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 successfulMethods in Molecular Biologyseries 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 Protocolsis 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. 

Preface...
Table of Contents...
Contributing Authors...

1. Genetic Bases of Complex Traits: From Quantitative Trait Loci to Predictions
Nourollah Ahmadi

2. Genomic Prediction of Complex Traits, Principles, Overview of Factors Affecting the Reliability of Genomic Prediction, and Algebra of the Reliability
Jean-Michel Elsen

3. Building a Calibration Set for Genomic Prediction, Characteristics to be Considered and Optimization Approaches
Simon Rio, Alain Charcosset, Tristan Mary-Huard, Laurence Moreau, and Renaud Rincent

4. Genotyping, the Usefulness of Imputation to Increase SNP Density, Imputation Methods and Tools
Florence Phocas

5. Overview of Genomic Prediction Methods and the Associated Assumptions on the Variance of Marker Effect, and on the Architecture of the Target Trait
Reka Howard, Diego Jarquin, and Jose Crossa

6. Overview of Major Computer Packages for Genomic Prediction of Complex Traits
Giovanny Covarrubias-Pazaran

7. Genome-Enabled Prediction Methods Based on Machine Learning
Edgar L. Reinoso-Peláez, Daniel Gianola, and Oscar González-Recio

8. Genomic Prediction Methods Accounting for Non-Additive Genetic Effects
Luis Varona, Andred Legarra, Miguel A. Toro, and Zulma G. Vitezica

9. Genome and Environment Based Prediction Models and Methods of Complex Traits Incorporating Genotype × Environment Interaction
Jose Cross, Osval Antonio Montesinos-López, Paulino Pérez-Rodríguez, Germano Costa-Neto, Abelardo Montesinos-López, Roberto Fritsche-Neto, Johannes W.R. Martini, Rodomiro Ortiz, Morten Lillemo, Diego Jarquin, Jaime Cuevas, and Renaud Rincent

10. Accounting for Correlation between Traits in Genomic Prediction
Osval Antonio Montesinos-López, Abelardo Montesinos-López, Brandon A. Mosqueda-Gonzalez, José Cricelio Montesinos-López, and José Crossa

11. Incorporation of Trait-Specific Genetic Information into Genomic Prediction Models
Shaolei Shi, Zhe Zhang, Bingjie Li, Shangli Zhang, and Lingzhao Fang

12. Incorporating Omics Data in Genomic Prediction
Johannes W.R. Martini, Ning Gao, and José Crossa

13. Integration of Crop Growth Models and Genomic Prediction
Akio Onogi

14. Phenomic Selection: A New and Efficient Alternative to Genomic Selection
Pauline Robert, Charlotte Brault, Renaud Rincent, and Vincent Segura

15. From Genotype to Phenotype: Polygenic Prediction of Complex Human Traits
Timothy G. Raben, Louis Lello, Erik Widen, and Stephen D.H. Hsu

16. Genomic Prediction of Complex Traits in Animal Breeding with Long Breeding History, The Dairy Cattle Case
Joel Ira Weller

17. Genomic Selection in Aquaculture Species
François Allal and Nguyen Hong Nguyen

18. Genomic Prediction of Complex Traits in Perennial Plants: A Case for Forest Trees
Fikret Isik

19. Genomic Prediction of Complex Traits in Forage Plants Species: Perennial Grasses Case
Philippe Barre, Torben Asp, Stephen Byrne, Michael Casler, Marty Faville, Odd-Arne Rognli, Isabel Roldan-Ruiz, Leif Skot, and Marc Ghesquière

20. Genomic Prediction of Complex Traits in an Allogamous Annual Crop: The Case of Maize Single-Cross Hybrids
Isadora C. Martins Oliviera, Arthur Bernardeli, José H. Soler Guilhen, and Maria M. Pastina

21. Genomic Prediction: Progress and Perspective for Rice Improvement 
Jérôme Bartholomé, Parthiban Thathapalli Prakash, and Joshua N. Cobb

22. Analyzing the Economic Effectiveness of Genomic Selection Relative to Conventional Breeding Approaches
Aline Fugeray-Scarbel, Sarah Ben-Sadoun, Sophie Bouchet, and Stéphane Lemarié

Subject Index List...

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 successfulMethods in Molecular Biologyseries 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 Protocolsis a valuable resource for scientists and researchers who are interested in learning more about this important and developing field.