PPT - Bruce Blumberg
Download
Report
Transcript PPT - Bruce Blumberg
BioSci D145 Lecture #1
• Bruce Blumberg ([email protected])
– 4103 Nat Sci 2 - office hours Tu, Th 3:30-5:00 (or by appointment)
– phone 824-8573
• TA – Riann Egusquiza ([email protected])
– 4351 Nat Sci 2– office hours TBA
– Phone 824-6873
• check e-mail and noteboard daily for announcements, etc..
– Please use the course noteboard for discussions of the material
• Updated lectures will be posted on web pages after lecture
– http://blumberg-lab.bio.uci.edu/biod145-w2017
– http://blumberg.bio.uci.edu/biod145-w2017
BioSci D145 lecture 1
page 1
©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.
BioSci D145 lecture 1
page 2
©copyright
Bruce Blumberg 2014. All rights reserved
Class requirements
•
Grading
Midterm
Final exam
Presentation
Term paper
Participation
35%
35%
10%
10%
10% (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 1/18 and 1/26? See Riann.
•
Attendance and participation is important
• Please come to class having read assigned material
•
Final examination will not be cumulative, however, understanding of concepts and
techniques from first part of course is required.
BioSci D145 lecture 1
page 3
©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
BioSci D145 lecture 1
page 4
©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
BioSci D145 lecture 1
page 5
©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.
BioSci D145 lecture 1
page 6
©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
BioSci D145 lecture 1
page 7
©copyright
Bruce Blumberg 2014. All rights reserved
Requirements for the term paper (contd)
• Outline (due Friday January 25)
– 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 later, if necessary
• What is a hypothesis?
– 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 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
BioSci D145 lecture 1
page 8
©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
BioSci D145 lecture 1
page 9
©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
BioSci D145 lecture 1
page 10
©copyright
Bruce Blumberg 2014. All rights reserved
Presentation schedule
•
Week 1 – Dear and Cook, 1993, Jiang et al, 2011 (Riann)
•
Week 2 – (1) Geisler et al., 1999 (2) Redon et al., 2006 (3) Myers et al., 2000
•
Week 3 – (4) Iyer et al., 1999 (5) Venter et al., 2004, (6) Bentley et al., 2008
•
Week 4 – (7) RIKEN, 2005 (8) Kapranov et al., 2007 (9) Lindblad-Toh et al., 2011
•
Week 5 – Midterm, no presentations
•
Week 6 – (10) Horak et al., 2002 (11) Chen et al., 2012 (12) Dewey et al., 2016
•
Week 7 – (13) Seisenberger et al, 2012 (14) Siklenka et al., 2015 (15) Donkin et al.,
2016
•
Week 8 – (16) Gilbert et al., 2014 (17) Liu et al., 2017 (18) Luo et al., 2009
•
Week 9 – (19) Ito et al., 2001 (20) Dejardin and Kingston, 2009 (21) Gavin et al., 2002
•
Week 10 - (22) David et al., 2014 (23) Breton et al., 2016 (24) Rampelli et al., 2015
BioSci D145 lecture 1
page 11
©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
BioSci D145 lecture 1
page 12
©copyright
Bruce Blumberg 2014. All rights reserved
The rise of -omics
• The -omics revolution of science
– http://www.genomicglossaries.com/content/omes.asp
• What does it all mean?
– Transcriptomics – large scale profiling of gene expression
– Proteomics – study of complement of expressed proteins
– Functional genomics – vague term, typically encompasses many others
– Structural genomics – prediction of structure and interactions from
sequence (Rick Lathrop, Pierre Baldi)
– Pharmacogenomics – transcriptional profiling of response to drug
treatment – often looking for genetic basis of differences
– Toxicogenomics – transcriptional profiling of response to toxicants
(often includes pharmacogenomics
• Seeks mechanistic understanding of toxic response
– Metabolomics – analysis of total metabolite pool ("metabolome") to
reveal novel aspects of cellular metabolism and global regulation
– Interactomics – genome wide study of macromolecular interactions,
physical and genetic are included
– Bibliomics – identifying words that occur together in papers
Sadly, usually just abstracts
BioSci D145 lecture 1
page 13
©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?
C- paradox
– i.e., what is the source of the differences?
• Do the number of genes required vary
so much?
unlikely
— (how many “phyla” are represented at
the right?)
Mixed bag
BioSci D145 lecture 1
page 14
©copyright
Bruce Blumberg 2014. All rights reserved
Phylum Chordata
Phylum Arthropoda
Organization and Structure of Genomes (contd)
• How to measure genome complexity?
– Hybridization kinetics
– Shear and melt DNA
– Allow to hybridize and measure doublestranded vs. single-stranded by
spectrophotometry
• Cot½ - 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
BioSci D145 lecture 1
page 15
©copyright
Bruce Blumberg 2014. All rights reserved
Organization and Structure of Genomes (contd)
• Assumptions
– Cot½ 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 ?
BioSci D145 lecture 1
page 16
©copyright
Bruce Blumberg 2014. All rights reserved
Organization and Structure of Genomes (contd)
• Measure eukaryotic DNA
– Multiple components
– Can calculate more than
1 Cot½ 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
BioSci D145 lecture 1
page 17
©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) ?
BioSci D145 lecture 1
page 18
©copyright
Bruce Blumberg 2014. All rights reserved
Organization and Structure of Genomes (contd)
• 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
– Rot½ 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
BioSci D145 lecture 1
page 19
©copyright
Bruce Blumberg 2014. All rights reserved