1. iPlant Genomics in Education Workshop Genome Exploration in Your Classroom

2. Big Data: data sets whose size and complexity is beyond the capabilities of commonly used tools to capture, manage, and process the data within a tolerable time frame. Big Data: constantly moving target currently ranging from a few dozen terabytes to many petabytes of data in single data sets, with different types of data sets potentially deeply intertwined. -Wikipedia (http://en.wikipedia.org/wiki/Big_data)Wikipedia Challenges: the scope and scale of life sciences data continue to grow Working with Big Data

3. Coming into the Genome Age For the first time in the history of science students can work with the same data and tools that are used by researchers. Learning by posing and answering question. Students generate new knowledge.

4. The iPlant Collaborative Vision How can we prepare for science we can’t anticipate?

5. The iPlant Collaborative Vision Enable life science researchers and educators to use and extend iPlant's foundational cyberinfrastructure to understand and ultimately predict the complexity of biological systems and their dynamic nature under various environmental conditions.

6. The iPlant Collaborative What is Cyberinfrastructure? Cyberinfrastructure (CI) is data storage, software, high- performance computing, and people – organized into systems that solve problems of size and scope that would not otherwise be solvable.

7. The iPlant Collaborative What is Cyberinfrastructure? Platforms, tools, datasets Storage and compute Training and support

8. The iPlant Collaborative What problems can iPlant Solve? Crops and model plant systems Animal and livestock Agronomic microbes, insects…

9. The iPlant Collaborative What problems can iPlant Solve? iPlant is built for Data

10. The iPlant Collaborative How was iPlant built?

11. “I had the feeling I have been exposed to many bioinformatics tools but I would be unable to use any of them on my own.” The limitations of any training workshop

12. 3. Keep asking questions If iPlant can, we’ll help show you how… If iPlant can’t we’ll find the path that gets you what you need Don’t hesitate to ask “Can iPlant do this?” Keep asking at ask.iplantcollabortive.org

13. Bringing Genomics into the Classroom Visualization of the Pectobacterium atrosepticum genome http://www.scri.ac.uk/research/pp/plantpathogengenomics/pathogenbioinformatics

14. Bringing Genomics into the Classroom “Essentially, all models are wrong, but some are useful” – George E.P. Box From This…

15. 1866 – Mendel publishes work on inheritance 1869 – DNA discovered 1915 – Hunt Morgan describes linkage and recombination 1953 – Structure of DNA described 1956 – Human chromosome number determined 1968 – First gene mapped to autosome 1977 – Dideoxy sequencing 1983 – PCR 1986 – Human Genome Project proposed Bringing Genomics into the Classroom

16. 1993 – First MicroRNAs described 2003 – First ‘Gold Standard’ human genome sequence 2005 – First draft of human haplotype map (HapMap) 2007 – ENCODE project Timeline: Welcome Trust (http://www.wellcome.ac.uk/stellent/groups/corporatesite/@policy_communications/documents/web_document/wtx063807.pdf) Bringing Genomics into the Classroom

17. 1973 Sharp, Sambrook, Sugden Gel Electrophoresis Chamber, $250 1958 Matt Meselson & Ultracentrifuge, $500,000 The Egalitarian Gene Agarose Gel Electrophoresis, 1973

18. The Egalitarian Genome Next Generation Sequencing, 2005 Bacterial coloniesPCR colonies (clusters, features) Hundreds of millions of…

19. To This… Bringing Genomics into the Classroom

20. ResearchEducation For the first time in the history of biology students can work with the same data at the same time and with the same tools as research scientists. Educational Challenge Context of scientific discovery

21. Walk or…

22. …ride an educational Discovery Environment

23. iPlant Genomics in Education Workshop Major Workshop Concepts: Biology is becoming a “Data Unlimited” science. Genomes are dynamic. Genomes are more than just protein coding genes. DNA sequence is information. Gene annotation adds “meaning” to DNA sequence. Biological concepts like “genes” and “species” continually evolving. DNA barcoding bridges molecular genetics, evolution, ecology.

24. The Problem of Big Data in Biology The abundance of biological data generated by high-throughput sequencing creates challenges, as well as opportunities: How do scientists share their data and make it publically available? How do scientists extract maximum value from the datasets they generate? How can students and educators (who will need to come to grips with data-intensive biology) be brought into the fold?

25. Majority of genome is transcribed ~50% transposons ~25% protein coding genes/1.3% exons ~23,700 protein coding genes ~160,000 transcripts Average Gene ~ 36,000 bp 7 exons @ ~ 300 bp 6 introns @ ~5,700 bp 7 alternatively spliced products (95% of genes) RefSeq: ~34,600 “reference sequence” genes (includes pseudogenes, known RNA genes) Bringing Genomics into the Classroom

26. Using Plants to Explore Genomics

27. There are a large number of plant genomes available for analysis.

28. Using Plants to Explore Genomics The “weirdness” of plant genomes on your dinner plate Triticum aestivum: allohexaploid Brachypodium Sorghum Oryza Brachypodium 12345 1 2345 1039784256 1 3615728 111294

29. 50-70 46 28 25 13 14 9 150-300 Monocots Dicots Time (million years) Present 204060 Oryza (rice) Avena (oats) Hordeum (barley) Triticum (wheat) Setaria (foxtail millet) Pennisetum (pearl millet) Sorghum Zea (maize) Arabidopsis Brachypodium Glycine max (soy) 2,500 Mb 750 Mb 20,000 Mb 270 Mb 430 Mb 145 Mb 1,115 Mb ?? Mb 5,200 Mb >20,000 Mb ?? Mb - Genome duplication event Using Plants to Explore Genomics

30. Using DNA Subway to Explore Genomics