ComputeBio logo ComputeBio

Professional development · 40 academic hours

Introduction to Genomic Selection

The Introduction to Genomic Selection course provides a systematic understanding of the fundamental principles behind modern genomic selection. The course is designed for participants with introductory knowledge of genetics and biology and assumes basic knowledge of mathematical statistics and programming. A key factor in the effectiveness of genomic selection is the accuracy of predicting an animal’s future breeding value. Participants will learn how to make these predictions using phenotypic and genotypic data, assess their accuracy, and select suitable prediction models for practical breeding tasks.

Explore the curriculum

About the course

From genotyping and sequencing to practical breeding value estimation

The course combines molecular genetics, bioinformatics, statistical models and hands-on experience with breeding software.

Introduction to Genomic Selection is a foundational course on how modern DNA analysis methods help identify the genetic characteristics of plants and animals.

Participants will learn how the genome is organised, why mutations affect productivity and health, and which mathematical tools are used to identify genetic variants associated with specific traits.

The course covers the workflow from genotyping and sequencing to estimating breeding values using specialised software. Through practical examples and simulations, participants will learn to analyse the relationship between genetic factors and productivity and apply these skills in real breeding programmes.

Course modules

Course structure

Three modules: genome structure, trait inheritance and breeding value estimation with BLUPF90.

Module 1

Understanding the genome in genomic selection

  • Genomic variation and SNPs
  • Haplotype blocks & inheretance
  • Imputation of untyped SNPs
  • Genome sequencing
  • Genes
  • Genetic arhitecture of traits
Module 2

Trait inheritance

  • Topic 2.1. Meiosis
  • Topic 2.2. Effects of SNPs on a trait
  • Topic 2.3. GWAS
  • Topic 2.4. Population stratification
  • Topic 2.6. Genetic covarinace between traits
  • Topic 2.7. BV & EBV
  • Topic 2.8. Introduction to R programming
Module 3

Breeding value estimation

  • Topic 3.1. Simulating a trait with a specified genetic architecture
  • Topic 3.2. Identifying new mutations associated with a trait
  • Topic 3.3. Practical aspects of breeding value estimation

What you will learn

Practical learning outcomes

Understand and apply the basic principles of genomic selection

Assess how genetic variants affect animal productivity

Use mathematical models and R programming to identify genetic variants

Estimate breeding values

Use sequencing and genotyping methods to analyse the genome

Course expert

Course expert

Maksim Struchalin

PhD, CEO of ComputeBio

Course expert with a PhD from Erasmus MC, the Netherlands, and experience working with animal genomes at Livestock Improvement Corporation, New Zealand. His projects include developing prediction models for Miratorg Genetics and SoyuzSemSvekla, designing a low-density SNP array for RusAgro, and developing genomic selection software for the Bashkir Meat Company. He specialises in genomics, bioinformatics and genomic selection.

Who the course is for

Who will benefit

01

Bioinformaticians looking to apply their expertise in agriculture.

02

Livestock breeders seeking to use the latest approaches to improve the genetic merit of their breeding populations.

03

Breeding programme managers interested in improving their organisation’s competitiveness through genomic technologies.

Training options

Course fees and training options

In-person training

1,500 USD
  • Duration: 40 academic hours
  • In-person or remotely

In-person training for a team of up to 5

6,500 USD
  • Duration: 40 academic hours
  • In-person or remotely
  • Practical examples and simulations
  • Focus on applying skills in breeding programmes

Contact

Have questions?

Get in touch with us.

Office 13, 12 Nikolayeva Street, Akademgorodok, Novosibirsk, Russia