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      Uncovering the Arabidopsis thaliana nectary transcriptome: investigation of differential gene expression in floral nectariferous tissues

      1 , 2 , , 1

      BMC Plant Biology

      BioMed Central

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Many flowering plants attract pollinators by offering a reward of floral nectar. Remarkably, the molecular events involved in the development of nectaries, the organs that produce nectar, as well as the synthesis and secretion of nectar itself, are poorly understood. Indeed, to date, no genes have been shown to directly affect the de novo production or quality of floral nectar. To address this gap in knowledge, the ATH1 Affymetrix ® GeneChip array was used to systematically investigate the Arabidopsis nectary transcriptome to identify genes and pathways potentially involved in nectar production.

          Results

          In this study, we identified a large number of genes differentially expressed between secretory lateral nectaries and non-secretory median nectary tissues, as well as between mature lateral nectaries (post-anthesis) and immature lateral nectaries (pre-anthesis). Expression within nectaries was also compared to thirteen non-nectary reference tissues, from which 270 genes were identified as being significantly upregulated in nectaries. The expression patterns of 14 nectary-enriched genes were also confirmed via RT PCR. Upon looking into functional groups of upregulated genes, pathways involved in gene regulation, carbohydrate metabolism, and lipid metabolism were particularly enriched in nectaries versus reference tissues.

          Conclusion

          A large number of genes preferentially expressed in nectaries, as well as between nectary types and developmental stages, were identified. Several hypotheses relating to mechanisms of nectar production and regulation thereof are proposed, and provide a starting point for reverse genetics approaches to determine molecular mechanisms underlying nectar synthesis and secretion.

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          Most cited references 83

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          Summaries of Affymetrix GeneChip probe level data.

          High density oligonucleotide array technology is widely used in many areas of biomedical research for quantitative and highly parallel measurements of gene expression. Affymetrix GeneChip arrays are the most popular. In this technology each gene is typically represented by a set of 11-20 pairs of probes. In order to obtain expression measures it is necessary to summarize the probe level data. Using two extensive spike-in studies and a dilution study, we developed a set of tools for assessing the effectiveness of expression measures. We found that the performance of the current version of the default expression measure provided by Affymetrix Microarray Suite can be significantly improved by the use of probe level summaries derived from empirically motivated statistical models. In particular, improvements in the ability to detect differentially expressed genes are demonstrated.
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            Genome-wide identification and testing of superior reference genes for transcript normalization in Arabidopsis.

            Gene transcripts with invariant abundance during development and in the face of environmental stimuli are essential reference points for accurate gene expression analyses, such as RNA gel-blot analysis or quantitative reverse transcription-polymerase chain reaction (PCR). An exceptionally large set of data from Affymetrix ATH1 whole-genome GeneChip studies provided the means to identify a new generation of reference genes with very stable expression levels in the model plant species Arabidopsis (Arabidopsis thaliana). Hundreds of Arabidopsis genes were found that outperform traditional reference genes in terms of expression stability throughout development and under a range of environmental conditions. Most of these were expressed at much lower levels than traditional reference genes, making them very suitable for normalization of gene expression over a wide range of transcript levels. Specific and efficient primers were developed for 22 genes and tested on a diverse set of 20 cDNA samples. Quantitative reverse transcription-PCR confirmed superior expression stability and lower absolute expression levels for many of these genes, including genes encoding a protein phosphatase 2A subunit, a coatomer subunit, and an ubiquitin-conjugating enzyme. The developed PCR primers or hybridization probes for the novel reference genes will enable better normalization and quantification of transcript levels in Arabidopsis in the future.
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              A gene expression map of Arabidopsis thaliana development.

              Regulatory regions of plant genes tend to be more compact than those of animal genes, but the complement of transcription factors encoded in plant genomes is as large or larger than that found in those of animals. Plants therefore provide an opportunity to study how transcriptional programs control multicellular development. We analyzed global gene expression during development of the reference plant Arabidopsis thaliana in samples covering many stages, from embryogenesis to senescence, and diverse organs. Here, we provide a first analysis of this data set, which is part of the AtGenExpress expression atlas. We observed that the expression levels of transcription factor genes and signal transduction components are similar to those of metabolic genes. Examining the expression patterns of large gene families, we found that they are often more similar than would be expected by chance, indicating that many gene families have been co-opted for specific developmental processes.
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                Author and article information

                Journal
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central
                1471-2229
                2009
                15 July 2009
                : 9
                : 92
                Affiliations
                [1 ]Department of Biology, University of Minnesota Duluth, Duluth, MN 55812, USA
                [2 ]Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA
                Article
                1471-2229-9-92
                10.1186/1471-2229-9-92
                2720969
                19604393
                Copyright © 2009 Kram et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Categories
                Research Article

                Plant science & Botany

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