November 12th, 2020

The continuous adoption of genomic prediction

The use of GP for early recycling reduces cohorts

1. Introduction to the problem

Crop by region


Problem specification

Reducing cycle time to increase rates of gain is not being fully exploited in classical programs neither the use of genomic prediction to boost even more the reduction of cycle time. Playing factors are not fully understood.

Breeding strategy component tackled

Crossing, Evaluation, Selection

Breeders’ equation terms tackled


\(\Delta_g = (i * \sigma_g * r)/L\)


Using genomic prediction in the recycling (selection) process to reduce the cycle time could increase the rate of genetic gain.

2.1 Materials and methods (reduced cycle time)


Treatment Description
TPn_PPn_SPf4f5 TrainingPop=NULL,PredictedPop=NULL,RecyclingPop=F4-F5 using an index.
TPn_PPn_SPf5f6 TrainingPop=NULL,PredictedPop=NULL,RecyclingPop=F5-F6 using an index.
TPn_PPn_SPf6f7 TrainingPop=NULL,PredictedPop=NULL,RecyclingPop=F6-F7 using an index.
TPn_PPn_SPf7f8 TrainingPop=NULL,PredictedPop=NULL,RecyclingPop=F7-F8 using an index.
TPn_PPn_SPf7f8_NF TrainingPop=NULL,PredictedPop=NULL,RecyclingPop=F7-F8 using an index with no family selection.
TPf5f6_PPf1_SPf1 TrainingPop=F5-F6, PredictedPop=F1, RecyclingPop=F1 using an index.

Simulation procedure

A 20 year burn-in period was used. Burn-in was followed by a 20 year evaluation period to measure rates of genetic gain in F9 lines. Genotype-by-year, genotype-by-location interaction variances were assumed to be equivalent to main genetic variance. 25 replications done. We simulated 5 complex and 3 simple traits to be behind the genetic merit. TP=random, N.TP=3K, N.Markers=5K.

2.2 Results for cycle time reduction

  • Reducing cycle time to F5-F6 will provide 1.31 (95% CI: 1.03,1.66) times more gain at year 10 and 1.26 (95% CI: 1.12,1.42) at year 20.
  • Reducing cycle time to F1 will provide 2.05 (95% CI: 1.45,2.9) times more gain at year 10 and 1.2 (95% CI: 1.03,1.4) at year 20.

2.2 Results for cycle time