scholarly journals Construction and Clarification of Dynamic Gene Regulatory Network of Cancer Cell Cycle via Microarray Data

2006 ◽  
Vol 2 ◽  
pp. 117693510600200 ◽  
Author(s):  
Cheng-Wei Li ◽  
Yung-Hsiang Chu ◽  
Bor-Sen Chen
Keyword(s):  
Cell Cycle ◽  
Hela Cell ◽  
Dynamic Model ◽  
Gene Regulatory Network ◽  
Cancer Cell ◽  
Microarray Data ◽  
Regulatory Network ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Regulatory

Background Cell cycle is an important clue to unravel the mechanism of cancer cells. Recently, expression profiles of cDNA microarray data of Cancer cell cycle are available for the information of dynamic interactions among Cancer cell cycle related genes. Therefore, it is more appealing to construct a dynamic model for gene regulatory network of Cancer cell cycle to gain more insight into the infrastructure of gene regulatory mechanism of cancer cell via microarray data. Results Based on the gene regulatory dynamic model and microarray data, we construct the whole dynamic gene regulatory network of Cancer cell cycle. In this study, we trace back upstream regulatory genes of a target gene to infer the regulatory pathways of the gene network by maximum likelihood estimation method. Finally, based on the dynamic regulatory network, we analyze the regulatory abilities and sensitivities of regulatory genes to clarify their roles in the mechanism of Cancer cell cycle. Conclusions Our study presents a systematically iterative approach to discern and characterize the transcriptional regulatory network in Hela cell cycle from the raw expression profiles. The transcription regulatory network in Hela cell cycle can also be confirmed by some experimental reviews. Based on our study and some literature reviews, we can predict and clarify the E2F target genes in G1/S phase, which are crucial for regulating cell cycle progression and tumorigenesis. From the results of the network construction and literature confirmation, we infer that MCM4, MCM5, CDC6, CDC25A, UNG and E2F2 are E2F target genes in Hela cell cycle.

scholarly journals Deciphering the genetic links between NAFLD and co-occurring conditions using a liver gene regulatory network

2021 ◽  
Author(s):  
Sreemol Gokuladhas ◽  
William Schierding ◽  
Roan Eltigani Zaied ◽  
Tayaza Fadason ◽  
Murim Choi ◽  
...  
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Complex Traits ◽  
Target Genes ◽  
Specific Gene ◽  
Fat Percentage ◽  
Alcoholic Fatty Liver ◽  
Regulatory Interactions ◽  
Hepatic Diseases ◽  
Gene Regulatory

Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is a multi-system metabolic disease that co-occurs with various hepatic and extra-hepatic diseases. The phenotypic manifestation of NAFLD is primarily observed in the liver. Therefore, identifying liver-specific gene regulatory interactions between variants associated with NAFLD and multimorbid conditions may help to improve our understanding of underlying shared aetiology. Methods: Here, we constructed a liver-specific gene regulatory network (LGRN) consisting of genome-wide spatially constrained expression quantitative trait loci (eQTLs) and their target genes. The LGRN was used to identify regulatory interactions involving NAFLD-associated genetic modifiers and their inter-relationships to other complex traits. Results and Conclusions: We demonstrate that MBOAT7 and IL32, which are associated with NAFLD progression, are regulated by spatially constrained eQTLs that are enriched for an association with liver enzyme levels. MBOAT7 transcript levels are also linked to eQTLs associated with cirrhosis, and other traits that commonly co-occur with NAFLD. In addition, genes that encode interacting partners of NAFLD-candidate genes within the liver-specific protein-protein interaction network were affected by eQTLs enriched for phenotypes relevant to NAFLD (e.g. IgG glycosylation patterns, OSA). Furthermore, we identified distinct gene regulatory networks formed by the NAFLD-associated eQTLs in normal versus diseased liver, consistent with the context-specificity of the eQTLs effects. Interestingly, genes targeted by NAFLD-associated eQTLs within the LGRN were also affected by eQTLs associated with NAFLD-related traits (e.g. obesity and body fat percentage). Overall, the genetic links identified between these traits expand our understanding of shared regulatory mechanisms underlying NAFLD multimorbidities.

scholarly journals Evolution of Regulatory Complexity for Cell-Cycle Control

2021 ◽  
Author(s):  
Sam H. A. von der Dunk ◽  
Berend Snel ◽  
Paulien Hogeweg
Keyword(s):  
Cell Cycle ◽  
Gene Regulation ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Caulobacter Crescentus ◽  
Genome Structure ◽  
Cell Cycle Checkpoint ◽  
Evolutionary Strategies ◽  
Nutrient Levels ◽  
Gene Regulatory

How complexity arises is a fundamental evolutionary question. Complex gene regulation is thought to arise by the interplay between adaptive and non-adaptive forces at multiple organizational levels. Using a computational model, we investigate how complexity arises in cell-cycle regulation. Starting from the well-known Caulobacter crescentus network, we study how cells adapt their cell-cycle behaviour to a gradient of limited nutrient conditions using 10 replicate in silico evolution experiments. We find adaptive expansion of the gene regulatory network: improvement of cell-cycle behaviour allows cells to overcome the inherent cost of complexity. Replicates traverse different evolutionary trajectories leading to distinct eco-evolutionary strategies. In four replicates, cells evolve a generalist strategy to cope with a variety of nutrient levels; in two replicates, different specialist cells evolve for specific nutrient levels; in the remaining four replicates, an intermediate strategy evolves. The generalist and specialist strategies are contingent on the regulatory mechanisms that arise early in evolution, but they are not directly linked to network expansion and overall fitness. This study shows that functionality of cells depends on the combination of gene regulatory network topology and genome structure. For example, the positions of dosage-sensitive genes are exploited to signal to the regulatory network when replication is completed, forming a de novo evolved cell-cycle checkpoint. Complex gene regulation can arise adaptively both from expansion of the regulatory network and from the genomic organization of the elements in this network, demonstrating that to understand complex gene regulation and its evolution, it is necessary to integrate systems that are often studied separately.

scholarly journals The transcription factor Zic4 acts as a transdifferentiation switch

2021 ◽  
Author(s):  
Matthias Christian Vogg ◽  
Jaroslav Ferenc ◽  
Wanda Christa Buzgariu ◽  
Chrystelle Perruchoud ◽  
Panagiotis Papasaikas ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Transcription Factor ◽  
Gene Regulatory Network ◽  
Cell Fate ◽  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Model System ◽  
Cell Identity ◽  
Transcriptional Switch ◽  
Gene Regulatory

The molecular mechanisms that maintain cell identities and prevent transdifferentiation remain mysterious. Interestingly, both dedifferentiation and transdifferentiation are transiently reshuffled during regeneration. Therefore, organisms that regenerate readily offer a fruitful paradigm to investigate the regulation of cell fate stability. Here, we used Hydra as a model system and show that Zic4 silencing is sufficient to induce transdifferentiation of tentacle into foot cells. We identified a Wnt-controlled Gene Regulatory Network that controls a transcriptional switch of cell identity. Furthermore, we show that this switch also controls the re-entry into the cell cycle. Our data indicate that maintenance of cell fate by a Wnt-controlled GRN is a key mechanism during both homeostasis and regeneration.

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