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Jeff Young, Botanist young@biol.wwu x3638 Office: BI412

Arabidopsis thaliana. Jeff Young, Botanist young@biol.wwu.edu x3638 Office: BI412. Office Hours M WF - 1 - 2 pm …by appointment. Genome-based, molecular study of plant physiology and environmental responses. DNA Sequence Reagent for the 21st Century.

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Jeff Young, Botanist young@biol.wwu x3638 Office: BI412

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  1. Arabidopsis thaliana Jeff Young, Botanistyoung@biol.wwu.edux3638Office: BI412 Office Hours M WF - 1 - 2 pm …by appointment. Genome-based, molecular study of plant physiology and environmental responses.

  2. DNA SequenceReagent for the 21st Century “Biology is in the midst of an intellectual and experimental sea change.... ...essentially the discipline is moving from being largely a data-poor science to becoming a data-rich science. ” Vukmirovic and Tilghman, Nature 405, 820-822 (2000)

  3. Data Poor Era Data Rich Era • Great DATA, but you had to get it yourself, • Collect data from previous day, • Set-up experiment, • Lunch, • Analyze, discuss data, • Repeat… • Free DATA, more than any one person could ever use.

  4. Course Goals • Introduce Genome Scale Research, • Develop and improve skills in reading, analyzing and understanding primary literature, • Enjoy, responsibly, the enormous amount of creativity and genius that is being expended, right now, in the biological sciences.

  5. Class Evaluation

  6. Reading Assignments available online  materials will be from the primary literature, and journal reviews.  All materials may be downloaded (for free) for printing, • however, sometimes figures are best viewed on a monitor.  You are responsible for understanding these papers, including all figures and tables.  You must read each assigned paper prior to lecture (if you want to do OK). Recommended (optional) background and supporting materials will be made available.

  7. Reading Recommendations Read before class, Follow references, • abstracts, if not entire papers are free on line (NCBI: PubMed), • may contain materials and methods, Look up words and concepts that aren’t familiar, Don’t neglect Figures and Tables.

  8. Genomics …the systematic study of genomes that begins with large scale DNA sequencing, • Structural genomics:the study of DNA sequence, chromatin structure, and DNA physical interactions, • Functional genomics: how particular DNA sequences facilitate biological functions, • Bioinformatics: computational discipline that has evolved to handle modern biological data...

  9. Hieter P and Boguski M. Science 278, 601-02. Genomics ... Genomics...is characterized by high throughput or large-scale experimental methodologies combined with statistical and computational analysis of the results. ...the fundamental strategy in a functional genomics approach is to expand the scope of biological investigation from studying single genes or proteins, to studying all genes or proteins at once in a systematic fashion.

  10. DNA mRNA Protein Genome Transcriptome Proteome • Genome... the dynamic complement of heritable genetic material, • Transcriptome... mRNA in a cell, tissue, organ or individual, • complexity increases resulting from transcription control and post-transcription modification, • Proteome... protein in a cell, tissue, organ or individual, • complexity increases due to post-translational modification, protein-protein interactions, etc. Modern research integrates data from all of these sources.

  11. Course Contents • Introduction to Functional Genomics • Sequencing Complex Genomes • Environmental Genome Sequencing • NexGen Technology • Bioinformatics I (Genetics, Mouse Knockouts) Bioinformatics II (Protein Biochemistry) • Reverse Genetics I (RNAi) • Reverse Genetics II (Target Genes) • Transcriptome I (Expression Microarray) • Transcriptome II* (DNA Microarray) • Proteomics I+ (Mass Spectrometry, Y2H) • Student Presentations

  12. Environmental/Ecological Genomics Canine Genomics Malaria Genomics Comparative Genomics NexGen Results Evolutionary Genomics Bioinformatics Personal Genome Projects Sequencing Projects/Results, Mouse Chicken Chimpanzee, etc. Systems Biology Others, with approval. Student Presentations

  13. GENOMICSControversial From the Start Objection #1: Big Biology Is Bad Biology Objection #2: Why Sequence the Junk? Objection #3: Impossible to Do! Besides, who’d want to do it?

  14. "Absurd," "dangerous," and "impossible," scoffed numerous critics, who noted that the technology did not exist to sequence a bacterium, much less a human. And even if the project's starry-eyed proponents could by some miracle pull it off, who would want the complete sequence data anyway?1 In the late 1970s, an entire doctoral thesis might be devoted to reporting the sequence of a gene of several thousand DNA bases.2 1Science 291 (5507), 1182-1188 2Science 287 (5459), 1777-1782 Gene Sequencing Ph.D. Projects 1970s: Thesis Title 1970s: Sequence Gene 1980s: Chapter Title 1980s: Sequence Gene(s) + Mol. Analysis 1990s: Material and Methods entry 1990s: Mol. Analysis + Pre-Genomics 2000s: Reference to Database 2000s: Post-Genom. + System Analysis

  15. Science 291 (5507), 1182-1188 In the 1980s… Sydney Brenner ... facetiously suggested that project leaders parcel out the job to prisoners as punishment--the more heinous the crime, the bigger the chromosome they would have to decipher. Who wanted to do it?

  16. It turns out a lot of people did....with the help of lots of machines. • “This once-ludicrous proposal became one of most hotly contested--and contentious--races in recent scientific history.” • “Although the race has been dominated in the past few years by the acrimonious feud between the public and private teams, tensions go way back…” Science 291 (5507), 1182-1188

  17. Objection #1: Big Biology Is Bad Biology • Researchers feared that a massive sequencing project would siphon precious dollars from investigator-initiated research, destroying the cottage industry culture of biology in the process. • 1988, US Congress agreed to fund the HGP separately. • ...just as bad, the project didn't even amount to hypothesis-driven science at all. Rather, critics charged, it was no more than a big fishing expedition, a mindless factory project that no scientists in their right minds would join. Science 291 (5507), 1182

  18. Hypothesis vs. Discovery • "Discovery science has absolutely revolutionized biology," says Leroy Hood, now director of the Institute for Systems Biology in Seattle, Washington... • ...it's given us new tools for doing hypothesis-driven research," maintains Hood, and these tools help rather than hinder individual investigators." Science 291 (5507), 1182

  19. Objection #2: Why Sequence the Junk? • ~2% of the human genome codes for polypeptides, • why not sequence the 6o million bases that “make something”. • besides, sequencing the rest, often called “junk DNA”, • “...(it) would be a waste of time and money to include the repetitive, hard-to-sequence regions in the genome project.” Science 291 (5507), 1184

  20. Why Sequence the Junk? • Promoters! • control expression. • Telomeres! • prevent the ends of the chromosome from fraying during cell division and help determine a cell's life-span. • Repetitive and “non-protein” coding sequences! • plays a crucial role in X chromosome inactivation, • plays a similar role in the regulation of other genes/genomic regions, • plays a role in genome surveillance/protection, • “noncoding DNA (may) provide "a built-in plasticity that ... if an organism is going to evolve, may be a huge selective advantage.” • Other? Science 291 (5507), 1184

  21. Objection #3: Impossible to Do • State-of-the-art sequencing could produce about 500 bases per 8 hours per rig, working day in and day out, • and the computer technology that came to play such a vital role in the project wasn't even invented yet. • "In the early days, it was believed that a radical new technology would be required to sequence the full human genome, • ...but it didn't turn out that way.” - Stanford University geneticist David Botstein. Science 291 (5507), 1186

  22. Not Revolution, Evolution • radioactive probes --> fluorescent probes, • allowed automated, laser-based detection, • slab gels --> capillary tubes, • automation and computer technology. • "It was definitely evolution...but you can go a long way with evolution.” • ...David Baltimore, president of the California Institute of Technology. Science 291 (5507), 1186

  23. > 206 Gb (Dec. 2007) • > 165,000 organisms Presently

  24. Reference, GOLD

  25. Nature Reviews Genetics Friday: pp. 302 - 307 (figs 1 -3)

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