Platform validation: Comparison of sequence-specific transcription
factor determinations by ChIP-seq and ChIP-qPCR
From the laboratory of Richard M. Myers
HudsonAlpha Institute for Biotechnology
601 Genome Way
Huntsville, AL 35806
Prepared by: Jason Gertz, Timothy E Reddy, Florencia Pauli, and Richard M Myers
September 9, 2011

As part of our contribution to the ENCODE Project, as well as our extended interests inunderstanding gene regulation in humans, we have performed large numbers ofchromatin immunoprecipitation experiments, followed by high-throughput DNA
sequencing (ChIP-seq). This has involved the analysis of more than 60 DNA binding
proteins, including general and sequence-specific transcription factors. In an effort tounderstand the performance of the DNA sequencing, we sought to evaluate ChIP-seq
results with an alternative approach, ChIP-qPCR.

We quantitatively compared thedensity of reads (binding site signal) in ChIP-seq binding sites to measurements ofbinding site enrichment using ChIP-qPCR. We tested the concordance of ChIP-seq andChIP-qPCR results for 12 transcription factors and found an overall good agreement
between ChIP-seq signal and ChIP-qPCR enrichment. These results indicate that highthroughput

DNAsequencing

maintains

anoverallrobustrepresentation

ofimmunoprecipitated material.

Methods
Chromatin Immunoprecipitation of sequence-specific factors
We performed chromatin immunoprecipitation (ChIP) experiments as previouslydescribed (Johnson et al. 2007) with 8x107 cells for the human cell lines GM12878 orK562. ChIP-seq libraries constructed using the method described in Johnson et al. aredenoted as PCR2x, because there are two PCR reactions performed, before and after size
selection. ChIP-seq libraries labeled as PCR1x were constructed with one PCR reactionthat was performed after size selection. Libraries were sequenced on Genome Analyzers(Illumina).

Target selection and primer design
Binding sites for sequence-specific transcription factors were identified using MACS
(Zhang et al. 2008) by comparing a sequenced input library (sonicated chromatin withformaldehyde crosslinks reversed) to a sequenced ChIP library. Binding sites were thenranked by their fold-enrichment, and 44 binding sites were randomly chosen to uniformly
cover the fold-enrichment levels. Primer pairs were designed for each binding site using
Primer3 (Rozen and Skaletsky 2000) with the following parameters: 50 bp to 100 bp
amplicon size, 19 bp to 26 bp primer length, 63°C to 67°C melting temperature range foreach primer. In addition to experimental primers, 2 pairs of negative primers were
designed against non-conserved and non-repetitive intergenic sequences located far fromany known genes using the same Primer3 parameters.

qPCR assay and analysis
We used 0.2% of the total DNA purified from a ChIP in each experimental qPCR
reaction. A standard curve was also performed for each primer pair using 0.5 ng, 5 ng,
and 50 ng of stock Human Genomic DNA (Roche). Two 96-well plates were set up foreach ChIP, with 22 binding site primer pairs and both negative control primer pairs oneach plate. For each qPCR reaction, DNA was mixed with 0.5 µM (final concentration)of each primer, 10 µL 2x DyNAmo Flash SYBR Green qPCR mix (Finnzymes F-415) ina total reaction volume of 20 µL. The reactions were incubated at 95°C for 7 minutes,
followed by 40 cycles of 94°C for 10 seconds and 60°C for 30 seconds on an iCycler IQ
Real-Time PCR Detection System (Biorad). Automatically detected threshold cycles
were used to determine relative abundance in each reaction and the experimental wells

were compared to the corresponding primers’ standard curve to determine the effective
concentration of each binding site. Effective concentrations were then compared to thenegative controls to determine the enrichment of the binding site in the ChIP. Spearman
rank correlations between fold enrichments from qPCR and fold enrichments from ChIPseq were calculated in Prism.

qPCR fold enrichments of 2-fold or greater wereconsidered positive when calculating false positive rates.

Results
We performed qPCR on ChIPs with antibodies that target 12 sequence-specifictranscription factors in the human cell lines GM12878 or K562.

Rank correlation

between ChIP enrichments from qPCR and ChIP-seq were significant for 11 out of the 12
ChIP experiments, with an average correlation of 0.635 (Table 1). NRSF was the onlytranscription factor that did not show significant correlation between qPCR and ChIP-seq.
All of the data points for individual experiments can be found in the SupplementalFigures.

The qPCR results were also used to experimentally evaluate the false positive rate ofChIP-seq binding sites. The positive predictive value (PPV) for each transcription factor
is shown in Table 1. On average, 89.7% of ChIP-seq binding sites exhibited enrichment
when assayed by qPCR. For every transcription factor more than 75% of ChIP-seq
binding sites were enriched over negative controls. Overall, these results show that thevast majority of ChIP-seq binding sites can also be detected by qPCR of ChIP material
and that the quantitative enrichments found in ChIP-seq data are usually recapitulated byqPCR.

References
Johnson DS, Mortazavi A, Myers RM, Wold B. 2007. Genome‐wide mapping of in vivo
protein‐DNA interactions. Science 316(5830): 1497‐1502.

Rozen S, Skaletsky H. 2000. Primer3 on the WWW for general users and for biologist
programmers. Methods Mol Biol 132: 365‐386.
Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers
RM, Brown M, Li W et al. 2008. Model‐based analysis of ChIP‐Seq (MACS).
Genome Biol 9(9): R137.

Table 1. Performance of qPCR validation
Positive
predictive
value (PPV)Transcription
FactorDNA
type

Cell type

Dataset identifier

ProtocolCorrelation between
Chip-seq and qPCR

BATF

ChIP

GM12878

SL839

PCR1x0.84

0.978

GABP

ChIP

GM12878

SL203

PCR2x0.59

0.864

HRT1

ChIP

K562

SL845

PCR1x0.65

0.953

IRF4

ChIP

GM12878

SL838

PCR1x0.70

0.773

NRSF

ChIP

Gm12878

SL202

PCR2x-0.130.767

OCT2

ChIP

GM12878

SL614

PCR1x0.580.773

P300

ChIP

GM12878

SL551

PCR1x0.750.955

PAX5ChIP

GM12878

SL675

PCR1x0.640.864

PBX3

ChIPGM12878

SL647

PCR1x0.76

0.909

POL2ChIP

GM12878

SL748

PCR1x0.76

1PU.1

ChIPK562

SL646

PCR1x0.69

1

SIX5

ChIP

K562

SL842

PCR1x0.79

0.932

Supplementary Figures. Comparison of ChIP­seq signal and relative qPCRexpression.

Each graph shows the 44 binding sites assayed by qPCR for aparticular factor with log base 2 of the ChIP‐seq signal divided by the reverse
crosslink control on the y‐axis and the log base 2 of the enrichment of the bindingsite compared to negative control regions measured by qPCR on the x‐axis.

ChIP-seq log2(peak / negative)

B-ATF
6

ρ = 0.84

420-202

4

qPCR log2(target / negative)

6

ChIP-seq log2(peak / negative)

GABP
8ρ = 0.59

6
4
20-2

02

4

qPCR log2(target / negative)

6

ChIP-seq log2(peak / negative)

HRT1
10

ρ = 0.65

864
20-202

4

6

qPCR log2(target / negative)

8

ChIP-seq log2(peak / negative)

IRF46

ρ = 0.70

420-2024qPCR log2(target / negative)

6

ChIP-seq log2(peak / negative)

NRSF
6ρ = -0.13420024qPCR log2(target / negative)

6

ChIP-seq log2(peak / negative)

OCT2
6

ρ = 0.58

420-202

4qPCR log2(target / negative)

6

ChIP-seq log2(peak / negative)

P300
6ρ = 0.75

420-202

4qPCR log2(target / negative)

6

ChIP-seq log2(peak / negative)

PAX58

ρ = 0.64

6420-202

4qPCR log2(target / negative)

6

ChIP-seq log2(peak / negative)

PBX3
8

ρ = 0.76

6420-202

46qPCR log2(target / negative)

8

ChIP-seq log2(peak / negative)

RNA Pol2
6ρ = 0.7642002

46qPCR log2(target / negative)

8

ChIP-seq log2(peak / negative)

PU.1
8ρ = 0.69

642002

4qPCR log2(target / negative)

6

ChIP-seq log2(peak / negative)

SIX56

ρ = 0.79

420-4-202

46qPCR log2(target / negative)

8