Biological diversity has proven essential towards maintaining many ecosystem functions, including biomass production. Diverse ecosystems often use available resources, such as nutrients and light, more completely and efficiently, thus creating greater biomass out of limited resources. Here, we investigate the genomic, and therefore more mechanistic, foundation of the existing theoretical and empirical evidence for diversity-productivity relationships. We raised eight species of freshwater algae as monoculture and biculture crops under controlled laboratory conditions. We quantified two measures of algal productivity: cell density and yields of fatty acid methyl ester (FAME). De-novo reconstruction of transcriptomes were generated with RNA-seq data via Trinity. We assigned function categories for each gene using Gene Ontology (GO) terms, and determined differential gene expressions of each species in each biculture relative to the monoculture condition.
Results/Conclusions
We observed overyielding of cell density and/or FAME production relative to additive expectations from monoculture yields in 64% of all algal bicultures. We found that both competitive and facilitative interspecific interactions can lead to overyielding. Using the entire available transcriptomes, we found that in some species these overyielding bicultures showed unique genomic signatures compared to monocultures and non-overyielding bicultures. We then identified a list of GO terms involved in lipid biosynthesis. We designated a subset of algal genes from each species that matched these GO terms as ‘lipid’ genes. Among the bicultures with overyielding FAME production, 46% exhibited significant differential expression of genes with these lipid functions relative to all other functions. In contrast, none of the non-overyielding bicultures showed significant differential expression of genes with lipid functions. We then identify specific genes predictive of FAME yield, including genes regulating fatty-acid and phospholipid biosynthesis. Overall, these results begin to narrow in on the genomic foundation and mechanistic basis of diversity-productivity relationships, and more broadly contribute to the integration of genomics with community ecology dynamics.