Identification and characterization of skewed X chromosome inactivation using exome, transcriptome and whole genome bisulfite sequencing in patients with suspected rare genetic disease

Abstract

X-chromosome inactivation (XCI) is an epigenetic process that occurs during early embryonic development in mammalian females by randomly silencing one of two copies of the X chromosome in each cell. The preferential inactivation of either the maternal or paternal copy of the X chromosome in a majority of cells results in a skewed or non-random pattern of X inactivation and is observed in over 25% of adult females. Identifying skewed X inactivation is of clinical significance in patients with suspected rare genetic diseases due to the possibility of biased expression of disease-causing genes present on the active X chromosome. The current clinical test for the detection of skewed XCI relies solely on the methylation status of the androgen receptor (AR) gene locus resulting in uninformative or inconclusive data for 10-20 % of tests. Further, recent studies have shown inconsistency between methylation of the AR locus and the state of inactivation of the X chromosome. Thus, there exists a pressing need for alternative methods facilitating X-skew discovery. In chapter 1, I discuss and introduce XCI and its diagnostic relevance in rare genetic disorders. In chapter 2, I developed a novel method for estimating X inactivation status, using exome and transcriptome sequencing data derived from blood in 227 female samples. The method was validated against results from the clinical AR gene assay in 11 females with undiagnosed rare genetic disorders.The comparison of clinical X-skew testing to results from the NGS based analysis revealed regional variability of XCI patterns along the X chromosome highlighting the need for an in-depth understanding of epigenetic mechanisms underlying XCI. In chapter 3, I present a comprehensive evaluation of allele specific methylation (ASM) on the X chromosome using whole genome bisulfite sequencing in a large cohort of female patients with rare genetic disorders. The analysis includes the comparison of X-skew results achieved in chapter 2 with ASM measures used for detecting statistically significant imbalances in methylation patterns between two parental alleles. Finally, chapter 4 presents a conclusive summary of this work and discusses the clinical utility of emerging long-read sequencing technologies for advancing XCI detection in rare disease diagnostics. To summarize, my dissertation research elucidates the intricate landscape of XCI patterns using a novel method for detection of XCI and evaluates its relationship with ASM.