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1

Functional genomic tools for Arabidopsis available at the MPIZ

100%
Dekker K., Sorensen T. R., Weisshaar B., Saedler H.
Biotechnologia
|
2003
|
issue 4
19-31
EN
This article summarizes the activities at the Max Planck Institute for Plant Breeding Research (Max-Planck-Institut f?r Z?chtungsforschung, MPIZ) in the area of ?Arabidopsis genomics?. We describe the status of three Arabidopsis thaliana genomic projects at the MPIZ: 1) The Gene Knock-Out Facility ZIGIA (Zentrum zur Identifikation von Genfunktionen durch Insertionsmutagenese bei A. thaliana, Center for Functional Genomics in A. thaliana) using lines tagged with the maize transposon En/Spm, 2) the GABI-Kat project that provides sequence indexed T-DNA tagged lines and 3) the GABI-MASC project that creates mapping tools based on single nucleotide polymorphisms (SNP) for efficient assessment of natural diversity in A. thaliana. The materials and tools developed by these projects are publicly available and used worldwide by scientist to explore the frontiers of plant sciences.
2

Physical, chemical and genetical methods of plant mutagenesis

100%
Sobkowiak L., Szweykowska-Kulinska Z.
|
2007
|
issue 4
157-169
EN
The challenge for the plant functional genomics is to elucidate the function of every gene in the plant genome. Definitive allocation of gene function requires the introduction of mutations and further analysis of their phenotypic repercussions. Chemical and ionizing radiation mutagenesis are useful tools to generate genetic variability for functional genomic studies. T-DNA fragments and transposable elements can potentially generate mutations disrupting gene continuity. ZFN mutagenesis method allows the introduction of genetic changes precisely into the desired genome region.
3

Metabolomics ? a tool in functional genomics and systems biology

88%
Stobiecki M.
Biotechnologia
|
2009
|
issue 2
54-64
EN
The concept of metabolomic studies has been developed during the last decade. Comprehensive analysis of primary and secondary metabolites in living organisms grown under genetic and environmental stresses may deliver interesting information about the status of the studied microorganisms, plants or animals. The metabolome analysis may be performed using different methodical approaches and various physicochemical methods may be applied for identification of low molecular compounds. Due to huge sets of data collected during the metabolomic studies, different statistical calculations and bioinformatic technologies are used for the presentation and interpretation of the results.
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