Sequence Signatures of Nucleosome Positioning in Caenorhabditis elegans

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.

The Transcript-centric Mutations in Human Genomes

Since the human genome is mostly transcribed, genetic variations must exhibit sequence signatures reflecting the relationship between transcription processes and chromosomal structures as we have observed in unicellular or- ganisms. In this study, a set of 646 ubiquitous expression-invariable genes （EIGs） which are present in germline cells were defined and examined based on RNA-sequencing data from multiple high-throughput transcriptomic data. We demonstrated a relationship between gene expression level and transcript-centric mutations in the human genome based on single nucleotide polymorphism （SNP） data. A significant positive correlation was shown be- tween gene expression and mutation, where highly-expressed genes accumulate more mutations than low- ly-expressed genes. Furthermore, we found four major types of transcript-centric mutations： C---~T, A---~G; C---~ and G--~T in human genomes and identified a negative gradient of the sequence variations aligning from the 5＇ end to the 3＇ end of the transcription units （TUs）. The periodical occurrence of these genetic variations across TUs is associated with nucleosome phasing. We propose that transcript-centric mutations are one of the major driving forces for gene and genome evolution along with creation of new genes, gene/genome duplication, and horizontal gene transfer.