Co-regulatory Network Analysis Research Articles

Co-regulatory network analysis of the main secondary metabolite (SM) biosynthesis in Crocus sativus L.

Saffron (Crocus sativus L.) is being embraced as the most important medicinal plant and the commercial source of saffron spice. Despite the beneficial economic and medicinal properties of saffron, the regulatory mechanism of the correlation of TFs and genes related to the biosynthesis of the apocarotenoids pathway is less obvious. Realizing these regulatory hierarchies of gene expression networks related to secondary metabolites production events is the main challenge owing to the complex and extensive interactions between the genetic behaviors. Recently, high throughput expression data have been highly feasible for constructing co-regulation networks to reveal the regulated processes and identifying novel candidate hub genes in response to complex processes of the biosynthesis of secondary metabolites. Herein, we performed Weighted Gene Co-expression Network Analysis (WGCNA), a systems biology method, to identify 11 regulated modules and hub TFs related to secondary metabolites. Three specialized modules were found in the apocarotenoids pathway. Several hub TFs were identified in notable modules, including MADS, C2H2, ERF, bZIP, HD-ZIP, and zinc finger protein MYB and HB, which were potentially associated with apocarotenoid biosynthesis. Furthermore, the expression levels of six hub TFs and six co-regulated genes of apocarotenoids were validated with RT-qPCR. The results confirmed that hub TFs specially MADS, C2H2, and ERF had a high correlation (P < 0.05) and a positive effect on genes under their control in apocarotenoid biosynthesis (CCD2, GLT2, and ADH) among different C. sativus ecotypes in which the metabolite contents were assayed. Promoter analysis of the co-expressed genes of the modules involved in apocarotenoids biosynthesis pathway suggested that not only are the genes co-expressed, but also share common regulatory motifs specially related to hub TFs of each module and that they may describe their common regulation. The result can be used to engineer valuable secondary metabolites of C. sativus by manipulating the hub regulatory TFs.

Bioinformatics and systems biology approaches to identify potential common pathogeneses for sarcopenia and osteoarthritis.

Sarcopenia, a geriatric syndrome characterized by progressive loss of muscle mass and strength, and osteoarthritis, a common degenerative joint disease, are both prevalent in elderly individuals. However, the relationship and molecular mechanisms underlying these two diseases have not been fully elucidated. In this study, we screened microarray data from the Gene Expression Omnibus to identify associations between sarcopenia and osteoarthritis. We employed multiple statistical methods and bioinformatics tools to analyze the shared DEGs (differentially expressed genes). Additionally, we identified 8 hub genes through functional enrichment analysis, protein-protein interaction analysis, transcription factor-gene interaction network analysis, and TF-miRNA coregulatory network analysis. We also discovered potential shared pathways between the two diseases, such as transcriptional misregulation in cancer, the FOXO signalling pathway, and endometrial cancer. Furthermore, based on common DEGs, we found that strophanthidin may be an optimal drug for treating sarcopenia and osteoarthritis, as indicated by the Drug Signatures database. Immune infiltration analysis was also performed on the sarcopenia and osteoarthritis datasets. Finally, receiver operating characteristic (ROC) curves were plotted to verify the reliability of our results. Our findings provide a theoretical foundation for future research on the potential common pathogenesis and molecular mechanisms of sarcopenia and osteoarthritis.

Diagnostic and prognostic value of ferroptosis-related genes in patients with Myelodysplastic neoplasms

ABSTRACT This study delves into the emerging role of ferroptosis in Myelodysplastic Neoplasms (MDS) and aims to identify a prognostic ferroptosis-related gene signature for MDS. Utilizing RNA-seq data and clinical information from the Gene Expression Omnibus database, the researchers extracted ferroptosis-related genes from the FerrDb website and conducted differential expression analysis using the 'limma' package in R. Hub ferroptosis-related genes in MDS were screened using the “RandomForest” and “carat” R packages. Kaplan -Meier and Cox regression analyses were employed to assess the prognostic role of three identified hub genes (BNIP3, MDM2, and RRM2). Receiver operator characteristic curve analysis confirmed the diagnostic efficacy of these genes. The study delved further into immune infiltration correlations, ncRNA-transcription factor coregulatory network analysis, and the identification of potential therapeutic drugs targeting hub ferroptosis-related genes in MDS. The researchers constructed a 3-gene signature-based risk score using datasets GSE58831 and GSE19429, demonstrating high accuracy (AUC > 0.75) in both datasets for survival prediction in MDS. A nomogram analysis reinforced the prognostic value of the risk-scoring model. Immunological analysis revealed an association between the risk score and immune infiltration. Quantitative reverse transcription polymerase chain reaction (qPCR) data indicated significant expression differences in MDM2, RRM2, and BNIP3 between MDS and healthy bone marrow samples. Notably, MDM2 and RRM2 showed decreased expression, while BNIP3 exhibited increased expression in MDS samples. This comprehensive study concludes that BNIP3, MDM2, and RRM2 hold diagnostic and prognostic significance in MDS and provide valuable insights into immune cell landscapes and potential therapeutic avenues for this condition.

Inferring the Regulatory Network of miRNAs on Terpene Trilactone Biosynthesis Affected by Environmental Conditions

As a medicinal tree species, ginkgo (Ginkgo biloba L.) and terpene trilactones (TTLs) extracted from its leaves are the main pharmacologic activity constituents and important economic indicators of its value. The accumulation of TTLs is known to be affected by environmental stress, while the regulatory mechanism of environmental response mediated by microRNAs (miRNAs) at the post-transcriptional levels remains unclear. Here, we focused on grafted ginkgo grown in northwestern, southwestern, and eastern-central China and integrally analyzed RNA-seq and small RNA-seq high-throughput sequencing data as well as metabolomics data from leaf samples of ginkgo clones grown in natural environments. The content of bilobalide was highest among detected TTLs, and there was more than a twofold variation in the accumulation of bilobalide between growth conditions. Meanwhile, transcriptome analysis found significant differences in the expression of 19 TTL-related genes among ginkgo leaves from different environments. Small RNA sequencing and analysis showed that 62 of the 521 miRNAs identified were differentially expressed among different samples, especially the expression of miRN50, miR169h/i, and miR169e was susceptible to environmental changes. Further, we found that transcription factors (ERF, MYB, C3H, HD-ZIP, HSF, and NAC) and miRNAs (miR319e/f, miRN2, miRN54, miR157, miR185, and miRN188) could activate or inhibit the expression of TTL-related genes to participate in the regulation of terpene trilactones biosynthesis in ginkgo leaves by weighted gene co-regulatory network analysis. Our findings provide new insights into the understanding of the regulatory mechanism of TTL biosynthesis but also lay the foundation for ginkgo leaves’ medicinal value improvement under global change.

Early life nutrition affects the molecular ontogeny of testicular development in the young bull calf

Enhanced early life nutrition accelerates sexual development in the bull calf through neuroendocrine-signalling mediated via the hypothalamic–pituitary–testicular axis. Our aim was to assess the impact of contrasting feeding regimes in bull calves during the first 12 weeks of life on the testes transcriptome and proteome. Holstein–Friesian bull calves were offered either a high (HI) or moderate (MOD) plane of nutrition, designed to support target growth rates of 1.0 and 0.5 kg/day, respectively. At 12 weeks of age all calves were euthanized, testicular parenchyma sampled, and global transcriptome (miRNAseq and mRNAseq) and proteome analyses undertaken. Bioinformatic analyses revealed 7 differentially expressed (DE) miRNA and 20 DE mRNA. There were no differentially abundant proteins between the two dietary groups. Integration of omics results highlighted a potential role for the cadherin gene, CDH13, in earlier reproductive development. Furthermore, co-regulatory network analysis of the proteomic data revealed CDH13 as a hub protein within a network enriched for processes related to insulin, IGF-1, androgen and Sertoli cell junction signalling pathways as well as cholesterol biosynthesis. Overall, results highlight a potential role for CDH13 in mediating earlier reproductive development as a consequence of enhanced early life nutrition in the bull calf.

Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer.

Though significant improvements have been made in the treatment methods for ovarian cancer (OC), the prognosis for OC patients is still poor. Exploring hub genes associated with the development of OC and utilizing them as appropriate potential biomarkers or therapeutic targets is highly valuable. In this study, the differentially expressed genes (DEGs) were identified from an independent GSE69428 Gene Expression Omnibus (GEO) dataset between OC and control samples. The DEGs were processed to construct the protein-protein interaction (PPI) network using STRING. Later, hub genes were identified through Cytohubba analysis of the Cytoscape. Expression and survival profiling of the hub genes were validated using GEPIA, OncoDB, and GENT2. For exploring promoter methylation levels and genetic alterations in hub genes, MEXPRESS and cBioPortal were utilized, respectively. Moreover, DAVID, HPA, TIMER, CancerSEA, ENCORI, DrugBank, and GSCAlite were used for gene enrichment analysis, subcellular localization analysis, immune cell infiltration analysis, exploring correlations between hub genes and different diverse states, lncRNA-miRNA-mRNA co-regulatory network analysis, predicting hub gene-associated drugs, and conducting drug sensitivity analysis, respectively. In total, 8947 DEGs were found between OC and normal samples in GSE69428. After STRING and Cytohubba analysis, 4 hub genes including TTK (TTK Protein Kinase), (BUB1 mitotic checkpoint serine/threonine kinase B) BUB1B, (Nucleolar and spindle-associated protein 1) NUSAP1, and (ZW10 interacting kinetochore protein) ZWINT were selected as the hub genes. Further, it was validated that these 4 hub genes were significantly up-regulated in OC samples compared to normal controls, but overexpression of these genes was not associated with overall survival (OS). However, genetic alterations in those genes were found to be linked with OS and disease-free (DFS) survival. Moreover, this study also revealed some novel links between TTK, BUB1B, NUSAP1, and ZWINT overexpression and promoter methylation status, immune cell infiltration, miRNAs, gene enrichment terms, and various chemotherapeutic drugs. Four hub genes, including TTK, BUB1B, NUSAP1, and ZWINT, were revealed as tumor-promotive factors in OC, having the potential to be utilized as novel biomarkers and therapeutic targets for OC management.

Bioinformatics and systems biology approach to identify the pathogenetic link of Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

BackgroundThe COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a global crisis. Although many people recover from COVID-19 infection, they are likely to develop persistent symptoms similar to those of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) after discharge. Those constellations of symptoms persist for months after infection, called Long COVID, which may lead to considerable financial burden and healthcare challenges. However, the mechanisms underlying Long COVID and ME/CFS remain unclear.MethodsWe collected the genes associated with Long COVID and ME/CFS in databases by restricted screening conditions and clinical sample datasets with limited filters. The common genes for Long COVID and ME/CFS were finally obtained by taking the intersection. We performed several advanced bioinformatics analyses based on common genes, including gene ontology and pathway enrichment analyses, protein–protein interaction (PPI) analysis, transcription factor (TF)–gene interaction network analysis, transcription factor–miRNA co-regulatory network analysis, and candidate drug analysis prediction.ResultsWe found nine common genes between Long COVID and ME/CFS and gained a piece of detailed information on their biological functions and signaling pathways through enrichment analysis. Five hub proteins (IL-6, IL-1B, CD8A, TP53, and CXCL8) were collected by the PPI network. The TF–gene and TF–miRNA coregulatory networks were demonstrated by NetworkAnalyst. In the end, 10 potential chemical compounds were predicted.ConclusionThis study revealed common gene interaction networks of Long COVID and ME/CFS and predicted potential therapeutic drugs for clinical practice. Our findings help to identify the potential biological mechanism between Long COVID and ME/CFS. However, more laboratory and multicenter evidence is required to explore greater mechanistic insight before clinical application in the future.

Host Factor Interaction Networks Identified by Integrative Bioinformatics Analysis Reveals Therapeutic Implications in COPD Patients With COVID-19.

Background: The COVID-19 pandemic poses an imminent threat to humanity, especially for those who have comorbidities. Evidence of COVID-19 and COPD comorbidities is accumulating. However, data revealing the molecular mechanism of COVID-19 and COPD comorbid diseases is limited. Methods: We got COVID-19/COPD -related genes from different databases by restricted screening conditions (top500), respectively, and then supplemented with COVID-19/COPD-associated genes (FDR<0.05, |LogFC|≥1) from clinical sample data sets. By taking the intersection, 42 co-morbid host factors for COVID-19 and COPD were finally obtained. On the basis of shared host factors, we conducted a series of bioinformatics analysis, including protein-protein interaction analysis, gene ontology and pathway enrichment analysis, transcription factor-gene interaction network analysis, gene-microRNA co-regulatory network analysis, tissue-specific enrichment analysis and candidate drug prediction. Results: We revealed the comorbidity mechanism of COVID-19 and COPD from the perspective of host factor interaction, obtained the top ten gene and 3 modules with different biological functions. Furthermore, we have obtained the signaling pathways and concluded that dexamethasone, estradiol, progesterone, and nitric oxide shows effective interventions. Conclusion: This study revealed host factor interaction networks for COVID-19 and COPD, which could confirm the potential drugs for treating the comorbidity, ultimately, enhancing the management of the respiratory disease.

Genomic landscape of the immune microenvironments of brain metastases in breast cancer

BackgroundThis study was intended to investigate the genomic landscape of the immune microenvironments of brain metastases in breast cancer.MethodsThree gene expression profile datasets (GSE76714, GSE125989 and GSE43837) of breast cancer with brain metastases were downloaded from Gene Expression Omnibus (GEO) database. After differential expression analysis, the tumor immune microenvironment and immune cell infiltration were analyzed. Then immune-related genes were identified, followed by function analysis, transcription factor (TF)-miRNA–mRNA co-regulatory network analysis, and survival analysis of metastatic recurrence.ResultsThe present results showed that the tumor immune microenvironment in brain metastases was immunosuppressed compared with primary caner. Compared with primary cancer samples, the infiltration ratio of plasma cells in brain metastases samples was significantly higher, while the infiltration ratio of macrophages M2 cells in brain metastases samples was significantly lower. Total 42 immune-related genes were identified, such as THY1 and NEU2. CD1B, THY1 and DOCK2 were found to be implicated in the metastatic recurrence of breast cancer.ConclusionsTargeting macrophages or plasma cells may be new strategies for immunotherapy of breast cancer with brain metastases. THY1 and NEU2 may be potential therapeutic targets for breast cancer with brain metastases, and THY1, CD1B and DOCK2 may serve as potential prognostic markers for improvement of brain metastases survival.

PLCG2 protective variant p.P522R modulates tau pathology and disease progression in patients with mild cognitive impairment

A rare coding variant (rs72824905, p.P522R) conferring protection against Alzheimer’s disease (AD) was identified in the gene encoding the enzyme phospholipase-C-γ2 (PLCG2) that is highly expressed in microglia. To explore the protective nature of this variant, we employed latent process linear mixed models to examine the association of p.P522R with longitudinal cognitive decline in 3595 MCI patients, and in 10,097 individuals from population-based studies. Furthermore, association with CSF levels of pTau181, total tau, and Aβ1-42 was assessed in 1261 MCI patients. We found that MCI patients who carried the p.P522R variant showed a slower rate of cognitive decline compared to non-carriers and that this effect was mediated by lower pTau181 levels in CSF. The effect size of the association of p.P522R with the cognitive decline and pTau181 was similar to that of APOE-ε4, the strongest genetic risk factor for AD. Interestingly, the protective effect of p.P522R was more pronounced in MCI patients with low Aβ1-42 levels suggesting a role of PLCG2 in the response to amyloid pathology. In line with this hypothesis, we observed no protective effect of the PLCG2 variant on the cognitive decline in population-based studies probably due to the lower prevalence of amyloid positivity in these samples compared to MCI patients. Concerning the potential biological underpinnings, we identified a network of co-expressed proteins connecting PLCG2 to APOE and TREM2 using unsupervised co-regulatory network analysis. The network was highly enriched for the complement cascade and genes differentially expressed in disease-associated microglia. Our data show that p.P522R in PLCG2 reduces AD disease progression by mitigating tau pathology in the presence of amyloid pathology and, as a consequence, maintains cognitive function. Targeting the enzyme PLCG2 might provide a new therapeutic approach for treating AD.

Identification, Evolution, and Expression Profiling of Histone Lysine Methylation Moderators in Brassica rapa.

Histone modifications, such as methylation and demethylation, are vital for regulating chromatin structure, thus affecting its expression patterns. The objective of this study is to understand the phylogenetic relationships, genomic organization, diversification of motif modules, gene duplications, co-regulatory network analysis, and expression dynamics of histone lysine methyltransferases and histone demethylase in Brassica rapa. We identified 60 SET (HKMTases), 53 JmjC, and 4 LSD (HDMases) genes in B. rapa. The domain composition analysis subcategorized them into seven and nine subgroups, respectively. Duplication analysis for paralogous pairs of SET and JmjC (eight and nine pairs, respectively) exhibited variation. Interestingly, three pairs of SET exhibited Ka/Ks > 1.00 values, signifying positive selection, whereas the remaining underwent purifying selection with values less than 1.00. Furthermore, RT-PCR validation analysis and RNA-sequence data acquired on six different tissues (i.e., leaf, stem, callus, silique, flower, and root) revealed dynamic expression patterns. This comprehensive study on the abundance, classification, co-regulatory network analysis, gene duplication, and responses to heat and cold stress of SET and JmjC provides insights into the structure and diversification of these family members in B. rapa. This study will be helpful to reveal functions of these putative SET and JmjC genes in B. rapa.

Transcriptional variation is associated with differences in shoot sodium accumulation in distinct barley varieties

Soil salinity causes large productivity losses for agriculture worldwide. Barley has been identified as one of the more salt tolerant staple crops compared to wheat and rice. Identification of genes and allelic variations underlying various salt tolerance mechanisms in barley will be a practical contribution towards the development of cereal lines with greater salinity tolerance. Here, RNA from six barley varieties with varying leaf blade and sheath Na+ accumulation following salt (NaCl) treatment were sequenced. Differential gene expression analysis, variant calling and gene co-regulatory network analysis was conducted to identify potential molecular components underlying the shoot Na+ phenotypes. We identified novel alleles of HKT1;5 that could be responsible for high Na+ accumulation in blade and sheath. Furthermore, through statistical modelling of gene expression, a Na+/H+ Exchanger (NHX) gene was identified as a candidate for high sheath Na+ accumulation. Through co-expression networks, we discovered expression pattern variation for genes related to terpenoid phenylpropanoid and flavonoid metabolism amongst the six varieties. The gene candidates identified in this study provide us with targets of interest for future characterisation of molecular mechanisms that may contribute to salt stress tolerance in barley.

Functional prediction of miR-3144-5p in human cardiac myocytes based on transcriptome sequencing and bioinformatics

Background:RAN guanine nucleotide release factor (RANGRF) encoding protein MOG1 plays an important role in cardiac arrhythmia, so we intended to investigate the regulatory miRNA of RANGRF and explore its potential regulatory mechanism in arrhythmogenesis.Methods:Based on bioinformatic analysis, miR-3144-5p was predicted to be a regulatory miRNA of RANGRF, which were then validated through a dual-luciferase reporter plasmid assay. Subsequently, the expression level of miR-3144-5p in human cardiac myocytes (HCMs) was detected, followed by cell transfection with miR-3144-5p mimics. Transcriptome sequencing was then performed in HCMs with or without transfection. The sequencing results were subjected to bioinformatic analyses, including differentially expressed gene (DEG) analysis, functional enrichment analysis, protein–protein interaction (PPI) network analysis, miRNA-target gene analysis, and miRNA-transcription factor (TF)-target gene coregulatory network analysis.Results:There really existed a regulatory relation between miR-3144-5p and RANGRF. The expression level of miR-3144-5p was low in HCMs. After cell transfection, miR-3144-5p expression level significantly increased in HCMs. Bioinformatic analyses of the transcriptome sequencing results identified 300 upregulated and 271 downregulated DEGs between miR-3144-5p mimic and control group. The upregulated genes ISL1 and neuregulin 1 (NRG1) were significantly enriched in cardiac muscle cell myoblast differentiation (GO:0060379). CCL21 was one of the hub genes in the PPI network and also a target gene of miR-3144-5p. Moreover, the TF of v-Myc avian myelocytomatosis viral oncogene neuroblastoma-derived homolog (MYCN) was involved in the miR-3144-5p-TF-target gene coregulatory network and interacted with the target genes of miR-3144-5p.Conclusion:ISL1, NRG1, CCL21, and MYCN were differentially expressed in the miR-3144-5p mimic group, suggesting that miR-3144-5p overexpression plays a role in HCMs by regulating these genes and TF. This study may provide new insight into the mechanisms behind the progression of cardiac arrhythmia.

Transcriptional Regulatory Network Analysis of MYB Transcription Factor Family Genes in Rice.

MYB transcription factor (TF) is one of the largest TF families and regulates defense responses to various stresses, hormone signaling as well as many metabolic and developmental processes in plants. Understanding these regulatory hierarchies of gene expression networks in response to developmental and environmental cues is a major challenge due to the complex interactions between the genetic elements. Correlation analyses are useful to unravel co-regulated gene pairs governing biological process as well as identification of new candidate hub genes in response to these complex processes. High throughput expression profiling data are highly useful for construction of co-expression networks. In the present study, we utilized transcriptome data for comprehensive regulatory network studies of MYB TFs by “top-down” and “guide-gene” approaches. More than 50% of OsMYBs were strongly correlated under 50 experimental conditions with 51 hub genes via “top-down” approach. Further, clusters were identified using Markov Clustering (MCL). To maximize the clustering performance, parameter evaluation of the MCL inflation score (I) was performed in terms of enriched GO categories by measuring F-score. Comparison of co-expressed cluster and clads analyzed from phylogenetic analysis signifies their evolutionarily conserved co-regulatory role. We utilized compendium of known interaction and biological role with Gene Ontology enrichment analysis to hypothesize function of coexpressed OsMYBs. In the other part, the transcriptional regulatory network analysis by “guide-gene” approach revealed 40 putative targets of 26 OsMYB TF hubs with high correlation value utilizing 815 microarray data. The putative targets with MYB-binding cis-elements enrichment in their promoter region, functional co-occurrence as well as nuclear localization supports our finding. Specially, enrichment of MYB binding regions involved in drought-inducibility implying their regulatory role in drought response in rice. Thus, the co-regulatory network analysis facilitated the identification of complex OsMYB regulatory networks, and candidate target regulon genes of selected guide MYB genes. The results contribute to the candidate gene screening, and experimentally testable hypotheses for potential regulatory MYB TFs, and their targets under stress conditions.

MiRNA and TF co-regulatory network analysis for the pathology and recurrence of myocardial infarction.

Myocardial infarction (MI) is a leading cause of death in the world and many genes are involved in it. Transcription factor (TFs) and microRNAs (miRNAs) are key regulators of gene expression. We hypothesized that miRNAs and TFs might play combinatory regulatory roles in MI. After collecting MI candidate genes and miRNAs from various resources, we constructed a comprehensive MI-specific miRNA-TF co-regulatory network by integrating predicted and experimentally validated TF and miRNA targets. We found some hub nodes (e.g. miR-16 and miR-26) in this network are important regulators, and the network can be severed as a bridge to interpret the associations of previous results, which is shown by the case of miR-29 in this study. We also constructed a regulatory network for MI recurrence and found several important genes (e.g. DAB2, BMP6, miR-320 and miR-103), the abnormal expressions of which may be potential regulatory mechanisms and markers of MI recurrence. At last we proposed a cellular model to discuss major TF and miRNA regulators with signaling pathways in MI. This study provides more details on gene expression regulation and regulators involved in MI progression and recurrence. It also linked up and interpreted many previous results.

Overexpression of E2F mRNAs associated with gastric cancer progression identified by the transcription factor and miRNA co-regulatory network analysis.

Gene expression is regulated at the transcription and translation levels; thus, both transcription factors (TFs) and microRNAs (miRNA) play roles in regulation of gene expression. This study profiled differentially expressed mRNAs and miRNAs in gastric cancer tissues to construct a TF and miRNA co-regulatory network in order to identify altered genes in gastric cancer progression. A total of 70 cases gastric cancer and paired adjacent normal tissues were subjected to cDNA and miRNA microarray analyses. We obtained 887 up-regulated and 93 down-regulated genes and 41 down-regulated and 4 up-regulated miRNAs in gastric cancer tissues. Using the Transcriptional Regulatory Element Database, we obtained 105 genes that are regulated by the E2F family of genes and using Targetscan, miRanda, miRDB and miRWalk tools, we predicted potential targeting genes of these 45 miRNAs. We then built up the E2F-related TF and miRNA co-regulatory gene network and identified 9 hub-genes. Furthermore, we found that levels of E2F1, 2, 3, 4, 5, and 7 mRNAs associated with gastric cancer cell invasion capacity, and has associated with tumor differentiation. These data showed Overexpression of E2F mRNAs associated with gastric cancer progression.

Comparative genomic analysis of NAC transcriptional factors to dissect the regulatory mechanisms for cell wall biosynthesis

BackgroundNAC domain transcription factors are important transcriptional regulators involved in plant growth, development and stress responses. Recent studies have revealed several classes of NAC transcriptional factors crucial for controlling secondary cell wall biosynthesis. These transcriptional factors mainly include three classes, SND, NST and VND. Despite progress, most current analysis is carried out in the model plant Arabidopsis. Moreover, many downstream genes regulated by these transcriptional factors are still not clear.MethodsIn order to identify the key homologue genes across species and discover the network controlling cell wall biosynthesis, we carried out comparative genome analysis of NST, VND and SND genes across 19 higher plant species along with computational modelling of genes regulated or co-regulated with these transcriptional factors.ResultsThe comparative genome analysis revealed that evolutionarily the secondary-wall-associated NAC domain transcription factors first appeared in Selaginella moellendorffii. In fact, among the three groups, only VND genes appeared in S. moellendorffii, which is evolutionarily earlier than the other two groups. The Arabidopsis and rice gene expression analysis showed specific patterns of the secondary cell wall-associated NAC genes (SND, NST and VND). Most of them were preferentially expressed in the stem, especially the second internodes. Furthermore, comprehensive co-regulatory network analysis revealed that the SND and MYB genes were co-regulated, which indicated the coordinative function of these transcriptional factors in modulating cell wall biosynthesis. In addition, the co-regulatory network analysis revealed many novel genes and pathways that could be involved in cell wall biosynthesis and its regulation. The gene ontology analysis also indicated that processes like carbohydrate synthesis, transport and stress response, are coordinately regulated toward cell wall biosynthesis.ConclusionsOverall, we provided a new insight into the evolution and the gene regulatory network of a subgroup of the NAC gene family controlling cell wall composition through bioinformatics data mining and bench validation. Our work might benefit to elucidate the possible molecular mechanism underlying the regulation network of secondary cell wall biosynthesis.

MicroRNA and transcription factor co-regulatory network analysis reveals miR-19 inhibits CYLD in T-cell acute lymphoblastic leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy. The understanding of its gene expression regulation and molecular mechanisms still remains elusive. Started from experimentally verified T-ALL-related miRNAs and genes, we obtained 120 feed-forward loops (FFLs) among T-ALL-related genes, miRNAs and TFs through combining target prediction. Afterwards, a T-ALL miRNA and TF co-regulatory network was constructed, and its significance was tested by statistical methods. Four miRNAs in the miR-17–92 cluster and four important genes (CYLD, HOXA9, BCL2L11 and RUNX1) were found as hubs in the network. Particularly, we found that miR-19 was highly expressed in T-ALL patients and cell lines. Ectopic expression of miR-19 represses CYLD expression, while miR-19 inhibitor treatment induces CYLD protein expression and decreases NF-κB expression in the downstream signaling pathway. Thus, miR-19, CYLD and NF-κB form a regulatory FFL, which provides new clues for sustained activation of NF-κB in T-ALL. Taken together, we provided the first miRNA-TF co-regulatory network in T-ALL and proposed a model to demonstrate the roles of miR-19 and CYLD in the T-cell leukemogenesis. This study may provide potential therapeutic targets for T-ALL and shed light on combining bioinformatics with experiments in the research of complex diseases.

Genetic Regulatory Network Analysis for &lt;i&gt;Rpe65&lt;/i&gt; in the Eye of BXD Mice

Previous studies have revealed that the mutation of Rpe65plays a critical role in inherited retinal dystrophies. However, little is known about the genetic regulatory network for Rpe65 and inherited retinal dystrophies. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Rpe65 expression in the eye of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Rpe65exhibited much variation in the eye across the BXD RI strains and between the parental strains, C57BL/6J and DBA/2J. Expression QTL (eQTL) mapping showed that one microarray probe set of Rpe65 has highly significant linkage (Likelihood Ratio Statistic) scores. Moreover, the QTL was mapped to within 3 Mb of the location of the gene itself (Rpe65) as a cis-acting QTL. Through mapping the joint modulation of Rpe65, we identified Ches1/Foxn3 as downstream gene of Rpe65. Then the gene co-regulatory network analysis was constructed. The genetic genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to inherited retinal dystrophies.

Expression quantitative trait loci and genetic regulatory network analysis reveals that Gabra2 is involved in stress responses in the mouse

Previous studies have revealed that the subunit α 2 (Gabra2) of the γ-aminobutyric acid receptor plays a critical role in the stress response. However, little is known about the gentetic regulatory network for Gabra2 and the stress response. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Gabra2 expression in the hippocampus of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Gabra2 exhibited much variation in the hippocampus across the BXD RI strains and between the parental strains, C57BL/6J, and DBA/2J. Expression QTL (eQTL) mapping showed three microarray probe sets of Gabra2 to have highly significant linkage likelihood ratio statistic (LRS) scores. Gene co-regulatory network analysis showed that 10 genes, including Gria3, Chka, Drd3, Homer1, Grik2, Odz4, Prkag2, Grm5, Gabrb1, and Nlgn1 are directly or indirectly associated with stress responses. Eleven genes were implicated as Gabra2 downstream genes through mapping joint modulation. The genetical genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to complex traits, such as stress responses.