RESUMEN
Several types of information can be used to select core collections, including passport data, agronomic data, and molecular data. However, little is known about the ability of core collections to retain the genetic diversity and structure of the whole collection for characters that were not considered during the selection, particularly when molecular markers are used. In this study, two core subsets were established for the apple (Malus spp) germplasm bank curated at the Apple Research Station, National Institute of Horticultural and Herbal Science, Korea, based upon genetic diversity estimated with 14 simple sequence repeat markers, and phenotypic diversity based on 23 traits. Comparisons between these two subsets and with the whole collection were used to determine the effect of the data used in the selection on phenotypic and genetic diversity, and population structure. The two subsets had a similar diversity and did not differ from the original collection, according to the Nei and Shannon diversity indices. Allele and class frequencies were also maintained in the two subsets. Overall, the type of data used to construct the core collection had little influence on the phenotypic and genetic diversity retained. Therefore, in the case of apple collections, the use of molecular markers is preferable, because they allow rapid and reliable characterization.
Asunto(s)
Variación Genética/genética , Genotipo , Malus/genética , Fenotipo , Alelos , Cruzamiento , República de Corea , Banco de SemillasRESUMEN
Fourier transform infrared spectroscopy (FTIR) provides biochemical profiles containing overlapping signals from a majority of the compounds that are present when whole cells are analyzed. Leaf samples of seven higher plant species and varieties were subjected to FTIR to determine whether plants can be discriminated phylogenetically on the basis of biochemical profiles. A hierarchical dendrogram based on principal component analysis (PCA) of FTIR data showed relationships between plants that were in agreement with known plant taxonomy. Genetic programming (GP) analysis determined the top three to five biomarkers from FTIR data that discriminated plants at each hierarchical level of the dendrogram. Most biomarkers determined by GP analysis at each hierarchical level were specific to the carbohydrate fingerprint region (1,200-800 cm(-1)) of the FTIR spectrum. Our results indicate that differences in cell-wall composition and structure can provide the basis for chemotaxonomy of flowering plants.
Asunto(s)
Biomarcadores/análisis , Clasificación/métodos , Flores/metabolismo , Plantas/metabolismo , Espectroscopía Infrarroja por Transformada de Fourier/métodos , Metabolismo de los Hidratos de Carbono , Carbohidratos/análisis , Carbohidratos/genética , Pared Celular/metabolismo , Flores/química , Flores/genética , Análisis de Fourier , Regulación de la Expresión Génica de las Plantas/genética , Genotipo , Análisis Multivariante , Filogenia , Plantas/química , Plantas/genéticaRESUMEN
Pyrolysis mass spectrometry (PyMS) is a rapid, simple, high-resolution analytical method based on thermal degradation of complex material in a vacuum and has been widely applied to the discrimination of closely related microbial strains. Leaf samples of six species and one variety of higher plants (Rosa multiflora, R. multiflora var. platyphylla, Sedum kamtschaticum, S. takesimense, S. sarmentosum, Hepatica insularis, and H. asiatica) were subjected to PyMS for spectral fingerprinting. Principal component analysis of PyMS data was not able to discriminate these plants in discrete clusters. However, canonical variate analysis of PyMS data separated these plants from one another. A hierarchical dendrogram based on canonical variate analysis was in agreement with the known taxonomy of the plants at the variety level. These results indicate that PyMS is able to discriminate higher plants based on taxonomic classification at the family, genus, species, and variety level.