Brazilian orchids are currently threatened with extinction due to habitat loss and, because of their high ornamental value, intense collecting pressure. Genetic diversity can play a key role in the survival of endangered orchid species. Here we provide the first data on genetic diversity and structure of wild populations in the genus Cattleya, in particular C. labiata, using random amplified polymorphic DNA (RAPD) and intersimple sequence repeat (ISSR) markers. We studied 130 individuals, 117 belonging to Cattleya labiata and 13 from 10 other species in the same genus. Data generated from 12 ISSR and 12 RAPD primers were used to determine genetic variability via a model-based Bayesian procedure (Structure) and molecular variance analysis. In addition, Shannon index, genetic diversity and Jaccard coefficients were also estimated. The marker data indicated that C. labiata has a high level of polymorphism, and five reconstructed populations were identified by Structure. The unweighted pair group method with arithmetic mean dendrogram did not group the samples by origin, which was also confirmed by Bayesian analysis, demonstrating the complex genetic structure of C. labiata. Other Cattleya species showed no relationship with any C. labiata sample. This genetic characterization of Cattleya from northeast Brazil contributes to knowledge of the genetic structure of the species and can be used to define strategies for conservation and breeding programmes.
White mold, caused by Sclerotinea sclerotiorum (Lib.) de Bary is one of the most important diseases of the common bean (Phaseolus vulgaris L.) worldwide. Physiological resistance and traits related to disease avoidance such as architecture contribute to field resistance. The aim of this study was to verify the efficiency of recurrent selection in physiological resistance to white mold, "Carioca" grain type and upright habit in common bean. Thirteen common bean lines with partial resistance to white mold were intercrossed by means of a circulant diallel table, and seven recurrent selection cycles were obtained. Of these cycles, progenies of the S 0:1 , S 0:2 and S 0:3 generations of cycles III, IV, V and VI were evaluated. The best (8 to 10) progenies of the seven cycles were also evaluated, in two experiments, one in the greenhouse and one in the field. Lattice and/or randomized block experimental designs were used. The traits evaluated were: resistance to white mold by the straw test method, growth habit and grain type. The most resistant progenies were selected based on the average score of resistance to white mold. Subsequently, they were evaluated with regard to grain type and growth habit. Recurrent selection allowed for genetic progress of about 11 % per year for white mold resistance and about 15 % per year for the plant architecture.There was no gain among cycles for grain type. Progeny selection and recurrent selection were efficient for obtaining progenies with a high level of resistance to white mold with "Carioca" grain type and upright habit.
The sweet potato, Ipomoea batatas (L.) Lam has its origin in Tropical America. In Sergipe State (Brazil), its production is very important, and to explore its potential in local agriculture in the State, the Embrapa Coastal Tableland created a collection with 52 accessions located in Umbaúba City. Some accessions were from germplasm belonging to Embrapa vegetables and others from local farmers of Sergipe. Here, we provide the first data on the genetic diversity and structure of sweet potato collection of SPGB using random amplified polymorphic DNA (RAPD) markers. RAPD data were used to determine genetic variability via a model-based Bayesian procedure (structure) and molecular variance analysis (AMOVA). In addition, Shannon index, genetic diversity and Jaccard coefficients were also estimated. RAPD was efficient for the analysis of genetic diversity to identify groups and measure the genetic distance between accessions. The markers showed that the collection had a high level of polymorphism. By UPGMA, we separated three groups of genotypes and identified two reconstructed populations by structure software.
ABSTRACT. In this study, we aimed to estimate the relationship between some common bean traits using molecular markers and applying QTL mapping. We used a segregating population derived from a crossing between common bean cultivars, Jalo and Small White, in the Southern State of Minas Gerais. Of F 2 plants, 190 F 2:3 progenies were generated. Phenotypic measures related to the pod and leaf lengths and the 100-grain weight were used. DNA sampling and genotyping with SSR markers were performed in F 2 plants and the pure parental. The 190 F 2:3 progenies and six controls were evaluated through a 14 x 14-m triple lattice. Adjusted means of evaluations related to F 2:3 were used in QTL mapping using Bayesian moving away method. Significant genetic differences were detected between parents and between progenies for all traits. The heritability estimates were 58.89, 79.39, and 50.37% for leaf length, 100-grain weight, and pod length, respectively. Genetic and phenotypic correlations were significant and ranged from 0.44 to 0.74, which indicated an association between leaf length, 100-grain weight, and pod length traits. Significant genetic correlations between the three morpho-agronomic traits may be due to associations between QTL for different traits. The most promising candidate marker was the BMD17 for leaf length; BM143 for 100-grain weight; X57211 and PVBR118 for pod length. The most promising markers, which might be used for indirect selection for all three traits, are simultaneously X57211 and BM197.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.