Mathematic descriptions - multifactorial gene expression

数学描述-多因素基因表达

• 批准号: 6898218
• 负责人: SANDRA L RODRIGUEZ ZAS
• 金额: $ 26.49万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-06-15 至 2007-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6898218
• 关键词: Hymenoptera; brain; gene expression; mathematics; microarray technology; neurobiology; science education; social behavior; statistics /biometry

DESCRIPTION (provided by applicant): Social behavior is a complex trait and social interactions are critical determinants of human mental and physical health. Our long-term objective is to explain the interplay among factors influencing complex traits like social behavior by the integration of genomic research, statistical analysis, bioinformatic resources and outreach. Six specific aims support this objective. 1) We will generate expression profiles for more than 7000 genes in the brain of the honey bee as a function of its complex pattern of behavioral maturation; samples will be taken every 3-4 days, as it moves through its in-hive tasks and then shifts to foraging outside. We will characterize these profiles in two distinct races known to differ in the rate of maturation. These biological findings will have a major impact on understanding behavior, neurological and mental processes, health and well-being in bees, humans and other species. Epistatic, pleiotropic, and polygenic background effects will be studied while accounting for systematic noise including array, dye and transcript level effects. 2) We will apply novel linear and nonlinear mixed-effects longitudinal models that seamlessly integrate intensity normalization and analyses. 3) We will use hierarchical models to identify between race variation. These models account for technical sources of variation and for correlation in expression that might arise among genes that are from the same family or code for proteins in the same pathway. This proposal fills an important need for general models suitable for complex sets of gene expression data. 4) Visual approaches will be developed to check for model adequacy. 5) The proposed methodology will be combined with bioinformatic resources in a publicly available suite of routines that facilitate the interpretation of results while assigning gene function. 6) The findings will be used as applied examples of mathematical and science concepts in inquiry-based, open-ended, educational materials; virtual and tangible presentations for high school students, teachers, and the general public will be developed. Our findings constitute stepping-stones for understanding and further studies of human neurological, mental, communication, and aging processes and disorders, giving rise to treatments and cures.

描述(申请人提供)：社会行为是一个复杂的特征，社会互动是人类心理和身体健康的关键决定因素。我们的长期目标是通过整合基因组研究、统计分析、生物信息资源和推广，解释影响复杂特征(如社会行为)的因素之间的相互作用。六个具体目标支持这一目标。1)我们将根据蜜蜂复杂的行为成熟模式，在其大脑中生成超过7000个基因的表达谱；每3-4天采集一次样本，因为它在蜂箱内完成任务，然后转移到外面觅食。我们将在已知成熟率不同的两个不同的种族中描述这些特征。这些生物学发现将对理解蜜蜂、人类和其他物种的行为、神经和心理过程、健康和福祉产生重大影响。将研究上位性、多效性和多基因背景效应，同时考虑系统噪声，包括阵列、染料和转录水平效应。2)我们将应用新的线性和非线性混合效应纵向模型，无缝集成强度归一化和分析。3)我们将使用层次模型来识别小种之间的变异。这些模型解释了变异的技术来源，以及来自同一家族或同一途径中蛋白质编码的基因之间可能出现的表达相关性。这一建议满足了对适用于复杂的基因表达数据集的通用模型的重要需求。4)将开发可视化方法来检查模型的充分性。5)建议的方法将与生物信息学资源结合在一套公开可用的例程中，以便在分配基因功能的同时解释结果。6)这些发现将作为数学和科学概念在基于探究的开放式教育材料中的应用范例；将为高中生、教师和普通公众开发虚拟和有形的演示。我们的发现构成了理解和进一步研究人类神经、精神、沟通和衰老过程和障碍的垫脚石，从而产生了治疗和治愈。