Functional Characterization of Hedychium coronarium J. Koenig MYB132 Confers the Potential Role in Floral Aroma Synthesis

The R2R3-MYB transcription factors (TFs) play several key roles in numerous plant biological processes. Hedychium coronarium is an important ornamental plant well-known for its elegant flower shape and abundant aroma type. The floral aroma of H. coronarium is due to the presence of a large amount of terpenes and benzenoids. However, less is known about the role of R2R3-MYB TFs in the regulatory mechanism of floral aroma production in this breed. Herein, we isolate and functionally characterize the R2R3-MYB TF HcMYB132, which is potentially involved in regulating floral aroma synthesis. Sequence alignment analysis revealed that it includes a nuclear localization signal NLS(s) and a 2R, 3R motif signature in the sequences. A subcellular localization assay revealed that HcMYB132 protein localizes to the nucleus. Real-time qPCR assays showed that HcMYB132 is specifically expressed in flowers and its expression pattern correlates with the emission of floral volatile compounds. In HcMYB132-silenced flowers, the levels of floral volatile compounds were significantly reduced, and the expression of key structural volatile synthesis genes was downregulated compared to control. Collectively, these results suggest that HcMYB132 might play a significant role in the regulation of terpenoid biosynthesis in H. coronarium.

Artefacts in statistical analyses of network motifs: general framework and application to metabolic networks

Few-node subgraphs are the smallest collective units in a network that can be investigated. They are beyond the scale of individual nodes but more local than, for example, communities. When statistically over- or under-represented, they are called network motifs. Network motifs have been interpreted as building blocks that shape the dynamic behaviour of networks. It is this promise of potentially explaining emergent properties of complex systems with relatively simple structures that led to an interest in network motifs in an ever-growing number of studies and across disciplines. Here, we discuss artefacts in the analysis of network motifs arising from discrepancies between the network under investigation and the pool of random graphs serving as a null model. Our aim was to provide a clear and accessible catalogue of such incongruities and their effect on the motif signature. As a case study, we explore the metabolic network of Escherichia coli and show that only by excluding ever more artefacts from the motif signature a strong and plausible correlation with the essentiality profile of metabolic reactions emerges.