南京林业大学学报(自然科学版) ›› 2006, Vol. 30 ›› Issue (03): 1-12.doi: 10.3969/j.jssn.1000-2006.2006.03.001

• 研究论文 •    下一篇

动态复杂性状遗传结构研究的统计模型

邬荣领1,2,林敏1,赵伟1,侯伟1,张博2,诸葛强2,黄敏仁2,徐立安2   

  1. 1. 美国佛罗里达大学统计系, Gainesville, FL 326U, USA; 2. 国家林业局、江苏省林木遗传和基因工程重点实验室南京林业大学, 江苏 南京 210037
  • 出版日期:2016-06-18 发布日期:2016-06-18

Statistical Models for Studying the Genetic Architecture of Dynamic Complex Traits

WU Rong-ling1,2, LIN Min1, ZHAO Wei1, HOU Wei1, ZHANG Bo2, ZHUGE Qiang2, HUANG Min-ren2, XU Li-an2   

  1. 1. Department of Statistics University of Florida, Gainesville, FL 32611, USA; 2. The Key Laboratory of Forest Genetics and Gene Engineering of the State Forestry Administration and Jiangsu Province Nanjing Forestry University, Nanjing 210037, China
  • Online:2016-06-18 Published:2016-06-18

摘要: <正>应用PCR-RFLP技术分析松材线虫与拟松材线虫之间的差异。实验扩增出松材线虫rDNA-ITS区片段长度约为890bp,拟松材线虫rDNA-ITS区片段长度约为930bp。用5种限制性内切酶对两种线虫的ITS区扩增产物进行酶切,结果表明:(1)Dra I酶切松材线虫群体均产生两个长度约510bp和380bp的片段,而拟松材线虫均不能被Dra I酶切;(2)所有的松材线虫群体与拟松材线虫群体的ITS区扩增产物均不能被Apa I酶切;(3)用Msp I酶切松材线虫群体,除GZ02不能够被酶切外,其余样本能够产生两条长度分别为530bp和360bp的谱带。拟松材线虫群体,都能产生3条一致的亮带,长度分别为340bp、290bp、180bp;(4)所有松材线虫样本均不能被Sal I酶切,而拟松材线虫群体均能够被酶切为两个720bp和220bp的片段;(5)Xho I酶切松材线虫ITS区为两条大小分别为520bp和370bp的谱带。而拟松材线虫产生两条大小分别为530bp和400bp的谱带。因此,内切酶Dra I、Sal I可以用于检测松材线虫与拟松材线虫。Msp I、Apal、Xho I不宜用于鉴别松材线虫与拟松材线虫。

Abstract: Many quantitative traits of agricultural, biological and biomedical importance alter their phenotypes over development and display a complicated dynamic feature. Traditional approaches for genetic mapping of these so called dynamic traits have been to associate markers with phenotypes for different ages or stages of development and to compare the differences across these stages, or to use multiple trait mapping where the same character is repeatedly measured at different times. In either case, these approaches does not capture the dynamic structure and pattern of the process, which greatly limits the scope of inference about its genetic architecture. To overcome these limitations, Functional Mapping, that is, the integration of the mathematical aspects of the biological mechanisms and processes of the traits within the statistical genetic mapping framework, is the natural way to approach the genetics of dynamic traits. The combination of statistical modelling, genetics, and developmental biology begs many questions, such as the patterns of genetic control over development, the duration of QTL effects, as well as what causes developmental trajectories to change or stop changing. This paper shows that the functional mapping provides a useful quantitative and testable framework for assessing the interplay between gene actions/interactions and developmental patterns.

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