Informational parameters of nucleic acid and molecular evolution

Affinity and Correlation in DNA

A statistical analysis of important DNA sequences and related proteins has been performed to study the relationships between monomers, and some general considerations about these macromolecules can be provided from the results. First, the most important relationship between sites in all the DNA sequences examined is that between two consecutive base pairs. This is an indication of an energetic stabilization due to the stacking interaction of these couples of base pairs. Secondly, the difference between human chromosome sequences and their coding parts is relevant both in the relationships between sites and in some specific compositional rules, such as the second Chargaff rule. Third, the evidence of the relationship in two successive triplets of DNA coding sequences generates a relationship between two successive amino acids in the proteins. This is obviously impossible if all the relationships between the sites are statistical evidence and do not involve causes; therefore, in this article, due to stacking interactions and this relationship in coding sequences, we will divide the concept of the relationship between sites into two concepts: affinity and correlation, the first with physical causes and the second without. Finally, from the statistical analyses carried out, it will emerge that the human genome is uniform, with the only significant exception being the Y chromosome.

Origin, Evolution and Stability of Overlapping Genes in Viruses: A Systematic Review

During their long evolutionary history viruses generated many proteins de novo by a mechanism called “overprinting”. Overprinting is a process in which critical nucleotide substitutions in a pre-existing gene can induce the expression of a novel protein by translation of an alternative open reading frame (ORF). Overlapping genes represent an intriguing example of adaptive conflict, because they simultaneously encode two proteins whose freedom to change is constrained by each other. However, overlapping genes are also a source of genetic novelties, as the constraints under which alternative ORFs evolve can give rise to proteins with unusual sequence properties, most importantly the potential for novel functions. Starting with the discovery of overlapping genes in phages infecting Escherichia coli, this review covers a range of studies dealing with detection of overlapping genes in small eukaryotic viruses (genomic length below 30 kb) and recognition of their critical role in the evolution of pathogenicity. Origin of overlapping genes, what factors favor their birth and retention, and how they manage their inherent adaptive conflict are extensively reviewed. Special attention is paid to the assembly of overlapping genes into ad hoc databases, suitable for future studies, and to the development of statistical methods for exploring viral genome sequences in search of undiscovered overlaps.

An analysis and prediction of nucleosome positioning based on information content

Nucleosome positioning plays a key role in the regulation of many biological processes. In this study, the statistical difference of information content was investigated in nucleosome and linker DNA regions across eukaryotic organisms. By analyzing the information redundancy, D k , in Saccharomyces cerevisiae, Drosophila melanogaster, and Caenorhabditis elegans genomes, the short-range dominance of nucleotide correlation in nucleosome and linker DNA regions was confirmed. Significant difference of the D k value between the nucleosome and linker DNA regions was also found. The underlying reason for many successful oligonucleotide-based predictions of nucleosome positioning in eukaryotic model organisms may be attributed to the short-range dominance of nucleotide correlation in the nucleosome and linker DNA regions. When applying power spectrum analysis to the nucleosome and linker DNA regions, some obvious differences in sequence periodic signals were observed. The parameter F k was introduced to describe particular base correlation. Furthermore, the support vector machine combining F k was used to classify nucleosome and linker DNA regions in Homo sapiens, Oryzias latipes, C. elegans, Candida albicans, and S. cerevisiae. Independent test demonstrated that a good performance can be achieved by using this algorithm. This result further revealed that base correlation information has an important role in nucleosome positioning.

A representation of DNA primary sequences by random walk

We describe the DNA primary sequences by random walk. With the description, two random sequences {Y(m)} and {X(n)} corresponding to a DNA sequence, as well as graphical representations of DNA sequences are given. We further prove that two random sequences {Y(m)} and {X(n)} are both Markov chains. Based on transition probability distributions of Markov chains, some numerical characterizations of random sequences, we introduce some new invariants for the DNA primary sequences. Then using these invariants, we make comparisons among primary sequences for exon 1 of beta-globin genes belonging to nine species for analysis of the similarity and dissimilarity.

Entropy of protein sequences: an integral approach

Several classifications of protein spatial structures and their structural elements are known. This makes revealing of the relation between these structural elements and sequence fragments rather topical. The most important move in this direction would be the determination of positional sensitivity levels and ranges between the residues in protein sequences. In this work the Shannon-Weaver informational entropy was used as a disorder criterion for solving this problem. This entropy was computed as function of the distance between the amino acid residues in different sets of unhomological protein sequences. Similarity of this function for different sets of protein sequences was shown. Analysis of informational entropy allows detecting a long-range positional correlation (> or =30) between the amino acid residues and oscillations with periods of 3.6 and 2.9. These oscillation periods correspond to periodicity of alpha- and 3(10)-helices.

Fuzzy classification of nucleotide sequences and bacterial evolution

A new method for reconstructing evolutionary relationship among bacteria by use of rRNA sequence data is proposed. The method is based on the concept of fuzzy classification of probabilities p(i), p(i/j) and p(i/j*) (i = A, G, C, U) of each sequence. The resulting partition tree shares common features of previous works but has some new peculiarities.

A stochastic evolutionary model of molecular sequences

A stochastic evolutionary model of molecular sequences is proposed. The basic forces in evolution are supposed to be mutation and selection. The concept is somewhat similar to Kauffman-Levin's concept of adaptive walks and corresponding analytical expressions have been developed. The selective force is divided into two parts: a slowly-varying part and a rapidly-changing fluctuation. The latter influences the distribution of sequences and results in an equation of motion along the flow line. The former plays a more important role in the emergence of evolutionary order. It is demonstrated that the asymmetry of selective forces would lead to a definite order of the system.

The statistical correlation of nucleotides in protein-coding DNA sequences

The statistical correlation of nucleotides in a DNA sequence is described by a set of redundancies D1, D2, D3, . . . . By calculation of [Dn] of 2341 coding regions of nucleic acid sequences it is demonstrated that about 2/3 of sequences has correlation length less than or equal to 2, 10% of sequences--correlation with 3-periodicity and others--long range aperiodic correlations. The implications of the results from the interactions of random mutation and natural selection are discussed briefly.