Enlarging a training set for genomic selction by imputation of un-genotyped animals in populations of varying genetic architecture

Background: The most common application of imputation is to infer genotypes of a high-density panel of markers on animals that are genotyped for a low-density panel. However, the increase in accuracy of genomic predictions resulting from an increase in the number of markers tends to reach a plateau beyond a certain density. Another application of imputation is to increase the size of the training set with un-genotyped animals. This strategy can be particularly successful when a set of closely related individuals are genotyped. ----- Methods: Imputation on completely un-genotyped dams was performed using known genotypes from the sire of each dam, one offspring and the offspring’s sire. Two methods were applied based on either allele or haplotype frequencies to infer genotypes at ambiguous loci. Results of these methods and of two available software packages were compared. Quality of imputation under different population structures was assessed. The impact of using imputed dams to enlarge training sets on the accuracy of genomic predictions was evaluated for different populations, heritabilities and sizes of training sets. ----- Results: Imputation accuracy ranged from 0.52 to 0.93 depending on the population structure and the method used. The method that used allele frequencies performed better than the method based on haplotype frequencies. Accuracy of imputation was higher for populations with higher levels of linkage disequilibrium and with larger proportions of markers with more extreme allele frequencies. Inclusion of imputed dams in the training set increased the accuracy of genomic predictions. Gains in accuracy ranged from close to zero to 37.14%, depending on the simulated scenario. Generally, the larger the accuracy already obtained with the genotyped training set, the lower the increase in accuracy achieved by adding imputed dams. ----- Conclusions: Whenever a reference population resembling the family configuration considered here is available, imputation can be used to achieve an extra increase in accuracy of genomic predictions by enlarging the training set with completely un-genotyped dams. This strategy was shown to be particularly useful for populations with lower levels of linkage disequilibrium, for genomic selection on traits with low heritability, and for species or breeds for which the size of the reference population is limited.

Pathogens occuring in the winter pea-maize-winter wheat rotation, their host specificity and the potential of compost in suppressing foot and root disease of peas

The overall aim of the work presented was to evaluate soil health management with a specific focus on soil borne diseases of peas. For that purpose field experiments were carried out from 2009 until 2013 to assess crop performance and pathogen occurrence in the rotation winter pea-maize-winter wheat and if the application of composts can improve system performance. The winter peas were left untreated or inoculated with Phoma medicaginis, in the presence or absence of yard waste compost at rate of 5 t dry matter ha-1. A second application of compost was made to the winter wheat. Fusarium ssp. were isolated and identified from the roots of all three crops and the Ascochyta complex pathogens on peas. Bioassays were conducted under controlled conditions to assess susceptibility of two peas to Fusarium avenaceum, F. solani, P. medicaginis and Didymella pinodes and of nine plant species to F. avenaceum. Also, effects of compost applications and temperature on pea diseases were assessed. Application of composts overall stabilized crop performance but it did not lead to significant yield increases nor did it affect pathogen composition and occurrence. Phoma medicaginis was dominating the pathogen complex on peas. F. graminearum, F. culmorum, F. proliferatum, Microdochium nivale, F. crookwellense, F. sambucinum, F. oxysporum, F. avenaceum and F. equiseti were frequently isolated species from maize and winter wheat with no obvious influence of the pre-crop on the Fusarium species composition. The spring pea Santana was considerably more susceptible to the pathogens tested than the winter pea EFB33 in both sterile sand and non-sterilized field soil. F. avenaceum was the most aggressive pathogen, followed by P. medicaginis, D. pinodes, and F. solani. Aggressiveness of all pathogens was greatly reduced in non-sterile field soil. F. avenaceum caused severe symptoms on roots of all nine plant species tested. Especially susceptible were Trifolium repens, T. subterraneum, Brassica juncea and Sinapis alba in addition to peas. Reduction of growing temperatures from 19/16°C day/night to 16/12°C and 13/10°C did not affect the efficacy of compost. It reduced plant growth and slightly increased disease on EFB33 whereas the highest disease severity on Santana was observed at the highest temperature, 19/16°C. Application of 20% v/v of compost reduced disease on peas due to all four pathogens depending on pea variety, pathogen and growing media used. Suppression was also achieved with lower application rate of 3.5% v/v. Tests with γ sterilized compost suggest that the suppression of disease caused by Fusarium spp. is biological in origin, whereas chemical and physical properties of compost are playing an additional role in the suppression of disease caused by D. pinodes and P. medicaginis.