Proteome compression via protein domain compositions.
In this paper, we study domain compositions of proteins via compression of whole proteins in an organism for the sake of obtaining the entropy that the individual contains. We suppose that a protein is a multiset of domains. Since gene duplication and fusion have occurred through evolutionary processes, the same domains and the same compositions of domains appear in multiple proteins, which enables us to compress a proteome by using references to proteins for duplicated and fused proteins. Such a network with references to at most two proteins is modeled as a directed hypergraph. We propose a heuristic approach by combining the Edmonds algorithm and an integer linear programming, and apply our procedure to 14 proteomes of Dictyostelium discoideum, Escherichia coli, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Caenorhabditis elegans, Drosophila melanogaster, Arabidopsis thaliana, Oryza sativa, Danio rerio, Xenopus laevis, Gallus gallus, Mus musculus, Pan troglodytes, and Homo sapiens. The compressed size using both of duplication and fusion was smaller than that using only duplication, which suggests the importance of fusion events in evolution of a proteome.
Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. Electronic address: morihiro@kuicr.kyoto-u.ac.jp.
Morihiro
M
Hayashida
Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.
Peiying
P
Ruan
Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.
Tatsuya
T
Akutsu
D000465:Algorithms; D000818:Animals; D030562:Databases, Protein; D006801:Humans; D017434:Protein Structure, Tertiary; D020543:Proteome; D040901:Proteomics / Q000379:methods*; D020539:Sequence Analysis, Protein
D020543:Proteome
Grammar-based compression; Integer linear programming; Protein domain composition