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Dissecting Pathway-Level Complex Traits In Yeast.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Dissecting Pathway-Level Complex Traits In Yeast./
Author:	Kern, Alexander F.
Description:	1 online resource (87 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 84-05, Section: B.
Contained By:	Dissertations Abstracts International84-05B.
Subject:	Gene expression. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29755785click for full text (PQDT)
ISBN:	9798352999837

Dissecting Pathway-Level Complex Traits In Yeast.
Kern, Alexander F.

Dissecting Pathway-Level Complex Traits In Yeast. - 1 online resource (87 pages)

Source: Dissertations Abstracts International, Volume: 84-05, Section: B.

Thesis (Ph.D.)--Stanford University, 2022.

Includes bibliographical references

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.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798352999837Subjects--Topical Terms:

643979
Gene expression.
Index Terms--Genre/Form:

542853
Electronic books.

Dissecting Pathway-Level Complex Traits In Yeast.
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502 $a Thesis (Ph.D.)--Stanford University, 2022.
504 $a Includes bibliographical references
520 $a 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.
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