GENETIC MANAGEMENT OF CHIMPANZEES IN BIOMEDICAL RESEARCH

黑猩猩是生物医学研究的重要动物模型。 遗传 管理可以用来最大化这些动物的价值， 育种和研究。 到目前为止，遗传管理计划已经评估了 遗传标记的遗传变异。 然而，数量性状也 可以用来估计潜在的遗传变异性。 几乎每一 群体具有丰富的数量性状数据，其形式为常规的 收集了可用于遗传管理的临床措施。 的 拟议项目的目标是开发面向研究的技术， 西南生物医学研究基金会的遗传管理 （SFBR）黑猩猩群体作为模型种群。 这些技术可以 很容易应用于其他非人类灵长类动物的群体。 的目标 研究内容是：（1）发展和评价定量 遗传学作为管理灵长类动物群体的工具，2）寻找 主要基因位点对临床测量的影响 生物医学研究中使用的灵长类动物，以及3）使用生成的数据， 制定管理策略，最大限度地提高动物产量 适合研究，同时最大限度地减少遗传变异性的损失。 具体地，将表征殖民地的15-20个多态性 标记。 这些数据将用于验证谱系并直接评估 殖民地的遗传变异性。 定量遗传分析，复杂 分离分析和测量的基因型分析将在 系列临床化学数据、血液学指标和体重 来评估数量遗传变异。 将制定方法， 利用遗传数量性状信息进行经营决策 制作。 作为这些技术与研究相关性的一个例子， 丙型肝炎病毒感染后肝功能反应的遗传因素 将被确定。 基于先前步骤中生成的数据，新方法 将发展到包括血统关系和遗传信息 在实验动物的选择过程中。 计算机模拟将 用于评估此类选择策略对未来的影响 殖民地的生存能力。 该项目将提供新的通用工具， 非人类遗传管理中的数量性状和谱系数据 灵长类群体，并将扩大我们的知识的遗传决定因素， 生理变化的影响。

Chimpanzees are important animal models in biomedical research. Genetic management can be used to maximize the value of these animals for both breeding and research. To date, genetic management programs have assessed genetic variation from genetic markers. However, quantitative traits also can be used to estimate underlying genetic variability. Almost every colony has a wealth of quantitative trait data in the form of routinely collected clinical measures that could be used in genetic management. The goal of the proposed project is to develop techniques for research-oriented genetic management using the Southwest Foundation for Biomedical Research (SFBR) chimpanzee colony as a model population. These techniques could be readily applied to other colonies of nonhuman primates. The objectives of the research are 1) to develop and evaluate techniques of quantitative genetics as tools for managing primate colonies, 2) to search for the influence of major gene loci on clinical measurements commonly made on primates used in biomedical research, and 3) to use the generated data to develop management strategies that will maximize production of animals suitable for research while minimizing loss of genetic variability. Specifically, the colony will be characterized for 15-20 polymorphic markers. These data will be used to validate pedigrees and directly assess genetic variability in the colony. Quantitative genetic analysis, complex segregation analysis, and measured genotype analysis will be performed on serial clinical chemistry data, hematological measures, and body weights to assess quantitative genetic variation. Methods will be developed to utilize heritable quantitative trait information in management decision making. As an example of the relevance of these techniques for research, the genetic components of liver function response to hepatitis C infection will be determined. Based on data generated in previous steps, new methods will be developed to include pedigree relationships and genetic information in experimental animal selection procedures. Computer simulation will be used to assess the impact of such selection strategies on the future viability of the colony. This project will provide new general tools for using widely available quantitative trait and pedigree data in the genetic management of nonhuman primate colonies, and will extend our knowledge of the genetic determinants of physiological variation.