Population Genetic Framework for Neuroanatomical Mechanisms of Behavioral Modific

行为改变的神经解剖学机制的群体遗传框架

• 批准号: 8109133
• 负责人: Sergey V Nuzhdin
• 金额: $ 41.13万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-03-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8109133
• 关键词: Address; Adult; Alleles; Animals; Backcrossings; Behavior; Behavior Therapy; Behavioral; Behavioral Mechanisms; Biochemical; Biological Assay; Brain; Candidate Disease Gene; Cells; Cognition; Complex; Courtship; DNA; DNA Resequencing; Data Analyses; Detection; Development; Drosophila genus; Drosophila melanogaster; Enzymes; Exhibits; Gene Expression; Gene Expression Profile; Genes; Genetic; Genetic Polymorphism; Genetic Techniques; Genetic Transcription; Genetic Variation; Genotype; Goals; Human; Individual; Individual Differences; Investigation; Knowledge; Larva; Learning; Measures; Mediating; Memory; Messenger RNA; Modeling; Molecular Genetics; Mushroom Bodies; Neurons; Neurophysiology - biologic function; Organism; Pain; Performance; Phenotype; Physiological; Play; Population; Population Genetics; Process; Protein Biosynthesis; RNA Interference; RNA purification; Recurrence; Role; Shock; Side; Smell Perception; Social Behavior; Social Environment; Social Interaction; Staging; Structure; Sum; System; Taxon; Techniques; Testing; Time; Tissue-Specific Gene Expression; Toxoplasma gondii; Training; Transcript; Transgenes; Uracil phosphoribosyltransferase; Variant; aversive conditioning; base; cDNA Library; classical conditioning; cognitive function; experience; fly; gene discovery; gene function; genetic analysis; innovation; insight; interest; long term memory; mRNA tagging; mutant; neural circuit; neurogenetics; new technology; novel; relating to nervous system; response; social; sugar; tool; transcription factor

DESCRIPTION (provided by applicant): PROJECT SUMMARY Animals have numerous opportunities to acquire information from one another. Although common across taxa, social learning requires the integration of associative learning, memory and social behavior (LMS); and these vary considerably among individuals within a species. How do genetic differences cause alterations in neural functions that ultimately cause variability in social learning? To address this question it is important to identify the genes and neural circuits that play a role in LMS. Here we propose to analyze the molecular-genetic basis that underlies individual differences in LMS in the fruit fly Drosophila melanogaster. Flies have been used extensively as a model to study the genetic basis of development, behavior and learning and flies are social animals that aggregate in large groups. This confluence provides an opportunity to examine how individual genetic differences underlie variation in sociality and learning. We will develop flies as a model for the integrated analyses of the genetic, biochemical, physiological, and environmental components of LMS. We hypothesize that transcription in specific neural circuits is modified by experience and this contributes to long- term memory. Further, we hypothesize that variation in transcription in these same neural circuits across individuals contributes to the differences in LMS. In Drosophila, the mushroom body (MB) is the neural center of learning and cognition. Using a new molecular-genetic technique that allows for the purification of RNA from subsets of cells, we will examine the variation in both the MB transcriptome and the LMS behaviors of 192 recurrent heterozygous F1 genotypes. These F1 individuals will be obtained from progeny of 192 sequenced natural Raleigh strains, each crossed to a sequenced w1118 strain. We will be able to: i) determine how transcriptional variation in LMS is associated with phenotypic variation, ii) partition the cis- and trans- components of expression variation for every gene, iii) focus on cis- expression variation that is associated with behavioral variation, and iv) pinpoint cis- DNA polymorphisms likely contributing to cis- expression variation. Once we have identified causes of MB expression variation, we will connect the transcriptome with LMS: our goal is to identify the candidate genes and their polymorphisms associated with differences in LMS. We will measure larval and adult behaviors of focal genotypes with natural and major-effect alleles in the LMS candidate genes in several social contexts. We will then determine the transcriptional differences in the MB that are due to these social encounters. Subsequent functional analyses of candidate genes will provide mechanistic knowledge about how genes contribute to LMS. In sum, we propose an investigation where we synthesize genetic, molecular and behavioral information about individual genotypes to ultimately decipher aspects of the population genetics of social learning. We believe our inferences will illuminate, at several levels, the range of LMS variation maintained in natural populations of flies, thus providing insight into the genetic basis of LMS variation in other social organisms, including humans. PUBLIC HEALTH RELEVANCE: PUBLIC HEALTH RELEVANCE: We will develop Drosophila melanogaster as a model for integrative analyses of the genetic, biochemical, physiological, and environmental components of social behavior. We will combine frontier genomic and molecular-genetic techniques that allow one to determine with high resolution the transcriptome in subsets of cells. Our research will identify candidate genes for associative learning, memory, and social interactions and move from associations to causation by mechanistic analyses. We will start answering several critical questions: how are learning and memory affected by different social experiences? How are learning, memory and sociality functionally integrated? And how do different social experiences alter gene expression in specific regions of the nervous system? Connecting the answers together will result in insights illuminating the maintenance of variation in natural populations, and in other social organisms including humans.

项目概述动物有很多机会从彼此身上获取信息。虽然社会学习在不同的分类群中很常见，但它需要联想学习、记忆和社会行为（LMS）的整合；这些在同一物种的个体之间差别很大。基因差异如何导致神经功能的改变，最终导致社会学习的可变性？为了解决这个问题，确定在LMS中起作用的基因和神经回路是很重要的。在此，我们建议分析果蝇LMS个体差异的分子遗传学基础。苍蝇被广泛用作研究发育、行为和学习的遗传基础的模型，苍蝇是群居的社会动物。这种融合提供了一个机会来研究个体遗传差异如何成为社会性和学习能力变化的基础。我们将以果蝇为模型，对LMS的遗传、生化、生理和环境成分进行综合分析。我们假设，特定神经回路的转录是由经验修改的，这有助于长期记忆。此外，我们假设这些相同神经回路的转录差异导致了LMS的差异。在果蝇中，蘑菇体（MB）是学习和认知的神经中枢。使用一种新的分子遗传学技术，允许从细胞亚群中纯化RNA，我们将检查192个复发杂合F1基因型的MB转录组和LMS行为的变化。这些F1个体将从192个已测序的自然Raleigh菌株的后代中获得，每个菌株与一个已测序的w1118菌株杂交。我们将能够：i)确定LMS的转录变异如何与表型变异相关联，ii)划分每个基因表达变异的顺式和反式成分，iii)关注与行为变异相关的顺式表达变异，以及iv)查明可能导致顺式表达变异的顺式DNA多态性。一旦我们确定了MB表达变异的原因，我们将把转录组与LMS联系起来：我们的目标是确定与LMS差异相关的候选基因及其多态性。我们将在几种社会环境中测量具有LMS候选基因中自然和主要效应等位基因的焦点基因型的幼虫和成虫行为。然后，我们将确定由于这些社会遭遇而导致的MB转录差异。候选基因的后续功能分析将提供基因如何促进LMS的机制知识。总之，我们提出了一项研究，我们综合了个体基因型的遗传，分子和行为信息，最终破译社会学习的群体遗传学方面。我们相信，我们的推断将在几个层面上阐明蝇类自然种群中LMS变异的范围，从而深入了解包括人类在内的其他社会生物中LMS变异的遗传基础。