Bedrock and biotic influence on on community composition of soils from the Sør Rondane Mountains, East Antarctica

• Main Authors: Tytgat, Bjorn, Verleyen, Elie, D'hondt, Sofie, Clercx, Pia, Van Ranst, Eric, Roberts, Stephen, Wilmotte, Annick, Vyverman, Wim, Willems, Anne
• Format: Conference Object
• Language: English
• Published: 2015
• Subjects: Earth and Environmental Sciences; EAST ANTARCTICA; TERRESTRIAL; SøR RONDANE MOUNTAINS; ILLUMINA; ARISA; Antarctic; East Antarctica; Dronning Maud Land; McMurdo Dry Valleys; Transantarctic Mountains; Sør-Rondane; Sør Rondane Mountains; Antarc*; Antarctica; DML
• Online Access: https://biblio.ugent.be/publication/6934857; http://hdl.handle.net/1854/LU-6934857

Antarctica is a continent of extremes; the low availability of liquid water and nutrients, extreme low temperatures and seasonally variable levels of solar radiation exert high selective pressures on organisms. Consequently, most life forms in the scarce ice-free regions which represent less than 1% of the surface area of the continent are microbial. Despite this, terrestrial microbial communities are poorly studied and the existing data are geographically focused on McMurdo dry valleys and volcanically active regions. Nunataks, mountain tops protruding through the ice sheets, occur along much of the East Antarctic coast and in the Transantarctic Mountains. Among them, several remained ice-free during Neogene and Pleistocene ice ages and thus may have acted as important refugia for terrestrial life. Here we present the results of a broad-scale survey of microbial biodiversity of ice-free regions in the western Sør Rondane Mountains (Dronning Maud Land (DML), East Antarctica). A total of 66 samples from eight different ice-free regions were selected to represent gradients in bedrock type (gneiss or granite), the macrobiotic content (presence or absence of moss, lichen and/or arthropods) and geographic location. All samples were subjected to both genetic fingerprinting (ARISA) and second generation sequencing (Illumina MiSeq 300PE) targeting the V1-V3 variable regions of the 16S rRNA gene. Mock communities were included to benchmark the bioinformatics pipeline. Reads were processed using Usearch (Edgar 2010), clustered based on a 97 % similarity cutoff using Uparse (Edgar 2013) and identified using the GreenGenes training set. The specific conductivity, pH, water content, and total (TC), total organic (TOC) and inorganic (IC) carbon content were determined and used as explanatory variables in direct ordination analyses of both the ARISA and the Illumina data. The Illumina sequencing resulted in ~600.000 high quality sequences divided over ~3980 OTUs in 28 phyla and 219 genera. No significant differences in ...