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Date Permissions Signed

1-27-2021

Date of Award

Winter 2021

Document Type

Masters Thesis

Department or Program Affiliation

Biology

Degree Name

Master of Science (MS)

Department

Biology

First Advisor

Pollard, Dan A.

Second Advisor

Pillitteri, Lynn

Third Advisor

Zinkgraf, Matthew

Abstract

As organisms respond to changes in their environment genetic variation between individuals can directly affect organismal trait phenotypes by altering gene expression. Historically, studies have focused on the effect of genetic variation on mRNA synthesis (transcription) and decay rates. Relatively few studies have probed the relationship between DNA variants and protein-specific regulation of individual genes, despite the plethora of evidence that RNA levels are often poor proxies for protein levels. No study to date has mapped genetic variation associated with dynamic protein levels. In this study we investigated the location and identity of genetic variants acting on protein expression dynamics for the genes Fig1, Fus3, and Tos6 during mating pheromone response in isolates of the budding yeast Saccharomyces cerevisiae. We classified protein level variation as either local (driven by variation within the locus of the gene of interest) or as trans-acting (driven by variation elsewhere in the genome) by swapping gene of interest alleles between lab and clinical strain isolates. We previously found that Fig1p protein levels are controlled by trans-acting genetic variants and in this study we found evidence of local effects acting on TOS6 protein abundance but could not disentangle local from trans effects for the Fus3 gene. To map quantitative trait loci associated with Fig1 protein level variation (pQTL) during mating pheromone response we used a novel time-based Bulk Segregant Analysis (BSA) approach combined with Fluorescence Activated single-Cell Sorting (FACS) and Next-Gen Sequencing (NGS). These findings demonstrate the value of mapping protein expression dynamics and shed light on the complex nature of genotype-phenotype relationships in natural populations.

Type

Text

Keywords

quantitative genetics, gene expression, protein expression, bulk segregant analysis, QTL mapping, yeast

Publisher

Western Washington University

OCLC Number

1241101549

Subject – LCSH

Human gene mapping; Quantitative genetics; Messenger RNA; Phenotype; Fluoroscopy; Genotype-environment interaction

Format

application/pdf

Genre/Form

masters theses

Language

English

Rights

Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this document for commercial purposes, or for financial gain, shall not be allowed without the author’s written permission.

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