Implementation of Genomic Prediction in Lolium perenne (L.) Breeding Populations.

Perennial ryegrass (Lolium perenne L.) is one of the most widely grown forage grasses in temperate agriculture. In order to maintain and increase its usage as forage in livestock agriculture, there is a continued need for improvement in biomass yield, quality, disease resistance, and seed yield. Genetic gain for traits such as biomass yield has been relatively modest. This has been attributed to its long breeding cycle, and the necessity to use population based breeding methods. Thanks to recent advances in genotyping techniques there is increasing interest in genomic selection from which genomically estimated breeding values are derived. In this paper we compare the classical RRBLUP model with state-of-the-art machine learning techniques that should yield themselves easily to use in GS and demonstrate their application to predicting quantitative traits in a breeding population of L. perenne. Prediction accuracies varied from 0 to 0.59 depending on trait, prediction model and composition of the training population. The BLUP model produced the highest prediction accuracies for most traits and training populations. Forage quality traits had the highest accuracies compared to yield related traits. There appeared to be no clear pattern to the effect of the training population composition on the prediction accuracies. The heritability of the forage quality traits was generally higher than for the yield related traits, and could partly explain the difference in accuracy. Some population structure was evident in the breeding populations, and probably contributed to the varying effects of training population on the predictions. The average linkage disequilibrium between adjacent markers ranged from 0.121 to 0.215. Higher marker density and larger training population closely related with the test population are likely to improve the prediction accuracy.

Temporal changes in population genetic diversity and structure in red and white clover grown in three contrasting environments in northern Europe.

UNLABELLED: BACKGOUND AND AIMS: Extending the cultivation of forage legume species into regions where they are close to the margin of their natural distribution requires knowledge of population responses to environmental stresses. This study was conducted at three north European sites (Iceland, Sweden and the UK) using AFLP markers to analyse changes in genetic structure over time in two population types of red and white clover (Trifolium pratense and T. repens, respectively): (1) standard commercial varieties; (2) wide genetic base (WGB) composite populations constructed from many commercial varieties plus unselected material obtained from germplasm collections. METHODS: At each site populations were grown in field plots, then randomly sampled after 3-5 years to obtain survivor populations. AFLP markers were used to calculate genetic differentiation within and between original and survivor populations. KEY RESULTS: No consistent changes in average genetic diversity were observed between original and survivor populations. In both species the original varieties were always genetically distinct from each other. Significant genetic shift was observed in the white clover 'Ramona' grown in Sweden. The WGB original populations were more genetically similar. However, genetic differentiation occurred between original and survivor WGB germplasm in both species, particularly in Sweden. Regression of climatic data with genetic differentiation showed that low autumn temperature was the best predictor. Within the set of cold sites the highest level of genetic shift in populations was observed in Sweden. CONCLUSIONS: The results suggest that changes in population structure can occur within a short time span in forage legumes, resulting in the rapid formation of distinct survivor populations in environmentally challenging sites.

Dynamics of initial colonization of nonconserved perennial ryegrass by anaerobic fungi in the bovine rumen.

Anaerobic fungi (Neocallimastigales) are active degraders of fibrous plant material in the rumen. However, only limited information is available relating to how quickly they colonize ingested feed particles. The aim of this study was to determine the dynamics of initial colonization of forage by anaerobic fungi in the rumen and the impact of different postsampling wash procedures used to remove loosely associated microorganisms. Neocallimastigales-specific molecular techniques were optimized to ensure maximal coverage before application to assess the population size (quantitative PCR) and composition (automated ribosomal intergenic spacer analysis) of the colonizing anaerobic fungi. Colonization of perennial ryegrass (PRG) was evident within 5 min, with no consistent effect of time or wash procedure on fungal population composition. Wash procedure had no effect on population size unlike time, which had a significant effect. Colonizing fungal population size continued to increase over the incubation period after an initial lag of c. 4 min. This dynamic differs from that reported previously for rumen bacteria, where substantial colonization of PRG occurred within 5 min. The observed delay in colonization of plant material by anaerobic fungi is suggested to be primarily mediated by the time taken for fungal zoospores to locate, attach and encyst on plant material.