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Comparison of the central human and mouse platelet signaling cascade by systems biological analysis
(2020)
Background
Understanding the molecular mechanisms of platelet activation and aggregation is of high interest for basic and clinical hemostasis and thrombosis research. The central platelet protein interaction network is involved in major responses to exogenous factors. This is defined by systemsbiological pathway analysis as the central regulating signaling cascade of platelets (CC).
Results
The CC is systematically compared here between mouse and human and major differences were found. Genetic differences were analysed comparing orthologous human and mouse genes. We next analyzed different expression levels of mRNAs. Considering 4 mouse and 7 human high-quality proteome data sets, we identified then those major mRNA expression differences (81%) which were supported by proteome data. CC is conserved regarding genetic completeness, but we observed major differences in mRNA and protein levels between both species. Looking at central interactors, human PLCB2, MMP9, BDNF, ITPR3 and SLC25A6 (always Entrez notation) show absence in all murine datasets. CC interactors GNG12, PRKCE and ADCY9 occur only in mice. Looking at the common proteins, TLN1, CALM3, PRKCB, APP, SOD2 and TIMP1 are higher abundant in human, whereas RASGRP2, ITGB2, MYL9, EIF4EBP1, ADAM17, ARRB2, CD9 and ZYX are higher abundant in mouse. Pivotal kinase SRC shows different regulation on mRNA and protein level as well as ADP receptor P2RY12.
Conclusions
Our results highlight species-specific differences in platelet signaling and points of specific fine-tuning in human platelets as well as murine-specific signaling differences.
CDC14A encodes the Cell Division Cycle 14A protein and has been associated with autosomal recessive non-syndromic hearing loss (DFNB32), as well as hearing impairment and infertile male syndrome (HIIMS) since 2016. To date, only nine variants have been associated in patients whose initial symptoms included moderate-to-profound hearing impairment. Exome analysis of Iranian and Pakistani probands who both showed bilateral, sensorineural hearing loss revealed a novel splice site variant (c.1421+2T>C, p.?) that disrupts the splice donor site and a novel frameshift variant (c.1041dup, p.Ser348Glnfs*2) in the gene CDC14A, respectively. To evaluate the pathogenicity of both loss-of-function variants, we analyzed the effects of both variants on the RNA-level. The splice variant was characterized using a minigene assay. Altered expression levels due to the c.1041dup variant were assessed using RT-qPCR. In summary, cDNA analysis confirmed that the c.1421+2T>C variant activates a cryptic splice site, resulting in a truncated transcript (c.1414_1421del, p.Val472Leufs*20) and the c.1041dup variant results in a defective transcript that is likely degraded by nonsense-mediated mRNA decay. The present study functionally characterizes two variants and provides further confirmatory evidence that CDC14A is associated with a rare form of hereditary hearing loss.
The current molecular genetic diagnostic rates for hereditary hearing loss (HL) vary considerably according to the population background. Pakistan and other countries with high rates of consanguineous marriages have served as a unique resource for studying rare and novel forms of recessive HL. A combined exome sequencing, bioinformatics analysis, and gene mapping approach for 21 consanguineous Pakistani families revealed 13 pathogenic or likely pathogenic variants in the genes GJB2, MYO7A, FGF3, CDC14A, SLITRK6, CDH23, and MYO15A, with an overall resolve rate of 61.9%. GJB2 and MYO7A were the most frequently involved genes in this cohort. All the identified variants were either homozygous or compound heterozygous, with two of them not previously described in the literature (15.4%). Overall, seven missense variants (53.8%), three nonsense variants (23.1%), two frameshift variants (15.4%), and one splice-site variant (7.7%) were observed. Syndromic HL was identified in five (23.8%) of the 21 families studied. This study reflects the extreme genetic heterogeneity observed in HL and expands the spectrum of variants in deafness-associated genes.
In Brassicaceae, tissue damage triggers the mustard oil bomb i.e., activates the degradation of glucosinolates by myrosinases leading to a rapid accumulation of isothiocyanates at the site of damage. Isothiocyanates are reactive electrophilic species (RES) known to covalently bind to thiols in proteins and glutathione, a process that is not only toxic to herbivores and microbes but can also cause cell death of healthy plant tissues. Previously, it has been shown that subtoxic isothiocyanate concentrations can induce transcriptional reprogramming in intact plant cells. Glutathione depletion by RES leading to breakdown of the redox potential has been proposed as a central and common RES signal transduction mechanism. Using transcriptome analyses, we show that after exposure of Arabidopsis seedlings (grown in liquid culture) to subtoxic concentrations of sulforaphane hundreds of genes were regulated without depletion of the cellular glutathione pool. Heat shock genes were among the most highly up-regulated genes and this response was found to be dependent on the canonical heat shock factors A1 (HSFA1). HSFA1-deficient plants were more sensitive to isothiocyanates than wild type plants. Moreover, pretreatment of Arabidopsis seedlings with subtoxic concentrations of isothiocyanates increased resistance against exposure to toxic levels of isothiocyanates and, hence, may reduce the autotoxicity of the mustard oil bomb by inducing cell protection mechanisms.
Objective
The biological interpretation of gene expression measurements is a challenging task. While ordination methods are routinely used to identify clusters of samples or co-expressed genes, these methods do not take sample or gene annotations into account. We aim to provide a tool that allows users of all backgrounds to assess and visualize the intrinsic correlation structure of complex annotated gene expression data and discover the covariates that jointly affect expression patterns.
Results
The Bioconductor package covRNA provides a convenient and fast interface for testing and visualizing complex relationships between sample and gene covariates mediated by gene expression data in an entirely unsupervised setting. The relationships between sample and gene covariates are tested by statistical permutation tests and visualized by ordination. The methods are inspired by the fourthcorner and RLQ analyses used in ecological research for the analysis of species abundance data, that we modified to make them suitable for the distributional characteristics of both, RNA-Seq read counts and microarray intensities, and to provide a high-performance parallelized implementation for the analysis of large-scale gene expression data on multi-core computational systems. CovRNA provides additional modules for unsupervised gene filtering and plotting functions to ensure a smooth and coherent analysis workflow.