Plant breeding can be broadly defined as alterations caused in plants as a result of their use by humans, ranging from unintentional changes resulting from the advent of agriculture to the application of molecular tools for precision breeding. The vast diversity of breeding methods can be simplified into three categories: (i) plant breeding based on observed variation by selection of plants based on natural variants appearing in nature or within traditional varieties; (ii) plant breeding based on controlled mating by selection of plants presenting recombination of desirable genes from different parents; and (iii) plant breeding based on monitored recombination by selection of specific genes or marker profiles, using molecular tools for tracking within-genome variation. The continuous application of traditional breeding methods in a given species could lead to the narrowing of the gene pool from which cultivars are drawn, rendering crops vulnerable to biotic and abiotic stresses and hampering future progress. Several methods have been devised for introducing exotic variation into elite germplasm without undesirable effects. Cases in rice are given to illustrate the potential and limitations of different breeding approaches.

Estimation of allele dosage, using genomic data, in autopolyploids is challenging and current methods often result in the misclassification of genotypes. Some progress has been made when using SNP arrays, but the major challenge is when using next generation sequencing data. Here we compare the use of read depth as continuous parameterization with ploidy parameterizations in the context of genomic selection (GS). Additionally, different sources of information to build relationship matrices were compared. A real breeding population of the autotetraploid species blueberry ( Vaccinium corybosum ), composed of 1,847 individuals was phenotyped for eight yield and fruit quality traits over two years. Continuous genotypic based models performed as well as the best models. This approach also reduces the computational time and avoids problems associated with misclassification of genotypic classes when assigning dosage in polyploid species. This approach could be very valuable for species with higher ploidy levels or for emerging crops where ploidy is not well understood. To our knowledge, this work constitutes the first study of genomic selection in blueberry. Accuracies are encouraging for application of GS for blueberry breeding. GS could reduce the time for cultivar release by three years, increasing the genetic gain per cycle by 86% on average when compared to phenotypic selection, and 32% when compared with pedigree-based selection. Finally, the genotypic and phenotypic data used in this study are made available for comparative analysis of dosage calling and genomic selection prediction models in the context of autopolyploids.

The "cagaita tree" (Eugenia dysenterica) is a plant found widespread in the Brazilian Cerrado. Its fruit is used for popular consumption and for industrial purposes. This study opens a new perspective for the generation of population genetic data and parameters estimates for devising sound collection and conservation procedures for Eugenia dysenterica. A battery of 356 primer pairs developed for Eucalyptus spp. was tested on the "cagaita tree". Only 10 primer pairs were found to be transferable between the two species. Using a polyacrilamide gel, an average of 10.4 alleles per locus was detected, in a sample of 116 individuals from 10 natural "cagaita tree" populations. Seven polymorphic loci allowed estimation of genetic parameters, including expected average heterozygosity H e = 0,442, among population diversity, R ST = 0,268 and gene flow Nm = 0,680. Results indicated a potential of SSR locus transferability developed for Eucalyptus to other species of different genera, such as in the case of the "cagaita tree". The high genetic diversity among populations detected with SSR markers indicated that these markers are highly sensitive to detect population structure. Estimated Nm values and the existence of private alleles indicated reduced gene flow and consequently possible damage to the metapopulation structure.

BackgroundCommon bean is a legume of social and nutritional importance as a food crop, cultivated worldwide especially in developing countries, accounting for an important source of income for small farmers. The availability of the complete sequences of the two common bean genomes has dramatically accelerated and has enabled new experimental strategies to be applied for genetic research. DArTseq has been widely used as a method of SNP genotyping allowing comprehensive genome coverage with genetic applications in common bean breeding programs.ResultsUsing this technology, 6286 SNPs (1 SNP/86.5 Kbp) were genotyped in genic (43.3%) and non-genic regions (56.7%). Genetic subdivision associated to the common bean gene pools (K = 2) and related to grain types (K = 3 and K = 5) were reported. A total of 83% and 91% of all SNPs were polymorphic within the Andean and Mesoamerican gene pools, respectively, and 26% were able to differentiate the gene pools. Genetic diversity analysis revealed an average H E of 0.442 for the whole collection, 0.102 for Andean and 0.168 for Mesoamerican gene pools (F ST = 0.747 between gene pools), 0.440 for the group of cultivars and lines, and 0.448 for the group of landrace accessions (F ST = 0.002 between cultivar/line and landrace groups). The SNP effects were predicted with predominance of impact on non-coding regions (77.8%). SNPs under selection were identified within gene pools comparing landrace and cultivar/line germplasm groups (Andean: 18; Mesoamerican: 69) and between the gene pools (59 SNPs), predominantly on chromosomes 1 and 9. The LD extension estimate corrected for population structure and relatedness (r2 SV) was ~ 88 kbp, while for the Andean gene pool was ~ 395 kbp, and for the Mesoamerican was ~ 130 kbp.ConclusionsFor common bean, DArTseq provides an efficient and cost-effective strategy of generating SNPs for large-scale genome-wide studies. The DArTseq resulted in an operational panel of 560 polymorphic SNPs in linkage equilibrium, providing high genome coverage. This SNP set could be used in genotyping platforms with many applications, such as population genetics, phylogeny relation between common bean varieties and support to molecular breeding approaches.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3805-4) contains supplementary material, which is available to authorized users.

Some species of Trichoderma have successfully been used in the commercial biological control of fungal pathogens, e.g., Sclerotinia sclerotiorum, an economically important pathogen of common beans (Phaseolus vulgaris L.). The objectives of the present study were (1) to provide molecular characterization of Trichoderma strains isolated from the Brazilian Cerrado; (2) to assess the metabolic profile of each strain by means of Biolog FF Microplates; and (3) to evaluate the ability of each strain to antagonize S. sclerotiorum via the production of cell wall-degrading enzymes (CWDEs), volatile antibiotics, and dual-culture tests. Among 21 isolates, we identified 42.86% as Trichoderma asperellum, 33.33% as Trichoderma harzianum, 14.29% as Trichoderma tomentosum, 4.76% as Trichoderma koningiopsis, and 4.76% as Trichoderma erinaceum. Trichoderma asperellum showed the highest CWDE activity. However, no species secreted a specific group of CWDEs. Trichoderma asperellum 364/01, T. asperellum 483/02, and T. asperellum 356/02 exhibited high and medium specific activities for key enzymes in the mycoparasitic process, but a low capacity for antagonism. We observed no significant correlation between CWDE and antagonism, or between metabolic profile and antagonism. The diversity of Trichoderma species, and in particular of T. harzianum, was clearly reflected in their metabolic profiles. Our findings indicate that the selection of Trichoderma candidates for biological control should be based primarily on the environmental fitness of competitive isolates and the target pathogen.