Biology subjects

Bourque, G.

Publications and source records attributed to Bourque, G..

36 records · Page 2Linked to original sources

bioRxiv2022

Selection for immune evasion in SARS-CoV-2 revealed by high-resolution epitope mapping combined with genome sequence analysis

A deeper understanding of the molecular determinants that drive humoral responses to coronaviruses, and in particular severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is critical for improving and developing diagnostics, therapies and vaccines. Moreover, viral mutations can change key antigens in a manner that alters the ability of the immune system to detect and clear infections. In this study, we exploit a deep serological profiling strategy coupled with an integrated, computational framework for the analysis of SARS-CoV-2 humoral immune responses of asymptomatic or recovered COVID-19-positive patients relative to COVID-19-negative patients. We made use of a novel high-density peptide array (HDPA) spanning the entire proteomes of SARS-CoV-2 and endemic human coronaviruses to rapidly identify B cell epitopes recognized by distinct antibody isotypes in patients blood sera. Using our integrated computational pipeline, we then evaluated the fine immunological properties of detected SARS-CoV-2 epitopes and relate them to their evolutionary and structural properties. While some epitopes are common across all CoVs, others are private to specific hCoVs. We also highlight the existence of hotspots of pre-existing immunity and identify a subset of cross-reactive epitopes that contributes to increasing the overall humoral immune response to SARS-CoV-2. Using a public dataset of over 38,000 viral genomes from the early phase of the pandemic, capturing both inter- and within-host genetic viral diversity, we determined the evolutionary profile of epitopes and the differences across proteins, waves and SARS-CoV-2 variants, which have important implications for genomic surveillance and vaccine design. Lastly, we show that mutations in Spike and Nucleocapsid epitopes are under stronger selection between than within patients, suggesting that most of the selective pressure for immune evasion occurs upon transmission between hosts.

genomics↗

bioRxiv2022

Epigenetic variation impacts ancestry-associated differences in the transcriptional response to influenza infection

Humans display remarkable inter-individual variation in immune response when exposed to identical immune challenges. Yet, our understanding of the genetic and epigenetic factors contributing to such variation remains limited. Here we carried out in-depth genetic, epigenetic, and transcriptional profiling on primary macrophages derived from a panel of European and African-ancestry individuals before and after infection with influenza A virus (IAV). We show that baseline epigenetic profiles are strongly predictive of the transcriptional response to IAV across individuals, and that ancestry-associated differences in gene expression are tightly coupled with variation in enhancer activity. Quantitative trait locus (QTL) mapping revealed highly coordinated genetic effects on gene regulation with many cis-acting genetic variants impacting concomitantly gene expression and multiple epigenetic marks. These data reveal that ancestry-associated differences in the epigenetic landscape are genetically controlled, even more so than variation in gene expression. Lastly, we show that among QTL variants that colocalized with immune-disease loci, only 7% were gene expression QTL, the remaining corresponding to genetic variants that impact one or more epigenetic marks, which stresses the importance of considering molecular phenotypes beyond gene expression in disease-focused studies.

genetics↗

bioRxiv2022

Transposable elements are associated with the variable response to influenza infection

Influenza A virus (IAV) infections are frequent every year and result in a range of disease severity. Given that transposable elements (TEs) contribute to the activation of innate immunity, we wanted to explore their potential role in this variability. Transcriptome profiling in monocyte-derived macrophages from 39 individuals following IAV infection revealed significant inter-individual variation in viral load post-infection. Using ATAC-seq we identified a set of TE families with either enhanced or reduced accessibility upon infection. Of the enhanced families, 15 showed high variability between individuals and had distinct epigenetic profiles. Motif analysis showed an association with known immune regulators in stably enriched TE families and with other factors in variable families, including KRAB-ZNFs. We also observed a strong association between basal TE transcripts and viral load post infection. Finally, we built a predictive model suggesting that TEs, and host factors regulating TEs, contribute to the variable response to infection.

immunology↗

bioRxiv2021

Genome graphs detect human polymorphisms in active epigenomic states during influenza infection

Genetic variants, including mobile element insertions (MEIs), are known to impact the epigenome. We hypothesized that the use of a genome graph, which encapsulates genetic diversity, could reveal missing epigenomic signal. Given the contributions of mobile elements to the evolution of primate innate immunity, we tested this in monocyte-derived macrophages obtained from 35 individuals before and after Influenza virus infection. After characterizing genetic variants in this cohort using linked-reads, including 5140 Alu, 316 L1, 94 SVAs and 48 ERVs, we incorporated them into a genome graph. Mapping epigenetic data to this graph revealed 2.5%, 3.0% and 2.3% novel peaks for H3K4me1 and H3K27ac ChIP-seq and ATAC-seq respectively. Notably, using a genome graph also modified quantitative trait loci estimates and we observed 375 polymorphic MEIs in active epigenomic state. For example, we found an AluYh3 polymorphism whose chromatin state changed after infection and that was associated with the expression of TRIM25, a gene that restricts influenza RNA synthesis. Our results demonstrate that graph genomes can reveal regulatory regions that would have been overlooked by other approaches.

bioinformatics↗

bioRxiv2021

Application of ATAC-Seq for genome-wide analysis of the chromatin state at single myofiber resolution

Skeletal myofibers are the main components of skeletal muscle which is the largest tissue in the body. Myofibers are highly adaptive in nature and they can vary in different biological and disease conditions. Therefore, transcriptional and epigenetic studies on myofibers are crucial to discover how chromatin alterations occur in the skeletal muscle under different conditions. However, due to the heterogenous nature of skeletal muscle, studying myofibers in isolation proves to be a challenging task. Single cell sequencing has permitted for the study of the epigenome of isolated myonuclei. While this provides sequencing with high dimensionality, the sequencing depth is lacking, which makes comparisons between different biological conditions difficult. Here we report the first implementation of single myofiber ATAC-Seq, which permits for the sequencing of an individual myofiber at a depth sufficient for peak calling and for comparative analysis of chromatin accessibility under various physiological, physical and disease conditions. Application of this technique revealed significant differences in chromatin accessibility between resting and regenerating myofibers. This technique can lead to wide application in identifying chromatin regulatory elements and epigenetic mechanisms in muscle fibers during development and in muscle-wasting diseases.

genetics↗

bioRxiv2021

CanDIG: Secure Federated Genomic Queries and Analyses Across Jurisdictions

Rapid expansions of bioinformatics and computational biology have broadened the collection and use of -omics data including genomic, transcriptomic, methylomic and a myriad of other health data types, in the clinic and the laboratory. Both clinical and research uses of such data require co-analysis with large datasets, for which participant privacy and the need for data custodian controls must remain paramount. This is particularly challenging in multi-jurisdictional settings, such as Canada, where health privacy and security requirements are often heterogeneous. Data federation presents a solution to this, allowing for integration and analysis of large datasets from various sites while abiding by local policies. The Canadian Distributed Infrastructure for Genomics platform (CanDIG) enables federated querying and analysis of -omics and health data while keeping that data local and under local control. It builds upon existing infrastructures to connect five health and research institutions across Canada, relies heavily on standards and tooling brought together by the Global Alliance for Genomics and Health (GA4GH), implements a clear division of responsibilities among its participants and adheres to international data sharing standards. Participating researchers and clinicians can therefore contribute to and quickly access a critical mass of -omics data across a national network in a manner that takes into account the multi-jurisdictional nature of our privacy and security policies. Through this, CanDIG gives medical and research communities the tools needed to use and analyze the ever-growing amount of -omics data available to them in order to improve our understanding and treatment of various conditions and diseases. CanDIG is being used to make genomic and phenotypic data available for querying across Canada as part of data sharing for five leading pan-Canadian projects including the Terry Fox Comprehensive Cancer Care Centre Consortium Network (TF4CN) and Terry Fox PRecision Oncology For Young peopLE (PROFYLE), and making data from provincial projects such as POG (Personalized Onco- Genomics) more widely available.

genomics↗

bioRxiv2020

precisionFDA Truth Challenge V2: Calling variants from short- and long-reads in difficult-to-map regions

The precisionFDA Truth Challenge V2 aimed to assess the state-of-the-art of variant calling in difficult-to-map regions and the Major Histocompatibility Complex (MHC). Starting with FASTQ files, 20 challenge participants applied their variant calling pipelines and submitted 64 variant callsets for one or more sequencing technologies (~35X Illumina, ~35X PacBio HiFi, and ~50X Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with the new GIAB benchmark sets and genome stratifications. Challenge submissions included a number of innovative methods for all three technologies, with graph-based and machine-learning methods scoring best for short-read and long-read datasets, respectively. New methods out-performed the 2016 Truth Challenge winners, and new machine-learning approaches combining multiple sequencing technologies performed particularly well. Recent developments in sequencing and variant calling have enabled benchmarking variants in challenging genomic regions, paving the way for the identification of previously unknown clinically relevant variants.

bioinformatics↗

bioRxiv2020

Genes on Different Strands Mark Boundaries Associated with Co-regulation Domains

Gene regulation is influenced by chromatin conformation. Current models suggest that topologically associating domains (TADs) act as regulatory units, which could also include distinct co-expression domains (CODs) favouring correlated gene expression. We integrated publicly available RNA-seq, ChIP-seq and Hi-C data from A549 cells stimulated with the glucocorticoid dexamethasone to explore how differentially expressed genes are co-regulated among TADs and CODs. Interestingly, we found that gene position and orientation also impact co-regulation. Indeed, divergent and convergent pairs of genes we enriched at sub-TAD boundaries, forming distinct CODs. We also found that genes at COD boundaries were less likely to be separated by structural proteins such as Cohesin and CTCF. A complementary analysis of lung expression quantitative trait loci (eQTL) demonstrated that genes affected by the same variant were more likely to be found on the same strand while lacking a TAD boundary. Taken together, these results suggest a model where gene orientation can provide a boundary between CODs, at the sub-TAD level, thus affecting their likelihood of co-regulation.

genomics↗

bioRxiv2019

Developmental Genome-Wide DNA Methylation Asymmetry Between Mouse Placenta and Embryo

In early embryos, DNA methylation is remodelled to initiate the developmental program but for mostly unknown reasons, methylation marks are acquired unequally between embryonic and placental cells. To better understand this, we generated high-resolution DNA methylation maps of mouse mid-gestation (E10.5) embryo and placenta. We uncovered specific subtypes of differentially methylated regions (DMRs) that contribute directly to the developmental asymmetry existing between mid-gestation embryonic and placental DNA methylation patterns. We show that the asymmetry occurs rapidly during the acquisition of marks in the post-implanted conceptus (E3.5-E6.5), and that these patterns are long-lasting across subtypes of DMRs throughout prenatal development and in somatic tissues. We reveal that at the peri-implantation stages, the de novo methyltransferase activity of DNMT3B is the main driver of methylation marks on asymmetric DMRs, and that DNMT3B can largely compensate for lack of DNMT3A in the epiblast and extraembryonic ectoderm, whereas DNMT3A can only partially compensate in the absence of DNMT3B. However, as development progresses and as DNMT3A becomes the principal de novo methyltransferase, the compensatory DNA methylation mechanism of DNMT3B on DMRs becomes less effective.

developmental biology↗

bioRxiv2019

Transposable elements have contributed human regulatory regions that are activated upon bacterial infection

Transposable elements (TEs) are increasingly recognized as important contributors to mammalian regulatory systems. For instance, they have been shown to play a role in the human interferon response. However, their involvement in other mechanisms of immune cell activation remains poorly understood. We investigated the profile of accessible chromatin enhanced in stimulated human macrophages using ATAC-Seq to assess the role of different TE subfamilies in regulating the immune response. We found that both previously identified and new repeats belonging to the MER44, THE1, Tigger3 and MLT1 families provide 14 subfamilies that are enriched in differentially accessible chromatin and found near differentially expressed genes. These TEs also harbour binding motifs for several candidate transcription factors, including important immune regulators AP-1 and NF-kB, present in 96% of accessible MER44B and 83% of THE1C instances, respectively. To more directly assess their regulatory potential, we evaluated their presence in regions putatively affecting gene expression, as defined by quantitative trait locus (QTL) analysis, and find that repeats are also contributing to accessible elements near QTLs. Together, these results suggest that a number of TE families have contributed to the regulation of the immunogenomic response to infection in humans.

genomics↗

bioRxiv2019

Single-cell analysis of childhood leukemia reveals a link between developmental states and ribosomal protein expression as a source of intra-individual heterogeneity

Childhood acute lymphoblastic leukemia (cALL) is the most common pediatric cancer. It is characterized by bone marrow lymphoid precursors that acquire genetic alterations, resulting in disrupted maturation and uncontrollable proliferation. More than a dozen molecular subtypes of variable severity can be used to classify cALL cases. Modern therapy protocols currently cure 85-90% of cases, but other patients are refractory or will relapse and eventually succumb to their disease. To better understand these difficult cases, we investigated the nature and extent of intra-individual transcriptional heterogeneity of cALL at the cellular level by sequencing the transcriptomes of 39,375 individual cells in eight patients (six pre-B and two pre-T) and three healthy pediatric controls. We observed intra-individual transcriptional clusters in five out of the eight patients. Using pseudotime maturation trajectories of healthy B and T cells, we obtained the predicted developmental state of each leukemia cell and observed distribution shifts within patients. We showed that the predicted developmental states of these cancer cells are inversely correlated with ribosomal protein expression levels, which could be a common contributor to intra-individual heterogeneity in cALL patients.

cancer biology↗

bioRxiv2018

GenPipes: an open-source framework for distributed and scalable genomic analyses

With the decreasing cost of sequencing and the rapid developments in genomics technologies and protocols, the need for validated bioinformatics software that enables efficient large-scale data processing is growing. Here we present GenPipes, a flexible Python-based framework that facilitates the development and deployment of multi-step workflows optimized for High Performance Computing clusters and the cloud. GenPipes already implements 12 validated and scalable pipelines for various genomics applications, including RNA-Seq, ChIP-Seq, DNA-Seq, Methyl-Seq, Hi-C, capture Hi-C, metagenomics and PacBio long read assembly. The software is available under a GPLv3 open source license and is continuously updated to follow recent advances in genomics and bioinformatics. The framework has been already configured on several servers and a docker image is also available to facilitate additional installations. In summary, GenPipes offers genomic researchers a simple method to analyze different types of data, customizable to their needs and resources, as well as the flexibility to create their own workflows.

bioinformatics↗

bioRxiv2018

Impact of using a personalized genome on histone ChIP-seq peak calls

BackgroundEpigenomic studies that use next generation sequencing experiments typically rely on the alignment of reads to a reference sequence. However, because of genetic diversity and the diploid nature of the human genome, we hypothesized that using a generic reference could lead to incorrectly mapped reads and bias downstream results.\n\nResultsWe show that accounting for genetic variation using a modified reference genome (MPG) or a denovo assembled genome (DPG) can alter histone H3K4me1 and H3K27ac ChIP-seq peak calls by either creating new personal peaks or by the loss of reference peaks. MPGs are found to alter approximately 1% of peak calls while DPGs alter up to 5% of peaks. We also show statistically significant differences in the amount of reads observed in regions associated with the new, altered and unchanged peaks. We report that short insertions and deletions (indels), followed by single nucleotide variants (SNVs), have the highest probability of modifying peak calls. A counter-balancing factor is peak width, with wider calls being less likely to be altered. Next, because high-quality DPGs remain hard to obtain, we show that using a graph personalized genome (GPG), represents a reasonable compromise between MPGs and DPGs and alters about 2.5% of peak calls. Finally, we demonstrate that altered peaks have a genomic distribution typical of other peaks. For instance, for H3K4me1, 518 personal-only peaks were replicated using at least two of three approaches, 394 of which were inside or within 10Kb of a gene.\n\nConclusionsAnalysing epigenomic datasets with personalized and graph genomes allows the recovery of new peaks enriched for indels and SNVs. These altered peaks are more likely to differ between individuals and, as such, could be relevant in the study of various human phenotypes.

bioinformatics↗

bioRxiv2018

Single-cell RNA-seq reveals that glioblastoma recapitulates normal brain development

SummaryCancer stem cells are critical for cancer initiation, development, and resistance to treatments. Our understanding of these processes, and how they relate to glioblastoma heterogeneity, is limited. To overcome these limitations, we performed single-cell RNA-sequencing on 38 296 glioblastoma cells and 22 637 normal human fetal brain cells. Using an unbiased approach, we mapped the lineage hierarchy of the developing human brain and compared the transcriptome of each cancer cell to this roadmap. We discovered a conserved neural trilineage cancer hierarchy with glial progenitor-like cells at the apex. We also found that this progenitor population contains the majority of cancers cycling cells and is the origin of heterogeneity. Finally, we show that this hierarchal map can be used to identify therapeutic targets specific to progenitor cancer stem cells. Our analyses show that normal brain development reconciles glioblastoma development, unravels the origin of glioblastoma heterogeneity, and helps to identify cancer stem cell-specific targets.

cancer biology↗

bioRxiv2018

Deleterious genetic variants in NOTCH1 are a major contributor to the incidence of non-syndromic Tetralogy of Fallot

AimsFamilial recurrence studies provide strong evidence for a genetic component to the predisposition to sporadic, non-syndromic Tetralogy of Fallot (TOF), the most common cyanotic congenital heart disease (CHD) phenotype. Rare genetic variants have been identified as important contributors to the risk of CHD, but relatively small numbers of TOF cases have been studied to date. Here, we use whole exome sequencing to assess the prevalence of rare, potentially deleterious variants in candidate genes previously associated with both syndromic and non-syndromic TOF, in the largest cohort of non-syndromic TOF patients reported to date.\n\nMethods & Results829 non-syndromic TOF patients underwent whole exome sequencing. A systematic review of the literature was conducted which revealed 77 genes in which mutations had been reported in patients with TOF. The presence of rare, deleterious variants in the 77 candidate genes was determined, defined by a minor allele frequency of [≤] 0.001 and scaled combined annotation-dependent depletion (CADD) score of [≥] 20. We found a clustering of heterozygous rare, deleterious variants in NOTCH1 (P=1.89E-15), DOCK6 (P=2.93E-07), MYOM2 (P= 7.35E-05), TTC37 (P=0.016), MESP1 (P=0.024) and TBX1 (P=0.039), after correcting for multiple testing. NOTCH1 was most frequently found to harbour deleterious variants. Changes were observed in 49 patients (6%; 95% confidence interval [CI]: 4.5% - 7.8%) and included six truncating/frameshift variants and forty missense variants. Sanger sequencing of the unaffected parents of thirteen cases identified five de novo variants. Variants were not confined to a single functional domain of the NOTCH1 protein but significant clustering of variants was evident in the EGF-like repeats (P=0.018). Three NOTCH1 missense variants (p.G200R, p.C607Y and de novo p.N1875S) were subjected to functional evaluation and showed a reduction in Jagged1 ligand-induced NOTCH signalling. p.C607Y, which exhibited the most significant reduction in signalling, also perturbed S1 cleavage of the NOTCH1 receptor in the Golgi.\n\nConclusionThe NOTCH1 locus is a frequent site of genetic variants predisposing to non-syndromic TOF with 6% of patients exhibiting rare, deleterious variants. Our data supports the polygenic origin of TOF and suggests larger studies may identify additional loci.

genetics↗

bioRxiv2018

RobusTAD: A Tool for Robust Annotation ofTopologically Associating Domain Boundaries

MotivationTopologically Associating Domains (TADs) are chromatin structures that can be identified by analysis of Hi-C data. Tools currently available for TAD identification are sensitive to experimental conditions such as coverage, resolution and noise level.\n\nResultsHere, we present RobusTAD, a tool to score TAD boundaries in a manner that is robust to these parameters. In doing so, RobusTAD eases comparative analysis of TAD structures across multiple heterogeneous samples.\n\nAvailabilityRobusTAD is implemented in R and released under a GPL license. RobusTAD can be downloaded from https://github.com/rdali/RobusTAD and runs on any standard desktop computer.\n\nContactrola.dali@mail.mcgill.ca, blanchem@cs.mcgill.ca\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2017

Genome-wide characterization of copy number variants in epilepsy patients

Epilepsy will affect nearly 3% of people at some point during their lifetime. Previous copy number variants (CNVs) studies of epilepsy have used array-based technology and were restricted to the detection of large or exonic events. In contrast, whole-genome sequencing (WGS) has the potential to more comprehensively profile CNVs but existing analytic methods suffer from limited accuracy. We show that this is in part due to the non-uniformity of read coverage, even after intra-sample normalization. To improve on this, we developed PopSV, an algorithm that uses multiple samples to control for technical variation and enables the robust detection of CNVs. Using WGS and PopSV, we performed a comprehensive characterization of CNVs in 198 individuals affected with epilepsy and 301 controls. For both large and small variants, we found an enrichment of rare exonic events in epilepsy patients, especially in genes with predicted loss-of-function intolerance. Notably, this genome-wide survey also revealed an enrichment of rare non-coding CNVs near previously known epilepsy genes. This enrichment was strongest for non-coding CNVs located within 100 Kbp of an epilepsy gene and in regions associated with changes in the gene expression, such as expression QTLs or DNase I hypersensitive sites. Finally, we report on 21 potentially damaging events that could be associated with known or new candidate epilepsy genes. Our results suggest that comprehensive sequence-based profiling of CNVs could help explain a larger fraction of epilepsy cases.\n\nAuthor summaryEpilepsy is a common neurological disorder affecting around 3% of the population. In some cases, epilepsy is caused by brain trauma or other brain anomalies but there are often no clear causes. Genetic factors have been associated with epilepsy in the past such as rare genetic variations found by linkage studies as well as common genetic variations found by genome-wide association studies and large copy-number variants. We sequenced the genome of[~] 200 epilepsy patients and[~] 300 healthy controls and compared the distribution of deletion (loss of a copy) and duplication (additional copy) of genomic regions. Thanks to the sequencing technology and a new method that takes advantage of the large sample size, we could compare the distribution of small copy- number variants between epilepsy patients and controls. Overall, we found that small variants are also associated with epilepsy. Indeed, the genome of epilepsy patients had more exonic copy- number variants, especially when rare or affecting genes with predicted loss-of-function intolerance. Focusing on regions around genes that have been previously associated with epilepsy, we also found more non-coding variants in epilepsy patients, especially deletions or variants in regulatory regions. Finally, we provide a list of 21 regions in which we found likely pathogenic variants.

genomics↗

bioRxiv2017

Pan-cancer analysis of whole genomes reveals driver rearrangements promoted by LINE-1 retrotransposition in human tumours

About half of all cancers have somatic integrations of retrotransposons. To characterize their role in oncogenesis, we analyzed the patterns and mechanisms of somatic retrotransposition in 2,954 cancer genomes from 37 histological cancer subtypes. We identified 19,166 somatically acquired retrotransposition events, affecting 35% of samples, and spanning a range of event types. L1 insertions emerged as the first most frequent type of somatic structural variation in esophageal adenocarcinoma, and the second most frequent in head-and-neck and colorectal cancers. Aberrant L1 integrations can delete megabase-scale regions of a chromosome, sometimes removing tumour suppressor genes, as well as inducing complex translocations and large-scale duplications. Somatic retrotranspositions can also initiate breakage-fusion-bridge cycles, leading to high-level amplification of oncogenes. These observations illuminate a relevant role of L1 retrotransposition in remodeling the cancer genome, with potential implications in the development of human tumours.

genomics↗