The Nature and Function of Genomic Imprinting in Monoaminergic Neurons

单胺能神经元基因组印记的性质和功能

• 批准号: 10367506
• 负责人: Chris Gregg
• 金额: $ 76.23万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-03-04 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10367506
• 关键词: Adrenal Glands; Adrenal Medulla; Affect; Alleles; Behavior; Behavior Control; Behavior Disorders; Behavioral; Behavioral Model; Biological Assay; Brain; Brain region; Catecholamines; Cells; Complex; DOPA decarboxylase; Decision Making; Dependovirus; Enzymes; Epigenetic Process; Epinephrine; Exhibits; Fasting; Female; Genes; Genetic; Genetic Models; Genomic Imprinting; Goals; Heritability; Heterozygote; Human; Hydrocortisone; Hypothalamic structure; Lead; Length; Link; Mammals; Mental disorders; Metabolic; Methods; Modeling; Mus; Mutant Strains Mice; Mutation; Nature; Neurons; Parents; Pathology; Pattern; Population; Process; Public Health; Publishing; Reporter; Reproducibility; Research; Resources; Rewards; Risk; Role; Serotonin; Stress; Testing; Therapeutic; Tissues; Tyrosine 3-Monooxygenase; behavior test; behavioral phenotyping; behavioral response; brain cell; cell type; genetic risk factor; genetic variant; hypothalamic-pituitary-adrenal axis; imprint; improved; machine learning method; male; maternal imprint; monoamine; novel; offspring; parental involvement; paternal imprint; sex; stressor; targeted treatment; unsupervised learning

Mental illnesses are complex, affected by stressors and metabolic factors and involve changes to multiple behavioral components and decision-making processes. Thousands of genetic variants with small effects are typically involved. Thus, we lack a coherent genetic, cellular and evolutionary model for understanding and modifying important behavioral components affecting decision-making, activity and stress. If such a fundamental model of control could be uncovered for conserved, naturalistic behavior, our capabilities for understanding and therapeutically modifying behavioral disorders would be improved. Foraging has been studied for decades to uncover the basic principles and mechanisms of decision-making. Studies typically use simplified binary choice tests. However, we recently published a naturalistic foraging assay and unsupervised machine-learning methods to study complex, naturalistic decision patterns in mice. We discovered that foraging is composed of reproducible, genetically controlled behavioral sequences that we call “modules”. Using these methods, we investigated roles for maternally and paternally imprinted genes in controlling naturalistic decision patterns in males and females. Canonical imprinting involves complete silencing of one parent’s allele; however, we previously described genes with “noncanonical imprinting effects” that involve parental allele expression biases at the tissue level. We now have evidence that noncanonical imprinting effects at the tissue level involve allele silencing in subpopulations of cells. Moreover, we uncovered important roles for noncanonical imprinting effects in controlling naturalistic foraging and risk-reward-effort decision patterns. Currently, we do not fully understand the behavioral roles for different noncanonical imprinted genes. MEGs (maternally expressed genes) and PEGs (paternally expressed genes) are postulated to have opposing functional roles, suggesting an enticing genetic and evolutionary model of mammalian decision control. Imprinting effects in different cell populations could regulate the form, expression, timing and/or sequential order of different behavioral components of foraging. Therefore, our proposed study tests the hypothesis that noncanonical MEGs and PEGs have opposing effects on discrete behavioral components of naturalistic foraging and their cell-type specific imprinting effects reveal cell populations controlling discrete behaviors. In Aim 1, we will determine how MEGs and PEGs co-expressed with Th (tyrosine hydroxylase) and Ddc (dopa decarboxylase) in monoaminergic brain cells affect naturalistic decisions. In Aim 2, we will define functional links between discrete cell populations with imprinting effects for particular genes and discrete behavioral components of naturalistic foraging and decision patterns. Our proposed study is significant because it will help define an important genetic, cellular and evolutionary model of behavioral and decision control. Our long-term objective is to define a new conserved mechanistic model of control over decision patterns that helps delineate targets for therapeutically modifying human behavior.

精神疾病很复杂，受到压力源和代谢因素的影响，涉及多种因素的变化。 行为成分和决策过程。数千种影响较小的基因变异 通常涉及。因此，我们缺乏一个连贯的遗传、细胞和进化模型来理解和 改变影响决策、活动和压力的重要行为成分。如果有这样一个 可以揭示保守的自然行为、我们的能力的基本控制模型 对行为障碍的理解和治疗改变将会得到改善。觅食有 经过几十年的研究，揭示了决策的基本原理和机制。研究 通常使用简化的二元选择测试。然而，我们最近发表了一项自然觅食测定法， 无监督机器学习方法来研究小鼠复杂、自然的决策模式。我们 发现觅食是由可重复的、基因控制的行为序列组成的，我们称之为 “模块”。使用这些方法，我们研究了母系和父系印记基因在 控制男性和女性的自然决策模式。规范印记涉及完整的 父母一方的等位基因沉默；然而，我们之前描述了具有“非典型印记效应”的基因 涉及组织水平上的亲本等位基因表达偏差。我们现在有证据表明非规范 组织水平的印记效应涉及细胞亚群中的等位基因沉默。此外，我们还发现 非典型印记效应在控制自然觅食和风险回报努力方面的重要作用 决策模式。目前，我们还不完全了解不同非规范的行为角色 印记基因。假设 MEG（母源表达基因）和 PEG（父源表达基因） 具有相反的功能作用，表明哺乳动物有一个诱人的遗传和进化模型 决策控制。不同细胞群中的印记效应可以调节形式、表达、时间 和/或觅食的不同行为成分的顺序。因此，我们建议的研究测试 非规范 MEG 和 PEG 对离散行为具有相反影响的假设 自然觅食的成分及其细胞类型特异性印记效应揭示了细胞 控制离散行为的人群。在目标 1 中，我们将确定 MEG 和 PEG 如何共表达 单胺能脑细胞中的 Th（酪氨酸羟化酶）和 Ddc（多巴脱羧酶）影响自然 决定。在目标 2 中，我们将定义具有印记效应的离散细胞群之间的功能联系 自然觅食和决策模式的特定基因和离散行为成分。我们的 拟议的研究意义重大，因为它将有助于定义一个重要的遗传、细胞和进化模型 行为和决策控制。我们的长期目标是定义一个新的保守机制模型 对决策模式的控制有助于描绘治疗性改变人类行为的目标。