The Signal and the Noise: Characteristics of Antisense RNA in Complex Microbial Communities

High-throughput sequencing has allowed unprecedented insight intothe composition and function of complex microbial communities. With metatranscriptomics,it is possible to interrogate the transcriptomes of multiple organisms simultaneouslyto get an overview of the gene expression of the entire community.Studies have successfully used metatranscriptomics to identify and describe relationshipsbetween gene expression levels and community characteristics. However,metatranscriptomic data sets contain a rich suite of additional information that isjust beginning to be explored. Here, we focus on antisense expression in metatranscriptomics,discuss the different computational strategies for handling it, and highlightthe strengths but also potentially detrimental effects on downstream analysisand interpretation. We also analyzed the antisense transcriptomes of multiple genomesand metagenome-assembled genomes (MAGs) from five different data setsand found high variability in the levels of antisense transcription for individual species,which were consistent across samples. Importantly, we challenged the conceptualframework that antisense transcription is primarily the product of transcriptionalnoise and found mixed support, suggesting that the total observed antisense RNA incomplex communities arises from the combined effect of unknown biological andtechnical factors. Antisense transcription can be highly informative, including technicaldetails about data quality and novel insight into the biology of complex microbialcommunities.