bioRxivPlant BiologyPreprint
Dosage of duplicated and antifunctionalized homeobox proteins influences spikelet development in barley
V. Thirulogachandar, G. Govind, G. Hensel, S. Kale, M. Kuhlmann, L. Eschen-Lippold, T. Rutten, R. Koppolu, J. Rajaraman, P. S. Reddy, C. Seiler, S. Sakuma, M. Jayakodi, J. Lee, J. Kumlehn, T. Komatsuda, T. Schnurbusch, N. Sreenivasulu
Abstract
Illuminating the mechanisms of inflorescence architecture of grain crops that feed our world may strengthen the goal towards sustainable agriculture. Lateral spikelet development of barley (Hordeum vulgare L.) is such an example of a floral architectural trait regulated by VRS1 (Vulgare Row-type Spike 1 or Six-rowed Spike 1, syn. HvHOX1). Its lateral spikelet-specific expression and the quantitative nature of suppressing spikelet development were previously shown in barley. However, the mechanistic function of this gene and its paralog HvHOX2 on spikelet development is still fragmentary.Here, we show that these duplicated transcription factors (TFs) have contrasting nucleotide diversity in various barley genotypes and several Hordeum species. Despite this difference, both proteins retain their basic properties of the homeodomain leucine zipper class I family of TFs. During spikelet development, these genes exhibit similar spatiotemporal expression patterns yet with anticyclic expression levels. A gene co-expression network analysis suggested that both have an ancestral relationship but their functions appear antagonistic to each other, i.e., HvHOX1 suppresses whereas HvHOX2 rather promotes spikelet development. Our transgenic promoter-swap analysis showed that HvHOX2 can restore suppressed lateral spikelets when expression levels are increased; however, at its low endogenous expression level, HvHOX2 appears dispensable for spikelet development. Collectively, this study proposes that the dosage of the two antagonistic TFs, HvHOX1 and HvHOX2, influence spikelet development in barley.
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: gene regulatory network inference
- approach: statistical model
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