CpG-poor Promoters Research Articles

Generalizations of Markov model to characterize biological sequences

BackgroundThe currently used kth order Markov models estimate the probability of generating a single nucleotide conditional upon the immediately preceding (gap = 0) k units. However, this neither takes into account the joint dependency of multiple neighboring nucleotides, nor does it consider the long range dependency with gap>0.ResultWe describe a configurable tool to explore generalizations of the standard Markov model. We evaluated whether the sequence classification accuracy can be improved by using an alternative set of model parameters. The evaluation was done on four classes of biological sequences – CpG-poor promoters, all promoters, exons and nucleosome positioning sequences. Using di- and tri-nucleotide as the model unit significantly improved the sequence classification accuracy relative to the standard single nucleotide model. In the case of nucleosome positioning sequences, optimal accuracy was achieved at a gap length of 4. Furthermore in the plot of classification accuracy versus the gap, a periodicity of 10–11 bps was observed which might indicate structural preferences in the nucleosome positioning sequence. The tool is implemented in Java and is available for download at .ConclusionMarkov modeling is an important component of many sequence analysis tools. We have extended the standard Markov model to incorporate joint and long range dependencies between the sequence elements. The proposed generalizations of the Markov model are likely to improve the overall accuracy of sequence analysis tools.

The human DNA methyltransferases DNMT3A and DNMT3B have two types of promoters with different CpG contents

DNA modification that is established by de novo methylation is involved in the epigenetic control of genome functions. The DNMT3A and DNMT3B genes encode putative de novo methyltransferases. In this paper, we investigated the transcriptional regulatory regions of the human DNMT3A and DNMT3B genes. We found that the DNMT3A and DNMT3B genes have multiple transcriptional start points (TSPs) that are separated on the chromosome and the expressions of these genes are controlled by multiple promoters. The DNMT3A gene has at least four TSPs and the expression is controlled by three different promoters. All three promoters lack typical TATA sequences adjacent to the TSPs. Two of them bear CpG-rich promoters and the other a CpG-poor promoter. The DNMT3B gene has at least two TSPs which exist in different exons and the expression is controlled by different promoters. Both promoter regions of the DNMT3B gene lack typical TATA sequences, where one promoter contains a CpG-rich area near the TSP, the other promoter is CpG-poor. Together with the data that the human DNMT1 gene has both CpG-rich and CpG-poor promoters, it is suggested that transcriptional regulation by two types of promoters, CpG-rich and CpG-poor, might be common characteristics in the DNMT gene family.