scholarly journals Small RNA-Seq reveals novel miRNAs shaping the transcriptomic identity of rat brain structures

2018 ◽  
Vol 1 (5) ◽  
pp. e201800018 ◽  
Author(s):  
Anaïs Soula ◽  
Mélissa Valere ◽  
María-José López-González ◽  
Vicky Ury-Thiery ◽  
Alexis Groppi ◽  
...  
Keyword(s):  
Small Rna ◽  
Critical Role ◽  
Differential Expression Analysis ◽  
Brain Structures ◽  
Strong Impact ◽  
The Novel ◽  
Rna Seq ◽  
Functional Identities ◽  
The Central Nervous System ◽  
Rat Cns

In the central nervous system (CNS), miRNAs are involved in key functions, such as neurogenesis and synaptic plasticity. Moreover, they are essential to define specific transcriptomes in tissues and cells. However, few studies were performed to determine the miRNome of the different structures of the rat CNS, although a major model in neuroscience. Here, we determined by small RNA-Seq, the miRNome of the olfactory bulb, the hippocampus, the cortex, the striatum, and the spinal cord and showed the expression of 365 known miRNAs and 90 novel miRNAs. Differential expression analysis showed that several miRNAs were specifically enriched/depleted in these CNS structures. Transcriptome analysis by mRNA-Seq and correlation based on miRNA target predictions suggest that the specifically enriched/depleted miRNAs have a strong impact on the transcriptomic identity of the CNS structures. Altogether, these results suggest the critical role played by these enriched/depleted miRNAs, in particular the novel miRNAs, in the functional identities of CNS structures.

scholarly journals CTCF, a novel fusion partner of ETO2 in a post-transplant relapsed acute myeloid leukemia patient

2020 ◽  
Author(s):  
Jiao Li ◽  
Zhen Shen ◽  
zheng wang ◽  
Yi Xu ◽  
Zhao Zeng ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Critical Role ◽  
Fusion Partner ◽  
The Novel ◽  
Rna Seq ◽  
Rt Pcr ◽  
Chimeric Genes ◽  
Post Transplant ◽  
Acute Myeloid

Abstract Background ETO2 is a nuclear co-repressor, which plays a critical role in the regulation of the cell cycle, self-renewal capacity, and differentiation of hematopoietic progenitor cells. Methods We identified novel fusion transcripts involving ETO2 and CTCF by RNA-seq in a post-transplant relapsed case. Results The CTCF-ETO2 and ETO2-CTCF chimeric genes were validated by RT-PCR and Sanger sequencing. In addition, both transcripts apparently promoted cell proliferation which is beneficial to tumorigenesis. Conclusion The novel fusions may have prognostic value and pathogenic mechanisms in acute myeloid leukemia.

scholarly journals WIND (Workflow for pIRNAs aNd beyonD): a strategy for in-depth analysis of small RNA-seq data

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1
Author(s):  
Konstantinos Geles ◽  
Domenico Palumbo ◽  
Assunta Sellitto ◽  
Giorgio Giurato ◽  
Eleonora Cianflone ◽  
...  
Keyword(s):  
Small Rna ◽  
Differential Expression Analysis ◽  
Small Rna Sequencing ◽  
Rna Seq ◽  
Sequencing Data ◽  
Transcript Quantification ◽  
Annotation Track ◽  
Depth Analysis ◽  
Exploratory Data ◽  
Downstream Analysis

Current bioinformatics workflows for PIWI-interacting RNA (piRNA) analysis focus primarily on germline-derived piRNAs and piRNA-clusters. Frequently, they suffer from outdated piRNA databases, questionable quantification methods, and lack of reproducibility. Often, pipelines specific to miRNA analysis are used for the piRNA research in silico. Furthermore, the absence of a well-established database for piRNA annotation, as for miRNA, leads to uniformity issues between studies and generates confusion for data analysts and biologists. For these reasons, we have developed WIND (Workflow for pIRNAs aNd beyonD), a bioinformatics workflow that addresses the crucial issue of piRNA annotation, thereby allowing a reliable analysis of small RNA sequencing data for the identification of piRNAs and other small non-coding RNAs (sncRNAs) that in the past have been incorrectly classified as piRNAs. WIND allows the creation of a comprehensive annotation track of sncRNAs combining information available in RNAcentral, with piRNA sequences from piRNABank, the first database dedicated to piRNA annotation. WIND was built with Docker containers for reproducibility and integrates widely used bioinformatics tools for sequence alignment and quantification. In addition, it includes Bioconductor packages for exploratory data and differential expression analysis. Moreover, WIND implements a "dual" approach for the evaluation of sncRNAs expression level quantifying the aligned reads to the annotated genome and carrying out an alignment-free transcript quantification using reads mapped to the transcriptome. Therefore, a broader range of piRNAs can be annotated, improving their quantification and easing the subsequent downstream analysis. WIND performance has been tested with several small RNA-seq datasets, demonstrating how our approach can be a useful and comprehensive resource to analyse piRNAs and other classes of sncRNAs.

scholarly journals WIND (Workflow for pIRNAs aNd beyonD): a strategy for in-depth analysis of small RNA-seq data

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1
Author(s):  
Konstantinos Geles ◽  
Domenico Palumbo ◽  
Assunta Sellitto ◽  
Giorgio Giurato ◽  
Eleonora Cianflone ◽  
...  
Keyword(s):  
Small Rna ◽  
Differential Expression Analysis ◽  
Small Rna Sequencing ◽  
Rna Seq ◽  
Sequencing Data ◽  
Transcript Quantification ◽  
Annotation Track ◽  
Depth Analysis ◽  
Exploratory Data ◽  
Downstream Analysis

Current bioinformatics workflows for PIWI-interacting RNA (piRNA) analysis focus primarily on germline-derived piRNAs and piRNA-clusters. Frequently, they suffer from outdated piRNA databases, questionable quantification methods, and lack of reproducibility. Often, pipelines specific to miRNA analysis are used for the piRNA research in silico. Furthermore, the absence of a well-established database for piRNA annotation, as for miRNA, leads to uniformity issues between studies and generates confusion for data analysts and biologists. For these reasons, we have developed WIND (Workflow for pIRNAs aNd beyonD), a bioinformatics workflow that addresses the crucial issue of piRNA annotation, thereby allowing a reliable analysis of small RNA sequencing data for the identification of piRNAs and other small non-coding RNAs (sncRNAs) that in the past have been incorrectly classified as piRNAs. WIND allows the creation of a comprehensive annotation track of sncRNAs combining information available in RNAcentral, with piRNA sequences from piRNABank, the first database dedicated to piRNA annotation. WIND was built with Docker containers for reproducibility and integrates widely used bioinformatics tools for sequence alignment and quantification. In addition, it includes Bioconductor packages for exploratory data and differential expression analysis. Moreover, WIND implements a "dual" approach for the evaluation of sncRNAs expression level quantifying the aligned reads to the annotated genome and carrying out an alignment-free transcript quantification using reads mapped to the transcriptome. Therefore, a broader range of piRNAs can be annotated, improving their quantification and easing the subsequent downstream analysis. WIND performance has been tested with several small RNA-seq datasets, demonstrating how our approach can be a useful and comprehensive resource to analyse piRNAs and other classes of sncRNAs.

RNA-Seq profiling of leukocytes reveals a sex-dependent global circular RNA upregulation in multiple sclerosis and 6 candidate biomarkers

2020 ◽  
Vol 29 (20) ◽  
pp. 3361-3372
Author(s):  
Leire Iparraguirre ◽  
Ainhoa Alberro ◽  
Lucía Sepúlveda ◽  
Iñaki Osorio-Querejeta ◽  
Laura Moles ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Differential Expression Analysis ◽  
Area Under The Curve ◽  
Circular Rna ◽  
Circular Rnas ◽  
Rna Seq ◽  
Paired Samples ◽  
The Central Nervous System ◽  
Chronic Autoimmune Disease ◽  
Diagnosis Classification

Abstract Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system, with higher prevalence in women, that leads to neurological disability. The disease course and clinical phenotype are highly variable, and therefore, biomarkers for the diagnosis, classification, monitoring of the disease and treatment assessment are needed. Studies have shown a dysregulation in the coding and non-coding RNAs and proposed some as biomarkers. However, still none of them have reached the clinical practice. Recently, circular RNAs (circRNAs) have emerged as new players in the transcriptome that hold a great potential as biomarkers in several diseases. Leukocytes from 30 MS patients and 20 healthy controls (HCs) were RNA-sequenced to study the linear and circular transcriptome. Differential expression analysis was performed by DESeq, and circRNA candidates were studied in a second cohort (70 MS and 46 HC) by RT-qPCR and in paired samples drawn during the relapse and remission phases (20 patients). Among the differentially expressed circRNAs, 96.1% are upregulated in patients compared with controls, but similar circRNA profiles are found between MS types. The same upregulation trend was observed in females but not in males or in the linear transcriptome. The upregulation of 6 circRNAs was validated, and a change in their expression was found between relapse and remission. The 6 circRNAs showed a good performance to discriminate patients from HC with a combined area under the curve of 0.852. There is global, specific and sex-dependent increase of circRNA expression in MS, and 6 circRNAs are proposed as potential biomarkers.

scholarly journals WIND (Workflow for pIRNAs aNd beyonD): a strategy for in-depth analysis of small RNA-seq data

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1
Author(s):  
Konstantinos Geles ◽  
Domenico Palumbo ◽  
Assunta Sellitto ◽  
Giorgio Giurato ◽  
Eleonora Cianflone ◽  
...  
Keyword(s):  
Small Rna ◽  
Differential Expression Analysis ◽  
Small Rna Sequencing ◽  
Rna Seq ◽  
Sequencing Data ◽  
Transcript Quantification ◽  
Annotation Track ◽  
Depth Analysis ◽  
Exploratory Data ◽  
Downstream Analysis

Current bioinformatics workflows for PIWI-interacting RNA (piRNA) analysis focus primarily on germline-derived piRNAs and piRNA-clusters. Frequently, they suffer from outdated piRNA databases, questionable quantification methods, and lack of reproducibility. Often, pipelines specific to miRNA analysis are used for the piRNA research in silico. Furthermore, the absence of a well-established database for piRNA annotation, as for miRNA, leads to uniformity issues between studies and generates confusion for data analysts and biologists. For these reasons, we have developed WIND (Workflow for pIRNAs aNd beyonD), a bioinformatics workflow that addresses the crucial issue of piRNA annotation, thereby allowing a reliable analysis of small RNA sequencing data for the identification of piRNAs and other small non-coding RNAs (sncRNAs) that in the past have been incorrectly classified as piRNAs. WIND allows the creation of a comprehensive annotation track of sncRNAs combining information available in RNAcentral, with piRNA sequences from piRNABank, the first database dedicated to piRNA annotation. WIND was built with Docker containers for reproducibility and integrates widely used bioinformatics tools for sequence alignment and quantification. In addition, it includes Bioconductor packages for exploratory data and differential expression analysis. Moreover, WIND implements a "dual" approach for the evaluation of sncRNAs expression level quantifying the aligned reads to the annotated genome and carrying out an alignment-free transcript quantification using reads mapped to the transcriptome. Therefore, a broader range of piRNAs can be annotated, improving their quantification and easing the subsequent downstream analysis. WIND performance has been tested with several small RNA-seq datasets, demonstrating how our approach can be a useful and comprehensive resource to analyse piRNAs and other classes of sncRNAs.

scholarly journals omiRas: a Web server for differential expression analysis of miRNAs derived from small RNA-Seq data

2013 ◽  
Vol 29 (20) ◽  
pp. 2651-2652 ◽  
Author(s):  
Sören Müller ◽  
Lukas Rycak ◽  
Peter Winter ◽  
Günter Kahl ◽  
Ina Koch ◽  
...  
Keyword(s):  
Differential Expression ◽  
Expression Analysis ◽  
Small Rna ◽  
Differential Expression Analysis ◽  
Web Server ◽  
Rna Seq

Heterogeneity and Proliferative and Differential Regulators of NG2-glia in Physiological and Pathological States

2020 ◽  
Vol 27 (37) ◽  
pp. 6384-6406 ◽  
Author(s):  
Zuo Zhang ◽  
Hongli Zhou ◽  
Jiyin Zhou
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Physiological State ◽  
Critical Role ◽  
Adult Brain ◽  
Pathological State ◽  
Peripheral Neurons ◽  
Neuronal Synapses ◽  
The Central Nervous System ◽  
Rapid Modulation

NG2-glia, also called Oligodendrocyte Precursor Cells (OPCs), account for approximately 5%-10% of the cells in the developing and adult brain and constitute the fifth major cell population in the central nervous system. NG2-glia express receptors and ion channels involved in rapid modulation of neuronal activities and signaling with neuronal synapses, which have functional significance in both physiological and pathological states. NG2-glia participate in quick signaling with peripheral neurons via direct synaptic touches in the developing and mature central nervous system. These distinctive glia perform the unique function of proliferating and differentiating into oligodendrocytes in the early developing brain, which is critical for axon myelin formation. In response to injury, NG2-glia can proliferate, migrate to the lesions, and differentiate into oligodendrocytes to form new myelin sheaths, which wrap around damaged axons and result in functional recovery. The capacity of NG2-glia to regulate their behavior and dynamics in response to neuronal activity and disease indicate their critical role in myelin preservation and remodeling in the physiological state and in repair in the pathological state. In this review, we provide a detailed summary of the characteristics of NG2-glia, including their heterogeneity, the regulators of their proliferation, and the modulators of their differentiation into oligodendrocytes.

JOINT ESTIMATION OF THE TRANSMISSIBILITY AND SEVERITY OF EBOLA VIRUS DISEASE IN REAL TIME

2017 ◽  
Vol 25 (04) ◽  
pp. 587-603 ◽  
Author(s):  
YUSUKE ASAI ◽  
HIROSHI NISHIURA
Keyword(s):  
Real Time ◽  
Ebola Virus ◽  
Virus Disease ◽  
Critical Role ◽  
Estimation Method ◽  
Case Fatality ◽  
Ascertainment Bias ◽  
Joint Estimation ◽  
Ebola Virus Disease ◽  
Strong Impact

The effective reproduction number [Formula: see text], the average number of secondary cases that are generated by a single primary case at calendar time [Formula: see text], plays a critical role in interpreting the temporal transmission dynamics of an infectious disease epidemic, while the case fatality risk (CFR) is an indispensable measure of the severity of disease. In many instances, [Formula: see text] is estimated using the reported number of cases (i.e., the incidence data), but such report often does not arrive on time, and moreover, the rate of diagnosis could change as a function of time, especially if we handle diseases that involve substantial number of asymptomatic and mild infections and large outbreaks that go beyond the local capacity of reporting. In addition, CFR is well known to be prone to ascertainment bias, often erroneously overestimated. In this paper, we propose a joint estimation method of [Formula: see text] and CFR of Ebola virus disease (EVD), analyzing the early epidemic data of EVD from March to October 2014 and addressing the ascertainment bias in real time. To assess the reliability of the proposed method, coverage probabilities were computed. When ascertainment effort plays a role in interpreting the epidemiological dynamics, it is useful to analyze not only reported (confirmed or suspected) cases, but also the temporal distribution of deceased individuals to avoid any strong impact of time dependent changes in diagnosis and reporting.

scholarly journals Novel late-stage radiosynthesis of 5-[18F]-trifluoromethyl-1,2,4-oxadiazole (TFMO) containing molecules for PET imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nashaat Turkman ◽  
Daxing Liu ◽  
Isabella Pirola
Keyword(s):  
Late Stage ◽  
Histone Deacetylases ◽  
Radiochemical Purity ◽  
Radiochemical Yield ◽  
Single Step ◽  
The Novel ◽  
Molar Activity ◽  
The Central Nervous System ◽  
Class Iia Hdacs ◽  
18F Fluoride

AbstractSmall molecules that contain the (TFMO) moiety were reported to specifically inhibit the class-IIa histone deacetylases (HDACs), an important target in cancer and the disorders of the central nervous system (CNS). However, radiolabeling methods to incorporate the [18F]fluoride into the TFMO moiety are lacking. Herein, we report a novel late-stage incorporation of [18F]fluoride into the TFMO moiety in a single radiochemical step. In this approach the bromodifluoromethyl-1,2,4-oxadiazole was converted into [18F]TFMO via no-carrier-added bromine-[18F]fluoride exchange in a single step, thus producing the PET tracers with acceptable radiochemical yield (3–5%), high radiochemical purity (> 98%) and moderate molar activity of 0.33–0.49 GBq/umol (8.9–13.4 mCi/umol). We validated the utility of the novel radiochemical design by the radiosynthesis of [18F]TMP195, which is a known TFMO containing potent inhibitor of class-IIa HDACs.

scholarly journals Best practices on the differential expression analysis of multi-species RNA-seq

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Matthew Chung ◽  
Vincent M. Bruno ◽  
David A. Rasko ◽  
Christina A. Cuomo ◽  
José F. Muñoz ◽  
...  
Keyword(s):  
Best Practices ◽  
Differential Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Single Species ◽  
Rna Seq ◽  
Species Analysis ◽  
Differential Gene ◽  
Multiple Species ◽  
Downstream Analysis

AbstractAdvances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression.

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