Sequence-dependent nucleosome formation in trinucleotide repeats evaluated by in vivo chemical mapping

Trinucleotide repeat sequences (TRSs), consisting of 10 unique classes of repeats in DNA, are members of microsatellites and abundantly and non-randomly distributed in many eukaryotic genomes. The lengths of TRSs are mutable, and the expansions of several TRSs are implicated in hereditary neurological diseases. However, the underlying causes of the biased distribution and the dynamic properties of TRSs in the genome remain elusive. Here, we examined the effects of TRSs on nucleosome formation in vivo by histone H4-S47C site-directed chemical cleavages, using well-defined yeast minichromosomes in which each of the ten TRS classes resided in the central region of a positioned nucleosome. We showed that (AAT)₁₂ and (ACT)₁₂ act as strong nucleosome-promoting sequences, while (AGG)₁₂ and (CCG)₁₂ act as nucleosome-excluding sequences in vivo. The local histone binding affinity scores support the idea that nucleosome formation in TRSs, except for (AGG)₁₂, is mainly determined by the affinity for the histone octamers. Overall, our study presents a framework for understanding the nucleosome-forming abilities of TRSs.

Computational discovery of feature patterns in nucleosomal DNA sequences

The identification of important factors that affect nucleosome formation is critical to clarify nucleosome-forming mechanisms and the role of the nucleosome in gene regulation. Various features reported in the literature led to our hypothesis that multiple features can together contribute to nucleosome formation. Therefore, we compiled 779 features and developed a pattern discovery and scoring algorithm FFN (Finding Features for Nucleosomes) to identify feature patterns that are differentially enriched in nucleosome-forming sequences and nucleosome-depletion sequences. Applying FFN to genome-wide nucleosome occupancy data in yeast and human, we identified statistically significant feature patterns that may influence nucleosome formation, many of which are common to the two species. We found that both sequence and structural features are important in nucleosome occupancy prediction. We discovered that, even for the same feature combinations, variations in feature values may lead to differences in predictive power. We demonstrated that the identified feature patterns could be used to assist nucleosomal sequence prediction.