Journal of Experimental BotanyPlant BiologyPeer-reviewed journal article
Auxin-induced expression divergence between Arabidopsis species likely originates within the TIR1/AFB-AUX/IAA-ARF module
Jana TrenneriD, Yvonne Poeschl, Jan GrauiD, Andreas Gogol-Döring, Marcel QuintiD, Carolin DelkeriD
Abstract
HighlightTIR1/AFB, AUX/IAA, and ARF proteins show interspecies expression variation correlating with variation in downstream responses which indicates a source for natural variation within this conserved signaling module.\n\nAbstractAuxin is an essential regulator of plant growth and development and auxin signaling components are conserved among land plants. Yet, a remarkable degree of natural variation in physiological and transcriptional auxin responses has been described among Arabidopsis thaliana accessions. As intra-species comparisons offer only limited genetic variation, we here inspect the variation of auxin responses between A. thaliana and A. lyrata. This approach allowed the identification of conserved auxin response genes including novel genes with potential relevance for auxin biology. Furthermore, promoter divergences were analyzed for putative sources of variation. De novo motif discovery identified novel and variants of known elements with potential relevance for auxin responses, emphasizing the complex, and yet elusive, code of element combinations accounting for the diversity in transcriptional auxin responses. Furthermore, network analysis revealed correlations of inter-species differences in the expression of AUX/IAA gene clusters and classic auxin-related genes. We conclude that variation in general transcriptional and physiological auxin responses may originate substantially from functional or transcriptional variations in the TIR1/AFB, AUX/IAA, and ARF signaling network. In that respect, AUX/IAA gene expression divergence potentially reflects differences in the manner in which different species transduce identical auxin signals into gene expression responses.
- organism: Arabidopsis
- assay: DNA methylation
- assay: proteomics
- research focus: gene regulatory network inference
- approach: statistical model
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