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Finding evolutionary relations beyond superfamilies: fold-based superfamilies.

ABSTRACT: Superfamily classifications are based variably on similarity of sequences, global folds, local structures, or functions. We have examined the possibility of defining superfamilies purely from the viewpoint of the global fold/function relationship. For this purpose, we first classified protein domains according to the beta-sheet topology. We then introduced the concept of kinship relations among the classified beta-sheet topology by assuming that the major elementary event leading to creation of a new beta-sheet topology is either an addition or deletion of one beta-strand at the edge of an existing beta-sheet during the molecular evolution. Based on this kinship relation, a network of protein domains was constructed so that the distance between a pair of domains represents the number of evolutionary events that lead one from the other domain. We then mapped on it all known domains with a specific core chemical function (here taken, as an example, that involving ATP or its analogs). Careful analyses revealed that the domains are found distributed on the network as >20 mutually disjointed clusters. The proteins in each cluster are defined to form a fold-based superfamily. The results indicate that >20 ATP-binding protein superfamilies have been invented independently in the process of molecular evolution, and the conservative evolutionary diffusion of global folds and functions is the origin of the relationship between them.

SUBMITTER: Matsuda K

PROVIDER: S-EPMC2366925 | biostudies-literature | 2003 Oct

REPOSITORIES: biostudies-literature

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Finding evolutionary relations beyond superfamilies: fold-based superfamilies.

Matsuda Keiko K Nishioka Takaaki T Kinoshita Kengo K Kawabata Takeshi T Go Nobuhiro N

Protein science : a publication of the Protein Society 20031001 10

Superfamily classifications are based variably on similarity of sequences, global folds, local structures, or functions. We have examined the possibility of defining superfamilies purely from the viewpoint of the global fold/function relationship. For this purpose, we first classified protein domains according to the beta-sheet topology. We then introduced the concept of kinship relations among the classified beta-sheet topology by assuming that the major elementary event leading to creation of ...[more]

PMID: 14500881

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Project description:Heat shock protein 20 (Hsp20) genes play important roles in plant growth, development, and response to environmental stress. However, the Hsp20 gene family has not yet been systematically investigated, and its function in red algae (Rhodophyta) remains poorly understood. Herein, we characterized Hsp20 gene families in red algae by studying gene structure, conserved motifs, phylogenetic relationships, chromosome location, gene duplication, cis-regulatory elements, and expression profiles. In this study, 97 Hsp20 genes were identified using bioinformatic methods and classified into 13 subfamilies based on phylogenetic relationships. Phylogenetic analysis revealed that Hsp20 genes might have a polyphyletic origin and a complex evolutionary pattern. Gene structure analysis revealed that most Hsp20 genes possessed no introns, and all Hsp20 genes contained a conserved α-crystalline domain in the C-terminal region. Conserved motif analysis revealed that Hsp20 genes belonging to the same subfamily shared similar motifs. Gene duplication analysis demonstrated that tandem and segmental duplication events occurred in these gene families. Additionally, these gene families in red algae might have experienced strong purifying selection pressure during evolution, and Hsp20 genes in Pyropia yezoensis, Pyropia haitanensis, and Porphyra umbilicalis were highly evolutionarily conserved. The cis-elements of phytohormone-, light-, stress-responsive, and development-related were identified in the red algal Hsp20 gene promoter sequences. Finally, using Py. yezoensis, as a representative of red algae, the Hsp20 gene expression profile was explored. Based on the RNA-seq data, Py. yezoensis Hsp20 (PyyHsp20) genes were found to be involved in Py. yezoensis responses against abiotic and biotic stresses and exhibited diverse expression patterns. Moreover, PyyHsp20 is involved in Py. yezoensis growth and development and revealed spatial and temporal expression patterns. These results provide comprehensive and valuable information on Hsp20 gene families in red algae and lay a foundation for their functional characterization. In addition, our study provides new insights into the evolution of Hsp20 gene families in red algae and will help understand the adaptability of red algae to diverse environments.

Project description:BACKGROUND:Influx of newly determined crystal structures into primary structural databases is increasing at a rapid pace. This leads to updation of primary and their dependent secondary databases which makes large scale analysis of structures even more challenging. Hence, it becomes essential to compare and appreciate replacement of data and inclusion of new data that is critical between two updates. PASS2 is a database that retains structure-based sequence alignments of protein domain superfamilies and relies on SCOP database for its hierarchy and definition of superfamily members. Since, accurate alignments of distantly related proteins are useful evolutionary models for depicting variations within protein superfamilies, this study aims to trace the changes in data in between PASS2 updates. RESULTS:In this study, differences in superfamily compositions, family constituents and length variations between different versions of PASS2 have been tracked. Studying length variations in protein domains, which have been introduced by indels (insertions/deletions), are important because theses indels act as evolutionary signatures in introducing variations in substrate specificity, domain interactions and sometimes even regulating protein stability. With this objective of classifying the nature and source of variations in the superfamilies during transitions (between the different versions of PASS2), increasing length-rigidity of the superfamilies in the recent version is observed. In order to study such length-variant superfamilies in detail, an improved classification approach is also presented, which divides the superfamilies into distinct groups based on their extent of length variation. CONCLUSIONS:An objective study in terms of transition between the database updates, detailed investigation of the new/old members and examination of their structural alignments is non-trivial and will help researchers in designing experiments on specific superfamilies, in various modelling studies, in linking representative superfamily members to rapidly expanding sequence space and in evaluating the effects of length variations of new members in drug target proteins. The improved objective classification scheme developed here would be useful in future for automatic analysis of length variation in cases of updates of databases or even within different secondary databases.

Dataset Information

Finding evolutionary relations beyond superfamilies: fold-based superfamilies.

Publications

Finding evolutionary relations beyond superfamilies: fold-based superfamilies.

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