eVITTA: a web-based visualization and inference toolbox for transcriptome analysis.

Transcriptome profiling is essential for gene regulation studies in development and disease. Current web-based tools enable functional characterization of transcriptome data, but most are restricted to applying gene-list-based methods to single datasets, inefficient in leveraging up-to-date and species-specific information, and limited in their visualization options. Additionally, there is no systematic way to explore data stored in the largest transcriptome repository, NCBI GEO. To fill these gaps, we have developed eVITTA (easy Visualization and Inference Toolbox for Transcriptome Analysis; https://tau.cmmt.ubc.ca/eVITTA/). eVITTA provides modules for analysis and exploration of studies published in NCBI GEO (easyGEO), detailed molecular- and systems-level functional profiling (easyGSEA), and customizable comparisons among experimental groups (easyVizR). We tested eVITTA on transcriptomes of SARS-CoV-2 infected human nasopharyngeal swab samples, and identified a downregulation of olfactory signal transducers, in line with the clinical presentation of anosmia in COVID-19 patients. We also analyzed transcriptomes of Caenorhabditis elegans worms with disrupted S-adenosylmethionine metabolism, confirming activation of innate immune responses and feedback induction of one-carbon cycle genes. Collectively, eVITTA streamlines complex computational workflows into an accessible interface, thus filling the gap of an end-to-end platform capable of capturing both broad and granular changes in human and model organism transcriptomes.

Invertebrate Models Untangle the Mechanism of Neurodegeneration in Parkinson's Disease.

Parkinson's disease (PD) is the second most common neurodegenerative disease, afflicting ~10 million people worldwide. Although several genes linked to PD are currently identified, PD remains primarily an idiopathic disorder. Neuronal protein α-synuclein is a major player in disease progression of both genetic and idiopathic forms of PD. However, it cannot alone explain underlying pathological processes. Recent studies demonstrate that many other risk factors can accelerate or further worsen brain dysfunction in PD patients. Several PD models, including non-mammalian eukaryotic organisms, have been developed to identify and characterize these factors. This review discusses recent findings in three PD model organisms, i.e., yeast, Drosophila, and Caenorhabditis elegans, that opened new mechanisms and identified novel contributors to this disorder. These non-mammalian models share many conserved molecular pathways and cellular processes with humans. New players affecting PD pathogenesis include previously unknown genes/proteins, novel signaling pathways, and low molecular weight substances. These findings might respond to the urgent need to discover novel drug targets for PD treatment and new biomarkers for early diagnostics of this disease. Since the study of neurodegeneration using simple eukaryotic organisms brought a huge amount of information, we include only the most recent or the most important relevant data.