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.
Original language | English (US) |
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Article number | 92 |
Journal | BMC plant biology |
Volume | 9 |
DOIs | |
State | Published - 2009 |
Bibliographical note
Funding Information:The authors thank members of the Carter lab for their helpful suggestions and assistance with development of nectary collection and RNA isolation procedures, particularly Mr. Robert Duerst and Mr. Ryan Leege. The authors also thank Dr. Marci Surpin for critical reading of the manuscript. This work was supported by the United States Department of Agriculture (2006-35301-16887 to CJC) and the National Science Foundation (0820730 to CJC), as well as computational resources available at the Minnesota Supercomputing Institute at the University of Minnesota Twin Cities.