Biology subjects

Veltman, J. A.

Publications and source records attributed to Veltman, J. A..

9 recordsLinked to original sources

bioRxiv2026

Functional modelling of human infertility-associated genetic variants using C. elegans and mice

Infertility affects one in six couples worldwide and has a significant genetic component. Genome sequencing efforts have identified increasing numbers of potentially pathogenic variants, including in conserved meiotic genes. However, the lack of functional validation remains a major barrier to establishing variant pathogenicity and clinical diagnoses. Here, we establish an experimental pipeline integrating C. elegans and mouse in vivo models with in silico protein structure predictions to functionally validate potentially pathogenic infertility-associated variants. Using CRISPR-Cas9 we generated worm and mouse models of a homozygous missense variant (P638L) in MSH4, a mismatch repair protein essential for meiotic recombination, identified in a patient with non-obstructive azoospermia (NOA). Homozygous msh-4P546L worms exhibited severe meiotic defects including an absence of chiasmata, accumulation of DNA damage, and loss of crossover markers. Comparable defects were observed in spermatocytes of homozygous Msh4P660L/P660L mice, while Msh4P660L/P660L ovaries lacked oocyte-containing follicles, demonstrating that this variant causes infertility in both sexes. Together, these findings support a model in which the MSH4 P638L substitution disrupts the conversion of early recombination events into crossovers, leading to NOA in men and primary ovarian insufficiency in women. Further worm modelling of human MSH4 genetic variants identified exclusively in heterozygosity (G649R) or also in homozygosity (Y589C) demonstrates the potential of worm models to predict the pathogenicity of missense variants in meiotic proteins found in the human population. We propose that this integrated worm-mouse pipeline provides a powerful framework for accelerating the genetic diagnosis of infertility and informing the clinical management of affected individuals.

cell biology↗

bioRxiv2023

Evolutionary constraint genes implicated in autism spectrum disorder across 2,054 nonhuman primate genomes

BackgroundSignificant progress has been made in elucidating the genetic underpinning of Autism Spectrum Disorder (ASD). This childhood-onset chronic disorder of cognition, communication and behaviour ranks among the most severe from a public health perspective, and it is therefore hoped that new discoveries will lead to better therapeutic options. However, there are still significant gaps in our understanding of the link between genomics, neurobiology and clinical phenotype in scientific discovery. New models are therefore needed to address these gaps. Rhesus macaques (Macaca mulatta) have been extensively used for preclinical neurobiological research because of remarkable similarities to humans across biology and behaviour that cannot be captured by other experimental animals. MethodsWe used the macaque Genotype and Phenotype (mGAP) resource (v2.0) consisting of 2,054 macaque genomes to examine patterns of evolutionary constraint in known human neurodevelopmental genes. Residual variation intolerance scores (RVIS) were calculated for all annotated autosomal genes (N = 18,168) and Gene Set Enrichment Analysis (GSEA) was used to examine patterns of constraint across ASD genes and related neurodevelopmental genes. ResultsWe demonstrated that patterns of constraint across autosomal genes are correlated in humans and macaques, and that ASD-implicated genes exhibit significant constraint in macaques (p = 9.4 x 10-27). Among macaques, many key ASD genes were observed to harbour predicted damaging mutations. A small number of key ASD genes that are highly intolerant to mutation in humans, however, showed no evidence of similar intolerance in macaques (CACNA1D, CNTNAP2, MBD5, AUTS2 and NRXN1). Constraint was also observed across genes implicated in intellectual disability (p = 1.1 x 10-46), epilepsy (p = 2.1 x 10-33) and schizophrenia (p = 4.2 x 10-45), and for an overlapping neurodevelopmental gene set (p = 4.0 x 10-10) LimitationsThe lack of behavioural phenotypes among the macaques whose genotypes were studied means that we are unable to further investigate whether genetic variants have similar phenotypic consequences among nonhuman primates. ConclusionThe presence of pathological mutations in ASD genes among macaques, and the evidence of similar constraints in these genes to humans, provide a strong rationale for further investigation of genotype-phenotype relationships in nonhuman primates. This highlights the importance of identifying phenotypic behaviours associated with clinical symptoms, elucidating the neurobiological underpinnings of ASD, and developing primate models for translational research to advance approaches for precision medicine and therapeutic interventions.

genetics↗

bioRxiv2022

Phasing of de novo mutations using a scaled-up multiple amplicon long-read sequencing approach

De novo mutations (DNMs) play an important role in severe genetic disorders that reduce fitness. To better understand the role of DNMs in disease, it is important to determine the parent-of-origin and timing of the mutational events that give rise to the mutations, especially in sex-specific developmental disorders such as male infertility. However, currently available short-read sequencing approaches are not ideally suited for phasing as this requires long continuous DNA strands that span both the DNM and one or more informative SNPs. To overcome these challenges, we optimised and implemented a multiplexed long-read sequencing approach using the Oxford Nanopore technologies MinION platform. We specifically focused on improving target amplification, integrating long-read sequenced data with high-quality short-read sequence data, and developing an anchored phasing computational method. This approach was able to handle the inherent phasing challenges that arise from long-range target amplification and the normal accumulation of sequencing error associated with long-read sequencing. In total, 77 out of 109 DNMs (71%) were successfully phased and parent-of-origin identified. The majority of phased DNMs were prezygotic (90%), the accuracy of which is highlighted by the average mutant allele frequency of 49.6% and a standard error margin of 0.84%. This study demonstrates the benefits of using an integrated short-read and long-read sequencing approach for large-scale DNM phasing.

genomics↗

bioRxiv2020

Stochasticity explains differences in the number of de novo mutations between families

The number of de novo mutations (DNMs) in the human germline is correlated with parental age at conception, but this explains only part of the observed variation. We investigated whether there is a family-specific contribution to the number of DNMs in offspring. The analysis of DNMs in 111 dizygotic twin pairs did not identify a significant family-specific contribution. This result was corroborated by comparing DNMs of 1669 siblings to those of age-matched unrelated offspring. In addition, by modeling DNM data from 1714 multi-offspring families we estimated that the family specific contribution explains approximately 5.2% of the variation in DNM number. Furthermore, we found no significant difference between the observed number of DNMs and those based on a stochastic Poisson process. We conclude that a family-specific contribution to DNMs is small and that stochasticity explains a large proportion of variation in DNM counts.

genomics↗

bioRxiv2019

Biallelic mutations in M1AP are a frequent cause of meiotic arrest leading to male infertility

Male infertility affects [~]7% of men in Western societies, but its causes remain poorly understood. The most clinically severe form of male infertility is non-obstructive azoospermia (NOA), which is, in part, caused by an arrest at meiosis, but so far only few genes have been reported to cause germ cell arrest in males. To address this gap, whole exome sequencing was performed in 60 German men with complete meiotic arrest, and we identified in three unrelated men the same homozygous frameshift variant c.676dup (p.Trp226LeufsTer4) in M1AP, encoding meiosis 1 arresting protein. Then, with collaborators from the International Male Infertility Genomics Consortium (IMIGC), we screened a Dutch cohort comprising 99 infertile men and detected the same homozygous variant c.676dup in a man with hypospermatogenesis predominantly displaying meiotic arrest. We also identified two Portuguese men with NOA carrying likely biallelic loss-of-function (LoF) and missense variants in M1AP among men screened by the Genetics of Male Infertility Initiative (GEMINI). Moreover, we discovered a homozygous missense variant p.(Pro389Leu) in M1AP in a consanguineous Turkish family comprising five infertile men. M1AP is predominantly expressed in human and mouse spermatogonia up to secondary spermatocytes and previous studies have shown that knockout male mice are infertile due to meiotic arrest. Collectively, these findings demonstrate that both LoF and missense M1AP variants that impair its protein cause autosomal-recessive meiotic arrest, non-obstructive azoospermia and male infertility. In view of the evidence from several independent groups and populations, M1AP should be included in the growing list of validated NOA genes.

genetics↗

bioRxiv2019

MetaDome: Pathogenicity analysis of genetic variants through aggregation of homologous human protein domains

The growing availability of human genetic variation has given rise to novel methods of measuring genetic tolerance that better interpret variants of unknown significance. We recently developed a novel concept based on protein domain homology in the human genome to improve variant interpretation. For this purpose we mapped population variation from the Exome Aggregation Consortium (ExAC) and pathogenic mutations from the Human Gene Mutation Database (HGMD) onto Pfam protein domains. The aggregation of these variation data across homologous domains into meta-domains allowed us to generate base-pair resolution of genetic intolerance profiles for human protein domains.\n\nHere we developed MetaDome, a fast and easy-to-use web service that visualizes meta-domain information and gene-wide profiles of genetic tolerance. We updated the underlying data of MetaDome to contain information from 56,319 human transcripts, 71,419 protein domains, 12,164,292 genetic variants from gnomAD, and 34,076 pathogenic mutations from ClinVar. MetaDome allows researchers to easily investigate their variants of interest for the presence or absence of variation at corresponding positions within homologous domains. We illustrate the added value of MetaDome by an example that highlights how it may help in the interpretation of variants of unknown significance. The MetaDome web server is freely accessible at https://stuart.radboudumc.nl/metadome.

bioinformatics↗

bioRxiv2018

A systematic review and standardized clinical validity assessment of male infertility genes

Study questionWhich genes are confidently linked to human male infertility?\n\nSummary answerOur systematic literature search and clinical validity assessment reveals that a total of 67 genes are currently confidently linked to 81 human male infertility phenotypes.\n\nWhat is known alreadyThe discovery of novel male infertility genes is rapidly accelerating with the availability of Next-Generation Sequencing methods, but the quality of evidence for gene-disease relationships varies greatly. In order to improve genetic research, diagnostics and counseling, there is a need for an evidence-based overview of the currently known genes.\n\nStudy design, size, durationWe performed a systematic literature search and evidence assessment for all publications in Pubmed until June 2018 covering genetic causes of male infertility and/or defective male genitourinary development.\n\nParticipants/materials, setting, methodsTwo independent reviewers conducted the literature search and included papers on the monogenic causes of human male infertility and excluded papers on genetic association or risk factors, karyotype anomalies and/or copy number variations affecting multiple genes. Next, the quality and the extent of all evidence supporting selected genes was weighed by a standardized scoring method and used to determine the clinical validity of each gene-disease relationship as expressed by the following six categories: no evidence, limited, moderate, strong, definitive or unable to classify.\n\nMain results and the role of chanceFrom a total of 23,031 records, we included 1,286 publications about monogenic causes of male infertility leading to a list of 471 gene-disease relationships. The clinical validity of these gene-disease relationships varied widely and ranged from definitive (n=36) to strong (n=12), moderate (n=33), limited (n=86) or no evidence (n=154). A total of 150 gene-disease relationships could not be classified.\n\nLimitations, reasons for cautionOur literature search was limited to Pubmed.\n\nWider implications of the findingsThe comprehensive overview will aid researchers and clinicians in the field to establish gene lists for diagnostic screening using validated gene-disease criteria and identify gaps in our knowledge of male infertility. For future studies, the authors discuss the relevant and important international guidelines regarding research related to gene discovery and provide specific recommendations to the field of male infertility.\n\nStudy funding/competing interest(s)This work was supported by a VICI grant from The Netherlands Organisation for Scientific Research (918-15-667 to JAV).

genetics↗

bioRxiv2018

Identifying long indels in exome sequencing data of patients with intellectual disability

Exome sequencing is a powerful tool for detecting both single and multiple nucleotide variation genome wide. However long indels, in the size range 20 - 200bp, remain difficult to accurately detect. By assessing a set of common exonic long indels, we estimate the sensitivity of long indel detection in exome sequencing data to be 92%. To clarify the role of pathogenic long indels in patients with intellectual disability (ID), we analysed exome sequencing data from 820 patients using two variant callers, Pindel and Platypus. We identified three indels explaining the patients clinical phenotype by disrupting the UBE3A, PGAP3 and MECP2 genes. Comparison of different tools demonstrated the importance of both correct genotyping and annotation variants. In conclusion, specialized long indel detection can improve diagnostic yield in ID patients.

genomics↗

bioRxiv2017

Germline De Novo Mutation Clusters Arise During Oocyte Aging In Genomic Regions With Increased Double-Strand Break Incidence

Clustering of mutations has been found both in somatic mutations from cancer genomes and in germline de novo mutations (DNMs). We identified 1,755 clustered DNMs (cDNMs) within whole-genome sequencing data from 1,291 parent-offspring trios and investigated the underlying mutational mechanisms. We found that the number of clusters on the maternalallele was positively correlated with maternal age and that these consist of more individual mutations with larger intra-mutational distances compared to paternal clusters. More than 50% of maternal clusters were located on chromosomes 8, 9 and 16, in regions with an overall increased maternal mutation rate. Maternal clusters in these regions showed a distinct mutation signature characterized by C>G mutations. Finally, we found that maternal clusters associate with processes involving double-stranded-breaks (DSBs) such as meiotic gene conversions and de novo deletions events. These findings suggest accumulation of DSB-induced mutations throughout oocyte aging as an underlying mechanism leading to maternal mutation clusters.

genomics↗