Dissecting pathway-level complex traits in yeast
Abstract/Contents
- Abstract
- Understanding the genetic and evolutionary basis of complex traits is an outstanding question in genetics. In contrast to Mendelian traits which are usually affected by one or a few genes, complex traits are affected by variation in multiple genes, often hundreds to thousands. This complexity makes it difficult to determine which biological processes and genetic variants affect these traits. Furthermore, identifying natural selection affecting these traits can be difficult without knowledge of which variants are relevant. One method for identifying the genetic basis of complex traits is quantitative trait locus (QTL) mapping using offspring from genetic crosses of laboratory organisms. In Chapter 2, S. cerevisiae offspring from two parental strains between which polygenic selection on gene expression in the ergosterol pathway was identified are examined to see the effect of this selection on metabolite levels, a more downstream endophenotype. While metabolite QTL and expression QTL overlapped well, the selection on gene expression did not lead to the expected changes in metabolite levels. A new test was developed to identify selection on the metabolite levels, and while there was significant evidence of natural selection affecting metabolite levels, it was clear that the selection on gene expression did not predict the selection on metabolite levels, suggesting the need for studying pathways at multiple levels of endophenotypes to understand selection on complex traits. An additional complexity in understanding complex traits is the effects of environment. Not only can the environment in which an organism lives directly affect a complex trait, but some genetic variants will have different effects on fitness or other traits based on the environment. These effects are known as gene-by-environment interactions (GxE). In chapter 3, we develop an improved method for precisely measuring the effects of natural genetic variants in yeast using precision editing and growth competitions. We then use this technique to identify natural variants in S. cerevisiae which have GxE interactions, first within QTL regions and then within the ergosterol biosynthesis pathway. Together, these two chapters advance our understanding of complex traits at the pathway-level, first by looking between levels of endophenotypes, and then looking at complexity imparted by the environment through GxE interactions.
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 | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Kern, Alexander |
|---|---|
| Degree supervisor | Fraser, Hunter B |
| Thesis advisor | Fraser, Hunter B |
| Thesis advisor | Gitler, Aaron D |
| Thesis advisor | Montgomery, Stephen, 1979- |
| Thesis advisor | Sherlock, Gavin |
| Degree committee member | Gitler, Aaron D |
| Degree committee member | Montgomery, Stephen, 1979- |
| Degree committee member | Sherlock, Gavin |
| Associated with | Stanford University, Department of Genetics |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Alexander F. Kern. |
|---|---|
| Note | Submitted to the Department of Genetics. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/vy082sz2508 |
Access conditions
- Copyright
- © 2022 by Alexander Kern
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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