Coronavirus phylogeny based on 2D graphical representation of DNA sequence.
Ontology highlight
ABSTRACT:
SUBMITTER: Liao B
PROVIDER: S-EPMC7167161 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In this study, chaos game representation (CGR) is introduced for investigating the pattern of genome sequences. It is an image representation of the genome for the overall visualization of the sequence. The CGR representation is a mapping technique that assigns each sequence base into the respective position in the two-dimension plane to portray the DNA sequence. Importantly, CGR provides one to one mapping to nucleotides as well as sequence. A coordinate of the CGR plane can tell the corresponding base and its location in the original genome. Therefore, the whole nucleotide sequence (until the current nucleotide) can be restored from the one point of the CGR. In this study, CGR coupled with artificial neural network (ANN) is introduced as a new way to represent the genome and to classify intra-coronavirus sequences. A hierarchy clustering study is done to validate the approach and found to be more than 90% accurate while comparing the result with the phylogenetic tree of the corresponding genomes. Interestingly, the method makes the genome sequence significantly shorter (more than 99% compressed) saving the data space while preserving the genome features.
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Project description:Graphical representation of DNA sequence provides a simple way of viewing, sorting and comparing various gene structures. A new two-dimensional graphical representation method using a two- quadrant Cartesian coordinates system has been derived for mathematical denotation of DNA sequence. The two-dimensional graphic representation resolves sequences' degeneracy and is mathematically proven to eliminate circuit formation. Given x-projection and y-projection of any point on the graphical representation, the number of A, G, C and T from the beginning of the sequence to that point could be found. Compared with previous methods, this graphical representation is more in-line with the conventional recognition of linear sequences by molecular biologists, and also provides a metaphor in two dimensions for local and global DNA sequence comparison.
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Project description:BackgroundThe number of available genome sequences is increasing, and easy-to-use software that enables efficient comparative analysis is needed.ResultsWe developed GenomeMatcher, a stand-alone software package for Mac OS X. GenomeMatcher executes BLAST and MUMmer, and the detected similarities are displayed in two-dimensional and parallel views with similarity values indicated by color. Selection and re-computation of any subregions is easily performed and allows flexible and in-depth analysis. Furthermore, symbols for annotation data are displayed along the views, and the user can relate the genomic differences with annotation data. While bl2seq allows sub-Giga base comparison, three alignment programs, bl2seq, MAFFT and ClustalW, together with a dotmatch program allow comparative analysis of single-nucleotide level resolution. GenomeMatcher images can be saved as PDF and TIFF files for presentation. As examples of graphical ability of GenomeMatcher to show similarity in colors, we show two cases in Burkholderia and Vivrio strains that the nucleotide sequence of the second largest chromosome changes more rapidly than the largest chromosome.ConclusionGenomeMatcher is efficient and easy-to-use stand-alone software for in-depth comparative analysis of two sequences. GenomeMatcher is useful for detecting similarities in DNA sequences ranging in size from a few to sub-Giga bases.
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