Biology subjects

Ragavendran, A.

Publications and source records attributed to Ragavendran, A..

8 recordsLinked to original sources

bioRxiv2025

The Liver is an Inflammatory Mediator of Pulmonary Arterial Hypertension

The livers contribution to pulmonary arterial hypertension (PAH) pathogenesis remains unclear. We hypothesized that the liver promotes inflammatory injury to the pulmonary endothelium. PAH patients without liver disease with pulmonary artery endothelial cell (PAEC) biopsies were included. Liver serologies and imaging were analyzed by unsupervised classification and regression tree (CART) to identify subclinical liver dysfunction clusters. Two machine-learning models predicted cluster assignment and informed differential expression. PAEC transcriptomes were compared to liver and lung data from monocrotaline and Sugen-Hypoxia rats. Liver fibrosis was assessed in rat and human PAH livers. Among 25 PAH patients (76% female, median age 61 [30 - 84] years), CART identified clusters distinguished by Model for End-Stage Liver Disease Sodium (MELD-Na) [≥]12, predicting higher pulmonary vascular resistance ({beta}=0.5 Wood units per point increase in MELD-Na, 95% CI 0.2-0.8, p=0.005) after adjustment for right atrial pressure. Subjects with MELD-Na [≥]12 had decreased 6-minute walk distance (353 [120 - 576] m vs. 411[300 - 600] m, p=0.03), with upregulation of apelin, beta-catenin, and immune signaling. Rat lung ECs demonstrated survival and hepatic growth-factor signaling, while rat livers showed immune activation. Rat (20.8 vs 16.6 % area stained, p=0.09) and human PAH livers revealed fibrosis despite absent right ventricular failure, supporting a pathogenic lung-liver axis in PAH.

cell biology↗

bioRxiv2022

Tissue and cell-type specific molecular and functional signatures of 16p11.2 reciprocal genomic disorder across mouse brain and human neuronal models

Recurrent deletion and duplication of [~]743 kilobases of unique genomic sequence and segmental duplications at chromosome 16p11.2 underlie a reciprocal genomic disorder (RGD; OMIM 611913 and 614671) associated with neurodevelopmental and psychiatric phenotypes, including intellectual disability, autism spectrum disorder (ASD), and schizophrenia (SCZ). To define molecular alterations associated with the 16p11.2 RGD, we performed transcriptome analyses of mice with reciprocal copy number variants (CNVs) of the syntenic chromosome 7qF3 region and human neuronal models derived from isogenic human induced pluripotent stem cells (hiPSCs) carrying CRISPR-engineered CNVs at 16p11.2. Analysis of differentially expressed genes (DEGs) in mouse cortex, striatum, cerebellum and three non-brain tissues, as well as in human neural stem cells and induced glutamatergic neurons revealed that the strongest and most consistent effects occurred within the CNV sequence, with notable instances of differential expression of genes in the immediate vicinity that could reflect position effect. While differential expression of genes outside of chromosome 16p11.2 was largely region, tissue, and cell type-specific, a small but significant minority of such DEGs was shared between brain regions or human cell types. Gene Ontology (GO) enrichment analyses to identify cellular processes dysregulated due to these CNVs found support in select circumstances for terms related to energy metabolism, RNA metabolism, and translation but did not reveal a single universally affected process. Weighted gene co-expression network analysis identified modules that showed significant correlation with reciprocal or individual CNV genotype and better captured shared effects, indicating that energy metabolism, RNA metabolism, translation and protein targeting were disrupted across all three brain regions. The first two of these processes also emerged in the human neural stem cell (NSC) data. A subset of co-expression modules that correlated with CNV genotype revealed significant enrichments for known neurodevelopmental disorder genes, loss-of-function constrained genes, FMRP targets, and chromatin modifiers. Intriguingly, neuronal differentiation of the hiPSCs revealed that both the deletion and duplication CNV resulted in similar deficits in neurite extension and branching and alterations in electrical activity. Finally, generation of cerebral organoid derivatives indicated that the CNVs reciprocally altered the ratio of excitatory and inhibitory GABAergic neurons generated during in vitro neurodevelopment, consistent with a major mechanistic hypothesis for ASD. Collectively, our data suggest that the 16p11.2 RGD involves disruption of multiple biological processes, with a relative impact that is context-specific. Perturbation of individual and multiple genes within the CNV region will be required to dissect single-gene effects, uncover regulatory interactions, and define how each contributes to abnormal neurodevelopment.

genomics↗

bioRxiv2021

Developmental regulation of neuronal gene expression by Elongator complex protein 1 dosage.

Elongator is a highly conserved protein complex required for transcriptional elongation, intracellular transport and translation. Elongator complex protein 1 (ELP1) is the scaffolding protein of Elongator and is essential for its assembly and stability. Familial dysautonomia (FD), a hereditary sensory and autonomic neuropathy, is caused by a mutation in ELP1 that lead to a tissue-specific reduction of ELP1 protein. Our work to generate a phenotypic mouse model for FD led to the discovery that homozygous deletion of the mouse Elp1 gene leads to embryonic lethality prior to mid-gestation. Given that FD is caused by a reduction, not loss, of ELP1, we generated two new mouse models by introducing different copy numbers of the human FD ELP1 transgene into the Elp1 knockout mouse (Elp1-/-) and observed that human ELP1 expression rescues embryonic development in a dose dependent manner. We then conducted a comprehensive transcriptome analysis in mouse embryos to identify genes and pathways whose expression correlates with the amount of ELP1. We found that ELP1 is essential for the expression of genes responsible for the formation and development of the nervous system. Further, gene length analysis of the differentially expressed genes showed that the loss of Elp1 mainly impacts the expression of long genes and that by gradually restoring Elongator their expression is progressively rescued. Finally, through evaluation of co-expression modules, we identified gene sets with unique expression patterns that depended on ELP1 expression. Overall, this study highlights the crucial role of ELP1 during early embryonic neuronal development and reveals gene networks and biological pathways that are regulated by Elongator.

developmental biology↗

bioRxiv2020

VarStack: a Web Tool for Data Retrieval to Interpret Somatic Variants in Cancer

Background and objectiveAdvances in tumor genome sequencing created an urgent need for bioinformatics tools to support the interpretation of the clinical significance of the variants detected. VarStack is a web tool which is a base to retrieve somatic variant data in cancer from existing databases. MethodsVarStack incorporates data from several publicly available databases and presents them with an easy-to-navigate user-interface. It currently supports data from the Catalogue of Somatic Mutations in Cancer (COSMIC), gnomAD, cBioPortal, ClinVar, OncoKB and UCSC Genome browser. It retrieves the data from these databases and returns back to the user in a fraction of the time it would take to manually navigate each site independently. ResultsUsers submit a variant with gene symbol, peptide change, and coding sequence change. They may select a variety of tumor specific studies in cBioportal to search through in addition to their original query. The results from the databases are presented in tabs. Users can export the results as a CSV file. VarStack also has the batch search feature in which user submits a list of variants and download a CSV file with the data from the databases. With the batch search and data download options users can easily incorporate VarStack into their workflow or tools. VarStack saves time by providing variant data to the user from multiple databases in an easy-to-export and interpretable format. AvailabilityVarStack is freely available under https://varstack.brown.edu.

bioinformatics↗

bioRxiv2020

A deep learning approach to identify new gene targets of a novel therapeutic for human splicing disorders

Pre-mRNA splicing is a key control point in human gene expression. Disturbances in splicing due to mutation or aberrant splicing regulatory networks lead to dysregulated protein expression and contribute to a substantial fraction of human disease. Several classes of active and selective splicing modulator compounds have been recently identified, thus proving that pre-mRNA splicing is a viable target for therapy. We describe herein the identification of BPN-15477, a novel splicing modulator compound, that restores correct splicing of exon 20 in the Elongator complex protein 1 (ELP1) gene carrying the major IVS20+6T>C mutation responsible for familial dysautonomia. We then developed a machine learning approach to evaluate the therapeutic potential of BPN-15477 to correct splicing in other human genetic diseases. Using transcriptome sequencing from compound-treated fibroblast cells, we identified treatment responsive sequence signatures, the majority of which center at the 5 splice site of exons whose inclusion or exclusion is modulated by SMC treatment. We then leveraged this model to identify 155 human disease genes that harbor ClinVar mutations predicted to alter pre-mRNA splicing as potential targets for BPN-15477 treatment. Using in vitro splicing assays, we validated representative predictions by demonstrating successful correction of splicing defects caused by mutations in genes responsible for cystic fibrosis (CFTR), cholesterol ester storage disease (LIPA), Lynch syndrome (MLH1) and familial frontotemporal dementia (MAPT). Our study shows that deep learning techniques can identify a complex set of sequence signatures and predict response to pharmacological modulation, strongly supporting the use of in silico approaches to expand the therapeutic potential of drugs that modulate splicing.

bioinformatics↗

bioRxiv2019

NMRdock: Lightweight and Modular NMR Processing

NMR is a widely employed tool in chemistry, biology, and physics for the study of molecular structure and dynamics. Advances in computation have produced scores of software programs necessary for the processing and analysis of NMR data. However, the production of NMR software has been largely overseen by academic labs, each with their own preferred OS, environment, and dependencies. This lack of broader standardization and the complexity of installing and maintaining NMR-related software creates a barrier of entry into the field. To further complicate matters, as computation evolves, many aging software packages become deprecated. To reduce the barrier for newcomers and to prevent deprecation of aging software, we have created the NMRdock container. NMRdock utilizes containerization to package NMR processing and analysis programs into a single, easy-to-install Docker image that can be run on any modern OS. The current image contains two bedrock NMR data processing programs (NMRPipe and NMRFAM Sparky). However, future development of NMRdock aims to add modules for additional analysis programs to build a library of tools in a standardized and easy-to-implement manner. NMRdock is open source and free to download at https://compbiocore.github.io/nmrdock/.

biophysics↗

bioRxiv2019

VIVA (VIsualization of VAriants): A VCF file visualization tool

The volume and pace of data accumulation from high-throughput sequencing studies have been amplified by recent rapid technological advances in biological sciences. Visualization of genomic data is essential for quality control, exploration, and interpretation. Here, we describe a user-friendly visualization tool for variant call format (VCF) files with which the users can interactively evaluate and share genomic data, as well as create publication quality graphics.

bioinformatics↗

bioRxiv2017

Dissecting the Causal Mechanism of X-Linked Dystonia-Parkinsonism by Integrating Genome and Transcriptome Assembly

X-linked Dystonia-Parkinsonism (XDP) is a Mendelian neurodegenerative disease endemic to the Philippines. We integrated genome and transcriptome assembly with induced pluripotent stem cell-based modeling to identify the XDP causal locus and potential pathogenic mechanism. Genome sequencing identified novel variation that was shared by all probands and three recombination events that narrowed the causal locus to a genomic segment including TAF1. Transcriptome assembly in neural derivative cells discovered novel TAF1 transcripts, including a truncated transcript exclusively observed in probands that involved aberrant splicing and intron retention (IR) associated with a SINE-VNTR-Alu (SVA)-type retrotransposon insertion. This IR correlated with decreased expression of the predominant TAF1 transcript and altered expression of neurodevelopmental genes; both the IR and aberrant TAF1 expression patterns were rescued by CRISPR/Cas9 excision of the SVA. These data suggest a unique genomic cause of XDP and may provide a roadmap for integrative genomic studies in other unsolved Mendelian disorders.\n\nHighlights O_LIGenome assembly narrows the XDP causal locus to a segment including TAF1\nC_LIO_LIXDP-specific SVA insertion induces intron retention and down-regulation of TAF1\nC_LIO_LICRISPR/Cas9 excision of SVA rescues aberrant splicing and cTAF1 expression in XDP\nC_LIO_LIGene networks perturbed in proband cells associate to synapse and neurodevelopment\nC_LI

genomics↗