SCIENCE@home

Optimization of transcription factor binding map accuracy utilizing knockout-mouse models

Wolfgang Krebs,S. Schmidt,A. Goren,D. De Nardo,L. Labzin,Anton Bovier,T. Ulas,Heidi Theis,Michael Kraut,E. Latz,M. Beyer,J. Schultze

Published 2014 in Nucleic Acids Research

ABSTRACT

Genome-wide assessment of protein–DNA interaction by chromatin immunoprecipitation followed by massive parallel sequencing (ChIP-seq) is a key technology for studying transcription factor (TF) localization and regulation of gene expression. Signal-to-noise-ratio and signal specificity in ChIP-seq studies depend on many variables, including antibody affinity and specificity. Thus far, efforts to improve antibody reagents for ChIP-seq experiments have focused mainly on generating higher quality antibodies. Here we introduce KOIN (knockout implemented normalization) as a novel strategy to increase signal specificity and reduce noise by using TF knockout mice as a critical control for ChIP-seq data experiments. Additionally, KOIN can identify ‘hyper ChIPable regions’ as another source of false-positive signals. As the use of the KOIN algorithm reduces false-positive results and thereby prevents misinterpretation of ChIP-seq data, it should be considered as the gold standard for future ChIP-seq analyses, particularly when developing ChIP-assays with novel antibody reagents.

PUBLICATION RECORD

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-33 of 33 references · Page 1 of 1

CITED BY

Showing 1-25 of 25 citing papers · Page 1 of 1