Literature DB >> 14963653

Metabolic control analysis as a mechanism that conserves genetic variance during advanced cycle breeding.

J Yu1, R Bernardo.   

Abstract

The recycling of elite inbreds (i.e., advanced cycle breeding) has led to significant genetic gains but also to a narrow gene pool in plant breeding programs. Sustained yield improvements in many crops have suggested that genetic variance is not depleted at a rate predicted by an additive genetic model. Unlike the additive model in classical quantitative genetic theory, metabolic control analysis relates the variation in a biochemical process with the genetic variation in a quantitative trait. Our objective was to determine whether metabolic control analysis is a mechanism that slows the decrease in genetic variance during advanced cycle breeding. Three cycles of advanced cycle breeding were simulated with 10, 50, or 100 quantitative trait loci (QTL) controlling a trait. In metabolic control analysis, these QTL coded for enzymes involved in a linear metabolic pathway that converted a substrate into a product. In the absence of selection, both the additive model and the metabolic control analysis model led to about a 50% reduction in genetic variance from cycle to cycle. With selection, the additive model led to a 50-58% reduction in genetic variance, but the metabolic control analysis model generally led to only a 12-54% reduction. We suggest selection in a metabolic control analysis model as a mechanism that slows the decrease in genetic variance during advanced cycle breeding. This conservation of genetic variance would allow breeders to achieve genetic gains for a longer period than expected under the additive model.

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Year:  2004        PMID: 14963653     DOI: 10.1007/s00122-004-1589-9

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  19 in total

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Authors:  B Bost; C Dillmann; D de Vienne
Journal:  Genetics       Date:  1999-12       Impact factor: 4.562

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Journal:  Genetics       Date:  1999-05       Impact factor: 4.562

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Journal:  J Theor Biol       Date:  1996-10-07       Impact factor: 2.691

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Journal:  Science       Date:  1997-08-22       Impact factor: 47.728

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Authors:  C C Cockerham; H Tachida
Journal:  Proc Natl Acad Sci U S A       Date:  1988-03       Impact factor: 11.205

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Journal:  Genetics       Date:  1981 Mar-Apr       Impact factor: 4.562

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  1 in total

1.  Multilocus epistasis, linkage, and genetic variance in breeding populations with few parents.

Authors:  D A Tabanao; J Yu; R Bernardo
Journal:  Theor Appl Genet       Date:  2007-06-12       Impact factor: 5.574

  1 in total

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