Genomic Prediction of Complex Traits: Methods and Protocols

This book explores the conceptual framework and practical issues related to genomic prediction of complex traits in human medicine, animal, and plant breeding. It is organized into five parts and provides theoretical bases and practical guidelines for practitioners.

Format: Paperback / softback
Length: 648 pages
Publication date: 23 April 2023
Publisher: Springer-Verlag New York Inc.

This comprehensive volume delves into the intricate realm of genomic prediction, encompassing both the conceptual framework and the practical challenges associated with its application in human medicine, animal breeding, and plant breeding. Structured into five distinct parts, the book offers a comprehensive exploration of this field.

Part One serves as a foundational primer, revisiting molecular genetics approaches aimed at predicting phenotypic variations. It sheds light on the theoretical foundations and methodologies employed in this domain, emphasizing their role in understanding the genetic basis of complex traits.

Part Two takes a deeper dive, presenting the principles of genomic prediction and delving into the factors that influence its reliability. It examines the challenges and opportunities inherent in accurately predicting the genetic contributions to complex traits, encompassing both genetic and environmental influences.

Part Three presents a comprehensive review of genomic prediction methods, encompassing a wide range of approaches. It explores machine-learning techniques, which have gained prominence in recent years due to their ability to handle large datasets and complex biological relationships. The chapter also discusses the incorporation of various degrees of biological complexity into genomic prediction models, accounting for the intricate interplay between genes and environmental factors.

Part Four explores emerging trends in genomic prediction, such as phenomic prediction, which involves the integration of multi-dimensional data, including genomics, transcriptomics, proteomics, and environmental information, to enhance trait prediction accuracy. Additionally, the chapter discusses the incorporation of "omics" data and crop growth models into genomic prediction frameworks, leveraging the vast amounts of available data to improve predictions.

Part Five focuses on lessons learned from case studies in human health and animal and plant breeding, highlighting the practical applications of genomic prediction. It explores the economic implications of genomic prediction, discussing the potential benefits and challenges associated with its implementation. The book also provides valuable insights into methods for analyzing the economic effectiveness of genomic prediction, aiding practitioners in making informed decisions about its adoption.

Written in the highly successful Methods in Molecular Biology series format, Complex Trait Predictions: Methods and Protocols serves as a valuable resource for scientists and researchers seeking to expand their knowledge in this rapidly evolving field. Each chapter is meticulously crafted, providing theoretical foundations and practical guidelines for an informed decision-making process. The book identifies pertinent routes for further methodological research, fostering a deeper understanding of genomic prediction and its potential applications.

In addition to its comprehensive content, the book offers several valuable features. Chapters 3, 9, 13, 14, and 21 are available open access under a Creative Commons Attribution 4.0 International License via the link: link.springer.com. This accessibility ensures that researchers from all backgrounds can access and utilize the valuable information contained within these chapters, fostering interdisciplinary collaboration and advancing the field of genomic prediction.

In conclusion, Complex Trait Predictions: Methods and Protocols is a groundbreaking resource that caters to the needs of scientists and researchers seeking to unravel the genetic basis of complex traits. With its comprehensive coverage, theoretical foundations, and practical guidelines, the book empowers practitioners to make informed decisions and identifies promising avenues for further methodological research. As the field of genomic prediction continues to evolve, this book will remain a valuable asset for anyone interested in advancing our understanding of genetics and its applications in medicine, agriculture, and other fields.

Weight: 1244g
Dimension: 254 x 178 (mm)
ISBN-13: 9781071622070
Edition number: 1st ed. 2022