Biology subjects

Vissers, L.

Publications and source records attributed to Vissers, L..

7 recordsLinked to original sources

bioRxiv2026

Mapping NMD-coupled alternative splicing in iPSC-derived brain cells: a resource for therapeutic discovery

Therapeutic options for neurodevelopmental disorders (NDD) are expanding. Targeting alternative splicing (AS) events linked to nonsense-mediated decay (NMD) offers a promising way to boost gene expression in haploinsufficiency disorders. However, naturally occurring NMD-coupled AS (NMD AS) events in brain cells remain poorly characterized. Here, we integrate long- and short-read RNA sequencing of NMD-inhibited induced pluripotent stem cell-derived excitatory neurons, astrocytes, and microglia to map and prioritize NMD AS events most suitable for therapeutic intervention. We developed an optimized prediction framework and provide an open access, queryable, database cataloging the existence and abundance of NMD AS events across these cell types. Querying this resource, we identified 936 NMD-sensitive AS events in 250 autosomal-dominant NDD genes and nominate 60 NMD AS events in haploinsufficient genes underlying 42 NDDs that are abundant in at least one cell type and thus represent promising therapeutic targets. These included a previously targeted NMD AS event in SCN1A, and known NMD AS events in CHD2, EZH2, and NR4A2, for which we confirm high cell type-specific abundance, as well as an newly identified abundant event in PHIP. Beyond NDD genes, we identify 1,817 differentially spliced AS events including NMD AS events, highlighting the potential functional role of (NMD) AS within brain cell-specific regulatory programs. This framework and resource enables systematic discovery and prioritization of therapeutically targetable NMD AS events and establish a cell-type resolved atlas to guide splice-modulating strategies in NDDs.

genetics↗

bioRxiv2024

Genome-wide profiling of highly similar paralogous genes using HiFi sequencing

Variant calling is hindered in segmental duplications by sequence homology. We developed Paraphase, a HiFi-based informatics method that resolves highly similar genes by phasing all haplotypes of a gene family. We applied Paraphase to 160 long (>10 kb) segmental duplication regions across the human genome with high (>99%) sequence similarity, encoding 316 genes. Analysis across five ancestral populations revealed highly variable copy numbers of these regions. We identified 23 families with exceptionally low within-family diversity, where extensive gene conversion and unequal-crossing over have resulted in highly similar gene copies. Furthermore, our analysis of 36 trios identified 7 de novo SNVs and 4 de novo gene conversion events, 2 of which are non-allelic. Finally, we summarized extensive genetic diversity in 9 medically relevant genes previously considered challenging to genotype. Paraphase provides a framework for resolving gene paralogs, enabling accurate testing in medically relevant genes and population-wide studies of previously inaccessible genes.

genomics↗

bioRxiv2023

SOD1 is a synthetic lethal target in PPM1D-mutant leukemia cells

The DNA damage response is critical for maintaining genome integrity and is commonly disrupted in the development of cancer. PPM1D (protein phosphatase, Mg2+/Mn2+ dependent 1D) is a master negative regulator of the response; gain-of-function mutations and amplifications of PPM1D are found across several human cancers making it a relevant pharmacologic target. Here, we used CRISPR/Cas9 screening to identify synthetic-lethal dependencies of PPM1D, uncovering superoxide dismutase-1 (SOD1) as a potential target for PPM1D-mutant cells. We revealed a dysregulated redox landscape characterized by elevated levels of reactive oxygen species and a compromised response to oxidative stress in PPM1D-mutant cells. Altogether, our results demonstrate the protective role of SOD1 against oxidative stress in PPM1D-mutant leukemia cells and highlight a new potential therapeutic strategy against PPM1D-mutant cancers.

cancer biology↗

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↗

bioRxiv2021

A de novo paradigm for male infertility

IntroductionDe novo mutations (DNMs) are known to play a prominent role in sporadic disorders with reduced fitness1. We hypothesize that DNMs play an important role in male infertility and explain a significant fraction of the genetic causes of this understudied disorder. To test this hypothesis, we performed trio-based exome-sequencing in a unique cohort of 185 infertile males and their unaffected parents. Following a systematic analysis, 29 of 145 rare protein altering DNMs were classified as possibly causative of the male infertility phenotype. We observed a significant enrichment of Loss-of-Function (LoF) DNMs in LoF-intolerant genes (p-value=1.00x10-5) as well as predicted pathogenic missense DNMs in missense-intolerant genes (p-value=5.01x10-4). One DNM gene identified, RBM5, is an essential regulator of male germ cell pre-mRNA splicing2. In a follow-up study, 5 rare pathogenic missense mutations affecting this gene were observed in a cohort of 2,279 infertile patients, with no such mutations found in a cohort of 5,784 fertile men (p-value=0.009). Our results provide the first evidence for the role of DNMs in severe male infertility and point to many new candidate genes affecting fertility.

genetics↗

bioRxiv2019

Integrating healthcare and research genetic data empowers the discovery of 49 novel developmental disorders

De novo mutations (DNMs) in protein-coding genes are a well-established cause of developmental disorders (DD). However, known DD-associated genes only account for a minority of the observed excess of such DNMs. To identify novel DD-associated genes, we integrated healthcare and research exome sequences on 31,058 DD parent-offspring trios, and developed a simulation-based statistical test to identify gene-specific enrichments of DNMs. We identified 285 significantly DD-associated genes, including 28 not previously robustly associated with DDs. Despite detecting more DD-associated genes than in any previous study, much of the excess of DNMs of protein-coding genes remains unaccounted for. Modelling suggests that over 1,000 novel DD-associated genes await discovery, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of dominant DDs.

genomics↗

bioRxiv2018

Identification of rare de novo epigenetic variations in congenital disorders

Certain human traits such as neurodevelopmental disorders (NDs) and congenital anomalies (CAs) are believed to be primarily genetic in origin. With recent dramatic advances in genomic technologies, genome-wide surveys of cohorts of patients with ND/CAs for point mutations and structural variations have greatly advanced our understanding of their genetic etiologies1,2. However, even after whole genome sequencing (WGS), a substantial fraction of such disorders remain unexplained3. In contrast, the possibility that constitutive epigenetic variations (epivariations) might underlie such traits has not been well explored. We hypothesized that some cases of ND/CA are caused by aberrations of DNA methylation that lead to a dysregulation of normal genome function. By comparing DNA methylation profiles from 489 individuals with ND/CAs against 1,534 population controls, we identified epivariations as a frequent occurrence in the human genome. De novo epivariations were significantly enriched in cases when compared to controls. RNAseq data from population studies showed that epivariations often have an impact on gene expression comparable to loss-of-function mutations. Additionally, we detected and replicated an enrichment of rare sequence mutations overlapping CTCF binding sites close to epivariations. Thus, some epivariations occur secondary to cis-linked mutations in regulatory regions, providing a rationale for interpreting non-coding genetic variation. We propose that epivariations likely represent the causative genomic defect in 5-10% of patients with unexplained ND/CAs. This constitutes a yield comparable to CNV microarrays, and as such has significant diagnostic relevance.

genomics↗