title: Systematic analysis of compositional order of proteins reveals new characteristics of biological functions and a universal correlate of macroevolution.
abstract: We present a novel analysis of compositional order (CO) based on the occurrence of Frequent amino-acid Triplets (FTs) that appear much more than random in protein sequences. The method captures all types of proteomic compositional order including single amino-acid runs, tandem repeats, periodic structure of motifs and otherwise low complexity amino-acid regions. We introduce new order measures, distinguishing between 'regularity', 'periodicity' and 'vocabulary', to quantify these phenomena and to facilitate the identification of evolutionary effects. Detailed analysis of representative species across the tree-of-life demonstrates that CO proteins exhibit numerous functional enrichments, including a wide repertoire of particular patterns of dependencies on regularity and periodicity. Comparison between human and mouse proteomes further reveals the interplay of CO with evolutionary trends, such as faster substitution rate in mouse leading to decrease of periodicity, while innovation along the human lineage leads to larger regularity. Large-scale analysis of 94 proteomes leads to systematic ordering of all major taxonomic groups according to FT-vocabulary size. This is measured by the count of Different Frequent Triplets (DFT) in proteomes. The latter provides a clear hierarchical delineation of vertebrates, invertebrates, plants, fungi and prokaryotes, with thermophiles showing the lowest level of FT-vocabulary. Among eukaryotes, this ordering correlates with phylogenetic proximity. Interestingly, in all kingdoms CO accumulation in the proteome has universal characteristics. We suggest that CO is a genomic-information correlate of both macroevolution and various protein functions. The results indicate a mechanism of genomic 'innovation' at the peptide level, involved in protein elongation, shaped in a universal manner by mutational and selective forces.
authors.affiliation: School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel.
authors.forename: Erez
authors.initials: E
authors.lastname: Persi
authors.forename: David
authors.initials: D
authors.lastname: Horn
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D005075:Biological Evolution; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D006801:Humans; D008954:Models, Biological; D058977:Molecular Sequence Annotation; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry* / Q000145:classification*; D012441:Saccharomyces cerevisiae; D020539:Sequence Analysis, Protein
chemical_list: D011506:Proteins