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.

Development of 18 Polymorphic Microsatellite Markers for Vinca minor (Apocynaceae) via 454 Pyrosequencing

• Premise of the study: Polymorphic microsatellite markers were developed in Vinca minor (Apocynaceae) to evaluate the level of clonality, population structure, and genetic diversity of the species within its native and introduced range. • Methods and Results: A total of 1371 microsatellites were found in 43,565 reads from 454 pyrosequencing of genomic V. minor DNA. Additional microsatellite loci were mined from publicly available cDNA sequences. After several rounds of screening, 18 primer pairs flanking di-, tri-, or tetranucleotide repeats were identified that revealed high levels of genetic diversity in two native Italian populations, with two to 11 alleles per locus. Clonal growth predominated in two populations from the introduced range in Germany. Five loci successfully cross-amplified in three additional Vinca species. • Conclusions: The novel polymorphic microsatellite markers are promising tools for studying clonality and population genetics of V. minor and for assessing the historical origin of Central European populations.

Microsatellites from Fosterella christophii (Bromeliaceae) by de novo transcriptome sequencing on the Pacific Biosciences RS platform

• Premise of the study: Microsatellite markers were developed in Fosterella christophii (Bromeliaceae) to investigate the genetic diversity and population structure within the F. micrantha group, comprising F. christophii, F. micrantha, and F. villosula. • Methods and Results: Full-length cDNAs were isolated from F. christophii and sequenced on a Pacific Biosciences RS platform. A total of 1590 high-quality consensus isoforms were assembled into 971 unigenes containing 421 perfect microsatellites. Thirty primer sets were designed, of which 13 revealed a high level of polymorphism in three populations of F. christophii, with four to nine alleles per locus. Each of these 13 loci cross-amplified in the closely related species F. micrantha and F. villosula, with one to six and one to 11 alleles per locus, respectively. • Conclusions: The new markers are promising tools to study the population genetics of F. christophii and to discover species boundaries within the F. micrantha group.