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Comparative Analysis of Bacterial Community Composition in Lakes of the Dry Valleys, East Antarctica

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dc.contributor.authorKwon, Miye-
dc.contributor.authorKim, Mincheol-
dc.contributor.authorPriscu, John C.-
dc.contributor.authorHong, Soon Gyu-
dc.contributor.authorKim, Sang Jong-
dc.contributor.authorKim, Ok-Sun-
dc.coverage.spatialDry Valleys-
dc.date.accessioned2017-08-03T12:09:42Z-
dc.date.available2017-08-03T12:09:42Z-
dc.date.issued2014-
dc.description.abstractIn the current study, the community composition of bacteria were investigated the perennial ice-covered lakes in the fine scale using 454-pyrosequencing; Fryxell (FRX), Hoare (HOR) and Miers (MIE). Based on 16S rRNA gene, total 124,803 sequences were quality filtered using 97% similarity cutoff, and 55 phyla were recovered containing the major phyla Actinobacteria (29%), Bacteroidetes (24.4%) and Proteobacteria (14%). In the phylum level, the bacterial taxonomy were highly shown the heterogeneous communities. Overall, microbial community composition varies not only between lakes, but also along the depth gradients within lake. Taken together, the diversity of microbial communities in lakes of MDVs provided a crucial evidence to understand the impact of microbial ecological roles in these ecosystems.-
dc.languageEnglish-
dc.titleComparative Analysis of Bacterial Community Composition in Lakes of the Dry Valleys, East Antarctica-
dc.typePoster-
dc.identifier.bibliographicCitationKwon, Miye, et al. 2014. Comparative Analysis of Bacterial Community Composition in Lakes of the Dry Valleys, East Antarctica. 2014 International Meeting of the Microbiological society of Korea. Daegu. 2014.04.30-05.02.-
dc.citation.conferenceDate2014.04.30-05.02-
dc.citation.conferenceName2014 International Meeting of the Microbiological society of Korea-
dc.citation.conferencePlaceDaegu-
dc.subject.keywordBacterial community-
dc.subject.keywordDry Valley-
dc.subject.keywordFresh water-
Appears in Collections  
2014-2016, Long-Term Ecological Researches on King George Island to Predict Ecosystem Responses to Climate Change (14-16) / Hong; Soon Gyu (PE14020; PE15020; PE16020)
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