Functional genetic analysis of epigenetic age acceleration and the regulatory landscape of the methylome

DNA甲基化(DNaM)在个体之间表现出显著的差异，并随着年龄的增长而改变。DNaM- 基于生物年龄的估计(DNAmAge；又名“表观遗传学时钟”)是一种强有力的、广泛使用的生物标志物 衰老，但其潜在的机制大多仍不清楚。表观遗传时钟滴答作响的速度， 通常被称为表观遗传年龄加速(EAA或DNAmAge-acc)，是对 生物老化，可预测健康和预期寿命，并可通过饮食改变。我们发现， EAA在属于BXD家族的小鼠品系之间差异很大，是一种高度可遗传的特征， 与强QTL相关。值得注意的是，我们在BXD中发现的EAA的QTL，重叠的基因座和 候选基因也与人类的EAA相关。这些基因包括Stxbp4、Nkx2-3、 还有卡特克。在目标1a中，我们将基于CRISPR/Cas9对这些候选基因中的几个进行缺失 小鼠成纤维细胞。我们将使用来自BXD的两个亲本菌株(C57BL/6J和 DBA/2J)。如果发现基因缺失或基因敲除对表观遗传时钟有影响，我们将继续跟进 对转录组进行深度测序(目标1b)，以更深入地了解相关基因 表达变化和可能的机制。在目标2中，我们将应用整合系统遗传学来定义 通过执行甲基化QTL而导致较大的甲基组变异的遗传变异 (MeQTL)分析。这将在BXD重组近交系和先进的更大的小组中进行 这将为我们提供足够的QTL检测能力。AIM 2将利用现有资源 生物库中的肝脏样本。从前期工作中，我们发现一些高度可变的CpG 肝脏中的区域与体重和预期寿命的压力差异显著相关。 我们将绘制顺式和反式作用遗传变异的网络，这些变异配置高度的甲基组 代谢组织(即肝脏)，并检查这些顺式和反式meQTL是否也与复杂的性状有关 例如体重和寿命的自然变化。此外，这些肝脏样本已经有多个- 组学数据集(转录组、蛋白质组学和代谢组学)，这将添加一个表观基因组层，将 促进多标量综合分析。这两个目标结合在一起，将揭示调控 表观遗传时钟，以及有助于形成更大的甲基组的遗传变异。此外，我们还将 能够研究这些表观遗传特征如何与下游分子特征相关联，并可能起到中介作用 例如基因表达，以及体重、新陈代谢和寿命等更高级别的性状。

DNA methylation (DNAm) shows significant variation between individuals and is altered by aging. The DNAm- based estimate of biological age (DNAmAge; aka, “epigenetic clock”) is a robust and widely used biomarker of aging, but its underlying mechanisms remain mostly unknown. The rate at which the epigenetic clock ticks, commonly referred to as epigenetic age acceleration (EAA or DNAmAge-acc), is a measure of the rate of biological aging and is predictive of health and life expectancy, and modifiable by diet. We have found that EAA varies significantly between mouse strains belonging to the BXD family, and is a highly heritable trait that is linked to strong QTLs. Strikingly, the QTLs we have uncovered for EAA in the BXDs, overlap loci and candidate genes that are also associated with EAA in humans. These include genes such as Stxbp4, Nkx2–3, and Cutc. In Aim 1a, we will perform CRISPR/Cas9 based gene deletion of few of these candidate genes in mouse fibroblast cells. We will use cells derived from the two parent strains of the BXDs (C57BL/6J, and DBA/2J). If gene deletion or knockdown is found to have an impact on the epigenetic clock, we will follow-up with deep sequencing of the transcriptome (Aim 1b) to gain deeper insights into the associated gene expression changes and potential mechanisms. In Aim 2, we will apply integrative systems genetics to define the genetic variants that contribute to variability in the larger methylome by performing methylation QTL (meQTL) analyses. This will be carried out in a larger panel of the BXD recombinant inbred and advanced intercross strains that will give us sufficient power for QTL detection. Aim 2 will leverage an existing resource of biobanked liver specimens. From preliminary work, we have found that some of the highly variable CpG regions in the liver are significantly correlated with body weight, and with strain differences in life expectancy. We will chart the networks of cis- and trans-acting genetic variants that configure the methylome in a highly metabolic tissue (i.e., liver), and examine whether these cis and trans-meQTLs also relate to complex traits such as body weight, and natural variation in lifespan. Furthermore, these liver samples already have multi- omics datasets (transcriptomics, proteomics, and metabolomics), and this will add an epigenomic layer that will facilitate multi-scalar integrative analyses. Together, the two aims will shed light on the genes that regulate the epigenetic clock, and the genetic variants that contribute to shaping the larger methylome. Additionally, we will be able to study how these epigenetic traits associate with, and possibly mediate, downstream molecular traits such as gene expression, and higher order traits such as body weight, metabolism, and longevity.