Functional Characterization of the Genetic and Environmental Determinants of Complex Traits

了解非编码区遗传变异的分子和组织功能对于 剖析复杂性状变异的遗传和进化基础。组合互补泛函 基因组数据集已被证明是一种成功的策略，可以精确定位最可能的原因变异和分子 支持遗传联系的机制。当前现有的注解仅捕获了法规条件 在基线水平上。然而，正如我们和其他人所展示的那样，基因变异对分子的影响 途径，并最终在个体的表型上，可能受到细胞环境背景的调节 (基因-环境相互作用，GxE)。我们将这些遗传变异称为GxE数量性状核苷酸 (GxE-fi)，并将蜂窝环境视为生物体的简单QTN但更好控制的代理 环境。转录因子与特定的fic基因组靶点的结合受序列基序和染色质表位的限制。 磁性标记，并可通过GxE-QTns的存在而改变。为了发现受GxE-QTns调控的基因， 我们最近建立了一种高通量方法，由50人组成的小组来扰乱蜂窝环境 体外治疗，包括维生素、金属离子、常见药物和激素。在这里，我们建议使用这个 解剖这些GxE-QTN的方法和潜在的分子机制：i)执行功能GE-QTN- Nomics分析捕捉染色质的可及性；ii)分析自然发生的遗传变异的影响 3)结合RNA-seq、atac-seq、mpra和gwas数据，共同定位关联。 信号和精确的复杂特征因果变异。

Understanding the molecular and organismal function of genetic variants in non-coding regions is crucial to dissect the genetic and evolutionary basis of variation in complex traits. Combining complementary functional genomics datasets has proven a successful strategy to pinpoint the most likely causal variant and molecular mechanism supporting a genetic association. Current existing annotations only capture regulatory conditions at the baseline level. However, as we and others have shown, the effect of a genetic variant on a molecular pathway, and ultimately on the individual's phenotype, may be modulated by the cellular environmental context (gene-environment interactions, GxE). We define these genetic variants as GxE quantitative trait nucleotides (GxE-QTNs) and consider the cellular environment as a simplified but better controlled proxy of the organismal environment. Binding of TFs to specific genomic targets is defined by sequence motifs and chromatin epige- netic marks, and can be altered by the presence of GxE-QTNs. To discover genes modulated by GxE-QTNs, we have recently established a high-throughput approach to perturb the cellular environment by a panel of 50 in vitro treatments, including vitamins, metal ions, common drugs and hormones. Here we propose to use this approach to dissect these GxE-QTNs and the underlying molecular mechanism by: i) performing functional ge- nomics assays capturing chromatin accessibility; ii) analyzing the effects of naturally occurring genetic variation in regulatory elements; and iii) combining RNA-seq, ATAC-seq, MPRA and GWAS data to co-localize association signals and pinpoint complex traits causal variants.