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Zenker, S.

Publications and source records attributed to Zenker, S..

2 recordsLinked to original sources

Transcription factors operate on a limited vocabulary of binding motifs in Arabidopsis thaliana

Predicting gene expression from promoter sequence requires understanding of the different signal integration points within a promoter. Sequence-specific transcription factors (TFs) binding to their cognate TF binding motifs control gene expression in eukaryotes by activating and repressing transcription. Their interplay generates complex expression patterns in reaction to environmental conditions and developmental cues. We hypothesized that signals are not only integrated by different TFs binding various positions in a promoter, but also by single TF binding motifs onto which multiple TFs can bind. Analyzing 2,190 binding motifs, we identified only 76 core TF binding motifs in plants. Twenty-one TF protein families act highly specific and bind a single conserved motif. Four TF families are classified as semi-conserved as they bind up to four motifs within a family, with divisions along phylogenetic groups. Five TF families bind diverse motifs. Expression analyses revealed high competition within TF families for the same binding motif. The results show that singular binding motifs act as signal integrators in plants where a combination of binding affinity and TF abundance likely determine the output.

systems biology↗

Transcription factors mediating regulation of photosynthesis

Photosynthesis by which plants convert carbon dioxide to sugars using the energy of light is fundamental to life as it forms the basis of nearly all food chains. Surprisingly, our knowledge about its transcriptional regulation remains incomplete. Effort for its agricultural optimization have mostly focused on post-translational regulatory processes1-3 but photosynthesis is regulated at the post-transcriptional4 and the transcriptional level5. Stacked transcription factor mutations remain photosynthetically active5,6 and additional transcription factors have been difficult to identify possibly due to redundancy6 or lethality. Using a random forest decision tree-based machine learning approach for gene regulatory network calculation7 we determined ranked candidate transcription factors and validated five out of five tested transcription factors as controlling photosynthesis in vivo. The detailed analyses of previously published and newly identified transcription factors suggest that photosynthesis is transcriptionally regulated in a partitioned, non-hierarchical, interlooped network.

plant biology↗