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Plant Biol (Stuttg). 2005 May;7(3):228-37.

Large-scale analysis of 73 329 physcomitrella plants transformed with different gene disruption libraries: production parameters and mutant phenotypes.

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Plant Biotechnology, Faculty of Biology, University of Freiburg, Schänzlestrasse 1, 79104 Freiburg, Germany.


Gene targeting in the moss Physcomitrella patens has created a new platform for plant functional genomics. We produced a mutant collection of 73 329 Physcomitrella plants and evaluated the phenotype of each transformant in comparison to wild type Physcomitrella. Production parameters and morphological changes in 16 categories, such as plant structure, colour, coverage with gametophores, cell shape, etc., were listed and all data were compiled in a database (mossDB). Our mutant collection consists of at least 1804 auxotrophic mutants which showed growth defects on minimal Knop medium but were rescued on supplemented medium. 8129 haploid and 11 068 polyploid transformants had morphological alterations. 9 % of the haploid transformants had deviations in the leaf shape, 7 % developed less gametophores or had a different leaf cell shape. Other morphological deviations in plant structure, colour, and uniformity of leaves on a moss colony were less frequently observed. Preculture conditions of the plant material and the cDNA library (representing genes from either protonema, gametophore or sporophyte tissue) used to transform Physcomitrella had an effect on the number of transformants per transformation. We found correlations between ploidy level and plant morphology and growth rate on Knop medium. In haploid transformants correlations between the percentage of plants with specific phenotypes and the cDNA library used for transformation were detected. The number of different cDNAs present during transformation had no effect on the number of transformants per transformation, but it had an effect on the overall percentage of plants with phenotypic deviations. We conclude that by linking incoming molecular, proteome, and metabolome data of the transformants in the future, the database mossDB will be a valuable biological resource for systems biology.

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