Catalysis Meeting

High-throughput biodiversity research using eukaryotic metagenetics

PI(s): Holly Bik (University of New Hampshire)
W. Kelley Thomas (University of New Hampshire)
Start Date: 10-Oct-2010
End Date: 10-Oct-2011
Keywords: biodiversity, evolutionary genetics, biogeography, molecular biology

Eukaryotic meiofauna (organisms 45μm-1mm) are abundant and ubiquitous across every ecosystem on earth. Yet, there exists a well-recognized gap in the understanding of their global biodiversity. This unexplored diversity represents one of the major challenges in biology and limits our capacity to understand, mitigate and remediate the consequences of environmental change. Driven by fundamental advances in DNA sequencing (Schuster, 2008) new high-throughput sequencing (HTS) platforms make it possible to explore biodiversity at a scale that allows for the discovery of virtually all of the of the organisms in an environmental sample. It is now possible to conduct en mass meiofaunal biodiversity assessment (metagenetics) using traditional molecular loci (e.g. ribosomal rRNA, Creer et al., 2010; Sogin et al., 2006) at a fraction of the time and cost required for traditional approaches. However, the field of metagenetics is still in its infancy; we currently have a poor understanding of key features of ribosomal RNA gene evolution and continue to lack the cyberinfrastructure needed for effective interpretation of large HTS datasets. Through the proposed catalysis meeting, we will bring together current collaborators and other investigators who are keen to share expertise and contribute towards computational/theoretical advances within the field. These discussions and interactions will be used as a basis for a longer-term Research Coordination Network funding proposal through NSF in 2011. Ultimately, we aim to coordinate the application and analysis of common genetic loci within the eukaryotic community, facilitate data sharing and promote comparative analyses using existing resources in conjunction with a new open-access database structure.