Systematic search for putative new domain families in Mycoplasma gallisepticum genome

Reddy, Chilamakuri C. S. ; Rani, Sane Sudha ; Offmann, Bernard ; Sowdhamini, R. (2010) Systematic search for putative new domain families in Mycoplasma gallisepticum genome BMC Research Notes, 3 . 98_1-98_10. ISSN 1756-0500

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Official URL: http://www.biomedcentral.com/1756-0500/3/98

Related URL: http://dx.doi.org/10.1186/1756-0500-3-98

Abstract

Background: Protein domains are the fundamental units of protein structure, function and evolution. The delineation of different domains in proteins is important for classification, understanding of structure, function and evolution. The delineation of protein domains within a polypeptide chain, namely at the genome scale, can be achieved in several ways but may remain problematic in many instances. Difficulties in identifying the domain content of a given sequence arise when the query sequence has no homologues with experimentally determined structure and searching against sequence domain databases also results in insignificant matches. Identification of domains under low sequence identity conditions and lack of structural homologues acquire a crucial importance especially at the genomic scale. Findings: We have developed a new method for the identification of domains in unassigned regions through indirect connections and scaled up its application to the analysis of 434 unassigned regions in 726 protein sequences of Mycoplasma gallisepticum genome. We could establish 71 new domain relationships and probable 63 putative new domain families through intermediate sequences in the unassigned regions, which importantly represent an overall 10% increase in PfamA domain annotation over the direct assignment in this genome. Conclusions: The systematic analysis of the unassigned regions in the Mycoplasma gallisepticum genome has provided some insight into the possible new domain relationships and putative new domain families. Further investigation of these predicted new domains may prove beneficial in improving the existing domain prediction algorithms.

Item Type:Article
Source:Copyright of this article belongs to BioMed Central.
ID Code:61282
Deposited On:15 Sep 2011 04:02
Last Modified:18 May 2016 11:03

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