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Riella, C. V.

Publications and source records attributed to Riella, C. V..

2 recordsLinked to original sources

a2iHelper: a Python toolkit for a differential editing site analysis of RNA-Seq data

BackgroundA-to-I RNA editing, mediated by ADAR enzymes, plays a crucial role in cancer and autoimmune disorders but lacks standardized tools for differential analysis. After reviewing 55 studies, it highlights significant methodological heterogeneity, hindering result comparability and reproducibility. To address this, we developed a2iHelper, a Python package that streamlines RNA editing analysis by filtering noise, performing statistical analyses, and generating visualizations. a2iHelper integrates seamlessly with Python machine learning tools, aiming to standardize and simplify RNA editing research. ResultsWe applied our methods to analyze A-to-I editing in a public dataset comparing wild-type and ADAR knockout. The source code is open, freely available on GitHub, and organized in a well-documented Python package. Using Snakemake for preprocessing, we conducted differential editing analysis on the top 104 most edited genes. The results include p-values from statistical tests, Odds ratios for Manhattan plots, and correlations between editing frequencies and gene expression, visualized in various plots. ConclusionsWe developed a2iHelper, a Python-based package for analyzing and visualizing A-to-I RNA editing data. It allows researchers with minimal programming experience to perform organized, reproducible editing analyses. Novice users can easily detect editing sites, filter noise, and generate figures, while advanced users can integrate functionalities into their workflows. a2iHelper runs on personal computers without needing High-Performance Computing resources.

bioinformatics↗

Missense Mutant Gain-of-Function Causes Inverted Formin 2 (INF2)-Related Focal Segmental Glomerulosclerosis (FSGS)

Inverted formin-2 (INF2) gene mutations are among the most common causes of genetic focal segmental glomerulosclerosis (FSGS) with or without Charcot-Marie-Tooth (CMT) disease. Recent studies suggest that INF2, through its effects on actin and microtubule arrangement, can regulate processes including vesicle trafficking, cell adhesion, mitochondrial calcium uptake, mitochondrial fission, and T-cell polarization. Despite roles for INF2 in multiple cellular processes, neither the human pathogenic R218Q INF2 point mutation nor the INF2 knock-out allele is sufficient to cause disease in mice. This discrepancy challenges our efforts to explain the disease mechanism, as the link between INF2-related processes, podocyte structure, disease inheritance pattern, and their clinical presentation remains enigmatic. Here, we compared the kidney responses to puromycin aminonucleoside (PAN) induced injury between R218Q INF2 point mutant knock-in and INF2 knock-out mouse models and show that R218Q INF2 mice are susceptible to developing proteinuria and FSGS. This contrasts with INF2 knock-out mice, which show only a minimal kidney phenotype. Co-localization and co-immunoprecipitation analysis of wild-type and mutant INF2 coupled with measurements of cellular actin content revealed that the R218Q INF2 point mutation confers a gain-of-function effect by altering the actin cytoskeleton, facilitated in part by alterations in INF2 localization. Differential analysis of RNA expression in PAN-stressed heterozygous R218Q INF2 point-mutant and heterozygous INF2 knock-out mouse glomeruli showed that the adhesion and mitochondria-related pathways were significantly enriched in the disease condition. Mouse podocytes with R218Q INF2, and an INF2-mutant human patients kidney organoid-derived podocytes with an S186P INF2 mutation, recapitulate the defective adhesion and mitochondria phenotypes. These results link INF2-regulated cellular processes to the onset and progression of glomerular disease. Thus, our data demonstrate that gain-of-function mechanisms drive INF2-related FSGS and explain the autosomal dominant inheritance pattern of this disease.

genetics↗