Biology subjects

Vilain, E.

Publications and source records attributed to Vilain, E..

10 recordsLinked to original sources

bioRxiv2026

Building an Interoperable Rare Disease Multi-omic Resource: The GREGoR Data Model and Dataset

Rare disease research and diagnosis rely on the integration of genomic and phenotypic data generated across diverse clinical sites; however, the absence of widely adopted standards for representing genomic data and associated metadata has limited data interoperability, reuse, and cross-study analysis. The Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) Consortium was established to investigate challenging rare disease cases and evaluate emerging multi-omic technologies for clinical translation. To support coordinated data integration across distributed research sites, we developed a common Consortium Data Model in partnership with domain experts to standardize the capture of participant-, family-, phenotype- and assay-level metadata, with a particular emphasis on using a modular architecture to support linking of multiple data versions from multiple omic technologies to a single individual and attribution of a genetic finding to the specific technology used for its initial discovery. Adoption of the GREGoR Data Model has enabled continued generation and public release of a harmonized, analysis-ready Consortium Dataset. The most recent release includes phenotypic, family and multi-omic data from 12,292 participants in 5,029 families. Other rare disease data sharing efforts are beginning to adopt this data model which will facilitate cross consortium analyses and empower rare disease research. This work demonstrates that a collaborative, flexible, and scalable data model can enable large-scale rare disease research, facilitate cross-center data harmonization, and enable data interoperability.

genomics↗

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

Development and Implementation of Novel Chatbot-based Genomic Research Consent

ObjectiveTo conduct a retrospective analysis comparing traditional human-based consenting to an automated chat-based consenting process. Materials and MethodsWe developed a new chat-based consent using our IRB-approved consent forms. We leveraged a previously developed platform (Gia(R), or "Genetic Information Assistant") to deliver the chat content to candidate participants. The content included information about the study, educational information, and a quiz to assess understanding. We analyzed 144 families referred to our study during a 6-month time period. A total of 37 families completed consent using the traditional process, while 35 families completed consent using Gia. ResultsEngagement rates were similar between both consenting methods. The median length of the consent conversation was shorter for Gia users compared to traditional (44 vs. 76 minutes). Additionally, the total time from referral to consent completion was faster with Gia (5 vs. 16 days). Within Gia, understanding was assessed with a 10-question quiz that most participants (96%) passed. Feedback about the chat consent indicated that 86% of participants had a positive experience. DiscussionUsing Gia resulted in time savings for both the participant and study staff. The chatbot enables studies to reach more potential candidates. We identified five key features related to human-centered design for developing a consent chat. ConclusionThis analysis suggests that it is feasible to use an automated chatbot to scale obtaining informed consent for a genomics research study. We further identify a number of advantages when using a chatbot.

genetics↗

bioRxiv2022

Reprograming human fibroblasts into Sertoli cells: a tool for personalized medicine

Disorders/Differences of Sex Development (DSD) are congenital conditions in which the development of chromosomal, gonadal, or anatomical sex is atypical. With overlapping phenotypes and multiple genes involved, poor diagnostic yields are achieved for many of these conditions. The current DSD diagnostic regimen can be augmented by investigating transcriptome/proteome in vivo, but it is hampered by the unavailability of affected gonadal tissue at the relevant developmental stage. We try to mitigate this limitation by reprogramming readily available skin tissue-derived dermal fibroblasts into Sertoli cells (SC), which could then be deployed for different diagnostic strategies. SCs form the target cell type of choice because they act like an organizing center of embryonic gonadal development and many DSD arise when these developmental processes go awry. We employed a computational predictive algorithm for cell conversions called Mogrify to predict the transcription factors (TFs) required for direct reprogramming of human dermal fibroblasts into SCs. We established trans-differentiation culture conditions where stable transgenic expression of these TFs was achieved in 46, XY adult dermal fibroblasts using lentiviral vectors. The resulting Sertoli like cells (SLCs) were validated for SC phenotype using several approaches. SLCs exhibited Sertoli-like morphological and cellular properties as revealed by morphometry and xCelligence cell behavior assays. They also showed Sertoli-specific expression of molecular markers such as SOX9, PTGDS, BMP4, or DMRT1 as revealed by IF imaging, RNAseq and qPCR. The SLC transcriptome shared about two thirds of its differentially expressed genes with a human adult SC transcriptome and expressed markers typical of embryonic SCs. Notably, SLCs lacked expression of markers of other gonadal cell types such as Leydig, germ, peritubular myoid or granulosa cells. The trans-differentiation method was applied to a variety of commercially available 46, XY fibroblasts derived from patients with DSD and to a 46, XX cell line. The DSD SLCs displayed altered levels of trans-differentiation in comparison to normal 46, XY-derived SLCs, thus showcasing the robustness of this new trans-differentiation model.

cell biology↗

bioRxiv2022

Identification of differential hypothalamic DNA methylation and gene expression associated with sexual partner preferences in rams

The sheep is a valuable model to test whether hormone mechanisms that sexually differentiate the brain underlie the expression of sexual partner preferences because as many as 8% of rams prefer same-sex partners. Epigenetic factors such as DNA methylation act as mediators in the interaction between steroid hormones and the genome. Variations in the epigenome could be important in determining morphological or behavior differences among individuals of the same species. In this study, we explored DNA methylation differences in the hypothalamus of male oriented rams (MORs) and female oriented rams (FORs). We employed reduced representation bisulfite sequencing (RRBS) to generate a genome-wide map of DNA methylation and RNA-Seq to profile the transcriptome. We found substantial DNA methylation and gene expression differences between FORs and MORs. Although none of the differentially methylated genes yielded significant functional terms directly associated with sex development, three differentially expressed genes were identified that have been associated previously with sexual behaviors. We hypothesize that these differences are involved in the phenotypic variation in ram sexual partner preferences, whereas future studies will have to find the specific mechanisms. Our results add an intriguing new dimension to sheep behavior that should be useful for further understanding epigenetic and transcriptomic involvement.

neuroscience↗

bioRxiv2021

Benchmarking long-read genome sequence alignment tools for human genomics applications

BackgroundThe utility of long-read genome sequencing platforms has been shown in many fields including whole genome assembly, metagenomics, and amplicon sequencing. Less clear is the applicability of long reads to reference-guided human genomics, the foundation of genomic medicine. Here, we benchmark available platform-agnostic alignment tools on datasets from nanopore and single-molecule real-time platforms to understand their suitability in producing a genome representation. ResultsFor this study, we leveraged publicly-available data from sample NA12878 generated on Oxford Nanopore and sample NA24385 on Pacific Biosciences platforms. Each tool that was benchmarked, including GraphMap2, LRA, Minimap2, NGMLR, and Winnowmap2 produced the same alignment file each time. However, the different tools widely disagreed on which reads to leave unaligned, affecting the end genome coverage and the number of discoverable breakpoints. Minimap2 and winnowmap2 were computationally lightweight enough for use at scale. No alignment from one tool independently resolved all large structural variants (10,000-100,000 basepairs) present in the Database of Genome Variants (DGV) for sample NA12878 or the truthset for NA24385. ConclusionsIt should be best practice to use an analysis pipeline that generates alignments with both minimap2 and winnowmap2 as both are lightweight and yield different views of the genome. If computational resources and time are not a factor for a given case or experiment, a third representation from NGMLR will provide another view, and another chance to resolve a case. LRA, while fast, did not work on the nanopore data for our cluster, but PacBio results were promising in that those computations completed faster than Mininmap2. Graphmap2 is not an ideal tool for exploration of a whole human genome generated on a long-read sequencing platform.

bioinformatics↗

bioRxiv2021

Long Reads Capture Simultaneous Enhancer-Promoter Methylation Status for Cell-type Deconvolution

MotivationWhile promoter methylation is associated with reinforcing fundamental tissue identities, the methylation status of distant enhancers was shown by genome-wide association studies to be a powerful determinant of cell-state and cancer. With recent availability of long-reads that report on the methylation status of enhancer-promoter pairs on the same molecule, we hypothesized that probing these pairs on the single-molecule level may serve the basis for detection of rare cancerous transformations in a given cell population. We explore various analysis approaches for deconvolving cell-type mixtures based on their genome-wide enhancer-promoter methylation profiles. ResultsTo evaluate our hypothesis we examine long-read optical methylome data for the GM12787 cell line and myoblast cell lines from two donors. We identified over 100,000 enhancer-promoter pairs that co-exist on at least 30 individual DNA molecules per pair. We developed a detailed methodology for mixture deconvolution and applied it to estimate the proportional cell compositions in synthetic mixtures based on analyzing their enhancer-promoter pairwise methylation. We found our methodology to lead to very accurate estimates, outperforming our promoter-based deconvolutions. Moreover, we show that it can be generalized from deconvolving different cell types to subtle scenarios where one wishes to deconvolve different cell populations of the same cell-type. AvailabilityThe code used in this work to analyze single-molecule Bionano Genomics optical maps is available via the GitHub repository https://github.com/ebensteinLab/Single_molecule_methylation_in_EP. Contactuv@post.tau.ac.il (Y.E), roded@tauex.tau.ac.il (R.S)

bioinformatics↗

bioRxiv2020

nanotatoR: A tool for enhanced annotation of genomic structural variants

Whole genome sequencing is effective at identification of small variants but, because it is based on short reads, assessment of structural variants (SVs) is limited. The advent of Optical Genome Mapping (OGM), which utilizes long fluorescently labeled DNA molecules for de novo genome assembly and SV calling, has allowed for increased sensitivity and specificity in SV detection. However, compared to small variant annotation tools, OGM-based SV annotation software has seen little development, and currently available SV annotation tools do not provide sufficient information for determination of variant pathogenicity. We developed an R-based package, nanotatoR, which provides comprehensive annotation as a tool for SV classification. nanotatoR uses both external (DGV; DECIPHER; Bionano Genomics BNDB) and internal (user-defined) databases to estimate SV frequency. Human genome reference GRCh37/38-based BED files are used to annotate SVs with overlapping, upstream, and downstream genes. Overlap percentages and distances for nearest genes are calculated and can be used for filtration. A primary gene list is extracted from public databases based on the patients phenotype and used to filter genes overlapping SVs, providing the analyst with an easy way to prioritize variants. If available, expression of overlapping or nearby genes of interest is extracted (e.g. from an RNA-Seq dataset, allowing the user to assess the effects of SVs on the transcriptome). Most quality-control filtration parameters are customizable by the user. The output is given in an Excel file format, subdivided into multiple sheets based on SV type and inheritance pattern (INDELs, inversions, translocations, de novo, etc.). nanotatoR passed all quality and run time criteria of Bioconductor, where it was accepted in the April 2019 release. We evaluated nanotatoRs annotation capabilities using publicly available reference datasets: the singleton sample NA12878, mapped with two types of enzyme labeling, and the NA24143 trio. nanotatoR was also able to accurately filter the known pathogenic variants in a cohort of patients with Duchenne Muscular Dystrophy for which we had previously demonstrated the diagnostic ability of OGM. The extensive annotation enables users to rapidly identify potential pathogenic SVs, a critical step toward use of OGM in the clinical setting.

bioinformatics↗

bioRxiv2018

DEAH-box helicase 37 (DHX37) defects are a novel molecular etiology of 46,XY gonadal dysgenesis spectrum

46,XY gonadal dysgenesis is a heterogeneous disorder of sex development (DSD) that features abnormal gonadal development and varying degrees of undervirilization of the external genitalia, ranging from micropenis to female-like genitalia. Embryonic testicular regression syndrome (ETRS; MIM: 273250) is considered part of the clinical spectrum of 46,XY gonadal dysgenesis. Most ETRS patients present micropenis or atypical genitalia associated with a complete absence of gonadal tissue in one or both sides. In most patients with gonadal dysgenesis, the genetic diagnosis is unclear. We performed whole exome sequencing in ETRS patients and identified a rare variant, the p.Arg308Gln, in DEAH (Asp-Glu-Ala-His) box polypeptide 37 (DHX37) in 5 affected individuals from three unrelated families. We expanded the analysis of DHX37 coding region to additional 71 patients with 46,XY gonadal dysgenesis and identified the p.Arg308Gln and three other DHX37 missense variants (p.Arg151Trp, p.Thr304Met and p.Arg674Trp) in 11 affected members from eight distinct families (8 patients with ETRS, two with partial gonadal dysgenesis and one 46,XY DSD female patient previously gonadectomized). The p.Arg308Gln and p.Arg674Trp recurrent variants were identified in six and three families, respectively. Segregation analysis revealed sex-limited autosomal dominant inheritance in 4 families, autosomal dominant with incomplete penetrance in one family and autosomal recessive in another family. Immunohistochemical analysis of normal testes revealed that DHX37 is expressed in germ cells at different stages of maturation.\n\nThis study demonstrates an expressive frequency of rare predicted to be deleterious DHX37 variants in 46,XY gonadal dysgenesis group, particularly those individuals exhibiting the ETRS phenotype (25% and 50%, respectively).\n\nOur findings indicate that DHX37 is a new player in the complex cascade of male gonadal differentiation and maintenance, thus establishing a novel and frequent molecular etiology for 46,XY gonadal dysgenesis spectrum, mainly for embryonic testicular regression syndrome.

developmental biology↗

bioRxiv2018

Programmatic Detection of Diploid-Triploid Mixoploidy via Whole Genome Sequencing

PurposeMixoploidy is a type of mosaicism where an organism is a mixture of cells with different numbers of chromosomes. There are a broad range of phenotypes associated with mixoploidy that vary greatly depending on the fraction of cells that are non-diploid, their chromosome number, their distribution, and presumably the specific variation present in the patient. Clinical detection of mixoploidy is important for diagnosis.\n\nMethodsWe developed a method to detect mixoploidy from clinical whole genome sequencing (WGS) data through the identification of excess of variant calls centered on unusual B-allele frequencies. Our method isolates the signal from these variants using trio calls and then solves a basic linear equation to estimate levels of diploid-triploid mixoploidy within the sample.\n\nResultsWe show that our method reflects the results from a cytogenetic test. We provide examples detailing how our method has been used to identify diploid-triploid mixoploid individuals from within the NIH Undiagnosed Diseases Network. We present confirmatory findings obtained by clinical cytogenetic testing and show that our method can be used to identify the diploid-triploid ratio in these cases.\n\nConclusionWGS data from patients with rare diseases can be used to identify mixoploid individuals. Individuals with certain characteristics as discussed should be tested for mixoploidy as part of standard clinical pipeline procedures. Scripts that perform this calculation are publicly available at https://github.com/HudsonAlpha/mixoviz.

genomics↗