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Genome Sequencing:
Technology and
Strategies
Chuong Huynh
NIH/NLM/NCBI
[email protected]
Acknowledgement: Daniel Lawson (Sanger Institute) and Jane Carlton (TIGR)
Bioinformatics Flow Chart
1a. Sequencing
1b. Analysis of
nucleic acid seq.
2. Analysis of protein seq.
3. Molecular structure prediction
6. Gene & Protein expression data
7. Drug screening
Ab initio drug design OR
Drug compound screening in
database of molecules
4. molecular interaction
8. Genetic variability
5. Metabolic and regulatory networks
How to sequence a genome
• development of sequencing strategy and source of funding
• procurement of DNA and initial library construction
• test sequencing
• large-scale random sequencing of small (2-3 kb), medium
(10 kb)
and large (>50 kb) libraries
• analysis of raw sequence data by: BLAST, RepeatFinder etc
• release of genome data onto sequencing center website
• at 8-10 X coverage, random stops
• closure of sequence gaps and physical gaps
• comparison to physical map
• gene model prediction
• final gene model annotation
• release of data to GenBank and publication
Full shotgun sequencing
Genomic DNA
Marker1
Marker2
large insert library (20 - 500 kb)
Minimal
tiling path
shotgun library: small (2-3 kb) and medium (10 kb)
Sequencing
(8-10 X)
Assembly
scaffold
contig
Gap closure
gene prediction, annotation and analysis
Partial shotgun sequencing
Genomic
DNA
shotgun library: small (2-3 kb) and medium (10 kb)
Sequencing
(5X)
Assembly
contig
scaffold
Analysis
Genome sequencing terms
Raw sequence: unassembled sequence reads produced from sequencing of inserts from
individual recombinant clones of a genomic DNA library.
Finished sequence: complete sequence of a genome with no gaps and an accuracy of > 99.9%.
Genome coverage: average number of times a nucleotide is represented by a high-quality base
in random raw sequence.
Full shotgun coverage: genome coverage in random raw sequence required to produce finished
sequence, usually 8-10 fold (‘8-10X’).
Partial shotgun coverage: typically 3-6X random coverage of a genome which produces
sequence data of sufficient quality to enable gene identification but which is not sufficient to
produce a finished genome sequence
Paired reads: sequence reads determined from both ends of a cloned insert in a recombinant
clone.
Contig: contiguous DNA sequence produced from joining overlapping raw sequence reads.
Singleton: single sequence read that cannot be joined (‘assembled’) into a contig.
Scaffold: a group of ordered and orientated contigs known to be physically linked to each
other by paired read information.
EST: expressed sequence tag generated by sequencing one end of a recombinant clone from a
cDNA library. ESTs are single-pass reads and therefore prone to contain sequence errors.
GSS: genome survey sequence generated by sequencing one end of a recombinant clone from a
genomic DNA library. The genomic DNA library can in some instances be enriched for the
presence of coding regions, for example through use of mung bean nuclease digestion of
genomic DNA prior to cloning.
SNP: single nucleotide polymorphism
ORF: open reading frame, stretches of codons in the same reading frame uninterrupted by
STOP codons and calculated from a six-frame translation of DNA sequence.
Jan 2003
NCBI Trace Archive Sep 23, 2003
Large-scale genome projects
• Sequencing DNA molecules in the Mb
size range
• All strategies employ the same
underlying principles:
Random Shotgun sequencing
Strategy
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Genomic DNA
Shearing/Sonication
Subclone and Sequence
Shotgun reads
Assembly
Contigs
Finishing read
Finishing
Complete sequence
Strategies for sequencing
• How big can you go??
Strategy
• Large-insert clones
Libraries
• cosmids 30-40 kb
• BACs/PACs 50 - 100 kb
• Whole chromosomes
• Whole genomes
Sequencing
Assembly
Closure
Annotation
Release
Genome size and sequencing
strategies
Genome size (log Mb)
0
1
2
3
4
H.sapiens (3000 Mb)
D.melanogaster (170 Mb)
C.elegans (100Mb)
P.falciparum (30 Mb)
S.cerevisiae (14 Mb)
E.coli (4 Mb)
Whole genome shotgun (WGS)
Clone-by-clone
Whole Chromosome Shotgun (WCS)
Whole Genome Shotgun (WGS)
with Clone ‘skims’
Genomic DNA
Shearing/Sonication
Subclone and Sequence
Shotgun reads
Assembly
Contigs
Finishing read
Finishing
Complete sequence
Strategies for sequencing
• Size and GC composition of genome
• Volume of data
• Ease of cloning
• Ease of sequencing
• Genome complexity
Strategy
Libraries
Sequencing
Assembly
Closure
• dispersed repetitive sequence
Annotation
• telomeres & centromeres
Release
• Politics/Funding
Strategies: Clone by Clone
• Simple (0.5 - 2 K reads)
Strategy
• Few problems with repeats
Libraries
• Relatively simple informatics
• Scalability
• Quality of physical map
• Fingerprint / STS maps
• End sequencing
Sequencing
Assembly
Closure
Annotation
Release
Strategies: Whole Chromosome
shotgun (WCS)
• Requires chromosome isolation
Strategy
• Moderate complexity (10’s K reads)
Libraries
• Problems with repeats
• Complex informatics
• Inefficient in isolation
• Quality of physical map (want good physical map)
• Skims of mapped clones
Sequencing
Assembly
Closure
Annotation
Release
Strategies: Whole Genome
shotgun (WGS)
• Moderate to High complexity (10-100’s K reads)
Strategy
• Massive Problems with repeats
Libraries
• Complex informatics
• Quality of physical map
• Fingerprint map
• STS markers
• End-sequences
• Skims of mapped clones
Sequencing
Assembly
Closure
Annotation
Release
Sequencing my
genome
Politics
Strategy
Libraries
Production
Sequencing
Assembly
Finishing
Closure
Annotation
Annotation
Release
TIME MONEY
What do you get?
DATA!!, DATA !!, and more DATA!!
Strategy
• Sequence
• incomplete complete
Libraries
Sequencing
• First-pass annotation
Assembly
• Gene discovery
Closure
• Full annotation
Annotation
• A starting point for research
Release
Genome annotation is central to functional genomics
ORFeome based functional genomics
RNAi phenotypes
Gene Knockout
Expression Microarray
Where is the problem?


Most genome will be sequenced and can be
sequenced; few problem are unsolvable.
Problems lies in understanding what you have:
gene prediction
 annotation

Sequencing
• Library construction
Strategy
• Colony picking (random)
Libraries
• DNA preparation (isolate DNA)
• Sequencing reactions
• Electrophoresis
• Tracking/Base calling
Sequencing
Assembly
Closure
Annotation
Release
Libraries
• Essentially Sub-cloning
• Generation of small insert libraries in a well
characterised vector.
• Ease of propagation
• Ease of DNA purification
• e.g. puc18, M13
Strategy
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Libraries - testing
• Simple concepts
• Insert/Vector ratio (Blue/White ratio)
• Real data
• Insert size
• Sequence ….
• Simple analysis
Strategy
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Sequence generation
• Pick colonies  growth medium
•Template preparation (DNA isolation)
• Sequence reactions
• Standard terminator chemistry
• pUC libraries sequenced with forward and
reverse primers
•Tracking and noise
Strategy
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Sequence generation
• Electrophoresis of products
• Old style - slab gels, 32 > 64 > 96 lanes
• New style - capillary gels, 96 lanes
• Transfer of gel image to UNIX
• Sequencing machines use a slave Mac/PC
• Move data to centralised storage area for
processing
Strategy
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Gel image processing
• Light-to-Dye estimation
• Lane tracking
• Lane editing
• Trace extraction
• Trace standardisation
• Mobility correction
• Background substitution
Strategy
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Pre-processing
• Base calling using Phred
• modifies SCF file format
• Quality clipping from Phred
• Vector clipping
• Sequencing vector
• Cloning vector
• Screen for contaminants
• Feature mark up (repeats/transposons)
Strategy
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Finishing
• Assembly: Process of taking raw single-pass
reads into contiguous consensus sequence
(Phred/Phrap)
• Closure: Process of ordering and merging
consensus sequences into a single contiguous
sequence
• Finished is defined as sequenced on both strands
using multiple clones. In the absence of multiple
clones the clone must be sequenced with multiple
chemistries. The overall error rate is estimated at
less than 1 error per 10 kb
Strategy
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Genome Assembly
Strategy
• Pre-assembly (assembly algorithm)
• Assembly
• Automated appraisal
• Manual review
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Pre-Assembly
Strategy
• Convert to CAF format
• flatfile text format
• choice of assembler
• choice of post-assembly modules
• choice of assembly editor
Libraries
Sequencing
Assembly
Closure
Annotation
Release
www.sanger.ac.uk/Software/CAF
Assembly
Strategy
• Assemble using Phrap
• Read fasta & quality scores from CAF file
• Merge existing Phrap .ace file (previous
assembly) as necessary
• Adjust clipping (where vector, quality start)
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Assembly appraisal
• auto-edit
• removes 70% of read discrepancies of seq.
assembly (highlight misassembly); manually
• Remove cloning vector
• Mark up sequence features (for finisher)
• “Finish” Program (or Program “AutoFinish”)
• Identify low-quality regions
• Cover using ‘re-runs’ and ‘long-runs’
• Compare with current databases
• plate contamination
Strategy
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Manual Assembly appraisal
Strategy
• Use a sequence editor (GAP/consed)
• Tools to identify Internal joins
• Tools to identify and import data from
an overlapping projects
• Tools to check failed or mis-assembled
reads for inclusion in project
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Manual editing
• Sanger uses 100% edit strategy
Strategy
• Where additional data is required:
Libraries
• Check clipping
• Additional sequencing
• Template / Primer / Chemistry
• Assemble new data into project
• GAP4 Auto-assemble
• Repeat whole process
Sequencing
Assembly
Closure
Annotation
Release
Manual Quality Checks
• Force annotation tag consistency
• All unedited data is re-assembled using Phrap
Strategy
• All high-quality discrepancies are reviewed
Libraries
• Confirm restriction digest (clones)
• Check for inverted repeats
• Manually check:
• Areas of high-density edits
• Areas with no supporting unedited data
• Areas of low read coverage (need to confirm)
Sequencing
Assembly
Closure
Annotation
Release
Gap closure
• Read pairs
Strategy
• PCR reactions (long-range / combinatorial)
Libraries
• Small-insert libraries
Sequencing
• Transposon-insertion libraries
Assembly
Closure
Annotation
Release
Gap closure - contig ordering
• Read pair consistency
Strategy
• STS mapping
Libraries
• Physical mapping
Sequencing
• Genetic mapping
• Optical mapping
• Large-insert clone
• skims
• end-sequencing
Assembly
Closure
Annotation
Release
Annotation
• DNA features (repeats/similarities)
Strategy
• Gene finding
Libraries
• Peptide features
• Initial role assignment
• Others- regulatory regions
Sequencing
Assembly
Closure
Annotation
Release
Annotation of eukaryotic genomes
Genomic DNA
ab initio gene
prediction
transcription
Unprocessed RNA
RNA processing
Mature mRNA
Gm3
AAAAAAA
translation
Nascent polypeptide
Comparative gene
prediction
folding
Active enzyme
Functional
identification
Function
Reactant A
Product B
Genome analysis overview: C.elegans
DNA features
• Similarity features
• mapping repeats
• simple tandem and inverted
• repeat families
• mapping DNA similarities
Strategy
Libraries
Sequencing
Assembly
• EST/mRNAs in eukaryotes
Closure
• Duplications,
Annotation
• RNAs
Release
• mapping peptide similarities
• protein similarities
Gene finding
• ORF finding (simple but messy)
Strategy
• ab initio prediction
Libraries
• Measures of codon bias
• Simple statistical frequencies
• Comparative prediction
• Using similarity data
• Using cross-species similarities
Sequencing
Assembly
Closure
Annotation
Release
Peptide features
• Peptide features
• low-complexity regions
• trans-membrane regions
• structural information (coiled-coil)
• Similarities and alignments
• Protein families (InterPro/COGS)
Strategy
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Initial role assignment
• Simple attempt to describe the
functional identity of a peptide
• Uses data from:
• peptide similarities
• protein families
• Vital for data mining
• Large number of predicted genes remain
hypothetical or unknown
Strategy
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Other regulatory features
• Ribosomal binding sites
Strategy
• Promoter regions
Libraries
Sequencing
Assembly
Closure
Annotation
Release
Data Release
• DNA release
• Unfinished
Strategy
• Finished
Libraries
• Nucleotide databases
• GENBANK/EMBL/DDBJ
• Peptide databases
• SWISSPROT/TREMBL/GENPEPT
• Others
Sequencing
Assembly
Closure
Annotation
Release
Real World Example:
Malaria Genome Project
If time permits.
Sequencing the Plasmodium genomes
Four species of malaria infect man:
Plasmodium falciparum
P. vivax
P. malariae
P. ovale
Four species of malaria infect rodents:
P. yoelii
P. berghei
P. chabaudi
P. vinckei
Plasmodium falciparum




~30 million base pairs
(Mb)
80% (A+T)
14 chromosomes
DNA “unstable” in E.
coli



No large insert DNA
clones suitable for
sequencing
Too large for whole
genome shotgun (‘96)
Whole chromosome
shotgun strategy was
selected
Comparison
of genome
features
Feature
P.falciparum
P.y.yoelii
Size (Mb)
No. chroms
Coverage (fold)
No. gaps
(G+C) content (%)
No. genes
Mean gene length (bp)
Gene density (bp/gene)
Genes with introns (%)
Genes with ESTs (%)
Genes with proteomic data (%)
Exons: Mean no./gene
(G+C) content (%)
Introns: (G+C) content
23.1
14
5
5,812
22.6
5,878
1,298
2,566
54.2
48.9
18.2
2.0
24.8
21.1
22.9
14
14.5
93
19.4
5,268
2,283
4,338
53.9
49.1
51.8
2.4
23.7
13.5
Intergenic sequences:
(G+C) content
RNAs: no. tRNAs
no. 5s rRNAs
no. rRNA units
20.7
39
3
4
13.6
43
3
7
P. falciparum genome status
Chr
Size (bp)
No. gaps
Fold coverage
1
643,293
0
13.3
2 (TIGR)
947,102
0
11.1
3
1,060,087
0
10.9
4
1,204,112
0
16.8
5
1,343,552
0
15.1
6
1,377,956
8
16.8
7
1,350,452
14
15.8
8
1,323,195
24
16.2
9
1,541,723
0
17.9
10 (TIGR)
1,694,445
4
15.6
11 (TIGR)
2,035,250
3
11.3
12 (Stanford)
2,271,477
0
16.3
13
2,747,327
37
17.2
14 (TIGR)
3,291,006
3
9.2
0
22,788
0
ND
22,853,764
93
14.5
Eukaryotic annotation - TIGR
Project
DB
Annotation
Station/Manatee
Annotation DB
DDS/DPS
EGC
Gene
finders
Gene
models BLAST
PFAM/TIGRFAM
SignalP/TMHMM
Alignments of genomic to
Functional
proteins and ESTs
assignments
PFB0680w
The P. falciparum genome
P. falciparum S. pombe
Size (bp)
S. cerevisiae D. discoideum A. thaliana
22,853,764
12,462,637
12,495,682
19.4
36.0
38.3
22.2
34.9
No. of genes
5,268
4,929
5,770
2,799
25,498
Mean gene length* (bp)
2,283
1,426
1,424
1,626
1,310
Gene density†
4,338
2,528
2,088
2,600
4,526
Percent coding
52.6
57.5
70.5
56.3
28.8
Genes with introns (%)
53.9
43
5.0
68
79
43
174
ND
73
ND
No. 5S rRNA genes
3
30
ND
NA
ND
No. rRNAs units
7
200-400
ND
NA
700-800
(G+C) content (%)
No. tRNA genes
*excluding introns; †bp per gene
8,100,000 115,409,949
Distribution of gene lengths
3000
P. falciparum
S. pombe
Number of genes
2500
S. cerevisiea
2000
1500
1000
15.5%
3.0-3.6%
500
0
< 300
300-999 1000-1999 2000-2999 3000-3999
Gene length (bp, excluding introns)
>4000
The P. falciparum proteome
Feature
Number
Per cent
Total predicted proteins
5,268
Hypothetical proteins
3,208
60.9
InterPro matches
2,650
52.8
PFAM matches
1,746
33.1
Process
1,301
24.7
Function
1,244
23.6
Component
2,412
45.8
Targeted to apicoplast
551
10.4
Targeted to mitochondrion
246
4.7
Transmembrane domain(s)
1,631
31.0
Signal peptide
544
10.3
Signal anchor
367
7.0
Non-secretory proteins
4,357
82.7
Gene Ontology™
Structural features
Florens et al. Nature 419:520-526
52% of predicted gene products detected by proteomics
Metabolism and transport

Analysis based on similarity searches with sequences of
known enzymes

14% (733) of genes encoded enzymes
 Lower than in bacterial genomes (25-33%)
Enzymes more difficult to identify due to AT-rich
genome and evolutionary distance between P.f. and
other sequenced organisms
Or


P.f. has smaller proportion of genome devoted to
enzymes, reduced metabolic potential
A T P A DP
(13)
H+ C a2+ H+ Zn2+
A T P A DP A T P A DP A T P A DP P Pi
(16)
N OVEL
INHIBITORS
N OVEL
INHIBITORS
PROTEASE
INHIBITORS
Large
peptides
H+
H+
H+
glucosamine
riboflavin
dephosphoCoA
aspartate
CoA
oxaloac etate
CO 2
malate
L-LACTATE
MITOCHONDRION
DHF
Sulfonamides
or
NADH
Purines and
Pyrimi dine s
NAD+
ATP
N OVEL
INHIBITORS
orotate
RNA
DNA
ornithine
N-acetyl-glutamate
cysteine
alanine
spermidine
methionine salvagepathway
dTMP
Cy tc
Fe2+
O2
UQH 2
Cy tc
Fe3+
H2O
THF
Pyrimethamine
Cy cloguany l
Shikimic Acid
Pathway
chor ism ate
pABA
DOXP Pathway
pyruvate
acetyl-CoA
UQ
deoxy xy lulose-5P
Fos midomy cin
2C-methy lerythrose-4P
Haem C Haem A
c is -ac onitate
Pr oto hae m
(FPIX 2+)
s uc cinate oxoglutarate
s uc ciny l-CoA
ubiquinonepool
DHF
Pu rine s alvag e,
Pyr im id ine syn thesis
APICOPLAST
Tricarboxylic acid
fumarate cycle isocitrate
UQ
Methy lene THF
PRPP
pyruvate
malate
Atovaquone
or
dihydroorotate
CDP dUMP
AMP
proline
serine
PEP
acetyl-CoA
oxaloac etate c itrate
malate
pABA
7,8-dihydropteroate
IMP
(6)
putrescine
N OVEL
x ylulos e-5P
INHIBITORS
+
erythros e-4P
3-deoxy arabinoheptulos anate7-phos phate
acetate
oxaloac etate
dCDP
glutamate
ribose-5P
N OVEL
INHIBITORS
Pyrimethamine
Cy cloguany l
hypox anthine
aspartate
glutamine
NOVEL INHI BITOR S
THF
XMP
Pi
Folate
biosynthes is
CO 2
Folate Biosynthesis
x anthine
asparagine
ornithine
ribulose-5P
dihydrox yacetone-P
+
gly ceraldehy de-3P
oxo acid amino acid
FAD
6-phos phogluconate
fructose-1,6-bis P
GLYCEROL
GMP
Pi
fructose-6P
glucosamine-6P
Haemozoin
FMN
(2)
gly cine
glucose-6P
glucosamine-1P
guanine
? ?
Amino ac ids
Chloroquine
Artemes inin
Quinine
GDP
di /t ri A T P A DPcarboxylate s
(4)
Pentose Phosphate
Pathway
GLUCOSE
Small
peptides
(3)
Glycolysis
glucose-1P
GTP
H+ Pi
Am ino Co m pou nds
my o-inositol-1P
FPIX 2+
O2- FPIX 3+
(2)
glycosyl
ph ophatidylin osito l
(GPI an cho rs )
FOOD VACUOLE
O2
H+
Pi
(2)
N OVEL
INHIBITORS
Haem o glob in
H+ SO 2-4 H+ ?
H+ Pi
P
(2)
PROTEASE
INHIBITORS
H+ Mn2+
sugar
phosphates
V
H+ N a+
water/
glycero l
PEP
F
?
H+
mitochondrial/plastidcarriers
sugar
H+
nucleosid e/base
glucose
H+
nucleotide
ornt-sugar?
metabolites
H+
dru gs?
2+,
P -l ipi ds, Cu
oth ercations?
carboxylates?
F, V, & P- type ATPases
drugs?
ABC
tr ansporter s
Haem
Biosynthesis
malony l-CoA
acetoacety l-ACP + malonyl-ACP
Glyce ro lipids
acy l- ACP
Tric losan
Glycerolipid Metabolism
gly cerol
triac ylglyc erol
c holine
phosphatidylcholine
m o difie d tRNAs
FattyAcid
Biosynthesis
Thiolac tomyc in
ALA
ALA
gly cine
ethanolamine
isopenteny l-PP
porphobilinogen
enoyl-ACP
N OVEL
INHIBITORS
phosphatidylethanolamine
3-ox oacy l-ACP
Fatty acid
elonga tion
3-hydrox yacy l-ACP
Analysis of
transporters in
P. falciparum
Organization of multi-gene families in P. falciparum
P. falciparum Genome Summary
Feature
Value
Comments
Genome size
24 million base pairs
1% of the human
genome
Number of chromosomes
14
23 pairs
Number of gaps
93 (0-37 per chr)
Genome >98% complete
(A+T) content
~ 80.6%
Number of genes
~5,300
Proteins of unknown
function
60%
Most (A+T) rich
genome sequenced to
date
Yeast: 5,770
Human: ~35,000
More than other
genomes
Possible surface proteins
~900
Test for use in vaccines
Gene products detected
52%
by proteomics
Genes conserved in rodent 60%
malaria P. yoelii yoelii
See Florens et al.
See Lasonder et al.
See Carlton et al.
Extra Slides