Biology subjects

Morange, P.-E.

Publications and source records attributed to Morange, P.-E..

5 recordsLinked to original sources

bioRxiv2021

Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score

Rare variant association tests (RVAT) have been developed to study the contribution of rare variants widely accessible through high-throughput sequencing technologies. RVAT require to aggregate rare variants in testing units and to filter variants to retain only the most likely causal ones. In the exome, genes are natural testing units and variants are usually filtered based on their functional consequences. However, when dealing with whole-genome sequence (WGS) data, both steps are challenging. No natural biological unit is available for aggregating rare variants. Sliding windows procedures have been proposed to circumvent this difficulty, however they are blind to biological information and result in a large number of tests. We propose a new strategy to perform RVAT on WGS data: "RAVA-FIRST" (RAre Variant Association using Functionally-InfoRmed STeps) comprising three steps. (1) New testing units are defined genome-wide based on functionally-adjusted Combined Annotation Dependent Depletion (CADD) scores of variants observed in the GnomAD populations, which are referred to as "CADD regions". (2) A region-dependent filtering of rare variants is applied in each CADD region. (3) A functionally-informed burden test is performed with sub-scores computed for each genomic category within each CADD region. Both on simulations and real data, RAVA-FIRST was found to outperform other WGS-based RVAT. Applied to a WGS dataset of venous thromboembolism patients, we identified an intergenic region on chromosome 18 that is enriched for rare variants in early-onset patients and that was that was missed by standard sliding windows procedures. RAVA-FIRST enables new investigations of rare non-coding variants in complex diseases, facilitated by its implementation in the R package Ravages. Author SummaryTechnological progresses have made possible whole genome sequencing at an unprecedented scale, opening up the possibility to explore the role of genetic variants of low frequency in common diseases. The challenge is now methodological and requires the development of novel methods and strategies to analyse sequencing data that are not limited to assessing the role of coding variants. With RAVA-FIRST, we propose a novel strategy to investigate the role of rare variants in the whole-genome that takes benefit from biological information. Especially, RAVA-FIRST relies on testing units that go beyond genes to gather rare variants in the association tests. In this work, we show that this new strategy presents several advantages compared to existing methods. RAVA-FIRST offers an easy and straightforward analysis of genome-wide rare variants, especially the intergenic ones which are frequently left behind, making it a promising tool to get a better understanding of the biology of complex diseases.

genetics↗

bioRxiv2020

Long-read sequencing resolves structural variants in SERPINC1 causing antithrombin deficiency and identifies a complex rearrangement and a retrotransposon insertion not characterized by routine diagnostic methods

The identification and characterization of structural variants (SVs) in clinical genetics have remained historically challenging as routine genetic diagnostic techniques have limited ability to evaluate repetitive regions and SVs. Long-read whole-genome sequencing (LR-WGS) has emerged as a powerful approach to resolve SVs. Here, we used LR-WGS to study 19 unrelated cases with type I Antithrombin Deficiency (ATD), the most severe thrombophilia, where routine molecular tests were either negative, ambiguous, or not fully characterized. We developed an analysis workflow to identify disease-associated SVs and resolved 10 cases. For the first time, we identified a germline complex rearrangement involved in ATD previously misclassified as a deletion. Additionally, we provided molecular diagnoses for two unresolved individuals that harbored a novel SINE-VNTR-Alu retroelement insertion that we fully characterized by de novo assembly and confirmed by PCR amplification in all affected relatives. Finally, the nucleotide-level resolution achieved for all the SVs allowed breakpoint analysis, which revealed a replication-based mechanism for most of the cases. Our study underscores the utility of LR-WGS as a complementary diagnostic method to identify, characterize, and unveil the molecular mechanism of formation of disease-causing SVs, and facilitates decision making about long-term thromboprophylaxis in ATD patients.

genomics↗

bioRxiv2020

MORFEE: a new tool for detecting and annotating single nucleotide variants creating premature ATG codons from VCF files

SummaryVariants in 5UTR regions that create upstream translation initiation AUG codons are a class of neglected non coding variations. When they associate with a premature stop codon and create upstream open reading frames (uORFs) whose translation competes with that of natural proteins, they can have strong impact on human diseases. We here describe MORFEE, a new bioinformatics tool that detects, annotates and predicts, from a standard VCF file, the creation of uORF by any 5UTR variants on uORF creation. MORFEE was applied to two genomic resources and identified candidate functional variants that could explain statistical association signals observed in the context of Genome Wide Association Studies or could be responsible for rare forms of diseases. In conclusion MORFEE is an easy-to-use tool complementary to existing ones that can help resolving genetic investigations that remained so far unfruitful. Availability and implementationMORFEE is written in R with code and package available at https://github.com/daissi/MORFEE. Contactdavid-alexandre.tregouet@inserm.fr; david-alexandre.tregouet@u-bordeaux.fr

bioinformatics↗

bioRxiv2020

A novel rare c. -39C>T mutation in the PROS1 5'UTR causing PS deficiency by creating a new upstream translation initiation codon and inhibiting the production of the natural protein.

Inherited Protein S deficiency (PSD) (MIM176880) is a rare automosal dominant disorder caused by rare mutations, mainly located in the coding sequence of the structural PROS1 gene, and associated with an increased risk of venous thromboembolism. To identify the molecular defect underlying PSD observed in an extended French pedigree with 7 PSD affected members in who no candidate deleterious PROS1 mutation was detected by Sanger sequencing of PROS1 exons and their flanking intronic regions or via a MLPA approach, a whole genome sequencing strategy was adopted. This led to the identification of a never reported C to T substitution at c.-39 from the natural ATG codon of the PROS1 gene that completely segregates with PSD in the whole family. This substitution ACG->ATG creates a new start codon upstream of the main ATG. We experimentally demonstrated that the variant generates a novel overlapping ORF and inhibits the translation of the wild type protein from the main ORF in HeLa cells. This work describes the first example of 5UTR PROS1 mutation causing PSD through the creation of an upstream ORF, a mutation that is not predicted to be deleterious by standard annotation softwares.

genetics↗

bioRxiv2018

OPTIMIR, a novel algorithm for integrating available genome-wide genotype data into miRNA sequence alignment analysis.

Next-generation sequencing is an increasingly popular and efficient approach to characterize the full set of microRNAs (miRNAs) present in human biosamples. MiRNAs detection and quantification still remain a challenge as they can undergo different post transcriptional modifications and might harbor genetic variations (polymiRs) that may impact on the alignment step. We present a novel algorithm, OPTIMIR, that incorporates biological knowledge on miRNA editing and genome-wide genotype data available in the processed samples to improve alignment accuracy. OPTIMIR was applied to 391 human plasma samples that had been typed with genome-wide genotyping arrays. OPTIMIR was able to detect genotyping errors, suggested the existence of novel miRNAs and highlighted the allelic imbalance expression of polymiRs in heterozygous carriers. OPTIMIR is written in python, and freely available on the GENMED website (http://www.genmed.fr/index.php/fr/) and on Github (github.com/FlorianThibord/OptimiR).

bioinformatics↗