Identifying transcription factor-DNA interactions using machine learning
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ABSTRACT:
ORGANISM(S): Glycine max
PROVIDER: GSE193400 | GEO | 2023/06/01
REPOSITORIES: GEO
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Project description:Auxin critically regulates nearly every aspect of plant growth and development. Auxin-driven transcriptional responses are mediated through the AUXIN RESPONSE FACTOR (ARF) family of transcription factors. Although ARF protein stability is regulated via the 26S proteasome, molecular mechanisms underlying ARF stability and turnover are unknown. Here, we report the identification and functional characterization of an F-Box E3 ubiquitin ligase, which we have named AUXIN RESPONSE FACTOR F-BOX1 (AFF1). AFF1 directly interacts with ARF19 and regulates its accumulation. Mutants defective in AFF1 display ARF19 protein hyperaccumulation, mild auxin resistance, and developmental defects. Together, our data suggest a new mechanism, namely control of ARF protein stability, in regulating auxin responsiveness.
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Project description:The phytohormone auxin plays crucial roles in nearly every aspect of plant growth and development. The AUXIN RESPONSE FACTOR (ARF) family of transcription factors regulates auxin-responsive gene expression and exhibit nuclear localization in regions of high auxin responsiveness. Here we show that activating ARF7 and ARF19 proteins accumulate in micron-sized assemblies within the cytoplasm of tissues with attenuated auxin responsiveness. The intrinsically disordered middle region and the folded PB1 interaction domain of ARFs drive protein assembly formation. Mutation of a single lysine within the PB1 domain abrogates cytoplasmic assemblies, promotes ARF nuclear localization, and results in an altered transcriptome and morphological defects. Our data suggest a model in which ARF nucleo-cytoplasmic partitioning regulates auxin responsiveness, thus providing a mechanism for cellular competence for auxin signaling.
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Project description:Plants depend on the signalling of the phytohormone auxin for their development and for responding to environmental perturbations. The associated biomolecular signalling network involves a negative feedback on Aux/IAA proteins which mediate the influence of auxin (the signal) on the auxin response factor (ARF) transcription factors (the drivers of the response). To probe the role of this feedback, we consider alternative in silico signalling networks implementing different operating principles. By a comparative analysis, we find that the presence of a negative feedback allows the system to have a far larger sensitivity in its dynamical response to auxin and that this sensitivity does not prevent the system from being highly resilient. Given this insight, we build a new biomolecular signalling model for quantitatively describing such Aux/IAA and ARF responses.
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Project description:Plants depend on the signalling of the phytohormone auxin for their development and for responding to environmental perturbations. The associated biomolecular signalling network involves a negative feedback on Aux/IAA proteins which mediate the influence of auxin (the signal) on the auxin response factor (ARF) transcription factors (the drivers of the response). To probe the role of this feedback, we consider alternative in silico signalling networks implementing different operating principles. By a comparative analysis, we find that the presence of a negative feedback allows the system to have a far larger sensitivity in its dynamical response to auxin and that this sensitivity does not prevent the system from being highly resilient. Given this insight, we build a new biomolecular signalling model for quantitatively describing such Aux/IAA and ARF responses.
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Project description:We have developed a high throughput, next-generation DNA sequencing assay for rapid transcription factor binding site (TFBS) discovery in a genomic context. DNA affinity purification sequencing (DAP-seq), which uses affinity-purified transcription factors (TFs) to capture genomic DNA fragments, was applied to all 1,725 Arabidopsis thaliana TFs. High confidence TFBS motifs for 529 TFs and genome-wide enrichment maps for 349 factors were identified. In total,~ 2.7 million TFBS were identified which predict thousands of TF target genes enriched for known and novel functions.. Comparison of TF-binding using cytosine-methylated and -unmethylated genomic DNA revealed a 2-50 fold inhibition at methylated motifs for ~82% (264) of factors tested while 4.6% (15) showed stronger binding to methylated motifs. Finally, we describe how binding of Arabidopsis and maize Auxin Response Factors (ARFs) at phased motif repeats is highly enriched at ARF target gene promoters and how this architecture may allow for stabilization of dimers/multimers.
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