Resumo

ANDRADE-RODRIGUEZ, M. et al. Analysis of morphological characters and RAPDs fragments of twelve species of the Crassulaceae Family. Revista bio ciencias [online]. 2019, vol.6, e537.  Epub 18-Mar-2020. ISSN 2007-3380.  https://doi.org/10.15741/revbio.06.e537.

The Crassulaceae family is the most representative of Mexico due to the high endemism of most of its species and to its historical-cultural significance. They are prized and valued on the international market, causing an intense and illegal harvest and sacking of plants, fruits and seeds, with the purpose of selling and recording them in other countries. Morphological characteristics are used to study genetic diversity, to identify cultivated plants and the method of molecular characterization measures genetic variability and diversity with the purpose of conservation and protection of genetic resources. On that basis, the objective of this research work was the morphological and molecular characterization by RAPD (Random Amplified Polymorphic DNA) of twelve species of the Crassulaceae family. Twelve species of the family Crassulaceae were studied: Echeveria runyonii, E. perle, E. agavoides, E. pumila var. glauca x E. Walther., E. elegans, E. pulvinata, E. derembergii, E. setosa, Pachyphytum oviferum, Sedum clavatum, S. nussbaumerianum, and S. palmeri, which are endemic species. For morphological characterization, some characteristics used for plant description of some species from the Crassulaceae family were employed. Molecular characterization was performed by RAPD. Data were processed using the Numerical Taxonomic and Multivariate Analysis System (NTSYSpc 2.1). Quantitative characters separated the twelve species into five groups according to the cluster analysis. Six groups were obtained with the RAPD analysis. The most genetically similar species were: E. runyonii and E. derembergii, indicating more genetic crossing possibilities for interspecific hybridization.

Palavras-chave : Endemic species; Morphological and molecular analysis; clustering; multivariate analysis.