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Multivariate Analysis of Genotype-Phenotype Association
Genetics (2016)
  • James M Cheverud, Loyola University Chicago
  • Philipp Mitteroecker, University of Vienna
  • Mihaela Pavlicev, Cincinnati Children's Hospital Medical Centre
With the advent of modern imaging and measurement technology, complex phenotypes are increasingly represented by large numbers of measurements, which may not bear biological meaning one by one. For such multivariate phenotypes, studying the pairwise associations between all measurements and all alleles is highly inefficient and prevents insight into the genetic pattern underlying the observed phenotypes. We present a new method for identifying patterns of allelic variation (genetic latent variables) that are maximally associated—in terms of effect size—with patterns of phenotypic variation (phenotypic latent variables). This multivariate
genotype–phenotype mapping (MGP) separates phenotypic features under strong genetic control from less genetically determined features and thus permits an analysis of the multivariate structure of genotype–phenotype association, including its dimensionality and the clustering of genetic and phenotypic variables within this association. Different variants of MGP maximize different measures of genotype–phenotype association: genetic effect, genetic variance, or heritability. In an application to a mouse sample, scored for 353 SNPs and 11 phenotypic traits, the first dimension of genetic and phenotypic latent variables accounted for .70% of genetic variation present in all 11 measurements; 43% of variation in this phenotypic pattern was explained by the corresponding genetic latent variable. The first three dimensions together sufficed to account for almost 90% of genetic variation in the measurements and for all the interpretable genotype–phenotype association. Each dimension can be tested as a whole against the hypothesis of no association, thereby reducing the number of statistical tests from 7766 to 3—the maximal number of meaningful independent tests. Important alleles can be selected based on their effect size (additive or nonadditive effect on the phenotypic latent variable). This low dimensionality of the genotype–phenotype map has important consequences for gene identification and may shed light on the evolvability of organisms.
  • genetic mapping,
  • genotype-phenotype map,
  • mouse,
  • multivariate analysis,
  • partial least squares
Publication Date
April, 2016
Publisher Statement
© 2016 by the Genetics Society of America
Citation Information
James M Cheverud, Philipp Mitteroecker and Mihaela Pavlicev. "Multivariate Analysis of Genotype-Phenotype Association" Genetics Vol. 202 Iss. 4 (2016) p. 1345 - 1363 ISSN: 1943-2631
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