine how likely it is that a signature can cause damaging mutations (i.e., mutations that affect protein function). This updated package supports stricter signature refitting on known signatures in order to prevent overfitting. Using simulated mutation matrices containing varied signature contributions, we showed that reliable refitting can be achieved even when only 50 mutations are present per signature. Additionally, we incorporated bootstrapped signature refitting to assess the robustness of the signature analyses. Finally, we applied the package on genome mutation data of cell lines in which we deleted specific DNA repair processes and on large cancer datasets, to show how the package can be used to generate novel biological insights. ConclusionsThis novel version of MutationalPatterns allows for more comprehensive analyses and visualization of mutational patterns in order to study the underlying processes. Ultimately, in-depth mutational analyses may contribute to improved biological insights in mechanisms of mutation accumulation as well as aid cancer diagnostics. MutationalPatterns is freely available at http://bioconductor.org/packages/MutationalPatterns.

genomics↗

bioRxiv2020

A multi-platform reference for somatic structural variation detection

Accurate detection of somatic structural variation (SV) in cancer genomes remains a challenging problem. This is in part due to the lack of high-quality gold standard datasets that enable the benchmarking of experimental approaches and bioinformatic analysis pipelines for comprehensive somatic SV detection. Here, we approached this challenge by genome-wide somatic SV analysis of the paired melanoma and normal lymphoblastoid COLO829 cell lines using four different technologies: Illumina HiSeq, Oxford Nanopore, Pacific Biosciences and 10x Genomics. Based on the evidence from multiple technologies combined with extensive experimental validation, including Bionano optical mapping data and targeted detection of candidate breakpoint junctions, we compiled a comprehensive set of true somatic SVs, comprising all SV types. We demonstrate the utility of this resource by determining the SV detection performance of each technology as a function of tumor purity and sequence depth, highlighting the importance of assessing these parameters in cancer genomics projects and data analysis tool evaluation. The reference truth somatic SV dataset as well as the underlying raw multi-platform sequencing data are freely available and are an important resource for community somatic benchmarking efforts.

genomics↗

bioRxiv2017

Mapping And Phasing Of Structural Variation In Patient Genomes Using Nanopore Sequencing

Structural genomic variants form a common type of genetic alteration underlying human genetic disease and phenotypic variation. Despite major improvements in genome sequencing technology and data analysis, the detection of structural variants still poses challenges, particularly when variants are of high complexity. Emerging long-read single-molecule sequencing technologies provide new opportunities for detection of structural variants. Here, we demonstrate sequencing of the genomes of two patients with congenital abnormalities using the ONT MinION at 11x and 16x mean coverage, respectively. We developed a bioinformatic pipeline - NanoSV - to efficiently map genomic structural variants (SVs) from the long-read data. We demonstrate that the nanopore data are superior to corresponding short-read data with regard to detection of de novo rearrangements originating from complex chromothripsis events in the patients. Additionally, genome-wide surveillance of SVs, revealed 3,253 (33%) novel variants that were missed in short-read data of the same sample, the majority of which are duplications < 200bp in size. Long sequencing reads enabled efficient phasing of genetic variations, allowing the construction of genome-wide maps of phased SVs and SNVs. We employed read-based phasing to show that all de novo chromothripsis breakpoints occurred on paternal chromosomes and we resolved the long-range structure of the chromothripsis. This work demonstrates the value of long-read sequencing for screening whole genomes of patients for complex structural variants.

genomics↗