Introduction to Next Generation
Sequencing
Overview
• Day 1: AM - Basic biology recap and Intro to NGS
• Day 1: PM - Intro to Data Analysis
– Format(s), Quality checking, Trimming
• Day 2: AM - General procedures and strategies in NGS
• Day 2: PM - Exome sequence analysis practical (Galaxy)
• Day 3: AM - Introduction to RNA-Seq (and a touch of miRNA-Seq)
• Day 3: PM - RNA-Seq practical (Tophat + Cuffdiff pipeline on Galaxy)
Note: practical write-ups = assessment assignment
Overview
• Day 4: AM – NGS in the wild (case studies)
– Clinical genomics
– Human microbiome
• Day 4: PM - Candidate filtering and prioritization
– Mostly SNP based
– Little bit of functional and pathway enrichment analysis
• Day 5: AM - Knowledge-driven methods for finding
‘causative’ genes & wrap-up
• Day 5: PM – Free or wrap up practical
Next Generation Sequencing
Day 1: Introduction
Full genome sequencing
Day 1 - Overview
• Central Dogma Review
• History of DNA Sequencing
• First Generation (Sanger) Sequencing
• Next Generation Sequencing Introduction
• NGS Opportunities and Challenges
• NGS Applications
• NGS Study Design and Technology Choice
History
1866
Gregor Mendel
published the results
of his investigations
of the inheritance of
"factors" in pea
plants.
DNA was first isolated by the Swiss
physician Friedrich Miescher in
1869.
1950's
• Maurice Wilkins (19162004), Rosalind Franklin
(1920-1957), Francis Crick
(1916-2004) and James
Watson (1928- ) discover
chemical structure of DNA
• Starts a new branch of
science - molecular
biology.
The Central Dogma of Molecular Biology
Reverse
Transcription
10
Structure of the DNA molecule
• DNA is shaped like a double helix
• It is like a spiral staircase
• Another way to think of it is a
twisted ladder
11
Connecting the DNA molecule
• Rails of the DNA ladder are
alternating sugar &
phosphates
• Rungs are composed of pairs
of bases
– A bonds with T
– G bonds with C
12
Connecting the DNA molecule
• The two strands of DNA are
different
• One is called the sense strand and
it is the plan to make a protein
• The other strand is the antisense
strand
13
Connecting the DNA molecule
• The two strands of DNA are said
to be antiparallel
antisense
• The other strand is oriented in
the opposite 3’ to 5’ direction
sense
• One strand is oriented in a 5’ to
3’ direction
5’ 3’
3’ 5’
14
Replication of DNA
15
DNA sequencing exploits the physicochemical
properties of DNA and the enzymes involved
in its replication
(more later…)
Introns and Exons
• Introns – non-coding sequences in the DNA
that are NOT used to make to make a protein
• Exons – coding sequences in the DNA that are
expressed or used to make mRNA and
ultimately are used to make a protein
17
Introns and Exons
18
Transcription
19
Transcription
20
Translation
21
Sanger Method
Fred Sanger, 1958
Was originally a protein chemist
Made his first mark in sequencing
proteins
Made his second mark in sequencing
RNA
1980 dideoxy sequencing
Sanger Method: Dideoxy Chain Termination
300-500 bases
Capillary Method - Fluorescent Dyes
800-1000 bases
Automated Sequencing
– Leroy Hood developed fluorescent color labels for the
4 terminator nucleotide bases (late 80s).
– This allowed all 4 bases to be sequenced in a single
reaction and sorted in a single gel lane.
– Hood also pioneered direct data collection by
computer
– Improvements in this technology now enabled
sequencing of billion base genomes in < 1 year.
• Automated sequencing machines use 4
colors, so they can read all 4 bases at once.
Genome Sequencing
TG..GT
TC..CC
AC..GC
CG..CA
TT..TC
TG..AC
AC..GC GA..GC
CT..TG
AC..GC
GT..GC
AC..GC
AA..GC
AT..AT
TT..CC
Genome
Short fragments of DNA
ACGTGGTAA
CGTATACAC
TAGGCCATA
GTAATGGCG
CACCCTTAG
TGGCGTATA
CATA…
ACGTGGTAATGGCGTATACACCCTTAGGCCATA
Short DNA sequences
ACGTGACCGGTACTGGTAACGTACA
CCTACGTGACCGGTACTGGTAACGT
ACGCCTACGTGACCGGTACTGGTAA
CGTATACACGTGACCGGTACTGGTA
ACGTACACCTACGTGACCGGTACTG
GTAACGTACGCCTACGTGACCGGTA
CTGGTAACGTATACCTCT...
Sequenced genome
28 28
-2001
The HGP consortium publishes
its working draft in Nature (15
February), and Celera publishes
its draft in Science (16 February).
Sequencing the Human Genome
2001: Human Genome Project
2.7G$, 11 years
Log10(price)
10
8
6
2007: 454
1M$, 3 months
2008: ABI SOLiD
60K$, 2 weeks
2001: Celera
100M$, 3 years
4
2009: Illumina,
Helicos
40-50K$
2
2000
2010: 5K$,
a few days?
2012: 100$, <24
hrs?
2005
Year
2010
30
Sequence Database Size
Exponential Data Increase
Year
NAR. 2007 September; 35(18): 6227–6237.
Adapted from Eric Green, NIH; Adapted from Messing & Llaca, PNAS (1998)
History of DNA Sequencing
1870
Miescher: Discovers DNA
1940
Avery: Proposes DNA as ‘Genetic Material’
Efficiency
(bp/person/year)
1953
Watson & Crick: Double Helix Structure of DNA
1
1965
Holley: Sequences Yeast tRNAAla
1970
Wu: Sequences  Cohesive End DNA
1977
Sanger: Dideoxy Chain Termination
Gilbert: Chemical Degradation
1980
Messing: M13 Cloning
1986
Hood et al.: Partial Automation
15
150
1,500
15,000
25,000
50,000
1990
• Cycle Sequencing
• Improved Sequencing Enzymes
• Improved Fluorescent Detection Schemes
200,000
50,000,000
100,000,000,000
2002
2008
• Next Generation Sequencing
•Improved enzymes and chemistry
•Improved image processing
Sanger vs NGS
• ‘Sanger sequencing’ has been the only DNA
sequencing method for 30 years but…
• …hunger for even greater sequencing
throughput, at lower cost
• NGS has the ability to process millions of
sequence reads in parallel rather than 96 at a
time (at a small fraction of the cost)
Next Generation Sequencing:
Why Now?
• Motivation: HGP and its derivatives,
personalized medicine
• Short reads applications: (re-)sequencing,
other methods (e.g. gene expression)
• Advancements in technology
34
“Paradigm Shift”
• Standard ABI “Sanger” sequencing
– 96 samples/day
– Read length ~650 bp = 450,000 bases
• 454 was the game changer!
– ~400,000 different templates (reads)/day
– Read length ~250 bp
– Total = 100,000,000 bases of sequence data!!!
Solexa ups the Game
• Solexa (Illumina GA)
– 60,000,000 different sequence templates (yes that
is an insane 60 million reads)
– 36 bp read length (much longer now)
– 4 billion bases of DNA per run (3 days)
Next Generation Sequencing
• 454 Life Sciences/Roche
– Genome Sequencer FLX: currently produces 400-600 million bases per
day per machine
– Published 1 million bases of Neanderthal DNA in 2006
– May 2007 published complete genome of James Watson (3.2 billion
bases ~20x coverage)
• Solexa/Illumina
– 10 GB per machine/week
– May 2008 published complete genomes for 3 hapmap subjects (14x
coverage)
• ABI SOLID
– 20 GB per machine/week
Nanotechnology
• Each system works differently, but they are all
based on a similar principals:
1.
2.
3.
4.
Shear target DNA into small pieces
bind individual DNA molecules to a solid surface,
amplify each molecule into a cluster
copy one base at a time and detect different
signals for A, C, T, & G bases
5. requires very precise high-resolution imaging of
tiny features
• (Solexa has 800 images @ 4 megapixels each)
Sequencing by Synthesis (SBS)
Problem: Huge Amount of Image Data
• Raw image data huge: 1-2 TB for the Solexa, more for
ABI-SOLID, less for 454
• The images are immediately processed into intensity
data (spots w/ location and brightness)
• Intensity data is then processed into basecalls (A, C, T,
or G plus a quality score for each)
• Basecall data is on the order of 5-10 GB per run (or a
week of runs for 454)
From John McPherson, OICR
Next-gen sequencers
100 Gb
AB/SOLiDv3, Illumina/GAII
short-read sequencers
(10+Gb in 50-100 bp reads,
>100M reads, 4-8 days)
bases per machine run
10 Gb
454 GS FLX pyrosequencer
1 Gb
(100-500 Mb in 100-400 bp reads,
0.5-1M reads, 5-10 hours)
100 Mb
ABI capillary sequencer
(0.04-0.08 Mb in 450-800 bp reads,
96 reads, 1-3 hours)
10 Mb
1 Mb
10 bp
100 bp
read length
1,000 bp
Adapted from John McPherson, OICR
2009/10
AB SOLiDv3
120Gb, 100 bp reads
100 Gb
Illumina HiSeq
100Gb, 150bp reads
bases per machine run
10 Gb
1 Gb
454 GS FLX Titanium
0.4-0.6 Gb, 100-400 bp reads
100 Mb
10 Mb
ABI capillary sequencer
(0.04-0.08 Mb,
450-800 bp reads
1 Mb
10 bp
100 bp
read length
1,000 bp
Stein Genome Biology 2010 11:207
Storage is becoming a real problem
Kahn, 2011, Science
Lower Cost = More Innovation
• As sequencing becomes cheaper, more
investigators can use it for routine assays
• Leads to variations and absolutely novel
applications
Lower Cost = More samples
• More patients in GWAS studies
• More replicates (or the use of some replicates
and statistical approaches) in all other assays
Bioinformatics is the Bottleneck
• Sequencing is a commodity – can easily be
outsourced
• Bioinformatics is the essential point of the
science
– Data analysis and discovery of meaning in results
• As the data throughput increases, the cost and
time spent on analysis increase more than
linearly
More Investigators = Less Informatics
skill
• Sequencing is a readout for many different
types of laboratory experiments
• Clinical and basic science investigators from all
areas of biology can make use of this
technology
• Many are completely naïve about
bioinformatics
• Informatics tools for NGS are very challenging
Challenging Bioinformatics
Environment
• Very rapid change in technology platform
– New file formats, new data types
– Different “standards” from different vendors
• Very rapid evolution of new methods
• Very rapid ‘release’ of methods as ‘software’ via
unsupported open source distribution
• Large data sizes (both experimental and reference)
The key
Automation, automation, automation…
454 Sequencing Overview
• Prepare library of single stranded DNA, 200-500 bp long
and ligate adapters
• Perform emulsion PCR, amplifying a single DNA template
molecule in each microreactor (bead).
• Sequence all clonally amplified sample fragments in
parallel using pyrosequencing technology
• Analyze sequence results
– CLEAN data
– Align overlapping sequence of individual reads to define contigs
(Shotgun)
– Order and orient contigs, create scaffolds (Paired End)
– Identify variants (Amplicon)
– Determine gene expression patterns (Transcriptome)
Emulsion Based Clonal Amplification
A
+ PCR Reagents
+ Emulsion Oil
B
Micro-reactors
Adapter carrying
library DNA
Mix DNA Library
& capture beads
(limited dilution)
“Break micro-reactors”
Isolate DNA containing beads
Create
“Water-in-oil”
emulsion
Perform emulsion PCR
• Generation of millions of clonally amplified sequencing templates on each bead
From: Roche 454 James Grabeau 2007 (www.lsbi.mafes.msstate.edu/Roche%20454%20James%20Grabau%202007.ppt )
Depositing DNA Beads into the PicoTiter™Plate
Load beads into
PicoTiter™Plate
Load Enzyme
Beads
44 μm
Adapted from: Roche 454 James Grabeau 2007 (www.lsbi.mafes.msstate.edu/Roche%20454%20James%20Grabau%202007.ppt )
Reagent flow and image capture
PicoTiterPlate
Wells
Reagent Flow
Sequencing
By Synthesis
Photons Generated
are Captured by
Camera
Sequencing Image Created
Adapted from: Roche 454 James Grabeau 2007
(www.lsbi.mafes.msstate.edu/Roche%20454%20James%20Grabau%202007.ppt )
FLX Sequencing Reaction
www.roche-applied-science.com
Different Library Preparation Methods for
Different Project Aims
•
Shotgun Library Preparation for de novo or
resequencing of genomic DNA or long PCR
product. Align overlapping reads to define
contigs
•
Paired End Library Preparation provides
regions of sequence a known distance apart,
allowing for ordering of contigs and analysis
of genetic rearrangement.
•
Amplicon Library Preparation for detection of
rare variants.
Shotgun Library Preparation
Create random DNA
fragments, 300-800
bp, by nebulization
with compressed N2
Ligate universal
adpaters “A” and “B”.
Select for “A” – “B”
fragments. Remove
second strand
Attach to library beads
via “B” adapter at
calculated
concentration to yield
a single template
molecule per library
bead
Proceed to emPCR
Images from: https://www.roche-applied-science.com/
Amplicon Library Preparation
• Target amplicon of 200-500 bp
– 200 bp for uni-direction reads
– 500 bp requires bi-directional reads
• Amplify using fusion primers that include template
specific primer and primers A and B
•Purify and quantify
•Proceed to emPCR
From Michael Metzker, http://view.ncbi.nlm.nih.gov/pubmed/19997069
Solexa/Illumina
Sequencing: Fluorescently labeled
Nucleotides (Solexa)
Complementary strand elongation: DNA Polymerase
60
From Debbie Nickerson, Department of Genome Sciences, University of Washington, http://tinyurl.com/6zbzh4
From Michael Metzker, http://view.ncbi.nlm.nih.gov/pubmed/19997069
From Michael Metzker, http://view.ncbi.nlm.nih.gov/pubmed/19997069
Sequencing by Synthesis (SBS)
From Debbie Nickerson, Department of Genome Sciences, University of Washington, http://tinyurl.com/6zbzh4
Illumina (Solexa) Applications
Resequencing
•
Characterise different related species or strains
Transcriptome analysis
•
•
No chip/array required!
random priming of RNA
DNA methylation analysis
•
sequencing bisulfite-converted DNA methylation-sensitive restriction digest enriched
fragments
Examine chromatin modifications
•
Quantify in vivo protein-DNA interactions using the combination of chromatin
immunoprecipitation and sequencing (ChIP-Seq)
Computational Biology Research Group
454 vs Solexa
•
•
•
•
•
Homopolymers (AAAAA..)
Read length: 400 bp
Number of reads: 400.000
Per-base cost greater
De novo assembly, metagenomics
•
•
•
•
Read length: 40 bp
Number of reads: millions
Per-base cost cheaper
Ideal for application requiring short reads: ncRNA
General ways of using the sequences:
• Assemble them and look at what you have
• You map them (align against a known genome) and then
look at what you have.
• Or a mixture of both!
• Sometimes you select the DNA you are sequencing or you
try to sequence everything
• Depends on biological question, sequencing machine you
have, and how much time and money you have
Bioinformatics Tools
• Alignment of reads to reference genome
• Assembly of de novo sequence
• Quality Control & Base Calling
• Polymorphism detection
• Differential expression and splicing detection
• Genome browsing and annotation
Alignment of reads
• Reads generated from sequencing is mapped
to a reference genome
• Conventional tools like BLAST or BLAT do not
work well with short sequence reads.
• Modification of existing alignment algorithms
to handle short reads.
Alignment Tools
•
•
•
•
•
•
•
•
ELAND
MAQ
Mosaik
SHRiMP
SOAP
BWA
Bowtie
NOVOALIGN (commercial)
Assembly
• De novo sequencing involves assembling
overlapping reads to form contiguous
sequence of DNA
• Done in cases where there’s no genomic
information available
NGS Applications
• DNA mixtures from diverse ecosystems = metagenomics
• Identification of all mutations in an organism
• Deciphering cell’s transcripts at sequence level without prior
knowledge of the genome sequence
• Chip-seq: interactions protein-DNA
• Epigenomics
• Detecting noncoding RNA (miRNA-Seq is BIG now)
• Genetic human variation : SNP, CNV (diseases)
• Ancient DNA
• Pooled sequencing
Take home message
Before you choose the analysis tools, choose
your NGS technology wisely
AND
Decide whether NGS is absolutely necessary
Where to get help/tips/clues