Quantifying ChIP-seq data: a spiking method providing an internal reference for sample-to-sample normalization

Abstract

Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) experiments are widely used to determine, within entire genomes, the occupancy sites of any protein of interest, including, for example, transcription factors, RNA polymerases, or histones with or without various modifications. In addition to allowing the determination of occupancy sites within one cell type and under one condition, this method allows, in principle, the establishment and comparison of occupancy maps in various cell types, tissues, and conditions. Such comparisons require, however, that samples be normalized. Widely used normalization methods that include a quantile normalization step perform well when factor occupancy varies at a subset of sites, but may miss uniform genome-wide increases or decreases in site occupancy. We describe a spike adjustment procedure (SAP) that, unlike commonly used normalization methods intervening at the analysis stage, entails an experimental step prior to immunoprecipitation. A constant, low amount from a single batch of chromatin of a foreign genome is added to the experimental chromatin. This “spike” chromatin then serves as an internal control to which the experimental signals can be adjusted. We show that the method improves similarity between replicates and reveals biological differences including global and largely uniform changes.

Diurnal regulation of RNA polymerase III transcription is under the control of both the feeding–fasting response and the circadian clock

“…4B). This observation is consistent with previous results obtained in Maf1 KO mouse liver (Bonhoure et al 2014) and with the recent observation that MAF1 is a chronic repressor of Pol III in human cells (Orioli et al 2016). Moreover, the Pol III occupancy pattern at the different time points showed an increase at the end of the day and beginning of the night (Fig.…”

“…The samples were spiked with a small, constant amount of human chromatin for sample-to-sample normalization (Bonhoure et al 2014). We analyzed a set of loci either annotated as Pol III genes in the genome assembly or found significantly occupied by Pol III in one of our previous ChIP-seq analyses (Canella 2012;Bonhoure et al 2014;Renaud 2014). Among these loci, we selected those significantly occupied by Pol III in at least one sample in one of the conditions.…”

“…Preparation of chromatin immunoprecipitation and libraries, high-throughput sequencing, and Pol III occupancy score calculations are as described in Bonhoure et al (2014).…”

Loss of the RNA polymerase III repressor MAF1 confers obesity resistance

“…These molecules are short-lived and are widely used to assess the level of transcription by RNA Pol III (Upadhya et al 2002;Michels et al 2010). Consistent with the increase in polymerase occupancy of Pol III genes in Maf1 −/− tissue (Bonhoure et al 2014), pre-tRNA-specific reads representing >100 different tRNA genes were markedly increased in the knockout ( Fig. 5A; Supplemental Table S3).…”

tRNA biology in the omics era: Stress signalling dynamics and cancer progression

“…Compared to lower eukaryotes, the functional annotation of large and complex mammalian genomes makes mapping of Pol III reads a much more complicated task, which was only recently addressed in a multiplicity of ChIP-seq studies [20][21][22][23][24][25][26][27][28][29][30][31]. Thanks to the gradual improvement in sequencing technologies and downstream analysis platforms, Pol III and its general transcription factors Brf1, Brf2, Bdp1 and TFIIIC were mapped in both the mouse and human genomes.…”