Universal evolutionary selection for high dimensional silent patterns of information hidden in the redundancy of viral genetic code

Goz, Eli; Zafrir, Zohar; Tuller, Tamir

doi:10.1093/bioinformatics/bty351

Cited by 13 publications

(11 citation statements)

References 55 publications

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“…Compositional similarities between viruses’ and their host’s genomes have been reported among phages and, to some extent, eukaryotic viruses 51–53 . The similarities were also confirmed by Roux et al .…”

Section: Discussionmentioning

confidence: 96%

Host Taxon Predictor - A Tool for Predicting Taxon of the Host of a Newly Discovered Virus

Galan

Bąk

Jakubowska

2019

Sci Rep

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Recent advances in metagenomics provided a valuable alternative to culture-based approaches for better sampling viral diversity. However, some of newly identified viruses lack sequence similarity to any of previously sequenced ones, and cannot be easily assigned to their hosts. Here we present a bioinformatic approach to this problem. We developed classifiers capable of distinguishing eukaryotic viruses from the phages achieving almost 95% prediction accuracy. The classifiers are wrapped in Host Taxon Predictor (HTP) software written in Python which is freely available at https://github.com/wojciech-galan/viruses_classifier . HTP’s performance was later demonstrated on a collection of newly identified viral genomes and genome fragments. In summary, HTP is a culture- and alignment-free approach for distinction between phages and eukaryotic viruses. We have also shown that it is possible to further extend our method to go up the evolutionary tree and predict whether a virus can infect narrower taxa.

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Section: Discussionmentioning

confidence: 96%

Host Taxon Predictor - A Tool for Predicting Taxon of the Host of a Newly Discovered Virus

Galan

Bąk

Jakubowska

2019

Sci Rep

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“…Unsurprisingly, viruses reported almost no ramp sequences. Viral genes are populated with regulatory sequences at the beginning of the coding region and host-repeating substrings throughout the genetic code (26), which potentially limits the applicability of selection for ramp sequences in viruses.…”

Section: Discussionmentioning

confidence: 99%

ExtRamp: a novel algorithm for extracting the ramp sequence based on the tRNA adaptation index or relative codon adaptiveness

Miller

Brase

Ridge

2019

Nucleic Acids Research

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Different species, genes, and locations within genes use different codons to fine-tune gene expression. Within genes, the ramp sequence assists in ribosome spacing and decreases downstream collisions by incorporating slowly-translated codons at the beginning of a gene. Although previously reported as occurring in some species, no previous attempt at extracting the ramp sequence from specific genes has been published. We present ExtRamp, a software package that quickly extracts ramp sequences from any species using the tRNA adaptation index or relative codon adaptiveness. Different filters facilitate the analysis of codon efficiency and enable identification of genes with a ramp sequence. We validate the existence of a ramp sequence in most species by running ExtRamp on 229 742 339 genes across 23 428 species. We evaluate differences in reported ramp sequences when we use different parameters. Using the strictest ramp sequence cut-off, we show that across most taxonomic groups, ramp sequences are approximately 20–40 codons long and occur in about 10% of gene sequences. We also show that in Drosophila melanogaster as gene expression increases, a higher proportion of genes have ramp sequences. We provide a framework for performing this analysis on other species. ExtRamp is freely available at https://github.com/ridgelab/ExtRamp.

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“…In his oral presentation, Tuller demonstrated the computational models that could predict various aspects of the biophysics of gene expression, and further evaluated our understanding of the evolution of cellular organisms and viruses. Further information on this interesting topic can be found in his papers [39][40][41].…”

Section: Virus Systemmentioning

confidence: 99%

Molecules to Microbes

Jheeta

2020

Sci

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How did life begin on Earth? And is there life elsewhere in the Cosmos? Challenging questions, indeed. The series of conferences established by NoR CEL in 2013 addresses these very questions. This paper comprises a summary report of oral presentations that were delivered by NoR CEL’s network members during the 2018 Athens conference and, as such, disseminates the latest research which they have put forward. More in depth material can be found by consulting the contributors referenced papers. Overall, the outcome of this conspectus on the conference demonstrates a case for the existence of “probable chemistry” during the prebiotic epoch.

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Universal evolutionary selection for high dimensional silent patterns of information hidden in the redundancy of viral genetic code

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 13 publications

References 55 publications

Host Taxon Predictor - A Tool for Predicting Taxon of the Host of a Newly Discovered Virus

Host Taxon Predictor - A Tool for Predicting Taxon of the Host of a Newly Discovered Virus

ExtRamp: a novel algorithm for extracting the ramp sequence based on the tRNA adaptation index or relative codon adaptiveness

Molecules to Microbes

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