Biology subjects

Thiruvahindrapuram, B.

Publications and source records attributed to Thiruvahindrapuram, B..

7 recordsLinked to original sources

bioRxiv2025

Beyond reference bias: Making pangenomes accessible with PangyPlot

Linear reference genomes have standardized genomics research but remain limited by reference bias, which skews read mapping and variant discovery. This bias can distort the interpretation of genetic variation, particularly for populations that are genetically distant from the reference. Pangenome graphs, such as those generated by the Human Pangenome Reference Consortium (HPRC), mitigate this limitation by integrating diverse haplotypes into a unified representation of human genetic variation. However, the complexity of graph-based data and the lack of intuitive visualization tools have hindered broader adoption. Here we introduce PangyPlot, a genome browser that simplifies exploration of pangenome graphs by retaining linear-style navigation, integrating gene annotations, abstracting complex variation into interpretable structures, and employing a dynamic, physics-based layout optimization engine. We demonstrate its utility by constructing a chromosome 7 graph from 101 individuals with cystic fibrosis (CF), capturing a broad spectrum of genetic variation. Using PangyPlot, we visualized CF-relevant loci and compared results with existing graph viewers, highlighting its ability to display both base-level and large structural variation. With an additional 64 PacBio HiFi assemblies, we fine-mapped a repeat-dense CF modifier locus on chromosome 5, where PangyPlot was used in conjunction with graph-based analysis to identify a repeat expansion in the 5' end of EXOC3 that may promote G-quadruplex formation and affect gene expression. Together, these examples demonstrate PangyPlot s capacity to make populationlevel variation interpretable. To support broader use of graph-based resources, we also released a live public instance of PangyPlot preloaded with HPRC data (https://pangyplot.research.sickkids.ca/).

genomics↗

bioRxiv2025

GWAS SVatalog: a visualization tool to aid fine-mapping of GWAS loci with structural variations

BackgroundGenome-wide association studies (GWAS) have been successful in identifying single nucleotide polymorphisms (SNPs) associated with phenotypic traits. However, SNPs form an incomplete set of variation across the genome and since a large percentage of GWAS-significant SNPs lie in non-coding regions, their impact on a given trait is difficult to decipher. Recognizing whether these SNPs are tagging other polymorphisms, like structural variations (SV), is an important step towards understanding the putative causal variation at GWAS loci. ResultsHere, we develop GWAS SVatalog (https://svatalog.research.sickkids.ca/), a novel open-source web tool that computes and visualizes linkage disequilibrium (LD) between SVs and GWAS-associated SNPs throughout the human genome. The tool combines GWAS Catalogs SNP-trait association data across 14,479 phenotypes with LD statistics calculated between 35,732 SVs and 116,870 SNPs identified in 101 whole-genome long-read sequences. We use GWAS SVatalog to identify SVs that may explain GWAS loci for iron levels, refractive error, and Alzheimers disease, where previously SNPs were unable to provide a causal explanation. ConclusionsGWAS SVatalog advances the fine-mapping of GWAS loci with structural variations, enabling researchers to associate 35,732 common SVs with 14,479 phenotypes, accelerating the understanding of disease etiology.

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↗

bioRxiv2022

High Quality Phasing Using Linked-Read Whole Genome Sequencing of Patient Cohorts Informs Genetic Understanding of Complex Traits

Phasing of heterozygous alleles is critical for interpretation of cis-effects of disease-relevant variation. For population studies, phase is often inferred from external data but read-based phasing approaches that span long genomic distances would be more accurate because they enable both genotype and phase to be obtained from a single dataset. To demonstrate how read-based phasing can provide functional insights, we sequenced 477 individuals with Cystic Fibrosis (CF) using linked-read sequencing. We benchmark read-based phasing with different short- and long-read sequencing technologies, prioritize linked-read technology as the most informative and produce a benchmark phase call set from reference sample HG002 for the community. The 477 samples display an average phase block N50 of 4.39 Mb. We use these samples to construct a graph representation of CFTR haplotypes, which facilitates understanding of complex CF alleles. Fine-mapping and phasing of the chr7q35 trypsinogen locus associated with CF meconium ileus demonstrates a 20 kb deletion and a PRSS2 missense variant p.Thr8Ile (rs62473563) independently contribute to meconium ileus risk (p=0.0028, p=0.011, respectively) and are PRSS2 pancreas eQTLs (p=9.5e-7 and p=1.4e-4, respectively), explaining the mechanism by which these polymorphisms contribute to CF. Phase enables access to haplotypes that can be used for genome graph or reference panel construction, identification of cis-effects, and for understanding disease associated loci. The phase information from linked-reads provides a causal explanation for variation at a CF-relevant locus which also has implications for the genetic basis of non-CF pancreatitis to which this locus has been reported to contribute.

genetics↗

bioRxiv2022

Neuron-specific protein network mapping of autism risk genes identifies shared biological mechanisms and disease relevant pathologies

Manuscript summaryThere are hundreds of risk genes associated with autism spectrum disorder (ASD), but signaling networks at the protein level remain unexplored. We use neuron-specific proximity-labeling proteomics (BioID) to identify protein-protein interaction (PPI) networks for 41 ASD-risk genes. Neuron-specific PPI networks, including synaptic transmission proteins, are disrupted by de novo missense variants. The PPI network map reveals convergent pathways, including mitochondrial/metabolic processes, Wnt signaling, and MAPK signaling. CRISPR knockout reveal an association between mitochondrial activity and ASD-risk genes. The PPI network shows an enrichment of 112 additional ASD-risk genes and differentially expressed genes from post-mortem ASD patients. Clustering of risk genes based on PPI networks identifies gene groups corresponding to clinical behavior score severity. Our data reveal that cell type-specific PPI networks can identify individual and convergent ASD signaling networks, provide a method to assess patient variants, and reveal biological insight into disease mechanisms and sub-cohorts of ASD.

neuroscience↗

bioRxiv2018

Complete Disruption of Autism-Susceptibility Genes by Gene-Editing Predominantly Reduces Functional Connectivity of Isogenic Human Neurons

Autism Spectrum Disorder is phenotypically and genetically heterogeneous, but genomic analyses have identified candidate susceptibility genes. We present a CRISPR gene editing strategy to insert a protein tag and premature termination sites creating an induced pluripotent stem cell (iPSC) knockout resource for functional studies of 10 ASD-relevant genes (AFF2/FMR2, ANOS1, ASTN2, ATRX, CACNA1C, CHD8, DLGAP2, KCNQ2, SCN2A, TENM1). Neurogenin 2 (NEUROG2)-directed differentiation of iPSCs allowed production of cortical excitatory neurons, and mutant proteins were not detectable. RNAseq revealed convergence of several neuronal networks. Using both patch-clamp and multi-electrode array approaches, the electrophysiological deficits measured were distinct for different mutations. However, they culminated in a consistent reduction in synaptic activity, including reduced spontaneous excitatory post-synaptic current frequencies in AFF2/FMR2-, ASTN2-, ATRX-, KCNQ2- and SCN2A-null neurons. Despite ASD susceptibility genes belonging to different gene ontologies, isogenic stem cell resources can reveal common functional phenotypes, such as reduced functional connectivity.

neuroscience↗

bioRxiv2017

Copy Number Variation Analysis of 100 Twin Pairs Enriched for Neurodevelopmental Disorders

Hundreds of penetrant risk loci have been identified across different neurodevelopmental disorders (NDDs), and these often involve rare (<1% frequency) copy number variations (CNVs), which can involve one or more genes. Monozygotic (MZ) twin pairs are long thought to share 100% of their genomic information. However, genetic differences in the form of postzygotic somatic variants have been reported recently both in typically developing (TD) and in clinically discordant MZ pairs. Here, we sought to investigate the contribution of CNVs in 100 twin pairs enriched for NDD phenotypes with a particular focus on MZ pairs discordant for autism spectrum disorder (ASD) using the PsychChip array. In our collection, no postzygotic de novo CNVs were found in 55 MZ twin pairs, including the 13 pairs discordant for ASD. When analyzing the burden of rare CNVs among pairs concordant and discordant for ASD/NDD in comparison with typically developed (TD) pairs, no differences were found. However, we did detect a higher rate of CNVs overlapping genes involved in disorders of the nervous system in MZ pairs discordant and concordant for ASD in comparison with TD pairs (p=0.02). Our results are in concordance with earlier findings that postzygotic de novo CNV events are typically rare in genomic DNA derived from saliva or blood and, in the majority of MZ twins, do not explain the discordance of NDDs. Still, studies investigating postzygotic variation in MZ discordant twins using DNA from different tissues and single cells and higher resolution genomics are needed in the future.

genetics↗