Algal and Fungal Diversity in Antarctic Lichens
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Title
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Algal and Fungal Diversity in Antarctic Lichens
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Authors
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Park, Chae Haeng
Kim, Kyung Mo
Elvebakk, Arve
Kim, Ok-Sun
Jeong, Gajin
Hong, Soon Gyu
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Subject
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Microbiology
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Keywords
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Cladonia; Lichen-associated fungi; Microalgae; Umbilicaria; Usnea
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Issue Date
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2014
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Citation
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Park, Chae Haeng, et al. 2014. "Algal and Fungal Diversity in Antarctic Lichens". Journal of Eukaryotic Microbiology, 62: 196-205.
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Abstract
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The composition of lichen ecosystems except mycobiont and photobiont has
not been evaluated intensively. In addition, recent studies to identify algal
genotypes have raised questions about the specific relationship between mycobiont
and photobiont. In the current study, we analyzed algal and fungal
community structures in lichen species from King George Island, Antarctica,
by pyrosequencing of eukaryotic large subunit (LSU) and algal internal transcribed
spacer (ITS) domains of the nuclear rRNA gene. The sequencing
results of LSU and ITS regions indicated that each lichen thallus contained
diverse algal species. The major algal operational taxonomic unit (OTU) defined
at a 99% similarity cutoff of LSU sequences accounted for 78.7-100% of the
total algal community in each sample. In several cases, the major OTUs
defined by LSU sequences were represented by two closely related OTUs
defined by 98% sequence similarity of ITS domain. The results of LSU
sequences indicated that lichen-associated fungi belonged to the Arthoniomycetes,
Eurotiomycetes, Lecanoromycetes, Leotiomycetes, and Sordariomycetes
of the Ascomycota, and Tremellomycetes and Cystobasidiomycetes of the
Basidiomycota. The composition of major photobiont species and lichen-associated
fungal community were mostly related to the mycobiont species. The
contribution of growth forms or substrates on composition of photobiont and
lichen-associated fungi was not evident.
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DOI
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http://dx.doi.org/10.1111/jeu.12159
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Type
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Article
- 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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