Some new sequencing technologies. Molecular Inversion Probes.

Some new sequencing technologies

Molecular Inversion Probes

Illumina Genotype Arrays

Single Molecule Array for Genotyping—Solexa

Nanopore Sequencing

http://www.mcb.harvard.edu/branton/index.htm

Pyrosequencing on a chip

Mostafa Ronaghi, Stanford Genome Technologies Center

454 Life Sciences

Polony Sequencing

Technologies available today

• Illumina 550,000 SNP array: $300-500 in bulk

• 454 200 bp reads, 100 Mbp total sequence in 1 run, $8K 500bp reads in much higher throughput coming soon

• Solexa 1Gbp of sequence coming in paired 35 bp reads 1 day, approx $10K / run

Short read sequencing protocol

• Random, high-coverage clone library (CovG = 7 – 10x)

• Low-coverage of clone by reads (CovR = 1 – 2x)

1234 1235

FRAGMENT

genome

clones

AMPLIFY & READ

12351234

reads

CovG

CovR

Short read sequencing protocol

RANDOMLY SELECT 200,000 FRAGMENTS

CLONE

FRAGMENT AND SELECT 150KB SEGMENTS

FRAGMENT

A C G A

bead attachment primer

adapter

clone id tag

LIGATE ADAPTERS

166 clone batch

CLONE ON BEADS BY PCR EMULSION

ACGATGATCGATGATTAC...

TGCTCAGACTTAGCTATT...

CAATTTATATCAGAGACA...

ACGAAATCGAGAGCAAGA...

clone id tag

SEQUENCE 250,000 READS ON PLATE

sequenceread

1200 plates

ASSEMBLY

target genome

“clones”

Ordering clones into clone contigs

293

1001

1234

882

7

94

clone graph

NODE CONTRACTION

clone contig1234

293

100194

7882

Contig assembly

CONSTRUCT READ SETS

Euler assembler

intersection read set

subtraction read set

Contig assemblyCONTIG

ASSEMBLY 1: READ SETS

CONSTRUCT READ SETS

Euler assembler

CONSTRUCT CONTIG SETS

CONTIG ASSEMBLY 2: CONTIG SETS

Euler assembler

CONTIG ASSEMBLY 3:

CLONE CONTIGS

assembly

intersection read set

subtraction read set

contig set

Assembly quality

Sequence CoverageContig N50 (Kb)

Base quality (Q)

Misassemblies (#/Mb)

Small indels (#/Mb)

D. Melanogaster(118 Mb)

94.2% 160.2 38.4 2.5 1.6

Human chr21(34 Mb)

97.5% 79.0 35.6 1.9 2.3

Human chr11(131 Mb)

96.3% 57.4 34.4 2.8 1.9

Human chr1(223 Mb)

96.2% 63.0 34.4 3.0 2.0

Read length = 200 bp, Error rate = 1%, Net coverage = 20.0x

Multiple Sequence Alignment

Evolution at the DNA level

…ACGGTGCAGTTACCA…

…AC----CAGTCCACCA…

Mutation

SEQUENCE EDITS

REARRANGEMENTS

Deletion

InversionTranslocationDuplication

Evolutionary Rates

OK

OK

OK

X

X

Still OK?

next generation

Genome Evolution – Macro Events

• Inversions• Deletions• Duplications

Synteny maps

Comparison of human and mouse

Synteny maps

Orthology, Paralogy, Inparalogs, Outparalogs

Synteny maps

Synteny maps

Building synteny maps

Recommended local aligners• BLASTZ

Most accurate, especially for genes Chains local alignments

• WU-BLAST Good tradeoff of efficiency/sensitivity Best command-line options

• BLAT Fast, less sensitive Good for

• comparing very similar sequences • finding rough homology map

Index-based local alignment

Dictionary:

All words of length k (~10)

Alignment initiated between words of alignment score T

(typically T = k)

Alignment:

Ungapped extensions until score

below statistical threshold

Output:

All local alignments with score

> statistical threshold

……

……

query

DB

query

scan

Question: Using an idea from overlap detection, better way to find all local alignments between two genomes?

Local Alignments

After chaining

Chaining local alignments

1. Find local alignments

2. Chain -O(NlogN) L.I.S.

3. Restricted DP

Progressive Alignment

• When evolutionary tree is known:

Align closest first, in the order of the tree In each step, align two sequences x, y, or profiles px, py, to generate a new

alignment with associated profile presult

Weighted version: Tree edges have weights, proportional to the divergence in that edge New profile is a weighted average of two old profiles

x

w

y

z

Example

Profile: (A, C, G, T, -)px = (0.8, 0.2, 0, 0, 0)py = (0.6, 0, 0, 0, 0.4)

s(px, py) = 0.8*0.6*s(A, A) + 0.2*0.6*s(C, A) + 0.8*0.4*s(A, -) + 0.2*0.4*s(C, -)

Result: pxy = (0.7, 0.1, 0, 0, 0.2)

s(px, -) = 0.8*1.0*s(A, -) + 0.2*1.0*s(C, -)

Result: px- = (0.4, 0.1, 0, 0, 0.5)

Threaded Blockset Aligner

Human–Cow

HMR – CDRestricted AreaProfile Alignment

Reconstructing the Ancestral Mammalian Genome

Human: C

Baboon: C

Cat: C

Dog: G

C

C or G

G