The ecology of microbes frequently involves the mixing of entire communities (community coalescence), for example, flooding events, host excretion, and soil tillage [1, 2], yet the consequences of this process for community structure and function are poorly understood [3-7]. Recent theory suggests that a community, due to coevolution between constituent species, may act as a partially cohesive unit [8-11], resulting in one community dominating after community coalescence. This dominant community is predicted to be the one that uses resources most efficiently when grown in isolation [11]. We experimentally tested these predictions using methanogenic communities, for which efficient resource use, quantified by methane production, requires coevolved cross-feeding interactions between species [12]. After propagation in laboratory-scale anaerobic digesters, community composition (determined from 16S rRNA sequencing) and methane production of mixtures of communities closely resembled that of the single most productive community grown in isolation. Analysis of each community's contribution toward the final mixture suggests that certain combinations of taxa within a community might be co-selected as a result of coevolved interactions. As a corollary of these findings, we also show that methane production increased with the number of inoculated communities. These findings are relevant to the understanding of the ecological dynamics of natural microbial communities, as well as demonstrating a simple method of predictably enhancing microbial community function in biotechnology, health, and agriculture [13].

Background Seminal studies of vertebrate protein evolution speculated that gene regulatory changes can drive anatomical innovations. However, very little is known about gene regulatory network (GRN) evolution associated with phenotypic effect across ecologically diverse species. Here we use a novel approach for comparative GRN analysis in vertebrate species to study GRN evolution in representative species of the most striking examples of adaptive radiations, the East African cichlids. We previously demonstrated how the explosive phenotypic diversification of East African cichlids can be attributed to diverse molecular mechanisms, including accelerated regulatory sequence evolution and gene expression divergence. Results To investigate these mechanisms across species at a genome-wide scale, we develop a novel computational pipeline that predicts regulators for co-extant and ancestral co-expression modules along a phylogeny, and candidate regulatory regions associated with traits under selection in cichlids. As a case study, we apply our approach to a well-studied adaptive trait—the visual system—for which we report striking cases of network rewiring for visual opsin genes, identify discrete regulatory variants, and investigate their association with cichlid visual system evolution. In regulatory regions of visual opsin genes, in vitro assays confirm that transcription factor binding site mutations disrupt regulatory edges across species and segregate according to lake species phylogeny and ecology, suggesting GRN rewiring in radiating cichlids. Conclusions Our approach reveals numerous novel potential candidate regulators and regulatory regions across cichlid genomes, including some novel and some previously reported associations to known adaptive evolutionary traits.

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