Transcript Chromatin Immunoprecipitation DNA Sequencing (ChIP-seq)

Chromatin
Immunoprecipitation DNA
Sequencing (ChIP-seq)
2nd and 3rd Generation DNA Sequencers and
Applications
Sequencing Platforms
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Roche 454 (2nd)
Illumina Solexa(2nd)
ABI SoLid (2nd)
Helicos (3rd)
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Applications
De novo sequencing
Targeted resequencing
Digital Gene Expression
(DGE)
RNA-seq
ChIP-seq
Why ChIP-seq?
• Protein-DNA interactions
• Chromatin States
• Transciptional regulation
ChIP experiment
In Nutshell
•Protein cross-linked to DNA in vivo
by treating cells with formaldehyde
•Shear chromatin (sonication)
•IP with specific antibody
•Reverse cross-links, purify DNA
•PCR amplification*
•Identify sequences
•Genome-wide association map
*-unless using a single molecule sequencer
History: From ChIP-chip to
ChIP-seq
ChIP-chip (c.2000)
• Resolution (30-100bp)
• Coverage limited by
sequences on the array
• Cross-hybridization between
probes and non-specific targets
creates background noise
ChIP-seq experiment (2007-present)
Sample Prep: Solexa vs. Helicos
ChIP-seq Material
sample preps with in-house protocols
Solexa sample prep
Helicos sample prep
Normal QC and ChIP steps
Input material typically >30ng
End-Repair (1h)
Purification (phenol/precipitation) (1.5h)
A-overhang (1h)
Purification (phenol/precipitation) (1.5h)
Adapter oligo ligation (30min)
Purification (phenol/precipitation) (1.5h)
Size-selection (30min by E-gel)
Precipitation (1h)
Amplification PCR (2h) (12-18 cycles)
Size-selection (30min by E-gel)
Precipitation (1h)
Diagnostic gel (30min)
QC by direct qPCR (4hours)
Normal QC and ChIP steps
Input material 3ng-9ng
RNAseA/ProteinaseK treatment (2-3h)
Purification (phenol/precipitation) (1.5h)
Tailing (1.5h)
Termination (1.5h)
Amount of library sequenced approx. 1/10
Amount of library sequenced approx. 1/3
Unique Tags after analysis > 3M
(based on our limited ERaChIP-seq libraries)
Unique Tags after analysis approx >12M
(based on our limited ERaChIP-seq libraries)
**Slide borrowed from Thomas Westerling
ChIP-chip
ChIP-seq (Solexa)
ChIP-seq ( Helicos )
Max
resolution
A rray- s pec ific , 3 0 - 1 0 0 bp
Coverage
L imited by alignability of
L imited by alignability of reads to
reads to genome; inc reas es
L imited by s equenc es on
genome; inc reas es with read
with read length; many
array and non- repetitive
length; many repetitive regions
repetitive regions c an be
c an be c overed
c overed
Cost
Source of
platform
noise
Required
amount of
ChIP DNA
Dyanmic
Range
$ 4 0 0 - 8 0 0 per array
(multiple arrays needed
for large genomes
1 nt
$ 1 ,0 0 0 -2 ,0 0 0 per lane
C ros s -hybridization
between probes and non-Some G C bias due to P C R
s pec ific targets
M ic rograms
1 0 - 5 0 ng
lower detec tion
limit;s aturation at high
s ignal
N o limit
Amplification
(PCR)
more required
Multi-plexing
not an option
les s (1 2 -1 7 c yc les
Y es
1 nt
$ 5 0 0 at M BC F
s ingle molec uleno
( P C R)
9 - 1 2 ng s tandard, have done
1 .5 ng at M BC F
N o limit
N one
Sure
Helicos vs Solexa vs ChIP2
Solexa data (red):
2900
1. Solexa
Unique tags 4M
Peaks called 10 500A
Negative peaks 20 000B
2541
433
Unique tags 13M
Peaks called 12 500
Negative peaks 1000E
4700
ChIP2C data (green):
Array technology, no tags
Peaks called 12 500
FDR 20D
3. ChIP2
5293
1661
Helicos data (blue):
2. Helicos
3744
A) More inclusive (10%) ELAND mapping used (compare to Bowtie in library table)
B) MACS performs a sample swap between ChIP and Input (chromatin) samples and calculates a local λ-value to determine level of background peaks called in
control data. This gives a FDR for each positive peak. Due to the nature of deep sequencing combined with PCR this parameter is in some sample extremely high and
not entirely trustworthy.
C) ChIP2 data published in Carroll et al. Nat Genet. 2006 Nov;38(11):1289-97.
D) FDR values of ChIP2 are calculated differently from FDRs by MACS and are not directly comparable.
E) Negative peaks and thus local FDR values are at first glance more reliable in Helicos sequencing, in part at least due to the lack of amplification the removes
scientist introduced artifacts and reduced complexity of sequenced library.
ChIP-seq Analysis
ChIP-seq peaks
• Only 5’ end of fragments are
sequenced
• Tags from both + and - strand
aligned to reference genome
+/- tag mapping
Types of Analysis
1. Binding site identification and discovery of
binding sequence motifs (Non-histone ChIP)
2. Epigenomic gene regulation and chromatin
structure (Histone ChIP)
Binding Site Detection
But where does the meat go?
Control: Input DNA
Measuring enrichment
Input DNA: portion of DNA sample removed before IP
Rozowsky, J. et al. PeakSeq enables systematic scoring of ChIPSeq experiments relative to controls. Nature Biotech. 27, 66-75 (2009)
Why we need to sequence Input DNA
• Input DNA does not demostrate “flat” or random
(Poisson) distribution
• Open chromatin regions tend to be fragmented more
easily during shearing
• Amplification bias
• Mapping artifacts-increased coverage of more
“mappable” regions (which also tend to be promotor
regions) and repetitive regions due inaccuracies in
number of copies in assembled genome
Depth of Sequencing
Are we there yet?
ERa E2 Helicos MACS peaks 12500
(tag30 mfold30) – sequence depth determination by subsampling
% peaks detected
of total peaks/bin
% of tags sampled
FoldChange Bins 0-20 20-40
Number of total 7687
2841
Peaks in each bin
40-60
935
60-80
429
80-100 100-120 120-140 140-160 160-180 180-200 200-220
217
140
85
49
23
7
4
Statistical Significance
MACS shifted tag-count graph –
i.e. Peak shapes
Helicos Input
HelicosChIP
SolexaChIP
Solexa Input
MACS shifted tag-count graph –
i.e. Peak shapes
Helicos Input
HelicosChIP
SolexaChIP
Solexa Input
MACS shifted tag-count graph –
i.e. Peak shapes
Helicos Input
HelicosChIP
SolexaChIP
Solexa Input