Dataset Information

Identification of transcriptional regulatory nodes in soybean defense networks using transient co-transactivation assays.

ABSTRACT: Plant responses to major environmental stressors, such as insect feeding, not only occur via the functions of defense genes but also involve a series of regulatory factors. Our previous transcriptome studies proposed that, in addition to two defense-related genes, GmVSP? and GmN:IFR, a high proportion of transcription factors (TFs) participate in the incompatible soybean-common cutworm interaction networks. However, the regulatory mechanisms and effects of these TFs on those induced defense-related genes remain unknown. In the present work, we isolated and identified 12 genes encoding MYB, WRKY, NAC, bZIP, and DREB TFs from a common cutworm-induced cDNA library of a resistant soybean line. Sequence analysis of the promoters of three co-expressed genes, including GmVSP?, GmVSP?, and GmN:IFR, revealed the enrichment of various TF-binding sites for defense and stress responses. To further identify the regulatory nodes composed of these TFs and defense gene promoters, we performed extensive transient co-transactivation assays to directly test the transcriptional activity of the 12 TFs binding at different levels to the three co-expressed gene promoters. The results showed that all 12 TFs were able to transactivate the GmVSP? and GmN:IFR promoters. GmbZIP110 and GmMYB75 functioned as distinct regulators of GmVSP?/? and GmN:IFR expression, respectively, while GmWRKY39 acted as a common central regulator of GmVSP?/? and GmN:IFR expression. These corresponding TFs play crucial roles in coordinated plant defense regulation, which provides valuable information for understanding the molecular mechanisms involved in insect-induced transcriptional regulation in soybean. More importantly, the identified TFs and suitable promoters can be used to engineer insect-resistant plants in molecular breeding studies.

SUBMITTER: Wang Y

PROVIDER: S-EPMC4621403 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Identification of transcriptional regulatory nodes in soybean defense networks using transient co-transactivation assays.

Wang Yongli Y Wang Hui H Ma Yujie Y Du Haiping H Yang Qing Q Yu Deyue D

Frontiers in plant science 20151027

Plant responses to major environmental stressors, such as insect feeding, not only occur via the functions of defense genes but also involve a series of regulatory factors. Our previous transcriptome studies proposed that, in addition to two defense-related genes, GmVSPβ and GmN:IFR, a high proportion of transcription factors (TFs) participate in the incompatible soybean-common cutworm interaction networks. However, the regulatory mechanisms and effects of these TFs on those induced defense-rela ...[more]

PMID: 26579162

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Project description:Current experimental evidence indicates that functionally related genes show coordinated expression in order to perform their cellular functions. In this way, the cell transcriptional machinery can respond optimally to internal or external stimuli. This provides a research opportunity to identify and study co-expressed gene modules whose transcription is controlled by shared gene regulatory networks.We developed and integrated a set of computational methods of differential gene expression analysis, gene clustering, gene network inference, gene function prediction, and DNA motif identification to automatically identify differentially co-expressed gene modules, reconstruct their regulatory networks, and validate their correctness. We tested the methods using microarray data derived from soybean cells grown under various stress conditions. Our methods were able to identify 42 coherent gene modules within which average gene expression correlation coefficients are greater than 0.8 and reconstruct their putative regulatory networks. A total of 32 modules and their regulatory networks were further validated by the coherence of predicted gene functions and the consistency of putative transcription factor binding motifs. Approximately half of the 32 modules were partially supported by the literature, which demonstrates that the bioinformatic methods used can help elucidate the molecular responses of soybean cells upon various environmental stresses.The bioinformatics methods and genome-wide data sources for gene expression, clustering, regulation, and function analysis were integrated seamlessly into one modular protocol to systematically analyze and infer modules and networks from only differential expression genes in soybean cells grown under stress conditions. Our approach appears to effectively reduce the complexity of the problem, and is sufficiently robust and accurate to generate a rather complete and detailed view of putative soybean gene transcription logic potentially underlying the responses to the various environmental challenges. The same automated method can also be applied to reconstruct differentially co-expressed gene modules and their regulatory networks from gene expression data of any other transcriptome.

Project description:Organisms regulate gene expression in response to the environment to coordinate metabolic reactions. Clostridium thermocellum expresses enzymes for both lignocellulose solubilization and its fermentation to produce ethanol. One LacI regulator termed GlyR3 in C. thermocellum ATCC 27405 was previously identified as a repressor of neighboring genes with repression relieved by laminaribiose (a ?-1,3 disaccharide). To better understand the three C. thermocellum LacI regulons, deletion mutants were constructed using the genetically tractable DSM1313 strain. DSM1313 lacI genes Clo1313_2023, Clo1313_0089, and Clo1313_0396 encode homologs of GlyR1, GlyR2, and GlyR3 from strain ATCC 27405, respectively. Growth on cellobiose or pretreated switchgrass was unaffected by any of the gene deletions under controlled-pH fermentations. Global gene expression patterns from time course analyses identified glycoside hydrolase genes encoding hemicellulases, including cellulosomal enzymes, that were highly upregulated (5- to 100-fold) in the absence of each LacI regulator, suggesting that these were repressed under wild-type conditions and that relatively few genes were controlled by each regulator under the conditions tested. Clo1313_2022, encoding lichenase enzyme LicB, was derepressed in a ?glyR1 strain. Higher expression of Clo1313_1398, which encodes the Man5A mannanase, was observed in a ?glyR2 strain, and ?-mannobiose was identified as a probable inducer for GlyR2-regulated genes. For the ?glyR3 strain, upregulation of the two genes adjacent to glyR3 in the celC-glyR3-licA operon was consistent with earlier studies. Electrophoretic mobility shift assays have confirmed LacI transcription factor binding to specific regions of gene promoters.IMPORTANCE Understanding C. thermocellum gene regulation is of importance for improved fundamental knowledge of this industrially relevant bacterium. Most LacI transcription factors regulate local genomic regions; however, a small number of those genes encode global regulatory proteins with extensive regulons. This study indicates that there are small specific C. thermocellum LacI regulons. The identification of LacI repressor activity for hemicellulase gene expression is a key result of this work and will add to the small body of existing literature on the area of gene regulation in C. thermocellum.

Project description:BackgroundComparative genomics methods enable the reconstruction of bacterial regulatory networks using available experimental data. In spite of their potential for accelerating research into the composition and evolution of bacterial regulons, few comparative genomics suites have been developed for the automated analysis of these regulatory systems. Available solutions typically rely on precomputed databases for operon and ortholog predictions, limiting the scope of analyses to processed complete genomes, and several key issues such as the transfer of experimental information or the integration of regulatory information in a probabilistic setting remain largely unaddressed.ResultsHere we introduce CGB, a flexible platform for comparative genomics of prokaryotic regulons. CGB has few external dependencies and enables fully customized analyses of newly available genome data. The platform automates the merging of experimental information and uses a gene-centered, Bayesian framework to generate and integrate easily interpretable results. We demonstrate its flexibility and power by analyzing the evolution of type III secretion system regulation in pathogenic Proteobacteria and by characterizing the SOS regulon of a new bacterial phylum, the Balneolaeota.ConclusionsOur results demonstrate the applicability of the CGB pipeline in multiple settings. CGB's ability to automatically integrate experimental information from multiple sources and use complete and draft genomic data, coupled with its non-reliance on precomputed databases and its easily interpretable display of gene-centered posterior probabilities of regulation provide users with an unprecedented level of flexibility in launching comparative genomics analyses of prokaryotic transcriptional regulatory networks. The analyses of type III secretion and SOS response regulatory networks illustrate instances of convergent and divergent evolution of these regulatory systems, showcasing the power of formal ancestral state reconstruction at inferring the evolutionary history of regulatory networks.

Dataset Information

Identification of transcriptional regulatory nodes in soybean defense networks using transient co-transactivation assays.

Publications

Identification of transcriptional regulatory nodes in soybean defense networks using transient co-transactivation assays.

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