Quantitative ‘laws’ of genome evolution: the interplay of stochasticity and selection
Prof.Eugene V. KOONIN
(National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda MD, USA & IHÉS)
Amphithéâtre Léon Motchane (IHES)
Amphithéâtre Léon Motchane
35, route de Chartres
Research in quantitative evolutionary genomics and systems biology led to the discovery of several universal regularities connecting genomic and molecular phenomic variables. These universals include the log-normal distribution of the evolutionary rates of orthologous genes; the power law-like distributions of paralogous family size and node degree in various biological networks; the negative correlation between a gene’s sequence evolution rate and expression level; and differential scaling of functional classes of genes with genome size. The universals of genome evolution can be accounted for by simple mathematical models similar to those used in statistical physics, such as the birth-death-innovation model. These ‘laws’ of evolutionary genomics, analogously to the laws of statistical physics, appear to emerge from the Maximum Entropy principle which dictates that the probability distribution of any variable in a large ensemble of data or measurements tends to the distribution with the maximum entropy within the applicable constraints. In the case of genome evolution, these constraints are readily interpretable as effects of purifying selection against gene malfunction.