scholarly journals RNA-seq and ChIP-seq as Complementary Approaches for Comprehension of Plant Transcriptional Regulatory Mechanism

2019 ◽  
Vol 21 (1) ◽  
pp. 167 ◽  
Author(s):  
Isiaka Ibrahim Muhammad ◽  
Sze Ling Kong ◽  
Siti Nor Akmar Abdullah ◽  
Umaiyal Munusamy
Keyword(s):  
Transcriptional Regulation ◽  
Regulatory Networks ◽  
Data Sets ◽  
Rna Seq ◽  
Transcriptional Regulatory Networks ◽  
Regulatory Pathways ◽  
Specific Biological Process ◽  
Transcriptional Regulatory ◽  
Chromatin Immunoprecipitation Sequencing ◽  
Sequencing Platforms

The availability of data produced from various sequencing platforms offer the possibility to answer complex questions in plant research. However, drawbacks can arise when there are gaps in the information generated, and complementary platforms are essential to obtain more comprehensive data sets relating to specific biological process, such as responses to environmental perturbations in plant systems. The investigation of transcriptional regulation raises different challenges, particularly in associating differentially expressed transcription factors with their downstream responsive genes. In this paper, we discuss the integration of transcriptional factor studies through RNA sequencing (RNA-seq) and Chromatin Immunoprecipitation sequencing (ChIP-seq). We show how the data from ChIP-seq can strengthen information generated from RNA-seq in elucidating gene regulatory mechanisms. In particular, we discuss how integration of ChIP-seq and RNA-seq data can help to unravel transcriptional regulatory networks. This review discusses recent advances in methods for studying transcriptional regulation using these two methods. It also provides guidelines for making choices in selecting specific protocols in RNA-seq pipelines for genome-wide analysis to achieve more detailed characterization of specific transcription regulatory pathways via ChIP-seq.

Transcriptional Control of Parturition: Insights from Gene Regulation Studies in the Myometrium

2021 ◽  
Author(s):  
Nawrah Khader ◽  
Virlana M Shchuka ◽  
Oksana Shynlova ◽  
Jennifer A Mitchell
Keyword(s):  
Transcription Factors ◽  
Regulatory Networks ◽  
Transcriptional Control ◽  
Progesterone Receptors ◽  
Activator Protein 1 ◽  
Transcriptional Regulatory Networks ◽  
Regulatory Pathways ◽  
Transcriptional Regulatory ◽  
Mechanistic Basis ◽  
Labour Onset

Abstract The onset of labour is a culmination of a series of highly coordinated and preparatory physiological events that take place throughout the gestational period. In order to produce the associated contractions needed for fetal delivery, smooth muscle cells in the muscular layer of the uterus (i.e. myometrium) undergo a transition from quiescent to contractile phenotypes. Here, we present the current understanding of the roles transcription factors play in critical labour-associated gene expression changes as part of the molecular mechanistic basis for this transition. Consideration is given to both transcription factors that have been well-studied in a myometrial context, i.e. activator protein 1 (AP-1), progesterone receptors (PRs), estrogen receptors (ERs), and nuclear factor kappa B (NF-κB), as well as additional transcription factors whose gestational event-driving contributions have been demonstrated more recently. These transcription factors may form pregnancy- and labour- associated transcriptional regulatory networks in the myometrium to modulate the timing of labour onset. A more thorough understanding of the transcription factor-mediated, labour-promoting regulatory pathways holds promise for the development of new therapeutic treatments that can be used for the prevention of preterm labour in at-risk women.

scholarly journals Identification of KLF6/PSGs and NPY-Related USF2/CEACAM Transcriptional Regulatory Networks via Spinal Cord Bulk and Single-Cell RNA-Seq Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Xinbing Liu ◽  
Wei Gao ◽  
Wei Liu
Keyword(s):  
Spinal Cord ◽  
Single Cell ◽  
Regulatory Networks ◽  
Single Cell Analysis ◽  
Transcriptional Regulatory Network ◽  
Transcriptional Regulator ◽  
Cell Analysis ◽  
Rna Seq ◽  
Transcriptional Regulatory Networks ◽  
Transcriptional Regulatory

Background. To further understand the development of the spinal cord, an exploration of the patterns and transcriptional features of spinal cord development in newborn mice at the cellular transcriptome level was carried out. Methods. The mouse single-cell sequencing (scRNA-seq) dataset was downloaded from the GSE108788 dataset. Single-cell RNA-Seq (scRNA-Seq) was conducted on cervical and lumbar spinal V2a interneurons from 2 P0 neonates. Single-cell analysis using the Seurat package was completed, and marker mRNAs were identified for each cluster. Then, pseudotemporal analysis was used to analyze the transcription changes of marker mRNAs in different clusters over time. Finally, the functions of these marker mRNAs were assessed by enrichment analysis and protein-protein interaction (PPI) networks. A transcriptional regulatory network was then constructed using the TRRUST dataset. Results. A total of 949 cells were screened. Single-cell analysis was conducted based on marker mRNAs of each cluster, which revealed the heterogeneity of neonatal mouse spinal cord neuronal cells. Functional analysis of pseudotemporal trajectory-related marker mRNAs suggested that pregnancy-specific glycoproteins (PSGs) and carcinoembryonic antigen cell adhesion molecules (CEACAMs) were the core mRNAs in cluster 3. GSVA analysis then demonstrated that the different clusters had differences in pathway activity. By constructing a transcriptional regulatory network, USF2 was identified to be a transcriptional regulator of CEACAM1 and CEACAM5, while KLF6 was identified to be a transcriptional regulator of PSG3 and PSG5. This conclusion was then validated using the Genotype-Tissue Expression (GTEx) spinal cord transcriptome dataset. Conclusions. This study completed an integrated analysis of a single-cell dataset with the utilization of marker mRNAs. USF2/CEACAM1&5 and KLF6/PSG3&5 transcriptional regulatory networks were identified by spinal cord single-cell analysis.

scholarly journals Analysis of next- and third-generation RNA-Seq data reveals the structures of alternative transcription units in bacterial genomes

2021 ◽  
Author(s):  
Qi Wang ◽  
Zhaoqian Liu ◽  
Bo Yan ◽  
Wen-Chi Chou ◽  
Laurence Ettwiller ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Programming Model ◽  
Third Generation ◽  
Rna Seq ◽  
Bacterial Genomes ◽  
Transcriptional Regulatory Networks ◽  
Computational Framework ◽  
Transcriptional Regulatory ◽  
Alternative Transcription ◽  
Genome Scale

ABSTRACTAlternative transcription units (ATUs) are dynamically encoded under different conditions or environmental stimuli in bacterial genomes, and genome-scale identification of ATUs is essential for studying the emergence of human diseases caused by bacterial organisms. However, it is unrealistic to identify all ATUs using experimental techniques, due to the complexity and dynamic nature of ATUs. Here we present the first-of-its-kind computational framework, named SeqATU, for genome-scale ATU prediction based on next-generation RNA-Seq data. The framework utilizes a convex quadratic programming model to seek an optimum expression combination of all of the to-be-identified ATUs. The predicted ATUs in E. coli reached a precision of 0.77/0.74 and a recall of 0.75/0.76 in the two RNA-Sequencing datasets compared with the benchmarked ATUs from third-generation RNA-Seq data. We believe that the ATUs identified by SeqATU can provide fundamental knowledge to guide the reconstruction of transcriptional regulatory networks in bacterial genomes.

scholarly journals Transcriptional regulatory networks mediated by abnormal m6A modifications in tumor development

2021 ◽  
Author(s):  
Wenzheng Qu ◽  
Xuekun Li
Keyword(s):  
Regulatory Networks ◽  
Tumor Development ◽  
Mapk Signaling ◽  
Rna Seq ◽  
Sequencing Data ◽  
Transcriptional Regulatory Networks ◽  
Transcriptional Regulatory ◽  
The Common ◽  
Related Proteins ◽  
Geo Database

Abstract Background N6-methyladenosine (m6A) is one of the common modifications of transcripts that is regulated by related proteins including writers, readers and erasers. Abnormal m6A modification plays an important role in the process of tumor development. Current approaches for tumor m6A RNA methylation, based on sequencing data from public databases, focus on the comparison of m6A modification regulator expression by RNA-seq data. Results We obtained MeRIP-seq and corresponding RNA-seq data from GEO database to compare and analyze the distributional characteristics of m6A in different types of tumor samples, the differences in m6A modification enrichment, and the regulatory role in gene transcriptional expression level. We found that the enrichment of m6A modification was enhanced in IMPA and GBM tumor samples, but was decreased in METTL3 knockdown tumor cells. Combined with clinical data from the TCGA database, we found that the high expression of DUSP7 significantly affected the overall survival of AML patients and was involved in tumor development through the PIK3R2 protein and MAPK signaling pathways. Conclusion Abnormal m6A modification enrichment in tumor samples leads to dysregulation in the expression of cancer-related genes.

scholarly journals Genome-wide binding analysis of the tomato transcription factor SlDof1 reveals its regulatory impacts on fruit ripening

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Yuying Wang ◽  
Peiwen Wang ◽  
Weihao Wang ◽  
Lingxi Kong ◽  
Shiping Tian ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Fruit Ripening ◽  
Regulatory Networks ◽  
Target Genes ◽  
Transcriptome Profiling ◽  
Flowering Plant ◽  
Transcriptional Regulatory Networks ◽  
Genome Wide ◽  
Transcriptional Regulatory ◽  
Chromatin Immunoprecipitation Sequencing

AbstractThe DNA binding with one finger (Dof) proteins are plant-specific transcription factors involved in a variety of biological processes. However, little is known about their functions in fruit ripening, a flowering-plant-specific process that is required for seed maturation and dispersal. Here, we found that the tomato Dof transcription factor SlDof1, is necessary for normal fruit ripening. Knockdown of SlDof1 expression by RNA interference delayed ripening-related processes, including lycopene synthesis and ethylene production. Transcriptome profiling indicated that SlDof1 influences the expression of hundreds of genes, and a chromatin immunoprecipitation sequencing revealed a large number of SlDof1 binding sites. A total of 312 genes were identified as direct targets of SlDof1, among which 162 were negatively regulated by SlDof1 and 150 were positively regulated. The SlDof1 target genes were involved in a variety of metabolic pathways, and follow-up analyses verified that SlDof1 directly regulates some well-known ripening-related genes including ACS2 and PG2A as well as transcriptional repressor genes such as SlIAA27. Our findings provide insights into the transcriptional regulatory networks underlying fruit ripening and highlight a gene potentially useful for genetic engineering to control ripening.

scholarly journals Plagl1 is part of the mammalian retinal injury response and a critical regulator of Müller glial cell quiescence

2021 ◽  
Author(s):  
Yacine Touahri ◽  
Luke Ajay David ◽  
Yaroslav Ilnytskyy ◽  
Edwin van Oosten ◽  
Joseph Hanna ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Visual Signal ◽  
Muller Glia ◽  
Müller Glia ◽  
Rna Seq ◽  
Transcriptional Regulatory Networks ◽  
Retinal Injury ◽  
Transcriptional Regulatory ◽  
Müller Glial Cell ◽  
Injury Models

ABSTRACTRetinal damage triggers reactive gliosis in Müller glia across vertebrate species, but only in regenerative animals, such as teleost fish, do Müller glia initiate repair; proliferating and undergoing neurogenesis to replace lost cells. By mining scRNA-seq and bulk RNA-seq datasets, we found that Plagl1, a maternally imprinted gene, is dynamically regulated in reactive Müller glia post-insult, with transcript levels transiently increasing before stably declining. To study Plagl1 retinal function, we examined Plagl1+/-pat null mutants postnatally, revealing defects in retinal architecture, visual signal processing and a reactive gliotic phenotype. Plagl1+/-pat Müller glia proliferate ectopically and give rise to inner retinal neurons and photoreceptors. Transcriptomic and ATAC-seq profiles revealed similarities between Plagl1+/-pat retinas and neurodegenerative and injury models, including an upregulation of pro-gliogenic and pro-proliferative pathways, such as Notch, not observed in wild-type retinas Plagl1 is thus an essential component of the transcriptional regulatory networks that retain mammalian Müller glia in quiescence.

Computational approaches to study transcriptional regulation

2008 ◽  
Vol 36 (4) ◽  
pp. 758-765 ◽  
Author(s):  
M. Madan Babu
Keyword(s):  
Transcriptional Regulation ◽  
Regulatory Networks ◽  
Regulatory Elements ◽  
Model Organisms ◽  
Emerging Pathogens ◽  
Transcriptional Regulatory Networks ◽  
Regulatory Interactions ◽  
Regulatory Circuits ◽  
Transcriptional Regulatory ◽  
The Individual

In recent years, a number of technical and experimental advances have allowed us to obtain an unprecedented amount of information about living systems on a genomic scale. Although the complete genomes of many organisms are available due to the progress made in sequencing technology, the challenge to understand how the individual genes are regulated within the cell remains. Here, I provide an overview of current computational methods to investigate transcriptional regulation. I will first discuss how representing protein–DNA interactions as a network provides us with a conceptual framework to understand the organization of regulatory interactions in an organism. I will then describe methods to predict transcription factors and cis-regulatory elements using information such as sequence, structure and evolutionary conservation. Finally, I will discuss approaches to infer genome-scale transcriptional regulatory networks using experimentally characterized interactions from model organisms and by reverse-engineering regulatory interactions that makes use of gene expression data and genomewide location data. The methods summarized here can be exploited to discover previously uncharacterized transcriptional pathways in organisms whose genome sequence is known. In addition, such a framework and approach can be invaluable to investigate transcriptional regulation in complex microbial communities such as the human gut flora or populations of emerging pathogens. Apart from these medical applications, the concepts and methods discussed can be used to understand the combinatorial logic of transcriptional regulation and can be exploited in biotechnological applications, such as in synthetic biology experiments aimed at engineering regulatory circuits for various purposes.

Controllability analysis of transcriptional regulatory networks reveals circular control patterns among transcription factors

2015 ◽  
Vol 7 (5) ◽  
pp. 560-568 ◽  
Author(s):  
Tobias Österlund ◽  
Sergio Bordel ◽  
Jens Nielsen
Keyword(s):  
Transcriptional Regulation ◽  
Transcription Factors ◽  
Regulatory Networks ◽  
Target Genes ◽  
Living Cells ◽  
Transcriptional Regulatory Networks ◽  
Transcriptional Regulatory ◽  
Control Patterns

Transcriptional regulation is the most committed type of regulation in living cells where transcription factors (TFs) control the expression of their target genes and TF expression is controlled by other TFs forming complex transcriptional regulatory networks that can be highly interconnected.

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