1. BioSci D145 lecture 1 page 1 © copyright Bruce Blumberg 2014. All rights reserved BioSci D145 Lecture #1 Bruce Blumberg (blumberg@uci.edu) –4103 Nat Sci 2 - office hours Tu, Th 3:30-5:00 (or by appointment) –phone 824-8573 TA – Bassem Shoucri (bshoucri@uci.edu) –4351 Nat Sci 2, 824-6873 – office hours Monday 2-4 PM check e-mail and noteboard daily for announcements, etc.. –Please use the course noteboard for discussions of the material lectures will be posted on web pages after lecture –http://blumberg.bio.uci.edu/biod145-w2015http://blumberg.bio.uci.edu/biod145-w2015 –http://blumberg-lab.bio.uci.edu/biod145-w2015http://blumberg-lab.bio.uci.edu/biod145-w2015

2. BioSci D145 lecture 1 page 2 © copyright Bruce Blumberg 2014. All rights reserved Introductions and Goals Let’s introduce each other - –Name –Major –Favorite thing about UCI –Least favorite thing about UCI On a 3 x 5 card write –a sentence or two describing what you want (or expect) to get out of this class.

3. BioSci D145 lecture 1 page 3 © copyright Bruce Blumberg 2014. All rights reserved Class requirements Grading Midterm35% Final exam35% Presentation10% Term paper10% Participation10% (attendance, class discussion) How are grades determined ? 20 minute presentation and discussion of a journal article is required These will be randomly assigned – Bassem will schedule yours Presentations will be done as teams for most papers (depending on class size) Volunteers for 1/15 and 1/22? Attendance and participation is important Please come to class having read assigned relevant material. Final examination will not be cumulative, however, understanding of concepts and techniques from first part of course is required.

4. BioSci D145 lecture 1 page 4 © copyright Bruce Blumberg 2014. All rights reserved General comments Overall philosophy –This class is about understanding genomic and proteomic (i.e. whole genome) approaches to problems of biological interest Focus will be on research problems –Intended to be informative and cutting edge but also interesting and relevant, even fun. –Office hours are after class but I am always around –Questions are welcome Please stop me and ask questions if something is unclear –I am going to ask you questions Answers get participation credit Memorizing vs. understanding –I am not concerned with your memory –This course is about problem solving – how to address interesting biological problems using modern, whole-genome approaches

5. BioSci D145 lecture 1 page 5 © copyright Bruce Blumberg 2014. All rights reserved General comments Letters of recommendation –If you want a letter from me, I need to know you as more than a student number and grade come to office hours participate in class discussions make your interest in the subject apparent

6. BioSci D145 lecture 1 page 6 © copyright Bruce Blumberg 2014. All rights reserved About the texts Bookstore vs. online? Neither text book is absolutely required –Copies are on reserve at the library –Brown is a very basic text with lots of introductory material that will help to fill in background between BioSci 99 and this class Reading noted in text books are intended to supplement lecture material Main source of material for this class will be lectures and assigned papers.

7. BioSci D145 lecture 1 page 7 © copyright Bruce Blumberg 2014. All rights reserved Requirements for the term paper Goals –Analytical thinking –Improved writing Select a topic related of interest to you and then propose a whole genome approach to address the problem (not necessarily your 199 research!) –Talk with me about your topic (so that I can help you focus it on something do-able and rewarding to you) Write a short paper (5 pages) in the style of a research grant describing how you will attack this problem (examples posted). –Specific aims (1/2 page) Hypotheses to be tested How will you test hypotheses? –Background and significance (1-2 pages) What is known, what remains to be learned why should someone give you money to study this problem? –Research plan (~3 pages) specific experiments to answer the questions posed in specific aims How will you handle expected vs. unexpected results

8. BioSci D145 lecture 1 page 8 © copyright Bruce Blumberg 2014. All rights reserved Requirements for the term paper (contd) Outline (due Thursday January 29) –Title and topic –Introductory paragraph telling why the problem is important –What is the hypothesis that your proposed research will address? –Enumerate 1-3 specific aims in the form of questions that will test aspects of your hypothesis Topic can be changed –A supposition or conjecture put forth to account for known facts; esp. in the sciences, a provisional supposition from which to draw conclusions that shall be in accordance with known facts, and which serves as a starting-point for further investigation by which it may be proved or disproved and the true theory arrived at. What is a hypothesis? What is a theory ? –An analytical framework that explains a set of observations –A comprehensive explanation of an important feature of nature that is supported by facts that have been repeatedly confirmed through observation and experiment

9. BioSci D145 lecture 1 page 9 © copyright Bruce Blumberg 2014. All rights reserved Requirements for the oral presentation Goal – again to get you to think more analytically –Exposure to literature (classic and current) –Learn critical reading –Discuss practical applications of what we are learning Powerpoint (“journal club”) presentation – as a presenter –15-20 minutes with time allowed for discussion (max of 15 – 20 slides) –Frame the problem – what is the big picture question? What was known before they started? What was unknown? Present background (not more than 5 slides) –What are specific questions asked or hypotheses tested Discuss figures –What is the question being asked in each figure or panel? –What experiments did the authors do to answer questions? –Do the data support the conclusions drawn? What did they conclude overall? What could have been improved? –Point out a few papers for further reading (reviews, follow-ups, etc) –Summarize main points and key techniques used at the end

10. BioSci D145 lecture 1 page 10 © copyright Bruce Blumberg 2014. All rights reserved Requirements for the oral presentation (contd) Powerpoint presentation – as a listener –READ THE PAPERS – you are responsible for the material covered –Study the figures What points don’t you understand? –Make notations, ask the speaker to clarify these –Listen to the speaker If presentation is unclear, ask the speaker to elaborate Always feel free to ask questions – we want an open discussion Papers are posted on the web sites listed Logistics –Prepare presentation and either e-mail to me or bring it on a USB drive

11. BioSci D145 lecture 1 page 11 © copyright Bruce Blumberg 2014. All rights reserved Presentation schedule Week 1 papers – Dear and Cook, 1993, Rana et al., 2006 (Bassem) Week 2 papers – (1) Geisler et al., 1999 (2) Redon et al., 2006 (3) Osoegawa et al., 2000 Week 3 papers – (4) Myers et al., 2000 (5) Venter et al., 2004, (6) Margulies et al., 2005 Week 4 papers – (7) Lindblad-Toh et al., 2011 (8) Chen et al., 2012 (9) Iyer et al., 1999 Week 5 – Midterm, no presentations Week 6 papers – (10) RIKEN, 2005 (11) Kapranov et al., 2007 (12) t'Hoen, 2008 Week 7 papers – (13) Thurman et al, 2012 (14) Filon et al., 2010 (15) Seisenberger et al, 2012 Week 8 papers – (16) Boutros et al., 2004 (17) Gilbert et al., 2014 (18) Luo et al., 2009 Week 9 papers – (19) Ito et al., 2001 (20) Dejardin and Kingston, 2009 (21) Gavin et al., 2002 Week 10 papers - (22) Halama et al., 2011 (23) Illig et al., 2010 (24) Scheer et al., 2008

12. BioSci D145 lecture 1 page 12 © copyright Bruce Blumberg 2014. All rights reserved Lecture Outline – Organization and Structure of Genomes Today’s topics –Genome complexity –Implications of split genes for protein diversity –Repetitive elements and gene evolution The big picture for the next 2 lectures –How are genomes similar and different? –How do we find out this information? –Why do we care? What is genomics? Proteomics? –‘omics is the study of a property using “whole genome” approach –Genomics – study of genes and gene function –Proteomics – study of all the proteins

13. BioSci D145 lecture 1 page 13 © copyright Bruce Blumberg 2014 All rights reserved The rise of -omics The -omics revolution of science –http://www.genomicglossaries.com/content/omes.asphttp://www.genomicglossaries.com/content/omes.asp What does it all mean? –Transcriptomics – –Proteomics – –Functional genomics – –Structural genomics – –Pharmacogenomics – –Toxicogenomics – –Metabolomics – –Interactomics – –Bibliomics – large scale profiling of gene expression study of complement of expressed proteins vague term, typically encompasses many others prediction of structure and interactions from sequence (Rick Lathrop, Pierre Baldi) transcriptional profiling of response to drug treatment – often looking for genetic basis of differences transcriptional profiling of response to toxicants (often includes pharmacogenomics Seeks mechanistic understanding of toxic response analysis of total metabolite pool ("metabolome") to reveal novel aspects of cellular metabolism and global regulation genome wide study of macromolecular interactions, physical and genetic are included identifying words that occur together in papers Sadly, usually just abstracts

14. BioSci D145 lecture 1 page 14 © copyright Bruce Blumberg 2014. All rights reserved Organization and Structure of Genomes (contd) Genome size –i.e. total number of DNA bp –Varies widely - WHY? –i.e., what is the source of the differences? Do the number of genes required vary so much? C- paradox —(how many “phyla” are represented at the right?) unlikely Phylum Chordata Phylum Arthropoda Mixed bag

15. BioSci D145 lecture 1 page 15 © copyright Bruce Blumberg 2014. All rights reserved Organization and Structure of Genomes (contd) How to measure genome complexity? –Hybridization kinetics –Shear and melt DNA –Allow to hybridize and measure double- stranded vs. single-stranded by spectrophotometry C o t ½ - measures genome size and complexity –What does a large value (longer to hybridize) mean? k is smaller (rate constant slower) Longer to hybridize – more unique sequences, larger genome –Much of what we knew about genome size and complexity (until advent of genome sequencing) comes from these studies

16. BioSci D145 lecture 1 page 16 © copyright Bruce Blumberg 2014. All rights reserved Organization and Structure of Genomes (contd) Assumptions –C o t ½ measures rate of association of sequences –Simple curves at right suggest simple composition No repetitive sequences What would a more complex genome look like? –Would it be just shifted further to the right? –Or ?

17. BioSci D145 lecture 1 page 17 © copyright Bruce Blumberg 2014. All rights reserved Organization and Structure of Genomes (contd) Measure eukaryotic DNA –Multiple components –Can calculate more than 1 C o t ½ value –Either means starting material is not pure (i.e., multiple types of DNA) –Or means different frequency classes of DNA Highly repetitive Moderately repetitive Unique –Very big surprise

18. BioSci D145 lecture 1 page 18 © copyright Bruce Blumberg 2014. All rights reserved Organization and Structure of Genomes (contd) What can we conclude from great variation in genome size ? Genetic complexity is not directly proportional to genome size! Increase in C is not always accompanied by proportional increase in number of genes —Gene number is controversial —Depends on what is a “gene” —Are we no more complicated than a weed (Arabidopsis) ?

19. BioSci D145 lecture 1 page 19 © copyright Bruce Blumberg 2014. All rights reserved Organization and Structure of Genomes (contd) stopped here What can we learn by hybridizing RNA back to the genomic DNA? –Label RNA and hybridize with excess DNA – measure formation of hybrids over time –R o t ½ analysis shows that RNA does not hybridize with highly repetitive DNA –What does this mean? Most of mRNA is transcribed from non-repetitive DNA Moderately repetitive DNA is transcribed Much of highly repetitive DNA is probably not transcribed into mRNA –Key argument why genome sequencers do not bother with “difficult” regions of repetitive DNA