2026 Summer Institute in Plant Breeding

Summer Institute in Plant Breeding (in person)

1 - 5 June 2026

Saint Paul, Minnesota, USA

Offered by the

Plant Breeding Center at the University of Minnesota

Modules

Participants can register for one module in Set 1 (Monday to Wednesday noon) and one module in Set 2 (Wednesday afternoon to Friday afternoon):

SET 1

• Plant Breeding 101 (James A. Anderson)
• Mixed-Model Analysis in Plant Breeding (Lucia Gutierrez)
• AlphaSimR for Plant Breeding Simulation (Chris Gaynor)

SET 2

• Biotechnology in Crop Improvement (Robert M. Stupar)
• Applied Plant Genomics and Bioinformatics (Candice N. Hirsch)
• Data Bootcamp for Genomic Prediction in Plant Breeding (Aaron J. Lorenz)

Target Audience

Plant Breeding 101 is intended for those who seek a course in the fundamentals of plant breeding (technicians, data scientists, managers, non-plant breeding graduate students, etc.).

The five other modules are intended for M.S. and Ph.D. students, postdocs, and industry scientists.

Costs

US $490 for graduate students, postdocs, and faculty

US $650 for industry participants

Cost includes lunch and morning and afternoon breaks. Breakfast, dinner, and accommodations are not included. We regret that scholarships or reduced fees are unavailable.

Questions?

Contact Rex Bernardo by email ([email protected])

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Module descriptions

Plant Breeding 101. This course is for those who seek to learn the fundamentals of plant breeding (e.g., technicians, data scientists, managers, non-plant breeding graduate students, etc.). Each session will include lecture/discussion, demonstrations, and problem-solving with sample data.

Session 1: Genetic variation, qualitative and quantitative inheritance, heritability

Session 2: Phenotyping, experimental design, genotype x environment interaction, data analysis and summary

Session 3: Modes of reproduction, types of cultivars, parent selection, breeding methodologies

Session 4: Genetic mapping, breeding using major genes/markers, genomic prediction

Session 5: Polyploidy, breeding for pest resistance, breeding asexually propagated species, intellectual property protection

Mixed-Model Analysis in Plant Breeding. This course provides an introduction to mixed-model analysis will cover the following topics: matrices and matrix manipulations; linear models; mixed effects models and their development; covariance structures; mixed-model equations; shrinkage; properties of estimates and predictions; analysis software; and applications in experimental designs and in plant breeding. The course will involve lectures, problem sets, and hands-on data analysis activities.

AlphaSimR for Plant Breeding Simulation. This course teaches how to use AlphaSimR to simulate plant breeding programs. It is intended for students with a basic knowledge of both plant breeding and the R programming language. This course will include lectures, demonstrations, and hands-on activities.

Session 1: Introduction to AlphaSimR and stochastic simulations

Session 2: Using AlphaSimR to simulate simple populations

Session 3: Simulating a burn-in and baseline breeding program

Session 4: Simulating alternative breeding programs and plotting results

Session 5: Introduction to advanced simulation topics

Biotechnology in Crop Improvement. This course will cover the history, practice, and modern advances in crop biotechnology. The course structure will include lectures, discussions, tours, and hands-on activities. (Prerequisite: an undergraduate genetics course)

Session 1: History of plant biotechnology, including mutation breeding, transgenesis, and gene editing. Development of technologies; original applications and products. Tour/lab experience on Agrobacterium-based transformation and tissue culture.

Session 2: Methods of gene discovery and gene target selection. Genetic mapping, candidate gene identification, gene cloning.

Session 3: Modern applications of transgenes, RNAi, gene editing, and gene regulation. Construct components and development. Tour/ lab experience on transgenic plant developmental stages.

Session 4: New methods of transgene and/or editing reagent delivery to the plant. Overcoming genotype-dependency -- developmental regulators, viral delivery.

Session 5: The biotech x genome interaction and implications for regulation. Tour/field experience on mutant populations and gene-edited materials.

Applied Plant Genomics and Bioinformatics. Principles, applications, and limitations regarding the development and use of genomics resources in plants. This course will include lectures, discussions, and hands-on activities. (Prerequisite: an undergraduate genetics course)

Session 1: Review components of the plant genome, current sequencing technologies, and hands-on activity to access existing sequence data and assess the quality of sequence data

Session 2: Methods and limitations for genome assembly, gene structural annotation, gene functional annotation, transposable element annotation, and hands-on resource allocation exercises

Session 3: Genomic variation (types of variation, methods to measure variation, limitations in measurements), principles of pan-genomics and applications to crop improvement

Session 4: Transcriptomics for estimating transcript abundance and transcriptome assembly, hands-on activity in differential expression

Session 5: Principles of visualization for large-scale genomics data, hands-on activity to generate visualizations from large-scale genomics data

Data Bootcamp for Genomic Prediction in Plant Breeding. This introductory-level course will cover common data structures, analysis techniques, and tools used for genomic selection in plant breeding. This course will include lectures and hands-on activities. Course content is designed for those new to data analysis for genomic prediction (Prerequisite: basic knowledge of programming in R).

Sessions 1-2: Formatting and quality control of genotype/phenotype data for genomic prediction, model implementation and exploration of various types of models, techniques in cross validation for assessing prediction accuracy

Sessions 3-4: Training population optimization, multi-trait prediction, genomic prediction for genotype x environment interaction, prediction of mean and variance of new breeding populations

Session 5: Other special topics in genomic prediction, tour of available tools for implementing genomic prediction

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Host or Publisher Rex Bernardo