Marine Group II (MGII) archaea represent the most abundant planktonic archaeal group in ocean surface waters, but our understanding of the group has been limited by a lack of cultured representatives and few sequenced genomes. Here, we conducted a comparative phylogenomic analysis of 270 recently available MGII metagenome-assembled genomes (MAGs) to investigate their evolution and ecology. Based on a rank-normalised genome phylogeny, we propose that MGII is an order-level lineage for which we propose the name Candidatus Poseidoniale s (after Gr. n. Poseidon, God of the sea), comprising the families Candidatus Poseidonaceae fam. nov. (formerly subgroup MGIIa) and Candidatus Thalassarchaeaceae fam. nov. (formerly subgroup MGIIb). Within these families, 21 genera could be resolved, many of which had distinct biogeographic ranges and inferred nutrient preferences. Phylogenetic analyses of key metabolic functions suggest that the ancestor of Ca . Poseidoniales was a surface water-dwelling photoheterotroph that evolved to occupy multiple related ecological niches based primarily on spectral tuning of proteorhodopsin genes. Interestingly, this adaptation appears to involve an overwrite mechanism whereby an existing single copy of the proteorhodopsin gene is replaced by a horizontally transferred copy, which in many instances should allow an abrupt change in light absorption capacity. Phototrophy was lost entirely from five Ca . Poseidoniales genera coinciding with their adaptation to deeper aphotic waters. We also report the first instances of nitrate reductase in two genera acquired via horizontal gene transfer (HGT), which was a potential adaptation to oxygen limitation. Additional metabolic traits differentiating families and genera include flagellar-based adhesion, transporters, and sugar, amino acid, and peptide degradation. Our results suggest that HGT has shaped the evolution of Ca . Poseidoniales to occupy a variety of ecological niches and to become the most successful archaeal lineage in ocean surface waters.

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Metataxonomic 16S rDNA based studies are a commonplace and useful tool in the research of the microbiome, but they do not provide the full investigative power of metagenomics and metatranscriptomics for revealing the functional potential of microbial communities. However, the use of metagenomic and metatranscriptomic technologies is hindered by high costs and skills barrier necessary to generate and interpret the data. To address this, a tool for Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was developed for inferring the functional potential of an observed microbiome profile, based on 16S data. This allows functional inferences to be made from metataxonomic 16S rDNA studies with little extra work or cost, but its accuracy relies on the availability of completely sequenced genomes of representative organisms from the community being investigated. The rumen microbiome is an example of a community traditionally underrepresented in genome and sequence databases, but recent efforts by projects such as the Global Rumen Census and Hungate 1000 have resulted in a wide sampling of 16S rDNA profiles and almost 500 fully sequenced microbial genomes from this environment. Using this information, we have developed “CowPI,” a focused version of the PICRUSt tool provided for use by the wider scientific community in the study of the rumen microbiome. We evaluated the accuracy of CowPI and PICRUSt using two 16S datasets from the rumen microbiome: one generated from rDNA and the other from rRNA where corresponding metagenomic and metatranscriptomic data was also available. We show that the functional profiles predicted by CowPI better match estimates for both the meta-genomic and transcriptomic datasets than PICRUSt, and capture the higher degree of genetic variation and larger pangenomes of rumen organisms. Nonetheless, whilst being closer in terms of predictive power for the rumen microbiome, there were differences when compared to both the metagenomic and metatranscriptome data and so we recommend, where possible, functional inferences from 16S data should not replace metagenomic and metatranscriptomic approaches. The tool can be accessed at http://www.cowpi.org and is provided to the wider scientific community for use in the study of the rumen microbiome.

HmtDB (http://www.hmtdb.uniba.it:8080/hmdb) is a open resource created to support population genetics and mitochondrial disease studies. The database hosts human mitochondrial genome sequences annotated with population and variability data, the latter being estimated through the application of the SiteVar software based on site-specific nucleotide and amino acid variability calculations. The annotations are manually curated thus adding value to the quality of the information provided to the end-user. Classifier tools implemented in HmtDB allow the prediction of the haplogroup for any human mitochondrial genome currently stored in HmtDB or externally submitted de novo by an end-user. Haplogroup definition is based on the Phylotree system. End-users accessing HmtDB are hence allowed to (i) browse the database through the use of a multi-criterion ‘query’ system; (ii) analyze their own human mitochondrial sequences via the ‘classify’ tool (for complete genomes) or by downloading the ‘fragment-classifier’ tool (for partial sequences); (iii) download multi-alignments with reference genomes as well as variability data.