Biology subjects

Wulf, D.

Publications and source records attributed to Wulf, D..

7 recordsLinked to original sources

bioRxiv2024

Many transcription factor families have evolutionarily conserved binding motifs in plants

Transcription factors control gene expression during development and in response to a broad range of internal and external stimuli. They regulate promoter activity by directly binding cis- regulatory elements in DNA. The angiosperm Arabidopsis thaliana contains more than 1,500 annotated transcription factors, each containing a DNA-binding domain that is used to define transcription factor families. Analyzing binding motifs of 686 and the binding sites of 335 A. thaliana transcription factors as well as motifs of 92 transcription factors from other plants, we identified a constrained vocabulary of 74 conserved motifs spanning 50 families in plants. Among 21 transcription factor families, we found one core motif for all analyzed members and between 2 and 72% overlapping binding sites. Five families show conservation of the motif along phylogenetic clades. Five families including the C2H2 zinc finger family show high diversity among motifs in plants, suggesting potential for neofunctionalization of duplicated transcription factors based on the motif recognized. For conserved motifs we tested if they remained conserved since at least 450 million years ago by determining the binding motifs of 17 orthologous transcription factors from 11 families in M. polymorpha using amplified DNA affinity purification sequencing. We detected nearly identical binding motifs as predicted from the angiosperm data. Taken together, the results show a large repertoire of overlapping binding sites within a TF family and species and a high degree of binding motif conservation for at least 450 million years. The results indicate more potential for evolution in cis- rather than trans-regulatory elements.

plant biology↗

bioRxiv2023

Comparative analysis of gene regulatory networks identifies conserved regulators in seed plants

Gene regulatory networks based on transcription factors control development and environmental responses in plants. Networks calculated by the machine learning algorithm random forest decision tree-based regression for the grasses barley, maize, wheat, Brachypodium, sorghum, and rice compared with Arabidopsis and an alga show substantial conservation. The degree of conservation depends on phylogenetic closeness. The processes, which are conserved between all species include basic cellular functions while the processes conserved in the grasses also more specific gene ontology terms. In the three species with a carbon concentration mechanism, photorespiration is partially disassociated from photosynthetic regulation. In contrast, in the C4 species, the regulation of C4 genes associates with photosynthetic regulation. The comparative analyses reveal conserved transcription factors, which control photosynthesis in seed plants but not in the alga. An analysis pipeline for the general transfer of information between the small weed Arabidopsis and the commercially relevant grasses is presented.

plant biology↗

bioRxiv2023

Multiple transcription factors mediate acclimation of Chlamydomonas to light stress

Light as a substrate for photosynthesis may be a boon or a bane. To thrive, photosynthetic organisms must constantly respond to changing light and CO2 conditions by balancing energy harvest and consumption in a highly dynamic way. Two major safeguard measures of photoacclimation, that is photoprotection and carbon concentrating mechanism, underlie tight transcriptional control, leading to expression changes under high light and limited CO2 with different dynamics for both systems. Here, by using a consensus gene regulatory network inferred by employing a compendium of 1,869 RNA-seq datasets, we identified and validated in vivo eight candidate transcription factors (TFs) that contribute to photoacclimation in Chlamydomonas reinhardtii. Target gene analyses indicate that the TFs act individually in associated pathways but also influence each other in expression, and function as network parts with partial redundancy with respect to photoprotection. The analyses unveil that stress responses in Chlamydomonas are mediated by a complex, interconnected network of TFs rather than a hierarchical system where multiple regulators can influence each other and target gene expression and thereby mitigate the effects of loss.

plant biology↗

bioRxiv2023

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↗

bioRxiv2023

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↗

bioRxiv2020

Local DNA shape is a general principle of transcription factor binding specificity in Arabidopsis thaliana

A genome encodes two types of information, the "what can be made" and the "when and where". The "what" are mostly proteins which perform the majority of functions within living organisms and the "when and where" is the regulatory information that encodes when and where DNA is transcribed. Currently, it is possible to efficiently predict the majority of the protein content of a genome but nearly impossible to predict the transcriptional regulation. This regulation is based upon the interaction between transcription factors and genomic sequences at the site of binding motifs1,2,3. Information contained within the motif is necessary to predict transcription factor binding, however, it is not sufficient4, as experimentally verified binding sites are substantially scarcer than the corresponding binding motif. Thus, it remains challenging to derive regulational information from binding motifs. Here we show that a random forest machine learning approach, which incorporates the 3D-shape of DNA, enhances binding prediction for all 216 tested Arabidopsis thaliana transcription factors and improves the resolution of differential binding by transcription factor family members which share the same binding motif. Our results contribute to the understanding of protein-DNA recognition and demonstrate the extraction of binding site features beyond the binding sequence. We observed that those features were individually weighted for each transcription factor, even if they shared the same binding sequence. We show that the gained insights enable a more robust prediction of binding behavior regarding novel, not-in-genome motif sequences. Understanding transcription factor binding as a combination of motif sequence and motif shape brings us closer to predicting gene expression from promoter sequence.

plant biology↗

bioRxiv2020

Ubiquitin ligase component LRS1 and transcription factor CrHy5 act as a light switch for photoprotection in Chlamydomonas

Survival under excess light conditions requires the light-induced accumulation of protein LHCSR3 and other photoprotection factors, to enable efficient energy-dependent quenching in the green microalga Chlamydomonas reinhardtii. Here, we demonstrate that the high light-tolerant phenotype of mutant hit1 is caused by a de-repression of promoters belonging to photoprotection genes, which in turn results from an inactivation of the E3 ubiquitin ligase substrate adaptor LRS1. Transcriptome analyses of hit1 revealed massive alterations of gene expression modulation as a consequence of perturbed LRS1 function, indicating its role as a crown regulator. In conjunction with random forest-based network modeling, these transcriptome analyses predicted that LRS1 controls photoprotection gene expression via an algal HY5 homolog as its prime transcription factor target. CrHY5 binds to T-box elements present in the promoters of these genes and its inactivation in the hit1 mutant via CRISPR-Cas9 genome editing, confirmed the regulatory connection between LRS1 and CrHY5, predicted by the network analysis.

plant biology↗