Volume 82, Issue 9
Article

Comparative analysis of sequence covariation methods to mine evolutionary hubs: Examples from selected GPCR families

Julien Pelé

UMR CNRS 6214–INSERM 1083, Laboratory of Integrated Neurovascular and Mitochondrial Biology, University of Angers, 49045 Angers, France

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Matthieu Moreau

UMR CNRS 6214–INSERM 1083, Laboratory of Integrated Neurovascular and Mitochondrial Biology, University of Angers, 49045 Angers, France

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Hervé Abdi

The University of Texas at Dallas, School of Behavioral and Brain Sciences, Richardson, TX, 75080‐3021 USA

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Patrice Rodien

UMR CNRS 6214–INSERM 1083, Laboratory of Integrated Neurovascular and Mitochondrial Biology, University of Angers, 49045 Angers, France

Department of Endocrinology, Reference Centre for the pathologies of hormonal receptivity, Centre Hospitalier Universitaire of Angers, 4 rue Larrey, 49933 Angers, France

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Hélène Castel

INSERM U982, Laboratory of Neuronal and Neuroendocrine Communication and Differentiation, DC2N, University of Rouen, 76821 Mont‐Saint‐Aignan, France

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Marie Chabbert

Corresponding Author

UMR CNRS 6214–INSERM 1083, Laboratory of Integrated Neurovascular and Mitochondrial Biology, University of Angers, 49045 Angers, France

Correspondence to: Marie Chabbert, UMR CNRS 6214‐INSERM U1083, Faculty of Medicine, 3 rue Haute de reculée, 49045 Angers, France. E‐mail: marie.chabbert@univ-angers.frSearch for more papers by this author
First published: 27 March 2014
Citations: 8

ABSTRACT

Covariation between positions in a multiple sequence alignment may reflect structural, functional, and/or phylogenetic constraints and can be analyzed by a wide variety of methods. We explored several of these methods for their ability to identify covarying positions related to the divergence of a protein family at different hierarchical levels. Specifically, we compared seven methods on a model system composed of three nested sets of G‐protein‐coupled receptors (GPCRs) in which a divergence event occurred. The covariation methods analyzed were based on: χ2 test, mutual information, substitution matrices, and perturbation methods. We first analyzed the dependence of the covariation scores on residue conservation (measured by sequence entropy), and then we analyzed the networking structure of the top pairs. Two methods out of seven—OMES (Observed minus Expected Squared) and ELSC (Explicit Likelihood of Subset Covariation)—favored pairs with intermediate entropy and a networking structure with a central residue involved in several high‐scoring pairs. This networking structure was observed for the three sequence sets. In each case, the central residue corresponded to a residue known to be crucial for the evolution of the GPCR family and the subfamily specificity. These central residues can be viewed as evolutionary hubs, in relation with an epistasis‐based mechanism of functional divergence within a protein family. Proteins 2014; 82:2141–2156. © 2014 Wiley Periodicals, Inc.

Number of times cited according to CrossRef: 8

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