Literature DB >> 28581166

A COMPARISON OF GENETIC AND PHENOTYPIC CORRELATIONS.

James M Cheverud1.   

Abstract

Genetic variances and correlations lie at the center of quantitative evolutionary theory. They are often difficult to estimate, however, due to the large samples of related individuals that are required. I investigated the relationship of genetic- and phenotypic-correlation magnitudes and patterns in 41 pairs of matrices drawn from the literature in order to determine their degree of similarity and whether phenotypic parameters could be used in place of their genetic counterparts in situations where genetic variances and correlations cannot be precisely estimated. The analysis indicates that squared genetic correlations were on average much higher than squared phenotypic correlations and that genetic and phenotypic correlations had only broadly similar patterns. These results could be due either to biological causes or to imprecision of genetic-correlation estimates due to sampling error. When only those studies based on the largest sample sizes (effective sample size of 40 or more) were included, squared genetic-correlation estimates were only slightly greater than their phenotypic counterparts and the patterns of correlation were strikingly similar. Thus, much of the dissimilarity between phenotypic- and genetic-correlation estimates seems to be due to imprecise estimates of genetic correlations. Phenotypic correlations are likely to be fair estimates of their genetic counterparts in many situations. These further results also indicate that genetic and environmental causes of phenotypic variation tend to act on growth and development in a similar manner. © 1988 The Society for the Study of Evolution.

Year:  1988        PMID: 28581166     DOI: 10.1111/j.1558-5646.1988.tb02514.x

Source DB:  PubMed          Journal:  Evolution        ISSN: 0014-3820            Impact factor:   3.694


  74 in total

1.  Diet-dependent genetic and genomic imprinting effects on obesity in mice.

Authors:  James M Cheverud; Heather A Lawson; Gloria L Fawcett; Bing Wang; L Susan Pletscher; Ashley R Fox; Taylor J Maxwell; Thomas H Ehrich; Jane P Kenney-Hunt; Jason B Wolf; Clay F Semenkovich
Journal:  Obesity (Silver Spring)       Date:  2010-06-10       Impact factor: 5.002

Review 2.  Applying a quantitative genetics framework to behavioural syndrome research.

Authors:  Ned A Dochtermann; Derek A Roff
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-12-27       Impact factor: 6.237

Review 3.  Mendelian randomization: can genetic epidemiology help redress the failures of observational epidemiology?

Authors:  Shah Ebrahim; George Davey Smith
Journal:  Hum Genet       Date:  2007-11-23       Impact factor: 4.132

4.  MIPoD: a hypothesis-testing framework for microevolutionary inference from patterns of divergence.

Authors:  Paul A Hohenlohe; Stevan J Arnold
Journal:  Am Nat       Date:  2008-03       Impact factor: 3.926

5.  Genetic and environmental links between cognitive and physical functions in old age.

Authors:  Wendy Johnson; Ian J Deary; Matt McGue; Kaare Christensen
Journal:  J Gerontol B Psychol Sci Soc Sci       Date:  2009-02-10       Impact factor: 4.077

6.  The heritability of fitness: some single gene models.

Authors:  O Mayo; R Bürger; C R Leach
Journal:  Theor Appl Genet       Date:  1990-02       Impact factor: 5.699

7.  Estimating genetic correlations based on phenotypic data: a simulation-based method.

Authors:  Elias Zintzaras
Journal:  J Genet       Date:  2011-04       Impact factor: 1.166

8.  Human variation in the shape of the birth canal is significant and geographically structured.

Authors:  Lia Betti; Andrea Manica
Journal:  Proc Biol Sci       Date:  2018-10-24       Impact factor: 5.349

9.  Genetic variation in baboon craniofacial sexual dimorphism.

Authors:  Katherine E Willmore; Charles C Roseman; Jeffrey Rogers; Joan T Richtsmeier; James M Cheverud
Journal:  Evolution       Date:  2009-02-03       Impact factor: 3.694

10.  Trait performance correlations across life stages under environmental stress conditions in the common frog, Rana temporaria.

Authors:  Frank Johansson; Baptiste Lederer; Martin I Lind
Journal:  PLoS One       Date:  2010-07-21       Impact factor: 3.240

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