A Student-Accessible Model for Human Genetics Using Fast Plants and Microsatellite Markers
A Student-Accessible Model for Human Genetics Using Fast Plants and Microsatellite Markers
批准号:
0340910
负责人:
Douglas Wendell
金额:
$7.49万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-05-01 至 2006-08-31
中文摘要
正在为教学实验室开发一个模拟人类遗传学的实验系统。 该实验涉及快速循环芜菁(RCBr)或快速植物的微卫星标记。 该项目的目标包括开发RCBr的微卫星标记和分析方法,使其能够进入教学实验室,具有类似人类遗传变异的确定微卫星基因型的RCBr菌株,用于微卫星标记和模型遗传疾病花青素的连锁分析的系谱分析实验,学生将与同龄人交换数据的虚拟实验室,分析数据,并允许教师跟踪他们的数据分析,以及一个原型网站和手册,供高中教师和学生分析由大学实验室产生的数据。 学生可以在这些教学实验室中使用的遗传分析类型包括微卫星分析技术,家庭信息量评估,高度多态性标记的遗传和单倍型分析。由于无法从单个家庭建立遗传连锁,学生们使用虚拟实验室来汇集数据。 通过这种方式,学生可以进行准确模拟人类遗传分析的实验,并获得分子标记的经验。基于网络的系统便于复杂数据的分析、单个学生数据的汇集以及教师对分析的跟踪。
英文摘要
An experimental system that models human genetics is being developed for instructional laboratories. The experiments involve microsatellite markers in rapid cycling Brassica rapa (RCBr), or Fast Plants. The objectives of the project include development of microsatellite markers for RCBr and analysis methods that make them accessible to the instructional lab, strains of RCBr with defined microsatellite genotypes resembling human genetic variation, a pedigree analysis experiment for linkage analysis with microsatellite markers and the model genetic disease anthocyaninless, a virtual laboratory in which students will exchange data with peers, analyze data, and allow the instructor to track their data analysis, and a prototype web site and manual for high school teachers and students to analyze data generated by the college labs. The types of genetic analysis the students can use in these instructional labs include techniques of microsatellite analysis, assessment of informativeness of families, inheritance of highly polymorphic markers, and haplotype analysis. Since genetic linkage cannot be established from a single family, students use the virtual lab to pool data. In this way, students can perform experiments that accurately model human genetic analysis and gain experience with molecular markers. The web-based system facilitates analysis of complex data, pooling of individual student data, and instructor tracking of analysis.
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