DNA as a crystal ball : predicting outcomes in complex traits and genome editing
Abstract/Contents
- Abstract
- Genome-scale molecular biology datasets, unobtainable only twenty years ago, are now routinely generated. New DNA-centric technologies are undoubtedly powerful, yet bias from low specificity hybridization and differential environmental and genetic backgrounds may still dwarf the anticipated effects of genetic elements. Indeed, the deluge of new data types has outpaced assessments of these biases. This work advances methods for maximizing insight and mitigating bias for three nascent tools: CRISPR-associated protein 9 (Cas9), chromatin profiling and genome-wide association studies. Cas9 has proven an extremely adaptable research tool, comprising several technologies that fall under the umbrella of precision genome and epigenome editing: knockout, deletion, activation and silencing of genetic elements, as well as homology-directed repair and base editing of living cells. A race to engineer ever more powerful Cas9 variants is underway, but the fundamental properties underlying Cas9 activity are not known. In turn, this work develops High-Throughput Sequencing followed by Fluorescent Ligand Interaction Profiling (HiTS-FLIP) and massively parallel filter binding to resolve the kinetic and thermodynamic properties that promote successful genome editing and offers an unsupervised method to remove signatures of confounding from large-scale Cas9 screening datasets downstream of editing. Advances in profiling histone marks, chromatin looping and human genetic variation have invited closer study of the significance of non-coding genetic variation. The strongly polygenic architecture indicated by genome-wide association studies for many complex traits has incited further interest and created openings for intersecting heritable signal with other molecular profiling. This work presents numerous approaches for synthesizing these data into novel findings. In particular, the broad enrichment for enhancers, promoters and genic regions, irrespective of whether the genetic elements are ostensibly pertinent to the trait of interest, suggests an extreme conclusion: that nearly all transcribed genes for a cell type can influence the traits derived from that cell type. If true, complex traits are not merely polygenic, but 'omnigenic.' The answers thought to lie in our DNA are perhaps irresistibly tantalizing, yet we gaze at our peril. Fortune-telling is best met with healthy skepticism; otherwise, every suspension of disbelief bolsters an ever more powerful illusion.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2019; ©2019 |
| Publication date | 2019; 2019 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Boyle, Evan August |
|---|---|
| Degree supervisor | Greenleaf, William James |
| Degree supervisor | Pritchard, Jonathan D |
| Thesis advisor | Greenleaf, William James |
| Thesis advisor | Pritchard, Jonathan D |
| Thesis advisor | Bassik, Michael |
| Thesis advisor | Fraser, Hunter B |
| Degree committee member | Bassik, Michael |
| Degree committee member | Fraser, Hunter B |
| Associated with | Stanford University, Department of Genetics. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Evan August Boyle. |
|---|---|
| Note | Submitted to the Department of Genetics. |
| Thesis | Thesis Ph.D. Stanford University 2019. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2019 by Evan August Boyle
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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