東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

FindBook

Google Book

Amazon

博客來

Dissecting Pathway-Level Complex Traits In Yeast.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Dissecting Pathway-Level Complex Traits In Yeast./
作者:	Kern, Alexander F.
面頁冊數:	1 online resource (87 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-05, Section: B.
Contained By:	Dissertations Abstracts International84-05B.
標題:	Gene expression. -
電子資源:	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.
LDR:03706nmm a2200361K 4500 001 2359856
005 20230917195306.5
006 m o d
007 cr mn ---uuuuu
008 241011s2022 xx obm 000 0 eng d
020 $a 9798352999837
035 $a (MiAaPQ)AAI29755785
035 $a (MiAaPQ)STANFORDvy082sz2508
035 $a AAI29755785
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Kern, Alexander F. $3 3700469
245 1 0 $a Dissecting Pathway-Level Complex Traits In Yeast.
264 0 $c 2022
300 $a 1 online resource (87 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 84-05, Section: B.
500 $a Advisor: Gitler, Aaron D. ; Montgomery, Stephen; Sherlock, Gavin.
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.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Gene expression. $3 643979
650 4 $a Genomes. $3 592593
650 4 $a Evolution. $3 532919
650 4 $a Genomics. $3 600531
650 4 $a Biosynthesis. $3 516407
650 4 $a Antibiotics. $3 670318
650 4 $a Cloning. $3 571606
650 4 $a Protein expression. $3 3554057
650 4 $a Bioinformatics. $3 553671
650 4 $a Evolution & development. $3 3172418
650 4 $a Genetics. $3 530508
650 4 $a Pharmaceutical sciences. $3 3173021
655 7 $a Electronic books. $2 lcsh $3 542853
690 $a 0715
690 $a 0412
690 $a 0369
690 $a 0572
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a Stanford University. $3 754827
773 0 $t Dissertations Abstracts International $g 84-05B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29755785 $z click for full text (PQDT)