1. Biodiversity initiative: Integrating Taxonomy, Genomics and Biodiversity ++ = ????? Speaker: Benjamin Linard Alfried Vogler Team

2. Arthropods metagenomics 1 / 8 DNA extraction PCR barcodes Mixed sample All 480 beetles Est. 288 species 1x Illumina MiSeq run (8.5Gb) Mitochondrial contigs De novo assembly into contigs Pool DNA by volume 1 SAMPLE: 480 beetle specimens captured in Borneo

3. Mitochondrial DNA 2 / 8 Harpalinae Chrysomelidae Coccinelidae Curculionidae Tenebrionidae Buprestidae Log(Biomass) = -2.37 + 0.85(log(No. Reads)) P<0.001; F 1,84 =73.32; R 2 =0.47 ~5% beetle mitochondrial DNA Shotgun output No. reads33,796,432 Est. proportion mitochondrial reads 4.94% Complete mitogenomes35 Partial mitogenomes >10kb85 Partial mitogenomes 2-10kb 420 Results of Alex Crampton Plat

4. Genomic information ? 3 / 8 ~95% genomic information, ~45 % is Coleoptera DNA ~5% beetle mitochondria Taxomomy Abundance Genomic analyses Functional information ? Tribolium castaneum, chromosome 3 # homologous contigs position Homologous contig% GC Chromosome region with known sequence NNNN region (unresolved sequence) Homologous DNA between 4 beetle metagenomic samples

5. Arthropods metagenomics Computational requirements to analyse 1 arthropod soup : Server:~128Gb RAM, 24 cores Xeon 2.4 GHz Assemblies TypeRAM (Gb)Time (6 cores)Disk (Go) Mitochondrial< 10< 12 hours< 30 Total DNA~ 100~ 5 days~ 300-500 ( in the best case... when data complexity is manageable by current algorithms ) Our last DNA assembly One assembly at a time, unpredictible risk of memory overload Several assemblies (~1.5 per week) Successful Aborted 4 / 8

6. Arthropods metagenomics Computational requirements to analyse 1 arthropod soup : Server:~128Gb RAM, 24 cores Xeon 2.4 GHz Assemblies TypeRAM (Gb)Time (6 cores)Disk (Go) Mitochondrial< 10< 12 hours< 30 Total DNA~ 100~ 5 days~ 300-500 ( in the best case... when data complexity is manageable by current algorithms ) 5 / 8 Genomic analyses : TypeRAM (Gb)Time (6 cores)Disk (Go) Homology/ alignments< 2~ 5 days< 10 Statistics / graphs< 2~ 1 day< 2 Need support of SQL database. Currenlty ~ 300 Gb

7. 5 / 8 Future ? for the analysis of 1 arthropod soup ~1 000 arthropods trancriptomes/genomes ~50 beetle species transcriptomes ~50 beetle draft/complete genomes Long term perspective: Disk space consuming...# more reference genomes # larger/more complex databases Growth of analysis pipeline ! More CPU to perform a complete metagenomic analyses standard MIGS (D Field & al, 2008) standards MINIMESS (J Raes & al, 2007) Biodiversity & functional analysis

8. Arthropods biodiversity n traps per site: (soil, canopy, Ground…) N plots Mitochondrial analysis, not a problem Full DNA analysis...  Which computational power could we access ?  More computations to answer more interesting questions Pooling DNA?We will loose metagenomic resolution... More complex assemblies Many soup analyses... 6 / 7

9. A source of DNA collection 7 / 8 Metadata (1 arthropod soup) General:Sampling localisation, date, methods... Mitochondrial information:Identified species/taxons Abundance Other identified species (plants, fungi...) Genomic information:Identified genes Identified functions (sugar degradation) Soup metadata 125 species, French Guyana Soup metadata 24 unidentified tenebrionidae from Madagascar Soup metadata 53 species + abundance data Soup metadata 24 species, Congo, Scientific community in NHM access NHM data portal Kemu Integration, links, queries... “I want all NHM collection data concerning the species X” Data storage ? NHM databases integration ? 8 specimens, 4 images, 2 metagenomic samples...

10. Thank you for your attention. BEETLE SOUP, Your daily source of DNA! BEETLE SOUP