Quantitative Analysis of Cis-Regulatory Element Activity Using Synthetic Promoters in Transgenic Plants

Benn, Geoffrey; Dehesh, Katayoon

doi:10.1007/978-1-4939-6396-6_2

Cited by 4 publications

(4 citation statements)

References 33 publications

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“…Testing the functional impact of a predicted TFBS usually involves targeted mutagenesis in a transgenic context, e.g., using reporter assays, or in an endogenous context using CRISPR-Cas9-based systems. By using reporter genes (e.g., GFP or luciferase) under control of the target gene regulatory regions with modified TFBSs, it is possible to dissect spatiotemporal and quantitative changes in target gene expression depending on the presence or absence of a TFBS (Benn and Dehesh, 2016;Díaz-Triviñ o et al, 2017). For example, the tissue specificity of the AP3 promoter was altered by replacing native TFBS with the ones of predicted specificity toward SEP3-AG or SEP3-AP1 floral homeotic protein complexes (Smaczniak et al, 2017).…”

Section: Targeted Tfbs Perturbationmentioning

confidence: 99%

Building Transcription Factor Binding Site Models to Understand Gene Regulation in Plants

et al. 2019

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Transcription factors (TFs) are key cellular components that control gene expression. They recognize specific DNA sequences, the TF binding sites (TFBSs), and thus are targeted to specific regions of the genome where they can recruit transcriptional co-factors and/or chromatin regulators to fine-tune spatiotemporal gene regulation. Therefore, the identification of TFBSs in genomic sequences and their subsequent quantitative modeling is of crucial importance for understanding and predicting gene expression. Here, we review how TFBSs can be determined experimentally, how the TFBS models can be constructed in silico, and how they can be optimized by taking into account features such as position interdependence within TFBSs, DNA shape, and/or by introducing state-of-the-art computational algorithms such as deep learning methods. In addition, we discuss the integration of context variables into the TFBS modeling, including nucleosome positioning, chromatin states, methylation patterns, 3D genome architectures, and TF cooperative binding, in order to better predict TF binding under cellular contexts. Finally, we explore the possibilities of combining the optimized TFBS model with technological advances, such as targeted TFBS perturbation by CRISPR, to better understand gene regulation, evolution, and plant diversity.

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Section: Targeted Tfbs Perturbationmentioning

confidence: 99%

Building Transcription Factor Binding Site Models to Understand Gene Regulation in Plants

et al. 2019

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“…Previous studies of plants at 5 min post wounding led to the identification of an over-represented functional cis-element, dubbed the rapid stress response element (RSRE; CGCGTT), which is analogous to the yeast stress response element (STRE) (Kobayashi & McEntee, 1993;Marchler et al, 1993;Walley et al, 2007). Exploitation of transgenic Arabidopsis expressing RSRE::Luciferase (4xRSRE::LUC) confirmed the multi-stress-responsive nature of RSRE induction and the suitability of the transgenic line for readout of stress-induced rapid transcriptional responses Benn & Dehesh, 2016;Bjornson et al, 2014;Walley et al, 2007). Various studies have established the role of CALMODULIN-BINDING TRAN-SCRIPTION ACTIVATORs (CAMTA) transcription factors in the activation of RSRE (Benn et al, 2014;Moore et al, 2021).…”

Section: Introductionmentioning

confidence: 98%

ORA47 is a transcriptional regulator of a general stress response hub

et al. 2022

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Transcriptional regulators of the general stress response (GSR) reprogram the expression of selected genes to transduce informational signals into cellular events, ultimately manifested in a plant's ability to cope with environmental challenges. Identification of the core GSR regulatory proteins will uncover the principal modules and their mode of action in the establishment of adaptive responses. To define the GSR regulatory components, we employed a yeast-one-hybrid assay to identify the protein(s) binding to the previously established functional GSR motif, termed the rapid stress response element (RSRE). This led to the isolation of octadecanoid-responsive AP2/ERF-domain transcription factor 47 (ORA47), a methyl jasmonate inducible protein. Subsequently, ORA47 transcriptional activity was confirmed using the RSRE-driven luciferase (LUC) activity assay performed in the ORA47 loss-and gain-of-function lines introgressed into the 4xRSRE::Luc background. In addition, the prime contribution of CALMODULIN-BINDING TRANSCRIPTIONAL ACTIVA-TOR3 (CAMTA3) protein in the induction of RSRE was reaffirmed by genetic studies. Moreover, exogenous application of methyl jasmonate led to enhanced levels of ORA47 and CAMTA3 transcripts, as well as the induction of RSRE::LUC activity. Metabolic analyses illustrated the reciprocal functional inputs of ORA47 and CAMTA3 in increasing JA levels. Lastly, transient assays identified JASMONATE ZIM-domain1 (JAZ1) as a repressor of RSRE::LUC activity. Collectively, the present study provides fresh insight into the initial features of the mechanism that transduces informational signals into adaptive responses. This mechanism involves the functional interplay between the JA biosynthesis/signaling cascade and the transcriptional reprogramming that potentiates GSR. Furthermore, these findings offer a window into the role of intraorganellar communication in the establishment of adaptive responses.

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“…In plants, synthetic promoters introduced either stably or instantly are valuable for identifying functional regulatory elements and the transcription factors that govern the amplitude, spatial distribution, and temporal pattern of gene expression [ 11 ]. The sequence function of promoter elements has been studied in plants by fusing promoter fragments with reporter genes, such as CAT (chloramphenicol acetyltransferase) or GUS (glucuronidase) [ 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

Expression Activity of Artificial Promoters for Disease Resistance in Transgenic Eucalyptus urophylla

Huang

Fang

et al. 2022

Genes

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The transcriptional properties of artificial promoters are closely related to the type and arrangement position of cis-elements. GWSF (374-bp) was an effective SPIP with four cis-element dimers. There were four pathogen-inducible cis-elements in the GWSF promoter (GST1-boxes, W-boxes, S-boxes, and F-boxes) and a minimal cauliflower mosaic virus 35S promoter. V-element dimers were inserted into the upstream (VGWSF), midstream (GWVSF), and downstream (GWSFV) regions of the original GWSF promoter sequence to examine their affect on the position. The expression activity of promoters was analyzed and estimated using the histochemical staining of leaf discs of eucalyptus with transient expression, an image digitization method to extract the color features, and the induction treatment by a plant pathogenic microorganism/inducer and qPCR assays. The histochemical staining results of the adventitious buds indicated that the promoters had been successfully integrated into the E.urophylla genome and that they drove the expression of the gus gene. There was a noticeable difference in the intensity of color between the adventitious buds on the same callus block, as well as the intensity of color within the same adventitious bud. According to the established two-factor model of blue value, there was a greater difference between the levels of the genotype factor than the promoter factor in eucalyptus leaf discs. Further, the basal and inducible transcriptional levels of the three improved promoters were investigated by qPCR. With the basal transcriptional level of the GWSF promoter normalized to one, the relative basal levels of VGWSF, GWVSF, and GWSFV were 1.40, 1.45, and 4.15, respectively. The qPCR results were consistent with the staining results of GUS histochemical staining. The three improved promoters all had the properties of being induced by salicylic acid, Ralstonia solanacearum, and Phytophthora capsici. The three improved promoters demonstrated a significantly higher TMV induction activity: their induction activity from high to low was GWSFV > GWVSF > VGWSF. The findings will be beneficial to the construction and optimization of artificial promoters for transgenic plants.

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Quantitative Analysis of Cis-Regulatory Element Activity Using Synthetic Promoters in Transgenic Plants

Cited by 4 publications

References 33 publications

Building Transcription Factor Binding Site Models to Understand Gene Regulation in Plants

Building Transcription Factor Binding Site Models to Understand Gene Regulation in Plants

ORA47 is a transcriptional regulator of a general stress response hub

Expression Activity of Artificial Promoters for Disease Resistance in Transgenic Eucalyptus urophylla

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