Publikationen - Molekulare Signalverarbeitung

Auxin 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.

Combining transcriptome data of biological processes or response to stimuli with evolutionary information such as the phylogenetic conservation of genes or their sequence divergence rates enables the investigation of evolutionary constraints on these processes or responses. Such phylotranscriptomic analyses recently unraveled that mid-developmental transcriptomes of fly, fish, and cress were dominated by evolutionarily conserved genes and genes under negative selection and thus recapitulated the developmental hourglass on the transcriptomic level. Here, we present a protocol for performing phylotranscriptomic analyses on any biological process of interest. When applying this protocol, users are capable of detecting different evolutionary constraints acting on different stages of the biological process of interest in any species. For each step of the protocol, modular and easy-to-use open-source software tools are provided, which enable a broad range of scientists to apply phylotranscriptomic analyses to a wide spectrum of biological questions.