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ABSTRACT To enable an in-depth survey of the metabolic potential of complex soil microbiomes, we performed ultra-deep metagenome sequencing, collecting >1 Tb of sequence data from three grassland soils representing different precipitation regimes.
As part of the Pacific Northwest National Laboratory’s (PNNL) Science Focus Area program we are investigating the impact of environmental change on microbial community function in grassland soils. To enable a comprehensive survey of the metabolic potential of complex soil microbiomes, we performed ultra-deep metagenome sequencing, collecting >1 terabase of sequence data from grassland soils representing different precipitation regimes. Intermediate precipitation regime soil (rain-fed and irrigated agriculture) was collected from Konza Prairie Biological Station (KPBS).
As part of the Pacific Northwest National Laboratory’s (PNNL) Science Focus Area program we are investigating the impact of environmental change on microbial community function in grassland soils. To enable a comprehensive survey of the metabolic potential of complex soil microbiomes, we performed ultra-deep metagenome sequencing, collecting >1 terabase of sequence data from grassland soils representing different precipitation regimes. Soil samples were collected from Washington State University’s Irrigated Agriculture Research and Extension Center (IAREC) in Prosser, WA.
As part of the Pacific Northwest National Laboratory’s (PNNL) Science Focus Area program we are investigating the impact of environmental change on microbial community function in grassland soils. To enable a comprehensive survey of the metabolic potential of complex soil microbiomes, we performed ultra-deep metagenome sequencing, collecting >1 terabase of sequence data from grassland soils representing different precipitation regimes. Frequent precipitation regime soil (rain-fed and tile-drained agriculture) was collected from Iowa State University’s Comparison of Biofuel Systems (COBS).
Petabases of reads are being produced by environmental metagenome sequencing. An essential step in analyzing these data is metagenome assembly, the computational reconstruction of genome sequences from microbial communities. “Coassembly” of metagenomic sequence data, in which multiple samples are assembled together, enables more complete detection of microbial genomes in an environment than “multiassembly,” in which samples are assembled individually.