Development and application of high-throughput sequencing based methods to explore human variation and disease
Abstract/Contents
- Abstract
- In-depth studies of human disease and variation have been greatly enabled by a variety of high-throughput sequencing methods. Efforts that integrate genomic, transcriptomic and protein/nucleic acid binding genome-wide further expand our understanding of the genome and the regulatory information that governs it. In this work we present three efforts centered on the use of integrated high-throughput sequencing methods to unravel questions of human disease and variation. The first describes a novel method for simultaneous DNA and RNA sequencing library preparation (Simul-seq), which provides comprehensive data from small quantities of cells or tissue in a streamlined workflow. Single assay integration provides opportunities for analysis of regulatory variation, RNA editing and allele-specific expression, in addition to genotype and phenotype information. Applying Simul-seq to a laser-capture microdissected esophageal adenocarcinoma, we reveal a highly aneuploid genome with corresponding increases in allele specific expression and both novel and known expressed, nonsynomous mutations. The next work uses ChIP-seq, RNA-seq and Hi-C among other data types to enumerate the effects of genetic variation on chromatin state and RNA levels. Among the findings, we show that long-range interactions govern the effects of QTLs on distal chromatin variation. Finally we profile a diverse panel of 25 cell lines using an improved ChIA-PET method along with RNA-seq to better understand the role chromosomal looping plays in genetic and epigenetic regulation. Enabled by the modified protocol, we find evidence for differential looping between cell types. Taken together we have shown that integration of sequencing methods, or their data provide the best possible foundation for genome interpretation and personalized medicine.
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 | Spacek, Damek Vaclav | |
|---|---|---|
| Associated with | Stanford University, Department of Genetics. | |
| Primary advisor | Snyder, Michael, Ph. D | |
| Thesis advisor | Snyder, Michael, Ph. D | |
| Thesis advisor | Altman, Russ | |
| Thesis advisor | Bustamante, Carlos | |
| Thesis advisor | Urban, Alexander | |
| Advisor | Altman, Russ | |
| Advisor | Bustamante, Carlos | |
| Advisor | Urban, Alexander |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Damek Vaclav Spacek. |
|---|---|
| Note | Submitted to the Department of Genetics. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2017. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2017 by Damek Vaclav Spacek
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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