BACKGROUND: The organization of eukaryotic DNA into chromatin has a strong 
influence on the accessibility and regulation of genetic information. The 
locations and occupancies of a principle component of chromatin, nucleosomes, 
are typically assayed through use of enzymatic digestion with micrococcal 
nuclease (MNase). MNase is an endo-exo nuclease that preferentially digests 
naked DNA and the DNA in linkers between nucleosomes, thus enriching for 
nucleosome-associated DNA. To determine nucleosome organization genome-wide, DNA 
remaining from MNase digestion is sequenced using high-throughput sequencing 
technologies (MNase-seq). Unfortunately, the results of MNase-seq can vary 
dramatically due to technical differences and this confounds comparisons between 
MNase-seq experiments, such as examining condition-dependent chromatin 
organizations.
RESULTS: In this study we use MNase digestion simulations to demonstrate how 
MNase-seq signals can vary for different nucleosome configuration when 
experiments are performed with different extents of MNase digestion. Signal 
variation in these simulations reveals an important DNA sampling bias that 
results from a neighborhood effect of MNase digestion techniques. The presence 
of this neighborhood effect ultimately confounds comparisons between different 
MNase-seq experiments. To address this issue we present a standardized chromatin 
preparation which controls for technical variance between MNase-based chromatin 
preparations and enables the collection of similarly sampled (matched) chromatin 
populations. Standardized preparation of chromatin includes a normalization step 
for DNA input into MNase digestions and close matching of the extent of 
digestion between each chromatin preparation using gel densitometry analysis. 
The protocol also includes directions for successful pairing with multiplex 
sequencing reactions.
CONCLUSIONS: We validated our method by comparing the experiment-to-experiment 
variation between biological replicates of chromatin preparations from S. 
cerevisiae. Results from our matched preparation consistently produced MNase-seq 
datasets that were more closely correlated than other unstandardized approaches. 
Additionally, we validated the ability of our approach at enabling accurate 
downstream comparisons of chromatin structures, by comparing the specificity of 
detecting Tup1-dependent chromatin remodeling events in comparisons between 
matched and un-matched wild-type and tup1Δ MNase-seq datasets. Our matched 
MNase-seq datasets demonstrated a significant reduction in non-specific 
(technical) differences between experiments and were able to maximize the 
detection of biologically-relevant (Tup1-dependent) changes in chromatin 
structure.