scholarly journals Effect of SARS-CoV-2 infection on host competing endogenous RNA and miRNA network

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12370
Author(s):  
Selcen Ari Yuka ◽  
Alper Yilmaz
Keyword(s):  
Large Scale ◽  
Network Effects ◽  
Metabolic Diseases ◽  
Competitive Behavior ◽  
Sequencing Data ◽  
Cell Functions ◽  
Large Scale Analysis ◽  
Competing Endogenous Rnas ◽  
Infected Cells ◽  
Regulatory Functions

Competing endogenous RNAs (ceRNA) play a crucial role in cell functions. Computational methods that provide large-scale analysis of the interactions between miRNAs and their competitive targets can contribute to the understanding of ceRNA regulations and critical regulatory functions. Recent reports showed that viral RNAs can compete with host RNAs against host miRNAs. Regarding SARS-CoV-2 RNA, no comprehensive study had been reported about its competition with cellular ceRNAs. In this study, for the first time, we used the ceRNAnetsim package to assess ceRNA network effects per individual cell and competitive behavior of SARS-CoV-2 RNA in the infected cells using single-cell sequencing data. Our computations identified 195 genes and 29 miRNAs which vary in competitive behavior specifically in presence of SARS-CoV-2 RNA. We also investigated 18 genes that are affected by genes that lost perturbation ability in presence of SARS-CoV-2 RNA in the human miRNA:ceRNA network. These transcripts have associations with COVID-19-related symptoms as well as many dysfunctions such as metabolic diseases, carcinomas, heart failure. Our results showed that the effects of the SARS-CoV-2 genome on host ceRNA interactions and consequent dysfunctions can be explained by competition among various miRNA targets. Our perturbation ability perspective has the potential to reveal yet to be discovered SARS-CoV-2 induced effects invisible to conventional approaches.

scholarly journals ASCOT identifies key regulators of neuronal subtype-specific splicing

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Jonathan P. Ling ◽  
Christopher Wilks ◽  
Rone Charles ◽  
Patrick J. Leavey ◽  
Devlina Ghosh ◽  
...  
Keyword(s):  
Rna Splicing ◽  
Large Scale ◽  
Splice Variants ◽  
Next Generation Sequencing Data ◽  
Data Sets ◽  
Cell Type ◽  
Sequencing Data ◽  
Large Scale Analysis ◽  
Cell Type Specific ◽  
Public Archives

AbstractPublic archives of next-generation sequencing data are growing exponentially, but the difficulty of marshaling this data has led to its underutilization by scientists. Here, we present ASCOT, a resource that uses annotation-free methods to rapidly analyze and visualize splice variants across tens of thousands of bulk and single-cell data sets in the public archive. To demonstrate the utility of ASCOT, we identify novel cell type-specific alternative exons across the nervous system and leverage ENCODE and GTEx data sets to study the unique splicing of photoreceptors. We find that PTBP1 knockdown and MSI1 and PCBP2 overexpression are sufficient to activate many photoreceptor-specific exons in HepG2 liver cancer cells. This work demonstrates how large-scale analysis of public RNA-Seq data sets can yield key insights into cell type-specific control of RNA splicing and underscores the importance of considering both annotated and unannotated splicing events.

scholarly journals Correction: Evidence for plant-derived xenomiRs based on a large-scale analysis of public small RNA sequencing data from human samples

PLoS ONE ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. e0230146
Author(s):  
Qi Zhao ◽  
Yuanning Liu ◽  
Ning Zhang ◽  
Menghan Hu ◽  
Hao Zhang ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Small Rna ◽  
Large Scale ◽  
Small Rna Sequencing ◽  
Scale Analysis ◽  
Sequencing Data ◽  
Human Samples ◽  
Large Scale Analysis

scholarly journals Genotype-Phenotype Relations of the von Hippel-Lindau Tumor Suppressor Inferred from a Large-Scale Analysis of Disease Mutations and Interactors

2018 ◽  
Author(s):  
Giovanni Minervini ◽  
Federica Quaglia ◽  
Francesco Tabaro ◽  
Silvio C.E. Tosatto
Keyword(s):  
Tumor Suppressor ◽  
Large Scale ◽  
Specific Cell ◽  
Scale Analysis ◽  
Cancer Syndrome ◽  
Von Hippel Lindau ◽  
Cell Functions ◽  
Large Scale Analysis ◽  
Tumor Transformation ◽  
Cancer Types

AbstractFamiliar cancers represent a privileged point of view for studying the complex cellular events inducing tumor transformation. Von Hippel-Lindau syndrome, a familiar predisposition to develop cancer is a clear example. Here, we present our efforts to decipher the role of von Hippel-Lindau tumor suppressor protein (pVHL) in cancer insurgence. We collected high quality information about both pVHL mutations and interactors to investigate the association between patient phenotypes, mutated protein surface and impaired interactions. Our data suggest that different phenotypes correlate with localized perturbations of the pVHL structure, with specific cell functions associated to different protein surfaces. We propose five different pVHL interfaces to be selectively involved in modulating proteins regulating gene expression, protein homeostasis as well as to address extracellular matrix (ECM) and ciliogenesis associated functions. These data were used to drive molecular docking of pVHL with its interactors and guide Petri net simulations of the most promising alterations. We predict that disruption of pVHL association with certain interactors can trigger tumor transformation, inducing metabolism imbalance and ECM remodeling. Collectively taken, our findings provide novel insights into VHL-associated tumorigenesis. This highly integrated in silico approach may help elucidate novel treatment paradigms for VHL disease.Author summaryCancer is generally caused by a series of mutations accumulating over time in a healthy tissue, which becomes re-programmed to proliferate at the expense of the hosting organism. This process is difficult to follow and understand as events in a multitude of different genes can lead to similar outcomes without apparent cause. The von Hippel-Lindau (VHL) tumor suppressor is one of the few genes harboring a familiar cancer syndrome, i.e. VHL mutations are known to cause a predictable series of events leading cancer in the kidneys and a few selected other tissues. This article describes a large-scale analysis to relate known VHL mutations to specific cancer pathways by looking at the molecular interactions. Different cancer types appear to be caused by mutations changing the surface of specific parts of the VHL protein. By looking at the VHL interactors involved, it is therefore possible to identify other candidate genes for mutations leading to very similar cancer types.

scholarly journals Evidence for plant-derived xenomiRs based on a large-scale analysis of public small RNA sequencing data from human samples

PLoS ONE ◽  
2018 ◽  
Vol 13 (6) ◽  
pp. e0187519 ◽  
Author(s):  
Qi Zhao ◽  
Yuanning Liu ◽  
Ning Zhang ◽  
Menghan Hu ◽  
Hao Zhang ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Small Rna ◽  
Large Scale ◽  
Small Rna Sequencing ◽  
Scale Analysis ◽  
Sequencing Data ◽  
Human Samples ◽  
Large Scale Analysis

scholarly journals Correction: Evidence for plant-derived xenomiRs based on a large-scale analysis of public small RNA sequencing data from human samples

PLoS ONE ◽  
2019 ◽  
Vol 14 (10) ◽  
pp. e0224537 ◽  
Author(s):  
Qi Zhao ◽  
Yuanning Liu ◽  
Ning Zhang ◽  
Menghan Hu ◽  
Hao Zhang ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Small Rna ◽  
Large Scale ◽  
Small Rna Sequencing ◽  
Scale Analysis ◽  
Sequencing Data ◽  
Human Samples ◽  
Large Scale Analysis

scholarly journals Superinfection and cure of infected cells as mechanisms for hepatitis C virus adaptation and persistence

2018 ◽  
Vol 115 (30) ◽  
pp. E7139-E7148 ◽  
Author(s):  
Ruian Ke ◽  
Hui Li ◽  
Shuyi Wang ◽  
Wenge Ding ◽  
Ruy M. Ribeiro ◽  
...  
Keyword(s):  
Hepatitis C Virus ◽  
Viral Load ◽  
Hepatitis C ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Antiviral Treatment ◽  
Strong Support ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Infected Cells

RNA viruses exist as a genetically diverse quasispecies with extraordinary ability to adapt to abrupt changes in the host environment. However, the molecular mechanisms that contribute to their rapid adaptation and persistence in vivo are not well studied. Here, we probe hepatitis C virus (HCV) persistence by analyzing clinical samples taken from subjects who were treated with a second-generation HCV protease inhibitor. Frequent longitudinal viral load determinations and large-scale single-genome sequence analyses revealed rapid antiviral resistance development, and surprisingly, dynamic turnover of dominant drug-resistant mutant populations long after treatment cessation. We fitted mathematical models to both the viral load and the viral sequencing data, and the results provided strong support for the critical roles that superinfection and cure of infected cells play in facilitating the rapid turnover and persistence of viral populations. More broadly, our results highlight the importance of considering viral dynamics and competition at the intracellular level in understanding rapid viral adaptation. Thus, we propose a theoretical framework integrating viral and molecular mechanisms to explain rapid viral evolution, resistance, and persistence despite antiviral treatment and host immune responses.

scholarly journals Utilities for High-Throughput Analysis of B-Cell Clonal Lineages

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
William D. Lees ◽  
Adrian J. Shepherd
Keyword(s):  
B Cell ◽  
Large Scale ◽  
Cell Lineage ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
High Throughput Analysis ◽  
Large Scale Analysis ◽  
Automated Pipeline ◽  
Lineage Trees ◽  
Generation Sequencing

There are at present few tools available to assist with the determination and analysis of B-cell lineage trees from next-generation sequencing data. Here we present two utilities that support automated large-scale analysis and the creation of publication-quality results. The tools are available on the web and are also available for download so that they can be integrated into an automated pipeline. Critically, and in contrast to previously published tools, these utilities can be used with any suitable phylogenetic inference method and with any antibody germline library and hence are species-independent.

СОЦИАЛЬНО-ЭКОНОМИЧЕСКИЕ КОНФЛИКТЫ В РАМКАХ «КАПИТАЛИЗМА ПЛАТФОРМ»

2019 ◽  
Vol 14 (3) ◽  
pp. 33
Author(s):  
L. V. Tomin
Keyword(s):  
Large Scale ◽  
Network Effects ◽  
Corporate Control ◽  
Balance Of Power ◽  
Negative Effects ◽  
Potential Threat ◽  
Communication Infrastructure ◽  
Political Effects ◽  
Information And Communication ◽  
Integrated Information

The article is devoted to the analysis of the structure, the peculiarities of functioning and the socio-economic and political effects of the «platform capitalism». The basis of this model is the network effects produced by the integrated information and communication infrastructure, which contribute to the monopolization and the constant expansion of platform companies into new areas. The principle of functioning of this infrastructure is the continuous collection and further monetization of data extracted from the interactions of individuals among themselves or with one of the elements of a digitalized economy or government structures. Such an infrastructure — forms a potential threat of strengthening state and corporate control over citizens. In addition, the activities of platform companies produce negative effects on the labor market, reinforcing the process of precarization of employment. The integrated information and communication infrastructure of platform companies form a system of a kind of «digital Taylorism», which deprives the employee of autonomy and privacy in the workplace. The influence of digitalization, subjected to the technocratic logic of the neoliberal model of governance in democratic countries, strengthens the de-politicization of relations between the citizen and the state and further changes the balance of power between labor and capital in favor of the latter. Large-scale protests of the last years against the companies of “capitalism of platforms” demonstrated the structural contradictions of this model and formed new forms of organization and actions of grassroots workers of the “digital economy”.

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