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Asymmetric Regulation of Peripheral Genes by Two Transcriptional Regulatory Networks.

ABSTRACT: Transcriptional regulatory network (TRN) reconstitution and deconstruction occur simultaneously during reprogramming; however, it remains unclear how the starting and targeting TRNs regulate the induction and suppression of peripheral genes. Here we analyzed the regulation using direct cell reprogramming from human dermal fibroblasts to monocytes as the platform. We simultaneously deconstructed fibroblastic TRN and reconstituted monocytic TRN; monocytic and fibroblastic gene expression were analyzed in comparison with that of fibroblastic TRN deconstruction only or monocytic TRN reconstitution only. Global gene expression analysis showed cross-regulation of TRNs. Detailed analysis revealed that knocking down fibroblastic TRN positively affected half of the upregulated monocytic genes, indicating that intrinsic fibroblastic TRN interfered with the expression of induced genes. In contrast, reconstitution of monocytic TRN showed neutral effects on the majority of fibroblastic gene downregulation. This study provides an explicit example that demonstrates how two networks together regulate gene expression during cell reprogramming processes and contributes to the elaborate exploration of TRNs.

SUBMITTER: Li JR

PROVIDER: S-EPMC4970704 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Asymmetric Regulation of Peripheral Genes by Two Transcriptional Regulatory Networks.

Li Jing-Ru JR Suzuki Takahiro T Nishimura Hajime H Kishima Mami M Maeda Shiori S Suzuki Harukazu H

PloS one 20160802 8

Transcriptional regulatory network (TRN) reconstitution and deconstruction occur simultaneously during reprogramming; however, it remains unclear how the starting and targeting TRNs regulate the induction and suppression of peripheral genes. Here we analyzed the regulation using direct cell reprogramming from human dermal fibroblasts to monocytes as the platform. We simultaneously deconstructed fibroblastic TRN and reconstituted monocytic TRN; monocytic and fibroblastic gene expression were anal ...[more]

PMID: 27483142

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Project description:BACKGROUND:Transcription factors (TFs) are proteins that can bind to DNA sequences and regulate gene expression. Many TFs are master regulators in cells that contribute to tissue-specific and cell-type-specific gene expression patterns in eukaryotes. Maize has been a model organism for over one hundred years, but little is known about its tissue-specific gene regulation through TFs. In this study, we used a network approach to elucidate gene regulatory networks (GRNs) in four tissues (leaf, root, SAM and seed) in maize. We utilized GENIE3, a machine-learning algorithm combined with large quantity of RNA-Seq expression data to construct four tissue-specific GRNs. Unlike some other techniques, this approach is not limited by high-quality Position Weighed Matrix (PWM), and can therefore predict GRNs for over 2000 TFs in maize. RESULTS:Although many TFs were expressed across multiple tissues, a multi-tiered analysis predicted tissue-specific regulatory functions for many transcription factors. Some well-studied TFs emerged within the four tissue-specific GRNs, and the GRN predictions matched expectations based upon published results for many of these examples. Our GRNs were also validated by ChIP-Seq datasets (KN1, FEA4 and O2). Key TFs were identified for each tissue and matched expectations for key regulators in each tissue, including GO enrichment and identity with known regulatory factors for that tissue. We also found functional modules in each network by clustering analysis with the MCL algorithm. CONCLUSIONS:By combining publicly available genome-wide expression data and network analysis, we can uncover GRNs at tissue-level resolution in maize. Since ChIP-Seq and PWMs are still limited in several model organisms, our study provides a uniform platform that can be adapted to any species with genome-wide expression data to construct GRNs. We also present a publicly available database, maize tissue-specific GRN (mGRN, https://www.bio.fsu.edu/mcginnislab/mgrn/ ), for easy querying. All source code and data are available at Github ( https://github.com/timedreamer/maize_tissue-specific_GRN ).

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.

Dataset Information

Asymmetric Regulation of Peripheral Genes by Two Transcriptional Regulatory Networks.

Publications

Asymmetric Regulation of Peripheral Genes by Two Transcriptional Regulatory Networks.

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