Abstract
Increasing the rate of genetic gain for dry matter (DM) yield in perennial ryegrass (Lolium perenne L.), which is a key source of nutrition for ruminants in temperate environments, is an important goal for breeders. Genomic selection (GS) is a strategy used to improve genetic gain by using molecular marker information to predict breeding values in selection candidates. An empirical assessment of GS for herbage accumulation (HA; proxy for DM yield) and days-to-heading (DTH) was completed by using existing genomic prediction models to conduct one cycle of divergent GS in four selection populations (Pop I G1 and G3; Pop III G1 and G3), for each trait. G1 populations were the offspring of the training set and G3 populations were two generations further on from that. The HA of the High GEBV selection group (SG) progenies, averaged across all four populations, was 28% higher (p < 0.05) than Low GEBV SGs when assessed in the target environment, while it did not differ significantly in a second environment. Divergence was greater in Pop I (43%–65%) than Pop III (10%–16%) and the selection response was higher in G1 than in G3. Divergent GS for DTH also produced significant (p < 0.05) differences between High and Low GEBV SGs in G1 populations (+6.3 to 9.1 days; 31%–61%) and smaller, non-significant (p > 0.05) responses in G3. This study shows that genomic prediction models, trained from a small, composite reference set, can be used to improve traits with contrasting genetic architectures in perennial ryegrass. The results highlight the importance of target environment selection for training models, as well as the influence of relatedness between the training set and selection populations.
Highlights
Pastures based on perennial ryegrass (Lolium perenne L.) are the principal source of nutrition for ruminant livestock in temperate environments across the globe
The purpose of this study was to determine if the application of divergent genomic selection using genomic prediction models trained for herbage accumulation (HA; [20], a proxy for dry matter (DM) yield potential), would elicit a selection response from breeding populations with differing levels of relatedness to the original training set
Selection populations showed close genetic alignment to their training set progenitors (Figure 1), but the G3 populations were more distal than the G1 populations, most noticeably for Pop III. This was reflected in the mean relatedness coefficients estimated for selection populations and their training set counterparts (Table 1), with relatedness to the training set generation declining by 7% from training to G1 and by 26% from training to G3, in both Pop I and Pop III
Summary
Pastures based on perennial ryegrass (Lolium perenne L.) are the principal source of nutrition for ruminant livestock in temperate environments across the globe. Estimates of the rate of genetic gain for annual DM yield in perennial ryegrass vary by location [7], but European and Australasian studies have placed the rate at between 0.2% and 0.6% per annum under grazing [7,8,9,10]. This is low, when contrasted against gains of up to 1.6% per annum realized for grain yield in major cereal crops [11]. The relatively slow rate of genetic progress for DM yield in forages has been ascribed to long breeding cycles, the inability to fully-exploit either heterosis or a harvest index, and the necessity for breeders to concurrently improve a range of other economic traits [12]
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