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Author: Publisher: ISBN: Category : Languages : en Pages : 328
Book Description
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
Author: Publisher: ISBN: Category : Languages : en Pages : 328
Book Description
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
Author: Nourollah Ahmadi Publisher: Springer Nature ISBN: 1071622056 Category : Science Languages : en Pages : 651
Book Description
This volume explores the conceptual framework and the practical issues related to genomic prediction of complex traits in human medicine and in animal and plant breeding. The book is organized into five parts. Part One reminds molecular genetics approaches intending to predict phenotypic variations. Part Two presents the principles of genomic prediction of complex traits, and reviews factors that affect its reliability. Part Three describes genomic prediction methods, including machine-learning approaches, accounting for different degree of biological complexity, and reviews the associated computer-packages. Part Four reports on emerging trends such as phenomic prediction and incorporation into genomic prediction models of “omics” data and crop growth models. Part Five is dedicated to lessons learned from cases studies in the fields of human health and animal and plant breeding, and to methods for analysis of the economic effectiveness of genomic prediction. Written in the highly successful Methods in Molecular Biology series format, the book provides theoretical bases and practical guidelines for an informed decision making of practitioners and identifies pertinent routes for further methodological researches. Cutting-edge and thorough, Complex Trait Predictions: Methods and Protocols is a valuable resource for scientists and researchers who are interested in learning more about this important and developing field. Chapters 3, 9, 13, 14, and 21 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Author: Andrew H. Paterson Publisher: CRC Press ISBN: 0429525419 Category : Science Languages : en Pages : 413
Book Description
In the past 10 years, contemporary geneticists using new molecular tools have been able to resolve complex traits into individual genetic components and describe each such component in detail. Molecular Dissection of Complex Traits summarizes the state of the art in molecular analysis of complex traits (QTL mapping), placing new developments in thi
Author: Rongling Wu Publisher: Springer ISBN: 9781441919120 Category : Science Languages : en Pages : 0
Book Description
This book introduces the basic concepts and methods that are useful in the statistical analysis and modeling of the DNA-based marker and phenotypic data that arise in agriculture, forestry, experimental biology, and other fields. It concentrates on the linkage analysis of markers, map construction and quantitative trait locus (QTL) mapping, and assumes a background in regression analysis and maximum likelihood approaches. The strength of this book lies in the construction of general models and algorithms for linkage analysis, as well as in QTL mapping in any kind of crossed pedigrees initiated with inbred lines of crops.
Author: Sukanta Mondal Publisher: Academic Press ISBN: 0128206128 Category : Science Languages : en Pages : 340
Book Description
Advances in Animal Genomics provides an outstanding collection of integrated strategies involving traditional and modern - omics (structural, functional, comparative and epigenomics) approaches and genomics-assisted breeding methods which animal biotechnologists can utilize to dissect and decode the molecular and gene regulatory networks involved in the complex quantitative yield and stress tolerance traits in livestock. Written by international experts on animal genomics, this book explores the recent advances in high-throughput, next-generation whole genome and transcriptome sequencing, array-based genotyping, and modern bioinformatics approaches which have enabled to produce huge genomic and transcriptomic resources globally on a genome-wide scale. This book is an important resource for researchers, students, educators and professionals in agriculture, veterinary and biotechnology sciences that enables them to solve problems regarding sustainable development with the help of current innovative biotechnologies. - Integrates basic and advanced concepts of animal biotechnology and presents future developments - Describes current high-throughput next-generation whole genome and transcriptome sequencing, array-based genotyping, and modern bioinformatics approaches for sustainable livestock production - Illustrates integrated strategies to dissect and decode the molecular and gene regulatory networks involved in complex quantitative yield and stress tolerance traits in livestock - Ensures readers will gain a strong grasp of biotechnology for sustainable livestock production with its well-illustrated discussion
Author: Laura Grapes Publisher: ISBN: Category : Languages : en Pages : 254
Book Description
One of the primary goals for molecular geneticists working with livestock species is to identify and characterize genes underlying complex traits, the so-called quantitative trait loci (QTL). The primary strategy for identifying QTL involves several steps, one being fine mapping of a previously defined chromosomal region and another being identification of candidate genetic polymorphisms that may cause differences in phenotype. The studies presented in this dissertation address fine mapping methodology, use of the candidate gene approach for directly identifying candidate genetic polymorphisms and use of bioinformatic tools for identifying genetic polymorphisms in silico. Results from simulation studies suggest that two linkage disequilibrium-based fine mapping methods, one using haplotype information, the other using single marker information, provide QTL position estimates with comparable accuracy. Additional research is necessary to determine optimal fine mapping methods under experimental research conditions. The candidate gene studies presented, concerting the porcine connexin 37 (CX37) and bone morphogenetic factor 15 (BMP15) genes, highlight use of comparative sequence and biological information for identifying candidate genetic variants. Two synonymous mutations were discovered in the CX37 gene, which was subsequently mapped to SSC6 q24-31; however, these mutations were not significantly associated with fertility traits as hypothesized. Unfortunately, mutations could not be identified in BMP15, which was physically mapped to SSCX p11-13. Bioinformatic tools are shown here to be lucrative for identifying putative single nucleotide polymorphisms (SNPs) from redundant expressed sequence tag (EST) information in the pig. Using computer-derived SNPs, a correlation of 0.77 (p
Author: Bruce Walsh Publisher: Oxford University Press ISBN: 0192566644 Category : Science Languages : en Pages : 1504
Book Description
Quantitative traits-be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene-usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important. Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, showing the interplay between theory and data with extensive discussions on statistical issues relating to the estimation of the biologically relevant parameters for these models. Quantitative genetics is viewed as the bridge between complex mathematical models of trait evolution and real-world data, and the authors have clearly framed their treatment as such. This is the second volume in a planned trilogy that summarizes the modern field of quantitative genetics, informed by empirical observations from wide-ranging fields (agriculture, evolution, ecology, and human biology) as well as population genetics, statistical theory, mathematical modeling, genetics, and genomics. Whilst volume 1 (1998) dealt with the genetics of such traits, the main focus of volume 2 is on their evolution, with a special emphasis on detecting selection (ranging from the use of genomic and historical data through to ecological field data) and examining its consequences.
Author: Sukanta Mondal Publisher: Academic Press ISBN: 0128205954 Category : Science Languages : en Pages : 338
Book Description
Advances in Animal Genomics provides an outstanding collection of integrated strategies involving traditional and modern - omics (structural, functional, comparative and epigenomics) approaches and genomics-assisted breeding methods which animal biotechnologists can utilize to dissect and decode the molecular and gene regulatory networks involved in the complex quantitative yield and stress tolerance traits in livestock. Written by international experts on animal genomics, this book explores the recent advances in high-throughput, next-generation whole genome and transcriptome sequencing, array-based genotyping, and modern bioinformatics approaches which have enabled to produce huge genomic and transcriptomic resources globally on a genome-wide scale. This book is an important resource for researchers, students, educators and professionals in agriculture, veterinary and biotechnology sciences that enables them to solve problems regarding sustainable development with the help of current innovative biotechnologies. Integrates basic and advanced concepts of animal biotechnology and presents future developments Describes current high-throughput next-generation whole genome and transcriptome sequencing, array-based genotyping, and modern bioinformatics approaches for sustainable livestock production Illustrates integrated strategies to dissect and decode the molecular and gene regulatory networks involved in complex quantitative yield and stress tolerance traits in livestock Ensures readers will gain a strong grasp of biotechnology for sustainable livestock production with its well-illustrated discussion
Author: Tim Bernard Bigdeli Publisher: ISBN: Category : Languages : en Pages :
Book Description
Etiological models of complex disease are elusive[46, 33, 9], as are consistently replicable findings for major genetic susceptibility loci[54, 14, 15, 24]. Commonly-cited explanations invoke low-frequency genomic variation[41], allelic heterogeneity at susceptibility loci[33, 30], variable etiological trajectories[18, 17], and epistatic effects between multiple loci; these represent among the most methodologically-challenging issues in molecular genetic studies of complex traits. The response has been con- sistently reactionary -- hypotheses regarding the relative contributions of known functional elements, or emphasizing a greater role of rare variation[46, 33] have undergone periodic revision, driving increasingly collaborative efforts to ascertain greater numbers of participants and which assay a rapidly-expanding catalogue of human genetic variation. Major deep-sequencing initiatives, such as the 1,000 Genomes Project, are currently identifying human polymorphic sites at frequencies previously unassailable and, not ten years after publication of the first major genome-wide association findings, re-sequencing has already begun to displace GWAS as the standard for genetic analysis of complex traits. With studies of complex disease primed for an unprecedented survey of human genetic variation, it is essential that human geneticists address several prominent, problematic aspects of this research. Realizations regarding the boundaries of human traits previously considered to be effectively disparate in presentation[44, 39, 35, 27, 25, 12, 4, 13], as well as profound insight into the extent of human genetic diversity[23, 22] are not without consequence. Whereas the resolution of fine-mapping studies have undergone persistent refinement, recent polygenic findings suggest a less discriminant basis of genetic liability, raising the question of what a given, unitary association finding actually represents. Furthermore, realistic expectations regarding the pattern of findings for a particular genetic factor between or even within populations remain unclear. Of interest herein are methodologies which exploit the finite extent of genomic variability within human populations to distinguish single-point and cumulative group differences in liability to complex traits, the range of allele frequencies for which common association tests are appropriate, and the relevant dimensionality of common genetic variation within ethnically-concordant but differentially ascertained populations. Using high-density SNP genotype data, we consider both hypothesis-driven and agnostic (genome-wide) approaches to association analysis, and address specific issues pertaining to empirical significance and the statistical properties of commonly- applied tests. Lastly, we demonstrate a novel perspective of genome-wide genetic "background" through exhaustive evaluation of fundamental, stochastic genetic processes in a sample of matched affected and unaffected siblings selected from high- density schizophrenia families.
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Author: Nourollah Ahmadi
Author: Andrew H. Paterson
Author: Rongling Wu
Author: Sukanta Mondal
Author: Laura Grapes
Author: Bruce Walsh
Author: Sukanta Mondal
Author: Hee-Bok Park
Author: Tim Bernard Bigdeli