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Related Experiment Videos

Genetic mapping of developmental instability: design, model and algorithm.

Jiasheng Wu1, Bo Zhang, Yuehua Cui

  • 1College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang 310029, People's Republic of China.

Genetics
|April 17, 2007
PubMed
Summary
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This study introduces a new method to genetically analyze developmental instability in traits lacking bilateral symmetry. It quantifies instability and maps quantitative trait loci (QTL) controlling it, advancing evolutionary developmental biology research.

Area of Science:

  • Evolutionary biology
  • Developmental biology
  • Quantitative genetics

Background:

  • Developmental instability (DI) is crucial for evolution but hard to study in non-bilateral traits.
  • Fluctuating asymmetry (FA) is the traditional method, limited to bilateral traits.
  • A new approach is needed to assess genetic control of DI in a broader range of traits.

Purpose of the Study:

  • To develop an experimental design and statistical model for assessing genetic control of DI in non-bilateral traits.
  • To quantify DI using spatial autocorrelation and environmental variance components.
  • To map quantitative trait loci (QTL) influencing DI.

Main Methods:

  • Designed an experiment with spatial autocorrelation to partition environmental variance.

Related Experiment Videos

  • Quantified DI by the ratio of random to total residual environmental variance.
  • Formulated a mixture model using the EM algorithm to estimate genetic parameters, including QTL effects and spatial autocorrelations.

    • Main Results:

    • The developed mixture model successfully estimates genetic parameters for DI.
    • Simulation studies validated the model's statistical behavior.
    • Successfully mapped QTL controlling root length growth and its DI in poplar trees.

    Conclusions:

    • The novel spatial autocorrelation design and mixture model effectively determine the genetic basis of DI in non-bilateral traits.
    • This approach expands the study of DI and its evolutionary implications.
    • Provides a framework for identifying genetic factors influencing phenotypic stability.