title: Protein family and fold occurrence in genomes: power-law behaviour and evolutionary model.
abstract: Global surveys of genomes measure the usage of essential molecular parts, defined here as protein families, superfamilies or folds, in different organisms. Based on surveys of the first 20 completely sequenced genomes, we observe that the occurrence of these parts follows a power-law distribution. That is, the number of distinct parts (F) with a given genomic occurrence (V) decays as F=aV(-b), with a few parts occurring many times and most occurring infrequently. For a given organism, the distributions of families, superfamilies and folds are nearly identical, and this is reflected in the size of the decay exponent b. Moreover, the exponent varies between different organisms, with those of smaller genomes displaying a steeper decay (i.e. larger b). Clearly, the power law indicates a preference to duplicate genes that encode for molecular parts which are already common. Here, we present a minimal, but biologically meaningful model that accurately describes the observed power law. Although the model performs equally well for all three protein classes, we focus on the occurrence of folds in preference to families and superfamilies. This is because folds are comparatively insensitive to the effects of point mutations that can cause a family member to diverge beyond detectable similarity. In the model, genomes evolve through two basic operations: (i) duplication of existing genes; (ii) net flow of new genes. The flow term is closely related to the exponent b and can accommodate considerable gene loss; however, we demonstrate that the observed data is reproduced best with a net inflow, i.e. with more gene gain than loss. Moreover, we show that prokaryotes have much higher rates of gene acquisition than eukaryotes, probably reflecting lateral transfer. A further natural outcome from our model is an estimation of the fold composition of the initial genome, which potentially relates to the common ancestor for modern organisms. Supplementary material pertaining to this work is available from www.partslist.org/powerlaw.
authors.affiliation: Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Avenue, New Haven, CT 06520-8114, USA.
authors.forename: J
authors.initials: J
authors.lastname: Qian
authors.forename: N M
authors.initials: NM
authors.lastname: Luscombe
authors.forename: M
authors.initials: M
authors.lastname: Gerstein
mesh_terms: D000818:Animals; D019295:Computational Biology; D003198:Computer Simulation; D019143:Evolution, Molecular; D020131:Genes, Duplicate / Q000235:genetics; D016678:Genome; D006801:Humans; D008957:Models, Genetic; D005810:Multigene Family / Q000235:genetics; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000145:classification / Q000235:genetics* / Q000378:metabolism; D020543:Proteome
chemical_list: D011506:Proteins; D020543:Proteome