Optimized Metavirome Analysis of Marine DNA Virus Communities for Taxonomic Profiling SCIE SCOPUS KCI

DC Field Value Language
dc.contributor.author Kim, Kang Eun -
dc.contributor.author Jung, Seung Won -
dc.contributor.author Park, Joon Sang -
dc.contributor.author Kim, Hyun Jung -
dc.contributor.author Lee, Chol Young -
dc.contributor.author Ha, Sun-Yong -
dc.contributor.author Lee, Taek Kyun -
dc.date.accessioned 2022-05-17T00:30:04Z -
dc.date.available 2022-05-17T00:30:04Z -
dc.date.created 2022-05-17 -
dc.date.issued 2022-06 -
dc.identifier.issn 1738-5261 -
dc.identifier.uri https://sciwatch.kiost.ac.kr/handle/2020.kiost/42480 -
dc.description.abstract Recent advances in metavirome technology have provided new insights into viral diversity and function. The bioinformatic process of metavirome study is generally divided into two (or three) steps: assembly and taxonomic profiling including nucleotide alignment. Moreover, k-mer size and contig length are known to considerably affect the results of the assembly and consequently those of taxonomic profiling; however, the optimal k-mer size and contig length have not been established. In the present study, we analyzed marine virus DNA datasets with three different k-mer sizes using different assemblers: 1 k-mer (20) in the CLC Genomics Workbench, and 4 (21, 33, 55, and 77) and 5 (21, 33, 55, 77, and 99) k-mers in metaSPAdes. The use of large k-mers had the advantage of resolving more repeat regions, with higher N50 values and average contig lengths. The contig length helps reduce the error of continuous sequences and determine the number of viral operational taxonomic units. Our analysis suggested that 300 bp may be an appropriate minimum contig length, depending on the characteristics of viral samples. Based on the assembly result using metaSPAdes, we analyzed the DNA virus community using three taxonomic profiling tools: MG-RAST online server, the taxonomic profiling tools function in the CLC microbial module, and customized taxonomic assignment coding (CUTAXAC) using RStudio based on the BLASTn analysis. CUTAXAC showed the most diverse viral composition at the family and species levels along with the highest Shannon diversity index and fastest analysis time. -
dc.description.uri 1 -
dc.language English -
dc.publisher 한국해양과학기술원 -
dc.title Optimized Metavirome Analysis of Marine DNA Virus Communities for Taxonomic Profiling -
dc.title.alternative Optimized Metavirome Analysis of Marine DNA Virus Communities for Taxonomic Profiling -
dc.type Article -
dc.citation.endPage 268 -
dc.citation.startPage 259 -
dc.citation.title OCEAN SCIENCE JOURNAL -
dc.citation.volume 57 -
dc.citation.number 2 -
dc.contributor.alternativeName 김강은 -
dc.contributor.alternativeName 정승원 -
dc.contributor.alternativeName 박준상 -
dc.contributor.alternativeName 김현정 -
dc.contributor.alternativeName 이철용 -
dc.contributor.alternativeName 이택견 -
dc.identifier.bibliographicCitation OCEAN SCIENCE JOURNAL, v.57, no.2, pp.259 - 268 -
dc.identifier.doi 10.1007/s12601-022-00064-0 -
dc.identifier.scopusid 2-s2.0-85129327520 -
dc.identifier.wosid 000789765900001 -
dc.type.docType Article; Early Access -
dc.identifier.kciid ART002861665 -
dc.description.journalClass 1 -
dc.description.isOpenAccess N -
dc.subject.keywordPlus METAGENOMIC ANALYSIS -
dc.subject.keywordPlus VIROME -
dc.subject.keywordPlus DIVERSITY -
dc.subject.keywordPlus ALGORITHMS -
dc.subject.keywordPlus GENOMES -
dc.subject.keywordAuthor Customized taxonomic assignment coding (CUTAXAC) -
dc.subject.keywordAuthor Marine metavirome -
dc.subject.keywordAuthor Taxonomy profiling -
dc.subject.keywordAuthor Fast analysis time -
dc.subject.keywordAuthor High Shannon diversity -
dc.relation.journalWebOfScienceCategory Marine & Freshwater Biology -
dc.relation.journalWebOfScienceCategory Oceanography -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.description.journalRegisteredClass kci -
dc.relation.journalResearchArea Marine & Freshwater Biology -
dc.relation.journalResearchArea Oceanography -
Appears in Collections:
South Sea Research Institute > Library of Marine Samples > 1. Journal Articles
South Sea Research Institute > Risk Assessment Research Center > 1. Journal Articles
Ocean Research, Operations & Support Department > Marine Bigdata Center > 1. Journal Articles
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