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...