Exploiting pleiotropy to map genes for oligogenic phenotypes using extended pedigree data.

Abstract:

:We investigated the utility of two approaches for exploiting pleiotropy to search for genes influencing related traits. To do this we first assessed the genetic correlations among a set of five closely related quantitative traits (Q1, Q2, Q3, Q4, Q5). We then used the genetic correlations among these five traits both to remove the common genetic effects of the four remaining traits, thereby identifying the unique genetic contribution to each trait, and to extract a synthetic phenotype which exploits the shared genetic information (pleiotropy) among these five traits. After obtaining these conditional traits, we then searched for evidence of quantitative trait loci (QTLs) (using variance component linkage) influencing the unique residual genetic component for each trait as well as those influencing the expression of the synthetic traits. From this work, we conclude that the removal of the common genetic effects of other traits in a group may be of greater utility when the majority of the pleiotropy initially detected between traits is attributable to the shared additive effects of polygenes, rather than to those of major loci. By contrast, decomposition of the genetic covariance matrix to its principal components is a greater utility when the majority of pleiotropy is attributable to major loci.

journal_name

Genet Epidemiol

journal_title

Genetic epidemiology

authors

Comuzzie AG,Mahaney MC,Almasy L,Dyer TD,Blangero J

doi

10.1002/(SICI)1098-2272(1997)14:6<975::AID-GEPI69>

subject

Has Abstract

pub_date

1997-01-01 00:00:00

pages

975-80

issue

6

eissn

0741-0395

issn

1098-2272

pii

10.1002/(SICI)1098-2272(1997)14:6<975::AID-GEPI69>

journal_volume

14

pub_type

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