Microbes play fundamental roles in all biology-associated processes on the planet. A powerful new tool in such studies is metagenomics wherein one uses high throughput DNA sequencing methods on DNA isolated directly from environmental samples. Metagenomics has the potential to revolutionize our understanding of the normally hidden yet incredibly important world of microorganisms. However this great potential comes with enormous challenges in the analysis of the sequence data, including (i) the fragmentary nature of sequence data, (ii) the sparse sampling of genomes, populations and communities, and (iii) the unknown phylogenetic diversity and ecological structure of the communities being sampled. We are now working on methodology for analysis of metagenomic data as part of a new collaborative project: Integrating Statistical Evolutionary, and Ecological Approaches to Metagenomics (iSEEM). The iSEEM Project, funded by the Gordon and Betty Moore Foundation, took an integrated,interdisciplinary approach to metagenomic analysis.
iSEEM was a collaboration between the labs of Jonathan Eisen (PI), Jessica Green (CoPI) from the University of Oregon and Katie Pollard (CoPI), originally at UC Davis and now at UCSF. More information about the project can be found at http://iseem.org.
Publications supported by the iSEEM project include:
- Drivers of bacterial beta-diversity depend on spatial scale.
- The phylogenetic diversity of metagenomes.
- PhylOTU: a high-throughput procedure quantifies microbial community diversity and resolves novel taxa from metagenomic data.
- Introducing W.A.T.E.R.S.: a workflow for the alignment, taxonomy, and ecology of ribosomal sequences.
- BioTorrents: a file sharing service for scientific data.
- A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea.
- A simple, fast, and accurate method of phylogenomic inference.
- An automated phylogenetic tree-based small subunit rRNA taxonomy and alignment pipeline (STAP).
- PHAST and RPHAST: phylogenetic analysis with space/time models.
- Biodiversity and biogeography of the atmosphere.
- Field theory for biogeography: a spatially explicit model for predicting patterns of biodiversity.
- Patterns and causes of species richness: a general simulation model for macro ecology.
- An integrative framework for stochastic, size-structured community assembly.
Jonathan Eisen's Lab 