Date of Award
Winter 12-15-2022
Degree Name
Doctor of Philosophy (PhD)
Degree Type
Dissertation
Abstract
Autism Spectrum Disorder (ASD) is a highly prevalent neurodevelopmental disorder that affects over 2% of the population. Studies of this disorder have demonstrated that genetics plays a strong role in the underlying etiology and over the past decade, substantial progress has been made in elucidating the genetic architecture. Large-scale studies have now been conducted to identify the genes involved in the genetic architecture by analyzing data from over 40,000 probands. However, the identification and characterization of regulatory elements involved have remained non-trivial for many reasons. Generally, studies that have analyzed whole genome sequencing (WGS) have demonstrated enrichment of de novo variants (DNVs), those that only appear in a child, in categories of regulatory elements in probands when compared to unaffected siblings. Therefore, a major goal in the field is to identify the individual regulatory elements that are involved in ASD and analyze the functional effects of regulatory mutations. In this dissertation, I present my findings focused on addressing this problem and present analyses and experiments generalizable to many human genetic applications. I first detail the analyses identifying and characterizing the first regulatory element associated with ASD. Second, I develop a method to analyze regulatory elements using large-scale reference genome data to help pinpoint sub-regions within the enhancer that may be crucial for activity as displayed by conservation across ~300 species. Last, I utilize massively parallel reporter assays (MPRAs) to screen the effects of rare regulatory variants identified from WGS of ASD families to identify functional patterns of these variants.
Language
English (en)
Chair and Committee
Tychele N Turner
Committee Members
Barak A Cohen
Recommended Citation
Padhi, Evin Mitchel, "Analysis of Regulatory Element Variation in Autism Spectrum Disorder" (2022). Arts & Sciences Electronic Theses and Dissertations. 2750.
https://openscholarship.wustl.edu/art_sci_etds/2750