Molecular, Bioinformatic and Statistical Approaches to Identify Genes Underlying Complex Traits in Livestock PDF Download

Author: Laura Grapes
Publisher:
ISBN:
Category :
Languages : en
Pages : 254

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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: Haja N. Kadarmideen
Publisher: Springer
ISBN: 3319433350
Category : Science
Languages : en
Pages : 161

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Book Description
This two-volume work provides an overview on various state of the art experimental and statistical methods, modeling approaches and software tools that are available to generate, integrate and analyze multi-omics datasets in order to detect biomarkers, genetic markers and potential causal genes for improved animal production and health. The book will contain online resources where additional data and programs can be accessed. Some chapters also come with computer programming codes and example datasets to provide readers hands-on (computer) exercises. This first volume presents the basic principles and concepts of systems biology with theoretical foundations including genetic, co-expression and metabolic networks. It will introduce to multi omics components of systems biology from genomics, through transcriptomics, proteomics to metabolomics. In addition it will highlight statistical methods and (bioinformatic) tools available to model and analyse these data sets along with phenotypes in animal production and health. This book is suitable for both students and teachers in animal sciences and veterinary medicine as well as to researchers in this discipline.

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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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: Rongling Wu
Publisher: Springer
ISBN: 9781441919120
Category : Science
Languages : en
Pages : 0

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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: Karsten Suhre
Publisher: Springer Science & Business Media
ISBN: 1461416892
Category : Medical
Languages : en
Pages : 328

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Book Description
This book is written by leading researchers in the fields about the intersection of genetics and metabolomics which can lead to more comprehensive studies of inborn variation of metabolism.

Author: Giovanni Parmigiani
Publisher: Springer Science & Business Media
ISBN: 0387216790
Category : Medical
Languages : en
Pages : 511

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Book Description
This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.

Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 740

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Book Description

Author: Nils Stein
Publisher: Springer
ISBN: 3319925288
Category : Science
Languages : en
Pages : 400

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Book Description
This book presents an overview of the state-of-the-art in barley genome analysis, covering all aspects of sequencing the genome and translating this important information into new knowledge in basic and applied crop plant biology and new tools for research and crop improvement. Unlimited access to a high-quality reference sequence is removing one of the major constraints in basic and applied research. This book summarizes the advanced knowledge of the composition of the barley genome, its genes and the much larger non-coding part of the genome, and how this information facilitates studying the specific characteristics of barley. One of the oldest domesticated crops, barley is the small grain cereal species that is best adapted to the highest altitudes and latitudes, and it exhibits the greatest tolerance to most abiotic stresses. With comprehensive access to the genome sequence, barley’s importance as a genetic model in comparative studies on crop species like wheat, rye, oats and even rice is likely to increase.

Author: Florian Markowetz
Publisher: Cambridge University Press
ISBN: 131638098X
Category : Science
Languages : en
Pages : 287

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Book Description
Whereas genetic studies have traditionally focused on explaining heritance of single traits and their phenotypes, recent technological advances have made it possible to comprehensively dissect the genetic architecture of complex traits and quantify how genes interact to shape phenotypes. This exciting new area has been termed systems genetics and is born out of a synthesis of multiple fields, integrating a range of approaches and exploiting our increased ability to obtain quantitative and detailed measurements on a broad spectrum of phenotypes. Gathering the contributions of leading scientists, both computational and experimental, this book shows how experimental perturbations can help us to understand the link between genotype and phenotype. A snapshot of current research activity and state-of-the-art approaches to systems genetics are provided, including work from model organisms such as Saccharomyces cerevisiae and Drosophila melanogaster, as well as from human studies.

Author: Yuan-Ming Zhang
Publisher: Frontiers Media SA
ISBN: 2889458342
Category :
Languages : en
Pages : 236

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Book Description
Genome-Wide Association Studies (GWAS) are widely used in the genetic dissection of complex traits. Most existing methods are based on single-marker association in genome-wide scans with population structure and polygenic background controls. To control the false positive rate, the Bonferroni correction for multiple tests is frequently adopted. This stringent correction results in the exclusion of important loci, especially for GWAS in crop genetics. To address this issue, multi-locus GWAS methodologies have been recommended, i.e., FASTmrEMMA, ISIS EM-BLASSO, mrMLM, FASTmrMLM, pLARmEB, pKWmEB and FarmCPU. In this Research Topic, our purpose is to clarify some important issues in the application of multi-locus GWAS methods. Here we discuss the following subjects: First, we discuss the advantages of new multi-locus GWAS methods over the widely-used single-locus GWAS methods in the genetic dissection of complex traits, metabolites and gene expression levels. Secondly, large experiment error in the field measurement of phenotypic values for complex traits in crop genetics results in relatively large P-values in GWAS, indicating the existence of small number of significantly associated SNPs. To solve this issue, a less stringent P-value critical value is often adopted, i.e., 0.001, 0.0001 and 1/m (m is the number of markers). Although lowering the stringency with which an association is made could identify more hits, confidence in these hits would significantly drop. In this Research Topic we propose a new threshold of significant QTN (LOD=3.0 or P-value=2.0e-4) in multi-locus GWAS to balance high power and low false positive rate. Thirdly, heritability missing in GWAS is a common phenomenon, and a series of scientists have explained the reasons why the heritability is missing. In this Research Topic, we also add one additional reason and propose the joint use of several GWAS methodologies to capture more QTNs. Thus, overall estimated heritability would be increased. Finally, we discuss how to select and use these multi-locus GWAS methods.