DNA Sequencing and Assembly

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DNA Sequencingand Assembly
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DNA sequencing

• How we obtain the sequence of nucleotides of a
  species

ACGTGACTGAGGACCGTG CGACTGAGACTGACTGGGT CTAGCTAGAC
TACGTTTTA TATATATATACGTCGTCGT ACTGATGACTAGATTACAG
ACTGATTTAGATACCTGAC TGATTTTAAAAAAATATT
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Which representative of the species?

• Which human?
• Answer one
• Answer two it doesnt matter
• Polymorphism rate number of letter changes
  between two different members of a species
• Humans 1/1,000 1/10,000
• Other organisms have much higher polymorphism
  rates

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DNA sequencing vectors
DNA
Shake
DNA fragments
Known location (restriction site)
Vector Circular genome (bacterium, plasmid)


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Different types of vectors
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DNA sequencing gel electrophoresis

• Start at primer
• (restriction site)
• Grow DNA chain
• Include dideoxynucleoside
• (modified a, c, g, t)
• Stops reaction at all
• possible points
• Separate products with
• length, using
• gel electrophoresis

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Electrophoresis diagrams
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Output of gel electrophoresis a read

• A read 500-700 nucleotides
• A C G A A T C A G . A
• 16 18 21 23 25 15 28 30 32 21
• Quality scores -10?log10Prob(Error)
• Reads can be obtained from leftmost, rightmost
  ends of the insert
• Double-barreled sequencing
• Both leftmost rightmost ends are sequenced

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Method to sequence segments longer than 500
genomic segment
cut many times at random (Shotgun)
Get one or two reads from each segment
500 bp
500 bp
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Reconstructing the Sequence (Fragment Assembly)
reads
Cover region with 7-fold redundancy (7X)
Overlap reads and extend to reconstruct the
original genomic region
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Definition of Coverage
C

• Length of genomic segment L
• Number of reads n
• Length of each read l
• Definition Coverage C nl/L
• How much coverage is enough?
• (Lander-Waterman model)
• Assuming uniform distribution of reads, C10
  results in 1 gapped region /1,000,000 nucleotides

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Challenges with Fragment Assembly

• Sequencing errors
• 1-2 of bases are wrong
• Repeats
• Computation O( N2 ) where N reads

false overlap due to repeat
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Repeats

• Bacterial genomes 5
• Mammals 50
• Repeat types
• Low-Complexity DNA (e.g. ATATATATACATA)
• Microsatellite repeats (a1ak)N where k 3-6
• (e.g. CAGCAGTAGCAGCACCAG)
• Common Repeat Families
• SINE (Short Interspersed Nuclear Elements)
• (e.g. ALU 300-long, 106 copies)
• LINE (Long Interspersed Nuclear Elements)
• 500-5,000-long, 200,000 copies
• MIR
• LTR/Retroviral
• Other
• -Genes that are duplicated then diverge
  (paralogs)
• -Recent duplications, 100,000-long, very
  similar copies

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What can we do about repeats?

• Two main approaches
• Cluster the reads
• Link the reads

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What can we do about repeats?

• Two main approaches
• Cluster the reads
• Link the reads

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Strategies for sequencing a whole genome

• Hierarchical Clone-by-clone
• Break genome into many long pieces
• Map each long piece onto the genome
• Sequence each piece with shotgun
• Example Yeast, Worm, Human, Rat
• Online version of (1) Walking
• Break genome into many long pieces
• Start sequencing each piece with shotgun
• Construct map as you go
• Example Rice genome
• Whole genome shotgun
• One large shotgun pass on the whole genome
• Example Drosophila, Human (Celera), Neurospora,
  Mouse, Rat, Fugu

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Hierarchical Sequencing
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Hierarchical Sequencing Strategy
genome

• Obtain a large collection of BAC clones
• Map them onto the genome (Physical Mapping)
• Select a minimum tiling path
• Sequence each clone in the path with shotgun
• Assemble
• Put everything together

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Methods of physical mapping

• Goal
• Make a map of the locations of each clone
  relative to one another
• Use the map to select a minimal set of clones to
  sequence
• Methods
• Hybridization
• Digestion

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1. Hybridization
p1
pn

• Short words, the probes, attach to complementary
  words
• Construct many probes
• Treat each BAC with all probes
• Record which ones attach to it
• Same words attaching to BACS X, Y ? overlap

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Hybridization Computational Challenge
p1 p2 .pm

• Matrix
• m probes ? n clones
• (i, j) 1, if pi hybridizes to Cj
• 0, otherwise
• Definition Consecutive ones matrix
• A matrix 1s are consecutive
• Computational problem
• Reorder the probes so that matrix is in
  consecutive-ones form
• Can be solved in O(m3) time (m gtgt n)
• Unfortunately, data is not perfect

0 0 1 ..1
C1 C2 .Cn
1 1 0 ..0
1 0 1...0
pi1pi2.pim
1 1 1 0 0 0..0
0 1 1 1 1 1..0
0 0 1 1 1 0..0
Cj1Cj2 .Cjn
0 0 0 0 0 01 1 1 0
0 0 0 0 0 00 1 1 1
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2. Digestion

• Restriction enzymes cut DNA where specific words
  appear
• Cut each clone separately with an enzyme
• Run fragments on a gel and measure length
• Clones Ca, Cb have fragments of length li, lj,
  lk ? overlap
• Double digestion
• Cut with enzyme A, enzyme B, then enzymes A B

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Whole-Genome Shotgun Sequencing
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Whole Genome Shotgun Sequencing
genome
plasmids (2 10 Kbp)
forward-reverse linked reads
known dist
cosmids (40 Kbp)
500 bp
500 bp
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The Overlap-Layout-Consensus approach
1. Find overlapping reads
2. Merge good pairs of reads into longer contigs
3. Link contigs to form supercontigs
..ACGATTACAATAGGTT..
4. Derive consensus sequence
many heuristics
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1. Find Overlapping Reads

• Sort all k-mers in reads (k 24)

• Find pairs of reads sharing a k-mer
• Extend to full alignment throw away if not gt95
  similar

TAGATTACACAGATTAC

TAGATTACACAGATTAC
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1. Find Overlapping Reads

• One caveat repeats
• A k-mer that appears N times, initiates N2
  comparisons
• ALU 1,000,000 times
• Solution
• Discard all k-mers that appear more than c ?
  Coverage, (c 10)

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1. Find Overlapping Reads

• Create local multiple alignments from the
  overlapping reads

TAGATTACACAGATTACTGA
TAGATTACACAGATTACTGA
TAG TTACACAGATTATTGA
TAGATTACACAGATTACTGA
TAGATTACACAGATTACTGA
TAGATTACACAGATTACTGA
TAG TTACACAGATTATTGA
TAGATTACACAGATTACTGA
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1. Find Overlapping Reads (contd)

• Correct errors using multiple alignment

C 20
C 20
C 35
C 35
T 30
C 0
C 35
C 35
TAGATTACACAGATTACTGA
C 40
C 40
TAGATTACACAGATTACTGA
TAG TTACACAGATTATTGA
TAGATTACACAGATTACTGA
TAGATTACACAGATTACTGA
A 15
A 15
A 25
A 25
-
A 0
A 40
A 40
A 25
A 25

• Score alignments
• Accept alignments with good scores

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Basic principle of assembly

• Repeats confuse us
• Ability to merge two reads ? ability to
  detect repeats
• We can dismiss as repeat any overlap of lt t
  similarity
• Role of error correction
• Discards 90 of single-letter sequencing errors
• ? Threshold t increases

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2. Merge Reads into Contigs (contd)

• Merge reads up to potential repeat boundaries
• (Myers, 1995)

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2. Merge Reads into Contigs (contd)

• Ignore non-maximal reads
• Merge only maximal reads into contigs

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2. Merge Reads into Contigs (contd)
sequencing error
b
a

• Ignore hanging reads, when detecting repeat
  boundaries

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2. Merge Reads into Contigs (contd)
?????
Unambiguous

• Insert non-maximal reads whenever unambiguous

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3. Link Contigs into Supercontigs
Normal density
Too dense Overcollapsed? (Myers et al. 2000)
Inconsistent links Overcollapsed?
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3. Link Contigs into Supercontigs (contd)
Find all links between unique contigs
Connect contigs incrementally, if ? 2 links
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3. Link Contigs into Supercontigs
Fill gaps in supercontigs with paths of
overcollapsed contigs
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3. Link Contigs into Supercontigs
Contig A
Contig B
Define G ( V, E ) V contigs E ( A, B
) such that d( A, B ) lt C Reason to do so
Efficiency full shortest paths cannot be computed
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3. Link Contigs into Supercontigs
Contig A
Contig B
Define T contigs linked to either A or B
Fill gap between A and B if there is a path in G
passing only from contigs in T
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4. Derive Consensus Sequence
TAGATTACACAGATTACTGA TTGATGGCGTAA CTA
TAGATTACACAGATTACTGACTTGATGGCGTAAACTA
TAG TTACACAGATTATTGACTTCATGGCGTAA CTA
TAGATTACACAGATTACTGACTTGATGGCGTAA CTA
TAGATTACACAGATTACTGACTTGATGGGGTAA CTA
TAGATTACACAGATTACTGACTTGATGGCGTAA CTA

• Derive multiple alignment from pairwise read
  alignments

Derive each consensus base by weighted voting
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Mouse Genome

• Several heuristics of iteratively
• Breaking supercontigs that are suspicious
• Rejoining supercontigs
• Size of problem 32,000,000 reads
• Time 15 days, 1 processor
• Memory 28 Gb
• N50 Contig size 16.3 Kb ? 24.8 Kb
• N50 Supercontig size .265 Mb ? 16.9 Mb

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Mouse Assembly
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Sequencing in the (near) future