Enhancing the rate of genetic gain in public-sector plant breeding programs: lessons from the breeder's equation

Theor Appl Genet. 2019 Mar;132(3):627-645. doi: 10.1007/s00122-019-03317-0. Epub 2019 Mar 1.

Abstract

The integration of new technologies into public plant breeding programs can make a powerful step change in agricultural productivity when aligned with principles of quantitative and Mendelian genetics. The breeder's equation is the foundational application of quantitative genetics to crop improvement. Guided by the variables that describe response to selection, emerging breeding technologies can make a powerful step change in the effectiveness of public breeding programs. The most promising innovations for increasing the rate of genetic gain without greatly increasing program size appear to be related to reducing breeding cycle time, which is likely to require the implementation of parent selection on non-inbred progeny, rapid generation advance, and genomic selection. These are complex processes and will require breeding organizations to adopt a culture of continuous optimization and improvement. To enable this, research managers will need to consider and proactively manage the, accountability, strategy, and resource allocations of breeding teams. This must be combined with thoughtful management of elite genetic variation and a clear separation between the parental selection process and product development and advancement process. With an abundance of new technologies available, breeding teams need to evaluate carefully the impact of any new technology on selection intensity, selection accuracy, and breeding cycle length relative to its cost of deployment. Finally breeding data management systems need to be well designed to support selection decisions and novel approaches to accelerate breeding cycles need to be routinely evaluated and deployed.

Publication types

  • Review

MeSH terms

  • Genetic Markers
  • Inheritance Patterns / genetics
  • Plant Breeding / methods*
  • Plants / genetics*
  • Polymorphism, Single Nucleotide / genetics
  • Public Sector*
  • Selection, Genetic

Substances

  • Genetic Markers