Getting specific: making taxonomic and ecological sense of large sequencing data sets.

Eukaryotic microbes comprise a diverse collection of phototrophic and heterotrophic creatures known to play fundamental roles in ecological processes. Some can be identified by light microscopy, generally the largest and with conspicuous shapes, while the smallest can be counted by epifluorescence microscopy or flow cytometry but remain largely unidentified. Microbial diversity studies greatly advanced with the analysis of phylogenetic markers sequenced from natural assemblages. Molecular surveys began in 1990 targeting marine bacterioplankton (Giovannoni et al. ) and first approached microbial eukaryotes in three studies published in 2001 (Díez et al. ; López-García et al. ; Moon-van der Staay et al. ). These seminal studies, based on cloning and Sanger sequencing the complete 18S rDNA, were critical for obtaining broad pictures of microbial diversity in contrasted habitats and for describing novel lineages by robust phylogenies, but were limited by the number of sequences obtained. So, inventories of species richness in a given sample and community comparisons through environmental gradients were very incomplete. These limitations have been overcome with the advent of high-throughput sequencing (HTS) methods, initially 454-pyrosequencing, today Illumina and soon others to come. In this issue of Molecular Ecology, Egge et al. () show a nice example of the use of HTS to study the biodiversity and seasonal succession of a particularly important group of marine microbial eukaryotes, the haptophytes. Temporal changes were analysed first at the community level, then at the clade level, and finally at the lowest rank comparable to species. Interesting and useful ecological insights were obtained at each taxonomic scale. Haptophyte diversity differed along seasons in a systematic manner, with some species showing seasonal preferences and others being always present. Many of these species had no correspondence with known species, pointing out the high level of novelty in microbial assemblages, only accessible by molecular tools. Moreover, the number of species detected was limited, agreeing with a putative scenario of constrained evolutionary diversification in free-living small eukaryotes. This study illustrates the potential of HTS to address ecological relevant questions in an accessible way by processing large data sets that, nonetheless, need to be treated with a fair understanding of their limitations.