Biology subjects

Bureau, A.

Publications and source records attributed to Bureau, A..

6 recordsLinked to original sources

bioRxiv2026

The reliability and accuracy of recombination inferred by Shapeit2 duoHMM on whole genome sequence

Few studies assessed the performance of population-based phasing combined with parental genotypes to infer recombination on whole genome sequence (WGS) data. In this study, our objective was to evaluate whether Shapeit2 duoHMM, a Hidden Markov Model using parental genotypes, infers recombination events reliably on WGS and with narrower intervals than SNP arrays. We based our analysis on the overlap between recombination events inferred by Merlin on SNP genotypes and Shapeit2 on WGS and SNP genotypes. We used a sample of 61 extended families from the GeneSTAR study with TopMED freeze 8 WGS on 580 sequenced subjects (60% of sample). Shapeit2 was run with a window size of 500 kilobases and 200 states on WGS. To mimic a SNP array, we extracted genotypes of 355,112 autosomal markers on the Illumina OmniExpress array. The number of recombination events per meiosis inferred by Shapeit2 on the WGS data (36.8) was aligned with the expected numbers over autosomes (35.7), although Merlin overestimated this number (115.0). 73% of Shapeit2 recombination events on WGS were detected by Merlin, a proportion rising to 91% when restricting to events also inferred by Shapeit2 on OmniExpress genotypes. Furthermore, Shapeit2 recombination intervals were narrower on WGS than OmniExpress genotypes (median of 4,530 bp vs. 49,458 bp). This suggests that Shapeit2 on WGS is a reliable and accurate method for inferring recombination events.

genomics↗

bioRxiv2023

Statistics to prioritize rare variants in family-based sequencing studies with disease subtypes

Family-based sequencing studies are increasingly used to find rare genetic variants of high risk for disease traits with familial clustering. In some studies, families with multiple disease subtypes are collected and the exomes of affected relatives are sequenced for shared rare variants. Since different families can harbor different causal variants and each family harbors many rare variants, tests to detect causal variants can have low power in this study design. Our goal is rather to prioritize shared variants for further investigation by, e.g., pathway analyses or functional studies. The transmission-disequilibrium test prioritizes variants based on departures from Mendelian transmission in parent-child trios. Extending this idea to families, we propose methods to prioritize rare variants shared in affected relatives with two disease subtypes, with one subtype more heritable than the other. Global approaches condition on a variant being observed in the study and assume a known probability of carrying a causal variant. In contrast, local approaches condition on a variant being observed in specific families to eliminate the carrier probability. Our simulation results indicate that global approaches are robust to mis-specification of the carrier probability and prioritize more effectively than local approaches even when the carrier probability is misspecified.

genetics↗

bioRxiv2022

CTCF mediates the Activity-by-contact derived cis-regulatory hubs

The 3D chromatin architecture establishes a complex network of genes and regulatory elements necessary for transcriptomic regulation in development and disease. This network can be modelled by cis-regulatory hubs (CRH), which underscore the local functional interactions between enhancers and promoter regions and differ from other higher-order chromatin structures such as topologically associated domains (TAD). The Activity-by-contact (ABC) model of enhancer-promoter regulation has been recently used in the identification of these CRHs, but little is known about the role of CTCF on the ABC scores and the consequent impact on CRHs. Here we show that the loss of CTCF leads to a reorganization of the ABC-derived rankings of the putative enhancers in the mouse heart, a global reduction of the total number of CRHs and an increase in the size of the CRHs. Furthermore, CTCF loss leads to a higher percentage of CRHs that cross TAD boundaries. These results provide another layer of evidence to support the importance of CTCF in the formation of regulatory networks necessary for gene regulation. SummaryDeletion of CTCF in mouse cardiomyocytes led to reorganization of the activity-by-contact scores of the heart enhancers and changes in the cis-regulatory hubs

molecular biology↗

bioRxiv2022

RetroFun-RVS: a retrospective family-based framework for rare-variant analysis incorporating functional annotations

A large proportion of genetic variations involved in complex diseases are rare and located within non-coding regions, making the interpretation of underlying biological mechanisms a daunting task. Although technical and methodological progresses have been made to annotate the genome, current disease - rare-variant association tests incorporating such annotations suffer from two major limitations. Firstly, they are generally restricted to case-control designs of unrelated individuals, which often require tens or hundreds of thousands of individuals to achieve sufficient power. Secondly, they were not evaluated with region-based annotations needed to interpret the causal regulatory mechanisms. In this work we propose RetroFun-RVS, a new retrospective family-based score test, incorporating functional annotations. One of the critical features of the proposed method is to aggregate genotypes while measuring rare variant sharing among affected family members to compute the test statistic. Through extensive simulations, we have demonstrated that RetroFun-RVS integrating networks based on 3D genome contacts as functional annotations reaches greater power over the region-wide test, other strategies to include sub-regions and competing methods. Also, the proposed framework shows robustness to non-informative annotations, keeping a stable power when causal variants are spread across regions. We provide recommendations when dealing with different types of annotations or family structures commonly encountered in practice. Application of RetroFun-RVS is illustrated on whole genome sequence in the Eastern Quebec Schizophrenia and Bipolar Disorder Kindred Study with networks constructed from 3D contacts and epigenetic data on neurons. In summary we argue that RetroFun-RVS, by allowing integration of functional annotations corresponding to regions or networks with transcriptional impacts, is a useful framework to highlight regulatory mechanisms involved in complex diseases.

genetics↗

bioRxiv2021

Cis-Regulatory Hubs: a Relevant 3D Model to Study the Genetics of Complex Diseases with an Application to Schizophrenia

The 3-dimensional (3D) conformation of the chromatin creates complex networks of noncoding regulatory regions (distal elements) and promoters impacting gene regulation. Despite the importance of the role of noncoding regions in complex diseases, little is known about their interplay within regulatory hubs and implication in multigenic diseases like schizophrenia. Here we show that cis-regulatory hubs (CRHs) in neurons highlight functional interactions between distal elements and promoters, providing a model to explain epigenetic mechanisms involved in complex diseases. CRHs represent a new 3D model, where distal elements interact to create a complex network of active genes. In a disease context, CRHs highlighted strong enrichments in schizophrenia-associated genes, schizophrenia-associated SNPs and schizophrenia heritability compared to equivalent structures. Finally, CRHs exhibit larger proportions of genes differentially expressed in schizophrenia compared to promoter-distal element pairs or TADs. CRHs thus capture causal regulatory processes improving the understanding of complex disease etiology such as schizophrenia. These multiple lines of genetic and statistical evidence support CRHs as 3D models to study dysregulation of gene expression in complex diseases more generally. Summary BlurbGenes and their regulatory elements are organized within 3D networks in neurons which model functional structures and explain schizophrenia genetic etiology.

genetics↗

bioRxiv2018

Inferring Disease Risk Genes from Sequencing Data in Multiplex Pedigrees Through Sharing of Rare Variants

We previously demonstrated how sharing of rare variants (RVs) in distant affected relatives can be used to identify variants causing a complex and heterogeneous disease. This approach tested whether single RVs were shared by all sequenced affected family members. However, as with other study designs, joint analysis of several RVs (e.g. within genes) is sometimes required to obtain sufficient statistical power. Further, phenocopies can lead to false negatives for some causal RVs if complete sharing among affecteds is required. Here we extend our methodology (Rare Variant Sharing, RVS) to address these issues. Specifically, we introduce gene-based analyses, refine RV definition based on haplotypes, and introduce a partial sharing test based on RV sharing probabilities for subsets of affected family members. RVS also has the desirable features of not requiring external estimates of variant frequency or control samples, provides functionality to assess and address violations of key assumptions, and is available as open source software for genome-wide analysis. Simulations including phenocopies, based on the families of an oral cleft study, revealed the partial and complete sharing versions of RVS achieved similar statistical power compared to alternative methods (RareIBD and the Gene-Based Segregation Test), and had superior power compared to the pedigree Variant Annotation, Analysis and Search Tool (pVAAST) linkage statistic. In studies of multiplex cleft families, analysis of rare single nucleotide variants in the exome of 151 affected relatives from 54 families revealed no significant excess sharing in any one gene, but highlighted different patterns of sharing revealed by the complete and partial sharing tests.

genetics↗