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Genomic selection is a promising breeding methodology that could increase selection accuracy and intensity and reduce generation interval. As the cost of genotyping decreases, it will be important to optimize training populations for costly phenotypic experiments for many complex traits. The aim of this research was to evaluate different optimization strategies, by using historical data from the Norwegian oat breeding programme at Graminor. In this paper, we focus on the optimization criteria: genetic diversity, phenotypic variance and genetic similarity between the training and testing populations. The four training population strategies—prediction core, diversity core, phenotypic selection and random selection—were applied to an oat candidate population of 1124 lines. An independent testing population was used to calculate the mean prediction abilities for the traits days to heading and plant height. Moreover, the strategies were tested in three independent wheat populations. The results showed that prediction core was the most promising strategy to select training populations with high genetic similarity to the testing set, high genetic diversity, and high phenotypic variance, which resulted in higher prediction ability across population sizes and traits. [ABSTRACT FROM AUTHOR]

The concept of essential derivation refers to cases where a new variety is obtained from an initial variety ( IV), of which it retains the expression of the essential characteristics resulting from the genotype or combination of genotypes of the IV. Protecting plant breeder's rights can be facilitated by identifying a species-specific threshold level of similarity above which the new variety could be suspected as essentially derived ( EDV). Amplified fragment length polymorphisms and simple sequence repeats proved suitable for measuring genetic similarity. Three approaches have been proposed for the definition of thresholds. According to the 'calibration principle', the critical level to discriminate EDVs is defined based on similarities among closely related genotypes. Adopting the 'tail principle', the threshold is placed at a given percentile of the distribution of the similarities within a reference population of independent genotypes. Finally, with the 'pedigree principle', the threshold is set starting from the a priori definition of breeding techniques that lead to EDVs. The tools and the approaches described in this review represent the basis for developing protocols useful in handling disputes of essential derivation. [ABSTRACT FROM AUTHOR]

Levels of genetic similarity characterizing 20 grasspea ( Lathyrus sativus L.) populations collected in central Italy (17 populations in the Marche region and three populations in the Abruzzo region) were analysed with amplified fragment length polymorphism (AFLP) molecular markers. Two main clusters were found: one included large-seeded populations from farms that were not market-oriented (named Household populations) and the second, small-seeded populations, cultivated in market-oriented farms (named Commercial populations). Relationships among populations collected in different regions were found, although one population of the Abruzzo region was placed between the two main clusters, suggesting a possible further genetic differentiation within this grasspea germplasm collection. Principal component analysis based on AFLP marker frequency was effective in identifying polymorphic markers showing high discriminating ability between clusters H and C. In particular, seven markers showing high positive and three markers with low negative PC1 scores showed an almost cluster-specific distribution. These results will be useful for enhancing Italian grasspea germplasm use in plant-breeding programmes and for extending grasspea cultivation within the sustainable agricultural systems of central Italy. [ABSTRACT FROM AUTHOR]

Fifteen amplified fragment length polymorphism (AFLP)EcoRI/MseI-based primer combinations with five selective bases (EcoRI-ANN,MseI-CN) were used to estimate genetic diversity among 45 line varieties of cultivated cornsalad and 19 genebank accessions classified into nine different species related to cornsalad. Polymorphic fragments were scored for calculation of Jaccard's coefficient of genetic similarity (GS). The average GS estimate in elite germplasm (GS = 0.90) was substantially higher than in exotic germplasm (GS = 0.47). UPGMA-cluster analysis revealed genetic relationships among recently bred varieties, old varieties and genebank accessions. Analysis of molecular variance indicated almost threefold variability within sets compared with between sets due to a high level of polymorphism among wild species. Sources for increasing genetic diversity in elite germplasm of cornsalad were suggested and a duplicate among the genebank accessions was detected. AFLPs could be considered a powerful tool for genetic diversity estimation in cornsalad germplasm and are recommended for systematic fingerprinting of remaining cornsalad species. [ABSTRACT FROM AUTHOR]

Two molecular marker approaches [amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR)] were employed to study genomic relationship among 96 rice cultivars. These included most of the best reputed Italian accessions. AFLP produced 461 fragments, 248 (53%) of which were polymorphic, SSR produced four to 11 alleles in the 12 genomic loci investigated. Genomic similarity was estimated independently for the two molecular marker techniques. Both AFLP and SSR dendrograms agree in splitting the cultivars into two main clusters: a small one, comprising four exotic accessions, and a larger one which could be split into four sub-groups. These were also analysed on the basis of historical and pedigree information. This is the first report on the application of DNA polymorphism analysis to reveal genomic relationship among cultivated Italian rice germplasm. Results will be useful for breeding programmes. [ABSTRACT FROM AUTHOR]

Abstract In order to obtain an overview of the genetic diversity present within the set of pea cultivars released in Germany, 21 cultivars were analysed at the DNA level by random amplified polymorphic DNAs (RAPDs) and amplified fragment length polymorphisms (AFLPs), as well as for agronomic traits. Yield of grain cultivars ranged from 2.95 to 3.87 t/ha. Based on the screening of 60 RAPD primers and 32 Eco RI+3/Mse I+3 AFLP primer combinations, 20 RAPD primers and 11 Eco RI+3/Mse I+3 primer combinations generating polymorphic and distinct fragments were chosen for estimation of genetic diversity. Twenty RAPD primers amplified a total of 314 scorable bands ranging from about 262 bp to 1996 bp. Of these, 175 fragments (55.7%) were polymorphic. Based on these data, genetic similarity (GS) was estimated between 0.80 (‘Lisa’ vs. ‘Grapis’) and 0.94 (‘Bohatyr’ vs. ‘Sponsor’; mean GS = 0.88). Eleven AFLP primer combinations led to the amplification of 949 scorable fragments ranging from 43 to 805 bp and of these, 462 (48.7%) were polymorphic. Genetic similarity based on AFLPs was calculated between 0.85 (‘Lisa’ vs. ‘Laser’) and 0.94 (‘Bohatyr’ vs. ‘Sponsor’, mean GS = 0.90). Correlation of genetic similarity estimated on RAPDs and AFLPs was estimated at r = 0.79** using Spearman's rank correlation coefficient and at r = 0.84 by the Mantel test, respectively. UPGMA cluster analysis carried out on these data separately for RAPDs and AFLPs and on the combined data reflected, to some extent, pedigree relationships and cophenetic correlations (r = 0.89 for RAPDs, r = 0.88 for AFLPs, and r = 0.93 RAPDs + AFLPs) indicate a good fit of respective clusters to genetic similarity data. The correlation of cluster analyses to pedigree information and the impact on parental genotype selection is discussed. [ABSTRACT FROM AUTHOR]

Eight genotypes of the main Fragaria × ananassa cultivars grown in Argentina were analysed using the random amplified polymorphic DNA (RAPD) technique combined with electrophoresis in polyacrylamide gels. The high resolution of this procedure allowed the detection, with only 13 random primers, of 37 genotype-specific bands that can be used as markers for verifying the identity of cultivars. By using this approach, three different accessions of the cultivar `Pájaro' exhibited differences in amplification profiles, confirming the need for DNA analysis to prevent misidentification of cultivars. In addition, RAPD bands and morphological traits were used to assess genetic relatedness among cultivars. Comparison of both dendrograms revealed that there is no correlation between the clustering obtained with molecular and morphological characters. [ABSTRACT FROM AUTHOR]

Twenty recombinant inbred line (RIL) populations of European tworow spring barley and their parents were tested in six environments in the Netherlands to investigate the prediction of progeny yield level, yield variance, stability levei and stability variance, based on parent information. Progeny yield levei is positively correlated with midparent value for average yield. Progeny yield variance is more dificult to predict, but there does appear to be a promising negative correlation between progeny yield variance and Habgood's (1977) parental similarity measure. To quantify yield stability, three statistics were calculated: Finlay and Wilkinson's (1963) regression coefficient b[sub i], Shukla's (1972) stability variance σ²[sub i] and Eberhart and Russell's (1966) mean squared deviation d²[sub i]. The rst stability statistic describes a different aspect of the response pattern to change in environment from the last two. Parents with high b[sub i] values appear to have a better average yield, i.e. they react more positively to an improvement in the environment than the other genotypes. The average b[sub i] value of the progeny is positively correlated with the midparent value, indicating its heritable nature. There are also indications that d²[sub i] and σ²[sub i] are heritable but their repeatability is poor. Therefore, it is concluded that only prediction of b[sub i] is useful in practical plant breeding. There is a positive correlation between progeny yield variance and progeny variance for b[sub i] but we conclude that the inaccuracy of the stability variance estimates is too high for good predictors for progeny stability variance to be found. [ABSTRACT FROM AUTHOR]