X-Viz: Annotation and Visualization of Genes in the Human X-Chromosomes by their Activation States
Open Access
Author:
Moussa, Karine
Graduate Program:
Bioinformatics and Genomics
Degree:
Master of Science
Document Type:
Master Thesis
Date of Defense:
November 05, 2021
Committee Members:
Dajiang Liu, Thesis Advisor/Co-Advisor Laura Carrel, Committee Member George Perry, Program Head/Chair Suzanne Gonzalez, Thesis Advisor/Co-Advisor
Keywords:
X chromosome inactivation gene expression sex-biased traits
Abstract:
The human X chromosome carries >1000 genes with essential functions that are critical for development and disease. However, the X chromosome is severely under- studied compared to autosomes, in part due to the unique biology of X chromosome inactivation (XCI). XCI is an epigenetic process that silences one X chromosome in each female and balances gene dosage between sexes. Yet, ~12-35% of genes escape XCI in females and exhibit expression in both X chromosomes. Escape from XCI shows inter- individual differences, induces dosage imbalance, and may influence disease. Much progress by us and others has been made to understand XCI. Researchers have developed several methods to classify and predict XCI status, each with their strengths and limitations. Yet, there still lacks a comprehensive and convenient platform for users to explore different analyses results, annotate X-linked genes and associate them with diseases. We present X- Viz, an R Shiny app, to fill this gap. This application is the first genome browser to summarize and synthesize the present knowledge of XCI escape genes through interactive visualization tools.
