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Using NGS to answer biological questions

Using NGS to answer biological questions. Usadellab.org @ RWTH Aachen, Forschungszentrum Jülich. Microarrays and RNA Seq the old and the new. You have heard it all before. Was considered big data once. Open platform Good for SNP calling Higher dynmic range Better reflects RT-PCR data.

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Using NGS to answer biological questions

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  1. Using NGS to answer biological questions Usadellab.org @ RWTH Aachen, ForschungszentrumJülich

  2. Microarrays and RNA Seq the old and the new You have heard it all before • Was considered big data once • Open platform • Good for SNP calling • Higher dynmic range • Better reflects RT-PCR data

  3. All that glitters is not gold The goldrush is still in its high steam But all that glitters is not gold Sometimes a closed platform is not too bad, this also means standardization and of course microarrays take much less time to download Did you ever ask yourself: Oh let’s have a brief look a this dataset… Next generation sequencing publications in pubmed

  4. All that glitters is not gold The goldrush is still in its high steam But all that glitters is not gold Sometimes a closed platform is not too bad, this also means standardization and of course microarrays take much less time to download And then there is still mapping and stats Next generation sequencing publications in pubmed

  5. All that glitters is not gold The goldrush is still in its high steam But all that glitters is not gold Sometimes a closed platform is not too bad, this also means standardization and of course microarrays take much less time to download And storage Btw did you buy that new storage pod? Next generation sequencing publications in pubmed Another 180TB Another 20k€ Or worse you can‘t build yourself

  6. But the goldrush is still on So does it all come to naught? The goldrush is still in its high steam, so there is of course something Did you ever think it were possible that you yourself can sequence a full genome, de novo of course? Well that‘s a PhD topic now. (Within reason, up to medium sized plants, bacteria can be dealt with in a Bsc if you gt lucky) So where are good claims to be had and what can one do about it? Can Bioinformatics help biologists?

  7. Solanum pennellii - a wild tomato relative Moyle 2008 Source: Tomato Genome Resource Centre (TGRC) Wild relative of S. lycopersicum Grows in Peru and Northern Chile (TGRC Accessions shown)

  8. Solanum pennellii - a greatsourceofgenticvariation Schauer et al., 2006 x S.lyc M82 S. pennellii x Introgression Lines F1 S.lyc M82 Metabolites Introgression Line Population

  9. Trimmomatic fast & precise

  10. FilteringEffects

  11. Solanum pennellii Assembly Split on ‘N’s SNP small indel <0.03%

  12. Solanum pennellii - a greatsourceofgenticvariation Unfortunately it was the cultivar Heinz and not M82 that was sequenced Schauer et al., 2006 x S.lyc M82 S. pennellii x Introgression Lines F1 S.lyc M82 Luckily re-sequencing is relatively straight forward (sometimes) Metabolites Introgression Line Population

  13. Solanacae..... What makes them what they are Physalis alkengi (Chinese lantern) Physalis peruviana (Cape gooseberry) Physalis ixocarpia (tomatillo)

  14. The MapMan Plant Ontology More than 2000 terms Redundancy reduced terms for better visualization and statistical analysis ~ 20 plant species Automatic tool for whole transcriptome annotation

  15. Mercator Mercator: Bulk Sequence classification Results Summary and Tables FASTA Sequence Data Submission Mercator is an online resource allowing to submit large FASTA files containing plant sequences Mercator compares the sequences to in-house annotated and classified plant sequences and searches for domains Mercator then classifies all genes/proteins Mercator typically processes one genome equivalent in 2-3 days in acurate mode (and faster in draft mode)

  16. MapMan MapMan: Omics on Plant Pathway visualization, testing Expression Data Pathway Visualization Enrichment testing Interactive data Exploration MapMan is a graphical tool allowing • Pathway visualization for more about 20 plant species including all major crops • Testing for enriched pathways and processes • Interactice data exploration and visualization e.g. Venn Diagrams, Clustering,…

  17. Bringing it together Physalis alkengi leaf versus root Something was done right

  18. Diurnal Cycles and an Extended Night across species Carbon Status day night extended night Arrays RNA Seq Metabolic profiling

  19. Diurnal Cycles and an Extended Night across species Carbon Status day night extended night Arrays RNA Seq The mciroarray was pretty useless <10k genes Metabolic profiling

  20. Peak times seem to be conserved If you are a cycling gene it seems to be good to peak around midday or midnight

  21. Phases for orthologs seem to do much worse..... Genes ordered by phase in Arabidopsis, if you are very far away you might see some conservation

  22. Diurnal Cycles and an Extended Night across species Looking at individual genes can help....

  23. Conserved Pathways Myo Inositol pathway (MIOX) shows a conserved response Blue up Red down UDP-Glucose UDP-Glucose UDP-Glucose CELL WALL UGD UGD UGD UDP-Glucuronic Acid UDP-Glucuronic Acid UDP-Glucuronic Acid Glucuronic Acid-1-P Glucuronic Acid-1-P Glucuronic Acid-1-P Glucuronic Acid Glucuronic Acid Glucuronic Acid Miox Miox Miox Myo-Inositol Myo-Inositol Myo-Inositol Maize Tomato Arabidopsis

  24. Conserved Pathways... And metabolites Miox Pathway shows a correlated change in metabolites and transcripts CELL WALL UDP-Glucose UGD UDP-Glucuronic Acid Glucuronic Acid-1-P Glucuronokinase Glucuronic Acid Miox Myo-Inositol Blue up Red down

  25. ED EN XN ED EN XN Carbon and the Wall UDP-sugars drop in response to Carbon depletion UGD GK MIOX

  26. ED EN XN ED EN XN Carbon and the Wall UDP-sugars drop in Carbon depletion UGD GK

  27. ED EN XN Carbon and the Wall Miox Mutants show a stronger drop in UDP-sugars UGD ED EN XN GK ED EN XN

  28. Summary • Not all that glitters is gold, but well treated you can find much more unexpected stories from NGS data (S.pimp) • NGS does allow us to actually get a handle on genomes and transcritomes we couldn’t dream of before (S.pennPhysalis) • Using the openness of NGS one starts seeing new things and can compare between species

  29. Acknowledgements usadellab.org Thomas Herter LC-MS Zhangjun Fei, Jim Giovannoni, Cornell University RaimundTenhaken, Salzburg University AlisdairFernie, Mark Stitt MPI Golm DetlefWeigel, MPI Tübingen

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