Animal Model of Genetics and Social Behavior in Autism Spectrum Disorders

描述(由申请者提供)：自闭症谱系障碍(ASD)在美国每110名儿童中就有1名患有社交和沟通能力障碍。有证据表明，自闭症患者的社会行为中的个体差异，以及典型的发育中的人类群体中的个体差异，是遗传倾向和个人经验的结合，但其潜在的生物学机制仍然知之甚少。进展滞后是因为缺乏合适的动物模型，在这种模型中，潜在遗传学和个人经验的自然变异产生了社会行为的异质性，这种异质性与人类的行为即使不是同源的，也是性质相似的。开发一种具有与人类相似的自然社会变异的动物模型，将使我们能够更有效地针对直接影响ASD受损行为的神经回路的干预措施。为了解决这一差距，我们将开发一个完全实现的生物学模型，说明基因对 社会行为表型，通过表征生活在自然环境中的大量动物的社会行为和认知及其遗传基础，最大限度地减少外部干预。我们将使用观察技术和现场实验来定量定义男性和女性在社会气质和社会认知表型上的异质性。在我们的分层方法中，我们将使用标准实验室任务的类比，通过对自然行为和社会认知的深入观察来评估社会气质。我们还将使用分层方法来分析遗传变异。我们将首先使用一种先验方法来分析先前与社会行为有关的基因多态，以及尚未在猕猴身上评估的相同或相关途径中的多态。遗传变异将包括重复长度多态(VNTRs)和单核苷酸多态(SNPs)，并将被用于识别社会表型的遗传生物标记物。同时，我们将使用数据驱动、自下而上的方法，通过对50个由血统和社会气质确定的关键个人进行全基因组测序，识别与社会行为和认知有关的新基因组变异。然后，通过对选定个体的全基因组测序确定的变异将在整个种群中进行分析，以评估统计与社会行为的相关性。计算技术将被用来开发具有生物学意义的表型和基因变异之间的关系的测量方法。生物信息学软件和基础设施以前由我们团队开发并广泛验证，用于分析人类种群的基因组变异，将被用于识别和注释猕猴种群的基因组变异，并识别与特定社会行为衡量标准相关的变异。这些数据将与生活史和谱系数据相结合，生成关于基因和社会表型对生物成功的影响的预测模型。

DESCRIPTION (provided by applicant): Autism spectrum disorder (ASD) handicaps the social and communicative abilities of 1 out of every 110 children in the United States. Evidence suggests that individual variation in social behavior in ASD, as well as within the typically developing human population, arises from a combination of genetic predispositions and individual experience, yet the underlying biological mechanisms remain poorly understood. Progress lags due to the lack of a suitable animal model in which natural variation in both underlying genetics and individual experience generates heterogeneity in social behavior that is qualitatively similar, if not homologous, to that in humans. Development of an animal model with natural social variation homologous to that of humans will permit us to more effectively target interventions that directly impact the neural circuits mediating behaviors impaired in ASD. To address this gap, we will develop a fully-realized biological model of the genetic contributions to social behavior phenotype by characterizing social behavior and cognition and their genetic foundations in a large population of animals living in naturalistic circumstances with minimal external intervention. We will use observational techniques and field experiments to quantitatively define heterogeneity in social temperament and social cognition phenotypes in males and females. In our stratified approach, we will assess social temperament using intensive observation of natural behavior and social cognition using analogs of standard laboratory tasks. We will also assay genetic variation using a stratified approach. We will first use an a priori approach that assays gene polymorphisms previously implicated in social behavior, as well as polymorphisms in the same or related pathways that have yet to be assessed in macaques. Genetic variation will include repeat length polymorphisms (VNTRs) as well as single nucleotide polymorphisms (SNPs) and will be used to identify genetic biomarkers for social phenotypes. In parallel, we will use a data-driven, bottom-up approach to identify new genomic variants linked to social behavior and cognition, by conducting full genome sequencing on 50 key individuals identified by pedigree and social temperament. Variants identified by whole-genome sequencing of selected individuals then will be assayed across the entire population to assess statistical correlations with social behaviors. Computational techniques will be used to develop biologically-meaningful measures of the relationships between phenotypic and genotypic variation. Bioinformatics software and infrastructure, previously developed and extensively validated by our group for analysis of genomic variants in human populations, will be adapted to identify and annotate genomic variations in the macaque population, and to identify variants correlated with specific measures of social behavior. These data will be combined with life history and pedigree data to generate predictive models of the impact of genotype and social phenotype on biological success.