Genomic Prediction of Complex Traits : Methods and Protocols / edited by Nourollah Ahmadi, Jérôme Bartholomé.

Format:

Book

Contributor:

Ahmadi, Nour, Editor.

Bartholome, Jérôme, Editor.

SpringerLink (Online service)

Series:

Springer Protocols (Springer-12345)

Methods in molecular biology 1940-6029 ; 2467

Methods in Molecular Biology, 1940-6029 ; 2467

Language:

English

Subjects (All):

Genetics.

Genetics and Genomics.

Local Subjects:

Genetics and Genomics.

Physical Description:

1 online resource (XI, 648 pages) : 73 illustrations, 63 illustrations in color.

Edition:

1st ed. 2022.

Contained In:

Springer Nature eBook

Place of Publication:

New York, NY : Springer US : Imprint: Humana, 2022.

System Details:

text file PDF

Summary:

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. .

Contents:

Genetic Bases of Complex Traits: From Quantitative Trait Loci to Predictions

Genomic Prediction of Complex Traits, Principles, Overview of Factors Affecting the Reliability of Genomic Prediction, and Algebra of the Reliability

Building a Calibration Set for Genomic Prediction, Characteristics to be Considered and Optimization Approaches

Genotyping, the Usefulness of Imputation to Increase SNP Density, Imputation Methods and Tools

Overview of Genomic Prediction Methods and the Associated Assumptions on the Variance of Marker Effect, and on the Architecture of the Target Trait

Overview of Major Computer Packages for Genomic Prediction of Complex Traits

Genome-Enabled Prediction Methods Based on Machine Learning

Genomic Prediction Methods Accounting for Non-Additive Genetic Effects

Genome and Environment Based Prediction Models and Methods of Complex Traits Incorporating Genotype × Environment Interaction

Accounting for Correlation between Traits in Genomic Prediction

Incorporation of Trait-Specific Genetic Information into Genomic Prediction Models

Incorporating Omics Data in Genomic Prediction

Integration of Crop Growth Models and Genomic Prediction

Phenomic Selection: A New and Efficient Alternative to Genomic Selection

From Genotype to Phenotype: Polygenic Prediction of Complex Human Traits

Genomic Prediction of Complex Traits in Animal Breeding with Long Breeding History, The Dairy Cattle Case

Genomic Selection in Aquaculture Species

Genomic Prediction of Complex Traits in Perennial Plants: A Case for Forest Trees

Genomic Prediction of Complex Traits in Forage Plants Species: Perennial Grasses Case

Genomic Prediction of Complex Traits in an Allogamous Annual Crop: The Case of Maize Single-Cross Hybrids

Genomic Prediction: Progress and Perspective for Rice Improvement

Analyzing the Economic Effectiveness of Genomic Selection Relative to Conventional Breeding Approaches.

Other Format:

Printed edition:

ISBN:

978-1-0716-2205-6

9781071622056

Access Restriction:

Restricted for use by site license.