Genetic regulation of genes on active and inactive X chromosome and their contribution to sex-biased diseases

项目总结/摘要 长期以来，人类X染色体一直被假设在性别偏见的病因学中起着重要作用。 疾病和特征，特别是自身免疫性疾病，如狼疮。尽管X染色体很重要， 在遗传关联和功能基因组学研究中，这种疏忽主要是由于 独特的生物学。XY男性的半合子性需要XX女性来实现剂量补偿。 通过X染色体失活（XCI）的方式X连锁基因。因此，在女性中， 仅从活动的X（Xa）中删除，而对非活动的X（Xi）保持沉默。然而，高达10%的基因始终 在健康女性中逃避XCI，并且从Xa和Xi两者转录。15%到30%的基因 雌性动物或组织亚组中的XCI。我们假设这种个体间和个体内的异质性是遗传的。 影响和疾病相关。然而，X连锁基因和XCI逃逸的遗传结构仍然存在， 不太了解。我们最近首次表明，XCI逃避具有显著的遗传性和可变性， XCI逃逸基因在雌性偏向性状中具有显著增加的遗传力富集， 与性别平衡的特征相比。虽然有希望，但XCI状态的注释仅从 淋巴母细胞系，其在人组织/细胞类型中可能不同。最近的研究表明， 遗传性在疾病相关组织特异性基因周围区域富集。因此，匹配每个 在遗传力分析中，将性状与相关组织/细胞类型特异性XCI状态进行比较，可以确定疾病和性状 相关组织/细胞类型，其中逃避XCI起着重要作用（目的1）。为此，我们首先建议 - 经验贝叶斯方法，以推断XCI镶嵌的个体样本不变量中的XCI逃逸状态，或者 在群体规模批量RNA-seq数据中存在转录的杂合SNP。与以往的努力不同， 方法最大限度地提高了样本和X连锁基因的测定，以构建最全面的XCI逃逸 人类组织/细胞类型的景观。这样一个完整的图谱将使可靠的遗传力估计成为可能。 接下来，为了理解遗传对变量XCI逃逸的影响，我们提出了一个两步方法， 通过联合建模男性和女性样本来检测Xa/Xi的XCI嵌合和遗传调控， 与Xa和Xi表达水平的相关性（Xa-/Xi- QTL）（目的2）。我们的方法提供了实质性的进步 与其他方法相比，提高了检测Xa-/Xi-QTL的能力， Xa和Xi在很大程度上相似或2）将X连锁基因的总表达归因于来自Xa和Xi的表达。我们 将我们的方法应用于组织/细胞类型，并将鉴定的Xa-/Xi- QTL与现有基因组整合 广泛的关联研究，以确定组织/细胞类型特异性Xa和Xi基因和性状的关联。我们将应用 我们的方法应用于一些最大的数据集，包括狼疮、糖尿病和成瘾等各种特征。总的来说， 我们提出的方法将允许全面评估X染色体和XCI逃逸的作用， 在疾病和特征的病因学中起作用，特别是那些有性别偏见的疾病，如自身免疫性疾病。

PROJECT SUMMARY/ABSTRACT The human X chromosome has long been hypothesized to play a significant role in the etiology of sex-biased diseases and traits, particularly autoimmune diseases like lupus. Despite its importance, the X chromosome is largely understudied in genetic association and functional genomics studies. Such an omission is largely due to its unique biology. The hemizygosity of XY males necessitates XX females to achieve dosage compensation of X-linked genes by the means of X-chromosome inactivation (XCI). Thus, in females most genes are expressed only from the active X (Xa) and remain silent on the inactive X (Xi). However, up to 10% of genes consistently escape XCI in healthy females and are transcribed from both Xa and Xi. And 15-30% of genes variably escape XCI in a subset of females or tissues. We hypothesize such inter- and intra- individual heterogeneity is genetically influenced and disease relevant. However, the genetic architecture of X-linked genes and XCI escape remains poorly understood. We recently showed, for the first time, that XCI escape has significant heritability and variable XCI escape genes have a significantly increased enrichment of heritability in female-biased traits when compared to sex-balanced traits. Although promising, the annotations for XCI states were inferred only from lymphoblast cell lines, which could differ across human tissue/cell types. Recent works have shown disease heritability is enriched in regions surrounding genes specific to disease relevant tissues. Thus, matching each trait to relevant tissue/cell type specific XCI states in heritability analysis could pinpoint the disease and trait relevant tissue/cell types in which escape from XCI plays a significant role (Aim 1). To do so, we first propose an empirical bayes method to infer XCI escape states in an individual sample invariant of XCI mosaicism or presence of transcribed heterozygous SNPs in population scale bulk RNA-seq data. Unlike previous efforts, our method maximizes the samples and X-linked genes assayed to construct the most comprehensive XCI escape landscape across human tissue/cell types to date. Such a complete map will enable robust heritability estimation. Next, to understand the genetic influence on variable XCI escape, we propose a two-step method that accurately models XCI mosaicism and genetic regulation of Xa/Xi by jointly modeling male and female samples to detect associations with Xa and Xi expression levels (Xa-/Xi- QTL) (Aim 2). Our method offers substantial advancement and improves power to detect Xa-/Xi- QTLs compared to other approaches that 1) assume genetic regulation on Xa and Xi are largely similar or 2) attribute total expression of X-linked genes to expression from Xa and Xi. We will apply our approach across tissue/cell types and integrate the identified Xa-/Xi- QTL with existence genome wide association studies to identify tissue/cell type specific Xa and Xi gene and trait associations. We will apply our methods to some of the largest datasets for a variety of traits including lupus, diabetes, and addiction. Overall, our proposed methods will allow comprehensive assessment of the role the X chromosome and XCI escape plays in the etiology of diseases and traits, particularly those that are sex-biased like autoimmune diseases.