Estimation of Realized Rates of Genetic Gain and Indicators for Breeding Program Assessment

Abstract

R ealized genetic gain is the change in average breeding value of a population over at least one cycle of selection for a particular trait or index of traits. Change in breeding or genetic values of populations over many cycles or years is referred to as genetic trend. When a genetic trend is linear, the rate of genetic gain per year (DG t ) that is realized can be estimated by regressing the average breeding value on year (Eberhart, 1964). Assuming the breeding process remains unchanged and the trait of interest is quantitatively inherited according to the infinitesimal model (Fisher, 1918), this estimate is can be used to predict future genetic gain.Analyses of genetic trends, often accompanied by estimation of realized DG t , have been conducted to analyze the outcomes of breeding programs or selection experiments in model species, livestock, and crops. In experimental populations of nonmodel and model species such as fruit flies (Drosophila melanogaster) and laboratory mice (Mus musculus), selection experiments and assessments of genetic trends have been used to study the genetics of complex traits, selection limits, and to test quantitative genetic models and assumptions (Hill and Caballero, 1992). In livestock, reports of genetic trends are used to assess the effectiveness of breeding programs and to determine if adjustments are needed (Oldenbroek and van der Waaij, 2015). In crop species, estimation of realized DG t is typically done after conducting selection experiments with the objective of comparing different breeding strategies (Hallauer et al., 2010) and, to a lesser extent, to assess the ABSTRACT Routine estimation of the rate of genetic gain (DG t ) realized by a breeding program has been proposed as a means to monitor its effectiveness. Several methods of realized DG t estimation have been used in other studies, but none have been objectively evaluated in a plant breeding context. Stochastic simulations of 80 rice (Oryza sativa L.) breeding programs over 28 yr were done to generate data used to evaluate five methods of realized DG t estimation in terms of error, precision, efficiency, and correlation between true and predicted annual mean breeding values. Two indicators of DG t , the expected DG t , and the average number of equivalent complete generations (EqCg), were described and evaluated. At best, estimates of realized DG t were over or underestimated by 15 and 27% when considering all 28 yr and the past 15 yr of breeding, respectively. The best methods were the estimated breeding value, control population, and era trial methods. Among these, correlations between true and estimated DG t were at best 0.59, indicating that these methods cannot very accurately rank breeding programs in terms of realized DG t . The expected DG t and the average EqCg were shown to be useful indicators for determining if a nonzero genetic gain is expected. Determining which of the three best realized DG t estimation methods evaluated, if any, would be appropriate for any given breeding program should be done with c...

A hybrid optimal contribution approach to drive short-term gains while maintaining long-term sustainability in a modern plant breeding program

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Strategies Using Genomic Selection to Increase Genetic Gain in Breeding Programs for Wheat

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Introducing Beneficial Alleles from Plant Genetic Resources into the Wheat Germplasm

“…Additionally, yields of major crops including wheat, rice, maize and soybean have stagnated or even collapsed due to harsher climatic conditions in some parts of the world [18][19][20]. Positive trends in genetic gain continue to be achieved in individual breeding programs, but at the expense of eroding large parts of genetic diversity [11,[21][22][23]. Will it, therefore, be possible to increase or even maintain the rate of genetic gain in the coming decades, despite the deteriorating climate conditions?…”