Abstract #302141

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JSM 2003 Abstract #302141
Activity Number: 311
Type: Invited
Date/Time: Wednesday, August 6, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract - #302141
Title: Statistical Analysis of Genome Sequences to Identify Novel Important Protein Domain Combinations
Author(s): Wolfgang Huber*+ and Gordana Apic and Sarah A. Teichmann
Companies: German Cancer Research Center and MRC Laboratory of Molecular Biology and MRC Laboratory of Molecular Biology
Address: Division of Molecular Genome Analysis (B050), 69120 Heidelberg, , Germany
Keywords: protein domains ; random graphs ; genomic databases
Abstract:

There is a limited repertoire of families of protein domains in nature, which are duplicated and combined in different ways to form the set of proteins in a genome. With 70 genomes sequenced, it becomes possible to gain a systematic overview over the ways in which duplication and combination events have been used in evolution. Most domain pairs occur in three to six different architectures: in isolation and in combinations with different partners. Looking at the full presently known set of all pairwise domain combinations, we observe that most small and medium-sized families combine with only one or two families, while a few large families are versatile and combine with many different partners. We investigate to which extent this can be explained by a "random combination" model, in which the frequency of combination is proportional to the size of a domain family. From the complete sequence data of 70 genomes, we find that about 1/3 of families show significantly more duplications than expected from their number of neighboring domains, and about 1/3 are combined with more different types of domains than expected from family size. They are interesting targets for structural elucidation.

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