In silico analysis of RNA-seq requires a more complete description of methodology

Abstract Background Numerous studies have been conducted on different aspects of the COVID-19 (coronavirus disease 2019) pandemic, which is caused by SARS-CoV-2, since its emergence in late 2019. Mutual relations among SARS-CoV-2 and neuro-pathophysiological phenomena are continuously being demonstrated, and several underlying diseases, such as those in the elderly, are positively correlated with susceptibility to SARS-CoV-2 infection. The expression of angiotensin converting enzyme 2 (ACE2), which is required for SARS-CoV-2 infection, was recently demonstrated to be increased in Alzheimer’s disease (AD) patients. Methods Recent preclinical studies have shown that Neuropilin-1 (NRP1), which is a transmembrane protein with roles in neuronal development, axonal outgrowth, and angiogenesis, also plays a role in the infectivity of SARS-CoV-2. Thus, we hypothesized that NRP1 may be upregulated in AD patients and that a correlation between AD and SARS-CoV-2 NRP1-mediated infectivity may exist. We used an AD mouse model that mimics AD and performed high throughput total RNA-seq with brain tissue and whole blood. For quantification of NPR1 in AD, brain tissues and blood were subjected to western blotting and RT-qPCR analysis. In silico analysis for NRP1 expression in AD patients has been performed on the human hippocampus data sets (GSE4226, GSE1297). Results Many cases of severe symptom of COVID-19 are concentrated in elderly group who have complications such as diabetes, degenerative disease, and brain disorders. Total RNA-seq analysis showed that Nrp1 gene was commonly overexpressed in AD model. Similar to ACE2, NRP1 protein also strongly expressed in the AD brain tissues. Interestingly, in silico analysis revealed that the level of expression for NRP1 was distinct at age and AD progression. Conclusions Given that the NRP1 is highly expressed in AD, it will be important to understand and predict that NRP1 may a risk factor for SARS-CoV-2 infection in AD patients. This will support to development of potential therapeutic drug to reduce SARS-CoV-2 transmission.

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Identifying new COVID-19 receptor Neuropilin-1 in severe Alzheimer’s diseases patients group brain using genome-wide association study approach

10.21203/rs.3.rs-151089/v1 ◽

2021 ◽

Author(s):

Key-Hwan Lim ◽

Sumin Yang ◽

Sung-Hyun Kim ◽

Jae-Yeol Joo

Keyword(s):

In Silico ◽

Genome Wide Association Study ◽

Transmembrane Protein ◽

In Silico Analysis ◽

Therapeutic Drug ◽

Rna Seq ◽

Total Rna ◽

Neuropilin 1 ◽

Silico Analysis ◽

Brain Tissues

Abstract Background Numerous studies have been conducted on different aspects of the COVID-19 (coronavirus disease 2019) pandemic, which is caused by SARS-CoV-2, since its emergence in late 2019. Mutual relations among SARS-CoV-2 and neuro-pathophysiological phenomena are continuously being demonstrated, and several underlying diseases, such as those in the elderly, are positively correlated with susceptibility to SARS-CoV-2 infection. The expression of angiotensin converting enzyme 2 (ACE2), which is required for SARS-CoV-2 infection, was recently demonstrated to be increased in Alzheimer’s disease (AD) patients.Methods Recent preclinical studies have shown that Neuropilin-1 (NRP1), which is a transmembrane protein with roles in neuronal development, axonal outgrowth, and angiogenesis, also plays a role in the infectivity of SARS-CoV-2. Thus, we hypothesized that NRP1 may be upregulated in AD patients and that a correlation between AD and SARS-CoV-2 NRP1-mediated infectivity may exist. We used an AD mouse model that mimics AD and performed high throughput total RNA-seq with brain tissue and whole blood. For quantification of NPR1 in AD, brain tissues and blood were subjected to western blotting and RT-qPCR analysis. In silico analysis for NRP1 expression in AD patients has been performed on the human hippocampus data sets (GSE4226, GSE1297).Results Many cases of severe symptom of COVID-19 are concentrated in elderly group who have complications such as diabetes, degenerative disease, and brain disorders. Total RNA-seq analysis showed that Nrp1 gene was commonly overexpressed in AD model. Similar to ACE2, NRP1 protein also strongly expressed in the AD brain tissues. Interestingly, in silico analysis revealed that the level of expression for NRP1 was distinct at age and AD progression.Conclusions Given that the NRP1 is highly expressed in AD, it will be important to understand and predict that NRP1 may a risk factor for SARS-CoV-2 infection in AD patients. This will support to development of potential therapeutic drug to reduce SARS-CoV-2 transmission.

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Evaluation role of miR-124 in neurodegenerative diseases: literature review and in silico analysis

10.1101/2021.10.17.464692 ◽

2021 ◽

Author(s):

Javad Amini ◽

Bahram Bibak ◽

Amir R Afshar ◽

Amirhossein Sahebkar

Keyword(s):

Alzheimer’S Disease ◽

Parkinson’S Disease ◽

Literature Review ◽

Neurodegenerative Diseases ◽

Signaling Pathway ◽

In Silico ◽

In Silico Analysis ◽

Rna Seq ◽

Silico Analysis

Neurodegenerative diseases (ND) are characterized by loss of function and structure of neurons. NDs like Alzheimer's disease (AD) and Parkinson's disease (PD) have high burden on the society and patients. Currently microRNAs (miRNAs) approach is growing. miRNAs express in different tissues, especially in the central neuron systems (CNS). miRNAs have a dynamic role in the CNS among this miRNAs, miR-124 significantly express in the CNS. Studies on miR-124 have shown that miR-124 improves ND. In this study, we evaluated the role of miR-124 in the ND by literature review and in silico analysis. We used Pubmed database to find miR-124 function in the Alzheimer's disease, Parkinson's disease, Multiple sclerosis, Huntington's disease and amyotrophic lateral sclerosis. To better understand the role of miR-124 in the neurons, RNA-seq data form miR-124-deleted neuronal cells extracted from GEO database and analyzed in Galaxy platform. According literature review miR-124 attenuates inflammation and apoptosis in the ND by target NF-kb signaling pathway and regulation of BAX/BCL-2. miR-124 targets BACE1 and decreases level of Aβ. RNA-seq data showed miR-124 downregulation, an increase in chemokine gene like CCL1 and cytokine-cytokine receptor-interaction, as well as MAPK-signaling pathway. Our study shows that miR-124 can be promising therapeutic approaches to ND.

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SMARCB1 expression is a novel diagnostic and prognostic biomarker for osteosarcoma

Bioscience Reports ◽

10.1042/bsr20212446 ◽

2022 ◽

Author(s):

Tao Guo ◽

Ran Wei ◽

Dylan C Dean ◽

Francis Hornicek ◽

Zhenfeng Duan

Keyword(s):

Clinical Significance ◽

Tissue Microarray ◽

In Silico ◽

Prognostic Biomarker ◽

In Silico Analysis ◽

Progression Free Survival ◽

Rna Seq ◽

Free Survival ◽

Chemotherapeutic Response ◽

Silico Analysis

Background: Although weak SMARCB1 expression is a known diagnostic and prognostic biomarker in several malignancies, its expression and clinical significance in osteosarcoma remain unknown. The aim of this study was to investigate SMARCB1 expression in osteosarcoma and its clinical significance with respect to chemosensitivity and prognosis. Methods: We obtained 114 specimens from 70 osteosarcoma patients to construct a tissue microarray (TMA) and assess SMARCB1 protein expression via immunohistochemistry. The mRNA expression of SMARCB1 was in silico analyzed using open-access RNA sequencing (RNA-Seq) and clinicopathological data provided by the Therapeutically Applicable Research to Generate Effective Treatments on Osteosarcoma (TARGET-OS) project. The correlations between SMARCB1 expression and clinical features were statistically analyzed. Results: Weak SMARCB1 expression occurred in 70% of the osteosarcoma patient specimens in the tissue microarray, and significantly correlated with poor neoadjuvant response as well as shorter overall and progression-free survival. In addition, mRNA in silico analysis confirmed SMARCB1 expression correlates with chemotherapeutic response and prognosis in osteosarcoma patients. Conclusion: To our knowledge, this study is the first to analyze SMARCB1 expression in osteosarcoma. SMARCB1 may serve as a novel diagnostic and prognostic biomarker in osteosarcoma.

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A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

Seminars in Oncology ◽

10.1053/j.seminoncol.2020.02.012 ◽

2020 ◽

Vol 47 (6) ◽

pp. 398-408

Author(s):

Sonam Tulsyan ◽

Showket Hussain ◽

Balraj Mittal ◽

Sundeep Singh Saluja ◽

Pranay Tanwar ◽

...

Keyword(s):

Systematic Review ◽

Gallbladder Carcinoma ◽

In Silico ◽

In Silico Analysis ◽

Transcriptomic Profile ◽

Silico Analysis

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In Silico Analysis of Single Nucleotide Polymorphism in Human Prothrombin Gene

10.1055/s-0039-1680245 ◽

2019 ◽

Author(s):

I. Farah ◽

A. El-Mubark ◽

M. Osman ◽

A. Soliman ◽

F. Ali ◽

...

Keyword(s):

Single Nucleotide Polymorphism ◽

In Silico ◽

In Silico Analysis ◽

Nucleotide Polymorphism ◽

Single Nucleotide ◽

Prothrombin Gene ◽

Silico Analysis

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Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

Current Medicinal Chemistry ◽

10.2174/0929867327666200727114410 ◽

2020 ◽

Vol 27 (38) ◽

pp. 6523-6535 ◽

Cited By ~ 3

Author(s):

Antreas Afantitis ◽

Andreas Tsoumanis ◽

Georgia Melagraki

Keyword(s):

Data Analysis ◽

Virtual Screening ◽

In Silico ◽

Model Development ◽

In Silico Analysis ◽

Material Design ◽

Efficient Solutions ◽

Biological Data ◽

Cost Efficient ◽

Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

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