1. Accelerating biology with bioinformatics: collaboration with lab scientists Lewitter, RECOMB BE, July 2011

2. Bioinformatics Definitions “An interdisciplinary field involving biology, computer science, mathematics, and statistics to analyze biological sequence data, genome content, and arrangement, and to predict the function and structure of macromolecules.” David Mount Lewitter, RECOMB BE, July 2011

3. Bioinformatics Definitions “An interdisciplinary field involving biology, computer science, mathematics, and statistics to analyze biological sequence data, genome content, and arrangement, and to predict the function and structure of macromolecules.” David Mount “The use of computational methods to make biological discoveries.” Fran Lewitter Lewitter, RECOMB BE, July 2011

4. Bioinformatics at Whitehead Bioinformatics for High School Students Other Educational Activities Lewitter, RECOMB BE, July 2011

5. Bioinformatics at Whitehead Part 1 Lewitter, RECOMB BE, July 2011

8. Projects we work on Lewitter, RECOMB BE, July 2011

9. http://jura.wi.mit.edu/bio Lewitter, RECOMB BE, July 2011

10. Who we train High School Computer Science students (6) High School Computer Science students (6) High School Computer Science teacher sabbatical (1) High School Computer Science teacher sabbatical (1) Undergrads – Biology, Math (3) Undergrads – Biology, Math (3) Bioinformatics Masters students (3) Bioinformatics Masters students (3) Biology grad students (100s) Biology grad students (100s) Biology postdocs (100s) Biology postdocs (100s) Lewitter, RECOMB BE, July 2011

11. Hot Topics Intro to R Statistics Querying Biological Databases with SQL Integrative Genomics Viewer (IGV) Mapping Next Generation Sequence Reads Analysis of ChIP-seq experiments RNA-Seq Methods and Applications Analysis of next-gen seq experiments with Galaxy Juggling Genome Coordinates Beginners class on creating figures in R http://iona.wi.mit.edu/bio/education/hottopics.php Lewitter, RECOMB BE, July 2011

13. http://jura.wi.mit.edu/bio/education Lewitter, RECOMB BE, July 2011

16. Bioinformatics for High School Students Part 2 Lewitter, RECOMB BE, July 2011

17. Exploring small regulatory RNAs Spring Lecture Series for High School Students April 21-23, 2009 Lewitter, RECOMB BE, July 2011

18. Bioinformatics The application of computational methods to the field of molecular biology We work on many different projects with many lab scientists Trained in biology and computation Sometimes called “computational biology” Lewitter, RECOMB BE, July 2011

19. BaRC website – http://jura.wi.mit.edu Lewitter, RECOMB BE, July 2011

20. Central dogma The flow of genetic information DNA RNA Protein mRNA tRNA rRNA transcriptiontranslation Lewitter, RECOMB BE, July 2011

22. History of RNA Late 1800’s - 2nd kind of nucleic acid not in the nucleus (rRNA) 1920’s - sugar for DNA vs RNA 1958 - tRNA (Hoagland) 1960’s – mRNA Last 15 years – miRNA, ncRNAs, snoRNA, snRNA, siRNA, piwiRNA, stRNA! Lewitter, RECOMB BE, July 2011

23. New Roles of RNA miRNA - tiny 21–24-nucleotide RNAs; reduce levels of specific mRNA and proteins (regulate elsewhere; many-to-many relationships of miRNAs to targets) miRNA and disease – cancer (bladder, breast, cervical, colorectal, lymphonas, leukemias, etc), asthma, alcoholic liver disease, autism, cardiomyopathy, coronary artery disease, muscular dystrophy, frontotemporal dementia, hypertension, schizophrenia, thalassemia, ulcerative colitis, etc. Lewitter, RECOMB BE, July 2011

24. New York Times – 11/12/08 NucleusCytoplasm Precursor micro-RNAmicro-RNARNAi blocks translation 3’ UTR Lewitter, RECOMB BE, July 2011

25. UTR Exon1 Exon2 Exon3 UTR mRNA5’ 3’ Exon1 Exon2 Exon3 Protein Target …UGCAUUCCAGG… mRNA Target Base pairing …ACGUAAGGUCC… Seed match Lewitter, RECOMB BE, July 2011

26. Human miR-16 targets in SMURF1 gene Alignment of DNA sequence in many organisms Human Chimp Rhesus Bushbaby Treeshrew Mouse Rat Guinea Pig Rabbit Shrew Hedgehog Dog Cat Horse Cow Armadillo Elephant Tenrec Opposum Platypus Lizard Chicken Frog Lewitter, RECOMB BE, July 2011

27. Summary of miRNAs MicroRNAs are small, recently discovered genes with RNA (but not protein) products MicroRNAs can base-pair to the end of mRNAs and target them for destruction or reduce protein synthesis A single miRNA can target lots of genes A single protein-coding gene can be regulated by lots of miRNAs Conservation of the miRNA binding site across different species can help identify gene targets Some diseases appear to be influenced by wrong levels of functional miRNAs High percentage of our genes are controlled by miRNAs Lewitter, RECOMB BE, July 2011

28. Today’s Exercise http://jura.wi.mit.edu/bio/education/HS2009 1.Conservation of miRNA genes 2.Conservation of miRNA targets 3.miRNAs and disease! Lewitter, RECOMB BE, July 2011

35. Summary of Exercise One miRNA can target multiple genes One gene can be controlled by multiple miRNAs miRNA binding sites are conserved by evolution. Lewitter, RECOMB BE, July 2011

36. Other Educational Activities Part 3 Lewitter, RECOMB BE, July 2011

37. PLoS Computational Biology http://www.ploscompbiol.org/ Lewitter, RECOMB BE, July 2011

38. PLoS Computational Biology Education Section –Tutorials –Quick Guides –Reviews Lewitter, RECOMB BE, July 2011

39. PLoS Computational Biology Lewitter, RECOMB BE, July 2011

40. PLoS: Roots of Bioinformatics Lewitter, RECOMB BE, July 2011

41. ISCB Education Committee Currently ~50 people, ~20 active members Meet annually at ISMB Email list and discussions during the year Activities –Accreditation (Task Force) –Bioinformatics in secondary school –Improve web information –Curriculum Initiative –Educating biologists (at what meetings?) –WEB11 Lewitter, RECOMB BE, July 2011

42. http://www.iscb.org Lewitter, RECOMB BE, July 2011

43. How far we’ve come! Closing slide Lewitter, RECOMB BE, July 2011