Global Analysis of Enhancer Targets Reveals Convergent Enhancer-Driven Regulatory Modules

Single-cell screens enable high-throughput functional assessment of enhancers in their endogenous genomic context. However, the design of current studies limits their application to identifying the primary gene targets of enhancers. Here, we improve the experimental and computational parameters of single-cell enhancer screens to identify the secondary gene targets of enhancers. Our analysis of >500 putative enhancers in K562 cells reveals an interwoven enhancer-driven gene regulatory network. We find that enhancers from distinct genomic loci converge to modulate the expression of common sub-modules, including the α- and β-globin loci, by directly regulating transcription factors. Our analysis suggests that several genetic variants associated with myeloid blood cell traits alter the activity of a distal enhancer of MYB (~140 kb away), with downstream consequences on hemoglobin genes expression and cell state. These data have implications for the understanding of enhancer-associated traits and emphasize the flexibility of controlling transcriptional systems by modifying enhancer activity.

Xie et al. apply improved strategies for single-cell screens to identify an enhancer-driven transcriptional regulatory network in K562 cells. They demonstrate that the same group of genes can be indirectly regulated by enhancers from distinct genomic loci. These data have implications for the understanding of enhancer-associated traits.

mRNA and P-element-induced wimpy testis-interacting RNA profile in chemical-induced oral squamous cell carcinoma mice model

P-element-induced wimpy testis (PIWI)-interacting RNAs (piRNAs), a novel class of noncoding RNAs, are involved in the carcinogenesis. However, the functional significance of piRNAs in oral squamous cell carcinoma (OSCC) remains unknown. In the present study, we used chemical carcinogen 4-nitroquinoline-1-oxide (4NQO) induced OSCC mouse model. piRNAs and mRNAs were profiled using next-generation sequencing in the tongue tumor tissues from 4NQO induction and healthy tongue tissues from control mice. Furthermore, we analyzed the differential gene expression of human OSCC in Gene Expression Omnibus (GEO) database. According to the common differentially expressed genes in the 4NQO model and human OSCC tissues, piRNAs and mRNAs network were established based on informatics method. A total of 14 known piRNAs and 435 novel predicted piRNAs were differently expressed in tumor tissue compared to healthy tissue. Among differently expressed piRNAs 260 were downregulated, and 189 were upregulated. The mRNA targets for the differentially expressed piRNAs were identified using RNAhybrid software. Primary immunodeficiency and herpes simplex infection were the most enriched pathways. A total of 22 mRNAs overlapped in human and mice OSCC. Moreover, we established the regulatory network of 11 mRNAs, including Tmc5, Galnt6, Spedf, Mybl2, Muc5b, Six31, Pigr, Lamc2, Mmp13, Mal, and Mamdc2, and 11 novel piRNAs. Our data showed the interaction between piRNAs and mRNAs in OSCC, which might provide new insights in the development of diagnostic biomarkers and therapeutic targets of OSCC.

Psychiatric Genetics, Epigenetics, and Cellular Models in Coming Years

Psychiatric genetic studies have uncovered hundreds of loci associated with various psychiatric disorders. We take the opportunity to review achievements in the past and provide our view of what is coming in the fields of molecular genetics, epigenetics, and cellular models. We expect that SNP-array and sequencing-based studies of genetic associations will continue to expand, covering more disorders, drug responses, phenotypes, and diverse populations. Epigenetic studies of psychiatric disorders will be another promising field with the growing recognition that environmental factors impact the risk for psychiatric disorders by modulating epigenetic factors. Functional studies of genetic findings will be needed in cellular models to provide important connections between genetic and epigenetic variants and biological phenotypes.

Regulatory networks in mechanotransduction reveal key genes in promoting cancer cell stemness and proliferation

Tumor-repopulating cells (TRCs) are cancer stem cell (CSC)-like cells with highly tumorigenic and self-renewing abilities, which were selected from tumor cells in soft three-dimensional (3D) fibrin gels with unidentified mechanisms. Here we evaluated the transcriptome alteration during TRCs generation in 3D culture and revealed that a variety of molecules related with integrin/membrane and stemness were continuously altered by mechanical environment. Some key regulators such as MYC/STAT3/hsa-miR-199a-5p, were changed in the TRCs generation. They regulated membrane genes and the downstream mechanotransduction pathways such as Hippo/WNT/TGF-β/PI3K-AKT pathways, thus further affecting the expression of downstream cancer-related genes. By integrating networks for membrane proteins, the WNT pathway and cancer-related genes, we identified key molecules in the selection of TRCs, such as ATF4, SLC3A2, CCT3, and hsa-miR-199a-5p. Silencing ATF4 or CCT3 inhibited the selection and growth of TRCs whereas reduction of SLC3A2 or hsa-miR-199a-5p promoted TRCs growth. Further studies showed that CCT3 promoted cell proliferation and stemness in vitro, while its suppression inhibited TRCs-induced tumor formation. We also contemplated CCT3 as a stemness-related gene. Our findings provide insights in the mechanism of TRCs selection through transcriptome analysis.

Cross talk between mineral metabolism and meat quality: a systems biology overview

Meat quality has an inherent complexity because of the multiple interrelated causative factors and layers of feedback regulation. Understanding the key factors and their interactions has been challenging, despite the availability of remarkable high-throughput tools and techniques that have provided insights on muscle metabolism and the genetic basis of meat quality. Likewise, we have deepened our knowledge about mineral metabolism and its role in cell functioning. Regardless of these facts, complex traits like mineral content and meat quality have been studied under reductionist approaches. However, as these phenotypes arise from complex interactions among different biological layers (genome, transcriptome, proteome, epigenome, etc.), along with environmental effects, a holistic view and systemic-level understanding of the genetic basis of complex phenotypes are in demand. Based on the state of the art, we addressed some of the questions regarding the interdependence of meat quality traits and mineral content. Furthermore, we sought to highlight potential regulatory mechanisms arising from the genes, miRNAs, and mineral interactions, as well as the pathways modulated by this interplay affecting muscle, mineral metabolism, and meat quality. By answering these questions, we did not intend to give an exhaustive review but to identify the key biological points, the challenges, and benefits of integrative genomic approaches.

Identification of Regulatory Networks of MicroRNAs and Their Targets in Response to Colletotrichum gloeosporioides in Tea Plant (Camellia sinensis L.)

Anthracnose disease is caused by Colletotrichum gloeosporioides, and is common in leaves of the tea plant (Camellia sinensis). MicroRNAs (miRNAs) have been known as key modulators of gene expression in response to environmental stresses, disease resistance, defense responses, and plant immunity. However, the role of miRNAs in responses to C. gloeosporioides remains unexplored in tea plant. Therefore, in the present study, six miRNA sequencing data sets and two degradome data sets were generated from C. gloeosporioides-inoculated and control tea leaves. A total of 485 conserved and 761 novel miRNAs were identified. Of those, 239 known and 369 novel miRNAs exhibited significantly differential expression under C. gloeosporioides stress. One thousand one hundred thirty-four and 596 mRNAs were identified as targets of 389 conserved and 299 novel miRNAs by degradome analysis, respectively. Based on degradome analysis, most of the predicted targets are negatively correlated with their corresponding conserved and novel miRNAs. The expression levels of 12 miRNAs and their targets were validated by quantitative real-time PCR. A negative correlation between expression profiles of five miRNAs (PC-5p-80764_22, csn-miR160c, csn-miR828a, csn-miR164a, and csn-miR169e) and their targets (WRKY, ARF, MYB75, NAC, and NFY transcription factor) was observed. The predicted targets of five interesting miRNAs were further validated through 5'RLM-RACE. Furthermore, Gene Ontology and metabolism pathway analysis revealed that most of the target genes were involved in the regulation of auxin pathway, ROS scavenging pathway, salicylic acid mediated pathway, receptor kinases, and transcription factors for plant growth and development as well as stress responses in tea plant against C. gloeosporioides stress. This study enriches the resources of stress-responsive miRNAs and their targets in C. sinensis and thus provides novel insights into the miRNA-mediated regulatory mechanisms, which could contribute to the enhanced susceptibility of C. gloeosporioides in tea plant.

Identification of Long Non-Coding RNAs and the Regulatory Network Responsive to Arbuscular Mycorrhizal Fungi Colonization in Maize Roots

Recently, long noncoding RNAs (lncRNAs) have emerged as vital regulators of many biological processes in animals and plants. However, to our knowledge no investigations on plant lncRNAs which respond to arbuscular mycorrhizal (AM) fungi have been reported thus far. In this study, maize roots colonized with AM fungus were analyzed by strand-specific RNA-Seq to identify AM fungi-responsive lncRNAs and construct an associated regulatory network. A total of 1837 differentially expressed protein coding genes (DEGs) were identified from maize roots with Rhizophagus irregularis inoculation. Many AM fungi-responsive genes were homologs to MtPt4, STR, STR2, MtFatM, and enriched pathways such as fatty acid biosynthesis, response to phosphate starvation, and nitrogen metabolism are consistent with previous studies. In total, 5941 lncRNAs were identified, of which more than 3000 were new. Of those, 63 lncRNAs were differentially expressed. The putative target genes of differentially expressed lncRNAs (DELs) were mainly related to phosphate ion transmembrane transport, cellular response to potassium ion starvation, and lipid catabolic processes. Regulatory network analysis showed that DELs might be involved in the regulation of bidirectional nutrient exchange between plant and AM fungi as mimicry of microRNA targets. The results of this study can broaden our knowledge on the interaction between plant and AM fungi.

Coordinated DNA Methylation and Gene Expression Data for Identification of the Critical Genes Associated with Childhood Atopic Asthma

Asthma is a chronic inflammatory disorder of airways that involves in many cells and factors. This study aimed to screen critical genes and miRNAs involved in childhood atopic asthma. DNA methylation and gene expression data (access numbers GSE65163 and GSE65204) were downloaded from Gene Expression Omnibus (GEO) database, which included 72 atopic asthmatic subject samples and 69 healthy samples. The differentially expressed genes (DEGs) with DNA methylation changes were identified, followed by Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Gene coexpression network and miRNA-target gene regulatory networks were then constructed. Besides, we screened critical drug molecules that have high correlation with atopic asthma in children. A total of 146 critical DEGs with DNA methylation changes were screened from atopic asthmatic samples compared with healthy control samples. GO and KEGG pathway enrichment analysis showed that the critical genes were mainly related to 20 GO terms and 13 KEGG pathways. In the coexpression network, tumor necrosis factor (TNF) and major histocompatibility complex, class II, DP alpha 1 (HLA-DPA1) were identified that were significantly related to immune response process. Analysis of miRNA-target gene network showed that hsa-miR-148b had the highest number of target genes(degree = 21). Besides, we found that Alsterpaullone had a correlation value closest to -1 (correlation = -0.884, p = 0.0031), which indicated that the agent might be considered as a potential agent that antagonized to asthma. The dysregulation of TNF, HLA-DPA1, and miR-148b might be related to the immune response of childhood atopic asthma.

Putrescine Is an Intraspecies and Interkingdom Cell-Cell Communication Signal Modulating the Virulence of Dickeya zeae

The infections caused by Dickeya zeae become a severe problem in recent years, but the regulatory mechanisms that govern the bacterial virulence remain to be fragmental. Here we report the investigation of potential involvement of polyamines in regulation of D. zeae virulence. We showed that null mutation of speA encoding arginine decarboxylase dramatically decreased the bacterial swimming motility, swarming motility and biofilm formation, and exogenous addition of putrescine effectively rescues the defective phenotypes of D. zeae. HPLC and mass spectrometry analysis validated that speA was essential for production of putrescine in D. zeae. In addition, we demonstrated that D. zeae EC1 could detect and response to putrescine molecules produced by itself or from host plant through specific transporters. Among the two transporters identified, the one represented by PotF played a dominated role over the other represented by PlaP in modulation of putrescine-dependent biological functions. Furthermore, we provided evidence that putrescine signal is critical for D. zeae EC1 bacterial invasion and virulence against rice seeds. Our data depict a novel function of putrescine signal in pathogen-host communication and in modulation of the virulence of an important plant bacterial pathogen.

Comparative Identification of MicroRNAs in Apis cerana cerana Workers' Midguts in Responseto Nosema ceranae Invasion

Here, the expression profiles and differentially expressed miRNAs (DEmiRNAs) in the midguts of Apis cerana cerana workers at 7 d and 10 d post-inoculation (dpi) with N. ceranae were investigated via small RNA sequencing and bioinformatics. Five hundred and twenty nine (529) known miRNAs and 25 novel miRNAs were identified in this study, and the expression of 16 predicted miRNAs was confirmed by Stem-loop RT-PCR. A total of 14 DEmiRNAs were detected in the midgut at 7 dpi, including eight up-regulated and six down-regulated miRNAs, while 12 DEmiRNAs were observed in the midgut at 10 dpi, including nine up-regulated and three down-regulated ones. Additionally, five DEmiRNAs were shared, while nine and seven DEmiRNAs were specifically expressed in midguts at 7 dpi and 10 dpi. Gene ontology analysis suggested some DEmiRNAs and corresponding target mRNAs were involved in various functions including immune system processes and response to stimulus. KEGG pathway analysis shed light on the potential functions of some DEmiRNAs in regulating target mRNAs engaged in material and energy metabolisms, cellular immunity and the humoral immune system. Further investigation demonstrated a complex regulation network between DEmiRNAs and their target mRNAs, with miR-598-y, miR-252-y, miR-92-x and miR-3654-y at the center. Our results can facilitate future exploration of the regulatory roles of miRNAs in host responses to N. ceranae, and provide potential candidates for further investigation of the molecular mechanisms underlying eastern honeybee-microsporidian interactions.

Genome-Wide Identification of Long Non-Coding RNAs and Their Regulatory Networks Involved in Apis mellifera ligustica Response to Nosema ceranae Infection

Long non-coding RNAs (lncRNAs) are a diverse class of transcripts that structurally resemble mRNAs but do not encode proteins, and lncRNAs have been proven to play pivotal roles in a wide range of biological processes in animals and plants. However, knowledge of expression patterns and potential roles of honeybee lncRNA response to Nosema ceranae infection is completely unknown. Here, we performed whole transcriptome strand-specific RNA sequencing of normal midguts of Apis mellifera ligustica workers (Am7CK, Am10CK) and N. ceranae-inoculated midguts (Am7T, Am10T), followed by comprehensive analyses using bioinformatic and molecular approaches. A total of 6353 A. m. ligustica lncRNAs were identified, including 4749 conserved lncRNAs and 1604 novel lncRNAs. These lncRNAs had minimal sequence similarities with other known lncRNAs in other species; however, their structural features were similar to counterparts in mammals and plants, including shorter exon and intron length, lower exon number, and lower expression level, compared with protein-coding transcripts. Further, 111 and 146 N. ceranae-responsive lncRNAs were identified from midguts at 7-days post-inoculation (dpi) and 10 dpi compared with control midguts. Twelve differentially expressed lncRNAs (DElncRNAs) were shared by Am7CK vs. Am7T and Am10CK vs. Am10T comparison groups, while the numbers of unique DElncRNAs were 99 and 134, respectively. Functional annotation and pathway analysis showed that the DElncRNAs may regulate the expression of neighboring genes by acting in cis and trans fashion. Moreover, we discovered 27 lncRNAs harboring eight known miRNA precursors and 513 lncRNAs harboring 2257 novel miRNA precursors. Additionally, hundreds of DElncRNAs and their target miRNAs were found to form complex competitive endogenous RNA (ceRNA) networks, suggesting that these DElncRNAs may act as miRNA sponges. Furthermore, DElncRNA-miRNA-mRNA networks were constructed and investigated, the results demonstrated that a portion of the DElncRNAs were likely to participate in regulating the host material and energy metabolism as well as cellular and humoral immune host responses to N. ceranae invasion. Our findings revealed here offer not only a rich genetic resource for further investigation of the functional roles of lncRNAs involved in the A. m. ligustica response to N. ceranae infection, but also a novel insight into understanding the host-pathogen interaction during honeybee microsporidiosis.

Transcriptome analysis of virulence gene regulation by the ATP-dependent Lon protease in Salmonella Typhimurium

Aim: Determination of the virulence regulatory network controlled by the ATP-dependent Lon protease in Salmonella enterica serovar Typhimurium. Materials & methods: The effect of Lon on S. Typhimurium virulence genes expression was investigated by RNA sequencing, and virulence-associated phenotypes between the wild-type and lon mutant were compared. Results: SPI-1, SPI-4, SPI-9 and flagellar genes were activated, while SPI-2 genes were repressed in the lon mutant. Accordingly, the lon mutant exhibited increased adhesion to and invasion of epithelial cells, increased motility and decreased replication in macrophages. The activation of SPI-2 genes by Lon partially accounts for the replication defect of the mutant. Conclusion: A wide range of virulence regulatory functions are governed by Lon in S. enterica ser. Typhimurium.

Relationships between SNPs and prognosis of breast cancer and pathogenic mechanism

Background

Association between several single‐nucleotide polymorphisms (SNPs) and breast cancer risk has been identified through genome‐wide association studies (GWAS), but little is known about their significance in patients’ prognosis. We screened SNPs which were related to the prognosis of breast cancer in Henan Han population, analyzed relevant genes by bioinformatics in database, and further constructed the genetic regulatory network involved in the pathogenesis of breast cancer.

Methods

We evaluated five SNPs in 232 cases of breast cancer at the Affiliated Tumor Hospital of Zhengzhou University. Relationships between five SNPs, clinical prognostic indicators, and disease‐free survival (DFS) were evaluated by Kaplan–Meier analysis and Cox proportional hazards model. Gene ontology (GO) functional annotation and Kyoto Encyclopedia of genes and Genome (KEGG) analysis were carried out to preliminarily establish genetic regulation network model of breast cancer. Bayesian algorithm was used to optimize the model.

Results

The multivariate Cox proportional hazards model confirmed that SNP rs3803662 (TOX3/TNRC9) had correlation with DFS independently. In the multivariate Cox proportional hazards model, compared with GA/AA, GG increased the recurrent risk of breast cancer (p = .021, hazard ratio [HR] = 2.914). GO analysis showed that the function of TOX3/TNRC9 included biological_process, molecular_function, and cellular_component. According to KEGG signaling pathway database, the map of breast cancer‐related gene regulatory network was obtained. IGF‐IGF1R‐PI3K‐Akt‐mTOR‐S6K was the best possible pathway for the differentiation of breast cancer cells in this network and ER‐TOX3/TNRC9 was the best possible pathway for the survival of tumor cells in this network by Bayesian theorem optimization.

Conclusions

SNP rs3803662 (TOX3/TNRC9) is an independent prognostic factor for breast cancer in Henan Han Population. ER‐TOX3/TNRC9 is the best possible pathway involved in the pathogenesis of breast cancer.

miRNA-Gene Regulatory Network in Gnotobiotic Mice Stimulated by Dysbiotic Gut Microbiota Transplanted From a Genetically Obese Child

Gut microbiota (GM) dysbiosis has been considered a pathogenic origin of many chronic diseases. In our previous trial, a shift in GM structure caused by a complex fiber-rich diet was associated with the health improvement of obese Prader-Willi syndrome (PWS) children. The pre- and post-intervention GMs (pre- and post-group, respectively) from one child were then transplanted into gnotobiotic mice, which resulted in significantly different physiological phenotypes, each of which was similar to the phenotype of the corresponding GM donor. This study was designed to investigate the miRNA-gene regulatory networks involved in causing these phenotypic differences. Using the post-group as a reference, we systematically identified and annotated the differentially expressed (DE) miRNAs and genes in the colon and liver of the pre-group in the second and fourth weeks after GM inoculation. Most of the significantly enriched GO terms and KEGG pathways were observed in the liver and were in the second week after GM transplantation. We screened 23 key genes along with their 73 miRNA regulators relevant to the host phenotype changes and constructed a network. The network contained 92 miRNA-gene regulation relationships, 51 of which were positive, and 41 of which were negative. Both the colon and liver had upregulated pro-inflammatory genes, and genes involved in fatty acid oxidation, lipolysis, and plasma cholesterol clearance were downregulated in only the liver. These changes were consistent with lipid and cholesterol accumulation in the host and with a high inflammation level. In addition, the colon showed an impacted glucagon-like peptide 1 (GLP-1) signaling pathway, while the liver displayed decreased insulin receptor signaling pathway activity. These molecular changes were mainly found in the second week, 2 weeks before changes in body fat occurred. This time lag indicated that GM dysbiosis might initially induce cholesterol and lipid metabolism-related miRNA and gene expression disorder and then lead to lipid accumulation and obesity development, which implicates a causative role of GM dysbiosis in obesity development rather than a result of obesity. This study provides fundamental molecular information that elucidates how dysbiotic GM increases host inflammation and disturbs host lipid and glucose metabolism.

Identification of crucial miRNAs and genes in esophageal squamous cell carcinoma by miRNA-mRNA integrated analysis

Esophageal squamous cell carcinoma (ESCC) is a malignancy that severely threatens human health and carries a high incidence rate and a low 5-year survival rate. MicroRNAs (miRNAs) are commonly accepted as a key regulatory function in human cancer, but the potential regulatory mechanisms of miRNA-mRNA related to ESCC remain poorly understood.The GSE55857, GSE43732, and GSE6188 miRNA microarray datasets and the gene expression microarray datasets GSE70409, GSE29001, and GSE20347 were downloaded from Gene Expression Omnibus databases. The differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) were obtained using GEO2R. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs were performed by Database for Annotation, Visualization and Integrated Discovery (DAVID). A protein-protein interaction (PPI) network and functional modules were established using the STRING database and were visualized by Cytoscape. Kaplan-Meier analysis was constructed based on The Cancer Genome Atlas (TCGA) database.In total, 26 DEMs and 280 DEGs that consisted of 96 upregulated and 184 downregulated genes were screened out. A functional enrichment analysis showed that the DEGs were mainly enriched in the ECM-receptor interaction and cytochrome P450 metabolic pathways. In addition, MMP9, PCNA, TOP2A, MMP1, AURKA, MCM2, IVL, CYP2E1, SPRR3, FOS, FLG, TGM1, and CYP2C9 were considered to be hub genes owing to high degrees in the PPI network. MiR-183-5p was with the highest connectivity target genes in hub genes. FOS was predicted to be a common target gene of the significant DEMs. Hsa-miR-9-3p, hsa-miR-34c-3p and FOS were related to patient prognosis and higher expression of the transcripts were associated with a poor OS in patients with ESCC.Our study revealed the miRNA-mediated hub genes regulatory network as a model for predicting the molecular mechanism of ESCC. This may provide novel insights for unraveling the pathogenesis of ESCC.

Overexpression of miR-101 May Target DUSP1 to Promote the Cartilage Degradation in Rheumatoid Arthritis

This study aimed to explore crucial genes that contribute to the development of rheumatoid arthritis (RA). Three GSE77298, GSE55457, and GSE55235 data sets were used to analyze the differentially expressed genes (DEGs) between RA synovial membrane tissue samples and normal synovial membrane tissue samples. Then, the functional enrichment analysis and protein-protein interactions (PPIs) construction were performed for DEGs. Subsequently, submodule analysis and regulatory network that contained transcription factors (TFs), microRNAs, and their targets were conducted. Finally, small-molecule drugs related to the DEGs were predicted. A total of 173 upregulated and 54 downregulated DEGs identified in at least 2 of 3 data sets. TYROBP, CTSS, MMP9, CXCR4, and CXCL10 were both highlighted in the PPI and submodule networks. In addition, miR-101, IRF1 TF, DUSP1, and CXCR4 had high degree in the regulatory network, and regulation pairs of miR-101-DUSP1 and IRF1 TF-CXCR4 were obtained. Drugs such as alemtuzumab and marimastat were negatively related to expression of the DEGs and might be useful drugs for RA treatment. In addition, most DEGs were involved in innate immune response (e.g., TYROBP, CCL5, CXCL10, FCGR1A, and FCGR3B) and phagosome pathway (e.g., CTSS). We suggested that miR-101 that regulated DUSP1, IRF1 TF that regulated CXCR4, as well as DEGs as TYROBP and CTSS might contribute to the RA pathogenesis. In addition, anti-inflammatory agent alemtuzumab and matrix metalloproteinase inhibitor marimastat might be useful drugs for RA treatment through functioning on their target genes.

Genome-Wide Profiling of the Microrna Transcriptome Regulatory Network to Identify Putative Candidate Genes Associated with Backfat Deposition in Pigs

Simple Summary

Backfat thickness is an important characteristic in pig breeding. In this study, the key microRNAs (miRNAs) and genes associated with pig backfat deposition were detected and characterized using RNA sequencing between adipose tissues of high-backfat and low-backfat pigs. Strong candidate mRNA‒miRNA interaction pairs were identified to affect backfat deposition through the regulation of target genes by miRNAs. These results provide novel insights into the backfat deposition mechanism in pigs.

Abstract

Backfat deposition is strongly related to carcass traits, growth rate, feed conversion rate, and reproductive performance in pig production. To understand the molecular mechanisms underlying porcine backfat thickness phenotypes, transcriptome and miRNA profiling of backfat from high-backfat thickness and low-backfat thickness pigs were performed by RNA sequencing. Twenty genes encoding for miRNAs and 126 genes encoding for protein-coding genes were found to be differentially expressed between the two libraries. After integrative analysis of DEMs targets and DEGs, a total of 33 mRNA‒miRNA interaction pairs were identified, and the regulatory networks of these pairs were determined. Among these genes, five (AQP9, DKK3, GLYCTK, GLIPR1, and DUSP2) related to fat deposition were found to be strong candidate genes, and mir-31-5p/AQP9 and mir-31-5p/GLIPR1 may play important roles in fat deposition. Additionally, potential adipogenesis-related genes and miRNAs were identified. These findings improve the current understanding of the molecular genetic mechanisms of subcutaneous fat deposition in pigs and provide a foundation for further studies.

Liver Zonation in Health and Disease: Hypoxia and Hypoxia-Inducible Transcription Factors as Concert Masters

The liver and its zonation contribute to whole body homeostasis. Acute and chronic, not always liver, diseases impair proper metabolic zonation. Various underlying pathways, such as β-catenin, hedgehog signaling, and the Hippo pathway, along with the physiologically occurring oxygen gradient, appear to be contributors. Interestingly, hypoxia and hypoxia-inducible transcription factors can orchestrate those pathways. In the current review, we connect novel findings of liver zonation in health and disease and provide a view about the dynamic interplay between these different pathways and cell-types to drive liver zonation and systemic homeostasis.

Comprehensive bioinformatics analysis of critical lncRNAs, mRNAs and miRNAs in non‑alcoholic fatty liver disease

Non‑alcoholic fatty liver disease (NAFLD) is the most common fatty liver disease in developed countries, in which fat accumulation in the liver is induced by non‑alcoholic factors. The present study was conducted to identify NAFLD‑associated long non‑coding RNAs (lncRNAs), mRNAs and microRNAs (miRNAs). The microarray dataset GSE72756, which included 5 NAFLD liver tissues and 5 controls, was acquired from the Gene Expression Omnibus database. Differentially expressed lncRNAs (DE‑lncRNAs) and mRNAs (DE‑mRNAs) were detected using the pheatmap package. Using the clusterProfiler package and Cytoscape software, enrichment and protein‑protein interaction (PPI) network analyses were conducted to evaluate the DE‑mRNAs. Next, the miRNA‑lncRNA‑mRNA interaction network was visualized using Cytoscape software. Additionally, RP11‑279F6.1 and AC004540.4 expression levels were analyzed by reverse transcription quantitative polymerase chain reaction. There were 318 DE‑lncRNAs and 609 DE‑mRNAs identified in the NAFLD tissues compared with the normal tissues. Jun proto‑oncogene, AP‑1 transcription factor subunit (JUN), which is regulated by AC004540.4 and RP11‑279F6.1, exhibited higher degree compared with other nodes in the PPI network. Furthermore, miR‑409‑3p and miR‑139 (targeting JUN) were predicted as PPI network nodes. In the miRNA‑lncRNA‑mRNA network, miR‑20a and B‑cell lymphoma 2‑like 11 (BCL2L11) were among the top 10 nodes. Additionally, BCL2L11, AC004540.4 and RP11‑279F6.1 were targeted by miR‑20a, miR‑409‑3p and miR‑139 in the miRNA‑lncRNA‑mRNA network, respectively. RP11‑279F6.1 and AC004540.4 expression was markedly enhanced in NAFLD liver tissues. These key RNAs may be involved in the pathogenic mechanisms of NAFLD.

An Integrated Regulatory Network Based on Comprehensive Analysis of mRNA Expression, Gene Methylation and Expression of Long Non-coding RNAs (lncRNAs) in Myelodysplastic Syndromes

Myelodysplastic syndromes (MDS) are a heterogeneous group of disorders characterized by ineffective hematopoiesis, defective differentiation of hematopoietic precursors, and expansion of the abnormal clones. The prevalence of MDS has raised great concerns worldwide, but its pathogenetic mechanisms remain elusive. To provide insights on novel biomarkers for the diagnosis and therapy of MDS, we performed high-throughput genome-wide mRNA expression profiling, DNA methylation analysis, and long non-coding RNAs (lncRNA) analysis on bone marrows from four MDS patients and four age-matched healthy controls. We identified 1,937 differentially expressed genes (DEGs), 515 methylated genes, and 214 lncRNA that showed statistically significant differences. As the most significant module-related DEGs, TCL1A, PTGS2, and MME were revealed to be enriched in regulation of cell differentiation and cell death pathways. In addition, the GeneGo pathway maps identified by top DEGs were shown to converge on cancer, immunoregulation, apoptosis and regulation of actin cytoskeleton, most of which are known contributors in MDS etiology and pathogenesis. Notably, as potential biomarkers for diagnosis of MDS, four specific genes (ABAT, FADD, DAPP1, and SMPD3) were further subjected to detailed pathway analysis. Our integrative analysis on mRNA expression, gene methylation and lncRNAs profiling facilitates further understanding of the pathogenesis of MDS, and may promote the diagnosis and novel therapeutics for this disease.

Comparison of Combinatorial Signatures of Global Network Dynamics Generated by Two Classes of ODE Models

Modeling the dynamics of biological networks introduces many challenges, among them the lack of first principle models, the size of the networks, and difficulties with parameterization. Discrete time Boolean networks and related continuous time switching systems provide a computationally accessible way to translate the structure of the network to predictions about the dynamics. Recent work has shown that the parameterized dynamics of switching systems can be captured by a combinatorial object, called a Dynamic Signatures Generated by Regulatory Networks (DSGRN) database, that consists of a parameter graph characterizing a finite parameter space decomposition, whose nodes are assigned a Morse graph that captures global dynamics for all corresponding parameters. We show that for a given network there is a way to associate the same type of object by considering a continuous time ODE system with a continuous right-hand side, which we call an L-system. The main goal of this paper is to compare the two DSGRN databases for the same network. Since the L-systems can be thought of as perturbations (not necessarily small) of the switching systems, our results address the correspondence between global parameterized dynamics of switching systems and their perturbations. We show that, at corresponding parameters, there is an order preserving map from the Morse graph of the switching system to that of the L-system that is surjective on the set of attractors and bijective on the set of fixed-point attractors. We provide important examples showing why this correspondence cannot be strengthened.

Unique Patterns and Biogeochemical Relevance of Two-Component Sensing in Marine Bacteria

Marine microbes must manage variation in their chemical, physical, and biological surroundings. Because they directly link bacterial physiology to environmental changes, TCS systems are crucial to the bacterial cell. This study surveyed TCS systems in a large number of marine bacteria and identified key phylogenetic and lifestyle patterns in environmental sensing. We found evidence that, in comparison with bacteria as a whole, marine organisms have irregular TCS system constructs which might represent an adaptation specific to the marine environment. Additionally, we demonstrate the biogeochemical relevance of TCS systems by correlating the presence of the PMT9312_0717 response regulator protein to phosphate concentrations in the South Pacific. We highlight that despite their potential ecological and biogeochemical relevance, TCS systems have been understudied in the marine ecosystem. This report expands our understanding of the breadth of bacterial TCS systems and how marine bacteria have adapted to survive in their unique environment.

Two-component sensory (TCS) systems link microbial physiology to the environment and thus may play key roles in biogeochemical cycles. In this study, we surveyed the TCS systems of 328 diverse marine bacterial species. We identified lifestyle traits such as copiotrophy and diazotrophy that are associated with larger numbers of TCS system genes within the genome. We compared marine bacterial species with 1,152 reference bacterial species from a variety of habitats and found evidence of extra response regulators in marine genomes. Examining the location of TCS genes along the circular bacterial genome, we also found that marine bacteria have a large number of “orphan” genes, as well as many hybrid histidine kinases. The prevalence of “extra” response regulators, orphan genes, and hybrid TCS systems suggests that marine bacteria break with traditional understanding of how TCS systems operate. These trends suggest prevalent regulatory networking, which may allow coordinated physiological responses to multiple environmental signals and may represent a specific adaptation to the marine environment. We examine phylogenetic and lifestyle traits that influence the number and structure of two-component systems in the genome, finding, for example, that a lack of two-component systems is a hallmark of oligotrophy. Finally, in an effort to demonstrate the importance of TCS systems to marine biogeochemistry, we examined the distribution of Prochlorococcus/Synechococcus response regulator PMT9312_0717 in metaproteomes of the tropical South Pacific. We found that this protein’s abundance is related to phosphate concentrations, consistent with a putative role in phosphate regulation.

IMPORTANCE Marine microbes must manage variation in their chemical, physical, and biological surroundings. Because they directly link bacterial physiology to environmental changes, TCS systems are crucial to the bacterial cell. This study surveyed TCS systems in a large number of marine bacteria and identified key phylogenetic and lifestyle patterns in environmental sensing. We found evidence that, in comparison with bacteria as a whole, marine organisms have irregular TCS system constructs which might represent an adaptation specific to the marine environment. Additionally, we demonstrate the biogeochemical relevance of TCS systems by correlating the presence of the PMT9312_0717 response regulator protein to phosphate concentrations in the South Pacific. We highlight that despite their potential ecological and biogeochemical relevance, TCS systems have been understudied in the marine ecosystem. This report expands our understanding of the breadth of bacterial TCS systems and how marine bacteria have adapted to survive in their unique environment.

Machine Learning of Stem Cell Identities From Single-Cell Expression Data via Regulatory Network Archetypes

The molecular regulatory network underlying stem cell pluripotency has been intensively studied, and we now have a reliable ensemble model for the "average" pluripotent cell. However, evidence of significant cell-to-cell variability suggests that the activity of this network varies within individual stem cells, leading to differential processing of environmental signals and variability in cell fates. Here, we adapt a method originally designed for face recognition to infer regulatory network patterns within individual cells from single-cell expression data. Using this method we identify three distinct network configurations in cultured mouse embryonic stem cells-corresponding to naïve and formative pluripotent states and an early primitive endoderm state-and associate these configurations with particular combinations of regulatory network activity archetypes that govern different aspects of the cell's response to environmental stimuli, cell cycle status and core information processing circuitry. These results show how variability in cell identities arise naturally from alterations in underlying regulatory network dynamics and demonstrate how methods from machine learning may be used to better understand single cell biology, and the collective dynamics of cell communities.

Construction of microRNA-messenger networks for human osteosarcoma

Osteosarcoma is the most common bone tumor in children and young adults. Although the microRNAs (miRNA) expression analyses of osteosarcoma have been performed previously, the construction of miRNA-messenger RNA (mRNA) networks for osteosarcoma is needed. This study aimed to identify osteosarcoma-related miRNAs through analyzing the microarray datasets and to construct the regulatory network of miRNA-mRNA for human osteosarcoma. The datasets were extracted from the Gene Expression Omnibus and the differentially expressed miRNAs were screened through the limma package in Bioconductor. Genes targeted by the differentially expressed miRNAs were screened out by using the Miranda, MirTarget2, PicTar, PITA, and TargetScan databases. The predicted target genes were further analyzed by Gene Ontology and pathway enrichment analysis and a regulatory network of differentially expressed miRNAs and their target osteosarcoma-associated genes was constructed. A total of 36 downregulated miRNAs and 182 upregulated miRNAs were identified in osteosarcoma samples compared with normal samples and 397 target genes for upregulated miRNAs and 222 target genes for downregulated miRNAs were obtained. The enriched pathways for target genes of differentially expressed miRNAs included transcriptional misregulation in cancer, the AMPK signaling pathway, and MAPK signaling pathway. In the regulatory network, has-miR-199a-5p targeted the highest number of genes and nemo-like kinase (NLK) was targeted by five miRNAs (hsa-miR-140-5p, hsa-miR-107, hsa-miR-324-5p, hsa-miR-199a-5p, and hsa-miR-28-5p). The has-miR-324-5p targets NLK, TGFB2, and PPARG. These miRNAs and their target genes may serve as potential therapeutic targets of osteosarcoma.

Identifying Transcriptional Regulatory Modules Among Different Chromatin States in Mouse Neural Stem Cells

Gene expression regulation is a complex process involving the interplay between transcription factors and chromatin states. Significant progress has been made toward understanding the impact of chromatin states on gene expression. Nevertheless, the mechanism of transcription factors binding combinatorially in different chromatin states to enable selective regulation of gene expression remains an interesting research area. We introduce a nonparametric Bayesian clustering method for inhomogeneous Poisson processes to detect heterogeneous binding patterns of multiple proteins including transcription factors to form regulatory modules in different chromatin states. We applied this approach on ChIP-seq data for mouse neural stem cells containing 21 proteins and observed different groups or modules of proteins clustered within different chromatin states. These chromatin-state-specific regulatory modules were found to have significant influence on gene expression. We also observed different motif preferences for certain TFs between different chromatin states. Our results reveal a degree of interdependency between chromatin states and combinatorial binding of proteins in the complex transcriptional regulatory process. The software package is available on Github at - https://github.com/BSharmi/DPM-LGCP.

Dysregulation of ncRNAs located at the DLK1‑DIO3 imprinted domain: involvement in urological cancers

Genomic imprinting has been found to be involved in human physical development and several diseases. The DLK1-DIO3 imprinted domain is located on human chromosome 14 and contains paternally expressed protein-coding genes (DLK1, RTL1, DIO3) and numerous maternally expressed ncRNA genes (MEG3, MEG8, antisense RTL1, miRNAs, piRNAs, and snoRNAs). Emerging evidence has implicated that dysregulation of the DLK1-DIO3 imprinted domain especially the imprinted ncRNAs is critical for tumor progressions. Multiple miRNAs and lncRNAs have been investigated in urological cancers, of which several are transcribed from this domain. In this review, we present current data about the associated miRNAs, lncRNAs, and piRNAs and the regulation of differentially methylated regions methylation status in the progression of urological cancers and preliminarily propose certain concepts about the potential regulatory networks involved in DLK1-DIO3 imprinted domain.

LncRNA-000133 from secondary hair follicle of Cashmere goat: identification, regulatory network and its effects on inductive property of dermal papilla cells

Long noncoding RNAs (lncRNAs), a class of non-protein conding RNAs > 200 nt in length, were thought to play critical roles in regulating the expression of protein-coding genes. Here, we identified and characterized a novel lncRNA-000133 from the secondary hair follicle (SHF) of cashmere goat with its ceRNA network analysis, as well as, its potential effects on inductive property of dermal papilla cells were evaluated through overexpression analysis. Expression analysis indicated that lncRNA-000133 had a significantly higher expression at anagen than that at telogen in SHF of Cashmere goat, suggesting that lncRNA-000133 might be involved in the reconstruction of SHF with the formation and growth of cashmere fiber. Taken together with methylation analysis, we showed that 5' regulatory region methylation of the lncRNA-000133 gene might be involved in its expression suppression in SHF of Cashmere goat. The ceRNA regulatory network showed that a rich and complex regulatory relationship between lncRNA-000133 and related miRNAs with their target genes. The overexpression of lncRNA-000133 led to a significant increasing in the relative expression of ET-1, SCF, ALP and LEF1 in dermal papilla cells suggesting that lncRNA-000133 appears to contribute the inductive property of dermal papilla cells.

Bioinformatics-Based Approaches Predict That MIR-17-5P Functions in the Pathogenesis of Seasonal Allergic Rhinitis Through Regulating ABCA1 and CD69

OBJECTIVE

As the most prevalent type of rhinitis, allergic rhinitis is consisted of seasonal allergic rhinitis (SAR) and perennial allergic rhinitis. This study is carried out for revealing the mechanisms of SAR.

METHODS

Microarray data set GSE43523 (including 7 SAR nasal epithelial cells and 5 nonallergic control nasal epithelial cells) was extracted from Gene Expression Omnibus database. Based on limma package, differential expression analysis for the 2 groups was performed to obtain differentially expressed genes (DEGs). Using Multifaceted Analysis Tool for Human Transcriptome online tool, the functions involving the DEGs were predicted by enrichment analysis. Combined with Cytoscape software, protein-protein interaction (PPI) network was built and a significant network module was acquired. In addition, transcription factor (TF)-target and miRNA-target pairs were predicted using WebGestalt tool, and then TF-miRNA-target regulatory network was built by Cytoscape software.

RESULTS

There were 274 DEGs between rhinitis and control samples, including 144 upregulated genes and 130 downregulated genes. After PPI for the DEGs was built, a significant network module was identified. In the TF-miRNA-target regulatory network, ABCA1, CPEB4, CD69, MIR-17-5P, and CREB had higher degrees. Furthermore, both ABCA1 and CD69 were targeted by MIR-17-5P in the regulatory network.

CONCLUSION

CPEB4 and CREB might be implicated in the pathogenesis of SAR. Besides, MIR-17-5P might also act in SAR via targeting ABCA1 and CD69.

Fat Body Biology in the Last Decade

The insect fat body is analogous to vertebrate adipose tissue and liver. In this review, the new and exciting advancements made in fat body biology in the last decade are summarized. Controlled by hormonal and nutritional signals, insect fat body cells undergo mitosis during embryogenesis, endoreplication during the larval stages, and remodeling during metamorphosis and regulate reproduction in adults. Fat body tissues are major sites for nutrient storage, energy metabolism, innate immunity, and detoxification. Recent studies have revealed that the fat body plays a central role in the integration of hormonal and nutritional signals to regulate larval growth, body size, circadian clock, pupal diapause, longevity, feeding behavior, and courtship behavior, partially by releasing fat body signals to remotely control the brain. In addition, the fat body has emerged as a fascinating model for studying metabolic disorders and immune diseases. Potential future directions for fat body biology are also proposed herein.

Abiotic Stresses: General Defenses of Land Plants and Chances for Engineering Multistress Tolerance

Abiotic stresses, such as low or high temperature, deficient or excessive water, high salinity, heavy metals, and ultraviolet radiation, are hostile to plant growth and development, leading to great crop yield penalty worldwide. It is getting imperative to equip crops with multistress tolerance to relieve the pressure of environmental changes and to meet the demand of population growth, as different abiotic stresses usually arise together in the field. The feasibility is raised as land plants actually have established more generalized defenses against abiotic stresses, including the cuticle outside plants, together with unsaturated fatty acids, reactive species scavengers, molecular chaperones, and compatible solutes inside cells. In stress response, they are orchestrated by a complex regulatory network involving upstream signaling molecules including stress hormones, reactive oxygen species, gasotransmitters, polyamines, phytochromes, and calcium, as well as downstream gene regulation factors, particularly transcription factors. In this review, we aimed at presenting an overview of these defensive systems and the regulatory network, with an eye to their practical potential via genetic engineering and/or exogenous application.

The Biological Significance and Regulatory Mechanism of c-Myc Binding Protein 1 (MBP-1)

Alternatively translated from the ENO gene and expressed in an array of vertebrate and plant tissues, c-Myc binding protein 1 (MBP-1) participates in the regulation of growth in organisms, their development and their environmental responses. As a transcriptional repressor of multiple proto-oncogenes, vertebrate MBP-1 interacts with other cellular factors to attenuate the proliferation and metastasis of lung, breast, esophageal, gastric, bone, prostrate, colorectal, and cervical cancer cells. Due to its tumor-suppressive property, MBP-1 and its downstream targets have been investigated as potential prognostic markers and therapeutic targets for various cancers. In plants, MBP-1 plays an integral role in regulating growth and development, fertility and abiotic stress responses. A better understanding of the functions and regulatory factors of MBP-1 in plants may advance current efforts to maximize plant resistance against drought, high salinity, low temperature, and oxidative stress, thus optimizing land use and crop yields. In this review article, we summarize the research advances in biological functions and mechanistic pathways underlying MBP-1, describe our current knowledge of the ENO product and propose future research directions on vertebrate health as well as plant growth, development and abiotic stress responses.

Identification of hub genes to regulate breast cancer metastasis to brain by bioinformatics analyses

Breast cancer with metastasis especially brain metastasis represents a significant cause of morbidity and mortality in patients. In this study, we aimed to investigate the hub genes and potential molecular mechanism in brain metastasis breast cancer. Expression profiles of the genes were extracted from the Gene Expression Omnibus (GEO) database. GO and KEGG pathway enrichment analyses were conducted at Database for Annotation, Visualization, and Integrated Discovery. Protein-protein interaction (PPI) network was established by STRING database constructed by Cytoscape software. Hub genes were identified by the molecular complex detection (MCODE) plugin and the CytoHubba plugin. The transcription factor (TF) that regulates the expression of hub genes was analyzed using the NetworkAnalyst algorithm. Kaplan-Meier curve was used to analyze the effects of hub genes on overall survival. Two GEO databases (GSE100534 and GSE52604) were downloaded from GEO databases. A total of 102 overlapped genes were identified, and the top five KEGG pathways enriched were pathways in cancer, HTLV-I infection, focal adhesion, ECM-receptor interaction, and protein digestion and absorption. By combing the results of MCODE and CytoHubba, a total of 10 hub genes were selected. Kaplan-Meier curve showed that ANLN, BUB1, TTK, and SKA3 were closely associated with the overall survival of breast cancer patients. TF analysis results showed that E2F4, KDM5B, and MYC were crucial regulators for these four hub genes. The current study based on the GEO database provided novel understanding regarding the mechanism of breast cancer metastasis to brain and may provide novel therapeutic targets.

Expression and regulatory networks of Mycobacterium tuberculosis PE/PPE family antigens

PE/PPE family antigens are distributed mainly in pathogenic mycobacteria and serve as potential antituberculosis (TB) vaccine components. Some PE/PPE family antigens can regulate the host innate immune response, interfere with macrophage activation and phagolysosome fusion, and serve as major sources of antigenic variation. PE/PPE antigens have been associated with mycobacteria pathogenesis; pe/ppe genes are mainly found in pathogenic mycobacteria and are differentially expressed between Mtb and Mycobacterium bovis. PE/PPE proteins were essential for the growth of Mtb, and PE/PPE proteins were differentially expressed under a variety of conditions. Multiple mycobacterial-virulence-related transcription factors, sigma factors, the global transcriptional regulation factor Lsr2, MprAB, and PhoPR two-component regulatory systems, and cyclic adenine monophosphate-dependent regulators, regulate the expression of PE/PPE family antigens. Multiple-scale integrative analysis revealed the expression and regulatory networks of PE/PPE family antigens underlying the virulence and pathogenesis of Mtb, providing important clues for the discovery of new anti-TB measures.

Inferring Novel Autophagy Regulators Based on Transcription Factors and Non-Coding RNAs Coordinated Regulatory Network

Autophagy is a complex cellular digestion process involving multiple regulators. Compared to post-translational autophagy regulators, limited information is now available about transcriptional and post-transcriptional regulators such as transcription factors (TFs) and non-coding RNAs (ncRNAs). In this study, we proposed a computational method to infer novel autophagy-associated TFs, micro RNAs (miRNAs) and long non-coding RNAs (lncRNAs) based on TFs and ncRNAs coordinated regulatory (TNCR) network. First, we constructed a comprehensive TNCR network, including 155 TFs, 681 miRNAs and 1332 lncRNAs. Next, we gathered the known autophagy-associated factors, including TFs, miRNAs and lncRNAs, from public data resources. Then, the random walk with restart (RWR) algorithm was conducted on the TNCR network by using the known autophagy-associated factors as seeds and novel autophagy regulators were finally prioritized. Leave-one-out cross-validation (LOOCV) produced an area under the curve (AUC) of 0.889. In addition, functional analysis of the top 100 ranked regulators, including 55 TFs, 26 miRNAs and 19 lncRNAs, demonstrated that these regulators were significantly enriched in cell death related functions and had significant semantic similarity with autophagy-related Gene Ontology (GO) terms. Finally, extensive literature surveys demonstrated the credibility of the predicted autophagy regulators. In total, we presented a computational method to infer credible autophagy regulators of transcriptional factors and non-coding RNAs, which would improve the understanding of processes of autophagy and cell death and provide potential pharmacological targets to autophagy-related diseases.

Deciphering the transcription factor-microRNA-target gene regulatory network associated with graphene oxide cytotoxicity

Graphene oxide (GO) has recently emanated as a promising material in cancer treatment. To unveil the underlying mechanisms of microRNAs (miRNAs) and potential target genes involved in GO cytotoxicity, we firstly compiled GO-related miRNAs and genes in human cancer cell lines treated with GO from public databases and published works. Besides miRNAs as post-transcriptional regulators of gene expression, transcription factors (TFs) are also the main regulators at the transcriptional level. In the following, we explored the regulatory relationships between miRNAs, target genes, and TFs. Thereafter, a gene regulatory network consisting of GO-responsive miRNAs, GO-responsive genes, and known human TFs was constructed. Then, 3-node regulatory motif types were detected in the resulting network. Among them, miRNA-FFL (feed-forward loop) was identified as a significant motif type. A total of 184 miRNA-FFLs were found and merged to generate a regulatory sub-network. Pathway analysis of the resulting sub-network highlighted adherens junction, focal adhesion, and TGFβ signaling pathways as the major pathways that previous studies demonstrate them to be the affected pathways in GO-treated cells. Functional investigations displayed that miRNAs might be involved in the control of apoptosis through disruption of cell adhesion in response to cytotoxicity. Moreover, GO-cell interactions can lead to miRNA targeting of genes (i.e. Rac1 and RhoA) involved in the cytoskeleton assembly process. These specific toxic properties support biomedical applications of GO, especially for cancer therapy.

Identification of Arbuscular Mycorrhiza Fungi Responsive microRNAs and Their Regulatory Network in Maize

Maize can form symbiotic relationships with arbuscular mycorrhiza (AM) fungus to increase productivity and resistance, but the miRNAs in maize responsible for this process have not been discovered. In this study, 155 known and 28 novel miRNAs were identified by performing high-throughput sequencing of sRNA in maize roots colonized by AM fungi. Similar to the profiles in other AM-capable plants, a large proportion of identified maize miRNAs were 24 nt in length. Fourteen and two miRNAs were significantly down- and up-regulated in response to AM fungus Glomus intraradices inoculation, respectively, suggesting potential roles of these miRNAs in AM symbiosis. Interestingly, 12 of 14 significantly down-regulated known maize miRNAs belong to the miR399 family, which was previously reported to be involved in the interaction between Medicago truncatula and AM fungi. This result indicated that the miR399 family should regulate AM symbiosis conservatively across different plant lineages. Pathway and network analyses showed that the differentially expressed miRNAs might regulate lipid metabolism and phosphate starvation response in maize during the symbiosis process via their target genes. Several members of the miR399 family and the miR397 family should be involved in controlling the fatty acid metabolism and promoting lipid delivering from plants to AM fungi. To the best of our knowledge, this is the first report on miRNAs mediating fatty acids from plant to AM fungi. This study provides insight into the regulatory roles of miRNAs in the symbiosis between plants and AM fungi.

Dissecting the Repertoire of DNA-Binding Transcription Factors of the Archaeon Pyrococcus furiosus DSM 3638

In recent years, there has been a large increase in the amount of experimental evidence for diverse archaeal organisms, and these findings allow for a comprehensive analysis of archaeal genetic organization. However, studies about regulatory mechanisms in this cellular domain are still limited. In this context, we identified a repertoire of 86 DNA-binding transcription factors (TFs) in the archaeon Pyrococcus furiosus DSM 3638, that are clustered into 32 evolutionary families. In structural terms, 45% of these proteins are composed of one structural domain, 41% have two domains, and 14% have three structural domains. The most abundant DNA-binding domain corresponds to the winged helix-turn-helix domain; with few alternative DNA-binding domains. We also identified seven regulons, which represent 13.5% (279 genes) of the total genes in this archaeon. These analyses increase our knowledge about gene regulation in P. furiosus DSM 3638 and provide additional clues for comprehensive modeling of transcriptional regulatory networks in the Archaea cellular domain.

Hanks-Type Serine/Threonine Protein Kinases and Phosphatases in Bacteria: Roles in Signaling and Adaptation to Various Environments

Reversible phosphorylation is a key mechanism that regulates many cellular processes in prokaryotes and eukaryotes. In prokaryotes, signal transduction includes two-component signaling systems, which involve a membrane sensor histidine kinase and a cognate DNA-binding response regulator. Several recent studies indicate that alternative regulatory pathways controlled by Hanks-type serine/threonine kinases (STKs) and serine/threonine phosphatases (STPs) also play an essential role in regulation of many different processes in bacteria, such as growth and cell division, cell wall biosynthesis, sporulation, biofilm formation, stress response, metabolic and developmental processes, as well as interactions (either pathogenic or symbiotic) with higher host organisms. Since these enzymes are not DNA-binding proteins, they exert the regulatory role via post-translational modifications of their protein targets. In this review, we summarize the current knowledge of STKs and STPs, and discuss how these enzymes mediate gene expression in prokaryotes. Many studies indicate that regulatory systems based on Hanks-type STKs and STPs play an essential role in the regulation of various cellular processes, by reversibly phosphorylating many protein targets, among them several regulatory proteins of other signaling cascades. These data show high complexity of bacterial regulatory network, in which the crosstalk between STK/STP signaling enzymes, components of TCSs, and the translational machinery occurs. In this regulation, the STK/STP systems have been proved to play important roles.

MicroRNA Functions in Thymic Biology: Thymic Development and Involution

During the entire processes of thymus organogenesis, maturation, and involution, gene regulation occurs post-transcriptionally via recently discovered microRNA (miRNA) transcripts. Numerous reports indicate that miRNAs may be involved in the construction of a normal thymic microenvironment, which constitutes a critical component to support T lymphocyte development. MiRNAs are also expressed in thymic stromal cells including thymic epithelial cells (TECs) during maturation and senescence. This review focuses on the function of miRNAs in thymic development and involution. A better understanding of these processes will provide new insights into the regulatory network of TECs and further comprehension of how genes control TECs to maintain the thymic microenvironment during thymus development and aging, thus supporting a normal cellular immune system.

Estimating Attractor Reachability in Asynchronous Logical Models

Logical models are well-suited to capture salient dynamical properties of regulatory networks. For networks controlling cell fate decisions, cell fates are associated with model attractors (stable states or cyclic attractors) whose identification and reachability properties are particularly relevant. While synchronous updates assume unlikely instantaneous or identical rates associated with component changes, the consideration of asynchronous updates is more realistic but, for large models, may hinder the analysis of the resulting non-deterministic concurrent dynamics. This complexity hampers the study of asymptotical behaviors, and most existing approaches suffer from efficiency bottlenecks, being generally unable to handle cyclical attractors and quantify attractor reachability. Here, we propose two algorithms providing probability estimates of attractor reachability in asynchronous dynamics. The first algorithm, named Firefront, exhaustively explores the state space from an initial state, and provides quasi-exact evaluations of the reachability probabilities of model attractors. The algorithm progresses in breadth, propagating the probabilities of each encountered state to its successors. Second, Avatar is an adapted Monte Carlo approach, better suited for models with large and intertwined transient and terminal cycles. Avatar iteratively explores the state space by randomly selecting trajectories and by using these random walks to estimate the likelihood of reaching an attractor. Unlike Monte Carlo simulations, Avatar is equipped to avoid getting trapped in transient cycles and to identify cyclic attractors. Firefront and Avatar are validated and compared to related methods, using as test cases logical models of synthetic and biological networks. Both algorithms are implemented as new functionalities of GINsim 3.0, a well-established software tool for logical modeling, providing executable GUI, Java API, and scripting facilities.

Network-Based Approaches to Explore Complex Biological Systems towards Network Medicine

Network medicine relies on different types of networks: from the molecular level of protein–protein interactions to gene regulatory network and correlation studies of gene expression. Among network approaches based on the analysis of the topological properties of protein–protein interaction (PPI) networks, we discuss the widespread DIAMOnD (disease module detection) algorithm. Starting from the assumption that PPI networks can be viewed as maps where diseases can be identified with localized perturbation within a specific neighborhood (i.e., disease modules), DIAMOnD performs a systematic analysis of the human PPI network to uncover new disease-associated genes by exploiting the connectivity significance instead of connection density. The past few years have witnessed the increasing interest in understanding the molecular mechanism of post-transcriptional regulation with a special emphasis on non-coding RNAs since they are emerging as key regulators of many cellular processes in both physiological and pathological states. Recent findings show that coding genes are not the only targets that microRNAs interact with. In fact, there is a pool of different RNAs—including long non-coding RNAs (lncRNAs) —competing with each other to attract microRNAs for interactions, thus acting as competing endogenous RNAs (ceRNAs). The framework of regulatory networks provides a powerful tool to gather new insights into ceRNA regulatory mechanisms. Here, we describe a data-driven model recently developed to explore the lncRNA-associated ceRNA activity in breast invasive carcinoma. On the other hand, a very promising example of the co-expression network is the one implemented by the software SWIM (switch miner), which combines topological properties of correlation networks with gene expression data in order to identify a small pool of genes—called switch genes—critically associated with drastic changes in cell phenotype. Here, we describe SWIM tool along with its applications to cancer research and compare its predictions with DIAMOnD disease genes.

Role of Cytokine Combinations on CD4+ T Cell Differentiation, Partial Polarization, and Plasticity: Continuous Network Modeling Approach

Purpose: We put forward a theoretical and dynamical approach for the semi-quantitative analysis of CD4+ T cell differentiation, the process by which cells with different functions are derived from activated CD4+ T naïve lymphocytes in the presence of particular cytokine microenvironments. We explore the system-level mechanisms that underlie CD4+ T plasticity-the conversion of polarized cells to phenotypes different from those originally induced. Methods: In this paper, we extend a previous study based on a Boolean network to a continuous framework. The network includes transcription factors, signaling pathways, as well as autocrine and exogenous cytokines, with interaction rules derived using fuzzy logic. Results: This approach allows us to assess the effect of relative differences in the concentrations and combinations of exogenous and endogenous cytokines, as well as of the expression levels of diverse transcription factors. We found either abrupt or gradual differentiation patterns between observed phenotypes depending on critical concentrations of single or multiple environmental cytokines. Plastic changes induced by environmental cytokines were observed in conditions of partial phenotype polarization in the T helper 1 to T helper 2 transition. On the other hand, the T helper 17 to induced regulatory T-cells transition was highly dependent on cytokine concentrations, with TGFβ playing a prime role. Conclusion: The present approach is useful to further understand the system-level mechanisms underlying observed patterns of CD4+ T differentiation and response to changing immunological challenges.

Dynamical Analysis of the Regulatory Network Controlling Natural Killer Cells Differentiation

Many disease fighting strategies have focused on the generation of NK cells, since they constitute the main immune barrier against cancer and intracellular pathogens such as viruses. Therefore, a predictive model for the development of NK cells would constitute a useful tool to test several hypotheses regarding the production of these cells during both physiological and pathological conditions. Here, we present a boolean network model that reproduces experimental results reported on the literature regarding the progressive stages of the development of NK cells in wild-type and mutant backgrounds. The model allows for the simulation of different conditions, including extracellular micro-environment as well as the simulation of genetic alterations. It also describes how NK cell differentiation depends on a molecular regulatory network that controls the specification of lymphoid lineages, such as T and B cells, which share a common progenitor with NKs. Furthermore, the study shows that the structure of the regulatory network strongly determines the stability of the expression patterns against perturbations.

Expression and network analysis of YBX1 interactors for identification of new drug targets in lung adenocarcinoma

Y-Box Binding protein 1 (YBX-1) is known to be involved in various types of cancers. It's interactors also play major role in various cellular functions. Present work aimed to study the expression profile of the YBX-1 interactors during lung adenocarcinoma (LUAD). The differential expression analysis involved 57 genes from 95 lung adenocarcinoma samples, construction of gene network and topology analysis. A Total of 43 genes were found to be differentially expressed from which 17 genes were found to be down regulated and 26 genes were up-regulated. We observed that Polyadenylate-binding protein 1 (PABPC1), a protein involved in YBX1 translation, is highly correlated with YBX1. The interaction network analysis for a differentially expressed non-coding RNA Growth Arrest Specific 5 (GAS5) suggests that two proteins namely, Growth Arrest Specific 2 (GAS2) and Peripheral myelin protein 22 (PMP22) are potentially involved in LUAD progression. The network analysis and differential expression suggests that Collagen type 1 alpha 2 (COL1A2) can be potential biomarker and target for LUAD.

Logical Modeling and Analysis of Cellular Regulatory Networks With GINsim 3.0

The logical formalism is well adapted to model large cellular networks, in particular when detailed kinetic data are scarce. This tutorial focuses on this well-established qualitative framework. Relying on GINsim (release 3.0), a software implementing this formalism, we guide the reader step by step toward the definition, the analysis and the simulation of a four-node model of the mammalian p53-Mdm2 network.

Bioinformatics analysis of microarray data to explore the key genes involved in HSF4 mutation-induced cataract

AIM

To reveal the mechanisms of heat-shock transcription factor 4 (HSF4) mutation-induced cataract.

METHODS

GSE22362, including 3 HSF4-null lens and 3 wild-type lens, was obtained from Gene Expression Omnibus database. After data preprocessing, the differentially expressed genes (DEGs) were identified using the limma package. Based on Database for Annotation, Visualization and Integrated Discovery (DAVID) tool, functional and pathway enrichment analyses were performed for the DEGs. Followed by protein-protein interaction (PPI) network was constructed using STRING database and Cytoscape software. Furthermore, the validated microRNA (miRNA)-DEG pairs were obtained from miRWalk2.0 database, and then miRNA-DEG regulatory network was visualized by Cytoscape software.

RESULTS

A total of 176 DEGs were identified in HSF4-null lens compared with wild-type lens. In the PPI network, FBJ osteosarcoma oncogene (FOS), early growth response 1 (EGR1) and heme oxygenase (decycling) 1 (HMOX1) had higher degrees and could interact with each other. Besides, mmu-miR-15a-5p and mmu-miR-26a-5p were among the top 10 miRNAs in the miRNA-DEG regulatory network. Additionally, mmu-miR-26a-5p could target EGR1 in the regulatory network.

CONCLUSION

FOS, EGR1, HMOX1, mmu-miR-26a-5p and mmu-miR-15a-5p might function in the pathogenesis of HSF4 mutation-induced cataract.

A Network of Noncoding Regulatory RNAs Acts in the Mammalian Brain

Noncoding RNAs (ncRNAs) play increasingly appreciated gene-regulatory roles. Here, we describe a regulatory network centered on four ncRNAs-a long ncRNA, a circular RNA, and two microRNAs-using gene editing in mice to probe the molecular consequences of disrupting key components of this network. The long ncRNA Cyrano uses an extensively paired site to miR-7 to trigger destruction of this microRNA. Cyrano-directed miR-7 degradation is much more effective than previously described examples of target-directed microRNA degradation, which come primarily from studies of artificial and viral RNAs. By reducing miR-7 levels, Cyrano prevents repression of miR-7-targeted mRNAs and enables accumulation of Cdr1as, a circular RNA known to regulate neuronal activity. Without Cyrano, excess miR-7 causes cytoplasmic destruction of Cdr1as in neurons, in part through enhanced slicing of Cdr1as by a second miRNA, miR-671. Thus, several types of ncRNAs can collaborate to establish a sophisticated regulatory network.

Identification of key genes in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis

Rheumatoid arthritis (RA) and osteoarthritis (OA) comprise the most common forms of arthritis. The aim of this study was to identify differentially expressed genes (DEGs) and associated biological processes between RA and OA using a bioinformatics approach to elucidate their potential pathogenesis.The gene expression profiles of the GSE55457 datasets, originally produced through use of the high-throughput Affymetrix Human Genome U133A Array, were downloaded from the Gene Expression Omnibus (GEO) database. The GSE55457 dataset contains information from 33 samples, including 10 normal control (NC) samples, 13 RA samples, and 10 OA samples. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed to identify functional categories and associated molecular and biochemical pathways, respectively, for the identified DEGs, and a protein-protein interaction (PPI) network of the DEGs was constructed using Cytoscape software.GO and KEGG results suggested that several biological pathways (ie, "immune response," "inflammation," and "osteoclast differentiation") are commonly involved in the development of both RA and OA, whereas several other pathways (eg, "MAPK signaling pathway," and "ECM-receptor interaction") presented significant differences between these disorders.This study provides further insights into the underlying pathogenesis of RA and OA, which may facilitate the diagnosis and treatment of these diseases.

An integrated analysis of key microRNAs, regulatory pathways and clinical relevance in bladder cancer

OBJECTIVE

The aim of this study was to identify the key microRNAs (miRNAs) and their regulatory networks in bladder cancer (BC).

MATERIALS AND METHODS

Three miRNA and three gene expression microarray datasets were downloaded for analysis from Gene Expression Omnibus database. The differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) were accessed by the use of GEO2R. Gene ontology process and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed by using the Database for Annotation, Visualization and Integrated Discovery program. Protein-protein interaction (PPI) and miRNA-mRNA regulatory networks were established by using the Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape tool. Besides, the results and clinical significance were validated in The Cancer Genome Atlas (TCGA) dataset.

RESULTS

A total of 18 significant DEMs, 121 upregulated DEGs and 199 downregulated DEGs were identified. Functional enrichment analysis showed that significant DEGs were related to cell cycle and MAPK pathway in BC. Key DEGs such as CDK1, CCNB1, VGL and PRKCA were found as the hub genes in PPI networks. TCGA analysis supported our results, and the miRNAs were correlated with the pathological stages and survival of BC patients.

CONCLUSION

In this study, we found 18 DEMs that may play key roles in the regulatory networks of BC. The higher expression of miR-99a, miR-100, miR-125b, miR-145, miR-214 and miR-487b or the lower expression of miR-138 and miR-200a can indicate poor survival in the prognosis of BC. Further experimental studies are required to test our results.

Genome-Scale Architecture of Small Molecule Regulatory Networks and the Fundamental Trade-Off between Regulation and Enzymatic Activity

Metabolic flux is in part regulated by endogenous small molecules that modulate the catalytic activity of an enzyme, e.g., allosteric inhibition. In contrast to transcriptional regulation of enzymes, technical limitations have hindered the production of a genome-scale atlas of small molecule-enzyme regulatory interactions. Here, we develop a framework leveraging the vast, but fragmented, biochemical literature to reconstruct and analyze the small molecule regulatory network (SMRN) of the model organism Escherichia coli, including the primary metabolite regulators and enzyme targets. Using metabolic control analysis, we prove a fundamental trade-off between regulation and enzymatic activity, and we combine it with metabolomic measurements and the SMRN to make inferences on the sensitivity of enzymes to their regulators. Generalizing the analysis to other organisms, we identify highly conserved regulatory interactions across evolutionarily divergent species, further emphasizing a critical role for small molecule interactions in the maintenance of metabolic homeostasis.