1989
DOI: 10.1007/bf01066250
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Interpreting studies that compare high- and low-selected lines on new characters

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… Show more

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Cited by 82 publications
(69 citation statements)
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“…29). However, it should be noted that some of the phenotypic differences observed between the HL and NHL might be attributed to a genetic drift phenomenon during the selection step (30), rather than being related to the trait of selection. Further segregating cross-breeding studies are necessary to determine whether phenotypic differences between the two lines have a genetic relationship to the trait of selection.…”
Section: Discussionmentioning
confidence: 99%
“…29). However, it should be noted that some of the phenotypic differences observed between the HL and NHL might be attributed to a genetic drift phenomenon during the selection step (30), rather than being related to the trait of selection. Further segregating cross-breeding studies are necessary to determine whether phenotypic differences between the two lines have a genetic relationship to the trait of selection.…”
Section: Discussionmentioning
confidence: 99%
“…Because the lines were separately propagated for 29 generations, mice in a given generation do not represent independent data points (i.e., mice within a line are genetically more similar to one another than mice between lines). Therefore, the individual subjects must be nested within the populations to which they belong (Henderson, 1989(Henderson, , 1997. To satisfy this requirement, line was always entered as a random effect (for theoretical justification of this approach see Pinheiro & Bates, 2000), nested within the fixed effect, line-type (S vs. C) using the Proc Mixed command in SAS (Littell, Milliken, Stroup, & Wolfinger, 1996).…”
Section: Discussionmentioning
confidence: 99%
“…For this purpose, each of the four replicates can be treated as an independent evolutionary event estimating the strength of the correlated response. The variance among replicates measures the deviation from the parametric value of (Henderson, 1989).…”
Section: Methodsmentioning
confidence: 99%