Biology subjects

Saci, Z.

Publications and source records attributed to Saci, Z..

9 recordsLinked to original sources

bioRxiv2026

gVCF2CNV: a scalable pipeline for CNV detection from whole-genome sequencing data

Motivation: Copy-number variants (CNVs) contribute to human disease and population trait variation. CNV detection from large whole-genome sequencing cohorts remains computationally demanding, as most methods require BAM or CRAM files. Genomic VCF (gVCF) files are smaller, routinely generated by standard variant-calling workflows, and contain the read depth and allelic information needed for CNV detection. However, gVCF files are not directly compatible with established CNV callers that rely on Log R Ratio (LRR) and B Allele Frequency (BAF) signals. Results: We present gVCF2CNV, a Nextflow pipeline that converts gVCF files into Log R Ratio and B Allele Frequency signals compatible with established CNV callers. Applied to 12,509 individuals from the SPARK cohort, gVCF2CNV generated signals at an average of 2.7 million SNV positions per individual and completed signal extraction in 4 hours using 192 CPUs. CNV calling with PennCNV and QuantiSNP identified candidate CNVs across a broad size range, with trio-based Mendelian precision reaching approximately 80% or higher for deletions of at least 30 kb and duplications of at least 5 kb. Application to 414,824 individuals from the All of Us cohort was completed in 96 hours, demonstrating feasibility at biobank scale. These results show that gVCF files can serve as a scalable input for CNV detection in large WGS cohorts. Availability and Implementation: gVCF2CNV is available at https://github.com/JacquemontLab/gVCF2CNV, implemented as a Nextflow pipeline with Perl and Python components, supported on Linux. Contact: mame.seynabou.diop@umontreal.ca

bioinformatics↗

bioRxiv2025

Mirror effect of genomic deletions and duplications on cognitive ability across the human cerebral cortex

Cognitive deficits are common across many neurodevelopmental and psychiatric conditions, including those studied in the current set of PGC-CNV papers. How changes in regional gene expression across the cerebral cortex influence cognitive ability remains unknown. Population variation in gene dosage--which significantly impacts gene expression--represents a unique paradigm to address this question. We developed a cerebral-cortex gene-set burden analysis (CC-GSBA) to associate a trait with genomic deletions and duplications that disrupt genes with similar expression profiles across 180 cortical regions. We performed CC-GSBA across 180 cortical regions to test associations with cognitive ability in 260,000 individuals from general population cohorts. Most cortical gene sets were associated with a decrease in cognitive ability when deleted or duplicated, and this novel approach revealed opposing cortical patterns for the effect sizes of deletions and duplications. These cortical patterns of effect sizes followed the cortical gradient previously characterized at the molecular, cellular, and functional levels. We show that genes with preferential expression in sensorimotor regions demonstrated the largest effect on cognition when deleted. At the opposing end of the cortical gradient, genes with preferential expression in multimodal association regions affected cognition the most when duplicated. These two gene dosage cortical patterns could not be explained by particular cell types, developmental epochs, or genetic constraints, highlighting the fact that the macroscopic network organization of the cerebral cortex is key to understanding the effects of gene dosage on cognitive traits.

neuroscience↗

bioRxiv2024

Effects of gene dosage on cognitive ability: A function-based association study across brain and non-brain processes

Genomic Copy Number Variants (CNVs) that increase risk for neurodevelopmental disorders are also associated with lower cognitive ability in general population cohorts. Studies have focussed on a small set of recurrent CNVs, but burden analyses suggested that the vast majority of CNVs affecting cognitive ability are too rare to reach variant-level association. As a result, the full range of gene-dosage-sensitive biological processes linked to cognitive ability remains unknown. To investigate this issue, we identified all CNVs >50 kilobases in 258k individuals from 6 general population cohorts with assessments of general cognitive abilities. We performed a CNV-GWAS and functional burden analyses, which tested 6502 gene-sets defined by tissue and cell-type transcriptomics as well as gene ontology disrupted by all rare coding CNVs. CNV-GWAS identified a novel duplication at 2q12.3 associated with higher performance in cognitive ability. Among the 864 gene-sets associated with cognitive ability, only 11% showed significant effects for both deletions and duplication. Accordingly, we systematically observed negative correlations between deletion and duplication effect sizes across all levels of biological observations. We quantified the preferential effects of deletions versus duplication using tagDS, a new normalized metric. Cognitive ability was preferentially affected by cortical, presynaptic, and negative-regulation gene-sets when duplicated. In contrast, preferential effects of deletions were observed for subcortical, post-synaptic, and positive-regulation gene-sets. A large proportion of gene-sets assigned to non-brain organs were associated with cognitive ability due to low tissue specificity genes, which were associated with higher sensitive to haploinsufficiency. Overall, most biological functions associated with cognitive ability are divided into those sensitive to either deletion or duplications.

genetics↗

bioRxiv2023

Using rare genetic mutations to revisit structural brain asymmetry

Asymmetry between the left and right brain is a key feature of brain organization. Hemispheric functional specialization underlies some of the most advanced human-defining cognitive operations, such as articulated language, perspective taking, or rapid detection of facial cues. Yet, genetic investigations into brain asymmetry have mostly relied on common variant studies, which typically exert small effects on brain phenotypes. Here, we leverage rare genomic deletions and duplications to study how genetic alterations reverberate in human brain and behavior. We quantitatively dissected the impact of eight high-effect-size copy number variations (CNVs) on brain asymmetry in a multi-site cohort of 552 CNV carriers and 290 non-carriers. Isolated multivariate brain asymmetry patterns spotlighted regions typically thought to subserve lateralized functions, including language, hearing, as well as visual, face and word recognition. Planum temporale asymmetry emerged as especially susceptible to deletions and duplications of specific gene sets. Targeted analysis of common variants through genome-wide association study (GWAS) consolidated partly diverging genetic influences on the right versus left planum temporale structure. In conclusion, our gene-brain-behavior mapping highlights the consequences of genetically controlled brain lateralization on human-defining cognitive traits.

neuroscience↗

bioRxiv2022

Rare CNVs and phenome-wide profiling: a tale of brain-structural divergence and phenotypical convergence

Copy number variations (CNVs) are rare genomic deletions and duplications that can exert profound effects on brain and behavior. Previous reports of pleiotropy in CNVs imply that they converge on shared mechanisms at some level of pathway cascades, from genes to large-scale neural circuits to the phenome. However, studies to date have primarily examined single CNV loci in small clinical cohorts. It remains unknown how distinct CNVs escalate the risk for the same developmental and psychiatric disorders. Here, we quantitatively dissect the impact on brain organization and behavioral differentiation across eight key CNVs. In 534 clinical CNV carriers from multiple sites, we explored CNV-specific brain morphology patterns. We extensively annotated these CNV-associated patterns with deep phenotyping assays through the UK Biobank resource. Although the eight CNVs cause disparate brain changes, they are tied to similar phenotypic profiles across [~]1000 lifestyle indicators. Our population-level investigation established brain structural divergences and phenotypical convergences of CNVs, with direct relevance to major brain disorders.

genetics↗

bioRxiv2020

Estimating the effect-size of gene dosage on cognitive ability across the coding genome

Genomic Copy Number Variants (CNVs) are routinely identified and reported back to patients with neuropsychiatric disorders, but their quantitative effects on essential traits such as cognitive ability are poorly documented. We have recently shown that the effect-size of deletions on cognitive ability can be statistically predicted using measures of intolerance to haploinsufficiency. However, the effect-sizes of duplications remain unknown. It is also unknown if the effect of multigenic CNVs are driven by a few genes intolerant to haploinsufficiency or distributed across tolerant genes as well. Here, we identified all CNVs >50 kilobases in 24,092 individuals from unselected and autism cohorts with assessments of general intelligence. Statistical models used measures of intolerance to haploinsufficiency of genes included in CNVs to predict their effect-size on intelligence. Intolerant genes decrease general intelligence by 0.8 and 2.6 points of IQ when duplicated or deleted, respectively. Effect-sizes showed no heterogeneity across cohorts. Validation analyses demonstrated that models could predict CNV effect-sizes with 78% accuracy. Data on the inheritance of 27,766 CNVs showed that deletions and duplications with the same effect-size on intelligence occur de novo at the same frequency. We estimated that around 10,000 intolerant and tolerant genes negatively affect intelligence when deleted, and less than 2% have large effect-sizes. Genes encompassed in CNVs were not enriched in any GOterms but gene regulation and brain expression were GOterms overrepresented in the intolerant subgroup. Such pervasive effects on cognition may be related to emergent properties of the genome not restricted to a limited number of biological pathways.

genetics↗

bioRxiv2020

Effects-sizes of deletions and duplications on autism risk across the genome

ObjectiveDeleterious copy number variants (CNVs) are identified in up to 20% of individuals with autism. However, only 13 genomic loci have been formally associated with autism because the majority of CNVs are too rare to perform individual association studies. To investigate the implication of undocumented CNVs in neurodevelopmental disorders, we recently developed a new framework to estimate their effect-size on intelligence quotient (IQ) and sought to extend this approach to autism susceptibility and multiple cognitive domains. MethodsWe identified CNVs in two autism samples (Simons Simplex Collection and MSSNG) and two unselected populations (IMAGEN and Saguenay Youth Study). Statistical models integrating scores of genes encompassed in CNVs were used to explain their effect on autism susceptibility and multiple cognitive domains. ResultsAmong 9 scores of genes, the "probability-of-being loss-of-function intolerant" (pLI) best explains the effect of CNVs on IQ and autism risk. Deletions decrease IQ by a mean of 2.6 points per point of pLI. The effect of duplications on IQ is three-fold smaller. The odd ratios for autism increases when deleting or duplicating any point of pLI. This increased autism risk is similar in subgroups of individuals below or above median IQ. Once CNV effects on IQ are accounted for, autism susceptibility remains mostly unchanged for duplications but decreases for deletions. Model estimates for autism risk overlap with previously published observations. Deletions and duplications differentially affect social communication, behaviour, and phonological memory, whereas both equally affect motor skills. ConclusionsAutism risk conferred by duplications is less influenced by IQ compared to deletions. CNVs increase autism risk similarly in individuals with high and low IQ. Our model, trained on CNVs encompassing >4,500 genes, suggests highly polygenic properties of gene dosage with respect to autism risk. These models will help interpreting CNVs identified in the clinic.

genetics↗

bioRxiv2019

HOTAIR promotes an epithelial-to-mesenchymal transition through relocation of the histone demethylase Lsd1

Epithelial-to-mesenchymal transition (EMT) drives a loss of epithelial traits by neoplastic cells enabling metastasis and recurrence in cancer. HOTAIR emerged as one of the most renowned long noncoding RNAs promoting EMT mostly as a scaffold for PRC2 and repressive histone H3 Lys27 methylation at gene promoters. In addition to PRC2, HOTAIR interacts with the Lsd1 lysine demethylase, a known epigenetic regulator of cell fate during development and differentiation. However, Lsd1 role in HOTAIR function is still poorly understood. Here, through expression of truncated variants of HOTAIR, we revealed that, in contrast to PRC2, its Lsd1-interacting domain is essential for acquisition of migratory properties by epithelial cells. HOTAIR induces Lsd1 relocation from its inherent genomic loci hence reprogramming the epithelial transcriptome. Our results uncovered an unexpected role of HOTAIR in EMT as an Lsd1 effector and pointed to the importance of Lsd1 as a guardian of the epithelial identity.

cancer biology↗

bioRxiv2019

Blind exploration of the unreferenced transcriptome reveals novel RNAs for prostate cancer diagnosis

The broad use of RNA-sequencing technologies held a promise of improved diagnostic tools based on comprehensive transcript sets. However, mining human transcriptome data for disease biomarkers in clinical specimens is restricted by the limited power of conventional reference-based protocols relying on uniquely mapped reads and transcript annotations. Here, we implemented a blind reference-free computational protocol, DE-kupl, to directly infer RNA variations of any origin, including yet unreferenced RNAs, from high coverage total stranded RNA-sequencing datasets of tissue origin. As a bench test, this protocol was powered for detection of RNA subsequences embedded into unannotated putative long noncoding (lnc)RNAs expressed in prostate cancer tissues. Through filtering and visual inspection of 1,179 candidates, we defined 21 lncRNA probes that were further validated for robust tumor-specific expression by NanoString single molecule-based RNA measurements in 144 tissue specimens. Predictive modeling yielded a restricted probe panel enabling over 90% of true positive detection of cancer in an independent dataset from The Cancer Genome Atlas. Remarkably, this clinical signature made of only 9 unannotated lncRNAs largely outperformed PCA3, the only RNA biomarker approved by the Food and Drug Administration agency, specifically, in detection of high-risk prostate tumors. The proposed reference-free computational workflow is modular, highly sensitive and robust and can be applied to any pathology and any clinical application.

genomics↗