CAA: Technology Transfer: Bringing the Tools of Molecular Biology to an Ecological Genetics Program

CAA：技术转让：将分子生物学工具引入生态遗传学项目

• 批准号: 9707679
• 负责人: Susan Kalisz
• 金额: $ 5万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-08-01 至 1998-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9707679&HistoricalAwards=false
• 关键词: CAA; Technology; Transfer; Bringing; Tools

Abstract Susan Kalisz 9707679 CAA Measuring dispersal or the rate of movement of individuals within and among populations in nature remains a challenge for ecologists and population geneticists because of the difficulty in detecting individual movements. This difficulty is exaggerated for many plant species, in which the dispersing stages are small, such as pollen or seed. However, our ability to quantify dispersal or migration within and among plant populations is central to understanding many population and regional processes. In particular, the extent to which populations or sub-populations are connected via migration of pollen or seed will determine 1) the extent to which different populations share genes in common and 2) the extent to which local extinctions are balanced by recolonization from other populations within a region, and 3) the extent to which local adaptation will occur. Emerging DNA technologies now make it possible to use genetic markers to detect migration and outcrossing events with greater accuracy. A powerful new molecular technique for ecological and population genetics, that of making and screening genomic libraries for microsatellite DNA repeats and microsatellite DNA polymorphism analysis will be learned by the PI. Microsatellites are short, tandemly repeated simple sequences, one to six base pairs in length, that are highly polymorphic for repeat number. Amplification of the microsatellite region by polymerase chain reaction (PCR) results in fully penetrant, Mendelian-inherited, codominant markers that can be precisely identified by length. Since these markers are allelic, microsatellite data are directly applicable to population genetic models and analysis. One of the greatest advantages of microsatellite DNA markers is their extreme variability (typically 10-20 alleles/locus) that can be used to characterize population structure, determine outcrossing rates and evaluate parentage by paternity exclusion. This award will facilitate al l facets of microsatellite library production, cloning, screening and scoring: in essence, the transfer of this PCR-based technology to my program. These techniques will be learned from Dr. M. Ashley who has developed microsatellite markers for several plant and animal systems in her laboratory. The analysis of microsatellite markers will enhance current research and future development in four distinct areas: 1) Environmental variance typical in natural populations causes local extinctions to occur. Such local population extinction should select for bet-hedging traits which restore populations, both demographically and genetically. With respect to local extinctions, we hypothesize that plant populations which exist within a matrix of other population of the same species should experience selection for seed dispersal. In contrast, isolated populations should experience selection for seed dormancy, since isolated population cannot receive nor cannot export successful migrants. One goal is to quantify the relationship between seed dispersal, seed dormancy and population genetic structure. Microsatellite markers would allow the assessment of the extent to which the study populations of Collinsia verna are genetically isolated entities (and express seed dormancy phenotypes) or exchange migrants via seed dispersal (and lack seed dormancy). 2) Most models of the evolution of selfing consider the negative genetic effects of inbreeding depression as the critical factors in mating system evolution. However, a new model demonstrates that environmental variance which prohibits pollinators from visiting flowers during some portion of the flowering season can be more important than inbreeding depression in driving the evolution and maintenance of self pollination mechanisms. We have demonstrated that C. verna has high levels of outcrossing and temporal separation of male and female phases but is capable of selfing. Microsatellite markers would allow us to test this model by conductin g paternity analysis and within flower outcrossing rates.

摘要Susan Kalisz 9707679 CAA测量分散或自然界人群内部和人群的运动率仍然是生态学家和人群遗传学家的挑战，因为难以检测个人运动。 对于许多植物物种而言，这种困难被夸大了，其中分散阶段很小，例如花粉或种子。但是，我们量化植物种群内部和迁移的能力对于了解许多人群和地区过程至关重要。 特别是，通过花粉或种子的迁移将种群或亚种群联系在一起的程度将确定1）不同人群共享共同基因的程度和2）2）局部灭绝的程度通过从地区内的其他人群中重新殖民化平衡的程度，以及3）局部适应的程度。 现在，新兴的DNA技术使使用遗传标记以更高的精度检测迁移和脱落事件成为可能。 PI将学习一种强大的新分子技术，用于生态和种群遗传学，用于制作和筛选微卫星DNA重复序列和微卫星DNA多态性分析的基因组文库。 微卫星是短的，串联重复的简单序列，长度为一对一对，是重复数的高度多态性。通过聚合酶链反应（PCR）对微卫星区域进行扩增会导致完全渗透物，孟德尔式属性，共同的标记，可以准确地按长度鉴定。由于这些标记是等位基因，因此微卫星数据直接适用于种群遗传模型和分析。 微卫星DNA标记的最大优势之一是它们的极端变异性（通常为10-20个等位基因/基因座），可用于表征人口结构，确定脱落率并通过亲子界排除评估父母。 该奖项将促进微卫星图书馆制作，克隆，筛选和评分的方面：从本质上讲，将这种基于PCR的技术转移到我的计划中。这些技术将从M. Ashley博士那里学到，后者为她的实验室中的几种动植物系统开发了微卫星标记。 微卫星标记的分析将在四个不同领域中增强当前的研究和未来发展：1）自然种群中典型的环境差异会导致局部灭绝。这种当地人口的灭绝应选择在人口统计学和遗传上恢复人口的赌注围墙特征。 关于局部灭绝，我们假设存在于同一物种其他种群中的矩阵中的植物种群应经历种子分散的选择。 相比之下，孤立的人群应经历种子休眠的选择，因为孤立的人口无法接受，也不能出口成功的移民。一个目标是量化种子分散，种子休眠和种群遗传结构之间的关系。微卫星标记将允许评估Collinsia verna的研究种群是遗传分离的实体（并表达种子休眠表型）或通过种子分散（并且缺乏种子休眠）交换迁移者。 2）自我发展的大多数模型都将近交性抑郁症的负面遗传作用视为交配系统进化的关键因素。 但是，一个新的模型表明，在开花季节的某些部分禁止传粉媒介无法参观花朵的环境差异比在推动自给授粉机制的演变和维持方面近亲抑郁症更为重要。 我们已经证明，C。Verna具有高水平的男性和女性阶段的时间分离和时间分离，但能够自我自我。 微卫星标志物将使我们能够通过托管陪审员分析和花朵脱落率来测试该模型。