RESUMO
Monitoring of transgenic plants in the field is important, but risk assessment has entailed laborious use of invisible marker genes. Here, we assessed three easily visible marker transgenes--green fluorescent protein (GFP), R, and Nicotiana tabacum homeobox (NTH) 15 genes--for their potential use as marker genes for monitoring genetically modified plants. Transgenic Arabidopsis thaliana plants for each of these genes were visibly distinguished from wild-type plants. We determined the germination rate, 3-week fresh weight, time to first flowering, and seed weight of the transgenic plants to evaluate whether the expression of these marker genes affected the growth of the host. Introduction of GFP gene had no effect on the evaluated parameters, and we then used the GFP gene as a marker to assess the outcrossing frequency between transgenic and two Arabidopsis species. Our results showed that the hybridization frequency between transgenic plants and Arabidopsis thaliana was 0.24%, and between transformants and Arabidopsis lyrata it was 2.6% under experimental condition. Out-crossing frequency was decreased by extending the distance between two kinds of plants. Thus, the GFP gene is a useful marker for assessing the whereabouts of transgenes/transformants in the field. We also demonstrated that the GFP gene is possibly applicable as a selection marker in the process of generation of transgenic plants.
Assuntos
Biomarcadores/análise , Poluição Ambiental , Plantas Geneticamente Modificadas/química , Plantas Geneticamente Modificadas/fisiologia , Medição de Risco , Arabidopsis/genética , Marcadores Genéticos , Germinação/fisiologia , Proteínas de Fluorescência Verde/análise , Proteínas de Fluorescência Verde/genética , Fenótipo , Sementes/fisiologia , Seleção GenéticaRESUMO
Various detrimental factors in the environment damage plants, resulting in growth inhibition or withering. However, it is not easy to identify causal factors by visually inspecting the damaged plants. Therefore, we have developed a sensitive and reliable method for plant diagnosis, based on measuring changes in expression of a set of genes in a DNA microarray. With this method, we have been able to detect and discriminate between plants stressed by ozone, drought, or wounding.