Development of a thematic collection of Musa spp accessions using SCAR markers for preventive breeding against Fusarium oxysporum f. sp cubense tropical race 4.

Bananas are one of the most consumed fruits worldwide, but are affected by many pests and diseases. One of the most devastating diseases is Fusarium wilt, caused by Fusarium oxysporum f. sp cubense (Foc). Recently, Fusarium tropical race 4 (Foc TR4) has been causing irreparable damage, especially in Asia and Africa where it has devastated entire plantations, including areas with Cavendish, which is known to be resistant to Foc race 1. Although this race is not yet present in Brazil, results obtained by Embrapa in partnership with the University of Wageningen, The Netherlands, indicate that 100% of the cultivars used by Brazilian growers are susceptible to Foc TR 4. In our study, 276 banana accessions were screened with sequence characterized amplified region (SCAR) markers that have been linked to the resistance of Foc TR 4. Two SCAR primers were tested and the results revealed that SCAR ScaU1001 was efficient at discriminating accessions with possible resistance in 36.6% of the evaluated accessions. This is the first attempt to develop a thematic collection of possible Foc TR 4 resistant banana accessions in Brazil, which could be tested in Asian or African countries to validate marker-assisted selection (MAS), and for use in the preventive breeding of the crop to safeguard our banana plantations against Foc TR 4. We believe that this is an important step towards the prevention of this devastating disease, especially considering that our banana plantations are at risk.

Evaluation of microsatellite loci from libraries derived from the wild diploid 'Calcutta 4' and 'Ouro' banana cultivars.

Microsatellite markers have been widely used in the quantification of genetic variability and for genetic breeding in Musa spp. The objective of the present study was to evaluate the discriminatory power of microsatellite markers derived from 'Calcutta 4' and 'Ouro' genomic libraries, and to analyze the genetic variability among 30 banana accessions. Thirty-eight markers were used: 15 from the 'Ouro' library and 23 from the 'Calcutta 4' library. Genetic diversity was evaluated by considering SSR markers as both dominant markers because of the presence of triploid accessions, and co-dominant markers. For the dominant analysis, polymorphism information content (PIC) values for 44 polymorphic markers ranged from 0.063 to 0.533, with a mean value of 0.24. A dendrogram analysis separated the BGB-Banana accessions into 4 groups: the 'Ouro' and 'Muísa Tia' accessions were the most dissimilar (93% dissimilarity), while the most similar accessions were 'Pacovan' and 'Walha'. The mean genetic distance between samples was 0.74. For the analysis considering SSR markers as co-dominants, using only diploid accessions, two groups were separated based on their genome contents (A and B). The PIC values for the markers from the 'Calcutta 4' library varied from 0.4836 to 0.7886, whereas those from the 'Ouro' library ranged from 0.3800 to 0.7521. Given the high PIC values, the markers from both the libraries showed high discriminatory power, and can therefore be widely applied for analysis of genetic diversity, population structures, and linkage mapping in Musa spp.

Adaptability and stability analysis of the juice yield of yellow passion fruit varieties.

This study analyzed the genotype x environment interaction (GE) for the juice productivity (JuProd) of 12 yellow passion fruit varieties (Passiflora edulis Sims. f. flavicarpa Deg.) using additive main effects and multiplicative interaction (AMMI) model and auxiliary parameters. The experiments were conducted in eight environments of Bahia State, Brazil, using a randomized block design with three replications. Analysis of variance showed significant effects (P ≤ 0.01) for environments, genotypes, and GE interaction. The first two interaction principal component axes (IPCAs) explained 81.00% of the sum of squares of the GE interaction. The AMMI1 and AMMI2 models showed that varieties 09 and 11 were the most stable. Other parameters, namely, the AMMI stability value (ASV), yield stability (YSI), sustainability, and stability index (StI), indicated that other varieties were more stable. These varying results were certainly a consequence of methodological differences. In contrast, the ranking of varieties for each of the stability parameters showed significant positive correlations (P ≤ 0.05) between IPCA1 x (ASV, YSI), JuProd x (StI, YSI), YSI x ASV, and StI x YSI. Cluster analysis based on the genotypic profile of the effects of the GE interaction identified three groups that correlated with the distribution of varieties in the AMMI1 biplot. However, the classification of stable genotypes was limited because the association with the productivity was not included in the analysis. Variety 08 showed the most stable and productive behavior, ranking above average in half of the environments, and it should be recommended for use.

Use of morpho-agronomic traits and DNA profiling for classification of genetic diversity in papaya.

We examined the genetic diversity of papaya (Carica papaya) based on morpho-agronomic and molecular data. Twenty-seven genotypes grown in Brazil were analyzed with 11 AFLP primer combinations, 23 ISSR markers, 22 qualitative, and 30 quantitative descriptors. For the joint analyses, we used the Gower algorithm (Joint Gower) and the average value of the individual dissimilarity matrix for each type of data (Average-Joint Gower); 359 AFLP and 52 ISSR polymorphic bands were found. Approximately 29.2 and 7.7% of the AFLP and ISSR bands, respectively, were genotype-specific and may therefore be used for papaya variety protection. Although there was a significant correlation between the qualitative and quantitative descriptor dissimilarity matrices (r = 0.43), the morpho-agronomic data were not highly correlated with the molecular data. Moreover, correlation between AFLP and ISSR dissimilarity matrices was nearly null (r = -0.01). Joint Gower analysis of all data showed high correlations, especially for AFLP markers, most likely due to the larger number of bands, generating a strong bias in the diversity estimates. The Average-Joint Gower analysis allowed a better balance between the correlations for the continuous and the discrete variables. The results generated by clustering analysis distinguished 5 genetically distinct groups. While we found that papaya genotypes are significantly variable for many traits, we observed that Average-Joint Gower analysis allowed for genotype clustering based on the most widely used criterion for classifying papaya genotypes, which is fruit type ('Formosa' or 'Solo'). This information helps provide an accurate estimate of the genetic diversity and structure of papaya germplasm, which will be used for further breeding strategies.