Genome-wide prediction of nucleosome occupancy in maize reveals plant chromatin structural features at genes and other elements at multiple scales.

The nucleosome is a fundamental structural and functional chromatin unit that affects nearly all DNA-templated events in eukaryotic genomes. It is also a biochemical substrate for higher order, cis-acting gene expression codes and the monomeric structural unit for chromatin packaging at multiple scales. To predict the nucleosome landscape of a model plant genome, we used a support vector machine computational algorithm trained on human chromatin to predict the nucleosome occupancy likelihood (NOL) across the maize (Zea mays) genome. Experimentally validated NOL plots provide a novel genomic annotation that highlights gene structures, repetitive elements, and chromosome-scale domains likely to reflect regional gene density. We established a new genome browser (http://www.genomaize.org) for viewing support vector machine-based NOL scores. This annotation provides sequence-based comprehensive coverage across the entire genome, including repetitive genomic regions typically excluded from experimental genomics data. We find that transposable elements often displayed family-specific NOL profiles that included distinct regions, especially near their termini, predicted to have strong affinities for nucleosomes. We examined transcription start site consensus NOL plots for maize gene sets and discovered that most maize genes display a typical +1 nucleosome positioning signal just downstream of the start site but not upstream. This overall lack of a -1 nucleosome positioning signal was also predicted by our method for Arabidopsis (Arabidopsis thaliana) genes and verified by additional analysis of previously published Arabidopsis MNase-Seq data, revealing a general feature of plant promoters. Our study advances plant chromatin research by defining the potential contribution of the DNA sequence to observed nucleosome positioning and provides an invariant baseline annotation against which other genomic data can be compared.