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 enriched for rare variants in early-onset patients. This region that was missed by standard sliding windows procedures is included in a TAD region that contains a strong candidate gene. RAVA-FIRST enables new investigations of rare non-coding variants in complex diseases, facilitated by its implementation in the R package Ravages.

RAVAQ: An integrative pipeline from quality control to region-based rare variant association analysis.

Next-generation sequencing technologies have opened up the possibility to sequence large samples of cases and controls to test for association with rare variants. To limit cost and increase sample sizes, data from controls could be used in multiple studies and might thus be generated on different sequencing platforms. This could pose some problems of comparability between cases and controls due to batch effects that could be confounding factors, leading to false-positive association signals. To limit batch effects and ensure comparability of datasets, stringent quality controls are required. We propose an integrative five-steps pipeline, RAVAQ, that (a) performs a specific three-step quality control taking into account the case-control status to ensure data comparability, (b) selects qualifying variants as defined by the user, and (c) performs rare variant association tests per genomic region. The RAVAQ pipeline is wrapped in an R package. It is user-friendly and flexible in its arguments to adapt to the specificity of each research project. We provide examples showing how RAVAQ improves rare variant association tests. The default RAVAQ quality control outperformed the widely used Variant Quality Score Recalibration method, removing inflation due to spurious signals. RAVAQ is open source and freely available at https://gitlab.com/gmarenne/ravaq.

End-Truncated LAMB1 Causes a Hippocampal Memory Defect and a Leukoencephalopathy.

OBJECTIVE: The majority of patients with a familial cerebral small vessel disease (CSVD) referred for molecular screening do not show pathogenic variants in known genes. In this study, we aimed to identify novel CSVD causal genes. METHODS: We performed a gene-based collapsing test of rare protein-truncating variants identified in exome data of 258 unrelated CSVD patients of an ethnically matched control cohort and of 2 publicly available large-scale databases, gnomAD and TOPMed. Western blotting was used to investigate the functional consequences of variants. Clinical and magnetic resonance imaging features of mutated patients were characterized. RESULTS: We showed that LAMB1 truncating variants escaping nonsense-mediated messenger RNA decay are strongly overrepresented in CSVD patients, reaching genome-wide significance (p < 5 × 10-8 ). Using 2 antibodies recognizing the N- and C-terminal parts of LAMB1, we showed that truncated forms of LAMB1 are expressed in the endogenous fibroblasts of patients and trapped in the cytosol. These variants are associated with a novel phenotype characterized by the association of a hippocampal type episodic memory defect and a diffuse vascular leukoencephalopathy. INTERPRETATION: These findings are important for diagnosis and clinical care, to avoid unnecessary and sometimes invasive investigations, and also from a mechanistic point of view to understand the role of extracellular matrix proteins in neuronal homeostasis. ANN NEUROL 2021;90:962-975.

Whole exome sequencing, a hypothesis-free approach to investigate recurrent early miscarriage.

RESEARCH QUESTION: Are there genetic determinants shared by unrelated women with unexplained recurrent early miscarriage (REM)? DESIGN: Thirty REM cases and 30 controls were selected with extreme phenotype among women from Eastern Brittany (France), previously enrolled in an incident case-control study on thrombophilic mutations. Cases and controls were selected based on the number of early miscarriages or live births, respectively. Peripheral blood was collected for DNA extraction at initial visit. The burden of low-frequency variants in the coding part of the genes was compared using whole exome sequencing (WES). RESULTS: Cases had 3 to 17 early miscarriages (20 cases: ≥5 previous losses). Controls had 1 to 4 live births (20 controls: ≥3 previous live births) and no miscarriages. WES data were available for 29 cases and 30 controls. A total of 209,387 variants were found (mean variant per patient: 59,073.05) with no difference between groups (P = 0.68). The top five most significantly associated genes were ABCA4, NFAM1, TCN2, AL078585.1 and EPS15. Previous studies suggest the involvement of vitamin B12 deficiency in REM. TCN2 encodes for vitamin B12 transporter into cells. Therefore, holotranscobalamin (active vitamin B12) was measured for both cases and controls (81.2 ± 32.1 versus 92.9 ± 34.3 pmol/l, respectively, P = 0.186). Five cases but no controls were below 50 pmol/l (P = 0.052). CONCLUSIONS: This study highlights four new genes of interest in REM, some of which belong to known networks of genes involved in embryonic development (clathrin-mediated endocytosis and ciliary pathway). The study also confirms the involvement of TCN2 (vitamin B12 pathway) in the early first trimester of pregnancy.

Rare variant association testing for multicategory phenotype.

Genetic association studies have provided new insights into the genetic variability of human complex traits with a focus mainly on continuous or binary traits. Methods have been proposed to take into account disease heterogeneity between subgroups of patients when studying common variants but none was specifically designed for rare variants. Because rare variants are expected to have stronger effects and to be more heterogeneously distributed among cases than common ones, subgroup analyses might be particularly attractive in this context. To address this issue, we propose an extension of burden tests by using a multinomial regression model, which enables association tests between rare variants and multicategory phenotypes. We evaluated the type I error and the power of two burden tests, CAST and WSS, by simulating data under different scenarios. In the case of genetic heterogeneity between case subgroups, we showed an advantage of multinomial regression over logistic regression, which considers all the cases against the controls. We replicated these results on real data from Moyamoya disease where the burden tests performed better when cases were stratified according to age-of-onset. We implemented the functions for association tests in the R package "Ravages" available on Github.

GEMPROT: visualization of the impact on the protein of the genetic variants found on each haplotype.

SUMMARY: When analyzing sequence data, genetic variants are considered one by one, taking no account of whether or not they are found in the same individual. However, variant combinations might be key players in some diseases as variants that are neutral on their own can become deleterious when associated together. GEMPROT is a new analysis tool that allows, from a phased vcf file, to visualize the consequences of the genetic variants on the protein. At the level of an individual, the program shows the variants on each of the two protein sequences and the Pfam functional protein domains. When data on several individuals are available, GEMPROT lists the haplotypes found in the sample and can compare the haplotype distributions between different sub-groups of individuals. By offering a global visualization of the gene with the genetic variants present, GEMPROT makes it possible to better understand the impact of combinations of genetic variants on the protein sequence. AVAILABILITY AND IMPLEMENTATION: GEMPROT is freely available at https://github.com/TaniaCuppens/GEMPROT. An on-line version is also available at http://med-laennec.univ-brest.fr/GEMPROT/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Assemble: an interactive graphical tool to analyze and build RNA architectures at the 2D and 3D levels.

SUMMARY: Assemble is an intuitive graphical interface to analyze, manipulate and build complex 3D RNA architectures. It provides several advanced and unique features within the framework of a semi-automated modeling process that can be performed by homology and ab initio with or without electron density maps. Those include the interactive editing of a secondary structure and a searchable, embedded library of annotated tertiary structures. Assemble helps users with performing recurrent and otherwise tedious tasks in structural RNA research. AVAILABILITY AND IMPLEMENTATION: Assemble is released under an open-source license (MIT license) and is freely available at http://bioinformatics.org/assemble. It is implemented in the Java language and runs on MacOSX, Linux and Windows operating systems.

RNA structure: bioinformatic analysis.

The range of functions ascribed to RNA molecules has grown considerably during recent years. Consequently, the analysis and comparison of RNA sequences have become recurrent tasks in molecular biology. Because the biological function of an RNA is expressed more by its folded architecture than by its sequence, original computational tools adapted to the multifaceted RNA functions have to be developed. Such tools, recently published, enable a user to solve classical problems related to RNA research: constructing 'structural' multiple alignments, inferring complete structures and structural motifs from RNA alignments, or searching structural homology in genomic databases.