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CBOL, DNA Barcoding and Long-Term Ecological Studies David E. Schindel, Executive Secretary National Museum of Natural History Smithsonian Institution [email protected]; http://www.barcoding.si.edu 202/633-0812; fax 202/633-2938 “The GO network aims to mainstream ecogenomic data into next-generation Earth Observing Systems, and improve and validate models – at the local and global levels – to better understand and manage climate change and ecosystem services.” A sample should be more than a sample Long-term observation/monitoring Understand long-term processes Measure responses to forcing functions: –Climatic shifts –Rare events (fire, flooding, drought) –Land use changes –Introductions, invasives, pathogens –Experimental manipulation Founding Philosophy Environmental change is inevitable Select a sentinel site (criteria vary) Establish a longitudinal baseline Wait for gradual shifts or rare events [Or conduct perturbation experiments] Document outcomes, impacts, underlying processes on varied levels Harvard Forest Long-Term Ecological Research Site Smithsonian Environmental Research Center, Edgewater, MD • • • • • What are (traditional) Observatories? Secure sites for long-term projects Heavily instrumented Environmental datastreams Rarely have biorepositories for voucher specimens [Data standards for comparative research] Where to site Observatories? Approaches to site selection and sampling: – ATBIs for deep analysis of local richness (repeated at sentinel sites?) – Site-based long-term ecological/ecosystem monitoring at edges of habitat domains – Virtual network: Compilations of projects to document range/physiology shifts – Bioblitzes as compromise Why create Genome Observatories (GOs)? Genomic level closer to biological responses (physiology, pop. variation) Weaknesses of taxonomic names: instability, non-standard protocols, string data, cost and delay in data acquisition Strengths of genetic data: standard protocols; digital data; speed of data acquisition; multiple uses: taxonomy, phylogenetics, function, applications GOs: How and Where? Add to existing networks? (LTER, NEON)? Or Should GOs be more mobile, work faster, conduct shallower repeatable sampling? Barcoding’s Contribution (1) Taxonomy by non-taxonomists Hidden splits Difficult groups as MOTUs Degraded, fragmental samples Biotic lists from mixtures Diet reconstruction from feces, gut contents Barcoding and NEON Sentinel sites Barcoding program with vouchers for: – Mosquitoes – Ground beetles Prototype effort aims to: – Evaluate barcoding methods – Establish the DNA barcode library – Develop workflow Longer-term: Track species richness? Biocode Inventory Progress Fungi Plants unique species Terrestrial Inverts DNA barcoded Specimens Algae Marine Invertebrates Marine Verts 1 10 100 1000 10000 100000 June 2011 Arctic Canada Barcode ATBI Michelle Van der Bank, Univ. of Johannesburg Accepting Toyotas for South African Barcoding Blitzes Barcodes in Ecology Vouchers as communities of species, samples of foodchains, not single taxon Pathogens and bloodmeals in a mosquito Pollen species on bees Specialists versus generalists in: – Insectivorous bats – Phytophagous insects Top herbivores and their impact on standing diversity Barcoding’s Contribution (2) Data standard for large scale – Standardized, calibrated unit of similarity/variation – Vouchering of specimens – Traceability to Vouchers in repositories Raw sequence data in trace files – Early data release for distributed data curation New Standards Needed Not just georeferenced – Ecoreferenced – place in habitat, surrounding organisms – Bioreferenced – place in organism Ecto/endoparasite? Taken from what organ system? Metadata on preservation methods used Metadata on handling/sorting of mixtures BARCODE Records in INSDC Specimen Metadata Georeference Habitat Character sets Images Behavior Other genes Voucher Specimen Barcode Sequence Trace files Literature citation Primers Species Name Indices - Catalogue of Life - GBIF/ECAT Nomenclators - Zoo Record - IPNI - NameBank Publication links - New species Record in BOLD Databases - Provisional sp. Voucher specimen ID Species ID Identified by Traditional Taxonomy GSC Minimum Standards (MI*) XXX XXX XXX XXX X X XXX XXX DNA sequence XXX Gene region Geographic origin (country, ocean) Latitude/Longitude Collection date, collector name Trace files Primer information Traditional GenBank XXX X XXX XXX XXX XXX XXX X XX XX New Traceability Needed Multiple proliferating generations of offsprings: – Tissue subsamples DNA extracts – PCR amplicons Transfer of offsprings to new repositories Retaining provenance data, ownership documentation, MTA, restrictions on re-use Synchronizing updates via BiSciCol Compliance with Standard (1) 1.37 million records in BOLD 514,390 BARCODE records in INSDC 395,774 have ordinal name plus Barcode Index Number for taxonomic ID – Rapid data release versus time for annotation – Exposure to data theft, risk of misidentification – Added value of Linnean name – Incidence of misidentifications in GenBank – Danger of circular reasoning Rod Page’s ‘Dark Taxa’ R. Page, iPhylo blogspot, 12 April 2011 Darwin Core Triplet Structured Link to Vouchers Institutional Acronym NHM personal : : : Collection Code LEP : : Catalog ID 123456 DHJanzen : SRNP12345 CBOL/GBIF/NCBI Registry of Biorepositories www.biorepositories.org Compliance with Standard (2) 514,390 BARCODE records in INSDC – Traces, primers, length, country, and presence of voucherID checked by GenBank 99.9% have entry for /specimen_voucher 13,151 have formatted voucher from 38 institutions – 20 confirmed in biorepositories – 11 unconfirmed – 7 unlisted Virtual Repository for the Tree of Life (VRTL) Exploratory workshop at Smithsonian National Museum Natural History, Oct 2011 23 participants, 11 institutions, 9 countries Representing major cryo-collections Advanced facilities like AMNH Integrated network: Germany DNA Bank Vision for virtual global resource for sample and data access Potential Impact Improved practices and policies within instiutions; Code of conduct leads to international access agreements Integrated distribtion maps enables gap analysis, more cost-effective collecting Virtual repository’s scale and data sharing requires