Displaying publications 1 - 20 of 72 in total

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  1. A review on the computational approaches for gene regulatory network construction
    Chai LE, Loh SK, Low ST, Mohamad MS, Deris S, Zakaria Z
    Comput Biol Med, 2014 May;48:55-65.
    PMID: 24637147 DOI: 10.1016/j.compbiomed.2014.02.011
    Many biological research areas such as drug design require gene regulatory networks to provide clear insight and understanding of the cellular process in living cells. This is because interactions among the genes and their products play an important role in many molecular processes. A gene regulatory network can act as a blueprint for the researchers to observe the relationships among genes. Due to its importance, several computational approaches have been proposed to infer gene regulatory networks from gene expression data. In this review, six inference approaches are discussed: Boolean network, probabilistic Boolean network, ordinary differential equation, neural network, Bayesian network, and dynamic Bayesian network. These approaches are discussed in terms of introduction, methodology and recent applications of these approaches in gene regulatory network construction. These approaches are also compared in the discussion section. Furthermore, the strengths and weaknesses of these computational approaches are described.
    Matched MeSH terms: Gene Regulatory Networks*
  2. Construction of a microRNA-mRNA Regulatory Network in De Novo Cytogenetically Normal Acute Myeloid Leukemia Patients
    Esa E, Hashim AK, Mohamed EHM, Zakaria Z, Abu Hassan AN, Mat Yusoff Y, et al.
    Genet Test Mol Biomarkers, 2021 Mar;25(3):199-210.
    PMID: 33734890 DOI: 10.1089/gtmb.2020.0182
    Background: The association between dysregulated microRNAs (miRNAs) and acute myeloid leukemia (AML) is well known. However, our understanding of the regulatory role of miRNAs in the cytogenetically normal AML (CN-AML) subtype pathway is still poor. The current study integrated miRNA and mRNA profiles to explore novel miRNA-mRNA interactions that affect the regulatory patterns of de novo CN-AML. Methods: We utilized a multiplexed nanoString nCounter platform to profile both miRNAs and mRNAs using similar sets of patient samples (n = 24). Correlations were assessed, and an miRNA-mRNA network was constructed. The underlying biological functions of the mRNAs were predicted by gene enrichment. Finally, the interacting pairs were assessed using TargetScan and microT-CDS. We identified 637 significant negative correlations (false discovery rate <0.05). Results: Network analysis revealed a cluster of 12 miRNAs representing the majority of mRNA targets. Within the cluster, five miRNAs (miR-495-3p, miR-185-5p, let-7i-5p, miR-409-3p, and miR-127-3p) were posited to play a pivotal role in the regulation of CN-AML, as they are associated with the negative regulation of myeloid leukocyte differentiation, negative regulation of myeloid cell differentiation, and positive regulation of hematopoiesis. Conclusion: Three novel interactions in CN-AML were predicted as let-7i-5p:HOXA9, miR-495-3p:PIK3R1, and miR-495-3p:CDK6 may be responsible for regulating myeloid cell differentiation in CN-AML.
    Matched MeSH terms: Gene Regulatory Networks/genetics
  3. Fulltext Rare Copy Number Variants Identified Suggest the Regulating Pathways in Hypertension-Related Left Ventricular Hypertrophy
    Boon-Peng H, Mat Jusoh JA, Marshall CR, Majid F, Danuri N, Basir F, et al.
    PLoS One, 2016;11(3):e0148755.
    PMID: 26930585 DOI: 10.1371/journal.pone.0148755
    Left ventricular hypertrophy (LVH) is an independent risk factor for cardiovascular morbidity and mortality, and a powerful predictor of adverse cardiovascular outcomes in the hypertensive patients. It has complex multifactorial and polygenic basis for its pathogenesis. We hypothesized that rare copy number variants (CNVs) contribute to the LVH pathogenesis in hypertensive patients. Copy number variants (CNV) were identified in 258 hypertensive patients, 95 of whom had LVH, after genotyping with a high resolution SNP array. Following stringent filtering criteria, we identified 208 rare, or private CNVs that were only present in our patients with hypertension related LVH. Preliminary findings from Gene Ontology and pathway analysis of this study confirmed the involvement of the genes known to be functionally involved in cardiac development and phenotypes, in line with previously reported transcriptomic studies. Network enrichment analyses suggested that the gene-set was, directly or indirectly, involved in the transcription factors regulating the "foetal cardiac gene programme" which triggered the hypertrophic cascade, confirming previous reports. These findings suggest that multiple, individually rare copy number variants altering genes may contribute to the pathogenesis of hypertension-related LVH. In summary, we have provided further supporting evidence that rare CNV could potentially impact this common and complex disease susceptibility with lower heritability.
    Matched MeSH terms: Gene Regulatory Networks
  4. Integrative analysis of chloroplast DNA methylation in a marine alga-Saccharina japonica
    Teng L, Han W, Fan X, Zhang X, Xu D, Wang Y, et al.
    Plant Mol Biol, 2021 Apr;105(6):611-623.
    PMID: 33528753 DOI: 10.1007/s11103-020-01113-9
    We applied an integrative approach using multiple methods to verify cytosine methylation in the chloroplast DNA of the multicellular brown alga Saccharina japonica. Cytosine DNA methylation is a heritable process which plays important roles in regulating development throughout the life cycle of an organism. Although methylation of nuclear DNA has been studied extensively, little is known about the state and role of DNA methylation in chloroplast genomes, especially in marine algae. Here, we have applied an integrated approach encompassing whole-genome bisulfite sequencing, methylated DNA immunoprecipitation, gene co-expression networks and photophysiological analyses to provide evidence for the role of chloroplast DNA methylation in a marine alga, the multicellular brown alga Saccharina japonica. Although the overall methylation level was relatively low in the chloroplast genome of S. japonica, gametophytes exhibited higher methylation levels than sporophytes. Gene-specific bisulfite-cloning sequencing provided additional evidence for the methylation of key photosynthetic genes. Many of them were highly expressed in sporophytes whereas genes involved in transcription, translation and biosynthesis were strongly expressed in gametophytes. Nucleus-encoded photosynthesis genes were co-expressed with their chloroplast-encoded counterparts potentially contributing to the higher photosynthetic performance in sporophytes compared to gametophytes where these co-expression networks were less pronounced. A nucleus-encoded DNA methyltransferase of the DNMT2 family is assumed to be responsible for the methylation of the chloroplast genome because it is predicted to possess a plastid transit peptide.
    Matched MeSH terms: Gene Regulatory Networks
  5. Fulltext REST and Neural Gene Network Dysregulation in iPSC Models of Alzheimer's Disease
    Meyer K, Feldman HM, Lu T, Drake D, Lim ET, Ling KH, et al.
    Cell Rep, 2019 01 29;26(5):1112-1127.e9.
    PMID: 30699343 DOI: 10.1016/j.celrep.2019.01.023
    The molecular basis of the earliest neuronal changes that lead to Alzheimer's disease (AD) is unclear. Here, we analyze neural cells derived from sporadic AD (SAD), APOE4 gene-edited and control induced pluripotent stem cells (iPSCs). We observe major differences in iPSC-derived neural progenitor (NP) cells and neurons in gene networks related to neuronal differentiation, neurogenesis, and synaptic transmission. The iPSC-derived neural cells from SAD patients exhibit accelerated neural differentiation and reduced progenitor cell renewal. Moreover, a similar phenotype appears in NP cells and cerebral organoids derived from APOE4 iPSCs. Impaired function of the transcriptional repressor REST is strongly implicated in the altered transcriptome and differentiation state. SAD and APOE4 expression result in reduced REST nuclear translocation and chromatin binding, and disruption of the nuclear lamina. Thus, dysregulation of neural gene networks may set in motion the pathologic cascade that leads to AD.
    Matched MeSH terms: Gene Regulatory Networks*
  6. CircRNA-miRNA interactions in atherogenesis
    Tong KL, Tan KE, Lim YY, Tien XY, Wong PF
    Mol Cell Biochem, 2022 Dec;477(12):2703-2733.
    PMID: 35604519 DOI: 10.1007/s11010-022-04455-8
    Atherosclerosis is the major cause of coronary artery disease (CAD) which includes unstable angina, myocardial infarction, and heart failure. The onset of atherogenesis, a process of atherosclerotic lesion formation in the intima of arteries, is driven by lipid accumulation, a vicious cycle of reactive oxygen species (ROS)-induced oxidative stress and inflammatory reactions leading to endothelial cell (EC) dysfunction, vascular smooth muscle cell (VSMC) activation, and foam cell formation which further fuel plaque formation and destabilization. In recent years, there is a surge in the number of publications reporting the involvement of circular RNAs (circRNAs) in the pathogenesis of cardiovascular diseases, cancers, and metabolic syndromes. These studies have advanced our understanding on the biological functions of circRNAs. One of the most common mechanism of action of circRNAs reported is the sponging of microRNAs (miRNAs) by binding to the miRNAs response element (MRE), thereby indirectly increases the transcription of their target messenger RNAs (mRNAs). Individual networks of circRNA-miRNA-mRNA associated with atherogenesis have been extensively reported, however, there is a need to connect these findings for a complete overview. This review aims to provide an update on atherogenesis-related circRNAs and analyze the circRNA-miRNA-mRNA interactions in atherogenesis. The atherogenic mechanisms and clinical relevance of each atherogenesis-related circRNA were systematically discussed for better understanding of the knowledge gap in this area.
    Matched MeSH terms: Gene Regulatory Networks
  7. Fulltext MicroRNA 299-3p modulates replicative senescence in endothelial cells
    Jong HL, Mustafa MR, Vanhoutte PM, AbuBakar S, Wong PF
    Physiol Genomics, 2013 Apr 1;45(7):256-67.
    PMID: 23362143 DOI: 10.1152/physiolgenomics.00071.2012
    MicroRNAs (miRNAs) regulate various cellular processes. While several genes associated with replicative senescence have been described in endothelial cells, miRNAs that regulate these genes remain largely unknown. The present study was designed to identify miRNAs associated with replicative senescence and their target genes in human umbilical vein endothelial cells (HUVECs). An integrated miRNA and gene profiling approach revealed that hsa-miR-299-3p is upregulated in senescent HUVECs compared with the young cells, and one of its target genes could be IGF1. IGF1 was upregulated in senescent compared with young HUVECs, and knockdown of hsa-miR-299-3p dose-dependently increased the mRNA expression of IGF1, more significantly observed in the presenescent cells (passage 19) compared with the senescent cells (passage 25). Knockdown of hsa-miR-299-3p also resulted in significant reduction in the percentage of cells positively stained for senescence-associated β-galactosidase and increases in cell viability measured by MTT assay but marginal increases in cell proliferation and cell migration capacity measured by real-time growth kinetics analysis. Moreover, knockdown of hsa-miR-299-3p also increased proliferation of cells treated with H2O2 to induce senescence. These findings suggest that hsa-miR-299-3p may delay or protect against replicative senescence by improving the metabolic activity of the senesced cells but does not stimulate growth of the remaining cells in senescent cultures. Hence, these findings provide an early insight into the role of hsa-miR-299-3p in the modulation of replicative senescence in HUVECs.
    Matched MeSH terms: Gene Regulatory Networks
  8. Fulltext Identification of four functionally important microRNA families with contrasting differential expression profiles between drought-tolerant and susceptible rice leaf at vegetative stage
    Cheah BH, Nadarajah K, Divate MD, Wickneswari R
    BMC Genomics, 2015;16:692.
    PMID: 26369665 DOI: 10.1186/s12864-015-1851-3
    Developing drought-tolerant rice varieties with higher yield under water stressed conditions provides a viable solution to serious yield-reduction impact of drought. Understanding the molecular regulation of this polygenic trait is crucial for the eventual success of rice molecular breeding programmes. microRNAs have received tremendous attention recently due to its importance in negative regulation. In plants, apart from regulating developmental and physiological processes, microRNAs have also been associated with different biotic and abiotic stresses. Hence here we chose to analyze the differential expression profiles of microRNAs in three drought treated rice varieties: Vandana (drought-tolerant), Aday Sel (drought-tolerant) and IR64 (drought-susceptible) in greenhouse conditions via high-throughput sequencing.
    Matched MeSH terms: Gene Regulatory Networks
  9. Fulltext A gene co-expression network model identifies yield-related vicinity networks in Jatropha curcas shoot system
    Govender N, Senan S, Mohamed-Hussein ZA, Wickneswari R
    Sci Rep, 2018 Jun 15;8(1):9211.
    PMID: 29907786 DOI: 10.1038/s41598-018-27493-z
    The plant shoot system consists of reproductive organs such as inflorescences, buds and fruits, and the vegetative leaves and stems. In this study, the reproductive part of the Jatropha curcas shoot system, which includes the aerial shoots, shoots bearing the inflorescence and inflorescence were investigated in regard to gene-to-gene interactions underpinning yield-related biological processes. An RNA-seq based sequencing of shoot tissues performed on an Illumina HiSeq. 2500 platform generated 18 transcriptomes. Using the reference genome-based mapping approach, a total of 64 361 genes was identified in all samples and the data was annotated against the non-redundant database by the BLAST2GO Pro. Suite. After removing the outlier genes and samples, a total of 12 734 genes across 17 samples were subjected to gene co-expression network construction using petal, an R library. A gene co-expression network model built with scale-free and small-world properties extracted four vicinity networks (VNs) with putative involvement in yield-related biological processes as follow; heat stress tolerance, floral and shoot meristem differentiation, biosynthesis of chlorophyll molecules and laticifers, cell wall metabolism and epigenetic regulations. Our VNs revealed putative key players that could be adapted in breeding strategies for J. curcas shoot system improvements.
    Matched MeSH terms: Gene Regulatory Networks/physiology*
  10. Fulltext Flexible model-based clustering of mixed binary and continuous data: application to genetic regulation and cancer
    Zainul Abidin FN, Westhead DR
    Nucleic Acids Res, 2017 04 20;45(7):e53.
    PMID: 27994031 DOI: 10.1093/nar/gkw1270
    Clustering is used widely in 'omics' studies and is often tackled with standard methods, e.g. hierarchical clustering. However, the increasing need for integration of multiple data sets leads to a requirement for clustering methods applicable to mixed data types, where the straightforward application of standard methods is not necessarily the best approach. A particularly common problem involves clustering entities characterized by a mixture of binary data (e.g. presence/absence of mutations, binding, motifs and epigenetic marks) and continuous data (e.g. gene expression, protein abundance, metabolite levels). Here, we present a generic method based on a probabilistic model for clustering this type of data, and illustrate its application to genetic regulation and the clustering of cancer samples. We show that the resulting clusters lead to useful hypotheses: in the case of genetic regulation these concern regulation of groups of genes by specific sets of transcription factors and in the case of cancer samples combinations of gene mutations are related to patterns of gene expression. The clusters have potential mechanistic significance and in the latter case are significantly linked to survival. The method is available as a stand-alone software package (GNU General Public Licence) from http://github.com/BioToolsLeeds/FlexiCoClusteringPackage.git.
    Matched MeSH terms: Gene Regulatory Networks
  11. Fulltext RNA sequencing analysis of human podocytes reveals glucocorticoid regulated gene networks targeting non-immune pathways
    Jiang L, Hindmarch CC, Rogers M, Campbell C, Waterfall C, Coghill J, et al.
    Sci Rep, 2016 10 24;6:35671.
    PMID: 27774996 DOI: 10.1038/srep35671
    Glucocorticoids are steroids that reduce inflammation and are used as immunosuppressive drugs for many diseases. They are also the mainstay for the treatment of minimal change nephropathy (MCN), which is characterised by an absence of inflammation. Their mechanisms of action remain elusive. Evidence suggests that immunomodulatory drugs can directly act on glomerular epithelial cells or 'podocytes', the cell type which is the main target of injury in MCN. To understand the nature of glucocorticoid effects on non-immune cell functions, we generated RNA sequencing data from human podocyte cell lines and identified the genes that are significantly regulated in dexamethasone-treated podocytes compared to vehicle-treated cells. The upregulated genes are of functional relevance to cytoskeleton-related processes, whereas the downregulated genes mostly encode pro-inflammatory cytokines and growth factors. We observed a tendency for dexamethasone-upregulated genes to be downregulated in MCN patients. Integrative analysis revealed gene networks composed of critical signaling pathways that are likely targeted by dexamethasone in podocytes.
    Matched MeSH terms: Gene Regulatory Networks/drug effects; Gene Regulatory Networks/genetics*
  12. Fulltext Endogenous HIF2A reporter systems for high-throughput functional screening
    Zaini MN, Patel SA, Syafruddin SE, Rodrigues P, Vanharanta S
    Sci Rep, 2018 08 13;8(1):12063.
    PMID: 30104738 DOI: 10.1038/s41598-018-30499-2
    Tissue-specific transcriptional programs control most biological phenotypes, including disease states such as cancer. However, the molecular details underlying transcriptional specificity is largely unknown, hindering the development of therapeutic approaches. Here, we describe novel experimental reporter systems that allow interrogation of the endogenous expression of HIF2A, a critical driver of renal oncogenesis. Using a focused CRISPR-Cas9 library targeting chromatin regulators, we provide evidence that these reporter systems are compatible with high-throughput screening. Our data also suggests redundancy in the control of cancer type-specific transcriptional traits. Reporter systems such as those described here could facilitate large-scale mechanistic dissection of transcriptional programmes underlying cancer phenotypes, thus paving the way for novel therapeutic approaches.
    Matched MeSH terms: Gene Regulatory Networks/genetics
  13. Fulltext A KLF6-driven transcriptional network links lipid homeostasis and tumour growth in renal carcinoma
    Syafruddin SE, Rodrigues P, Vojtasova E, Patel SA, Zaini MN, Burge J, et al.
    Nat Commun, 2019 03 11;10(1):1152.
    PMID: 30858363 DOI: 10.1038/s41467-019-09116-x
    Transcriptional networks are critical for the establishment of tissue-specific cellular states in health and disease, including cancer. Yet, the transcriptional circuits that control carcinogenesis remain poorly understood. Here we report that Kruppel like factor 6 (KLF6), a transcription factor of the zinc finger family, regulates lipid homeostasis in clear cell renal cell carcinoma (ccRCC). We show that KLF6 supports the expression of lipid metabolism genes and promotes the expression of PDGFB, which activates mTOR signalling and the downstream lipid metabolism regulators SREBF1 and SREBF2. KLF6 expression is driven by a robust super enhancer that integrates signals from multiple pathways, including the ccRCC-initiating VHL-HIF2A pathway. These results suggest an underlying mechanism for high mTOR activity in ccRCC cells. More generally, the link between super enhancer-driven transcriptional networks and essential metabolic pathways may provide clues to the mechanisms that maintain the stability of cell identity-defining transcriptional programmes in cancer.
    Matched MeSH terms: Gene Regulatory Networks
  14. Fulltext Eukaryotic pathways targeted by the type III secretion system effector protein, BipC, involved in the intracellular lifecycle of Burkholderia pseudomallei
    Kang WT, Vellasamy KM, Vadivelu J
    Sci Rep, 2016 09 16;6:33528.
    PMID: 27634329 DOI: 10.1038/srep33528
    Burkholderia pseudomallei, the etiological agent for melioidosis, is known to secrete a type III secretion system (TTSS) protein into the host's internal milieu. One of the TTSS effector protein, BipC, has been shown to play an important role in the B. pseudomallei pathogenesis. To identify the host response profile that was directly or indirectly regulated by this protein, genome-wide transcriptome approach was used to examine the gene expression profiles of infected mice. The transcriptome analysis of the liver and spleen revealed that a total of approximately 1,000 genes were transcriptionally affected by BipC. Genes involved in bacterial invasion, regulation of actin cytoskeleton, and MAPK signalling pathway were over-expressed and may be specifically regulated by BipC in vivo. These results suggest that BipC mainly targets pathways related to the cellular processes which could modulate the cellular trafficking processes. The host transcriptional response exhibited remarkable differences with and without the presence of the BipC protein. Overall, the detailed picture of this study provides new insights that BipC may have evolved to efficiently manipulate host-cell pathways which is crucial in the intracellular lifecycle of B. pseudomallei.
    Matched MeSH terms: Gene Regulatory Networks
  15. Fulltext Identification of Gene Modules Associated with Low Temperatures Response in Bambara Groundnut by Network-Based Analysis
    Bonthala VS, Mayes K, Moreton J, Blythe M, Wright V, May ST, et al.
    PLoS One, 2016;11(2):e0148771.
    PMID: 26859686 DOI: 10.1371/journal.pone.0148771
    Bambara groundnut (Vigna subterranea (L.) Verdc.) is an African legume and is a promising underutilized crop with good seed nutritional values. Low temperature stress in a number of African countries at night, such as Botswana, can effect the growth and development of bambara groundnut, leading to losses in potential crop yield. Therefore, in this study we developed a computational pipeline to identify and analyze the genes and gene modules associated with low temperature stress responses in bambara groundnut using the cross-species microarray technique (as bambara groundnut has no microarray chip) coupled with network-based analysis. Analyses of the bambara groundnut transcriptome using cross-species gene expression data resulted in the identification of 375 and 659 differentially expressed genes (p<0.01) under the sub-optimal (23°C) and very sub-optimal (18°C) temperatures, respectively, of which 110 genes are commonly shared between the two stress conditions. The construction of a Highest Reciprocal Rank-based gene co-expression network, followed by its partition using a Heuristic Cluster Chiseling Algorithm resulted in 6 and 7 gene modules in sub-optimal and very sub-optimal temperature stresses being identified, respectively. Modules of sub-optimal temperature stress are principally enriched with carbohydrate and lipid metabolic processes, while most of the modules of very sub-optimal temperature stress are significantly enriched with responses to stimuli and various metabolic processes. Several transcription factors (from MYB, NAC, WRKY, WHIRLY & GATA classes) that may regulate the downstream genes involved in response to stimulus in order for the plant to withstand very sub-optimal temperature stress were highlighted. The identified gene modules could be useful in breeding for low-temperature stress tolerant bambara groundnut varieties.
    Matched MeSH terms: Gene Regulatory Networks
  16. Fulltext Neuroinflammation as a Key Driver of Secondary Neurodegeneration Following Stroke?
    Stuckey SM, Ong LK, Collins-Praino LE, Turner RJ
    Int J Mol Sci, 2021 Dec 03;22(23).
    PMID: 34884906 DOI: 10.3390/ijms222313101
    Ischaemic stroke involves the rapid onset of focal neurological dysfunction, most commonly due to an arterial blockage in a specific region of the brain. Stroke is a leading cause of death and common cause of disability, with over 17 million people worldwide suffering from a stroke each year. It is now well-documented that neuroinflammation and immune mediators play a key role in acute and long-term neuronal tissue damage and healing, not only in the infarct core but also in distal regions. Importantly, in these distal regions, termed sites of secondary neurodegeneration (SND), spikes in neuroinflammation may be seen sometime after the initial stroke onset, but prior to the presence of the neuronal tissue damage within these regions. However, it is key to acknowledge that, despite the mounting information describing neuroinflammation following ischaemic stroke, the exact mechanisms whereby inflammatory cells and their mediators drive stroke-induced neuroinflammation are still not fully understood. As a result, current anti-inflammatory treatments have failed to show efficacy in clinical trials. In this review we discuss the complexities of post-stroke neuroinflammation, specifically how it affects neuronal tissue and post-stroke outcome acutely, chronically, and in sites of SND. We then discuss current and previously assessed anti-inflammatory therapies, with a particular focus on how failed anti-inflammatories may be repurposed to target SND-associated neuroinflammation.
    Matched MeSH terms: Gene Regulatory Networks/drug effects
  17. Fulltext Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data
    Aketarawong N, Isasawin S, Sojikul P, Thanaphum S
    Zookeys, 2015.
    PMID: 26798262 DOI: 10.3897/zookeys.540.10058
    The Carambola fruit fly, Bactrocera carambolae, is an invasive pest in Southeast Asia. It has been introduced into areas in South America such as Suriname and Brazil. Bactrocera carambolae belongs to the Bactrocera dorsalis species complex, and seems to be separated from Bactrocera dorsalis based on morphological and multilocus phylogenetic studies. Even though the Carambola fruit fly is an important quarantine species and has an impact on international trade, knowledge of the molecular ecology of Bactrocera carambolae, concerning species status and pest management aspects, is lacking. Seven populations sampled from the known geographical areas of Bactrocera carambolae including Southeast Asia (i.e., Indonesia, Malaysia, Thailand) and South America (i.e., Suriname), were genotyped using eight microsatellite DNA markers. Genetic variation, genetic structure, and genetic network among populations illustrated that the Suriname samples were genetically differentiated from Southeast Asian populations. The genetic network revealed that samples from West Sumatra (Pekanbaru, PK) and Java (Jakarta, JK) were presumably the source populations of Bactrocera carambolae in Suriname, which was congruent with human migration records between the two continents. Additionally, three populations of Bactrocera dorsalis were included to better understand the species boundary. The genetic structure between the two species was significantly separated and approximately 11% of total individuals were detected as admixed (0.100 ≤ Q ≤ 0.900). The genetic network showed connections between Bactrocera carambolae and Bactrocera dorsalis groups throughout Depok (DP), JK, and Nakhon Sri Thammarat (NT) populations. These data supported the hypothesis that the reproductive isolation between the two species may be leaky. Although the morphology and monophyly of nuclear and mitochondrial DNA sequences in previous studies showed discrete entities, the hypothesis of semipermeable boundaries may not be rejected. Alleles at microsatellite loci could be introgressed rather than other nuclear and mitochondrial DNA. Bactrocera carambolae may be an incipient rather than a distinct species of Bactrocera dorsalis. Regarding the pest management aspect, the genetic sexing Salaya5 strain (SY5) was included for comparison with wild populations. The SY5 strain was genetically assigned to the Bactrocera carambolae cluster. Likewise, the genetic network showed that the strain shared greatest genetic similarity to JK, suggesting that SY5 did not divert away from its original genetic makeup. Under laboratory conditions, at least 12 generations apart, selection did not strongly affect genetic compatibility between the strain and wild populations. This knowledge further confirms the potential utilization of the Salaya5 strain in regional programs of area-wide integrated pest management using SIT.
    Matched MeSH terms: Gene Regulatory Networks
  18. Fulltext Overexpression of endothelin B receptor in glioblastoma: a prognostic marker and therapeutic target?
    Vasaikar S, Tsipras G, Landázuri N, Costa H, Wilhelmi V, Scicluna P, et al.
    BMC Cancer, 2018 02 06;18(1):154.
    PMID: 29409474 DOI: 10.1186/s12885-018-4012-7
    BACKGROUND: Glioblastoma (GBM) is the most common malignant brain tumor with median survival of 12-15 months. Owing to uncertainty in clinical outcome, additional prognostic marker(s) apart from existing markers are needed. Since overexpression of endothelin B receptor (ETBR) has been demonstrated in gliomas, we aimed to test whether ETBR is a useful prognostic marker in GBM and examine if the clinically available endothelin receptor antagonists (ERA) could be useful in the disease treatment.

    METHODS: Data from The Cancer Genome Atlas and the Gene Expression Omnibus database were analyzed to assess ETBR expression. For survival analysis, glioblastoma samples from 25 Swedish patients were immunostained for ETBR, and the findings were correlated with clinical history. The druggability of ETBR was assessed by protein-protein interaction network analysis. ERAs were analyzed for toxicity in in vitro assays with GBM and breast cancer cells.

    RESULTS: By bioinformatics analysis, ETBR was found to be upregulated in glioblastoma patients, and its expression levels were correlated with reduced survival. ETBR interacts with key proteins involved in cancer pathogenesis, suggesting it as a druggable target. In vitro viability assays showed that ERAs may hold promise to treat glioblastoma and breast cancer.

    CONCLUSIONS: ETBR is overexpressed in glioblastoma and other cancers and may be a prognostic marker in glioblastoma. ERAs may be useful for treating cancer patients.

    Matched MeSH terms: Gene Regulatory Networks
  19. Fulltext Understanding Glioblastoma Biomarkers: Knocking a Mountain with a Hammer
    Hassn Mesrati M, Behrooz AB, Y Abuhamad A, Syahir A
    Cells, 2020 05 16;9(5).
    PMID: 32429463 DOI: 10.3390/cells9051236
    Gliomas are the most frequent and deadly form of human primary brain tumors. Among them, the most common and aggressive type is the high-grade glioblastoma multiforme (GBM), which rapidly grows and renders patients a very poor prognosis. Meanwhile, cancer stem cells (CSCs) have been determined in gliomas and play vital roles in driving tumor growth due to their competency in self-renewal and proliferation. Studies of gliomas have recognized CSCs via specific markers. This review comprehensively examines the current knowledge of the most significant CSCs markers in gliomas in general and in glioblastoma in particular and specifically focuses on their outlook and importance in gliomas CSCs research. We suggest that CSCs should be the superior therapeutic approach by directly targeting the markers. In addition, we highlight the association of these markers with each other in relation to their cascading pathways, and interactions with functional miRNAs, providing the role of the networks axes in glioblastoma signaling pathways.
    Matched MeSH terms: Gene Regulatory Networks
  20. Fulltext Research trends in microarray data analysis: modelling gene regulatory network by integrating transcription factors data
    Farzana Kabir Ahmad, Siti Sakira Kamaruddin
    Scientific Research Journal, 2015;12(1):1-10.
    MyJurnal
    The invention of microarray technology has enabled expression levels of thousands of genes to be monitored at once. This modernized approach has created large amount of data to be examined. Recently, gene regulatory network has been an interesting topic and generated impressive research goals in computational biology. Better understanding of the genetic regulatory processes would bring significant implications in the biomedical fields and many other pharmaceutical industries. As a result, various mathematical and computational methods have been used to model gene regulatory network from microarray data. Amongst those methods, the Bayesian network model attracts the most attention and has become the prominent technique since it can capture nonlinear and stochastic relationships between variables. However, structure learning of this model is NP-hard and computationally complex as the number of potential edges increase drastically with the number of genes. In addition, most of the studies only focused on the predicted results while neglecting the fact that microarray data is a fragmented information on the whole biological process. Hence this study proposed a network-based inference model that combined biological knowledge in order to verify the constructed gene regulatory relationships. The gene regulatory network is constructed using Bayesian network based on low-order conditional independence approach. This technique aims to identify from the data the dependencies to construct the network structure, while addressing the structure learning problem. In addition, three main toolkits such as Ensembl, TFSearch and TRANSFAC have been used to determine the false positive edges and verify reliability of regulatory relationships. The experimental results show that by integrating biological knowledge it could enhance the precision results and reduce the number of false positive edges in the trained gene regulatory network.
    Matched MeSH terms: Gene Regulatory Networks
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