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What should Bioinformatics do for EvoDevo?
- 1. Insights into the evolution and development of planarian regeneration from the genome of the flatworm Girardia tigrina SUJAI KUMAR 2014-07-24 VIENNA EURO EVODEVO WHAT SHOULD BIOINFORMATICS DO FOR EVODEVO?
- 3. SUJAI KUMAR "Winkel triple projection SW" by Strebe - Own work Licensed under Creative Commons Attribution-Share Alike 3.0 via Wikimedia Commons http://commons.wikimedia.org/wiki/File:Winkel_triple_projection_SW.jpg Cartoonist and mathematics teacher in New Delhi
- 4. SUJAI KUMAR Finding patterns in sequences: TIMSS 1999 video study MS in Educational Psychology at the University of Illinois
- 5. SUJAI KUMAR Self-organising systems research in New Delhi
- 6. SUJAI KUMAR Sequenced four nematode genomes for PhD in Blaxter Lab, Edinburgh
- 7. SUJAI KUMAR Planarian regeneration genomics in Aboobaker Lab, Oxford
- 8. Outline of this talk 1. Regeneration, planarian flatworms, and Girardia tigrina 2. Creating G tigrina genomic resources 3. Using these resources to understand regeneration 4. What should bioinformatics do for EvoDevo
- 9. 1. Regeneration, planarian flatworms, and Girardia tigrina Bely and Nyberg, 2010 DOI:10.1016/j.tree.2009.08.005
- 10. 1. Regeneration, planarian flatworms, and Girardia tigrina Kao, 2014. PhD Thesis “Transcriptome assembly and analysis of the freshwater planarian Schmidtea mediterranea” Platyhelminthes Cestoda Monogenea Trematoda Rhabditophora Turbellaria Tricladida Macrostomorpha Lecithoepitheliata Rhabdocoela T T T T T T Girardia tigrina aboobakerlab.com/genomes G Schmidtea mediterranea smedgd.neuro.utah.edu G Polycladida
- 11. 1. Regeneration, planarian flatworms, and Girardia tigrina • What we know already • Some genes and pathways that are essential for WBR • Some transcription expression profiles • No transgenics in any planarian
- 12. 2. Creating G tigrina genomic resources Sequencing > Assembly > Annotation > Delivery
- 13. 2. Creating G tigrina genomic resources Sequencing > Assembly > Annotation > Delivery Illumina HiSeq: Workhorse Short paired reads ~$£€ 1,000 / 100 MegaBase Mate pairs essential PacBio: expensive High quality fly genome ~$£€ 10,000 / 100 MegaBase Nanopore – not a game changer just yet
- 14. 2. Creating G tigrina genomic resources Sequencing > Assembly > Annotation > Delivery • Quality Control • Raw data QC fastqc • Preliminary assembly Blobology • Separate components contaminants/ endosymbionts/ mitochondrial • Assess insert sizes Bad mate pair libraries confound scaffolding
- 15. Each point is a contig from a preliminary assembly (Caenorhabditis Sp. 5) Taxon-annotated GC-Coverage (TAGC) Plots a.k.a “Blobology”
- 17. 2. Creating G tigrina genomic resources Sequencing > Assembly > Annotation > Delivery • Quality Control • Raw data QC fastqc • Preliminary assembly Blobology • Separate components contaminants/ endosymbionts/ mitochondrial • Assess insert sizes Bad mate pair libraries confound scaffolding • Generate many assemblies • ABySS, CLC, MaSurCA, SGA, Spades, ALLPATHS-LG • Evaluate assemblies • FRCbam, REAPR, CGAL • CEGMA, alignments to known sequences • Freeze and release
- 18. 2. Creating G tigrina genomic resources Sequencing > Assembly > Annotation > Delivery • NOT a great assembly • But it was GoodEnough™ • Next version with long-insert mate pairs • Diploid, but high heterozygosity Assembly version nGt.0.3 nGt.0.5 Raw read data ~500M short read pairs 160 GBases Consolidating near identical contigs Total Span Gbases 1.898 1.500 Num Contigs 581,558 422,617 Span Contigs >10kb 541,653,308 536,575,093 Num Contigs >10kb 29,050 27,495 N50 5,751 6,827 CEGMA 45% 56%
- 19. 2. Creating G tigrina genomic resources Sequencing > Assembly > Annotation > Delivery • Gene prediction • RNA-seq • Predictors Augustus, SNAP, GeneMark • Consolidators MAKER, EVM, ENSEMBL genebuild • Evaluate use Annotation Edit Distance (AED) as a metric • Functional annotation • InterProScan, Trinotate, Blast2GO • Community annotation • WebApollo, Community Annotation Portal Annotation Version Num of Genes Num of Genes with AED>0.5 Mean aa length Num of Genes with InterPro annotations nGt.0.5.1 39,119 35,061 268 22,747
- 20. 2. Creating G tigrina genomic resources Sequencing > Assembly > Annotation > Delivery • Genome Browser • Blast server • Bulk data downloads • Interface • Badger, Tripal, InterMine, Ensembl
- 21. 3. Using these resources to understand regeneration • Individual genes and pathways • Transgenics • Protein ortholog analysis • 4 triclads, 1 other platyhelminth, 2 ecdysozoa, 4 deuterostomes • 14k out of 40k G tigrina proteins in strict ortholog clusters • ~8000 triclad-specific clusters • ~800 triclad-specific clusters with all 4 species represented • Cis-regulatory analysis • Neoblast specific regulatory regions
- 22. 4. What should bioinformatics do for EvoDevo • What should I do for an experimental EvoDevo lab • Visual > Text • View additional information in place • Plot everything vs everything • Create gene models visually • Routine analyses should not require bioinformatician • Clear explanations of how a resource was created • Not too many versions • Minimum standards
- 23. 4. What should bioinformatics do for EvoDevo • What should the bioinformatics community do for me as an EvoDevo bioinformatician • Best practice documentation for analyses • Easy to install tools • Minimum standards for assembly, metadata, annotation, and delivery • Grants for coordination, tools, resources
- 24. Summary • Please use the resources at aboobakerlab.com/genomes • Tell us what other resources you’d like to see as standard • Fund technology development and training
- 25. Acknowledgements • AboobakerLab.com • Aziz Aboobaker • Natalia Pouchkina-Stantcheva • Damian Kao • Yuliana Mihaylova • Aphrodite Zhao • Blaxter Lab (nematodes.org) • Ben Elsworth (Badger) • Sequencing • Edinburgh Genomics • Funding • BBSRC • BSDB / Company of Biologists travel grant
Editor's Notes
- Target audience Biologists who want genomic resources for their favourite species but are not sure of what is possible Bioinformaticians who are creating these resources
- Pic of sequencing from Lex – highlight technologies, put costs/advantages on side Drosophila contigs better than Sanger Sequencing 42 SMRT for 160 MB cells, approx cost for 60 = 18,000, fo 40 should cost ~12,000 PacBio promising 4X improvement so even lower Human 54X coverage ~ 40,000 so much less
- 1 in 200 bp 1 in 500 bp
- Delivery – whatever you choose, be sure it can support a large number of draft contigs/scaffolds – many tools that work well for a few chroosomes or a few hundred scaffolds don’t work so well for thousands (as we had)
- Think of a good way to get Triclad only Lopho only Protostomia only All --- (rename sp as cols, and check cols) using regexp (with counts)
- Work in progress. We do some things ok. 1. Planmine and Badger vs FTP downloads 2. Additional info in one place (don’t make users click around too much). Gbrowse is fabulous - http://banana-genome.cirad.fr great example, inline help as well 3. In the future – on the fly? (what takes time is the computation and recomputation for a whole genome, but individual genes/contigs should be doable on the fly) 3. Say something provocative
- Work in progress. We do some things ok. 1. Compare badger to – FTP download site (because it has descriptive information) 2. Additional info in one place (don’t make users click around too much). Gbrowse is fabulous - http://banana-genome.cirad.fr great example, inline help as well In the future – on the fly? (what takes time is the computation and recomputation for a whole genome, but individual genes/contigs should be doable on the fly) 3. Say something provocative