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      Empirical Relationship between Intra-Purine and Intra-Pyrimidine Differences in Conserved Gene Sequences

      PLoS ONE
      Public Library of Science

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          DNA sequences seen in the normal character-based representation appear to have a formidable mixing of the four nucleotides without any apparent order. Nucleotide frequencies and distributions in the sequences have been studied extensively, since the simple rule given by Chargaff almost a century ago that equates the total number of purines to the pyrimidines in a duplex DNA sequence. While it is difficult to trace any relationship between the bases from studies in the character representation of a DNA sequence, graphical representations may provide a clue. These novel representations of DNA sequences have been useful in providing an overview of base distribution and composition of the sequences and providing insights into many hidden structures. We report here our observation based on a graphical representation that the intra-purine and intra-pyrimidine differences in sequences of conserved genes generally follow a quadratic distribution relationship and show that this may have arisen from mutations in the sequences over evolutionary time scales. From this hitherto undescribed relationship for the gene sequences considered in this report we hypothesize that such relationships may be characteristic of these sequences and therefore could become a barrier to large scale sequence alterations that override such characteristics, perhaps through some monitoring process inbuilt in the DNA sequences. Such relationship also raises the possibility of intron sequences playing an important role in maintaining the characteristics and could be indicative of possible intron-late phenomena.

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          A codon-based model of nucleotide substitution for protein-coding DNA sequences.

          A codon-based model for the evolution of protein-coding DNA sequences is presented for use in phylogenetic estimation. A Markov process is used to describe substitutions between codons. Transition/transversion rate bias and codon usage bias are allowed in the model, and selective restraints at the protein level are accommodated using physicochemical distances between the amino acids coded for by the codons. Analyses of two data sets suggest that the new codon-based model can provide a better fit to data than can nucleotide-based models and can produce more reliable estimates of certain biologically important measures such as the transition/transversion rate ratio and the synonymous/nonsynonymous substitution rate ratio.
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            Long-range correlations in nucleotide sequences.

            DNA sequences have been analysed using models, such as an n-step Markov chain, that incorporate the possibility of short-range nucleotide correlations. We propose here a method for studying the stochastic properties of nucleotide sequences by constructing a 1:1 map of the nucleotide sequence onto a walk, which we term a 'DNA walk'. We then use the mapping to provide a quantitative measure of the correlation between nucleotides over long distances along the DNA chain. Thus we uncover in the nucleotide sequence a remarkably long-range power law correlation that implies a new scale-invariant property of DNA. We find such long-range correlations in intron-containing genes and in nontranscribed regulatory DNA sequences, but not in complementary DNA sequences or intron-less genes.
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              On the genetic basis of variation and heterogeneity of DNA base composition.

              N SUEOKA (1962)

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                28 August 2009
                : 4
                : 8
                : e6829
                [1]School of Environmental Studies, Jadavpur University, Kolkata, West Bengal, India
                Aarhus University, Denmark
                Author notes

                Conceived and designed the experiments: AN. Performed the experiments: AN. Analyzed the data: AN. Contributed reagents/materials/analysis tools: AN. Wrote the paper: AN.

                Ashesh Nandy. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                : 18 May 2009
                : 24 July 2009
                Page count
                Pages: 12
                Research Article
                Computational Biology/Evolutionary Modeling
                Molecular Biology/DNA Repair
                Molecular Biology/Molecular Evolution



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