Systematic evaluation of variability in ChIP-chip experiments using predefined DNA targets

Abstract

The most widely used method for detecting genome-wide protein–DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and “spike-ins” comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols, and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated.

Evaluation of affinity-based genome-wide DNA methylation data: Effects of CpG density, amplification bias, and copy number variation

“…It is well established that the GC content of a DNA template can affect the efficiency of amplification, often resulting in a bias against the GC-rich regions of the genome (Bredel et al 2005;Pugh et al 2008;Teo et al 2008). Johnson et al (2008) also report a significant drop in sensitivity, most notably for Affymetrix tiling arrays, when amplified DNA is hybridized. Amplification bias is perhaps even more of a potential concern in DNA methylation mapping, since CpG islands are GC-rich by their very nature and therefore more prone to any extant bias.…”

“…Chromatin immunoprecipitation (ChIP) has been used extensively to study protein-DNA interactions (Ren et al 2000), and recently, an extensive benchmarking study has been conducted comparing microarray platforms and analysis methods ( Johnson et al 2008). Comparison studies for DNA methylation platforms are now starting to emerge (Li et al 2010).…”

Discovery and verification of functional single nucleotide polymorphisms in regulatory genomic regions: Current and developing technologies

“…Discovery methods such as ChIP-chip are powerful because they allow genomic scale identification of both known and novel DNA binding sites. Encouragingly, a recent independent and blind test of different ChIP-chip platforms using the same DNA samples with "spiked-in" targets found that ChIP-chip was very reproducible, where variation tended to result from lab, protocol, and computational algorithm differences [84]. However, ChIP-chip detection limit is somewhat sensitive to protein expression levels and may be influenced by protein-protein interactions such as competitive DNA binding of other proteins [83].…”

Epigenetics meets next-generation sequencing

“…[8][9][10][11][12] In order to estimate binding locations, these methods use various smoothing techniques to reduce noise in the data and search for regions in which consecutive probes along the chromosomes give consistent signals. 13 …”