1. Bruce Blumberg (blumberg@uci.edu)
BioSci D145 Lecture #3
Bruce Blumberg
4103 Nat Sci 2 - office hours Tu, Th 3:30-5:00 (or by appointment)
phone
TA – Riann Egusquiza
4351 Nat Sci 2– office hours M 1:45-3:45
Phone
check 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
Don’t forget to discuss term paper topics with me
BioSci D145 lecture 1 page 1 ©copyright Bruce Blumberg All rights reserved

2. Why should any funding agency give you money to pursue this research?
Term paper outline
Title of your proposal
A paragraph introducing your topic and explaining why it is important; i.e., what impact will the knowledge gained have.
Why should any funding agency give you money to pursue this research?
NIH now requires a statement of human health relevance for all grant applications
NSF wants to know what is the intellectual merit of your proposed research and what broader impacts of your proposed research
Present your 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.
Enumerate 2-3 specific aims in the form of questions that test your hypothesis
At least one of these aims needs to have a strong “whole genome” component
This is not a review article – propose something new.
BioSci D145 lecture 4 page 2 ©copyright Bruce Blumberg All rights reserved

3. Genome mapping (contd)
How are maps made?
What do we map these days?
Restriction digestion and ordering of fragments to build contigs
Fingerprinting
Location of marker sequences onto larger chunks
Hybridization of markers to larger chunks
Calculation of recombination frequencies between loci
BACs are most common target for mapping of new genomes
Radiation hybrid panels still in wide use
Goal is always to map markers onto ordered large fragments and infer location of genes relative to each other.
HAPPY mapping becoming widely used again
BioSci D145 lecture 2 page 3 ©copyright Bruce Blumberg All rights reserved

4. Genome mapping (contd)
Useful markers
STS – sequence tagged sites
Short randomly acquired sequences
PCRing sequences, then prove by hybridization that only a single sequence is amplified/genome
VERY tedious and slow
validated ones mapped back to RH panels
Orders sequences on large chunks of DNA
STC – sequence tagged connectors
Array BAC libraries to 15x coverage of genome
Sequence BAC ends
Combine with genomic maps and fingerprints to link clones
Average about 1 tag/5 kb
Most useful preparatory to sequencing
BioSci D145 lecture 2 page 4 ©copyright Bruce Blumberg All rights reserved

5. Genome mapping (contd)
Useful markers (contd)
ESTs – expressed sequence tags
randomly acquired cDNA sequences
Lots of value in ESTs
Info about diversity of genes expressed
Quick way to get expressed genes
Better than STS because ESTs are expressed genes
Can be mapped to
chromosomes by FISH
RH panels
BAC contigs
Polymorphic STS – STS with variable lengths
Often due to microsatellite differences
Useful for determining relationships
Also widely used for forensic analysis
OJ, Kobe, etc
BioSci D145 lecture 2 page 5 ©copyright Bruce Blumberg All rights reserved

6. Genome mapping (contd)
Useful markers (contd)
SNPs – single nucleotide polymorphisms
Extraordinarily useful - ~1/1000 bp in humans
Much of the differences among us are in SNPs
SNPs that change restriction sites cause RFLPs (restriction fragment length polymorphisms
Detected in various ways
Hybridization to high density arrays (Affymetrix)
Sequencing
Denaturing electrophoresis or HPLC
Invasive cleavage
Tony Long in E&E Biology has method for ligation mediated SNP detection that they use for evolutionary analyses
BioSci D145 lecture 2 page 6 ©copyright Bruce Blumberg All rights reserved

7. Genome mapping (contd)
Useful markers (contd)
RAPDs – randomly amplified polymorphic DNA
Amplify genomic DNA with short, arbitrary primers
Some fraction will amplify fragments that differ among individuals
These can be mapped like STS
Issues with PCR amplification
Benefit – no sequence information required for target
AFLPs – amplified fragment length polymorphisms
Cut with enzymes (6 and 4 cutter) that yield a variety of small fragments ( < 1 kb)
Ligate sequences to ends and amplify by PCR
Generates a fingerprint
Controlled by how frequently enzymes cut
Often correspond to unique regions of genome
Can be mapped
Benefit – no sequence required.
BioSci D145 lecture 2 page 7 ©copyright Bruce Blumberg All rights reserved

8. Genome mapping (contd)
Mapping by walking/hybridization
Start with a seed clone then walk along the chromosome
Takes a LOOONNNNGGG time
Benefit – can easily jump repetitive sequences
BioSci D145 lecture 2 page 8 ©copyright Bruce Blumberg All rights reserved

9. Genome mapping (contd)
Mapping by hybridization
Array library – pick a “seed clone”
See where it hybridizes, pick new seed and repeat
Product
BioSci D145 lecture 2 page 9 ©copyright Bruce Blumberg All rights reserved

10. Genome mapping (contd) Restriction mapping of large insert clones
Mapping by restriction digest fingerprinting
Order clones by comparing patterns from restriction enzyme digestion
BioSci D145 lecture 2 page 10 ©copyright Bruce Blumberg All rights reserved

11. Genome mapping (contd)
FISH - Fluorescent in situ hybridization – can detect chromosomes or genes
Can localize probes to chromosomes and
Relationship of markers to each other
Requires much knowledge of genome being mapped (i.e., not good for new genomes)
Chromosome painting marker detection
BioSci D145 lecture 2 page 11 ©copyright Bruce Blumberg All rights reserved

12. Genome mapping (contd)
Radiation hybrid mapping
Old but very useful technique (Geisler paper)
Lethally irradiate cells with X-rays
Fuse with cells of another species, e.g., blast human cells then fuse with hamster cells
Chunks of human DNA will remain in mouse cells
Expand colonies of cells to get a collection of cell lines, each containing a single chunk of human cDNA
Collection = RH panel
Now map markers onto these RH panels
Can identify which of any type of markers map together
STS, EST (very commonly used), etc
Can then map others by linkage to the ones you have mapped
Compare RH panel with other maps
Utility – great for cloning gaps in other maps
HAPPY Mapping –
PCR-based method – see Riann’s presentation
BioSci D145 lecture 3 page 12 ©copyright Bruce Blumberg All rights reserved

13. Genome mapping (contd)
How should maps be made with current knowledge?
All methods have strengths and weaknesses – must integrate data for useful map
e.g, RH panel, BAC maps, STS, ESTs
Size and complexity of genome is important
More complex genomes require more markers and time mapping
Breakpoints and markers are mapped relative to each other
Maps need to be defined by markers (cities, lakes, roads in analogy)
Key part of making a finely detailed map is construction of genomic libraries and cell lines for common use
Efforts by many groups increase resolution and utility of maps
Current strategies
BAC end sequencing
Whole genome shotgun sequencing
EST sequencing
HAPPY mapping
Mapping of above to RH panels
Fancier techniques (Dovetail, Chicago reads, Hi-C assemblies)
BioSci D145 lecture 3 page 13 ©copyright Bruce Blumberg All rights reserved

14. DNA sequencing = determining the nucleotide sequence of DNA
DNA sequence analysis
DNA sequencing = determining the nucleotide sequence of DNA
Originally two main methods
shared Nobel prize in 1980
Chemical cleavage – Maxam and Gilbert
Enzymatic sequencing (based on polymerization reaction)
Nobel Prize in Chemistry 1980
Walter Gilbert (Harvard) & Frederick Sanger (MRC Labs)
(Sanger also won Nobel in 1958 for protein sequencing)
BioSci D145 lecture 4 page 14 ©copyright Bruce Blumberg All rights reserved

15. One of the first reasonable sequencing methods
DNA sequence analysis
Maxam and Gilbert
One of the first reasonable sequencing methods
Very popular in late 70s and early 80s
VERY TEDIOUS!!
Totally superceded by dideoxy sequencing now
BioSci D145 lecture 4 page 15 ©copyright Bruce Blumberg All rights reserved

16. DNA sequence analysis (contd)
Dideoxy sequencing – Sanger 1977
Virtually all routine sequencing is done this way now
Requires modified nucleotide
2’3’-dideoxy dNTP
DNA polymerase incorporates the ddNTP and chain elongation terminates
Original method used 4 separate elongation reactions
Products separated by denaturing PAGE and visualized by autoradiography
BioSci D145 lecture 4 page 16 ©copyright Bruce Blumberg All rights reserved

17. DNA sequence analysis (contd)
Dideoxy sequencing (contd) – Sanger 1977
Dideoxy NTPs present at ~1% of [dNTP]
Each reaction has identified end
In principle, all possible chain lengths are represented
varies by [dNTPs], [ddNTPs], [primer] and [template] and ratios
BioSci D145 lecture 4 page 17 ©copyright Bruce Blumberg All rights reserved

18. DNA sequence analysis (contd)
A C G T A C G T
A C G T
BioSci D145 lecture 4 page 18 ©copyright Bruce Blumberg All rights reserved

19. Automated DNA sequence analysis
How to improve throughput of sequencing?
Incorporate fluorescent ddNTPs, separate products by PAGE
Base calling and lane calling issues
Key advance was capillary sequencers
Separate DNA in a thin capillary instead of gel
Very accurate, no tracking errors, much more automation friendly
Trace files (dye signals) are analyzed and bases called to create chromatograms.
Chromatograms from opposite strands are reconciled with software to create double-stranded sequence data.
BioSci D145 lecture 4 page 19 ©copyright Bruce Blumberg All rights reserved

20. Automated DNA sequence analysis
Capillaries vs gels
Capillaries much faster – higher field strength possible
Fully automated = higher throughput
BioSci D145 lecture 4 page 20 ©copyright Bruce Blumberg All rights reserved

21. Applied Biosystems PRISM 377 (Gel, 34-96 lanes)
(Capillary, 96 capillaries)
BioSci D145 lecture 4 page 21 ©copyright Bruce Blumberg All rights reserved

22. PCR – polymerase chain reaction amplification of DNA
PCR is most routinely used method to amplify DNA
Exponential amplification of DNA by polymerases – Saiki et al, 1985
2n fold amplification, n= # cycles
35 cycles = 235 = 3.4 x 1010 fold
Originally used DNA polymerase I
Needed to add fresh enzyme at every cycle because heat denaturation of template killed the enzyme
Not widely used – too painful to do manually
Nobel Prize to Kary Mullis in 1993 for deciding to use Taq DNA polymerase for PCR
He was middle author on paper!
BioSci D145 lecture 4 page 22 ©copyright Bruce Blumberg All rights reserved

23. PCR – polymerase chain reaction amplification of DNA (contd)
Hot water bacteria:
Thermus aquaticus
Taq DNA polymerase
Life at High Temperatures by Thomas D. Brock
Biotechnology in Yellowstone
© 1994 Yellowstone Association for Natural Science
BioSci D145 lecture 4 page 23 ©copyright Bruce Blumberg All rights reserved

24. Cycle sequencing – fusion of PCR and fluorescent ddNTP sequencing
Combine PCR amplification with dideoxy sequencing – cycle sequencing
Linear amplification of template in the presence of fluorescent ddNTPs
When nucleotides are used up reaction is over
Separate on capillary electrophoresis instrument
Advantages
Fast, single tube reaction
Works with small amounts of starting material
Disadvantages
Still need to prepare high quality template to sequence
Cost and time
Many sequencing centers spend time, $$ on template prep
Automation requirements
BioSci D145 lecture 4 page 24 ©copyright Bruce Blumberg All rights reserved

25. Isothermal amplification – the solution to template preparation
How to make template preparation faster, easier and more reliable?
Eliminate automation requirement, amplify starting material in some other way
Φ29 DNA polymerase (aka TempliPhi)
Enzyme has high processivity and strand displacement activity
Isothermal reaction produces huge quantities of DNA from tiny amount of input
More efficient than PCR (no temp change, no machine, no cleanup)
BioSci D145 lecture 4 page 25 ©copyright Bruce Blumberg All rights reserved

26. Modern DNA sequence analysis
Cycle sequencing
Virtually all routine DNA sequencing today is done by cycle sequencing with fluorescent ddNTPs
ABI Big Dye chemistry
Template preparation still tedious for small scale
TempliPHi used in genome centers (no need for most automation)
Capillary sequencers predominant form of technology in use
But, next generation sequencing has already rapidly displaced old technology in genome centers.
454 sequencing (Roche)
Solexa (Illumina) *dominant player at the moment*
SoLID (Applied Biosystems) (dead technology due to poor support)
3rd generation sequencing (individual DNA molecule) now available
e.g., Pacific Biosciences (sequence reads of 1,000-10K bases)
Oxford Biosciences Nanopore (read length 5 kb—200 kb)
BioSci D145 lecture 4 page 26 ©copyright Bruce Blumberg All rights reserved

27. Landmarks in DNA sequencing
DNA sequence analysis
Landmarks in DNA sequencing
Sanger, Nicklen and Coulson. Sequencing with chain terminating inhibitors. Proc. Natl. Acad. Sci. 74, (1977).
Sanger, F. et al. The nucleotide sequence of bacteriophage ΦX174. J Mol Biol 125, (1978).
Sutcliffe, J. G. Complete nucleotide sequence of the Escherichia coli plasmid pBR322. Cold Spring Harb Symp Quant Biol 43, (1979).
Sanger et al., Nucleotide sequence of bacteriophage lambda DNA. J Mol Biol 162, (1982).
Messing, J., Crea, R. & Seeburg, P. H. A system for shotgun DNA sequencing. Nucl.Acids Res 9, (1981).
Anderson, S. et al. Sequence and organization of the human mitochondrial genome. Nature 290, (1981).
Deininger, P. L. Random subcloning of sonicated DNA: application to shotgun DNA sequence analysis. Anal Biochem 129, (1983).
Baer et al. DNA sequence and expression of the B95-8 Epstein-Barr virus genome. Nature 310, (1984). (189 kb)
Innis et al. DNA sequencing with Taq DNA polymerase and direct sequencing of PCR-amplified DNA Proc. Natl. Acad. Sci. 85, (1988)
BioSci D145 lecture 4 page 27 ©copyright Bruce Blumberg All rights reserved

28. DNA sequence analysis (contd)
Landmarks in DNA sequencing (contd).
Haemophilus influenzae (1.83 Mb)
Mycoplasma genitalium (0.58 Mb)
Saccharomyces cerevisiae genome (13 Mb)
Methanococcus jannaschii (1.66 Mb)
Escherichia coli (4.6 Mb)
Bacillus subtilis (4.2 Mb)
Borrelia burgdorferi (1.44 Mb)
Archaeoglobus fulgidus (2.18 Mb)
Helicobacter pylori (1.66 Mb)
first bacterium sequenced, human pathogen
smallest free living organism
first Archaebacterium
Lyme disease
first sulfur metabolizing bacterium
first bacterium proven to cause cancer
BioSci D145 lecture 4 page 28 ©copyright Bruce Blumberg All rights reserved

29. DNA sequence analysis (contd)
Landmarks in DNA sequencing (contd)
Treponema pallidum (1.14 Mb)
Caenorhabditis elegans genome (97 Mb)
Deinococcus radiodurans (3.28 Mb)
Drosophila melanogaster (120 Mb)
Arabidopsis thaliana (115 Mb)
Escherichia coli O157:H7 (4.1 Mb)
2001 – draft Human “genome”
2002 – mouse genome
2002 – Ciona intestinalis
2003 – “complete “human genome
2004 – rat genome
2006 – Human “genome” complete sequence of all chromosomes
Many more genomes underway, check JGI, Sanger and other web sites
resistant to radiation, starvation, ox stress
Pathogenic variant of E. coli
Primitive chordate
BioSci D145 lecture 4 page 29 ©copyright Bruce Blumberg All rights reserved

30. Complete DNA sequence (all nts both strands, no gaps)
DNA Sequence analysis
Complete DNA sequence (all nts both strands, no gaps)
complete sequence is desirable but takes time
how long depends on size and strategy employed
which strategy to use depends on various factors
how large is the clone?
cDNA
genomic
How fast is sequence required?
sequencing strategies
primer walking
cloning and sequencing of restriction fragments
progressive deletions
Bidirectional, unidirectional
Shotgun sequencing
whole genome
with mapping
map first (C. elegans)
map as you go (many)
BioSci D145 lecture 4 page 30 ©copyright Bruce Blumberg All rights reserved

31. DNA Sequence analysis (contd)
Primer walking - walk from the ends with oligonucleotides
sequence, back up ~50 nt from end, make a primer and continue
Why back up?
Need to see overlap to be sure about sequence you are reading
BioSci D145 lecture 4 page 31 ©copyright Bruce Blumberg All rights reserved

32. DNA Sequence analysis (contd)
Primer walking (contd)
advantages
very simple
no possibility to lose bits of DNA
restriction mapping
deletion methods
no restriction map needed
best choice for short DNA
disadvantages
slowest method
about a week between sequencing runs
oligos are not free (and not reusable)
not feasible for large sequences
applications
cDNA sequencing when time is not critical
targeted sequencing
verification
closing gaps in sequences
BioSci D145 lecture 4 page 32 ©copyright Bruce Blumberg All rights reserved

33. DNA Sequence analysis (contd)
Cloning and sequencing of restriction fragments
once the most popular method
make a restriction map, subclone fragments
sequence
advantages
straightforward
directed approach
can go quickly
cloned fragments often useful otherwise
RNase protection, nuclease mapping, in situ hybridization
disadvantages
possible to lose small fragments
must run high quality analytical gels
depends on quality of restriction map
mistaken mapping -> wrong sequence
restriction site availability
applications
sequencing small cDNAs
isolating regions to close gaps
BioSci D145 lecture 4 page 33 ©copyright Bruce Blumberg All rights reserved

34. DNA Sequence analysis (contd)
nested deletion strategies - sequential deletions from one end of the clone
cut, close and sequence
Approach
make restriction map
use enzymes that cut in polylinker and insert
Religate, sequence from end with restriction site
repeat until finished, filling in gaps with oligos
advantages
Fast, simple, efficient
disadvantages
limited by restriction site availability in vector and insert
need to make a restriction map
BioSci D145 lecture 4 page 34 ©copyright Bruce Blumberg All rights reserved

35. DNA Sequence analysis (contd)
nested deletion strategies (contd)
Exonuclease III-mediated deletion
cut with polylinker enzyme
protect ends -
3’ overhang
phosphorothioate
cut with enzyme between first cut and the insert
can’t leave 3’ overhang
timed digestions with Exonuclease III
stop reactions, blunt ends
ligate and size select recombinants
sequence
advantages
unidirectional
processivity of enzyme gives nested deletions
BioSci D145 lecture 4 page 35 ©copyright Bruce Blumberg All rights reserved

36. DNA Sequence analysis (contd)
Nested deletion strategies
Exonuclease III-mediated deletion (contd)
disadvantages
need two unique restriction sites flanking insert on each side
best used successively to get > 10kb total deletions
may not get complete overlaps of sequences
fill in with restriction fragments or oligos
applications
method of choice for moderate size sequencing projects
cDNAs
genomic clones
good for closing larger gaps
Small-scale sequence analysis – how is it practiced today?
Primer walking
ExoIII-mediated deletion with primer walking
BioSci D145 lecture 4 page 36 ©copyright Bruce Blumberg All rights reserved

37. Genome sizes for most eukaryotes are large (108-109 bp)
Genome sequencing
The problem
Genome sizes for most eukaryotes are large ( bp)
High quality sequences only about bp per run
The solution
Break genome into lots of bits and sequence them all
Reassemble with computer
The benefit
Rapid increase in information about genome size, gene comparisons, etc
The cost
3 x 109 bp(human haploid genome) ÷ 600 bp/reaction = 5 x 106 reactions for 1x coverage!
Need both strands (x2), need overlaps and need to be sure of sequences
~ reactions/runs required for a human-sized genome
About $1-2 per reaction these days, ~$8 commercially.
BioSci D145 lecture 4 page 37 ©copyright Bruce Blumberg All rights reserved

38. Genome sequencing (contd)
Shotgun sequencing NOT invented by Craig Venter
Messing 1981 first description of shotgun sequencing
Sanger lab developed current methods in 1983
approach
blast genome into small chunks
clone these chunks
3-5 kb, 8 kb plasmid
40 kb fosmid jump repetitive sequences
sequence + assemble by computer
A priori difficulties
how to get nice uniform distribution
how to assemble fragments
what to do about repeats?
How to minimize sequence redundancy?
BioSci D145 lecture 4 page 38 ©copyright Bruce Blumberg All rights reserved

39. Genome sequencing(contd)
BioSci D145 lecture 4 page 39 ©copyright Bruce Blumberg All rights reserved

40. Genome sequencing(contd)
BioSci D145 lecture 4 page 40 ©copyright Bruce Blumberg All rights reserved

41. Genome sequencing (contd)
Shotgun sequencing (contd)
How to minimize sequence redundancy?
Best way to minimize redundancy is map before you start
C. elegans was done this way - when the sequence was finished, it was FINISHED
mapping took almost 10 years
mapping much too tedious and nonprofitable for Celera
who cares about redundancy, let’s sequence and make $$
There is scientific value to draft genomes, too.
why does redundancy matter?
Finished sequence today costs about $0.50/base
Note that 10x, % coverage leaves at least 150 kb unsequenced
BioSci D145 lecture 4 page 41 ©copyright Bruce Blumberg All rights reserved

42. Other sequencing technologies
Sequencing by hybridization
Construct a high-density microchip with all possible combinations of a short oligonucleotide
Up to 25-mers
By photolithography
Synthesized on chip directly
Label and hybridize fragment to be sequenced
Wash stringently
Read fluorescent spots
Reconstruct sequence by computer
BioSci D145 lecture 5 page 42 ©copyright Bruce Blumberg All rights reserved

43. Other sequencing technologies (contd) stoopped here)
Sequencing by hybridization rarely used for de novo sequencing
Extremely fast and useful to sequence something you already know the sequence of but want to identify mutation - resequencing
Disease causing changes
e.g in mitochondrial DNA
SNP discovery
Works best for examining sequence of <10 kb
BioSci D145 lecture 5 page 43 ©copyright Bruce Blumberg All rights reserved

44. Other sequencing technologies (contd)
SNP discovery
Photo shows mitochondrial chip
Right panel shows pairs of normal (top) vs disease (bottom) (Leber’s Hereditary Optic Neuropathy)
Top 3 disease mutations
Bottom control with no change
BioSci D145 lecture 5 page 44 ©copyright Bruce Blumberg All rights reserved

45. Other sequencing technologies – Next Generation sequencing
2nd generation = high throughput, short sequences
3rd generation = single molecule sequencing
Small number of sequence templates (thousands) but very long reads (~105 bp)
What is the immediate implication of this technology for genome assembly?
Key review is Metzger, M.L. (2010) Sequencing technologies — the next generation, Nature Reviews Genetics 11,
We should now be able to completely sequence large insert clones directly and avoid fragmentation by repetitive elements!
BioSci D145 lecture 5 page 45 ©copyright Bruce Blumberg All rights reserved

46. 3rd generation