Searcharxiv⌕ Search

arXiv subjects

Dmitri V. Parkhomchuk

Publications and source records attributed to Dmitri V. Parkhomchuk.

3 recordsLinked to original sources

Darwinian Genetic Drift

Genetic drift is stochastic fluctuations of alleles frequencies in a population due to sampling effects. We consider a model of drift in an equilibrium population, with high mutation rates: few functional mutations per generation. Such mutation rates are common in multicellular organisms including humans, however they are not explicitly considered in most population genetics models. Under these assumptions the drift shows properties distinct from the classical drift models, which ignore realistic mutation rates: i) All (non-lethal) variants of a site have a characteristic average frequencies, which are independent of population size, however the magnitude of fluctuations around these frequencies depends on population size. ii) There is no "mutational meltdown" due to "low efficiency of selection" for small population size. Population average fitness does not depend on population size. iii) Drift (and molecular clock) can be represented as wandering by compensatory mutations, postulate of neutral mutations is not necessary for explaining the high rate of mutation accumulation. Our results, which adjust the meaning of the neutral theory from the individual neutrality of the majority of mutations, to the collective neutrality of compensatory mutations, are applicable to investigations in phylogeny and coalescent and for GWAS design and analysis.

q-bio.PE↗

Drake's Rule as a Consequence of Approaching Channel Capacity

How mutations accumulate in genomes is the central question of molecular evolution theories, however our understanding of this process is far from complete. Drake's rule is a notoriously universal property of genomes from microbes to mammals - the number of (functional) mutations per-genome per-generation is approximately constant within a phylum, despite orders of magnitude differences in genome sizes and diverse populations properties. So far there is no concise explanation for this phenomenon. A formal model of storage of genetic information suggests that a genome of any species operates near its maximum informational storage capacity, and the mutation rate is near its upper limit, providing a simple explanation for the rule with minimal assumptions.

q-bio.PE↗

Information Theory of Genomes

Relation of genome sizes to organisms complexity is still described rather equivocally. Neither the number of genes (G-value), nor the total amount of DNA (C-value) correlates consistently with phenotype complexity. Using information theory considerations we developed a model that allows a quantative estimate for the amount of functional information in a genomic sequence. This model easily answers the long-standing question of why GC content is increased in functional regions. The model allows consistent estimate of genome complexities, resolving the major discrepancies of G- and C-values. For related organisms with similarly complex phenotypes, this estimate provides biological insights into their niches complexities. This theoretical framework suggests that biological information can rapidly evolve on demand from environment, mainly in non-coding genomic sequence and explains the role of duplications in the evolution of biological information. Knowing the approximate amount of functionality in a genomic sequence is useful for many applications such as phylogenetics analyses, in-silico functional elements discovery or prioritising targets for genotyping and sequencing.

q-bio.GN↗