Metagenomic data of the microbial community of the chemocline layer of the meromictic subarctic Lake Bolshie Hruslomeny, North European Russia
Vitaly V. Kadnikov,
Alexander S. Savvichev,
Andrey V. Mardanov,
Alexey V. Beletsky,
Nikolai V. Ravin,
Nikolai V. Pimenov
Affiliations
Vitaly V. Kadnikov
Institute of Bioengineering, Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia; Corresponding author. Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia.
Alexander S. Savvichev
Winogradsky Institute of Microbiology, Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia
Andrey V. Mardanov
Institute of Bioengineering, Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia
Alexey V. Beletsky
Institute of Bioengineering, Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia
Nikolai V. Ravin
Institute of Bioengineering, Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia; Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
Nikolai V. Pimenov
Winogradsky Institute of Microbiology, Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia
The Lake Bolshie Hruslomeny is located on the shores of the Kandalaksha Bay of the White Sea, North European Russia. This lake, formed from the sea bay and still retaining the subsurface connection with the sea, is meromictic, with a fresh oxygenated upper layer and an anoxic brackish hypolimnion with high concentrations of methane and hydrogen sulphide. To characterize the microbial communities involved in the carbon and sulfur cycles in the lake, we sequenced the metagenome of a water sample collected at the chemocline level. At the phylum level, Chlorobi, Proteobacteria, Bacteroidetes and Firmicutes were the most numerous groups. The obtained data will help investigate the diversity and ecological role of the microbial community in the Lake Bolshie Hruslomeny and provide insight into the biogeochemical processes in subarctic lakes. The raw sequencing data is available from the NCBI Sequence Read Archive (SRA) database under the BioProject PRJNA503531.
