Abstract
Our recent investigation in the protist Trichomonas vaginalis suggested a DNA sequence periodicity with a unit length of 120.9 nt, which represents a sequence signature for nucleosome positioning. We now extended our observation in higher eukaryotes and identified a similar periodicity of 175 nt in length in Caenorhabditis elegans. In the process of defining the sequence compositional characteristics, we found that the 10.5-nt periodicity, the sequence signature of DNA double helix, may not be sufficient for cross-nucleosome positioning but provides essential guiding rails to facilitate positioning. We further dissected nucleosome-protected sequences and identified a strong positive purine (AG) gradient from the 5'-end to the 3'-end, and also learnt that the nucleosome-enriched regions are GC-rich as compared to the nucleosome-free sequences as purine content is positively correlated with GC content. Sequence characterization allowed us to develop a hidden Markov model (HMM) algorithm for decoding nucleosome positioning computationally, and based on a set of training data from the fifth chromosome of C. elegans, our algorithm predicted 60%-70% of the well-positioned nucleosomes, which is 15%-20% higher than random positioning. We concluded that nucleosomes are not randomly positioned on DNA sequences and yet bind to different genome regions with variable stability, well-positioned nucleosomes leave sequence signatures on DNA, and statistical positioning of nucleosomes across genome can be decoded computationally based on these sequence signatures.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 92-102 |
| Number of pages | 11 |
| Journal | Genomics, Proteomics and Bioinformatics |
| Volume | 8 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jun 2010 |
Keywords
- HMM
- Nucleosome positioning
- Periodicity
- Sequence signature
ASJC Scopus subject areas
- Biochemistry
- Molecular Biology
- Genetics
- Computational Mathematics
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