We propose and study a duplication-innovation-loss model of genome evolution taking into account biological roles of constituent genes . In our model numbers of genes in different functional categories are coupled to each other. For example, an increase in the number of metabolic enzymes in a genome is usually accompanied by addition of new transcription factors regulating these enzymes. Such coupling can be thought of as a proportional "recipe" for genome composition of the type "a spoonful of sugar for each egg yolk". The model jointly reproduces two known empirical scaling laws: the scale-free distribution of family sizes and the nonlinear scaling of the number of genes in certain functional categories  with genome size. In addition, it allows us to derive a novel relation between the exponents characterizing these two scaling laws. This mathematical property of our model was subsequently confirmed in real-life prokaryotic genomes. To further support the assumptions of our model we present an empirical evidence of correlations between functional repertoires of prokaryotic genomes. The overall pattern of these correlations remains mostly unchanged when large and small genomes are analyzed separately. This hints at universality of biological mechanisms shaping up prokaryotic genomes irrespective of their size .
We propose and study a duplication-innovation-loss model of genome evolution taking into account biological roles of genes and their constituent domains . In our model numbers of genes in different functional categories are coupled to each other. For example, an increase in the number of metabolic enzymes in a genome is usually accompanied by addition of new transcription factors regulating these enzymes. Such coupling can be thought of as a proportional "recipe" for genome composition of the type "a spoonful of sugar for each egg yolk". The model jointly reproduces two known empirical laws: the powerlaw distribution of family sizes and the nonlinear scaling of the number of genes in certain functional categories (e.g. transcription factors) with genome size. In addition, it allows us to derive a novel relation between the exponents characterizing these two scaling laws. It predicts that functional categories that grow faster-than-linearly with genome size to be characterized by flatter-than-average family size distributions. This exponent relation is subsequently confirmed by our bioinformatics analysis of prokaryotic genomes .
R
constituent genes
genes and their constituent domains
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scaling
R
scale-free
powerlaw
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(e.g. transcription factors)
R
This mathematical property of our model was subsequently confirmed in real-life prokaryotic genomes. To further support the assumptions of our model we present an empirical evidence of correlations between functional repertoires of prokaryotic genomes. The overall pattern of these correlations remains mostly unchanged when large and small genomes are analyzed separately. This hints at universality of biological mechanisms shaping up prokaryotic genomes irrespective of their size
It predicts that functional categories that grow faster-than-linearly with genome size to be characterized by flatter-than-average family size distributions. This exponent relation is subsequently confirmed by our bioinformatics analysis of prokaryotic genomes