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A probabilistic method to identify compensatory substitutions for pathogenic mutations

Easton, Brett; Isaev, Alexander; Huttley, Gavin Austin; Maxwell, Peter

Description

Complex systems of interactions govern the structure and function of biomolecules. Mutations that substantially disrupt these interactions are deleterious and should not persist under selection. Yet, several instances have been reported where a variant confirmed as pathogenic in one species is fixed in the orthologs of other species. Here we introduce a novel method for detecting compensatory substitutions for these so-called compensated pathogenic deviations (CPDs), incorporating knowledge of...[Show more]

dc.contributor.authorEaston, Brett
dc.contributor.authorIsaev, Alexander
dc.contributor.authorHuttley, Gavin Austin
dc.contributor.authorMaxwell, Peter
dc.coverage.spatialHong Kong
dc.date.accessioned2015-12-07T22:51:02Z
dc.date.createdJanuary 15-17 2007
dc.identifier.isbn9781860947834
dc.identifier.urihttp://hdl.handle.net/1885/27271
dc.description.abstractComplex systems of interactions govern the structure and function of biomolecules. Mutations that substantially disrupt these interactions are deleterious and should not persist under selection. Yet, several instances have been reported where a variant confirmed as pathogenic in one species is fixed in the orthologs of other species. Here we introduce a novel method for detecting compensatory substitutions for these so-called compensated pathogenic deviations (CPDs), incorporating knowledge of pathogenic variants into a probabilistic method for detecting correlated evolution. The success of this approach is demonstrated for 26 of 31 CPDs observed in mitochondrial transfer RNAs and for one in beta hemoglobin. The detection of multiple compensatory sites is demonstrated for two of these CPDs. The methodology is applicable to comparative sequence data for biomolecules expressed in any alphabet, real or abstract. It provides a widely applicable approach to the prediction of compensatory substitutions for CPDs, avoiding any reliance on rigid non-probabilistic criteria or structural data. The detection of compensatory substitutions that facilitate the substitution of otherwise pathogenic variants offers valuable insight into the molecular constraints imposed on adaptive evolution.
dc.publisherImperial College Press
dc.relation.ispartofseriesAsia-Pacific Bioinformatics Conference (APBC 2007)
dc.sourceProceedings of the 5th Asia-Pacific Bioinformatics Conference (APBC 2007)
dc.subjectKeywords: Adaptive evolution; Non-probabilistic; Orthologs; Pathogenic mutation; Probabilistic methods; Sequence data; Structural data; Biomolecules; Bioinformatics
dc.titleA probabilistic method to identify compensatory substitutions for pathogenic mutations
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2007
local.identifier.absfor110311 - Medical Genetics (excl. Cancer Genetics)
local.identifier.absfor060409 - Molecular Evolution
local.identifier.ariespublicationu4020362xPUB50
local.type.statusPublished Version
local.contributor.affiliationEaston, Brett, College of Physical and Mathematical Sciences, ANU
local.contributor.affiliationIsaev, Alexander, College of Physical and Mathematical Sciences, ANU
local.contributor.affiliationHuttley, Gavin Austin, College of Medicine, Biology and Environment, ANU
local.contributor.affiliationMaxwell, Peter, College of Medicine, Biology and Environment, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.startpage195
local.bibliographicCitation.lastpage204
dc.date.updated2016-02-24T10:27:58Z
local.identifier.scopusID2-s2.0-60849115679
CollectionsANU Research Publications

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