Researchers at Wageningen University & Research Animal Breeding & Genomics (WUR-ABG) recently implemented an efficient algorithm, called the deflated preconditioned conjugate gradient method.

In collaboration with the Technical University of Delft, the WUR-ABG researchers said the algorithm, new in animal breeding, aims to allow large routine, single-step genomic evaluations to predict genomic breeding values more accurately.

The first tests of this new algorithm were performed on large data sets provided by the Breed4Food partner CRV BV, and their results showed promising efficiency, WUR-ABG said in an announcement.

Breed4Food is a consortium established by WUR and four international animal breeding companies: CRV BV, Hendrix Genetics, Topigs Norsvin and Cobb Europe.

According to WUR-ABG, these four companies use, or will soon use, the so-called single-step genomic methods to routinely estimate genomic breeding values of their livestock selection candidates.

The single-step methods are appealing due to their simplicity of simultaneously combining traditionally recorded data with recently recorded genomic information, WUR-ABG said. Unfortunately, the fast increase of genomic information limits the feasibility of routine single-step genomic evaluations with software and algorithms currently used.

A new algorithm in animal breeding

Within Breed4Food, and in collaboration with professor Kees Vuik of the Technical University of Delft, researchers at WUR-ABG have integrated the deflated preconditioned conjugate gradient method into their software (under development).

Results of the first tests of the new algorithm showed promising efficiency, WUR-ABG said. Furthermore, it has been shown that this new algorithm could be easily implemented in software currently used in animal breeding.

More information on the algorithm was published in Genetics Selection Evolution.

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