The Impact of Heat Stress on Morpho-Physiological Response and Expression of Specific Genes in the Heat Stress-Responsive Transcriptional Regulatory Network in Brassica oleracea

Knowledge of heat-tolerant/sensitive cultivars based on morpho-physiological indicators and an understanding of the action and interaction of different genes in the molecular network are critical for genetic improvement. To screen these indicators, the physiological performance of two different varieties of white and red cabbages (B. oleracea var. capitate f. alba and f. rubra, respectively) under heat stress (HS) and non-stress (NS) was evaluated. Cultivars that showed considerable cell membrane thermostability and less reduction in chlorophyll content with better head formation were categorized as the heat-tolerant cultivars (HTC), while those with reduction in stomatal conductance, higher reduction incurred in chlorophyll and damage to thylakoid membranes are categorized as the heat-sensitive cultivars (HSC). Expression profiling of key genes in the HS response network, including BoHSP70 (HEAT SHOCK PROTEIN 70), BoSCL13 (SCARECROW-LIKE 13) and BoDPB3-1 (transcriptional regulator DNA POLYMERASE II SUBUNIT B3-1 (DPB3-1))/NUCLEAR FACTOR Y SUBUNIT C10 (NF-YC10), were evaluated in all cultivars under HS compared to NS plants, which showed their potential as molecular indicators to differentiate HTC from HSC. Based on the results, the morphophysiological and molecular indicators are applicable to cabbage cultivars for differentiating HTC from HSC, and potential target genes for genome editing were identified for enhancing food security in the warmer regions of the world.

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Screening Driving Transcription Factors in the Processing of Gastric Cancer

Gastroenterology Research and Practice ◽

10.1155/2016/8431480 ◽

2016 ◽

Vol 2016 ◽

pp. 1-9 ◽

Cited By ~ 5

Author(s):

Guangzhong Xu ◽

Kai Li ◽

Nengwei Zhang ◽

Bin Zhu ◽

Guosheng Feng

Keyword(s):

Gastric Cancer ◽

Transcription Factors ◽

Regulatory Network ◽

Target Genes ◽

Transcriptional Regulatory Network ◽

Expression Profiles ◽

Functional Enrichment ◽

Regulatory Mechanisms ◽

Integrated Analysis ◽

Transcriptional Regulatory

Background. Construction of the transcriptional regulatory network can provide additional clues on the regulatory mechanisms and therapeutic applications in gastric cancer.Methods. Gene expression profiles of gastric cancer were downloaded from GEO database for integrated analysis. All of DEGs were analyzed by GO enrichment and KEGG pathway enrichment. Transcription factors were further identified and then a global transcriptional regulatory network was constructed.Results. By integrated analysis of the six eligible datasets (340 cases and 43 controls), a bunch of 2327 DEGs were identified, including 2100 upregulated and 227 downregulated DEGs. Functional enrichment analysis of DEGs showed that digestion was a significantly enriched GO term for biological process. Moreover, there were two important enriched KEGG pathways: cell cycle and homologous recombination. Furthermore, a total of 70 differentially expressed TFs were identified and the transcriptional regulatory network was constructed, which consisted of 566 TF-target interactions. The top ten TFs regulating most downstream target genes were BRCA1, ARID3A, EHF, SOX10, ZNF263, FOXL1, FEV, GATA3, FOXC1, and FOXD1. Most of them were involved in the carcinogenesis of gastric cancer.Conclusion. The transcriptional regulatory network can help researchers to further clarify the underlying regulatory mechanisms of gastric cancer tumorigenesis.

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Transcriptional regulatory network analysis of developing human erythroid progenitors reveals patterns of coregulation and potential transcriptional regulators

Physiological Genomics ◽

10.1152/physiolgenomics.00055.2006 ◽

2006 ◽

Vol 28 (1) ◽

pp. 114-128 ◽

Cited By ~ 37

Author(s):

M. A. Keller ◽

S. Addya ◽

R. Vadigepalli ◽

B. Banini ◽

K. Delgrosso ◽

...

Keyword(s):

Network Analysis ◽

Blood Cell ◽

Regulatory Network ◽

Target Genes ◽

Transcriptional Regulatory Network ◽

Expression Patterns ◽

Transcriptional Regulators ◽

Erythroid Progenitors ◽

Hematopoietic Stem ◽

Transcriptional Regulatory

Deciphering the molecular basis for human erythropoiesis should yield information benefiting studies of the hemoglobinopathies and other erythroid disorders. We used an in vitro erythroid differentiation system to study the developing red blood cell transcriptome derived from adult CD34+ hematopoietic progenitor cells. mRNA expression profiling was used to characterize developing erythroid cells at six time points during differentiation ( days 1, 3, 5, 7, 9, and 11). Eleven thousand seven hundred sixty-three genes (20,963 Affymetrix probe sets) were expressed on day 1, and 1,504 genes, represented by 1,953 probe sets, were differentially expressed (DE) with 537 upregulated and 969 downregulated. A subset of the DE genes was validated using real-time RT-PCR. The DE probe sets were subjected to a cluster metric and could be divided into two, three, four, five, or six clusters of genes with different expression patterns in each cluster. Genes in these clusters were examined for shared transcription factor binding sites (TFBS) in their promoters by comparing enrichment of each TFBS relative to a reference set using transcriptional regulatory network analysis. The sets of TFBS enriched in genes up- and downregulated during erythropoiesis were distinct. This analysis identified transcriptional regulators critical to erythroid development, factors recently found to play a role, as well as a new list of potential candidates, including Evi-1, a potential silencer of genes upregulated during erythropoiesis. Thus this transcriptional regulatory network analysis has yielded a focused set of factors and their target genes whose role in differentiation of the hematopoietic stem cell into distinct blood cell lineages can be elucidated.

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Modeling gene regulation from paired expression and chromatin accessibility data

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1704553114 ◽

2017 ◽

Vol 114 (25) ◽

pp. E4914-E4923 ◽

Cited By ~ 76

Author(s):

Zhana Duren ◽

Xi Chen ◽

Rui Jiang ◽

Yong Wang ◽

Wing Hung Wong

Keyword(s):

Gene Expression ◽

Target Genes ◽

Transcriptional Regulatory Network ◽

Joint Modeling ◽

Regulatory Elements ◽

Chromatin Accessibility ◽

Exciting Opportunity ◽

Transcriptional Regulatory ◽

Dna Elements ◽

Context Specific

The rapid increase of genome-wide datasets on gene expression, chromatin states, and transcription factor (TF) binding locations offers an exciting opportunity to interpret the information encoded in genomes and epigenomes. This task can be challenging as it requires joint modeling of context-specific activation of cis-regulatory elements (REs) and the effects on transcription of associated regulatory factors. To meet this challenge, we propose a statistical approach based on paired expression and chromatin accessibility (PECA) data across diverse cellular contexts. In our approach, we model (i) the localization to REs of chromatin regulators (CRs) based on their interaction with sequence-specific TFs, (ii) the activation of REs due to CRs that are localized to them, and (iii) the effect of TFs bound to activated REs on the transcription of target genes (TGs). The transcriptional regulatory network inferred by PECA provides a detailed view of how trans- and cis-regulatory elements work together to affect gene expression in a context-specific manner. We illustrate the feasibility of this approach by analyzing paired expression and accessibility data from the mouse Encyclopedia of DNA Elements (ENCODE) and explore various applications of the resulting model.

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

BMC Genomics ◽

10.1186/s12864-019-6190-3 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 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.

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Spatial organization of the transcriptional regulatory network of Saccharomyces cerevisiae

10.1101/509224 ◽

2019 ◽

Author(s):

Dong-Qing Sun ◽

Liu Tian ◽

Bin-Guang Ma

Keyword(s):

Saccharomyces Cerevisiae ◽

Regulatory Network ◽

Spatial Organization ◽

Target Genes ◽

Transcriptional Regulatory Network ◽

3D Structure ◽

Three Dimensional ◽

3D Genome ◽

Transcriptional Regulatory ◽

Four Levels

AbstractTranscriptional regulatory network (TRN) is a directed complex network composed of all regulatory interactions between transcription factors and corresponding target genes. Recently, the three-dimensional (3D) genomics studies have shown that the 3D structure of the genome makes a difference to the regulation of gene transcription, which provides us with a novel perspective. In this study, we constructed the TRN of the budding yeast Saccharomyces cerevisiae and placed it in the context of 3D genome model. We analyzed the spatial organization of the yeast TRN on four levels: global feature, central nodes, hierarchical structure and network motifs. Our results suggested that the TRN of S. cerevisiae presents an optimized structure in space to adapt to functional requirement.

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Identification of transcriptional regulatory network associated with response of host epithelial cells to SARS-CoV-2

Scientific Reports ◽

10.1038/s41598-021-03309-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Chen Su ◽

Simon Rousseau ◽

Amin Emad

Keyword(s):

Gene Expression ◽

Epithelial Cells ◽

Regulatory Network ◽

Transcriptional Regulatory Network ◽

Organ Damage ◽

Host Cells ◽

Regulatory Mechanisms ◽

Transcriptional Regulatory ◽

Transcriptional Regulatory Mechanisms ◽

The Impact

AbstractIdentification of transcriptional regulatory mechanisms and signaling networks involved in the response of host cells to infection by SARS-CoV-2 is a powerful approach that provides a systems biology view of gene expression programs involved in COVID-19 and may enable the identification of novel therapeutic targets and strategies to mitigate the impact of this disease. In this study, our goal was to identify a transcriptional regulatory network that is associated with gene expression changes between samples infected by SARS-CoV-2 and those that are infected by other respiratory viruses to narrow the results on those enriched or specific to SARS-CoV-2. We combined a series of recently developed computational tools to identify transcriptional regulatory mechanisms involved in the response of epithelial cells to infection by SARS-CoV-2, and particularly regulatory mechanisms that are specific to this virus when compared to other viruses. In addition, using network-guided analyses, we identified kinases associated with this network. The results identified pathways associated with regulation of inflammation (MAPK14) and immunity (BTK, MBX) that may contribute to exacerbate organ damage linked with complications of COVID-19. The regulatory network identified herein reflects a combination of known hits and novel candidate pathways supporting the novel computational pipeline presented herein to quickly narrow down promising avenues of investigation when facing an emerging and novel disease such as COVID-19.

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Human transcriptional gene regulatory network compiled from 14 data resources

10.1101/2021.08.28.457834 ◽

2021 ◽

Author(s):

VIJAYKUMAR Yogesh MULEY ◽

Rainer Koenig

Keyword(s):

Regulatory Network ◽

Transcriptional Repression ◽

Target Genes ◽

Transcriptional Regulatory Network ◽

Confidence Score ◽

Expression Of Genes ◽

Transcriptional Regulatory ◽

Significant Gene ◽

Spatio Temporal ◽

Weak Expression

Transcriptional regulatory network (TRN) orchestrates spatio-temporal expression of genes to generate cellular responses for survival. The transcription factors (TF) regulating expression of their target genes (TG) are the fundamental units of TRN. Several databases have been developed to catalogue human TRN based on low- and high-throughput experimental and computational studies considering their importance in understanding cellular physiology. However, literature lacks comparative assessment on the strength and weakness of each database. In this study, we compared over 2.2 million regulatory pairs between 1,379 TF and 22,518 TG assembled from 14 data resources. Our study reveals that the TF and TG were common across data resources but not their regulatory pairs. We observed that the TF and TG of the regulatory pairs showed weak expression correlation, significant gene ontology overlap, co-citations in PubMed and low numbers of TF-TG pairs representing transcriptional repression relationships. Furthermore, each TF-TG regulatory pair assigned a combined confidence score reflecting its reliability based on its presence in multiple databases and co-expression. The TRN containing 2,246,598 TF-TG pairs, of which, 44,284 with the information on TF′s activating or repressing effects on their TG is available upon request. This study brings the information about transcriptional regulation scattered over the literature and databases at one place in the form of one of the most comprehensive and complete human TRNs assembled to date, which will be a valuable resource for benchmarking TRN prediction tools, and to the scientific community working in functional genomics, gene expression and gene regulation analysis.

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Genomic Selection Improves Heat Tolerance in Dairy Cattle

Scientific Reports ◽

10.1038/srep34114 ◽

2016 ◽

Vol 6 (1) ◽

Cited By ~ 35

Author(s):

J. B. Garner ◽

M. L. Douglas ◽

S. R. O Williams ◽

W. J. Wales ◽

L. C. Marett ◽

...

Keyword(s):

Heat Stress ◽

Dairy Cattle ◽

Genomic Selection ◽

Milk Production ◽

Heat Tolerance ◽

Dairy Products ◽

Dairy Herds ◽

Physiological Indicators ◽

Genome Wide ◽

Heat Tolerant

Abstract Dairy products are a key source of valuable proteins and fats for many millions of people worldwide. Dairy cattle are highly susceptible to heat-stress induced decline in milk production, and as the frequency and duration of heat-stress events increases, the long term security of nutrition from dairy products is threatened. Identification of dairy cattle more tolerant of heat stress conditions would be an important progression towards breeding better adapted dairy herds to future climates. Breeding for heat tolerance could be accelerated with genomic selection, using genome wide DNA markers that predict tolerance to heat stress. Here we demonstrate the value of genomic predictions for heat tolerance in cohorts of Holstein cows predicted to be heat tolerant and heat susceptible using controlled-climate chambers simulating a moderate heatwave event. Not only was the heat challenge stimulated decline in milk production less in cows genomically predicted to be heat-tolerant, physiological indicators such as rectal and intra-vaginal temperatures had reduced increases over the 4 day heat challenge. This demonstrates that genomic selection for heat tolerance in dairy cattle is a step towards securing a valuable source of nutrition and improving animal welfare facing a future with predicted increases in heat stress events.

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Comparative Analysis of miRNA Expression Profiles between Heat-Tolerant and Heat-Sensitive Genotypes of Flowering Chinese Cabbage Under Heat Stress Using High-Throughput Sequencing

Genes ◽

10.3390/genes11030264 ◽

2020 ◽

Vol 11 (3) ◽

pp. 264 ◽

Cited By ~ 2

Author(s):

Waqas Ahmed ◽

Ronghua Li ◽

Yanshi Xia ◽

Guihua Bai ◽

Kadambot H. M. Siddique ◽

...

Keyword(s):

Heat Stress ◽

Heat Tolerance ◽

Chinese Cabbage ◽

Target Genes ◽

Expression Profiles ◽

Mapk Signaling ◽

Differentially Expressed ◽

Transcriptional Level ◽

Flowering Chinese Cabbage ◽

Heat Tolerant

Heat stress disturbs cellular homeostasis, thus usually impairs yield of flowering Chinese cabbage (Brassica campestris L. ssp. chinensis var. utilis Tsen et Lee). MicroRNAs (miRNAs) play a significant role in plant responses to different stresses by modulating gene expression at the post-transcriptional level. However, the roles that miRNAs and their target genes may play in heat tolerance of flowering Chinese cabbage remain poorly characterized. The current study sequenced six small RNA libraries generated from leaf tissues of flowering Chinese cabbage collected at 0, 6, and 12 h after 38 °C heat treatment, and identified 49 putative novel miRNAs and 43 known miRNAs that differentially expressed between heat-tolerant and heat-sensitive flowering Chinese cabbage. Among them, 14 novel and nine known miRNAs differentially expressed only in the heat-tolerant genotype under heat-stress, therefore, their target genes including disease resistance protein TAO1-like, RPS6, reticuline oxidase-like protein, etc. might play important roles in enhancing heat-tolerance. Gene Ontology (GO) analysis revealed that targets of these differentially expressed miRNAs may play key roles in responses to temperature stimulus, cell part, cellular process, cell, membrane, biological regulation, binding, and catalytic activities. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis identified their important functions in signal transduction, environmental adaptation, global and overview maps, as well as in stress adaptation and in MAPK signaling pathways such as cell death. These findings provide insight into the functions of the miRNAs in heat stress tolerance of flowering Chinese cabbage.

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