Scaling properties and fractality in the distribution of coding segments in eukaryotic genomes revealed through a block entropy approach

Information Theory in Computational Biology: Where We Stand Today

"A Mathematical Theory of Communication" was published in 1948 by Claude Shannon to address the problems in the field of data compression and communication over (noisy) communication channels. Since then, the concepts and ideas developed in Shannon's work have formed the basis of information theory, a cornerstone of statistical learning and inference, and has been playing a key role in disciplines such as physics and thermodynamics, probability and statistics, computational sciences and biological sciences. In this article we review the basic information theory based concepts and describe their key applications in multiple major areas of research in computational biology-gene expression and transcriptomics, alignment-free sequence comparison, sequencing and error correction, genome-wide disease-gene association mapping, metabolic networks and metabolomics, and protein sequence, structure and interaction analysis.

Orphan and gene related CpG Islands follow power-law-like distributions in several genomes: evidence of function-related and taxonomy-related modes of distribution

CpG Islands (CGIs) are compositionally defined short genomic stretches, which have been studied in the human, mouse, chicken and later in several other genomes. Initially, they were assigned the role of transcriptional regulation of protein-coding genes, especially the house-keeping ones, while more recently there is found evidence that they are involved in several other functions as well, which might include regulation of the expression of RNA genes, DNA replication etc. Here, an investigation of their distributional characteristics in a variety of genomes is undertaken for both whole CGI populations as well as for CGI subsets that lie away from known genes (gene-unrelated or "orphan" CGIs). In both cases power-law-like linearity in double logarithmic scale is found. An evolutionary model, initially put forward for the explanation of a similar pattern found in gene populations is implemented. It includes segmental duplication events and eliminations of most of the duplicated CGIs, while a moderate rate of non-duplicated CGI eliminations is also applied in some cases. Simulations reproduce all the main features of the observed inter-CGI chromosomal size distributions. Our results on power-law-like linearity found in orphan CGI populations suggest that the observed distributional pattern is independent of the analogous pattern that protein coding segments were reported to follow. The power-law-like patterns in the genomic distributions of CGIs described herein are found to be compatible with several other features of the composition, abundance or functional role of CGIs reported in the current literature across several genomes, on the basis of the proposed evolutionary model.

Conserved noncoding elements follow power-law-like distributions in several genomes as a result of genome dynamics

Conserved, ultraconserved and other classes of constrained elements (collectively referred as CNEs here), identified by comparative genomics in a wide variety of genomes, are non-randomly distributed across chromosomes. These elements are defined using various degrees of conservation between organisms and several thresholds of minimal length. We here investigate the chromosomal distribution of CNEs by studying the statistical properties of distances between consecutive CNEs. We find widespread power-law-like distributions, i.e. linearity in double logarithmic scale, in the inter-CNE distances, a feature which is connected with fractality and self-similarity. Given that CNEs are often found to be spatially associated with genes, especially with those that regulate developmental processes, we verify by appropriate gene masking that a power-law-like pattern emerges irrespectively of whether elements found close or inside genes are excluded or not. An evolutionary model is put forward for the understanding of these findings that includes segmental or whole genome duplication events and eliminations (loss) of most of the duplicated CNEs. Simulations reproduce the main features of the observed size distributions. Power-law-like patterns in the genomic distributions of CNEs are in accordance with current knowledge about their evolutionary history in several genomes.

Information theory applications for biological sequence analysis

Information theory (IT) addresses the analysis of communication systems and has been widely applied in molecular biology. In particular, alignment-free sequence analysis and comparison greatly benefited from concepts derived from IT, such as entropy and mutual information. This review covers several aspects of IT applications, ranging from genome global analysis and comparison, including block-entropy estimation and resolution-free metrics based on iterative maps, to local analysis, comprising the classification of motifs, prediction of transcription factor binding sites and sequence characterization based on linguistic complexity and entropic profiles. IT has also been applied to high-level correlations that combine DNA, RNA or protein features with sequence-independent properties, such as gene mapping and phenotype analysis, and has also provided models based on communication systems theory to describe information transmission channels at the cell level and also during evolutionary processes. While not exhaustive, this review attempts to categorize existing methods and to indicate their relation with broader transversal topics such as genomic signatures, data compression and complexity, time series analysis and phylogenetic classification, providing a resource for future developments in this promising area.