Technology Transfer

Course Description

In collaboration with the Indian Council for Agricultural Research – Indian Institute of Rice Research (ICAR-IIRR), the course “Fundamentals of Genomic Predictions and Data-Driven Crop Breeding” offers a thorough exploration of the latest techniques in modern plant breeding. Participants will delve into the areas of quantitative genetics and statistical genomics, acquiring vital knowledge of genomic selection strategies and their practical applications. The curriculum includes advanced statistical models such as linear and mixed models, ridge regression, Bayesian methods, and kernel approaches, giving participants a strong foundation in predictive breeding.

Additionally, the course covers new concepts like the Usefulness Criterion and Optimal Parental Contributions, aimed at enhancing the effectiveness and efficiency of crossing strategies. It also addresses the dissection of genotype-by-environment (G x E) interactions in crop breeding, employing predictive tools for their analysis. Attendees will learn about innovative approaches for designing training and testing sets, incorporating sparse testing, and more.

The course features a hands-on approach, allowing participants to work with real-world datasets to implement genomic selection in breeding programs, analyze G x E interactions, and design crossing strategies. This practical experience ensures that participants not only understand theoretical concepts but also develop the essential skills needed to apply genomic selection in their professional endeavors.

Designed for individuals with a basic understanding of crop breeding and genetics, the course is accessible to professionals with varied levels of statistical and R programming expertise, accommodating a diverse audience in the field.

Course Objectives

This course integrates quantitative genetics and statistical genomics with modern breeding approaches, focusing on genomic selection and data-driven decision-making in crop breeding. It enhances understanding of quantitative genetics, statistical models for genomic predictions, and genomic selection implementation in breeding programs. The course covers advanced techniques for parent selection and crossing block design using genotypic and phenotypic datasets. Participants will gain practical skills to apply these concepts in real-world crop improvement scenarios.

By the end of the training course, the participants should be able to:

• Gain the basic and advanced knowledge of quantitative genetic and statistical genomics relevant to modern breeding
• Understand the different relationship matrices and their use in genomic predictions and crop breeding
• Understand the linear and mixed models to perform phenotypic data analysis and genomic predictions
• Understand and apply the basic and advanced statistical models to perform the genomic selections
• Understand the fundamentals of genomic selection (3W’s of Genomic selection: Why, When, and Where to apply it in the breeding program)
• Understand the G x E interactions and design sparse testing design in dissecting G x E interactions and
• Understand the Usefulness criterion and Optimal Parental Contributions to design the crossing block and predict the performance of cross combinations.

Target Learners

Plant breeders, geneticists, graduate students, postdoctoral fellows, research scholars, and assistants involved in crop breeding programs. This course is mainly intended for those keen to learn the modern data-driven breeding approaches and how to leverage the data sets to perform genomic selection and implement them in breeding programs.

Key Modules:

• Module 1: Introduction and Learning R and R Markdown
• Module 2: Fundamentals of Quantitative Genetics and Predictive Modeling
• Module 3: G x E Interactions Dissection in Predictive Breeding
• Module 4: Practical Implementation of Genomic Selection in Plant Breeding
• Module 5: Breeding and Crossing Scheme Optimizations.

Learning Modality

The course will be delivered face-to-face with a mixed modality of synchronous and asynchronous discussions involving theoretical concepts, practical and hands-on exercises, and self-paced e-learning activities.

Participants eligibility

The participant highly encourages a basic understanding of breeding and statistics. Experience in using and running R is highly encouraged.

Course Overview

Biotic stresses due to pests and diseases are dynamic, and their occurrence is influenced by several factors, such as host genotype, cropping practices, and extreme weather events brought about by climate change. Major diseases caused by pathogens, and nematodes and insect pests, such as brown planthoppers, green leafhoppers and stemborers, reduce rice yields in different ecosystems, if these are not properly assessed and managed.

The use of host plant resistance is generally considered as the most economical, practical and environment-friendly strategy for pest management. It enables farmers to reduce yield losses, improve productivity and profitability without reliance on pesticides, which becomes increasingly important in the face of climate change. However, robust screening protocols are often lacking or not standardized. Hence, capacity development on the protocols used at IRRI for evaluation of resistance to biotic stresses will facilitate the identification and selection of resistant genotypes. A standard protocol will facilitate collaboration among different institutes. Acquiring skills in the evaluation of rice genotypes to biotic stresses is crucial for developing pest management strategies.

This two-week hands-on training course is designed to equip the participants with experiential skills in identification, collection, isolation,and evaluation of damages caused by major rice pests and diseases through immersive and applied learning.

The major rice diseases and pests covered by this course are bacterial blight, leaf and neck blast, sheath blight, false smut and tungro, root-knot nematode, brown planthopper, green leafhopper and yellow stemborer.

Course Objectives

In this training course, the participants are expected to:

• Familiarize themselves with the major pests and diseases of rice
• Obtain basic skills in proper handling and maintenance of pathogens and pests
• Undergo hands-on training on IRRI’s standard protocols for the evaluation of rice germplasm against major insect pests, nematode and diseases
• Learn skills in the interpretation of evaluation results
• Develop the ability to set-up appropriate conditions for the evaluation of resistance to insect pests, diseases, and nematode

Key Modules

• Overview of the major rice diseases and pests
• Collection and rearing of insects and nematodes in the greenhouse
• Collection, isolation, purification and preservation of pathogens
• Artificial pathogen inoculation and insect infestation of host plants
• Data collection, analysis, and interpretation

Target Participants

The course is intended for IRRI Staff, NARES partners, scientists, and students from research institutions. The training can accommodate 20 participants.

Learning Modality

The course will be delivered face-to-face through a mixed modality of synchronous and asynchronous discussions with hands-on exercises in the laboratory, greenhouse, and open concrete beds, and field trips.

Course Overview

The Fundamentals of Genomic Predictions and Data-Driven Crop Breeding is tailored for individuals engaged in crop sciences, such as students, researchers, and practitioners. It aims to integrate knowledge in quantitative genetics, predictive breeding, and innovative breeding methods, including usefulness criteria and optimal contributions in applied crop breeding. Participants will be educated on utilizing R software for fundamental and sophisticated data analysis. The course will delve deeply into the essential principles of quantitative genetics and the application of genomic selection in crop breeding.

We will explore a comprehensive understanding of basic and advanced genomic prediction models. Detailed discussions will focus on analyzing genotype-by-environment (G x E) interactions through relationship matrices and the design of sparse testing. The course will also use real-world examples and interactive exercises to illustrate the practical application of key concepts such as usefulness criterion and optimal contributions in selecting progenitors for crossing and maintaining genetic diversity in breeding programs.

Throughout this course, actual data sets will be employed to showcase these genomic predictions/selections, examine G x E interactions, and perform other pertinent analyses. The course is organized into five distinct modules spread across five days. Each day will feature lectures on critical subjects that blend theoretical knowledge with practical exercises, enabling participants to apply these skills to actual challenges in crop breeding. Assignments will be given for home study and reviewed collectively on the following day.

Course Objectives

This course intends to blend quantitative genetics and statistical genomics with modern breeding approaches and data sets to perform genomic selections and make data-driven breeding decisions in crop breeding. Overall, the course aims to enhance the understanding of quantitative genetics and statistical models used in performing genomic predictions/selections, in breeding programs. Newer approaches to selecting parents and designing the crossing block will be covered using real datasets.

By the end of the training course, the participants should be able to:

• Master the R language to perform the visualizations and analysis.
• Gain the fundamental knowledge and understanding of quantitative genetic and statistical genomics applicable in crop breeding.;
• Understand the concept of genomic selection (3W’s of Genomic selection: Why, When, and Where to apply it in the breeding program);
• Understand the different relationship matrices and their use in genomic predictions;
• Understand the linear and mixed models to perform the genomic predictions/selections;
• Understand and apply the basic and advanced statistical models to perform the genomic predictions;
• Understand the G x E interactions and design sparse testing in dissecting G x E interactions and
• Understand and explore the usefulness criterion and optimal contributions to design the crossing block and predict the performance of cross combinations.

Target Learners

The course is intended for individuals with a basic understanding of crop breeding and genetics. While a basic understanding of statistics and proficiency in using the R language would be advantageous, the course is structured to accommodate participants with diverse levels of knowledge and expertise in crop breeding, statistics, and R programming.

Key Modules:

• Module 1: Introduction and Learning R and R Markdown
• Module 2: Fundamentals of Quantitative Genetics
• Module 3: Statistical Modelling in Predictive Genetics and Breeding
• Module 4: Implementation of Genomic Selection in Plant Breeding
• Module 5: Dissecting G x E Interactions and Crossing Strategies

Learning Modality

The course will be delivered face-to-face with a mixed modality of synchronous and asynchronous discussions involving theoretical concepts, practical and hands-on exercises, and self-paced e-learning activities.

Pre-requisites

The participant highly encourages a basic understanding of breeding and statistics. Experience in using and running R is highly encouraged, but it is optional.