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Better breeding values

Breeding values give a prediction of the genetic merit of an individual animal and are commonly generated for economic, environmental or welfare related traits. One way to improve the accuracy of breeding values earlier in the animal’s life than what would otherwise be available is via genomic prediction. Calculating genomic breeding values in this way increases the rate of genetic gain in the target population, and has the potential to help make valuable genetic improvements across New Zealand’s biological industries.

Genomic selection can be employed using a range of genotyping methods, and the volume of data available is increasing dramatically. But genomic prediction can be daunting, particularly for some species other than sheep and cattle in New Zealand, because there is a lack of cohesive and straight-forward statistical and bioinformatics techniques and resources available.

Dairy cattle

Photo: Dairy cattle by Dave Young

There is a need for better approaches to deal with the sheer amount of data and to better use the data we already have. New technologies are also needed to ensure our biological industries benefit from the increased accuracy and are competitive internationally.

Working with industry leaders, this project has worked on new statistical approaches, developed new data sources and produced tools for, and related to, breeding value prediction. A focus has been on imputation, particularly to whole genome sequence.

The approaches are being made accessible across all primary industries, so that they can cost-effectively adopt genomic selection to suit their own circumstances. They may also be relevant to conservation, where genomic management of endangered species will require similar support. 

This project brought together researchers from the plant, sheep, beef and dairy industries via two Crown Research Institutes, two universities, Livestock Improvement Corporation (LIC), AbacusBio Limited and industry, as well as crucial skills and capabilities to complement other Genomics Aotearoa projects. Two postdocs, managed across institutions, were employed to build capability.

Outcomes

An imputation workshop run by the group in September 2020 shared project findings on:

  • Novel approaches to imputation of large datasets to whole genome sequence
  • Identification of highly informative sequence variants from genome-wide association studies
  • New approaches to breeding value prediction using sequence variants

For more information: https://github.com/GenomicsAotearoa/Imputation-workshop

Effective co-operation has been established between GA partners and industry stakeholders. Industry partners will now be investigating how to implement findings on their respective species to improve farming of New Zealand cattle and sheep.

See our new project, High quality genomes and population genomics

Team

  • Professor Dorian Garrick (Massey University) – co-lead researcher
  • Dr Michael Lee (University of Otago) – co-lead researcher
  • Dr Phil Wilcox (University of Otago)
  • Dr Shannon Clarke (AgResearch)
  • Dr Rudiger Brauning (AgResearch)
  • Dr David Chagne (Plant & Food)
  • Dr Christine Couldrey (LIC)
  • Dr Neville Jopson (AbacusBio)
  • Andrew Hess (AgResearch)
  • Yu Wang (Massey University and Livestock Improvement Corporation)
  • Brittany Jones (University of Otago)
  • Joshua Rich (University of Otago/AgResearch)

Presentations

A Hess et al., Considerations for designing imputation studies using whole genome sequence data: A study in a diverse New Zealand sheep population, Plant and Animal Genome XXVIII conference, San Diego, USA, January 2020.