ena-STUDY-CEBITEC-13-03-2015-21:15:36:667-141
Deeply sequenced metagenome and metatranscriptome of a biogas-producing microbial community from an agricultural production-scale biogas plant
Background Most of the organisms of biogas communities are still unknown and non-cultivable. Accordingly, metagenome sequencing is currently the only possibility to obtain insights into community composition and the genetic repertoire.  Findings We report the first deeply sequenced metagenome and metatranscriptome of a biogas-producing microbial community from an agricultural production-scale biogas plant. Our metagenome assembly reconstructed most genes involved in methane metabolism, a key pathway involving methanogenesis populated by low-abundance archaea, indicating sufficient coverage for many downstream analyses.  Conclusions Sequenced at least one order of magnitude deeper than previous studies, our metagenome data will enable novel insights into community composition and the genetic potential of important community members. Moreover, mapping of transcripts to reconstructed genome sequences will enable the identification of active metabolic pathways in target organisms.
Background Most of the organisms of biogas communities are still unknown and non-cultivable. Accordingly, metagenome sequencing is currently the only possibility to obtain insights into community composition and the genetic repertoire.  Findings We report the first deeply sequenced metagenome and metatranscriptome of a biogas-producing microbial community from an agricultural production-scale biogas plant. Our metagenome assembly reconstructed most genes involved in methane metabolism, a key pathway involving methanogenesis populated by low-abundance archaea, indicating sufficient coverage for many downstream analyses.  Conclusions Sequenced at least one order of magnitude deeper than previous studies, our metagenome data will enable novel insights into community composition and the genetic potential of important community members. Moreover, mapping of transcripts to reconstructed genome sequences will enable the identification of active metabolic pathways in target organisms.