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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
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*
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*
Fulltext A side-effect free method for identifying cancer drug targets

Ashraf MI, Ong SK, Mujawar S, Pawar S, More P, Paul S, et al.

Sci Rep, 2018 04 27;8(1):6669.
PMID: 29703908 DOI: 10.1038/s41598-018-25042-2

Identifying effective drug targets, with little or no side effects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side effect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identification of effective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying effective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as effective candidates for drug development.

Matched MeSH terms: Gene Regulatory Networks/drug effects
Biomarkers for ischemic stroke subtypes: A protein-protein interaction analysis

Wei LK, Quan LS

Comput Biol Chem, 2019 Dec;83:107116.
PMID: 31561071 DOI: 10.1016/j.compbiolchem.2019.107116

According to the Trial of Org 10172 in Acute Stroke Treatment, ischemic stroke is classified into five subtypes. However, the predictive biomarkers of ischemic stroke subtypes are still largely unknown. The utmost objective of this study is to map, construct and analyze protein-protein interaction (PPI) networks for all subtypes of ischemic stroke, and to suggest the predominant biological pathways for each subtypes. Through 6285 protein data retrieved from PolySearch2 and STRING database, the first PPI networks for all subtypes of ischemic stroke were constructed. Notably, F2 and PLG were identified as the critical proteins for large artery atherosclerosis (LAA), lacunar, cardioembolic, stroke of other determined etiology (SOE) and stroke of undetermined etiology (SUE). Gene ontology and DAVID analysis revealed that GO:0030193 regulation of blood coagulation and GO:0051917 regulation of fibrinolysis were the important functional clusters for all the subtypes. In addition, inflammatory pathway was the key etiology for LAA and lacunar, while FOS and JAK2/STAT3 signaling pathways might contribute to cardioembolic stroke. Due to many risk factors associated with SOE and SUE, the precise etiology for these two subtypes remained to be concluded.

Matched MeSH terms: Gene Regulatory Networks
Blood gene signature for early hepatocellular carcinoma detection in patients with chronic hepatitis B

Omar H, Lim CR, Chao S, Lee MM, Bong CW, Ooi EJ, et al.

J Clin Gastroenterol, 2015 Feb;49(2):150-7.
PMID: 25569223 DOI: 10.1097/MCG.0000000000000112

Up to 25% of chronic hepatitis B (CHB) patients eventually develop hepatocellular carcinoma (HCC), a disease with poor prognosis unless detected early. This study identifies a blood-based RNA biomarker panel for early HCC detection in CHB.

Matched MeSH terms: Gene Regulatory Networks
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
Fulltext Circular RNA- and microRNA-Mediated Post-Transcriptional Regulation of Preadipocyte Differentiation in Adipogenesis: From Expression Profiling to Signaling Pathway

Huang CJ, Choo KB

Int J Mol Sci, 2023 Feb 25;24(5).
PMID: 36901978 DOI: 10.3390/ijms24054549

Adipogenesis is an indispensable cellular process that involves preadipocyte differentiation into mature adipocyte. Dysregulated adipogenesis contributes to obesity, diabetes, vascular conditions and cancer-associated cachexia. This review aims to elucidate the mechanistic details on how circular RNA (circRNA) and microRNA (miRNA) modulate post-transcriptional expression of targeted mRNA and the impacted downstream signaling and biochemical pathways in adipogenesis. Twelve adipocyte circRNA profiling and comparative datasets from seven species are analyzed using bioinformatics tools and interrogations of public circRNA databases. Twenty-three circRNAs are identified in the literature that are common to two or more of the adipose tissue datasets in different species; these are novel circRNAs that have not been reported in the literature in relation to adipogenesis. Four complete circRNA-miRNA-mediated modulatory pathways are constructed via integration of experimentally validated circRNA-miRNA-mRNA interactions and the downstream signaling and biochemical pathways involved in preadipocyte differentiation via the PPARγ/C/EBPα gateway. Despite the diverse mode of modulation, bioinformatics analysis shows that the circRNA-miRNA-mRNA interacting seed sequences are conserved across species, supporting mandatory regulatory functions in adipogenesis. Understanding the diverse modes of post-transcriptional regulation of adipogenesis may contribute to the development of novel diagnostic and therapeutic strategies for adipogenesis-associated diseases and in improving meat quality in the livestock industries.

Matched MeSH terms: Gene Regulatory Networks
Fulltext Comparative analysis of cardiovascular development related genes in stem cells isolated from deciduous pulp and adipose tissue

Loo ZX, Kunasekaran W, Govindasamy V, Musa S, Abu Kasim NH

ScientificWorldJournal, 2014;2014:186508.
PMID: 25548778 DOI: 10.1155/2014/186508

Human exfoliated deciduous teeth (SHED) and adipose stem cells (ASC) were suggested as alternative cell choice for cardiac regeneration. However, the true functionability of these cells toward cardiac regeneration is yet to be discovered. Hence, this study was carried out to investigate the innate biological properties of these cell sources toward cardiac regeneration. Both cells exhibited indistinguishable MSCs characteristics. Human stem cell transcription factor arrays were used to screen expression levels in SHED and ASC. Upregulated expression of transcription factor (TF) genes was detected in both sources. An almost equal percentage of >2-fold changes were observed. These TF genes fall under several cardiovascular categories with higher expressions which were observed in growth and development of blood vessel, angiogenesis, and vasculogenesis categories. Further induction into cardiomyocyte revealed ASC to express more significantly cardiomyocyte specific markers compared to SHED during the differentiation course evidenced by morphology and gene expression profile. Despite this, spontaneous cellular beating was not detected in both cell lines. Taken together, our data suggest that despite being defined as MSCs, both ASC and SHED behave differently when they were cultured in a same cardiomyocytes culture condition. Hence, vigorous characterization is needed before introducing any cell for treating targeted diseases.

Matched MeSH terms: Gene Regulatory Networks
Fulltext Comparative genome-wide analysis of WRKY, MADS-box and MYB transcription factor families in Arabidopsis and rice

Abdullah-Zawawi MR, Ahmad-Nizammuddin NF, Govender N, Harun S, Mohd-Assaad N, Mohamed-Hussein ZA

Sci Rep, 2021 10 04;11(1):19678.
PMID: 34608238 DOI: 10.1038/s41598-021-99206-y

Transcription factors (TFs) form the major class of regulatory genes and play key roles in multiple plant stress responses. In most eukaryotic plants, transcription factor (TF) families (WRKY, MADS-box and MYB) activate unique cellular-level abiotic and biotic stress-responsive strategies, which are considered as key determinants for defense and developmental processes. Arabidopsis and rice are two important representative model systems for dicot and monocot plants, respectively. A comprehensive comparative study on 101 OsWRKY, 34 OsMADS box and 122 OsMYB genes (rice genome) and, 71 AtWRKY, 66 AtMADS box and 144 AtMYB genes (Arabidopsis genome) showed various relationships among TFs across species. The phylogenetic analysis clustered WRKY, MADS-box and MYB TF family members into 10, 7 and 14 clades, respectively. All clades in WRKY and MYB TF families and almost half of the total number of clades in the MADS-box TF family are shared between both species. Chromosomal and gene structure analysis showed that the Arabidopsis-rice orthologous TF gene pairs were unevenly localized within their chromosomes whilst the distribution of exon-intron gene structure and motif conservation indicated plausible functional similarity in both species. The abiotic and biotic stress-responsive cis-regulatory element type and distribution patterns in the promoter regions of Arabidopsis and rice WRKY, MADS-box and MYB orthologous gene pairs provide better knowledge on their role as conserved regulators in both species. Co-expression network analysis showed the correlation between WRKY, MADs-box and MYB genes in each independent rice and Arabidopsis network indicating their role in stress responsiveness and developmental processes.

Matched MeSH terms: Gene Regulatory Networks
Fulltext Comprehensive functional profiling of long non-coding RNAs through a novel pan-cancer integration approach and modular analysis of their protein-coding gene association networks

Walters K, Sarsenov R, Too WS, Hare RK, Paterson IC, Lambert DW, et al.

BMC Genomics, 2019 Jun 03;20(1):454.
PMID: 31159744 DOI: 10.1186/s12864-019-5850-7

BACKGROUND: Long non-coding RNAs (lncRNAs) are emerging as crucial regulators of cellular processes in diseases such as cancer, although the functions of most remain poorly understood. To address this, here we apply a novel strategy to integrate gene expression profiles across 32 cancer types, and cluster human lncRNAs based on their pan-cancer protein-coding gene associations. By doing so, we derive 16 lncRNA modules whose unique properties allow simultaneous inference of function, disease specificity and regulation for over 800 lncRNAs.
RESULTS: Remarkably, modules could be grouped into just four functional themes: transcription regulation, immunological, extracellular, and neurological, with module generation frequently driven by lncRNA tissue specificity. Notably, three modules associated with the extracellular matrix represented potential networks of lncRNAs regulating key events in tumour progression. These included a tumour-specific signature of 33 lncRNAs that may play a role in inducing epithelial-mesenchymal transition through modulation of TGFβ signalling, and two stromal-specific modules comprising 26 lncRNAs linked to a tumour suppressive microenvironment and 12 lncRNAs related to cancer-associated fibroblasts. One member of the 12-lncRNA signature was experimentally supported by siRNA knockdown, which resulted in attenuated differentiation of quiescent fibroblasts to a cancer-associated phenotype.
CONCLUSIONS: Overall, the study provides a unique pan-cancer perspective on the lncRNA functional landscape, acting as a global source of novel hypotheses on lncRNA contribution to tumour progression.

Matched MeSH terms: Gene Regulatory Networks*
Fulltext Concentration Dependent Effect of Human Dermal Fibroblast Conditioned Medium (DFCM) from Three Various Origins on Keratinocytes Wound Healing

Maarof M, Chowdhury SR, Saim A, Bt Hj Idrus R, Lokanathan Y

Int J Mol Sci, 2020 Apr 22;21(8).
PMID: 32331278 DOI: 10.3390/ijms21082929

Fibroblasts secrete many essential factors that can be collected from fibroblast culture medium, which is termed dermal fibroblast conditioned medium (DFCM). Fibroblasts isolated from human skin samples were cultured in vitro using the serum-free keratinocyte-specific medium (Epilife (KM1), or define keratinocytes serum-free medium, DKSFM (KM2) and serum-free fibroblast-specific medium (FM) to collect DFCM-KM1, DFCM-KM2, and DFCM-FM, respectively). We characterised and evaluated the effects of 100-1600 µg/mL DFCM on keratinocytes based on attachment, proliferation, migration and gene expression. Supplementation with 200-400 µg/mL keratinocyte-specific DFCM-KM1 and DFCM-KM2 enhanced the attachment, proliferation and migration of sub-confluent keratinocytes, whereas 200-1600 µg/mL DFCM-FM significantly increased the healing rate in the wound healing assay, and 400-800 µg/mL DFCM-FM was suitable to enhance keratinocyte attachment and proliferation. A real-time (RT2) profiler polymerase chain reaction (PCR) array showed that 42 genes in the DFCM groups had similar fold regulation compared to the control group and most of the genes were directly involved in wound healing. In conclusion, in vitro keratinocyte re-epithelialisation is supported by the fibroblast-secreted proteins in 200-400 µg/mL DFCM-KM1 and DFCM-KM2, and 400-800 µg/mL DFCM-FM, which could be useful for treating skin injuries.

Matched MeSH terms: Gene Regulatory Networks
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
Fulltext Decoding the differentiation of mesenchymal stem cells into mesangial cells at the transcriptomic level

Wong CY, Chang YM, Tsai YS, Ng WV, Cheong SK, Chang TY, et al.

BMC Genomics, 2020 Jul 07;21(1):467.
PMID: 32635896 DOI: 10.1186/s12864-020-06868-5

BACKGROUND: Mesangial cells play an important role in the glomerulus to provide mechanical support and maintaine efficient ultrafiltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) can differentiate into many cell types, including mesangial cells. However transcriptomic profiling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells, to understand the involvement of transcription factor (TF) along the differentiation process, and finally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells.
RESULTS: Several ascending and descending monotonic key genes were identified by Monotonic Feature Selector. The identified descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were arranged in a co-expression network in order of time by Time-Ordered Gene Co-expression Network (TO-GCN) analysis. TO-GCN analysis can classify the differentiation process into three stages: differentiation preparation, differentiation initiation and maturation. Furthermore, it can also explore TF-TF-key genes regulatory relationships in the muscle contraction process.
CONCLUSIONS: A systematic analysis for transcriptomic profiling of MSC differentiation into mesangial cells has been established. Key genes or biomarkers, TFs and pathways involved in differentiation of MSC-mesangial cells have been identified and the related biological implications have been discussed. Finally, we further elucidated for the first time the three main stages of mesangial cell differentiation, and the regulatory relationships between TF-TF-key genes involved in the muscle contraction process. Through this study, we have increased fundamental understanding of the gene transcripts during the differentiation of MSC into mesangial cells.

Matched MeSH terms: Gene Regulatory Networks
Fulltext Differentially expressed genes on the growth of mouse Leydig cells treated with standardised Eurycoma longifolia extract

Khurshid Ahmed NA, Lim SK, Pandian GN, Sugiyama H, Lee CY, Khoo BY, et al.

Mol Med Rep, 2020 Nov;22(5):3645-3658.
PMID: 32901880 DOI: 10.3892/mmr.2020.11485

Eurycoma (E.) longifolia Jack (Tongkat Ali) is a widely applied medicine that has been reported to boost serum testosterone and increase muscle mass. However, its actual biological targets and effects on an in vitro level remain poorly understood. Therefore, the present study aimed to investigate the effects of a standardised E. longifolia extract (F2) on the growth and its associated gene expression profile in mouse Leydig cells. F2, even at lower doses, was found to induce a high level of testosterone by ELISA. The level was as high as the levels induced by eurycomanone and formestane in Leydig cells. However, Leydig cells treated with F2 demonstrated reduced viability, which was likely due to the diminished cell population at the G0/G1 phase and increased cell population arrested at the S phase in the cell cycle, as assessed by MTT assay and flow cytometry, respectively. Cell viability was revived when the treatment time‑point was prolonged to 96 h. Genome‑wide gene analysis by reverse transcription‑quantitative PCR of F2‑treated Leydig cells at 72 h, when the cell growth was not revived, and 96 h, when the cell growth had started to revive, revealed cyclin‑dependent kinase‑like 2 (CDKL2) to be a potential target in regulating the viability of F2‑treated Leydig cells. Functional analysis, as analysed using GeneMANIA Cytoscape program v.3.6.0 (https://genemania.org/), further suggested that CDKL2 could act in concert with Casitas B‑lineage lymphoma and sphingosine kinase 1 interactor‑A‑kinase anchoring protein domain‑containing genes to regulate the viability of F2‑treated Leydig cells. The findings of the present study provide new insights regarding the potential molecular targets associated with the biological effect of E. longifolia extract on cell growth, particularly on the cell cycle, which could aid in enhancing the bioefficacy and reducing the toxicity of this natural product in the future.

Matched MeSH terms: Gene Regulatory Networks/drug effects*
Discovery of precursor and mature microRNAs and their putative gene targets using high-throughput sequencing in pineapple (Ananas comosus var. comosus)

Yusuf NH, Ong WD, Redwan RM, Latip MA, Kumar SV

Gene, 2015 Oct 15;571(1):71-80.
PMID: 26115767 DOI: 10.1016/j.gene.2015.06.050

MicroRNAs (miRNAs) are a class of small, endogenous non-coding RNAs that negatively regulate gene expression, resulting in the silencing of target mRNA transcripts through mRNA cleavage or translational inhibition. MiRNAs play significant roles in various biological and physiological processes in plants. However, the miRNA-mediated gene regulatory network in pineapple, the model tropical non-climacteric fruit, remains largely unexplored. Here, we report a complete list of pineapple mature miRNAs obtained from high-throughput small RNA sequencing and precursor miRNAs (pre-miRNAs) obtained from ESTs. Two small RNA libraries were constructed from pineapple fruits and leaves, respectively, using Illumina's Solexa technology. Sequence similarity analysis using miRBase revealed 579,179 reads homologous to 153 miRNAs from 41 miRNA families. In addition, a pineapple fruit transcriptome library consisting of approximately 30,000 EST contigs constructed using Solexa sequencing was used for the discovery of pre-miRNAs. In all, four pre-miRNAs were identified (MIR156, MIR399, MIR444 and MIR2673). Furthermore, the same pineapple transcriptome was used to dissect the function of the miRNAs in pineapple by predicting their putative targets in conjunction with their regulatory networks. In total, 23 metabolic pathways were found to be regulated by miRNAs in pineapple. The use of high-throughput sequencing in pineapples to unveil the presence of miRNAs and their regulatory pathways provides insight into the repertoire of miRNA regulation used exclusively in this non-climacteric model plant.

Matched MeSH terms: Gene Regulatory Networks
Fulltext Drought Response in Rice: The miRNA Story

Nadarajah K, Kumar IS

Int J Mol Sci, 2019 Aug 01;20(15).
PMID: 31374851 DOI: 10.3390/ijms20153766

As a semi-aquatic plant, rice requires water for proper growth, development, and orientation of physiological processes. Stress is induced at the cellular and molecular level when rice is exposed to drought or periods of low water availability. Plants have existing defense mechanisms in planta that respond to stress. In this review we examine the role played by miRNAs in the regulation and control of drought stress in rice through a summary of molecular studies conducted on miRNAs with emphasis on their contribution to drought regulatory networks in comparison to other plant systems. The interaction between miRNAs, target genes, transcription factors and their respective roles in drought-induced stresses is elaborated. The cross talk involved in controlling drought stress responses through the up and down regulation of targets encoding regulatory and functional proteins is highlighted. The information contained herein can further be explored to identify targets for crop improvement in the future.

Matched MeSH terms: Gene Regulatory Networks
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
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
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

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