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Quantitative Genomic Approaches for ...

Penagaricano, Francisco.

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Quantitative Genomic Approaches for the Genetic Analysis of Complex Traits in Livestock Species.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Quantitative Genomic Approaches for the Genetic Analysis of Complex Traits in Livestock Species./
Author:	Penagaricano, Francisco.
Description:	172 p.
Notes:	Source: Dissertation Abstracts International, Volume: 76-04(E), Section: B.
Contained By:	Dissertation Abstracts International76-04B(E).
Subject:	Animal sciences. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3667837
ISBN:	9781321423587

Quantitative Genomic Approaches for the Genetic Analysis of Complex Traits in Livestock Species.
Penagaricano, Francisco.

Quantitative Genomic Approaches for the Genetic Analysis of Complex Traits in Livestock Species. - 172 p.

Source: Dissertation Abstracts International, Volume: 76-04(E), Section: B.

Thesis (Ph.D.)--The University of Wisconsin - Madison, 2014.

This dissertation deals with the genetic analysis of complex traits in livestock species. The first part focuses on the analysis of bull fertility with the aim of finding and characterizing genomic regions responsible for the genetic variation in this trait in cattle. Two complementary studies were performed, namely a genome-wide association study and a subsequent quantitative trait pathway-based analysis. These studies identified genomic regions, and particularly individual genes and pathways that showed significant effects on bull fertility. These findings contribute to a better understanding of the genetics underlying this complex traits in cattle, as well as provide opportunities for changing fertility by means of selective breeding. The second part of this thesis tackles the effect of maternal nutrition on the epigenome of the offspring in order to understand the genetic mechanisms underlying fetal programing in livestock. In particular, the effect of maternal methionine supplementation on the transcriptome of bovine preimplantation embryos, and the impact of different maternal diets on the transcriptome of fetal tissues in sheep were investigated. These studies provided evidence that maternal diet can indeed modulate gene expression in the offspring. Determination of gene expression changes could foreshadow potential effects of maternal diets on the future development of offspring, such as postnatal growth, production, health, and reproductive performance. The last part of this thesis evaluates the inference of causal networks in multivariate genetic systems. In particular, the inference of causal networks including latent variables in a quantitative genetics context, and the reconstruction of gene-phenotype networks integrating multi-omics data were investigated. Both procedures were applied to pig data to unravel the mechanisms underlying the antagonist relationship between growth and meat lean content with fat deposition and product quality. More generally, the proposed methods provide useful analytical tools to further learning about phenotypic and molecular causal structures underlying complex traits in farm species.

ISBN: 9781321423587Subjects--Topical Terms:

3174829
Animal sciences.

Quantitative Genomic Approaches for the Genetic Analysis of Complex Traits in Livestock Species.
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245 1 0 $a Quantitative Genomic Approaches for the Genetic Analysis of Complex Traits in Livestock Species.
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500 $a Source: Dissertation Abstracts International, Volume: 76-04(E), Section: B.
500 $a Adviser: Guilherme J.M. Rosa.
502 $a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2014.
520 $a This dissertation deals with the genetic analysis of complex traits in livestock species. The first part focuses on the analysis of bull fertility with the aim of finding and characterizing genomic regions responsible for the genetic variation in this trait in cattle. Two complementary studies were performed, namely a genome-wide association study and a subsequent quantitative trait pathway-based analysis. These studies identified genomic regions, and particularly individual genes and pathways that showed significant effects on bull fertility. These findings contribute to a better understanding of the genetics underlying this complex traits in cattle, as well as provide opportunities for changing fertility by means of selective breeding. The second part of this thesis tackles the effect of maternal nutrition on the epigenome of the offspring in order to understand the genetic mechanisms underlying fetal programing in livestock. In particular, the effect of maternal methionine supplementation on the transcriptome of bovine preimplantation embryos, and the impact of different maternal diets on the transcriptome of fetal tissues in sheep were investigated. These studies provided evidence that maternal diet can indeed modulate gene expression in the offspring. Determination of gene expression changes could foreshadow potential effects of maternal diets on the future development of offspring, such as postnatal growth, production, health, and reproductive performance. The last part of this thesis evaluates the inference of causal networks in multivariate genetic systems. In particular, the inference of causal networks including latent variables in a quantitative genetics context, and the reconstruction of gene-phenotype networks integrating multi-omics data were investigated. Both procedures were applied to pig data to unravel the mechanisms underlying the antagonist relationship between growth and meat lean content with fat deposition and product quality. More generally, the proposed methods provide useful analytical tools to further learning about phenotypic and molecular causal structures underlying complex traits in farm species.
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773 0 $t Dissertation Abstracts International $g 76-04B(E).
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