首页> 外文会议>International Symposium of Biological Shape Analysis >Quantitative Genetic Analyses of Crop Organ Shape based on Principal Components of Elliptic Fourier Descriptors
【24h】

Quantitative Genetic Analyses of Crop Organ Shape based on Principal Components of Elliptic Fourier Descriptors

机译:基于椭圆傅立叶描述符的主要成分的作物器官形状的定量遗传分析

获取原文
获取外文期刊封面目录资料

摘要

Crop organ shape as well as size is an important trait for the genetic improvement of crops because it directly or indirectly influences the values of agricultural products. In general, crop organ shape shows continuous variation. In order to clarify its genetic structure it is necessary to measure this genetic variation with a quantitative method. Principal component analysis (PCA) of a set of elliptic Fourier descriptors (EFDs) enables one to decompose the shape variation into statistically independent characteristics and to analyze these characteristics as ordinary quantitative traits. So far, crop organ shape has been analyzed with various quantitative genetic methods based on the principal components (PCs) of EFDs. Diallel analysis enabled the clarification of the mode of inheritance of commercially important shape characteristics in the radish root. Genome-wide association studies enabled the estimation of the positions and effects of quantitative trait loci (QTL) controlling rice grain shape variation observed in a germplasm collection. The results of these analyses were easy-to-understand because of the visualization of the results, and served as useful knowledge for plant breeding. In a series of analyses, different PCs of EFDs showed a different mode of inheritance or were controlled by different QTLs in general, indicating that PCA of EFDs unraveled the inheritance of shape controlled by a number of genes into simpler and more easily understood components. Recent advances in molecular biology technology allow one to utilize a more advanced method in quantitative genetics for the understanding of the biological processes controlling crop organ shape. For example, genomic selection may enable one to predict unobserved organ shapes of unknown genotypes and select desirable genotypes based on the predicted shape. Combining the PCA of EFDs with statistical genetic methods, may provide genetic improvement of crop organ shape. Moreover, this approach allowed for a more rapid and efficient procedure for the design of new and novel crop organ shapes.
机译:作物器官形状以及大小是作物遗传改善的重要特征,因为它直接或间接地影响农产品的价值。通常,作物器官形状显示连续变化。为了阐明其遗传结构,有必要用定量方法测量该遗传变异。一组椭圆傅立叶描述符(EFDS)的主成分分析(PCA)使得能够将形状变化分解为统计学独立的特性,并分析这些特征作为普通定量性状。到目前为止,基于EFD的主要成分(PC),以各种定量遗传方法分析了作物器官形状。 Diallel分析使rollish根系中商业上重要形状特征的遗传方式澄清。基因组 - 范围的协会研究使得估计在种质收集中观察到的定量性状基因座(QTL)控制稻粒形状变化的位置和效果。由于结果的可视化,这些分析的结果易于理解,并作为植物育种的有用知识。在一系列分析中,不同的EFDS的PC显示出不同的继承方式,或者通常由不同的QTL控制,表明EFDS的PCA揭开了由许多基因控制的形状的遗传成更简单,更容易理解组件。分子生物学技术的最新进展允许人们在定量遗传学中利用更先进的方法,以了解控制作物器官形状的生物过程。例如,基因组选择可以使其能够预测未知基因型的未观察室形状,并基于预测的形状选择所需基因型。将EFD的PCA与统计遗传方法相结合,可以提供作物器官形状的遗传改善。此外,这种方法允许更快速高效地进行新的新型作物器官形状的设计。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号