Developing an ultra-efficient microsatellite discoverer to find structural differences between SARS-CoV-1 and Covid-19

Naghibzadeh, Mahmoud; Savari, Hossein; Savadi, Abdorreza; Saadati, Nayyereh; Mehrazin, Elahe

doi:10.1016/j.imu.2020.100356

Cited by 10 publications

(8 citation statements)

References 25 publications

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“…Tandem repeats, continuously repeated motifs, with the core subsequence less than 7 are called microsatellite which can help in structural analysis. All of SARS-CoV-2 microsatellites are extracted with FMSD [ 49 ] (fast microsatellite discovery method) and reported in Table 3 .…”

Section: Resultsmentioning

confidence: 99%

SARS-CoV-2-human protein-protein interaction network

Khorsand

Savadi

Naghibzadeh

2020

Informatics in Medicine Unlocked

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the novel coronavirus which caused the coronavirus disease 2019 pandemic and infected more than 12 million victims and resulted in over 560,000 deaths in 213 countries around the world. Having no symptoms in the first week of infection increases the rate of spreading the virus. The increasing rate of the number of infected individuals and its high mortality necessitates an immediate development of proper diagnostic methods and effective treatments. SARS-CoV-2, similar to other viruses, needs to interact with the host proteins to reach the host cells and replicate its genome. Consequently, virus-host protein-protein interaction (PPI) identification could be useful in predicting the behavior of the virus and the design of antiviral drugs. Identification of virus-host PPIs using experimental approaches are very time consuming and expensive. Computational approaches could be acceptable alternatives for many preliminary investigations. In this study, we developed a new method to predict SARS-CoV-2-human PPIs. Our model is a three-layer network in which the first layer contains the most similar Alphainfluenzavirus proteins to SARS-CoV-2 proteins. The second layer contains protein-protein interactions between Alphainfluenzavirus proteins and human proteins. The last layer reveals protein-protein interactions between SARS-CoV-2 proteins and human proteins by using the clustering coefficient network property on the first two layers. To further analyze the results of our prediction network, we investigated human proteins targeted by SARS-CoV-2 proteins and reported the most central human proteins in human PPI network. Moreover, differentially expressed genes of previous researches were investigated and PPIs of SARS-CoV-2-human network, the human proteins of which were related to upregulated genes, were reported.

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Section: Resultsmentioning

confidence: 99%

SARS-CoV-2-human protein-protein interaction network

Khorsand

Savadi

Naghibzadeh

2020

Informatics in Medicine Unlocked

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“…Microsatellite analysis tracks the repetitive sequences in the genome that have a significant impact on diseases and evolution. For the comparison of SARS‐CoV, MERS‐CoV, BAT‐SARS, and SARS‐CoV‐2, the microsatellite analysis was performed using imperfect microsatellite extractor (IMEX) 24 and fast microsatellite discovery (FMSD) 15 online tools. From IMEX, 20 genome sequences of SARS‐CoV ( n = 5), MERS‐CoV ( n = 5), BAT‐CoV ( n = 5), SARS‐CoV‐2 ( n = 5), and the reference of Wuhan (accession‐id: NC_045512) were selected from the data set (Table ) for microsatellite analysis.…”

Section: Methodsmentioning

confidence: 99%

Comprehensive comparative genomic and microsatellite analysis of SARS, MERS, BAT‐SARS, and COVID‐19 coronaviruses

Rehman

Ramzan

Basharat

et al. 2021

Journal of Medical Virology

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The coronavirus disease 2019 (COVID-19) pandemic has spread around the globe very rapidly. Previously, the evolution pattern and similarity among the COVID-19 causative organism severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and causative organisms of other similar infections have been determined using a single type of genetic marker in different studies. Herein, the SARS-CoV-2 and related β coronaviruses Middle East respiratory syndrome coronavirus (MERS-CoV), SARS-CoV, bat coronavirus (BAT-CoV) were comprehensively analyzed using a

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“…Recently we developed an ultra-efficient microsatellite detector [2] ; The Fast Microsatellite Detector (FMSD) makes use of an indexing method called K-Mer Hash Index (KMHI) [3] . To minimize the space requirement of this table a novel technique was imposed to the base KMHI.…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Statistics and Patterns of Occurrence of Simple Tandem Repeats in SARS-CoV-1 and SARS-CoV-2 Genomic Data

et al. 2021

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The data presented in this article is related to the research article entitled “Developing an ultra-efficient microsatellite discoverer to find structural differences between SARS-CoV-1 and Covid-19” [Naghibzadeh et al. 2020]. Simple tandem repeats (microsatellites, STR) are extracted and investigated across all viral families from four main viral realms. An ultra-efficient and reliable software, which is recently developed by the authors and published in the above-mentioned article, is used for extracting STRs. The analysis is done for k-mer tandem repeats where k varies from one to seven. In particular the frequency of trimer STRs is shown to be low in RNA viruses compared with DNA viruses. Special attention is paid to seven zoonotic viruses from family Coronaviridae which caused several severe human crises during last two decades including MERS, SARS 2003 and Covid-19.

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Developing an ultra-efficient microsatellite discoverer to find structural differences between SARS-CoV-1 and Covid-19

Cited by 10 publications

References 25 publications

SARS-CoV-2-human protein-protein interaction network

SARS-CoV-2-human protein-protein interaction network

Comprehensive comparative genomic and microsatellite analysis of SARS, MERS, BAT‐SARS, and COVID‐19 coronaviruses

Statistics and Patterns of Occurrence of Simple Tandem Repeats in SARS-CoV-1 and SARS-CoV-2 Genomic Data

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