Literature DB >> 2803180

Interpreting studies that compare high- and low-selected lines on new characters.

N D Henderson.   

Abstract

The attempt to characterize high- and low-selected lines on new variables poses serious interpretative problems when replicate lines are not available. Modest but significant line differences on new measures may be due to genetic drift totally irrelevant to the originally selected trait. Often these differences are exaggerated by inappropriate analysis using individual subject measurements rather than family means. Mean differences in high- and low-selected lines on new characters should not be ascribed to the originally selected trait unless (1) genetic drift can be estimated through the use of replicate lines, (2) the standardized mean difference exceeds 1/4 of the equivalent difference on the original selected trait, or (3) strong predictions involving multiple noncontingent measures are unconditionally supported. For most purposes of analysis, line means can be considered individual data points which can be used to compute correlations among measures. An alternative to selection with replicates--two-stage testing of commercially available inbred strains--should be considered when large genetic correlations between the characters are expected.

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Year:  1989        PMID: 2803180     DOI: 10.1007/bf01066250

Source DB:  PubMed          Journal:  Behav Genet        ISSN: 0001-8244            Impact factor:   2.805


  5 in total

1.  The effect of selection on genetic variability: a simulation study.

Authors:  M G Bulmer
Journal:  Genet Res       Date:  1976-10       Impact factor: 1.588

2.  Evolution in Mendelian Populations.

Authors:  S Wright
Journal:  Genetics       Date:  1931-03       Impact factor: 4.562

3.  Selection for growth on normal and reduced protein diets in mice. I. Direct and correlated responses for growth.

Authors:  V H Nielsen; S Andersen
Journal:  Genet Res       Date:  1987-08       Impact factor: 1.588

4.  Inference about genetic correlations.

Authors:  G Carey
Journal:  Behav Genet       Date:  1988-05       Impact factor: 2.805

5.  Response to 30 generations of selection for open-field activity in laboratory mice.

Authors:  J C DeFries; M C Gervais; E A Thomas
Journal:  Behav Genet       Date:  1978-01       Impact factor: 2.805

  5 in total
  19 in total

1.  Analyzing phenotypic correlations in studies with selected lines.

Authors:  D A Blizard
Journal:  Behav Genet       Date:  1992-01       Impact factor: 2.805

Review 2.  The complexity of alcohol drinking: studies in rodent genetic models.

Authors:  John C Crabbe; Tamara J Phillips; John K Belknap
Journal:  Behav Genet       Date:  2010-06-15       Impact factor: 2.805

Review 3.  Recombinant-inbred strains: general methodological considerations relevant to the study of complex characters.

Authors:  D A Blizard
Journal:  Behav Genet       Date:  1992-11       Impact factor: 2.805

4.  A strong response to selection on mass-independent maximal metabolic rate without a correlated response in basal metabolic rate.

Authors:  B W M Wone; P Madsen; E R Donovan; M K Labocha; M W Sears; C J Downs; D A Sorensen; J P Hayes
Journal:  Heredity (Edinb)       Date:  2015-01-21       Impact factor: 3.821

5.  Selection for increased mass-independent maximal metabolic rate suppresses innate but not adaptive immune function.

Authors:  Cynthia J Downs; Jessi L Brown; Bernard Wone; Edward R Donovan; Kenneth Hunter; Jack P Hayes
Journal:  Proc Biol Sci       Date:  2013-01-08       Impact factor: 5.349

6.  Metabolomics of aerobic metabolism in mice selected for increased maximal metabolic rate.

Authors:  Bernard Wone; Edward R Donovan; Jack P Hayes
Journal:  Comp Biochem Physiol Part D Genomics Proteomics       Date:  2011-09-16       Impact factor: 2.674

Review 7.  Hormones and the Evolution of Complex Traits: Insights from Artificial Selection on Behavior.

Authors:  Theodore Garland; Meng Zhao; Wendy Saltzman
Journal:  Integr Comp Biol       Date:  2016-06-01       Impact factor: 3.326

Review 8.  The genetics of pain and pain inhibition.

Authors:  J S Mogil; W F Sternberg; P Marek; B Sadowski; J K Belknap; J C Liebeskind
Journal:  Proc Natl Acad Sci U S A       Date:  1996-04-02       Impact factor: 11.205

9.  Behavioral, neurochemical, and electrophysiological characterization of a genetic mouse model of depression.

Authors:  Malika El Yacoubi; Saoussen Bouali; Daniela Popa; Laurent Naudon; Isabelle Leroux-Nicollet; Michel Hamon; Jean Costentin; Joëlle Adrien; Jean-Marie Vaugeois
Journal:  Proc Natl Acad Sci U S A       Date:  2003-05-05       Impact factor: 11.205

10.  Metabolic rates associated with membrane fatty acids in mice selected for increased maximal metabolic rate.

Authors:  Bernard W M Wone; Edward R Donovan; John C Cushman; Jack P Hayes
Journal:  Comp Biochem Physiol A Mol Integr Physiol       Date:  2013-02-16       Impact factor: 2.320

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