Biology subjects

Vermeesch, J. R.

Publications and source records attributed to Vermeesch, J. R..

At least 19 recordsLinked to original sources

bioRxiv2025

Longitudinal cell-free DNA methylome and fragmentome profiles in health uncover signatures of cell type and demographic origin

Cell-free DNA (cfDNA) is a powerful analyte for liquid biopsy applications. However, the composition and fragmentation of cfDNA in health remains incompletely characterized. Here, we profiled 432 plasma cfDNA samples from healthy individuals using targeted enzymatic methyl-sequencing, allowing cell-type of origin inference and assessment of fragmentation features. Both in a diurnal and a cross-sectional cohort, we observed that cfDNA levels and cellular contributions show lower variability within than between individuals. Hematopoietic lineages are the dominant cfDNA sources, with interindividual variability particularly evident in granulocyte contributions. Demographic factors such as sex, age and body mass index (BMI) contribute to changes in the contribution of various blood cell types, and cfDNA concentrations are 1.6-fold higher in early morning collections (P = 1.8 x 10-5). By integrating cell-type-specific cfDNA methylation, fragment size and dinucleotide end motif information, we demonstrate distinct associations of these characteristics with specific cell types. Granulocyte-derived fragments showed a consistent enrichment in mononucleosomal sizes (P = 3.5 x 10-54) and CC end motifs, while also cfDNA from non-hematopoietic cells exhibited distinct size and end-motif profiles. In addition, we observed hypomethylated DNA to be associated with shorter fragment sizes and altered end-motif frequencies, emphasizing interactions between DNA methylation, nuclease activity and chromatin context in shaping cfDNA features. Together, our results provide a view on processes and cell types involved in cfDNA biogenesis in healthy individuals. They underscore that demographic variables and sampling time should be considered for cfDNA-based assay design, but also highlight novel opportunities to improve the representation of specific cell types in cfDNA, thus providing a foundation for optimizing cfDNA diagnostics by leveraging multiple axes of information.

genomics↗

bioRxiv2025

Unlocking the full potential of Oxford Nanopore reads with NOVOLoci

Long-read sequencing technologies and accompanying algorithms have substantially advanced genome assembly. However, there are ongoing challenges in assembling complex genomic regions, particularly those associated with genetic disorders. Moreover, assemblies of non-model organisms are often limited by the amount of DNA that can be extracted, so reducing the data modalities that can be obtained. Here, we introduce NOVOLoci, a haplotype-aware assembler capable of high-quality targeted and whole-genome assemblies, despite the relatively high error rates of Oxford Nanopore Technologies (ONT) data. By adopting a novel seed-extension approach with iterative conflict resolution, it achieves accurate haplotype phasing, thus overcoming a critical limitation of current graph-based assemblers. Benchmarking shows that NOVOLoci consistently outperforms the four leading assembly tools across five clinically relevant genomic disorder loci by delivering accurately phased assemblies with superior contiguity and completeness, even compared with hybrid assemblers that combine PacBio and ONT sequencing reads (nearly triple the N90 value compared with Verkko hybrid). We demonstrate its broader utility in assembling the genome of a highly heterozygous non-model animal Oikopleura dioica, whose small size limits the amount of DNA available from an individual. Using data only from a single ONT flow cell, NOVOLoci assembles a phased diploid genome with high contiguity and a 32-fold increase in N50 values compared with existing methods. NOVOLocis distinct algorithmic strategy demonstrates that substantial advances in genome assembly can still be made. This development brings routine clinical diagnosis of genomic disorders and diploid assembly of non-model organisms with ONT reads a step closer to reality.

bioinformatics↗

bioRxiv2025

Population differences of chromosome 22q11.2 duplication structure predisposes differentially to microdeletion and inversion.

The most common genomic disorder, chromosome 22q11.2 microdeletion syndrome (22q11.2DS), is mediated by highly identical and polymorphic segmental duplications (SDs) known as low copy repeats (LCRs; regions A-D) that have been challenging to sequence and characterize. Here, we report the sequence-resolved genomic architecture of 135 chromosome 22q11.2 haplotypes from diverse 1000 Genomes Project samples. We find that more than 90% of the copy number variation is polarized to the most proximal LCR region A (LCRA) where 50 distinct structural configurations are observed ([~]189 kbp to [~]2.15 Mbp or 11-fold length variation). A higher-order SD cassette structure of 105 kbp in length, flanked by 25 kbp long inverted repeats, drives this variation and emerged in the human-chimpanzee ancestral lineage later expanding in humans [~]1.0 [0.8-1.2] million years ago. African LCRA haplotypes are significantly longer (p=0.0047) when compared to non-Africans yet are predicted to be more protected against recurrent microdeletions (p=0.00053) due to a preponderance of flanking SDs in an inverted orientation. Conversely, we identified nine distinct inversion polymorphisms, including five recurrent [~]2.28 Mbp inversions extending across the critical region (LCRA-D) and four smaller inversions (two LCRA-B, one LCRC-D, and one LCRB-D); 7/9 of these events were identified in haplotypes of African and admixed American ancestry. Finally, we sequence and assemble four families and show that LCRA-D deletion breakpoints map to the 105 kbp repeat unit while inversion breakpoints associate with the 25 kbp repeats adjacent to palindromic AT-rich regions. In one family, we observe evidence of more complex unequal crossover events associated with gene conversion and multiple breakpoints. Our findings suggest that specific haplotype configurations are protective and susceptible to chromosome 22q11.2DS while recurrent large-scale inversions help to explain why this syndrome is less prevalent among individuals of African descent.

genomics↗

bioRxiv2024

Long-read whole-genome sequencing-based concurrent haplotyping and aneuploidy profiling of single cells

Long-read whole-genome sequencing (lrWGS) enhances haplotyping by providing more phasing information per read compared to short-read sequencing. However, its use for single-cell haplotype phasing remains underexplored. This proof-of-concept study examines lrWGS data from single cells for small variant (SNV and indel) calling and haplotyping using the Genome in a Bottle (GIAB) Ashkenazi trio. lrWGS was performed on single-cell (1 cell) and multi-cell (10 cells) samples from the offspring. Chromosome-length haplotypes were obtained by leveraging both long reads and pedigree information. These haplotypes were further refined by replacing them with matched parental haplotypes. In single-cell and multi-cell samples, 92% and 98% of heterozygous SNVs, and 74% and 78% of heterozygous indels were accurately haplotyped. Applied to human embryos for preimplantation genetic testing (PGT), lrWGS demonstrated 100% consistency with array-based methods for detecting monogenic disorders, without requiring phasing references. Aneuploidies were accurately detected, with insights into the mechanistic origins of chromosomal abnormalities inferred from the parental unique allele fractions. We show that lrWGS-based concurrent haplotyping and aneuploidy profiling of single cells provides an alternative to current PGT methods, with applications potential in areas such as cell-based prenatal diagnosis and animal and plant breeding.

genomics↗

bioRxiv2024

Mechanistic origin and preimplantation development of uniparental and polyploid blastomeres

Whole-genome (WG) abnormalities, such as uniparental diploidy and triploidy, cause fetal death. Occasionally, they coexist with biparental diploid cells in live births. Understanding the origin and early development of WG abnormal blastomeres is crucial for explaining the formation of androgenotes, gynogenotes, triploidy, chimerism, and mixoploidy. By haplotyping 118 blastomeres from first cleavages, we identified various mechanisms of heterogoneic divisions that lead to WG abnormal blastomeres or their coexistence with normal blastomeres in both multipolar and bipolar cleaving zygotes. After culturing the totipotent blastomeres to three preimplantation stages and performing transcriptome profiling on over 600 cells, we discovered that stress responses contribute to developmental impairment in WG abnormal cells, resulting in either cell arrest or blastocyst formation. Some first-cleavage-derived WG abnormal blastomeres can survive early development and progress to blastocysts. Their potential dominance in preimplantation embryos represents an overlooked cause of abnormal development. Haplotype based screening could further increase pregnancy rates.

genetics↗

bioRxiv2024

Alleviating cell-free DNA sequencing biases with optimal transport

Cell-free DNA (cfDNA) is a rich source of biomarkers for various (patho)physiological conditions. Recent developments have used Machine Learning on large cfDNA data sets to enhance the detection of cancers and immunological diseases. Preanalytical variables, such as the library preparation protocol or sequencing platform, are major confounders that influence such data sets and lead to domain shifts (i.e., shifts in data distribution as those confounders vary across time or space). Here, we present a domain adaptation method that builds on the concept of optimal transport, and explicitly corrects for the effect of such preanalytical variables. Our approach can be used to merge cohorts representative of the same population but separated by technical biases. Moreover, we also demonstrate that it improves cancer detection via Machine Learning by alleviating the sources of variation that are not of biological origin. Our method also improves over the widely used GC-content bias correction, both in terms of bias removal and cancer signal isolation. These results open perspectives for the downstream analysis of larger data sets through the integration of cohorts produced by different sequencing pipelines or collected in different centers. Notably, the approach is rather general with the potential for application to many other genomic data analysis problems.

bioinformatics↗

bioRxiv2024

Multiple paralogues and recombination mechanisms drive the high incidence of 22q11.2 Deletion Syndrome

The 22q11.2 deletion syndrome (22q11.2DS) is the most common microdeletion disorder. Why the incidence of 22q11.2DS is much greater than that of other genomic disorders remains unknown. Short read sequencing cannot resolve the complex segmental duplicon structure to provide direct confirmation of the hypothesis that the rearrangements are caused by non-allelic homologous recombination between the low copy repeats on chromosome 22 (LCR22s). To enable haplotype-specific assembly and rearrangement mapping in LCR22 regions, we combined fiber-FISH optical mapping with whole genome (ultra-)long read sequencing or rearrangement-specific long-range PCR on 24 duos (22q11.2DS patient and parent-of-origin) comprising several different LCR22-mediated rearrangements. Unexpectedly, we demonstrate that not only different paralogous segmental duplicon but also palindromic AT-rich repeats (PATRR) are driving 22q11.2 rearrangements. In addition, we show the existence of two different inversion polymorphisms preceding rearrangement, and somatic mosaicism. The existence of different recombination sites and mechanisms in paralogues and PATRRs which are copy number expanding in the human population are a likely explanation for the high 22q11.2DS incidence.

genetics↗

bioRxiv2023

A multi-omics genome-and-transcriptome single-cell atlas of human preimplantation embryogenesis reveals the cellular and molecular impact of chromosome instability

The frequent acquisition of genomic abnormalities in human preimplantation embryos is a leading cause of pregnancy loss, but does not necessarily prohibit healthy offspring. However, the impact of genomic abnormalities on cellular states and development of the early human embryo remains largely unclear. Here, we characterise aneuploidy and reconstruct gene regulatory networks in human preimplantation embryos, and investigate gene expression and developmental perturbations instigated by aneuploidy using single-cell genome-and-transcriptome sequencing (G&T-seq). At the genomic level, we show that acquired numerical and structural chromosomal aberrations are frequent across all stages of early embryogenesis and in all cell lineages. At the transcriptome level, we identify regulators of cell identity and uncover a network of 248 transcription factors from 10 major gene regulatory modules that characterise the distinct lineages of human preimplantation embryos. By integrating single-cell DNA-with RNA-information, we unveil how expression levels are affected by losses or gains of the corresponding genes in embryonic cells across human preimplantation development, as well as how copy-number aberrant transcription factor genes perturb the expression of their cognate target genes in euploid regions. Furthermore, we reveal a majority of aneuploid cells show a developmental delay and reduced fitness, indicating cell competition within the mosaic diploid-aneuploid embryo, which may contribute to selection against aneuploid cells and the birth of healthy offspring from mosaic diploid-aneuploid embryos. In summary, our multi-modal analyses provide unprecedented insights into early human embryo development.

developmental biology↗

bioRxiv2022

Chromatin regulators in the TBX1 network confer risk for conotruncal heart defects in 22q11.2DS and sporadic congenital heart disease

BackgroundCongenital heart disease (CHD) affecting the conotruncal region of the heart, occur in half of patients with 22q11.2 deletion syndrome. This syndrome is a rare disorder with relative genetic homogeneity that can facilitate identification of genetic modifiers. Haploinsufficiency of TBX1, mapped to the 22q11.2 region, encoding a T-box transcription factor, is one of the main genes for the etiology of the syndrome. We suggest that genetic modifiers of CHD in patients with 22q11.2 deletion syndrome may be in the TBX1 gene network. MethodsTo identify genetic modifiers of 22q11.2 deletion syndrome, we analyzed whole genome sequence of subjects with 22q11.2DS, of which 456 were cases with conotruncal heart defects and 537 were controls with normal cardiac structures. We retained the most damaging rare coding variants and examined 19 functional gene sets for association that were weighted upon expression of genes in cardiac progenitor cells in mouse embryos identified by RNA-sequencing. ResultsWe identified rare damaging coding variants in chromatin regulatory genes as modifiers of conotruncal heart defects in 22q11.2DS. Chromatin genes with recurrent damaging variants include EP400, KAT6A, KMT2C, KMT2D, NSD1, CHD7 and PHF21A. In total, we identified 37 chromatin regulatory genes, that may increase risk for conotruncal heart defects in 8.5% of 22q11.2 deletion syndrome cases. Many of these genes were identified as risk factors for sporadic CHD in the general population increasing the likelihood that these genes are medically important contributors for CHD. These genes are co-expressed in cardiac progenitor cells with TBX1, suggesting that they may be in the same genetic network. Some of the genes identified, such as KAT6A, KMT2C, CHD7 and EZH2, have been previously shown to genetically interact with TBX1 in mouse models, providing mechanistic validation of these genes found. ConclusionsOur findings indicate that disturbance of chromatin regulatory genes impact a TBX1 gene network serving as genetic modifiers of 22q11.2 deletion syndrome. Since some of these chromatin regulatory genes were found in individuals with sporadic CHD, we suggest that there are shared mechanisms involving the TBX1 gene network in the etiology of CHD.

genetics↗

bioRxiv2022

WiNGS: Widely integrated NGS platform for federated genome analysis

Next-generation sequencing (NGS) has been increasingly used in a wide range of research communities and in routine clinical practice and leads to an ever increasing amount of sequencing data. Sequencing data comes with, several challenges such as sharing, storing, integrating, analyzing, and interpretion. The management of the expanding amount of data is challenging and, especially for human omics data, privacy protection is crucial. Unraveling the causes of rare diseases is critically dependent on data sharing, but progress is hampered by regulations and privacy concerns. To overcome the concerns associated with centralized human genomic data storage, we developed a federated analysis platform, referred to as Widely Integrated NGS (WiNGS). The presented approach enables datasharing and combined data-analysis of omics data across a consortium without a centralized data store. Moreover, the platform incorporates extensive variant interpretation tools from genotype to phenotype for the diagnosis of rare developmental disorders.

bioinformatics↗

bioRxiv2021

Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples

MotivationNon-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no comprehensive and direct accuracy comparison of these tools is published. Here, we evaluate and determine the precision of five commonly used computational NIPT aneuploidy analysis tools, considering diverse sequencing depth (coverage) and fetal DNA fraction (FF) on clinically validated NIPT samples. MethodsWe evaluated computational NIPT aneuploidy analysis tools WisecondorX, NIPTeR, NIPTmer, RAPIDR, and GIPseq, on the same set of clinically validated samples, subsampled to different sequencing coverages between 1.25-20M reads per sample (RPS). These clinically validated samples consisted of 423 samples, including 19 samples with fetal chromosome 21 trisomy (T21, Down syndrome), eight trisomy 18 (T18, Edwards syndrome) and three trisomy 13 (T13, Patau syndrome) samples. For each software and sequencing coverage, we determined the number of false-negative and false-positive trisomy/euploidy calls. For a uniform trisomy detection interpretation, we defined a framework based on the percent-point function for determining the cut-off threshold for calling aneuploidy based on the sample Z-score and the reference group Z-score distribution. We also determined the effect of the naturally occurring arbitrary read placement driven uncertainty on T21 detection at very low sequencing coverage and the effect of cell-free fetal DNA fraction (FF) on the accuracy of these computational tools in the case of various sequencing coverages. ResultsThis is the first head-to-head comparison of NIPT aneuploidy detection tools for the low-coverage whole-genome sequencing approach. We determined that, with the currently available software tools, the minimum sequencing coverage with no false-negative trisomic cases was 5M RPS. Secondly, for these compared tools, the number of false-negative trisomic cases could be reduced if the trisomy call cut-off threshold considers the Z-score distribution of euploid reference samples. Thirdly, we observed that in the case of low FF, both aneuploidy Z-score and FF inference was considerably less accurate, especially in NIPT assays with 5M RPS or lower coverage. ConclusionsWe determined that all compared computational NIPT tools were affected by lower sequencing depth, resulting in systematically increasing the proportions of false-negative trisomy results as the sequencing depth decreased. Trisomy detection for lower coverage NIPT samples (e.g. 2.5M RPS) is technically possible but can increase the proportion of false-positive and false-negative trisomic cases, especially in the case of low FF.

bioinformatics↗

bioRxiv2020

A benchmark of structural variation detection by long reads through a realistic simulated model.

Despite the rapid evolution of new sequencing technologies, structural variation detection remains poorly ascertained. The high discrepancy between the results of structural variant analysis programs makes it difficult to assess their performance on real datasets. Accurate simulations of structural variation distributions and sequencing data of the human genome are crucial for the development and benchmarking of new tools. In order to gain a better insight into the detection of structural variation with long sequencing reads, we created a realistic simulated model to thoroughly compare SV detection methods and the impact of the chosen sequencing technology and sequencing depth. To achieve this, we developed Sim-it, a straightforward tool for the simulation of both structural variation and long-read data. These simulations from Sim-it revealed the strengths and weaknesses for current available structural variation callers and long read sequencing platforms. Our findings were also supported by the latest structural variation benchmark set developed by the GIAB Consortium. With these findings, we developed a new method (combiSV) that can combine the results from five different SV callers into a superior call set with increased recall and precision. Both Sim-it and combiSV are open source and can be downloaded at https://github.com/ndierckx/.

bioinformatics↗

bioRxiv2020

Human-specific expansion of 22q11.2 low copy repeats

Segmental duplications or low copy repeats (LCRs) constitute complex regions interspersed in the human genome. They have contributed significantly to human evolution by stimulating neo- or sub-functionalization of duplicated transcripts. The 22q11.2 region carries eight LCRs (LCR22s). One of these LCR22s was recently reported to be hypervariable in the human population. It remains unknown whether this variability exists also in non-human primates. To assess the inter- and intra-species variability, we de novo assembled the region in non-human primates by a combination of optical mapping techniques. Orangutan carries three LCR22-mediated inversions of which one is the ancient haplotype since it is also present in macaque. Using fiber-FISH, lineage-specific differences in LCR22 composition were mapped. The smallest and likely ancient haplotype is present in the chimpanzee, bonobo and rhesus macaque. The absence of intra-species variation in chimpanzee indicates the LCR22-A expansion to be unique to the human population. Further, we demonstrate that LCR22-specific genes are expressed in both human and non-human primate neuronal cell lines and show expression of several primate LCR22 transcripts for the first time. The human-specificity of the expansions suggest an important role for the region in human evolution and adaptation. Author summaryLow copy repeats or segmental duplications are DNA segments composed of various subunits which are duplicated across the genome. Due to the high level of sequence identity between these segments, homologous regions can misalign, resulting in reciprocal deletions and duplications, classified as genomic disorders. These regions are subject to structural variation in the human population. We recently detected extreme structural variation in one of the most complex segmental duplication regions of the human genome, the low copy repeats on chromosome 22 (LCR22s). Rearrangements between the LCR22s result in the 22q11.2 deletion/duplication syndrome, the most common human genomic disorder. However, it remains unknown whether this variability is human-specific. In this study, we investigated those LCR22s in several individuals of the different great apes and macaque. We show only the smallest haplotype is present without any intra-species variation in the Pan genus, our closest ancestors. Hence, LCR22 expansions are human-specific, suggesting a role of these LCR22s in human evolution and adaptation and hypothesize the region contributes to the 22q11.2 deletion syndrome inter-patient phenotypic variability.

genetics↗

bioRxiv2020

Complete and haplotype-specific sequence assembly of segmental duplication-mediated genome rearrangements using targeted CRISPR-targeted ultra-long read sequencing (CTLR-Seq)

We have developed a generally applicable method based on CRISPR/Cas9-targeted ultra-long read sequencing (CTLR-Seq) to completely and haplotype-specifically resolve, at base-pair resolution, large, complex, and highly repetitive genomic regions that had been previously impenetrable to next-generation sequencing analysis such as large segmental duplication (SegDup) regions and their associated genome rearrangements that stretch hundreds of kilobases. Our method combines in vitro Cas9-mediated cutting of the genome and pulse-field gel electrophoresis to haplotype-specifically isolate intact large (200-550 kb) target regions that encompass previously unresolvable genomic sequences. These target fragments are then sequenced (amplification-free) to produce ultra-long reads at up to 40x on-target coverage using Oxford nanopore technology, allowing for the complete assembly of the complex genomic regions of interest at single base-pair resolution. We applied CTLR-Seq to resolve the exact sequence of SegDup rearrangements that constitute the boundary regions of the 22q11.2 deletion CNV and of the 16p11.2 deletion and duplication CNVs. These CNVs are among the strongest known risk factors for schizophrenia and autism. We then perform de novo assembly to resolve, for the first time, at single base-pair resolution, the sequence rearrangements of the 22q11.2 and 16p11.2 CNVs, mapping out exactly the genes and non-coding regions that are affected by the CNV for different carriers.

genomics↗

bioRxiv2020

MSH2 knock-down shows CTG repeat stability and concomitant upstream demethylation at the DMPK locus in myotonic dystrophy type 1 human embryonic stem cells

Myotonic dystrophy type 1 (DM1) is caused by expansion of a CTG repeat in the DMPK gene, where expansion size and somatic mosaicism correlates with disease severity and age of onset. While it is known that the mismatch repair protein MSH2 contributes to the unstable nature of the repeat, its role on other disease-related features, such as CpG methylation upstream of the repeat, is unknown. In this study, we investigated the effect of an MSH2 knock-down (MSH2KD) on both CTG repeat dynamics and CpG methylation pattern in human embryonic stem cells (hESC) carrying the DM1 mutation. Repeat size in MSH2 wild type (MSH2WT) and MSH2KD DM1 hESC was determined by PacBio sequencing and CpG methylation by bisulfite massive parallel sequencing. We found stabilization of the CTG repeat concurrent with a gradual loss of methylation upstream of the repeat in MSH2KD cells, while the repeat continued to expand and upstream methylation remained unchanged in MSH2WT control lines. Repeat instability was re-established and biased towards expansions upon MSH2 transgenic re-expression in MSH2KD lines while upstream methylation was not consistently re-established. We hypothesize that the hypermethylation at the mutant DM1 locus is promoted by the MMR machinery and sustained by a constant DNA repair response, establishing a potential mechanistic link between CTG repeat instability and upstream CpG methylation. Our work represents a first step towards understanding how epigenetic alterations and repair pathways connect and contribute to the DM1 pathology.

genetics↗

bioRxiv2019

HiVA: an integrative wet- and dry-lab platform for haplotype and copy number analysis of single-cell genomes

Haplotyping is imperative for comprehensive analysis of genomes, imputation of genetic variants and interpretation of error-prone single-cell genomic data. Here we present a novel sequencing-based approach for whole-genome SNP typing of single cells, and determine genome-wide haplotypes, the copy number of those haplotypes as well as the parental and segregational origin of chromosomal aberrations from sequencing- and array-based SNP landscapes of single cells. The analytical workflow is made available as an interactive web application HiVA (https://hiva.esat.kuleuven.be).

genomics↗

bioRxiv2018

RLIM enhances BMP signalling mediated fetal lung development in mice

RLIM, also called RNF12, is an X-linked E3 ubiquitin ligase. It is a pleotropic protein acting as a negative regulator of LIM-homeodomain transcription factors and of SMAD7, an antagonist of the BMP and TGF{beta} pathways. Mutations in RLIM are associated with variable congenital malformations in human. The molecular mechanism causing these malformations is still poorly understood.\n\nIn this study, we used a conventional knockout (KO) mouse model to phenotypically characterize male mutants and to investigate the effect of Rlim mutation on BMP pathway signalling. Only 50% of KO male neonates survive and are significantly smaller. We show that Rlim deletion alters lung branching and maturation resulting in severe respiratory distress and neonatal death. Except for a single case of cardiac interventricular septal defect, no other malformations that mimic the human condition were observed. Western blot analysis shows that RLIM deficiency is associated with an increase of its target SMAD7 levels and a loss of SMAD1/5/9 activation. Interestingly, SMAD5 levels were diminished, suggesting another regulatory loop between RLIM and the BMP pathway.\n\nIn conclusion, RLIM is important for lung development in mice and exerts this function in part through intracellular propagation of BMP signalling.\n\nAuthor summaryRLIM is an X-linked gene encoding an enzyme that regulates a number of proteins including SMAD7, an antagonist of BMP pathway. RLIM mutations are associated with intellectual disability and several congenital malformations in boys. In mice, RLIM is thought to be nonessential for embryos development. Using a mouse model in which Rlim is deleted, we show that 50% of males carrying the deletion display respiratory distress and die short after birth. No congenital malformations mimicking the human phenotype have been observed. Histological analysis of lung samples show that Rlim is critical for late lung development and maturation. The analysis of lung samples by western blot, a technique that quantifies proteins, is consistent with a dysregulation of BMP pathway. These finding confirm the importance of RLIM for murine embryos development and provide a link between human RLIM pathology and BMP pathway.

genetics↗

bioRxiv2018

The 22q11 low copy repeats are characterized by unprecedented size and structure variability

AbstractLow copy repeats (LCRs) are recognized as a significant source of genomic instability, driving genome variability and evolution. The chromosome 22 LCRs (LCR22s) are amongst the most complex regions in the genome and their structure remains unresolved. These LCR22s mediate non-allelic homologous recombination (NAHR) leading to the 22q11 deletion syndrome (22q11DS), causing the most frequent genomic disorder. Using fiber FISH optical mapping, we have de novo assembled the LCR22s in 33 cell lines. We observed a high level of variation in LCR22 structures, including 26 different haplotypes of LCR22A with alleles ranging from 250 Kb to over 2,000 Kb. An additional four haplotypes were detected using Bionano mapping. Further, Bionano maps generated from 154 individuals from different populations suggested significantly different LCR22 haplotype frequencies between populations. Furthermore, haplotype analysis in nine 22q11DS patients resulted in the localization of the NAHR site to a 160 Kb paralog between LCR22A and -D in seven patients and to a 31 Kb region in two individuals with a rearrangement between LCR22A and -B.. This 31 Kb region contains a palindromic AT-rich repeat known to be a driver of chromosomal rearrangements. Our study highlights an unprecedented level of polymorphism in the structure of LCR22s, which are likely still evolving. We present the most comprehensive map of LCR22 variation to date, paving the way towards investigating the role of LCR variation as a driver of 22q11 rearrangements and the phenotypic variability in 22q11DS patients as well as in the general population.

genomics↗