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Biology subjects

Swamy, V. S.

Publications and source records attributed to Swamy, V. S..

5 recordsLinked to original sources

PLAE web app enables powerful searching and multiple visualizations across one million unified single-cell ocular transcriptomes

PURPOSETo create a high performance reactive web application to query single cell gene expression data across cell type, species, study, and other factors. METHODSWe updated the content and structure of the underlying data (single cell Eye in a Disk, scEiaD) and wrote the web application PLAE (https://plae.nei.nih.gov) to visualize and explore it. RESULTSThe new portal provides quick visualization of over a million individual cells from vertebrate eye-and body transcriptomes encomopassing four species, 60 cell types, six ocular tissues, and 23 body tissues across 37 publications. To demonstrate the value of this unified pan-eye dataset, we replicate known neurogenic and cone macula markers as well as propose six new cone human region markers. CONCLUSIONThe PLAE web application provides the eye community a powerful and quick means to test hypotheses related to gene expression across a highly diverse, community-derived database.

genomics↗

Building the Mega Single Cell Transcriptome Ocular Meta-Atlas

The development of highly scalable single cell transcriptome technology has resulted in the creation of thousands of datasets, over 30 in the retina alone. Analyzing the transcriptomes between different projects is highly desirable as this would allow for better assessment of which biological effects are consistent across independent studies. However it is difficult to compare and contrast data across different projects as there are substantial batch effects from computational processing, single cell technology utilized, and the natural biological variation. While many single cell transcriptome specific batch correction methods purport to remove the technical noise it is difficult to ascertain which method functions works best. We developed a lightweight R package (scPOP) that brings in batch integration methods and uses a simple heuristic to balance batch merging and celltype/cluster purity. We use this package along with a Snakefile based workflow system to demonstrate how to optimally merge 766,615 cells from 33 retina datsets and three species to create a massive ocular single cell transcriptome meta-atlas. This provides a model how to efficiently create meta-atlases for tissues and cells of interest.

bioinformatics↗

A short read de novo transcriptome construction pipeline optimized by long reads reveals novel developmentally regulated gene isoforms and disease targets in hundreds of eye samples

De novo transcriptome construction from short-read RNA-seq is a common method for reconstructing mRNA transcripts within a given sample. However, the precision of this process is unclear as it is difficult to obtain a ground-truth measure of transcript expression. With advances in third generation sequencing, full length transcripts of whole transcriptomes can be accurately sequenced to generate a ground-truth transcriptome. We generated long-read PacBio and short-read Illumina RNA-seq data from a human induced pluripotent stem cell- derived retinal pigmented epithelium (iPSC-RPE) cell line. We use long-read data to identify simple metrics for assessing de novo transcriptome construction and optimize a short-read based de novo transcriptome construction pipeline. We apply this this pipeline to construct transcriptomes for 340 short-read RNA-seq samples originating from healthy adult and fetal human retina, cornea, and RPE. We identify hundreds of novel gene isoforms and examine their significance in the context of ocular development and disease.

genomics↗

Phenotypic and functional characterization of corneal endothelial cells during in vitro expansion

The advent of cell culture-based methods for the establishment and expansion of human corneal endothelial cells (CEnC) has provided a source of transplantable corneal endothelium, with a significant potential to challenge the one donor-one recipient paradigm. However, concerns over cell identity remain, and a comprehensive characterization of the cultured CEnC across serial passages has not been performed. To this end, we compared two established CEnC culture methods by assessing the transcriptomic changes that occur during in vitro expansion. In confluent monolayers, low mitogenic culture conditions preserved corneal endothelial cell state identity better than culture in high mitogenic conditions. Expansion by continuous passaging induced replicative cell senescence. Transcriptomic analysis of the senescent phenotype identified a cell senescence signature distinct for CEnC. We identified activation of both classic and new cell signaling pathways that may be targeted to prevent senescence, a significant barrier to realizing the potential clinical utility of in vitro expansion.

cell biology↗

ZEB1 insufficiency causes corneal endothelial cell state transition and altered cellular processing

The zinc finger e-box binding homeobox 1 (ZEB1) transcription factor is a master regulator of the epithelial to mesenchymal transition (EMT), and of the reverse mesenchymal to epithelial transition (MET) processes. ZEB1 plays an integral role in mediating cell state transitions during cell lineage specification, wound healing and disease. EMT/MET are characterized by distinct changes in molecular and cellular phenotype that are generally context-independent. Posterior polymorphous corneal dystrophy (PPCD), associated with ZEB1 insufficiency, provides a new biological context in which to understand and evaluate the classic EMT/MET paradigm. PPCD is characterized by a cadherin-switch and transition to an epithelial-like transcriptomic and cellular phenotype, which we study in a cell-based model of PPCD generated using CRISPR-Cas9-mediated ZEB1 knockout in corneal endothelial cells (CEnCs). Transcriptomic and functional studies support the hypothesis that CEnC undergo a MET-like transition in PPCD, termed endothelial to epithelial transition (EnET), and lead to the conclusion that EnET may be considered a corollary to the classic EMT/MET paradigm.

cell biology↗