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Our working group is a part of the Laboratory of Plant Morphogenesis led by Dr. Ivana Macháková. We are interested in various aspects of plant reproduction in lesser-known plant species with an aim to clarify phenomena that are absent or overlooked in classic model plants. We are identifying key genes of flowering induction pathways in Chenopodium rubrum (goosefoot), which can be induced to flower at a seedling stage. We are also searching for cytoplasmic male sterility genes in the mitochondrial genome of Silene vulgaris (bladder campion), a plant species with an enormous polymorphism of mitochondrial DNA. This plant is well suited to reveal interactions governing transcription, recombination, and replication of mitochondrial genome—the most enigmatic plant DNA molecule. Transcription analysis of the genes involved in plant regulation networks is an important tool of our research. We adopted and modified various techniques of messenger RNA (mRNA) quantification to support not only our projects, but also to help other colleagues of our institute.
www.ueb.cas.cz/laboratory_of_plant_morphogenesis/Storchova/homeus.html
The Technique
Quantitative reverse transcription PCR (RT-PCR) has become an essential method in flowering, plant hormone, and stress response studies and complements traditional physiological approaches. However, selecting appropriate reference genes in not-so-favored plants is a very challenging task, particularly when stress response is being analyzed. We sought a more universal standard to enable normalization of expression data without the need for reference gene selection. Here, we show that quantification of cDNA with a single-stranded DNA binding dye fulfilled this need. We plan to apply this method for direct normalization of expression data in studies of abiotic stress response in plants. This modification of quantitative RT-PCR has already contributed to the fast progress of many projects in our institute.
Quantification of cDNA generated by reverse transcription of total RNA provides a simple alternative tool for quantitative RT-PCR normalization, p. 156.
