Next Generation Sequencing Technologies - PowerPoint PPT Presentation

Loading...

PPT – Next Generation Sequencing Technologies PowerPoint presentation | free to download - id: 442daa-MzlhO



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

Next Generation Sequencing Technologies

Description:

Next Generation Sequencing Technologies Rob Mitra Lecture 02/17/09 * We established that we could amplify polonies But can we sequence them? Rather than sequencing ... – PowerPoint PPT presentation

Number of Views:824
Avg rating:3.0/5.0
Slides: 49
Provided by: HornD
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: Next Generation Sequencing Technologies


1
Next Generation Sequencing Technologies
  • Rob Mitra
  • Lecture
  • 02/17/09

2
Forward Genetics
Genotype
Phenotype
Hypothesis
Test Hypothesis By Genetic Manipulation
3
Forward Genetics
Mutation in APC Gene
Two groups 1. Develop Colorectal cancer At Young
Age 2. Do not
Genotype
Phenotype
Hypothesis
APC is a Tumor Supressor Gene
Test Hypothesis By Genetic Manipulation
Delete APC in Mouse Control Isogenic APC
4
The Cycle of Forward Genetics
In 2005 9 million/genome Not feasible
?Sequencing?
Genotype
Observation
Thinking
Phenotype
Hypothesis
Test Hypothesis By Genetic Manipulation
Gene Deletion/Replacement Recombinant Technology
5
End Runs
  • Linkage Studies (Humans, Model Organisms)
  • Association Studies (GWAS)

BUT, these end runs have a cost! 1. Requires a
large family (many crosses in model organisms)
very difficult to analyze multi-factorial
traits 2. Common variants
But, these end runs will not be needed in 5-10
years. Why?
6
The Problem with Forward Genetics
Currently 60,000 /genome Cost is rapidly dropping
Sequencing
Genotype
Observation
Thinking
Phenotype
Hypothesis
Test Hypothesis By Genetic Manipulation
Gene Deletion/Replacement Recombinant Technology
7
Bp/US dollar increases exponentially with time
Adapted from Shendure et al 2004
8
Two questions
  • How was this dramatic acceleration achieved?
  • What will it mean?

9
How was this achieved?
  • Integration (Think about sequencing pipeline)
  • Parallelization
  • Miniaturization
  • Same concepts the revolutionarized integrated
    circuits

Plus one additional insight
10
Read Length is Not As Important For Resequencing
Jay Shendure
11
Two Short Read Techologies
  • Illumina GA
  • ABI SOLID

12
Technology Overview Solexa/Illumina Sequencing
http//www.illumina.com/
13
Immobilize DNA to Surface
Source www.illumina.com
14
Technology Overview Solexa Sequencing
15
Sequence Colonies
16
Sequence Colonies
17
Call Sequence
18
ABI Solid
Dressman 2003
19
Sequencing By Ligation
Shendure et al
20
ABI SOLID
21
ABI SOLID
22
ABI SOLID
23
ABI SOLID
24
ABI SOLID
This allows for error correction
See board
Raw error rate 3 Corrected error rate 0.1
25
Paired End Reads are Important!
Known Distance
Read 1
Read 2
Repetitive DNA
Unique DNA
Paired read maps uniquely
Single read maps to multiple positions
26
Paired Ends are Important Part 2
Deletion
Insertion
Inversion
Shendure et al 2005
27
How can we generate paired end reads?
  • Amplify Large Fragments and Sequence From Each
    End (some trickery required see board)
  • Length is limited (150bp 1kb).
  • Jumping Library

28
Jumping Library Contruction
From Shendure et al
29
Other Second Generation Technologies
  • 454
  • Emulsion PCR
  • Polymerase
  • Natural Nucleotides
  • 20-100Mb for 5-15k
  • 1 error rate
  • Homopolymers

30
Helicos
  • No Amplification Single molecule detection
  • Homopolymer (solved)
  • Expensive Detection

31
Pacific Biosciences A Third Generation
Sequencing Technology
Eid et al 2008
32
(No Transcript)
33
(No Transcript)
34
How did they do?
  • 150 bp circular template
  • 93 raw accuracy
  • 15x coverage 99.3 accuracy
  • Still early days

35
Where are they going
  • Phi29 so long read lengths possible
  • Ease of sample prep
  • Camera costs

36
Summary
  • Sequencing will become very inexpensive in 3-5
    years
  • So now what?

37
Areas of Broad Impact
  • Understanding Common Diseases
  • Cancer

38
Why dont we understand common traits or diseases?
  • GWAS is relatively new
  • But, this method can only analyze common variants
  • If rare variants play a significant role in
    common traits then we need to sequence. (Board)
  • SO DO THEY?

39
Studies on human height
  • Heritability of height is 0.8 (80 of variation
    in height is due to genetic factors)
  • 3 studies genotyped 63,000 individuals at 500,000
    loci (biggest cohort analyzed to date)
  • 54 loci explain 4 of the variance. WHAT!?

40
Do rare variants matter?
  • What is the genetic basis of variation in blood
    pressure?
  • Lifton and colleagues sequenced 1000 individuals
    at these 3 loci (SLC12A3, SLC12A1, and KCNJ1) and
    correlated the observed genetic variation with
    blood pressure measurements.
  • 20 individuals had heterozygous, rare mutations
    that caused a significant decrease in blood
    pressure. Each rare mutation had a relatively
    large effect, and these mutations also protected
    individuals against developing clinical
    hypertension.
  • Although only about 2 of the population has a
    functional mutation in one of these three genes,
    Lifton and colleagues hypothesize
  • Because these three genes comprise only a small
    fraction of those in which mutations are known to
    alter blood pressure, and because there are
    likely to be many more genes yet to be
    discovered, it seems probable that the combined
    effects of rare independent mutations will
    account for a substantial fraction of blood
    pressure variation in the population.

Ji et al 2008
41
Conclusions
  • CDCV may not hold for many common traits
  • Rare variants may cumulatively play a big role in
    common traits, but sequencing candidate genes
    isnt getting it done.
  • Whole genome sequencing.

42
Cancer and Whole Genome Sequencing
  • Cancer is a disease of the genome
  • Acquisition of somatic mutation
  • The genome records a history of disease

43
  • Complete genome sequence of AML genome
  • 32.7 fold haploid coverage
  • 14 fold coverage of normal skin
  • Remove SNPs, check for non-synonymous somatic
    mutations in coding DNA
  • 10 mutations found (2 known to be involved in
    cancer progression)

44
We need more genomes!
  • Complete genomics (5000)
  • ABI (10,000)
  • Illumina (?)
  • Intelligent Biosystems (lt1000)

45
Sequencing coverage calculations
  • Lets say you need a base to be sequenced 5x for
    an accurate base call
  • How much average coverage do you need to ensure
    that 95 of the genome is sequenced at least 5
    times?

46
Poisson Distribution
Originally derived for time.
Average coverage lambda Probability of getting
k reads from a base given the average coverage
lambda
47
Example
  • Average coverage 5x
  • Probability of a given base being sequenced 10
    times is
  • 510e-5/10! 0.018 or about 2 of bases will have
    10x coverage.

48
What about our question?
About PowerShow.com