Identification and characterization of jasmonic acid- and linolenic acid-mediated transcriptional regulation of secondary laticifer differentiation in Hevea brasiliensis

Abstract Hevea brasiliensis remains the primary crop commercially exploited to obtain latex, which is produced from the articulated secondary laticifer. Here, we described the transcriptional events related to jasmonic acid (JA)- and linolenic acid (LA)-induced secondary laticifer differentiation (SLD) in H. brasiliensis clone RRIM 600 based on RNA-seq approach. Histochemical approach proved that JA- and LA-treated samples resulted in SLD in H. brasiliensis when compared to ethephon and untreated control. RNA-seq data resulted in 86,614 unigenes, of which 2,664 genes were differentially expressed in JA and LA-induced secondary laticifer harvested from H. brasiliensis bark samples. Among these, 450 genes were unique to JA and LA as they were not differentially expressed in ethephon-treated samples compared with the untreated samples. Most transcription factors from the JA- and LA-specific dataset were classified under MYB, APETALA2/ethylene response factor (AP2/ERF), and basic-helix-loop-helix (bHLH) gene families that were involved in tissue developmental pathways, and we proposed that Bel5-GA2 oxidase 1-KNOTTED-like homeobox complex are likely involved in JA- and LA-induced SLD in H. brasiliensis. We also discovered alternative spliced transcripts, putative novel transcripts, and cis-natural antisense transcript pairs related to SLD event. This study has advanced understanding on the transcriptional regulatory network of SLD in H. brasiliensis.

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Laticifer Differentiation in Hevea brasiliensis: Induction by Exogenous Jasmonic Acid and Linolenic Acid

Annals of Botany ◽

10.1006/anbo.1999.0995 ◽

2000 ◽

Vol 85 (1) ◽

pp. 37-43 ◽

Cited By ~ 101

Author(s):

B HAO

Keyword(s):

Jasmonic Acid ◽

Linolenic Acid ◽

Hevea Brasiliensis

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Distinct gene signatures predict insulin resistance in young mice with high fat diet-induced obesity

Physiological Genomics ◽

10.1152/physiolgenomics.00045.2017 ◽

2018 ◽

Vol 50 (3) ◽

pp. 144-157 ◽

Cited By ~ 7

Author(s):

Katherine Chen ◽

Alice Jih ◽

Olivia Osborn ◽

Sarah T. Kavaler ◽

Wenxian Fu ◽

...

Keyword(s):

Insulin Resistance ◽

High Fat Diet ◽

Expression Patterns ◽

Gene Families ◽

Differentially Expressed ◽

Rna Seq ◽

High Fat ◽

Diet Induced Obesity ◽

Before And After ◽

Young Mice

Highly inbred C57BL/6 mice show wide variation in their degree of insulin resistance in response to diet-induced obesity even though they are almost genetically identical. Here we employed transcriptional profiling by RNA sequencing (RNA-Seq) of visceral adipose tissue (VAT) and liver in young mice to determine how gene expression patterns correlate with the later development of high-fat diet (HFD)-induced insulin resistance in adulthood. To accomplish this goal, we partially removed and banked tissues from pubertal mice. Mice subsequently received HFD followed by metabolic phenotyping to identify two well-defined groups of mice with either severe or mild insulin resistance. The remaining tissues were collected at study termination. We then applied RNA-Seq to generate transcriptome profiles associated with worsened insulin resistance before and after the initiation of HFD. We found 244 up- and 109 downregulated genes in VAT of the most insulin-resistant mice even before HFD exposure. Downregulated genes included serine protease inhibitor, major urinary protein, and complement genes; upregulated genes represented mostly muscle constituents. These gene families were also differentially expressed in VAT of mice with high or low insulin resistance after HFD. Inflammatory genes predicted insulin resistance in liver, but not in VAT. In contrast, when we compared VAT of all mice before and after HFD, differentially expressed genes were predominantly composed of immune response genes. These data show a distinct set of gene transcripts in young mice correlates with the severity of insulin resistance in adulthood, providing insight into the pathogenesis of insulin resistance in early life.

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The polar flagellar transcriptional regulatory network in Vibrio campbellii deviates from canonical Vibrio species

10.1101/2021.05.10.443453 ◽

2021 ◽

Author(s):

Blake D Petersen ◽

Michael S Liu ◽

Ram Podicheti ◽

Albert Ying-Po Yang ◽

Chelsea A Simpson ◽

...

Keyword(s):

Regulatory Network ◽

Transcriptional Regulatory Network ◽

Vibrio Species ◽

Flagellar Motor ◽

Rna Seq ◽

Free Living ◽

Transcriptional Regulatory ◽

Host Mortality ◽

Vibrio Campbellii ◽

Fish And Shellfish

Vibrio campbellii is a Gram-negative bacterium that is free-living and ubiquitous in marine environments, and it is a pathogen of fish and shellfish. Swimming motility via a single polar flagellum is a critical virulence factor in V. campbellii pathogenesis, and disruption of the flagellar motor significantly decreases host mortality. To examine V. campbellii flagellar gene regulation, we identified homologs of flagellar and chemotaxis genes conserved in other members of the Vibrionaceae and determined the transcriptional profile of these loci using differential RNA-seq. We systematically deleted all 63 predicted flagellar and chemotaxis genes in V. campbellii and examined their effects on motility and flagellum production. We specifically focused on the core flagellar regulators of the flagellar regulatory hierarchy established in other Vibrios: RpoN (σ54), FlrA, FlrC, and FliA. Our results show that V. campbellii transcription of flagellar and chemotaxis genes is governed by a multi-tiered regulatory hierarchy similar to other motile Vibrio species but with two critical differences: the σ54-dependent regulator FlrA is dispensable for motility, and Class II gene expression is independent of σ54 regulation. Our genetic and phenotypic dissection of the V. campbellii flagellar regulatory network highlights the differences that have evolved in flagellar regulation across the Vibrionaceae.

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

Disease Markers ◽

10.1155/2021/2826609 ◽

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.

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Pan-genomic analysis of transcriptional modules across Salmonella Typhimurium reveals the regulatory landscape of different strains

10.1101/2022.01.11.475931 ◽

2022 ◽

Author(s):

Yuan Yuan ◽

Yara Seif ◽

Kevin Rychel ◽

Reo Yoo ◽

Siddharth M Chauhan ◽

...

Keyword(s):

Transcriptional Regulatory Network ◽

Genomic Analysis ◽

Rna Seq ◽

High Quality ◽

Transcriptional Regulatory ◽

Serovar Typhimurium ◽

Gene Modules ◽

Different Strains ◽

Genetic Signatures ◽

Regulatory Landscape

Salmonella enterica Typhimurium is a serious pathogen that is involved in human nontyphoidal infections. Tackling Typhimurium infections is difficult due to the species' dynamic adaptation to its environment, which is dictated by a complex transcriptional regulatory network (TRN). While traditional biomolecular methods provide characterizations of specific regulators, it is laborious to construct the global TRN structure from this bottom-up approach. Here, we used a machine learning technique to understand the transcriptional signatures of S. enterica Typhimurium from the top down, as a whole and in individual strains. Furthermore, we conducted cross-strain comparison of 6 strains in serovar Typhimurium to investigate similarities and differences in their TRNs with pan-genomic analysis. By decomposing all the publicly available RNA-Seq data of Typhimurium with independent component analysis (ICA), we obtained over 400 independently modulated sets of genes, called iModulons. Through analysis of these iModulons, we 1) discover three transport iModulons linked to antibiotic resistance, 2) describe concerted responses to cationic antimicrobial peptides (CAMPs), 3) uncover evidence towards new regulons, and 4) identify two iModulons linked to bile responses in strain ST4/74. We extend this analysis across the pan-genome to show that strain-specific iModulons 5) reveal different genetic signatures in pathogenicity islands that explain phenotypes and 6) capture the activity of different phages in the studied strains. Using all high-quality publicly-available RNA-Seq data to date, we present a comprehensive, data-driven Typhimurium TRN. It is conceivable that with more high-quality datasets from more strains, the approach used in this study will continue to guide our investigation in understanding the pan-transcriptome of Typhimurium. Interactive dashboards for all gene modules in this project are available at https://imodulondb.org/ to enable browsing for interested researchers.

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Single-Cell Transcriptomics-Based Study of Transcriptional Regulatory Features in the Mouse Brain Vasculature

BioMed Research International ◽

10.1155/2021/7643209 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Wei-Wei Lin ◽

Lin-Tao Xu ◽

Yi-Sheng Chen ◽

Ken Go ◽

Chenyu Sun ◽

...

Keyword(s):

Single Cell ◽

Mouse Brain ◽

Regulatory Network ◽

Regulatory Networks ◽

Transcriptional Regulatory Network ◽

Rna Seq ◽

Brain Vasculature ◽

Transcriptional Regulatory ◽

Cell Transcriptome ◽

Single Cell Transcriptome

Background. The critical role of vascular health on brain function has received much attention in recent years. At the single-cell level, studies on the developmental processes of cerebral vascular growth are still relatively few. Techniques for constructing gene regulatory networks (GRNs) based on single-cell transcriptome expression data have made significant progress in recent years. Herein, we constructed a single-cell transcriptional regulatory network of mouse cerebrovascular cells. Methods. The single-cell RNA-seq dataset of mouse brain vessels was downloaded from GEO (GSE98816). This cell clustering was annotated separately using singleR and CellMarker. We then used a modified version of the SCENIC method to construct GRNs. Next, we used a mouse version of SEEK to assess whether genes in the regulon were coexpressed. Finally, regulatory module analysis was performed to complete the cell type relationship quantification. Results. Single-cell RNA-seq data were used to analyze the heterogeneity of mouse cerebrovascular cells, whereby four cell types including endothelial cells, fibroblasts, microglia, and oligodendrocytes were defined. These subpopulations of cells and marker genes together characterize the molecular profile of mouse cerebrovascular cells. Through these signatures, key transcriptional regulators that maintain cell identity were identified. Our findings identified genes like Lmo2, which play an important role in endothelial cells. The same cell type, for instance, fibroblasts, was found to have different regulatory networks, which may influence the functional characteristics of local tissues. Conclusions. In this study, a transcriptional regulatory network based on single-cell analysis was constructed. Additionally, the study identified and profiled mouse cerebrovascular cells using single-cell transcriptome data as well as defined TFs that affect the regulatory network of the mouse brain vasculature.

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PRECISE 2.0: an expanded high-quality RNA-seq compendium for Escherichia coli K-12 reveals high-resolution transcriptional regulatory structure

10.1101/2021.04.08.439047 ◽

2021 ◽

Author(s):

Cameron R. Lamoureux ◽

Katherine T. Decker ◽

Anand V. Sastry ◽

John Luke McConn ◽

Ye Gao ◽

...

Keyword(s):

Gene Expression ◽

Escherichia Coli ◽

Multiple Scales ◽

Transcriptional Regulatory Network ◽

Differential Expression Analysis ◽

Rna Seq ◽

High Quality ◽

Standardized Protocol ◽

Transcriptional Regulatory ◽

K 12

Uncovering the structure of the transcriptional regulatory network (TRN) that modulates gene expression in prokaryotes remains an important challenge. Transcriptomics data is plentiful, necessitating the development of scalable methods for converting this data into useful knowledge about the TRN. Previously, we published the PRECISE dataset for Escherichia coli K-12 MG1655, containing 278 RNA-seq datasets created using a standardized protocol. Here, we present PRECISE 2.0, which is nearly three times the size of the original PRECISE dataset and also created using a standardized protocol. We analyze PRECISE 2.0 at multiple scales, demonstrating multiple analytical strategies for extracting knowledge from this dataset. Specifically, we: (1) highlight patterns in gene expression across the dataset; (2) utilize independent component analysis to extract 218 independently modulated groups of genes (iModulons) that describe the TRN at the systems level; (3) demonstrate the utility of iModulons over traditional differential expression analysis; and (4) uncover 6 new potential regulons. Thus, PRECISE 2.0 is a large-scale, high-quality transcriptomics dataset which may be analyzed at multiple scales to yield important biological insights.

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Spliced genes in muscle from Nelore Cattle and their association with carcass and meat quality

Scientific Reports ◽

10.1038/s41598-020-71783-4 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Danielly B. S. Silva ◽

Larissa F. S. Fonseca ◽

Daniel G. Pinheiro ◽

Ana F. B. Magalhães ◽

Maria M. M. Muniz ◽

...

Keyword(s):

Biological Process ◽

Gene Families ◽

Differentially Expressed ◽

Rna Seq ◽

Splice Sites ◽

Protein Ubiquitination ◽

Alternatively Spliced ◽

Nelore Cattle ◽

Go Terms ◽

Intramuscular Fat Content

Abstract Transcript data obtained by RNA-Seq were used to identify differentially expressed alternatively spliced genes in ribeye muscle tissue between Nelore cattle that differed in their ribeye area (REA) or intramuscular fat content (IF). A total of 166 alternatively spliced transcripts from 125 genes were significantly differentially expressed in ribeye muscle between the highest and lowest REA groups (p ≤ 0.05). For animals selected on their IF content, 269 alternatively spliced transcripts from 219 genes were differentially expressed in ribeye muscle between the highest and lowest IF animals. Cassette exons and alternative 3′ splice sites were the most frequently found alternatively spliced transcripts for REA and IF content. For both traits, some differentially expressed alternatively spliced transcripts belonged to myosin and myotilin gene families. The hub transcripts were identified for REA (LRRFIP1, RCAN1 and RHOBTB1) and IF (TRIP12, HSPE1 and MAP2K6) have an important role to play in muscle cell degradation, development and motility. In general, transcripts were found for both traits with biological process GO terms that were involved in pathways related to protein ubiquitination, muscle differentiation, lipids and hormonal systems. Our results reinforce the biological importance of these known processes but also reveal new insights into the complexity of the whole cell muscle mRNA of Nelore cattle.

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Relationship between the structure and function of the transcriptional regulator E2A

Journal of Biological Research-Thessaloniki ◽

10.1186/s40709-021-00146-5 ◽

2021 ◽

Vol 28 (1) ◽

Author(s):

Jia-Jie Liang ◽

Hu Peng ◽

Jiao-Jiao Wang ◽

Xiao-Hui Liu ◽

Lan Ma ◽

...

Keyword(s):

Transcriptional Regulation ◽

Transcriptional Regulatory Network ◽

Homo Sapiens ◽

E Proteins ◽

Activation Domains ◽

Bhlh Domain ◽

Helix Loop Helix ◽

Dna Motif ◽

Transcriptional Regulatory ◽

And Function

AbstractE proteins are transcriptional regulators that regulate many developmental processes in animals and lymphocytosis and leukemia in Homo sapiens. In particular, E2A, a member of the E protein family, plays a major role in the transcriptional regulatory network that promotes the differentiation and development of B and T lymphocytes. E2A-mediated transcriptional regulation usually requires the formation of E2A dimers, which then bind to coregulators. In this review, we summarize the mechanisms by which E2A participates in transcriptional regulation from a structural perspective. More specifically, the C-terminal helix-loop-helix (HLH) region of the basic HLH (bHLH) domain first dimerizes, and then the activation domains of E2A bind to different coactivators or corepressors in different cell contexts, resulting in histone acetylation or deacetylation, respectively. Then, the N-terminal basic region (b) of the bHLH domain binds to or dissociates from a specific DNA motif (E-box sequence). Last, trans-activation or trans-repression occurs. We also summarize the properties of these E2A domains and their interactions with the domains of other proteins. The feasibility of developing drugs based on these domains is discussed.

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