Quantitative analysis of cell-type specific gene expression in the green alga <it>Volvox carteri</it>

<p>Abstract</p> <p>Background</p> <p>The multicellular alga <it>Volvox carteri </it>possesses only two cell types: mortal, motile somatic cells and potentially immortal, immotile reproductive cells. It is therefore an attractive model system for studying how...

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Bibliographic Details
Main Authors: Hallmann Armin, Kianianmomeni Arash, Nematollahi Ghazaleh
Format: Article
Language:English
Published: BMC 2006-12-01
Series:BMC Genomics
Online Access:http://www.biomedcentral.com/1471-2164/7/321
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Summary:<p>Abstract</p> <p>Background</p> <p>The multicellular alga <it>Volvox carteri </it>possesses only two cell types: mortal, motile somatic cells and potentially immortal, immotile reproductive cells. It is therefore an attractive model system for studying how cell-autonomous cytodifferentiation is programmed within a genome. Moreover, there are ongoing genome projects both in <it>Volvox carteri </it>and in the closely related unicellular alga <it>Chlamydomonas reinhardtii</it>. However, gene sequencing is only the beginning. To identify cell-type specific expression and to determine relative expression rates, we evaluate the potential of real-time RT-PCR for quantifying gene transcript levels.</p> <p>Results</p> <p>Here we analyze a diversified pool of 39 target genes by real-time RT-PCR for each cell type. This gene pool contains previously known genes with unknown localization of cellular expression, 28 novel genes which are described in this study for the first time, and a few known, cell-type specific genes as a control. The respective gene products are, for instance, part of photosynthesis, cellular regulation, stress response, or transport processes. We provide expression data for all these genes.</p> <p>Conclusion</p> <p>The results show that quantitative real-time RT-PCR is a favorable approach to analyze cell-type specific gene expression in <it>Volvox</it>, which can be extended to a much larger number of genes or to developmental or metabolic mutants. Our expression data also provide a basis for a detailed analysis of individual, previously unknown, cell-type specifically expressed genes.</p>
ISSN:1471-2164