Optimal Contribution Selection

Modern breeding schemes, utilizing both advanced reproductive, statistical and molecular genetics methods and technologies, harvest high genetic progress, but also high rates of inbreeding. This has increased the need for tools to monitor and control rates of inbreeding in a population, such as optimal genetic contribution selection (OCS). EVA is a software package aimed at describing inbreeding in a population and predicting genetic contributions of breeding candidates while maximizing response to selection given a penalty on/constraining the rate of inbreeding.

EVA perfoms two tasks:

1. Describes the history of populations in terms of

  • Individual inbreeding coefficients and completeness of the pedigree
  • Average inbreeding, coancestry, pedigree completeness and generation equivalents per cohort
  • Genetic contributions of:
    • All founders
    • Most contributing ancestors
    • Any user-specified individuals to any individual or cohort

2. Optimizes genetic contributions

  • Optimizes the linear function of genetic merit and average additive genetic relationships
  • Conditional on optimal contributions, individuals may be mated randomly or while minimizing inbreeding in the offspring

By optimal balancing of inbreeding and genetic gain, EVA provides means for sustainable long-term breeding decisions regardless of population size or structure. EVA has been successfully applied and tested in both commercial and endangered populations in the Nordic and Baltic countries.

To use EVA you will need accurate and consistent pedigree information. An ordinary desktop computer has in most cases enough capacity to run EVA, with exception of very large population sizes.

NordGen regularly arranges workshops on OCS. The next workshop will be arranged in Oslo,Norway. Lectures and exercises from the workshop are available on the workshop website.

EVA is freely available for Windows , Linux and Mac . If you are a new user of EVA, please send an email to the Farm Animal section to register.

How to cite EVA software in scientific papers?

Berg P., Nielsen J. and Sørensen M.K. 2006. EVA: Realized and predicted optimal genetic contributions. CD communication 27-09, 2pp. WCGALP, 2006, s.246.