NucTools: analysis of chromatin feature occupancy profiles from high-throughput sequencing data

Area of Science:

• Genomics
• Epigenetics
• Computational Biology

Background:

• High-throughput sequencing generates vast genomic data, often analyzed as binary presence/absence of chromatin features.
• Continuous chromatin landscapes like nucleosome occupancy are challenging to analyze and integrate with discrete features.

Purpose of the Study:

• To introduce NucTools, a suite for downstream analysis of deep sequencing data centered on nucleosome occupancy.
• To enable integration of continuous nucleosome data with discrete chromatin features for comprehensive analysis.

Main Methods:

• NucTools suite of Perl scripts with MATLAB and R visualization programs.
• Accounts for continuous nucleosome occupancy distributions.
• Facilitates annotation with transcription factor binding, histone modifications, and DNA methylation.

Main Results:

• Calculates averaged nucleosome occupancy profiles across replicates.
• Enables comparison of nucleosome landscapes between experimental conditions.
• Estimates changes in chromatin properties like nucleosome repeat length.

Conclusions:

• NucTools reveals interplay between nucleosome positioning and features like CTCF binding and epigenetic marks (e.g., K9me2).
• Demonstrates applications in comparing mouse embryonic stem cell and fibroblast datasets.
• Addresses inter-replicate variability in MNase-seq experiments.