scholarly journals Comparative transcriptome analysis of cells from different areas reveals ROS responsive mechanism at sclerotial initiation stage in Morchella importuna

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qizheng Liu ◽  
Guoqiang He ◽  
Jinkang Wei ◽  
Caihong Dong
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Target Genes ◽  
Comparative Transcriptome ◽  
Medicinal Mushrooms ◽  
Metabolic Characteristics ◽  
Transcription Process ◽  
Sclerotial Formation ◽  
Initiation Stage ◽  
Scientific Value

AbstractMorels are some of the most highly prized edible and medicinal mushrooms, with great economic and scientific value. Outdoor cultivation has been achieved and expanded on a large scale in China in recent years. Sclerotial formation is one of the most important phases during the morel life cycle, and previous reports indicated that reactive oxygen species (ROS) play an important role. However, ROS response mechanisms at sclerotial initiation (SI) stage are poorly understood. In this study, comparative transcriptome analyses were performed with sclerotial and hyphal cells at different areas in the same plate at SI stage. Gene expression was significantly different at SI stage between sclerotial formation and mycelia growth areas. GO and KEGG analyses indicated more vigorous metabolic characteristics in the hyphae area, while transcription process, DNA repair, and protein processing were enriched in sclerotial cells. Gene expression related to H2O2 production was high in the hyphae area, while expression of H2O2-scavenging genes was high in sclerotial cells, leading to a higher H2O2 concentration in the hyphal region than in the sclerotium. Minor differences were observed in gene expression of H2O2-induced signaling pathway in sclerotial and hyphal cells; however, expression levels of the target genes of transcription factor MSN2, important in the H2O2-induced signaling pathways, were significantly different. MSN2 enhanced stress response regulation in sclerotia by regulating these target genes. Small molecular HSPs were also found upregulated in sclerotial cells. This study indicated that sclerotial cells are more resistant to ROS stress than hyphal cells through transcriptional regulation of related genes.

scholarly journals Inferring TF activities and activity regulators from gene expression data with constraints from TF perturbation data

2020 ◽  
Author(s):  
Cynthia Ma ◽  
Michael R. Brent
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Large Scale ◽  
Target Genes ◽  
Activity Levels ◽  
Expression Data ◽  
Performance Constraints ◽  
Perturbation Data ◽  
Carry Over ◽  
Insight Into

ABSTRACTBackgroundThe activity of a transcription factor (TF) in a sample of cells is the extent to which it is exerting its regulatory potential. Many methods of inferring TF activity from gene expression data have been described, but due to the lack of appropriate large-scale datasets, systematic and objective validation has not been possible until now.ResultsUsing a new dataset, we systematically evaluate and optimize the approach to TF activity inference in which a gene expression matrix is factored into a condition-independent matrix of control strengths and a condition-dependent matrix of TF activity levels. These approaches require a TF network map, which specifies the target genes of each TF, as input. We evaluate different approaches to building the network map and deriving constraints on the matrices. We find that such constraints are essential for good performance. Constraints can be obtained from expression data in which the activities of individual TFs have been perturbed, and we find that such data are both necessary and sufficient for obtaining good performance. Remaining uncertainty about whether a TF activates or represses a target is a major source of error. To a considerable extent, control strengths inferred using expression data from one growth condition carry over to other conditions. As a result, the control strength matrices derived here can be used for other applications. Finally, we apply these methods to gain insight into the upstream factors that regulate the activities of four yeast TFs: Gcr2, Gln3, Gcn4, and Msn2. Evaluation code and data available at https://github.com/BrentLab/TFA-evaluationConclusionsWhen a high-quality network map, constraints, and perturbation-response data are available, inferring TF activity levels by factoring gene expression matrices is effective. Furthermore, it provides insight into regulators of TF activity.

scholarly journals Multiple transcription factors co-regulate the Mycobacterium tuberculosis adaptation response to vitamin C

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Malobi Nandi ◽  
Kriti Sikri ◽  
Neha Chaudhary ◽  
Shekhar Chintamani Mande ◽  
Ravi Datta Sharma ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Mycobacterium Tuberculosis ◽  
Vitamin C ◽  
Large Scale ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Transcriptional Regulators ◽  
Transcriptional Regulatory ◽  
Modulation Of Gene Expression

Abstract Background Latent tuberculosis infection is attributed in part to the existence of Mycobacterium tuberculosis in a persistent non-replicating dormant state that is associated with tolerance to host defence mechanisms and antibiotics. We have recently reported that vitamin C treatment of M. tuberculosis triggers the rapid development of bacterial dormancy. Temporal genome-wide transcriptome analysis has revealed that vitamin C-induced dormancy is associated with a large-scale modulation of gene expression in M. tuberculosis. Results An updated transcriptional regulatory network of M.tuberculosis (Mtb-TRN) consisting of 178 regulators and 3432 target genes was constructed. The temporal transcriptome data generated in response to vitamin C was overlaid on the Mtb-TRN (vitamin C Mtb-TRN) to derive insights into the transcriptional regulatory features in vitamin C-adapted bacteria. Statistical analysis using Fisher’s exact test predicted that 56 regulators play a central role in modulating genes which are involved in growth, respiration, metabolism and repair functions. Rv0348, DevR, MprA and RegX3 participate in a core temporal regulatory response during 0.25 h to 8 h of vitamin C treatment. Temporal network analysis further revealed Rv0348 to be the most prominent hub regulator with maximum interactions in the vitamin C Mtb-TRN. Experimental analysis revealed that Rv0348 and DevR proteins interact with each other, and this interaction results in an enhanced binding of DevR to its target promoter. These findings, together with the enhanced expression of devR and Rv0348 transcriptional regulators, indicate a second-level regulation of target genes through transcription factor- transcription factor interactions. Conclusions Temporal regulatory analysis of the vitamin C Mtb-TRN revealed that there is involvement of multiple regulators during bacterial adaptation to dormancy. Our findings suggest that Rv0348 is a prominent hub regulator in the vitamin C model and large-scale modulation of gene expression is achieved through interactions of Rv0348 with other transcriptional regulators.

scholarly journals Mining influential genes based on deep learning

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Lingpeng Kong ◽  
Yuanyuan Chen ◽  
Fengjiao Xu ◽  
Mingmin Xu ◽  
Zutan Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Deep Learning ◽  
Expression Profiling ◽  
Large Scale ◽  
Target Genes ◽  
Expression Profiles ◽  
Pearson Correlation ◽  
Genomic Information ◽  
Deep Mine ◽  
Functional Connections

Abstract Background Currently, large-scale gene expression profiling has been successfully applied to the discovery of functional connections among diseases, genetic perturbation, and drug action. To address the cost of an ever-expanding gene expression profile, a new, low-cost, high-throughput reduced representation expression profiling method called L1000 was proposed, with which one million profiles were produced. Although a set of ~ 1000 carefully chosen landmark genes that can capture ~ 80% of information from the whole genome has been identified for use in L1000, the robustness of using these landmark genes to infer target genes is not satisfactory. Therefore, more efficient computational methods are still needed to deep mine the influential genes in the genome. Results Here, we propose a computational framework based on deep learning to mine a subset of genes that can cover more genomic information. Specifically, an AutoEncoder framework is first constructed to learn the non-linear relationship between genes, and then DeepLIFT is applied to calculate gene importance scores. Using this data-driven approach, we have re-obtained a landmark gene set. The result shows that our landmark genes can predict target genes more accurately and robustly than that of L1000 based on two metrics [mean absolute error (MAE) and Pearson correlation coefficient (PCC)]. This reveals that the landmark genes detected by our method contain more genomic information. Conclusions We believe that our proposed framework is very suitable for the analysis of biological big data to reveal the mysteries of life. Furthermore, the landmark genes inferred from this study can be used for the explosive amplification of gene expression profiles to facilitate research into functional connections.

scholarly journals Ten-Eleven Translocation 1 (Tet1) Is Regulated by O-Linked N-Acetylglucosamine Transferase (Ogt) for Target Gene Repression in Mouse Embryonic Stem Cells

2013 ◽  
Vol 288 (29) ◽  
pp. 20776-20784 ◽  
Author(s):  
Feng-Tao Shi ◽  
Hyeung Kim ◽  
Weisi Lu ◽  
Quanyuan He ◽  
Dan Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Target Genes ◽  
Es Cells ◽  
Ectopic Expression ◽  
Embryonic Stem ◽  
Dna Demethylation ◽  
Mouse Es Cells ◽  
Chromatin Regulators ◽  
Glcnac Transferase

As a member of the Tet (Ten-eleven translocation) family proteins that can convert 5-methylcytosine (5mC) to 5-hydroxylmethylcytosine (5hmC), Tet1 has been implicated in regulating global DNA demethylation and gene expression. Tet1 is highly expressed in embryonic stem (ES) cells and appears primarily to repress developmental genes for maintaining pluripotency. To understand how Tet1 may regulate gene expression, we conducted large scale immunoprecipitation followed by mass spectrometry of endogenous Tet1 in mouse ES cells. We found that Tet1 could interact with multiple chromatin regulators, including Sin3A and NuRD complexes. In addition, we showed that Tet1 could also interact with the O-GlcNAc transferase (Ogt) and be O-GlcNAcylated. Depletion of Ogt led to reduced Tet1 and 5hmC levels on Tet1-target genes, whereas ectopic expression of wild-type but not enzymatically inactive Ogt increased Tet1 levels. Mutation of the putative O-GlcNAcylation site on Tet1 led to decreased O-GlcNAcylation and level of the Tet1 protein. Our results suggest that O-GlcNAcylation can positively regulate Tet1 protein concentration and indicate that Tet1-mediated 5hmC modification and target repression is controlled by Ogt.

scholarly journals Differential activation of P-TEFb complexes in the development of cardiomyocyte hypertrophy following activation of distinct GPCRs

2020 ◽  
Author(s):  
Ryan D. Martin ◽  
Yalin Sun ◽  
Sarah MacKinnon ◽  
Luca Cuccia ◽  
Viviane Pagé ◽  
...  
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Target Genes ◽  
Elongation Factor ◽  
Neonatal Rat ◽  
Cardiomyocyte Hypertrophy ◽  
Rat Cardiomyocytes ◽  
Hypertrophic Response ◽  
Specific Regulation ◽  
Brd4 Inhibition

AbstractPathological cardiac hypertrophy is driven by neurohormonal activation of specific G protein-coupled receptors (GPCRs) in cardiomyocytes and is accompanied by large-scale changes in cardiomyocyte gene expression. These transcriptional changes require activity of positive transcription elongation factor b (P-TEFb), which is recruited to target genes by the bromodomain protein Brd4 or the Super Elongation Complex (SEC). Here we describe GPCR-specific regulation of these P-TEFb complexes and a novel mechanism for activating Brd4 in primary neonatal rat cardiomyocytes. The SEC was required for the hypertrophic response downstream of either the α1-adrenergic receptor (α1-AR) or the endothelin receptor (ETR). In contrast, Brd4 inhibition selectively impaired the α1-AR response. This was corroborated by the finding that activation of α1-AR, but not ETR, increased Brd4 occupancy at promoters and super enhancers of hypertrophic genes. Transcriptome analysis demonstrated that activation of both receptors initiated similar gene expression programs, but that Brd4 inhibition attenuated hypertrophic genes more robustly following α1-AR activation. Finally, we show that protein kinase A (PKA) is required for α1-AR stimulation of Brd4 chromatin occupancy. The differential role of the Brd4/P-TEFb complex in response to distinct GPCR pathways has potential clinical implications as therapies targeting this complex are currently being explored for heart failure.

scholarly journals Differential Activation of P-TEFb Complexes in the Development of Cardiomyocyte Hypertrophy following Activation of Distinct G Protein-Coupled Receptors

2020 ◽  
Vol 40 (14) ◽  
Author(s):  
Ryan D. Martin ◽  
Yalin Sun ◽  
Sarah MacKinnon ◽  
Luca Cuccia ◽  
Viviane Pagé ◽  
...  
Keyword(s):  
Gene Expression ◽  
G Protein ◽  
Large Scale ◽  
Target Genes ◽  
G Protein Coupled Receptors ◽  
Neonatal Rat ◽  
Cardiomyocyte Hypertrophy ◽  
Rat Cardiomyocytes ◽  
Brd4 Inhibition ◽  
G Protein Coupled

ABSTRACT Pathological cardiac hypertrophy is driven by neurohormonal activation of specific G protein-coupled receptors (GPCRs) in cardiomyocytes and is accompanied by large-scale changes in cardiomyocyte gene expression. These transcriptional changes require activity of positive transcription elongation factor b (P-TEFb), which is recruited to target genes by the bromodomain protein Brd4 or the super elongation complex (SEC). Here, we describe GPCR-specific regulation of these P-TEFb complexes and a novel mechanism for activating Brd4 in primary neonatal rat cardiomyocytes. The SEC was required for the hypertrophic response downstream of either the α1-adrenergic receptor (α1-AR) or the endothelin receptor (ETR). In contrast, Brd4 inhibition selectively impaired the α1-AR response. This was corroborated by the finding that the activation of α1-AR, but not ETR, increased Brd4 occupancy at promoters and superenhancers of hypertrophic genes. Transcriptome analysis demonstrated that the activation of both receptors initiated similar gene expression programs, but that Brd4 inhibition attenuated hypertrophic genes more robustly following α1-AR activation. Finally, we show that protein kinase A (PKA) is required for α1-AR stimulation of Brd4 chromatin occupancy. The differential role of the Brd4/P-TEFb complex in response to distinct GPCR pathways has potential clinical implications, as therapies targeting this complex are currently being explored for heart failure.

scholarly journals Histone H3.3 regulates mitotic progression in mouse embryonic fibroblasts

2017 ◽  
Vol 95 (4) ◽  
pp. 491-499 ◽  
Author(s):  
Aysegul Ors ◽  
Christophe Papin ◽  
Bertrand Favier ◽  
Yohan Roulland ◽  
Defne Dalkara ◽  
...  
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Target Genes ◽  
Global Gene Expression ◽  
Histone Variant ◽  
Mitotic Progression ◽  
Mouse Embryonic Fibroblasts ◽  
Embryonic Fibroblasts ◽  
Transcription Start Sites ◽  
Short Hairpin Rnas

H3.3 is a histone variant that marks transcription start sites as well as telomeres and heterochromatic sites on the genome. The presence of H3.3 is thought to positively correlate with the transcriptional status of its target genes. Using a conditional genetic strategy against H3.3B, combined with short hairpin RNAs against H3.3A, we essentially depleted all H3.3 gene expression in mouse embryonic fibroblasts. Following nearly complete loss of H3.3 in the cells, our transcriptomic analyses show very little impact on global gene expression or on the localization of histone variant H2A.Z. Instead, fibroblasts displayed slower cell growth and an increase in cell death, coincident with large-scale chromosome misalignment in mitosis and large polylobed or micronuclei in interphase cells. Thus, we conclude that H3.3 may have an important under-explored additional role in chromosome segregation, nuclear structure, and the maintenance of genome integrity.

scholarly journals ChIP-BIT2: a software tool to detect weak binding events using a Bayesian integration approach

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xi Chen ◽  
Xu Shi ◽  
Andrew F. Neuwald ◽  
Leena Hilakivi-Clarke ◽  
Robert Clarke ◽  
...  
Keyword(s):  
Gene Expression ◽  
Binding Sites ◽  
Large Scale ◽  
Target Genes ◽  
Gene Expression Regulation ◽  
Software Tool ◽  
Gene Promoters ◽  
Weak Binding ◽  
Genomic Locations ◽  
And Control

Abstract Background ChIP-seq combines chromatin immunoprecipitation assays with sequencing and identifies genome-wide binding sites for DNA binding proteins. While many binding sites have strong ChIP-seq ‘peak’ observations and are well captured, there are still regions bound by proteins weakly, with a relatively low ChIP-seq signal enrichment. These weak binding sites, especially those at promoters and enhancers, are functionally important because they also regulate nearby gene expression. Yet, it remains a challenge to accurately identify weak binding sites in ChIP-seq data due to the ambiguity in differentiating these weak binding sites from the amplified background DNAs. Results ChIP-BIT2 (http://sourceforge.net/projects/chipbitc/) is a software package for ChIP-seq peak detection. ChIP-BIT2 employs a mixture model integrating protein and control ChIP-seq data and predicts strong or weak protein binding sites at promoters, enhancers, or other genomic locations. For binding sites at gene promoters, ChIP-BIT2 simultaneously predicts their target genes. ChIP-BIT2 has been validated on benchmark regions and tested using large-scale ENCODE ChIP-seq data, demonstrating its high accuracy and wide applicability. Conclusion ChIP-BIT2 is an efficient ChIP-seq peak caller. It provides a better lens to examine weak binding sites and can refine or extend the existing binding site collection, providing additional regulatory regions for decoding the mechanism of gene expression regulation.

scholarly journals Overexpression of Hoxc13 in differentiating keratinocytes results in downregulation of a novel hair keratin gene cluster and alopecia

Development ◽  
2001 ◽  
Vol 128 (9) ◽  
pp. 1547-1558
Author(s):  
A.V. Tkatchenko ◽  
R.P. Visconti ◽  
L. Shang ◽  
T. Papenbrock ◽  
N.D. Pruett ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Cluster ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Hox Genes ◽  
Skin Condition ◽  
Hair Follicles ◽  
Keratin Gene ◽  
Downstream Target

Studying the roles of Hox genes in normal and pathological development of skin and hair requires identification of downstream target genes in genetically defined animal models. We show that transgenic mice overexpressing Hoxc13 in differentiating keratinocytes of hair follicles develop alopecia, accompanied by a progressive pathological skin condition that resembles ichthyosis. Large-scale analysis of differential gene expression in postnatal skin of these mice identified 16 previously unknown and 13 known genes as presumptive Hoxc13 targets. The majority of these targets are downregulated and belong to a subgroup of genes that encode hair-specific keratin-associated proteins (KAPs). Genomic mapping using a mouse hamster radiation hybrid panel showed these genes to reside in a novel KAP gene cluster on mouse chromosome 16 in a region of conserved linkage with human chromosome 21q22.11. Furthermore, data obtained by Hoxc13/lacZ reporter gene analysis in mice that overexpress Hoxc13 suggest negative autoregulatory feedback control of Hoxc13 expression levels, thus providing an entry point for elucidating currently unknown mechanisms that are required for regulating quantitative levels of Hox gene expression. Combined, these results provide a framework for understanding molecular mechanisms of Hoxc13 function in hair growth and development.

scholarly journals Long-range promoter-enhancer contacts are conserved during evolution and contribute to gene expression robustness

2021 ◽  
Author(s):  
Alexandre Laverré ◽  
Eric Tannier ◽  
Anamaria Necsulea
Keyword(s):  
Gene Expression ◽  
Long Range ◽  
Large Scale ◽  
Target Genes ◽  
Expression Profiles ◽  
Regulatory Element ◽  
Gene Expression Profiles ◽  
Evolutionary Conservation ◽  
Regulatory Elements ◽  
Regulatory Landscapes

AbstractGene expression is regulated through complex molecular interactions, involving cis-acting elements that can be situated far away from their target genes. Data on long-range contacts between promoters and regulatory elements is rapidly accumulating. However, it remains unclear how these regulatory relationships evolve and how they contribute to the establishment of robust gene expression profiles. Here, we address these questions by comparing genome-wide maps of promoter-centered chromatin contacts in mouse and human. We show that there is significant evolutionary conservation of cis-regulatory landscapes, indicating that selective pressures act to preserve regulatory element sequences and their interactions with target genes. The extent of evolutionary conservation is remarkable for long-range promoter-enhancer contacts, illustrating how the structure of regulatory interactions constrains large-scale genome evolution. Notably, we show that the evolution of cis-regulatory landscapes, measured in terms of distal element sequences, synteny or contacts with target genes, is tightly linked to gene expression evolution.

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