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Statistical methods for detecting major genes of quantitative traits using phenotypic data of a diallel mating.

机译：使用Dialell交配的表型数据检测定量性状的主要基因的统计方法。

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摘要

The objectives of this thesis are to develop and evaluate the statistical methods to detect the major genes controlling quantitative traits in tree breeding population using simulated data and phenotypic data derived from a half-diallel mating design.; Three simple statistical tests, the Bartlett test, the Fain test, and the log-ANOVA test, were evaluated for detection of major gene segregation in a half-diallel mating design. Powers of detection and robustness to the presence of a half-sib relationship, a skewed distribution, and unbalanced data were investigated by using a series of simulated data sets. The most powerful tests were the Bartlett test and log-ANOVA test, but the Bartlett test was sensitive to the presence of a half-sib relationship and a skewed distribution. The Fain test had very limited power to detect the segregation of major genes although it was robust to the presence of a half-sib relationship and a skewed distribution. Overall, the log-ANOVA test may be the best simple test for detecting the major gene segregation for a half-diallel mating dataset. The major gene effects and the possible genotypes of parents and progenies cannot be estimated by the simple tests.; A Bayesian based segregation analysis method was developed to detect a major gene having large effects on the phenotype of a quantitative trait. A mixed inheritance model with a major gene plus polygenes was used to analyze the progeny population derived from a half-diallel mating design. Three simple tests and the parent block Gibbs sampling segregation analysis were also applied to eight progeny data sets of second generation of loblolly pine (Pinus Taeda L.) from the North Carolina State University - Industry Tree Improvement Program.; The log-ANOVA test was the most suitable simple test for screening populations for possible major gene segregation with the diallel mating progeny data in this study. The Bayesian based segregation analysis may be more powerful to estimate the genetic parameters of the major gene and polygenes, and the possible genotypes of the major gene of parents and progenies. In combination with molecular confirmation, these statistical methods are invaluable for detecting major genes of quantitative traits. (Abstract shortened by UMI.)
机译：本文的目的是开发和评估统计方法，以利用模拟数据和半圆角交配设计产生的表型数据检测树木育种种群中控制数量性状的主要基因。评估了三个简单的统计学检验，即Bartlett检验，Fain检验和log-ANOVA检验，以检测半圆角交配设计中的主要基因分离。通过使用一系列模拟数据集，研究了半同胞关系，偏斜分布和不平衡数据的存在的检测能力和鲁棒性。最强大的测试是Bartlett测试和log-ANOVA测试，但是Bartlett测试对半同胞关系和偏斜分布的存在很敏感。 Fain检验对主要基因分离的检测能力非常有限，尽管它对于存在半同胞关系和偏斜分布的存在是很可靠的。总体而言，log-ANOVA检验可能是检测半DIAL交配数据集主要基因分离的最佳简单检验。不能通过简单的测试来估计主要基因效应以及亲本和后代的可能基因型。开发了一种基于贝叶斯的分离分析方法，以检测对定量性状表型有较大影响的主要基因。使用具有主要基因加多基因的混合遗传模型来分析源自半圆角交配设计的后代种群。还对北卡罗来纳州立大学工业树改良计划的第二代火炬松（Pinus Taeda L.）的八个后代数据集进行了三个简单的测试和父代Gibbs采样隔离分析。 log-ANOVA检验是最合适的简单检验，用于利用本研究中的二代交配后代数据筛选人群中可能存在的主要基因分离现象。基于贝叶斯的分离分析可能更强大，可以估计主要基因和多基因的遗传参数，以及亲本和后代主要基因的可能基因型。结合分子确认，这些统计方法对于检测定量性状的主要基因是无价的。 （摘要由UMI缩短。）

著录项

  • 作者

    Zeng, Wen.;

  • 作者单位

    North Carolina State University.;

  • 授予单位 North Carolina State University.;
  • 学科 Biology Biostatistics.; Agriculture Forestry and Wildlife.; Biology Genetics.
  • 学位 Ph.D.
  • 年度 2000
  • 页码 145 p.
  • 总页数 145
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物数学方法;森林生物学;遗传学;
  • 关键词

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