Impact of common and rare regulatory variation on human disease

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Abstract/Contents

Abstract
The rate at which we have identified human genetic variation has greatly outpaced our capacity to characterize the functional significance of individual variants. This interpretation bottleneck is the product of several distinct challenges that ultimately hinder our ability to link individual variants with specific phenotypes. One challenge is that the vast majority of variants are found in non-coding regions of the human genome and have no immediately obvious functional consequences. Another challenge is the overwhelming abundance of rare and novel variants that are found in a given individual - these variants are difficult to interpret because we cannot be certain of their association with any particular phenotypic effect. In this thesis, I address several questions regarding the interpretation of genetic variants, with a focus on those that are found in non-coding regions of the genome. After providing a general overview of the variant interpretation problem, I discuss one of the primary risks associated with clinical genome sequencing - namely the problem of dealing with incidental findings. I then discuss how we can improve our ability to identify common and rare regulatory variation using isolated populations and family-based study designs. Finally, I provide several examples demonstrating the clinical utility of RNA sequencing for patients with rare, undiagnosed genetic disorders.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2017
Issuance monographic
Language English

Creators/Contributors

Associated with Zappala, Zachary
Associated with Stanford University, Department of Genetics.
Primary advisor Montgomery, Stephen, 1979-
Thesis advisor Montgomery, Stephen, 1979-
Thesis advisor Bustamante, Carlos
Thesis advisor Pritchard, Jonathan D
Thesis advisor Sidow, Arend
Advisor Bustamante, Carlos
Advisor Pritchard, Jonathan D
Advisor Sidow, Arend

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Zachary Zappala.
Note Submitted to the Department of Genetics.
Thesis Thesis (Ph.D.)--Stanford University, 2017.
Location electronic resource

Access conditions

Copyright
© 2017 by Zachary Zappala
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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