Current Issue : April-June Volume : 2025 Issue Number : 2 Articles : 5 Articles
Background/Objectives: Biallelic mutations in the PTRH2 gene are associated with a rare genetic disease known as infantile-onset multisystem neurologic, endocrine, and pancreatic disease (IMNEPD). In this study, we describe a new case carrying a previously identified mutation, provide an updated analysis of the relative frequencies of the clinical features across all published cases (including the three latest studies), and perform a bioinformatics analysis of the newly identified PTRH2 protein variants from a structural perspective. Methods: Clinical examination of the patients was carried out, and genetic testing was performed using a genome sequencing strategy. A bioinformatics analysis was carried out for the newly reported mutations using PYMOL that was utilized to view the structure and analyze the mutations. Additionally, the ThermoMPNN webserver was employed to check the effect of point mutations on the overall stability of the protein. Results: Our findings indicate that motor delay, neuropathy, intellectual disability, distal weakness, hearing impairment, and ataxia are the most common symptoms, while the other clinical features fall into two frequency categories: moderately common ones and the least common ones. The bioinformatics analysis revealed that the Q85 residue is highly conserved, suggesting that mutations at this position could disrupt key signaling pathways or cellular functions. Indeed, the Q85R mutation was shown to significantly impair the stability and functionality of the protein. Conclusions: The clinical presentation of IMNEPD remains highly variable in terms of both severity and progression. Mutations at the Q85 residue have been identified in nearly 50% of reported cases, highlighting this position as a potential mutational hotspot in the PTRH2 protein....
The high recurrence rate of feline meningioma despite the generally benign histomorphology warrants additional markers of clinical aggressiveness. The Ki-67 index is commonly used as prognostic marker for meningioma recurrence in people. Osteopontin (OPN) is a protein involved in tumor progression and may be a potential malignancy marker. To date, osteopontin expression has not been investigated in feline meningioma. The aim of this study was to evaluate the extent of Ki-67 and osteopontin immunostaining of feline meningioma and to find possible associations with WHO (World Health Organization) grades and subtypes. Fifty-three feline meningioma samples were graded according to the human WHO classification and underwent immunohistochemical examination for Ki-67 and OPN. Fifty samples were classified as WHO grade I and three as WHO grade II. The mean Ki-67 ratio was 9.19 ± 9.47. Osteopontin expression was correspondingly high with a mean OPN IHC score of 150.17 (0–242.8), and a median Allred score of 7 (0–8). There was no significant correlation with Ki-67 index, osteopontin expression, WHO grades, or subtypes. The overall high expressions of osteopontin and Ki-67 may help explain the tendency for recurrence of feline meningioma. The human WHO grading system may not be sufficient to accurately estimate the clinical behavior of meningioma in this species....
Metagenomics analysis has enabled the measurement of the microbiome diversity in environmental samples without prior targeted enrichment. Functional and phylogenetic studies based on microbial diversity retrieved using HTS platforms have advanced from detecting known organisms and discovering unknown species to applications in disease diagnostics. Robust validation processes are essential for test reliability, requiring standard samples and databases deriving from real samples and in silico generated artificial controls. We propose a MeStanG as a resource for generating HTS Nanopore data sets to evaluate present and emerging bioinformatics pipelines. MeStanG allows samples to be designed with user-defined organism abundances expressed as number of reads, reference sequences, and predetermined or custom errors by sequencing profiles. The simulator pipeline was evaluated by analyzing its output mock metagenomic samples containing known read abundances using read mapping, genome assembly, and taxonomic classification on three scenarios: a bacterial community composed of nine different organisms, samples resembling pathogen-infected wheat plants, and a viral pathogen serial dilution sampling. The evaluation was able to report consistently the same organisms, and their read abundances as provided in the mock metagenomic sample design. Based on this performance and its novel capacity of generating exact number of reads, MeStanG can be used by scientists to develop mock metagenomic samples (artificial HTS data sets) to assess the diagnostic performance metrics of bioinformatic pipelines, allowing the user to choose predetermined or customized models for research and training....
Background: Over the last decade the drop in short-read sequencing costs has allowed experimental techniques utilizing sequencing to address specific biological questions to proliferate, oftentimes outpacing standardized or effective analysis approaches for the data generated. There are growing amounts of bacterial 3-end sequencing data, yet there is currently no commonly accepted analysis methodology for this datatype. Most data analysis approaches are somewhat ad hoc and, despite the presence of substantial signal within annotated genes, focus on genomic regions outside the annotated genes (e.g. 3 or 5 UTRs). Furthermore, the lack of consistent systematic analysis approaches, as well as the absence of genome-wide ground truth data, make it impossible to compare conclusions generated by different labs, using different organisms. Results: We present PIPETS, (Poisson Identification of PEaks from Term-Seq data), an R package available on Bioconductor that provides a novel analysis method for 3’-end sequencing data. PIPETS is a statistically informed, gene-annotation agnostic methodology. Across two different datasets from two different organisms, PIPETS identified significant 3’-end termination signal across a wider range of annotated genomic contexts than existing analysis approaches, suggesting that existing approaches may miss biologically relevant signal. Furthermore, assessment of the previously called 3-end positions not captured by PIPETS showed that they were uniformly very low coverage. Conclusions: PIPETS provides a broadly applicable platform to explore and analyze 3-end sequencing data sets from across different organisms. It requires only the 3-end sequencing data, and is broadly accessible to non-expert users....
Background: Rare copy number variants (CNVs) significantly influence the human genome and may contribute to disease susceptibility. High-throughput SNP genotyping platforms provide data that can be used for CNV detection, but it requires the complex pipelining of bioinformatic tools. Here, we propose a flexible bioinformatic pipeline for rare CNV analysis from human SNP array data. Results: The pipeline consists of two major sub-pipelines: (1) Calling and quality control (QC) analysis, and (2) Rare CNV analysis. It is implemented in Snakemake following a rule-based structure that enables automation and scalability while maintaining flexibility. Conclusions: Our pipeline automates the detection and analysis of rare CNVs. It implements a rigorous CNV quality control, assesses the frequencies of these rare CNVs in patients versus controls, and evaluates the impact of CNVs on specific genes or pathways. We hence aim to provide an efficient yet flexible bioinformatic framework to investigate rare CNVs in biomedical research....
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