scholarly journals Molecular Mediators of RNA Loading into Extracellular Vesicles

Cells ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3355
Author(s):  
Chiara Corrado ◽  
Maria Magdalena Barreca ◽  
Chiara Zichittella ◽  
Riccardo Alessandro ◽  
Alice Conigliaro
Keyword(s):  
Gene Expression ◽  
Extracellular Vesicles ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Translation Regulation ◽  
Circular Rnas ◽  
Non Coding Rna ◽  
Gene Regulatory ◽  
Non Coding Rnas ◽  
Different Levels

In the last decade, an increasing number of studies have demonstrated that non-coding RNA (ncRNAs) cooperate in the gene regulatory networks with other biomolecules, including coding RNAs, DNAs and proteins. Among them, microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) are involved in transcriptional and translation regulation at different levels. Intriguingly, ncRNAs can be packed in vesicles, released in the extracellular space, and finally internalized by receiving cells, thus affecting gene expression also at distance. This review focuses on the mechanisms through which the ncRNAs can be selectively packaged into extracellular vesicles (EVs).

scholarly journals An Evaluation of Information Technology of Gene Expression Profiles Processing Stability for Different Levels of Noise Component

2018 ◽  
Author(s):  
Sergii Babichev
Keyword(s):  
Gene Expression ◽  
Information Technology ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Noise Component ◽  
Gene Regulatory ◽  
Processing Stability ◽  
Different Levels

The paper presents the results of the research concerning an evaluation of information 1 technology of gene expression profiles processing stability with the use of gene expression profiles 2 with different levels of noise component. The information technology is presented as a structural 3 block-chart, which contains all stages of the studied data processing. The hybrid model of objective 4 clustering based on SOTA algorithm and the technology of gene regulatory networks reconstruction 5 have been studied to evaluate the stability to the level of the noise component. The results of the 6 simulation have shown that the hybrid model of objective clustering has high level of stability 7 to noise component and vice versa, the technology of gene regulatory networks reconstruction is 8 very sensitivity to level of noise component. The obtained results indicate the importance of gene 9 expression profiles preprocessing at early stage of gene regulatory network reconstruction in order to 10 remove background noise and non-informative genes in terms of used criteria

scholarly journals An Evaluation of the Information Technology of Gene Expression Profiles Processing Stability for Different Levels of Noise Components

Data ◽  
2018 ◽  
Vol 3 (4) ◽  
pp. 48 ◽  
Author(s):  
Sergii Babichev
Keyword(s):  
Gene Expression ◽  
Information Technology ◽  
Hybrid Model ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Regulatory ◽  
Processing Stability ◽  
Different Levels

This paper presents the results of research concerning the evaluation of stability of information technology of gene expression profiles processing with the use of gene expression profiles, which contain different levels of noise components. The information technology is presented as a structural block-chart, which contains all stages of the studied data processing. The hybrid model of objective clustering based on the SOTA algorithm and the technology of gene regulatory networks reconstruction have been investigated to evaluate the stability to the level of the noise components. The results of the simulation have shown that the hybrid model of the objective clustering has high level of stability to noise components and vice versa, the technology of gene regulatory networks reconstruction is rather sensitive to the level of noise component. The obtained results indicate the importance of gene expression profiles preprocessing at the early stage of the gene regulatory network reconstruction in order to remove background noise and non-informative genes in terms of the used criteria.

scholarly journals GATA-targeted compounds modulate cardiac subtype cell differentiation in dual reporter stem cell line

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Mika J. Välimäki ◽  
Robert S. Leigh ◽  
Sini M. Kinnunen ◽  
Alexander R. March ◽  
Ana Hernández de Sande ◽  
...  
Keyword(s):  
Gene Expression ◽  
Progenitor Cells ◽  
Cell Fate ◽  
Reporter Gene ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Cell Fate Decisions ◽  
Dual Reporter ◽  
Gene Regulatory ◽  
Reporter Gene Assays

AbstractBackgroundPharmacological modulation of cell fate decisions and developmental gene regulatory networks holds promise for the treatment of heart failure. Compounds that target tissue-specific transcription factors could overcome non-specific effects of small molecules and lead to the regeneration of heart muscle following myocardial infarction. Due to cellular heterogeneity in the heart, the activation of gene programs representing specific atrial and ventricular cardiomyocyte subtypes would be highly desirable. Chemical compounds that modulate atrial and ventricular cell fate could be used to improve subtype-specific differentiation of endogenous or exogenously delivered progenitor cells in order to promote cardiac regeneration.MethodsTranscription factor GATA4-targeted compounds that have previously shown in vivo efficacy in cardiac injury models were tested for stage-specific activation of atrial and ventricular reporter genes in differentiating pluripotent stem cells using a dual reporter assay. Chemically induced gene expression changes were characterized by qRT-PCR, global run-on sequencing (GRO-seq) and immunoblotting, and the network of cooperative proteins of GATA4 and NKX2-5 were further explored by the examination of the GATA4 and NKX2-5 interactome by BioID. Reporter gene assays were conducted to examine combinatorial effects of GATA-targeted compounds and bromodomain and extraterminal domain (BET) inhibition on chamber-specific gene expression.ResultsGATA4-targeted compounds 3i-1000 and 3i-1103 were identified as differential modulators of atrial and ventricular gene expression. More detailed structure-function analysis revealed a distinct subclass of GATA4/NKX2-5 inhibitory compounds with an acetyl lysine-like domain that contributed to ventricular cells (%Myl2-eGFP+). Additionally, BioID analysis indicated broad interaction between GATA4 and BET family of proteins, such as BRD4. This indicated the involvement of epigenetic modulators in the regulation of GATA-dependent transcription. In this line, reporter gene assays with combinatorial treatment of 3i-1000 and the BET bromodomain inhibitor (+)-JQ1 demonstrated the cooperative role of GATA4 and BRD4 in the modulation of chamber-specific cardiac gene expression.ConclusionsCollectively, these results indicate the potential for therapeutic alteration of cell fate decisions and pathological gene regulatory networks by GATA4-targeted compounds modulating chamber-specific transcriptional programs in multipotent cardiac progenitor cells and cardiomyocytes. The compound scaffolds described within this study could be used to develop regenerative strategies for myocardial regeneration.

scholarly journals Modeling transcriptional regulation using gene regulatory networks based on multi-omics data sources

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Neel Patel ◽  
William S. Bush
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Transcriptional Regulation ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Prediction Models ◽  
Long Distance ◽  
Chromatin Looping ◽  
Gene Regulatory ◽  
The Impact

Abstract Background Transcriptional regulation is complex, requiring multiple cis (local) and trans acting mechanisms working in concert to drive gene expression, with disruption of these processes linked to multiple diseases. Previous computational attempts to understand the influence of regulatory mechanisms on gene expression have used prediction models containing input features derived from cis regulatory factors. However, local chromatin looping and trans-acting mechanisms are known to also influence transcriptional regulation, and their inclusion may improve model accuracy and interpretation. In this study, we create a general model of transcription factor influence on gene expression by incorporating both cis and trans gene regulatory features. Results We describe a computational framework to model gene expression for GM12878 and K562 cell lines. This framework weights the impact of transcription factor-based regulatory data using multi-omics gene regulatory networks to account for both cis and trans acting mechanisms, and measures of the local chromatin context. These prediction models perform significantly better compared to models containing cis-regulatory features alone. Models that additionally integrate long distance chromatin interactions (or chromatin looping) between distal transcription factor binding regions and gene promoters also show improved accuracy. As a demonstration of their utility, effect estimates from these models were used to weight cis-regulatory rare variants for sequence kernel association test analyses of gene expression. Conclusions Our models generate refined effect estimates for the influence of individual transcription factors on gene expression, allowing characterization of their roles across the genome. This work also provides a framework for integrating multiple data types into a single model of transcriptional regulation.

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