Mapping of transcription factor binding regions in mammalian cells by ChIP: comparison of array- and sequencing-based technologies

• Published in: Genome Research Vol. 17; no. 6; pp. 898 - 909
• Main Authors: Euskirchen, Ghia M, Rozowsky, Joel S, Wei, Chia-Lin, Lee, Wah Heng, Zhang, Zhengdong D, Hartman, Stephen, Emanuelsson, Olof, Stolc, Viktor, Weissman, Sherman, Gerstein, Mark B, Ruan, Yijun, Snyder, Michael
• Format: Journal Article
• Language: English
• Published: United States Cold Spring Harbor Laboratory Press 01.06.2007
• Subjects: Animals; Binding Sites - genetics; CDNA MICROARRAY; CHROMATIN-IMMUNOPRECIPITATION; EMBRYONIC STEM-CELLS; GENE-EXPRESSION; Genome, Human; HeLa Cells; HUMAN GENOME; HUMAN-CHROMOSOME-22; Humans; IDENTIFICATION; Methods; MICROARRAY ANALYSIS; Microfluidic Analytical Techniques; Oligonucleotide Array Sequence Analysis; OLIGONUCLEOTIDE ARRAYS; Sequence Analysis, DNA; SITES; STAT1 Transcription Factor - genetics; Human; Sequence Analysis; Genome; DNA
• ISSN: 1088-9051; 1549-5469; 1549-5469; 1549-5477
• DOI: 10.1101/gr.5583007

Recent progress in mapping transcription factor (TF) binding regions can largely be credited to chromatin immunoprecipitation (ChIP) technologies. We compared strategies for mapping TF binding regions in mammalian cells using two different ChIP schemes: ChIP with DNA microarray analysis (ChIP-chip) and ChIP with DNA sequencing (ChIP-PET). We first investigated parameters central to obtaining robust ChIP-chip data sets by analyzing STAT1 targets in the ENCODE regions of the human genome, and then compared ChIP-chip to ChIP-PET. We devised methods for scoring and comparing results among various tiling arrays and examined parameters such as DNA microarray format, oligonucleotide length, hybridization conditions, and the use of competitor Cot-1 DNA. The best performance was achieved with high-density oligonucleotide arrays, oligonucleotides >/=50 bases (b), the presence of competitor Cot-1 DNA and hybridizations conducted in microfluidics stations. When target identification was evaluated as a function of array number, 80%-86% of targets were identified with three or more arrays. Comparison of ChIP-chip with ChIP-PET revealed strong agreement for the highest ranked targets with less overlap for the low ranked targets. With advantages and disadvantages unique to each approach, we found that ChIP-chip and ChIP-PET are frequently complementary in their relative abilities to detect STAT1 targets for the lower ranked targets; each method detected validated targets that were missed by the other method. The most comprehensive list of STAT1 binding regions is obtained by merging results from ChIP-chip and ChIP-sequencing. Overall, this study provides information for robust identification, scoring, and validation of TF targets using ChIP-based technologies.