Comparison of sample preparation methods for ChIP-chip assays

被引:107
|
作者
O'Geen, Henriette
Nicolet, Charles M.
Blahnik, Kim
Green, Roland
Farnham, Peggy J.
机构
[1] Univ Calif Davis, Genome & Biomed Sci Facil, Davis, CA 95616 USA
[2] NimbleGen Syst Inc, Madison, WI USA
关键词
D O I
10.2144/000112268
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
A single chromatin immunoprecipitation (ChIP) sample does not provide enough DNA for hybridization to a genomic tiling array. A commonly used technique for amplifying the DNA obtained from ChIP assays is ligation-mediated PCR (LM-PCR). However using this amplification method, we could not identify Oct4 binding sites on genomic tiling arrays representing 1% of the human genome (ENCODE arrays). In contrast, hybridization of a pool of 10 ChIP samples to the arrays produced reproducible binding patterns and low background signals. However the pooling method would greatly increase the number of ChIP reactions needed to analyze the entire human genome. Therefore, we have adapted the GenomePlex (R) whole genome amplification (WGA) method for use in ChIP-chip assays; detailed ChIP and amplification protocols used for these analyses are provided as supplementary material. When applied to ENCODE arrays, the products prepared using this new method resulted in an Oct4 binding pattern similar to that from the pooled Oct4 ChIP samples. Importantly, the signal-to-noise ratio using the GenomePlex WGA method is superior to the LM-PCR amplification method.
引用
收藏
页码:577 / 580
页数:4
相关论文
共 50 条
  • [31] Quantized correlation coefficient for measuring reproducibility of ChIP-chip data
    Shouyong Peng
    Mitzi I Kuroda
    Peter J Park
    BMC Bioinformatics, 11
  • [32] Parameter estimation for robust HMM analysis of ChIP-chip data
    Peter Humburg
    David Bulger
    Glenn Stone
    BMC Bioinformatics, 9
  • [33] Quantitative Visualization of ChIP-chip Data by Using Linked Views
    Huang, Min-Yu
    Weber, Gunther H.
    Li, Xiao-Yong
    Biggin, Mark D.
    Hamann, Bernd
    2010 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE WORKSHOPS (BIBMW), 2010, : 195 - 200
  • [34] Statistics for ChIP-chip and DNase hypersensitivity experiments on NimbleGen arrays
    Scacheri, Peter C.
    Crawford, Gregory E.
    Davis, Sean
    DNA MICROARRAYS, PART B: DATABASES AND STATISTICS, 2006, 411 : 270 - +
  • [35] Bayesian modeling of ChIP-chip data using latent variables
    Mingqi Wu
    Faming Liang
    Yanan Tian
    BMC Bioinformatics, 10
  • [36] Ringo – an R/Bioconductor package for analyzing ChIP-chip readouts
    Joern Toedling
    Oleg Sklyar
    Wolfgang Huber
    BMC Bioinformatics, 8
  • [37] A boosting approach for motif modeling using ChIP-chip data
    Hong, PY
    Liu, XS
    Zhou, Q
    Lu, X
    Liu, JS
    Wong, WH
    BIOINFORMATICS, 2005, 21 (11) : 2636 - 2643
  • [38] Bayesian modeling of ChIP-chip data using latent variables
    Wu, Mingqi
    Liang, Faming
    Tian, Yanan
    BMC BIOINFORMATICS, 2009, 10
  • [39] Computational Reconstruction of Transcriptional Relationships from ChIP-Chip Data
    Ngoc Tu Le
    Tu Bao Ho
    Bich Hai Ho
    IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2013, 10 (02) : 300 - 307
  • [40] Membrane based sample preparation chip
    Morschhauser, A.
    Stiehl, C.
    Grosse, A.
    Nestler, J.
    Otto, T.
    Gessner, T.
    BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK, 2012, 57 : 923 - 925