vhcub: Virus-host codon usage co-adaptation analysis

Anwar, Ali Mostafa; Soudy, Mohamed; Mohamed, Radwa

doi:10.12688/f1000research.21763.1

Cited by 18 publications

(20 citation statements)

References 13 publications

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“…However, from Table 4 it is evident that codon usage in eukaryotic viruses is independent of the codon usage of their hosts (see, for instance: Cristina et al, 2015 ; Castells et al, 2017 ; Tian et al, 2018 ; Anwar et al, 2019 ), although some exceptions do this general rule exist, at least in some unicellular eukaryotes and giant viruses ( Michely et al, 2013 ). This is important given that a codon usage pattern in viruses similar to their hosts could be advantageous for these obligate parasites, since this would allow them to replicate faster and with a lesser extent of errors ( Bahir et al, 2009 ).…”

Section: Discussionmentioning

confidence: 99%

Nucleotide Composition and Codon Usage Across Viruses and Their Respective Hosts

2021

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The genetic material of the three domains of life (Bacteria, Archaea, and Eukaryota) is always double-stranded DNA, and their GC content (molar content of guanine plus cytosine) varies between ≈ 13% and ≈ 75%. Nucleotide composition is the simplest way of characterizing genomes. Despite this simplicity, it has several implications. Indeed, it is the main factor that determines, among other features, dinucleotide frequencies, repeated short DNA sequences, and codon and amino acid usage. Which forces drive this strong variation is still a matter of controversy. For rather obvious reasons, most of the studies concerning this huge variation and its consequences, have been done in free-living organisms. However, no recent comprehensive study of all known viruses has been done (that is, concerning all available sequences). Viruses, by far the most abundant biological entities on Earth, are the causative agents of many diseases. An overview of these entities is important also because their genetic material is not always double-stranded DNA: indeed, certain viruses have as genetic material single-stranded DNA, double-stranded RNA, single-stranded RNA, and/or retro-transcribing. Therefore, one may wonder if what we have learned about the evolution of GC content and its implications in prokaryotes and eukaryotes also applies to viruses. In this contribution, we attempt to describe compositional properties of ∼ 10,000 viral species: base composition (globally and according to Baltimore classification), correlations among non-coding regions and the three codon positions, and the relationship of the nucleotide frequencies and codon usage of viruses with the same feature of their hosts. This allowed us to determine how the base composition of phages strongly correlate with the value of their respective hosts, while eukaryotic viruses do not (with fungi and protists as exceptions). Finally, we discuss some of these results concerning codon usage: reinforcing previous results, we found that phages and hosts exhibit moderate to high correlations, while for eukaryotes and their viruses the correlations are weak or do not exist.

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Section: Discussionmentioning

confidence: 99%

Nucleotide Composition and Codon Usage Across Viruses and Their Respective Hosts

2021

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“…The R package vhcub (Anwar et al, 2019) was used to compute codon usage bias indices including the effective number of codons (ENc), codon adaptation index (CAI), relative codon deoptimization index (RCDI), similarity index (SiD), and relative synonymous codon usage (RSCU). The vhcub package was also used for analyzing dinucleotide over-and under-representation based on base model, codon and syncodon models.…”

Section: Determination Of Codon Usage Indicesmentioning

confidence: 99%

Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19

Nambou¹,

Anakpa

2020

Infection, Genetics and Evolution

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Coronavirus disease 2019 (COVID-19) has caused thousands of deaths worldwide and has become an urgent public health concern. The extraordinary interhuman transmission of this disease has urged scientists to examine the various facets of its pathogenic agent, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Herein, based on publicly available genomic data, we analyzed the codon usage co-adaptation profiles of SARS-CoV-2 and other respiratory coronaviruses (CoVs) with their human host, identified CoV-responsive human genes and their functional roles on the basis of both the relative synonymous codon usage (RSCU)-based correlation of viral genes with human genes and differential gene expression analysis, and predicted potential drugs for COVID-19 treatment based on these genes. The relatively high codon adaptation index (CAI) values (> 0.70) signposted the gene expressivity efficiency of CoVs in human. The ENc-GC3 plot indicated that SARS-CoV-2 genome was under strict selection pressure while SARS-CoV and MERS-CoV were under selection and mutational pressures. The RSCU-based correlation analysis indicated that the viral genomes shared similar codons with a panoply of human genes. The merging of RSCU-based correlation data and SARS-CoV-2-responsive differentially expressed genes allowed the identification of human genes potentially affected by SARS-CoV-2 infection. Functional enrichment analysis indicated that these genes were enriched in biological processes and pathways related to host response to viral infection and immune response. Using the drug-gene interaction database, we screened a list of drugs that could target these genes as potential COVID-19 therapeutics. Our findings not only will contribute in vaccine development but also provide a useful set of drugs that could guide practitioners in strategical monitoring of COVID-19. We recommend practitioners to scrupulously screen this list of predicted drugs in order to authenticate those qualified for treating COVID-19 symptoms.

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“…Spearman's rank correlation and linear regression analyses were performed using R Language (R Core Team, 2016). Different R packages as vhcub, SeqinR, ggplot2 and stats (Anwar et al, 2020;Charif and Lobry, 2007;R Core Team, 2018;Wickham, 2016) were used to calculate various CUB indices and to draw the graphs in this study. As well as a python package named CAI (Lee, 2018) was used to estimate the CAI for the tested viral isolates.…”

Section: Software and Statistical Analysismentioning

confidence: 99%

Insights into The Codon Usage Bias of 13 Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Isolates from Different Geo-locations

Khodary

Anwar

2020

Preprint

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of Coronavirus disease 2019 which is an infectious disease that spread throughout the world and was declared as a pandemic by the World Health Organization (WHO). In the present study, we analyzed genome-wide codon usage patterns in 13 SARS-CoV-2 isolates from different geo-locations (countries) by utilizing different CUB measurements. Nucleotide and di-nucleotide compositions displayed bias toward A/U content in all codon positions and CpU-ended codons preference, respectively. Relative Synonymous Codon Usage (RSCU) analysis revealed 8 common putative preferred codons among all the 13 isolates.Interestingly, all of the latter codons are A/U-ended (U-ended: 7, A-ended: 1). Cluster analysis (based on RSCU values) was performed and showed comparable results to the phylogenetic analysis (based on their whole genome sequences) indicating that the CUB pattern may reflect the evolutionary relationship between the tested isolates. To investigate the force (mutation and/or selection) influencing the pattern of CUB in SARS-CoV-2 coding sequences, we employed the following; (i). Effective number of codons (ENc), (ii). ENc-GC3 plot, (iii). Neutrality plot, and (iv) Codon adaptation index (CAI). According to their results, natural selection and/or other factors (not investigated in this study) may be the dominant force driving SARS-CoV-2 CUB. It is also worth mentioning that, by using the most expressed genes in human lung tissues as a reference set, some viral genes such as Nucleocapsid phosphoprotein, ORF7a protein, and surface glycoprotein had high CAI values which may indicate for selection force acting on their codon usage, as they play important roles in viral assembly and may help viruses avoid the host immune system. The outcome of our study may help in understanding the underlying factors involved in the evolution of SARS-CoV-2 viruses, and the interactions with their host. Also, it may aid in vaccine design strategies.

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vhcub: Virus-host codon usage co-adaptation analysis

Cited by 18 publications

References 13 publications

Nucleotide Composition and Codon Usage Across Viruses and Their Respective Hosts

Nucleotide Composition and Codon Usage Across Viruses and Their Respective Hosts

Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19

Insights into The Codon Usage Bias of 13 Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Isolates from Different Geo-locations

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