2. Genome sequence assembly
Assembly concepts and methods
(some slides courtesy of Mihai Pop)

3. Building a library Break DNA into random fragments (8-10x coverage)
Actual situation

4. Building a library Break DNA into random fragments (8-10x coverage)
Sequence the ends of the fragments
Amplify the fragments in a vector
Sequence ( ) bases at each end of the fragment

5. Assembling the fragments
NOte that contig orientation/order is not determined

6. Forward-reverse constraints
The sequenced ends are facing towards each other
The distance between the two fragments is known (within certain experimental error)
Insert F R F R I II R I F II
Clone F II R I

7. Building Scaffolds Break DNA into random fragments (8-10x coverage)
Sequence the ends of the fragments
Assemble the sequenced ends
Build scaffolds
We need to determine the relative order/orientation of contigs
Using forward-reverse constraints helps

8. Assembly gaps Physical gaps Sequencing gaps
sequencing gap - we know the order and orientation of the contigs and have at least one clone spanning the gap
physical gap - no information known about the adjacent contigs, nor about the DNA spanning the gap
Sequencing gap is "easy"
Physical gap resolution takes more than 1/2 of closure effort
Multiplex PCR

9. Unifying view of assembly
Scaffolding

10. Shotgun sequencing statistics

11. Typical contig coverage
Imagine raindrops on a sidewalk

12. Lander-Waterman statistics
L = read length
T = minimum detectable overlap
G = genome size
N = number of reads
c = coverage (NL / G)
σ = 1 – T/L
E(#islands) = Ne-cσ
E(island size) = L((ecσ – 1) / c + 1 – σ)
contig = island with 2 or more reads

13. Example c N #islands #contigs bases not in any read
Genome size: 1 Mbp Read Length: Detectable overlap: 40 c N
#islands
#contigs
bases not in any read
bases not in contigs 1
1,667
655
614
698
367,806 3
5,000
304
250
121
49,787 5
8,334 78 57 20
6,735 8
13,334 7
335

14. Experimental data X coverage # ctgs % > 2X avg ctg size (L-W)
max ctg size
# ORFs 1
284 54
1,234 (1,138)
3,337
526 3
597 67
1,794 (4,429)
9,589
1,092 5
548 79
2,495 (21,791)
17,977
1,398 8
495 85
3,294 (302,545)
64,307
1,762
complete
100
1.26 M
1,329
Caveat: numbers based on artificially chopping up
the genome of Wolbachia pipientis dMel

15. Read coverage vs. Clone coverage
4 kbp
1 kbp
Read coverage = 8X
Clone (insert) coverage = 16
2X coverage in BAC-ends implies 100x coverage by BACs
(1 BAC clone = approx. 100kbp)

16. Assembly paradigms Overlap-layout-consensus
greedy (TIGR Assembler, phrap, CAP3...)
graph-based (Celera Assembler, Arachne)
Eulerian path (especially useful for short read sequencing)

17. TIGR Assembler/phrap Greedy Build a rough map of fragment overlaps
Pick the largest scoring overlap
Merge the two fragments
Repeat until no more merges can be done

18. Overlap-layout-consensus
Main entity: read
Relationship between reads: overlap 1 4 7 2 5 8 3 6 9 1 2 3 4 5 6 7 8 9
ACCTGA
AGCTGA
ACCAGA 1 1 2 3 1 2 3 2 3 2 3 1 3 1 1 3 2 2

19. Paths through graphs and assembly
Hamiltonian circuit: visit each node (city) exactly once, returning to the start
Genome

20. Implementation details

21. Overlap between two sequences
overlap (19 bases)
overhang (6 bases)
…AGCCTAGACCTACAGGATGCGCGGACACGTAGCCAGGAC
CAGTACTTGGATGCGCTGACACGTAGCTTATCCGGT…
overhang
% identity = 18/19 % = 94.7%
overlap - region of similarity between regions
overhang - un-aligned ends of the sequences
The assembler screens merges based on:
length of overlap
% identity in overlap region
maximum overhang size.
when a pair of sequences is considered,the two sequences are merged only if they match the criteria

22. All pairs alignment Needed by the assembler
Try all pairs – must consider ~ n2 pairs
Smarter solution: only n x coverage (e.g. 8) pairs are possible
Build a table of k-mers contained in sequences (single pass through the genome)
Generate the pairs from k-mer table (single pass through k-mer table)
k-mer

24. REPEATS

25. RptA
RptB 3 6 9 12 2 5 8 11 1 4 7 10 13 6 4 8 10 2 12 1 13 3 11 5 7 9

26. Non-repetitive overlap graph1 2 3 4
5,9 7 8
6,10 11 12 13

27. Handling repeats Repeat detection Repeat resolution
pre-assembly: find fragments that belong to repeats
statistically (most existing assemblers)
repeat database (RepeatMasker)
during assembly: detect "tangles" indicative of repeats (Pevzner, Tang, Waterman 2001)
post-assembly: find repetitive regions and potential mis-assemblies.
Reputer, RepeatMasker
"unhappy" mate-pairs (too close, too far, mis-oriented)
Repeat resolution
find DNA fragments belonging to the repeat
determine correct tiling across the repeat

28. Statistical repeat detection
Significant deviations from average coverage flagged as repeats.
- frequent k-mers are ignored
- “arrival” rate of reads in contigs compared with theoretical value
(e.g., 800 bp reads & 8x coverage - reads "arrive" every 100 bp)
Problem 1: assumption of uniform distribution of fragments - leads to false positives
non-random libraries
poor clonability regions
Problem 2: repeats with low copy number are missed - leads to false negatives

29. Mis-assembled repeats
excision
collapsed tandem
rearrangement

30. An assembly puzzle: contradictory data (discovered after publication)
ribosomal RNA repeats, Ames Porton strain
“chimeras”
“mates”
How do you align the green pieces?

31. Puzzle solution Reference: Ames ‘ancestor’ strain
Ames Porton Down strain
Tandem duplication

32. Anthrax attack strain history
1981
“Ames”
isolate
Ft Detrick
(Ames ancestor)
1982 …
Lab B
Lab C
Lab D
Porton
Down ? ? ?
Plasmids cured ?
Attack
Strain
Porton
Strain
UC Berkeley
Victim
2001
1998
2001
Florida
isolate
Porton 1
Porton 2

33. Probability of base-calling error
GBX(g)
b. anthracis SNP CS-1
Cut of assembly from GBX0130.contig (11 bases)
Cut at ungapped consensus offset (from 1), +/- 5 positions:
Cut at gapped consensus offset (from 1) 11 positions
Ungapped consensus TGAATGCACAC
Gapped consensus TGAATGCACAC T G A A T G C A C A C
Covering reads:
GBZEI27TF TGAATGCACAC
GBXEZ08TR TGAATGCACAC
GBZDA09TF TGAATGCACAC
Summary info:
P-value (10^q)
Quality Class
Coverage depth
Homogeneity
Cut of assembly 6264 from GBA0117.contig (11 bases)
Cut at ungapped consensus offset (from 1), +/- 5 positions:
Cut at gapped consensus offset (from 1) 11 positions
Ungapped consensus TGAATACACAC
Gapped consensus TGAATACACAC T G A A T A C A C A C
GBIFW80TF TGAATA-ACAC
GBICA33TR TGAATACACAC
GBIFQ32TR TGAATACACAC
GBICH40TF TGAATACACAC
GBICU19TR TGAATACACAC
P-value (10^q)
Quality Class
Coverage depth
GBA(a)
Probability of base-calling
error
Not shown