TRANSFAC: an integrated system for gene expression regulation

Gene regulatory network inference resources: A practical overview

Transcriptional regulation is a fundamental molecular mechanism involved in almost every aspect of life, from homeostasis to development, from metabolism to behavior, from reaction to stimuli to disease progression. In recent years, the concept of Gene Regulatory Networks (GRNs) has grown popular as an effective applied biology approach for describing the complex and highly dynamic set of transcriptional interactions, due to its easy-to-interpret features. Since cataloguing, predicting and understanding every GRN connection in all species and cellular contexts remains a great challenge for biology, researchers have developed numerous tools and methods to infer regulatory processes. In this review, we catalogue these methods in six major areas, based on the dominant underlying information leveraged to infer GRNs: Coexpression, Sequence Motifs, Chromatin Immunoprecipitation (ChIP), Orthology, Literature and Protein-Protein Interaction (PPI) specifically focused on transcriptional complexes. The methods described here cover a wide range of user-friendliness: from web tools that require no prior computational expertise to command line programs and algorithms for large scale GRN inferences. Each method for GRN inference described herein effectively illustrates a type of transcriptional relationship, with many methods being complementary to others. While a truly holistic approach for inferring and displaying GRNs remains one of the greatest challenges in the field of systems biology, we believe that the integration of multiple methods described herein provides an effective means with which experimental and computational biologists alike may obtain the most complete pictures of transcriptional relationships. This article is part of a Special Issue entitled: Transcriptional Profiles and Regulatory Gene Networks edited by Dr. Federico Manuel Giorgi and Dr. Shaun Mahony.

Inference of plant gene regulatory networks using data-driven methods: A practical overview

Transcriptional regulation is a complex and dynamic process that plays a vital role in plant growth and development. A key component in the regulation of genes is transcription factors (TFs), which coordinate the transcriptional control of gene activity. A gene regulatory network (GRN) is a collection of regulatory interactions between TFs and their target genes. The accurate delineation of GRNs offers a significant contribution to our understanding about how plant cells are organized and function, and how individual genes are regulated in various conditions, organs or cell types. During the past decade, important progress has been made in the identification of GRNs using experimental and computational approaches. However, a detailed overview of available platforms supporting the analysis of GRNs in plants is missing. Here, we review current databases, platforms and tools that perform data-driven analyses of gene regulation in Arabidopsis. The platforms are categorized into two sections, 1) promoter motif analysis tools that use motif mapping approaches to find TF motifs in the regulatory sequences of genes of interest and 2) network analysis tools that identify potential regulators for a set of input genes using a range of data types in order to generate GRNs. We discuss the diverse datasets integrated and highlight the strengths and caveats of different platforms. Finally, we shed light on the limitations of the above approaches and discuss future perspectives, including the need for integrative approaches to unravel complex GRNs in plants.

A method for identifying allele-specific hydroxymethylation

We previously identified sequence-dependent allele-specific methylation (sd-ASM) in adult human peripheral blood leukocytes, in which ASM occurs in cis depending on adjacent polymorphic sequences. A number of groups have identified sd-ASM sites in the human and mouse genomes, illustrating the prevalence of sd-ASM in mammalian genomes. In addition, sd-ASM can lead to sequence-dependent allele-specific expression of neighbouring genes. Imprinted genes also often exhibit parent-of-origin-dependent allele-specific methylation (pd-ASM), which causes parent-of-origin-dependent allele-specific expression. However, whether most of the already known sd-ASM and pd-ASM sites are methylated or hydroxymethylated remains unclear due to technical restrictions. Accordingly, a novel method that enables examination of allelic methylation and hydroxymethylation status and also overcomes the drawbacks of conventional methods is needed. Such a method could also be used to elucidate the mechanisms underlying polymorphism-associated inter-individual differences in disease susceptibility and the mechanism of genomic imprinting. Here, we developed a simple method to determine allelic hydroxymethylation status and identified novel sequence- and parent-of-origin-dependent allele-specific hydroxymethylation sites. Correlation analyses of TF binding sequences and methylation or hydroxymethylation between three mouse strains revealed the involvement of Pax5 in strain-specific methylation and hydroxymethylation in exon 7 of Pdgfrb.

A Muscle Hybrid Promoter as a Novel Tool for Gene Therapy

Gene therapy is a promising strategy to cure rare diseases. The lack of regulatory sequences ensuring specific and robust expression in skeletal and cardiac muscle is a substantial limitation of gene therapy efficiency targeting the muscle tissue. Here we describe a novel muscle hybrid (MH) promoter that is highly active in both skeletal and cardiac muscle cells. It has an easily exchangeable modular structure, including an intronic module that highly enhances the expression of the gene driven by it. In cultured myoblasts, myotubes, and cardiomyocytes, the MH promoter gives relatively stable expression as well as higher activity and protein levels than the standard CMV and desmin gene promoters or the previously developed synthetic or CKM-based promoters. Combined with AAV2/9, the MH promoter also provides a high in vivo expression level in skeletal muscle and the heart after both intramuscular and systemic delivery. It is much more efficient than the desmin-encoding gene promoter, and it maintains the same specificity. This novel promoter has potential for gene therapy in muscle cells. It can provide stable transgene expression, ensuring high levels of therapeutic protein, and limited side effects because of its specificity. This constitutes an improvement in the efficiency of genetic disease therapy.

A network-based analysis for mining the risk pathways in glioblastoma

The most malignant type of brain tumour is glioblastoma multiforme (GBM). Patients with GBM often have a poor prognosis, as a result of incomplete or inaccurate diagnoses. Regulatory pathways have been demonstrated to serve important roles in complex human diseases. Therefore, deciphering these risk pathways may shed light on the molecular mechanisms underlying GBM progression. In the present study, differentially expressed genes and microRNAs (miRNAs) in a publicly available database were identified between normal and tumour samples. To determine the pathophysiology and molecular mechanisms underlying GBM, integrated network analysis was performed to mine GBM-specific risk pathways. Specifically, a GBM-specific regulatory network was constructed that integrated manually curated GBM-associated transcription and post-transcriptional data resources, including transcription factors and miRNAs. A total of 1,827 differentially expressed genes and 30 miRNAs were identified. The differentially expressed genes were significantly enriched in a number of immune response-associated functions. Based on the GBM-specific regulatory network, 15 risk regulatory pathways containing not only known regulators, but also potential novel targets that might be involved in tumourigenesis were identified. Network analysis provides a strategy for leveraging genomic data to identify potential oncogenic pathways and molecular targets for GBM.

MeDReaders: a database for transcription factors that bind to methylated DNA

Understanding the molecular principles governing interactions between transcription factors (TFs) and DNA targets is one of the main subjects for transcriptional regulation. Recently, emerging evidence demonstrated that some TFs could bind to DNA motifs containing highly methylated CpGs both in vitro and in vivo. Identification of such TFs and elucidation of their physiological roles now become an important stepping-stone toward understanding the mechanisms underlying the methylation-mediated biological processes, which have crucial implications for human disease and disease development. Hence, we constructed a database, named as MeDReaders, to collect information about methylated DNA binding activities. A total of 731 TFs, which could bind to methylated DNA sequences, were manually curated in human and mouse studies reported in the literature. In silico approaches were applied to predict methylated and unmethylated motifs of 292 TFs by integrating whole genome bisulfite sequencing (WGBS) and ChIP-Seq datasets in six human cell lines and one mouse cell line extracted from ENCODE and GEO database. MeDReaders database will provide a comprehensive resource for further studies and aid related experiment designs. The database implemented unified access for users to most TFs involved in such methylation-associated binding actives. The website is available at http://medreader.org/.

YEASTRACT: an upgraded database for the analysis of transcription regulatory networks in Saccharomyces cerevisiae

The YEAst Search for Transcriptional Regulators And Consensus Tracking (YEASTRACT—www.yeastract.com) information system has been, for 11 years, a key tool for the analysis and prediction of transcription regulatory associations at the gene and genomic levels in Saccharomyces cerevisiae. Since its last update in June 2017, YEASTRACT includes approximately 163000 regulatory associations between transcription factors (TF) and target genes in S. cerevisiae, based on more than 1600 bibliographic references; it also includes 247 specific DNA binding consensus recognized by 113 TFs. This release of the YEASTRACT database provides new visualization tools to visualize each regulatory network in an interactive fashion, enabling the user to select and observe subsets of the network such as: (i) considering only DNA binding evidence or both DNA binding and expression evidence; (ii) considering only either positive or negative regulatory associations; or (iii) considering only one set of related environmental conditions. A further tool to observe TF regulons is also offered, enabling a clear-cut understanding of the exact meaning of the available data. We believe that with this new version, YEASTRACT will improve its role as an open web resource instrumental for Yeast Biologists and Systems Biology researchers.

TFutils: Data structures for transcription factor bioinformatics

DNA transcription is intrinsically complex. Bioinformatic work with transcription factors (TFs) is complicated by a multiplicity of data resources and annotations. The Bioconductor package TFutils includes data structures and functions to enhance the precision and utility of integrative analyses that have components involving TFs. TFutils provides catalogs of human TFs from three reference sources (CISBP, HOCOMOCO, and GO), a catalog of TF targets derived from MSigDb, and multiple approaches to enumerating TF binding sites, including an interface to results of 690 ENCODE experiments. Aspects of integration of TF binding patterns and genome-wide association study results are explored in examples.

Role of 4‑aminobutyrate aminotransferase (ABAT) and the lncRNA co‑expression network in the development of myelodysplastic syndrome

IncRNAs play an important role in the regulation of gene expression. The present study profiled differentially expressed lncRNAs (DELs) and mRNAs (DEMs) in myelodysplastic syndrome (MDS) to construct a 4-aminobutyrate aminotransferase (ABAT)-DEL-DEM co-expression network in MDS development using the Agilent human BeadChips and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and network analyses. Compared with controls, there were 543 DELs and 2,705 DEMs in MDS patients, among which 285 (52.5%) DELs were downregulated and 258 (47.5%) DELs were upregulated, whereas 1,521 (56.2%) DEMs were downregulated and 1,184 (43.70%) DEMs were upregulated in MDS patients. The ABAT-DEL-DEM co-expression network contained six DELs that were co-expressed with ABAT in MDS. The GO analysis revealed that the co-expression network mainly participated in response to organic cyclic compound, cell proliferation, cell part morphogenesis, regulation of cell proliferation and enzyme-linked receptor protein signaling pathways, while the KEGG database showed that the co-expression network was involved in various pathways, such as phagosome and metabolic pathways. Furthermore, the expression of a selected DEL (lncENST00000444102) and ABAT was shown to be significantly downregulated in MDS patients, and in SKM-1 and THP-1 cells. The selected lncENST00000444102 was then overexpressed and ABAT expression was knocked down in the MDS cell lines using lentiviral transfection. In addition, lncENST00000444102 overexpression reduced the viability and increased the apoptosis of MDS cells, ABAT expression was upregulated by lncENST00000444102.

Rare non-coding Desmoglein-2 variant contributes to Arrhythmogenic right ventricular cardiomyopathy

Arrhythmogenic right ventricular cardiomyopathy (ARVC) has been linked to variants in the coding sequence of desmosomal genes. The potential contribution of non-coding desmoglein-2 (DSG2) variants for development of ARVC is undescribed. We sequenced 1450 base pairs upstream of ATG in the DSG2 gene in 65 unrelated patients diagnosed with ARVC (10 borderline cases). Identified variants was evaluated by cosegregation and allele population frequency analysis, in silico tools, immunohistological investigations of myocardial biopsies, gene reporter assays, electrophoretic mobility shift assays (EMSA), and chromatin immunoprecipitation. The genetic analysis identified one novel, rare heterozygous DSG2 upstream variant (-317G > A) in a genetically unexplained ARVC patient. The variant segregated with signs of disease, was absent in publicly available databases, and affected a predicted binding site for activating protein-1 (AP-1). Immunohistochemical analysis of a myocardial biopsy from the -317G > A patient showed a marked reduction in DSG2 protein levels compared to healthy controls. Luciferase reporter gene assays showed promoter activity of the identified DSG2 upstream region and a general reduction in transcriptional activity in the presence of the minor DSG2_A allele (p < .01). Moreover, the DSG2_A allele reduced DSG2 activation by TGF-beta1 and a protein kinase C pathway activator (PMA; all p < .001 vs. DSG2_G). EMSAs showed altered transcription factor binding in presence of the DSG2_A allele. Chromatin immunoprecipitation assays in wild type epithelial cells identified AP-1 components c-FOS and c-JUN at the -317 locus. In conclusion, the non-coding DSG2 promoter variant -317G > A reduces DSG2 transcription in vitro and reduced myocardial DSG2 protein levels were observed in vivo. Our data support a contribution of non-coding DSG2 variants to the pathogenesis of ARVC.

Exploring integument transcriptomes, cuticle ultrastructure, and cuticular hydrocarbons profiles in eusocial and solitary bee species displaying heterochronic adult cuticle maturation

Differences in the timing of exoskeleton melanization and sclerotization are evident when comparing eusocial and solitary bees. This cuticular maturation heterochrony may be associated with life style, considering that eusocial bees remain protected inside the nest for many days after emergence, while the solitary bees immediately start outside activities. To address this issue, we characterized gene expression using large-scale RNA sequencing (RNA-seq), and quantified cuticular hydrocarbon (CHC) through gas chromatography-mass spectrometry in comparative studies of the integument (cuticle plus its underlying epidermis) of two eusocial and a solitary bee species. In addition, we used transmission electron microscopy (TEM) for studying the developing cuticle of these and other three bee species also differing in life style. We found 13,200, 55,209 and 30,161 transcript types in the integument of the eusocial Apis mellifera and Frieseomelitta varia, and the solitary Centris analis, respectively. In general, structural cuticle proteins and chitin-related genes were upregulated in pharate-adults and newly-emerged bees whereas transcripts for odorant binding proteins, cytochrome P450 and antioxidant proteins were overrepresented in foragers. Consistent with our hypothesis, a distance correlation analysis based on the differentially expressed genes suggested delayed cuticle maturation in A. mellifera in comparison to the solitary bee. However, this was not confirmed in the comparison with F. varia. The expression profiles of 27 of 119 genes displaying functional attributes related to cuticle formation/differentiation were positively correlated between A. mellifera and F. varia, and negatively or non-correlated with C. analis, suggesting roles in cuticular maturation heterochrony. However, we also found transcript profiles positively correlated between each one of the eusocial species and C. analis. Gene co-expression networks greatly differed between the bee species, but we identified common gene interactions exclusively between the eusocial species. Except for F. varia, the TEM analysis is consistent with cuticle development timing adapted to the social or solitary life style. In support to our hypothesis, the absolute quantities of n-alkanes and unsaturated CHCs were significantly higher in foragers than in the earlier developmental phases of the eusocial bees, but did not discriminate newly-emerged from foragers in C. analis. By highlighting differences in integument gene expression, cuticle ultrastructure, and CHC profiles between eusocial and solitary bees, our data provided insights into the process of heterochronic cuticle maturation associated to the way of life.

Allele specific chromatin signals, 3D interactions, and motif predictions for immune and B cell related diseases

Several Genome Wide Association Studies (GWAS) have reported variants associated to immune diseases. However, the identified variants are rarely the drivers of the associations and the molecular mechanisms behind the genetic contributions remain poorly understood. ChIP-seq data for TFs and histone modifications provide snapshots of protein-DNA interactions allowing the identification of heterozygous SNPs showing significant allele specific signals (AS-SNPs). AS-SNPs can change a TF binding site resulting in altered gene regulation and are primary candidates to explain associations observed in GWAS and expression studies. We identified 17,293 unique AS-SNPs across 7 lymphoblastoid cell lines. In this set of cell lines we interrogated 85% of common genetic variants in the population for potential regulatory effect and we identified 237 AS-SNPs associated to immune GWAS traits and 714 to gene expression in B cells. To elucidate possible regulatory mechanisms we integrated long-range 3D interactions data to identify putative target genes and motif predictions to identify TFs whose binding may be affected by AS-SNPs yielding a collection of 173 AS-SNPs associated to gene expression and 60 to B cell related traits. We present a systems strategy to find functional gene regulatory variants, the TFs that bind differentially between alleles and novel strategies to detect the regulated genes.

Systems Biology Approach to Identify Novel Genomic Determinants for Pancreatic Cancer Pathogenesis

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with a 5-year survival rate of <8%. Its dismal prognosis stems from inefficient therapeutic modalities owing to the lack of understanding about pancreatic cancer pathogenesis. Considering the molecular complexity and heterogeneity of PDAC, identification of novel molecular contributors involved in PDAC onset and progression using global "omics" analysis will pave the way to improved strategies for disease prevention and therapeutic targeting. Meta-analysis of multiple miRNA microarray datasets containing healthy controls (HC), chronic pancreatitis (CP) and PDAC cases, identified 13 miRNAs involved in the progression of PDAC. These miRNAs showed dysregulation in both tissue as well as blood samples, along with progressive decrease in expression from HC to CP to PDAC. Gene-miRNA interaction analysis further elucidated 5 miRNAs (29a/b, 27a, 130b and 148a) that are significantly downregulated in conjunction with concomitant upregulation of their target genes throughout PDAC progression. Among these, miRNA-29a/b targeted genes were found to be most significantly altered in comparative profiling of HC, CP and PDAC, indicating its involvement in malignant evolution. Further, pathway analysis suggested direct involvement of miRNA-29a/b in downregulating the key pathways associated with PDAC development and metastasis including focal adhesion signaling and extracellular matrix organization. Our systems biology data analysis, in combination with real-time PCR validation indicates direct functional involvement of miRNA-29a in PDAC progression and is a potential prognostic marker and therapeutic candidate for patients with progressive disease.

Constructing tissue-specific transcriptional regulatory networks via a Markov random field

BACKGROUND

Recent advances in sequencing technologies have enabled parallel assays of chromatin accessibility and gene expression for major human cell lines. Such innovation provides a great opportunity to decode phenotypic consequences of genetic variation via the construction of predictive gene regulatory network models. However, there still lacks a computational method to systematically integrate chromatin accessibility information with gene expression data to recover complicated regulatory relationships between genes in a tissue-specific manner.

RESULTS

We propose a Markov random field (MRF) model for constructing tissue-specific transcriptional regulatory networks via integrative analysis of DNase-seq and RNA-seq data. Our method, named CSNets (cell-line specific regulatory networks), first infers regulatory networks for individual cell lines using chromatin accessibility information, and then fine-tunes these networks using the MRF based on pairwise similarity between cell lines derived from gene expression data. Using this method, we constructed regulatory networks specific to 110 human cell lines and 13 major tissues with the use of ENCODE data. We demonstrated the high quality of these networks via comprehensive statistical analysis based on ChIP-seq profiles, functional annotations, taxonomic analysis, and literature surveys. We further applied these networks to analyze GWAS data of Crohn's disease and prostate cancer. Results were either consistent with the literature or provided biological insights into regulatory mechanisms of these two complex diseases. The website of CSNets is freely available at http://bioinfo.au.tsinghua.edu.cn/jianglab/CSNETS/ .

CONCLUSIONS

CSNets demonstrated the power of joint analysis on epigenomic and transcriptomic data towards the accurate construction of gene regulatory network. Our work provides not only a useful resource of regulatory networks to the community, but also valuable experiences in methodology development for multi-omics data integration.

A new sequence logo plot to highlight enrichment and depletion

BACKGROUND

Sequence logo plots have become a standard graphical tool for visualizing sequence motifs in DNA, RNA or protein sequences. However standard logo plots primarily highlight enrichment of symbols, and may fail to highlight interesting depletions. Current alternatives that try to highlight depletion often produce visually cluttered logos.

RESULTS

We introduce a new sequence logo plot, the EDLogo plot, that highlights both enrichment and depletion, while minimizing visual clutter. We provide an easy-to-use and highly customizable R package Logolas to produce a range of logo plots, including EDLogo plots. This software also allows elements in the logo plot to be strings of characters, rather than a single character, extending the range of applications beyond the usual DNA, RNA or protein sequences. And the software includes new Empirical Bayes methods to stabilize estimates of enrichment and depletion, and thus better highlight the most significant patterns in data. We illustrate our methods and software on applications to transcription factor binding site motifs, protein sequence alignments and cancer mutation signature profiles.

CONCLUSIONS

Our new EDLogo plots and flexible software implementation can help data analysts visualize both enrichment and depletion of characters (DNA sequence bases, amino acids, etc.) across a wide range of applications.

Methylglyoxal induces retinopathy-type lesions in the absence of hyperglycemia: studies in a rat model

The aim of this study was to evaluate whether damage to the neurovascular unit in diabetes depends on reactive metabolites such as methylglyoxal (MG), and to assess its impact on retinal gene expression. Male Wistar rats were supplied with MG (50 mM) by drinking water and compared with age-matched streptozotocin-diabetic animals and untreated controls. Retinal damage was evaluated for the accumulation of MG-derived advanced glycation end products, changes in hexosamine and PKC pathway activation, microglial activation, vascular alterations (pericyte loss and vasoregression), neuroretinal function assessed by electroretinogram, and neurodegeneration. Retinal gene regulation was studied by microarray analysis, and transcription factor involvement was identified by upstream regulator analysis. Systemic application of MG by drinking water increased retinal MG to levels comparable with diabetic animals. Elevated retinal MG resulted in MG-derived hydroimidazolone modifications in the ganglion cell layer, inner nuclear layer, and outer nuclear layer, a moderate activation of the hexosamine pathway, a pan-retinal activation of microglia, loss of pericytes, increased formation of acellular capillaries, decreased function of bipolar cells, and increased expression of the crystallin gene family. MG mimics important aspects of diabetic retinopathy and plays a pathogenic role in microglial activation, vascular damage, and neuroretinal dysfunction. In response to MG, the retina induces expression of neuroprotective crystallins.-Schlotterer, A., Kolibabka, M., Lin, J., Acunman, K., Dietrich, N., Sticht, C., Fleming, T., Nawroth, P., Hammes, H.-P. Methylglyoxal induces retinopathy-type lesions in the absence of hyperglycemia: studies in a rat model.

Integrative workflows for network analysis

Due to genetic heterogeneity across patients, the identification of effective disease signatures and therapeutic targets is challenging. Addressing this challenge, we have previously developed a network-based approach, which integrates heterogeneous sources of biological information to identify disease specific core-regulatory networks. In particular, our workflow uses a multi-objective optimization function to calculate a ranking score for network components (e.g. feedback/feedforward loops) based on network properties, biomedical and high-throughput expression data. High ranked network components are merged to identify the core-regulatory network(s) that is then subjected to dynamical analysis using stimulus-response and in silico perturbation experiments for the identification of disease gene signatures and therapeutic targets. In a case study, we implemented our workflow to identify bladder and breast cancer specific core-regulatory networks underlying epithelial-mesenchymal transition from the E2F1 molecular interaction map.In this study, we review our workflow and described how it has developed over time to understand the mechanisms underlying disease progression and prediction of signatures for clinical decision making.

A comprehensive manually-curated compendium of bovine transcription factors

Transcription factors (TFs) are pivotal regulatory proteins that control gene expression in a context-dependent and tissue-specific manner. In contrast to human, where comprehensive curated TF collections exist, bovine TFs are only rudimentary recorded and characterized. In this article, we present a manually-curated compendium of 865 sequence-specific DNA-binding bovines TFs, which we analyzed for domain family distribution, evolutionary conservation, and tissue-specific expression. In addition, we provide a list of putative transcription cofactors derived from known interactions with the identified TFs. Since there is a general lack of knowledge concerning the regulation of gene expression in cattle, the curated list of TF should provide a basis for an improved comprehension of regulatory mechanisms that are specific to the species.

Burkitt lymphoma-associated network construction and important network motif analysis

Biological and medical researchers have discovered numerous transcription factors (TFs), microRNAs (miRNAs) and genes associated with Burkitt lymphoma (BL) through individual experiments; however, their regulatory mechanisms remain unclear. In the present study, BL-dysregulated and BL-associated networks were constructed to investigate these mechanisms. All data and regulatory associations were from known data resources and literature. The dysregulated network consisted of dysregulated TFs, miRNAs and genes, and partially determined the pathogenesis mechanisms underlying BL. The BL-associated network consisted of BL-associated TFs, miRNAs and genes. It has been indicated that the network motif consisted of TFs, miRNAs and genes serve potential functions in numerous biological processes within cancer. Two of the most studied network motifs are feedback loop (FBL) and feed-forward loop (FFL). The important network motifs were extracted, including the FBL motif, 3-nodes FFL motif and 4-nodes motif, from BL-dysregulated and BL-associated networks, and 10 types of motifs were identified from BL-associated network. Finally, 26/31 FBL motifs, 45/75 3-nodes FFL motifs and 54/94 4-nodes motifs were obtained from the dysregulated/associated networks. A total of four TFs (E2F1, NFKB1, E2F4 and TCF3) exhibit complicated regulation associations in BL-associated networks. The biological network does not demonstrate the dysregulated status for healthy people. When the individual becomes unwell, their biological network exhibits a dysregulated status. If the dysregulated status is regulated to a normal status by a number of medical methods, the diseases may be treated successfully. BL-dysregulated networks serve important roles in pathogenesis mechanisms underlying BL regulation of the dysregulated network, which may be an effective strategy that contributes to gene therapy for BL.

Silencing of adaptor protein SH3BP2 reduces KIT/PDGFRA receptors expression and impairs gastrointestinal stromal tumors growth

Gastrointestinal stromal tumors (GISTs) represent about 80% of the mesenchymal neoplasms of the gastrointestinal tract. Most GISTs contain oncogenic KIT (85%) or PDGFRA (5%) receptors. The kinase inhibitor imatinib mesylate is the preferential treatment for these tumors; however, the development of drug resistance has highlighted the need for novel therapeutic strategies. Recently, we reported that the adaptor molecule SH3 Binding Protein 2 (SH3BP2) regulates KIT expression and signaling in human mast cells. Our current study shows that SH3BP2 is expressed in primary tumors and cell lines from GIST patients and that SH3BP2 silencing leads to a downregulation of oncogenic KIT and PDGFRA expression and an increase in apoptosis in imatinib-sensitive and imatinib-resistant GIST cells. The microphthalmia-associated transcription factor (MITF), involved in KIT expression in mast cells and melanocytes, is expressed in GISTs. Interestingly, MITF is reduced after SH3BP2 silencing. Importantly, reconstitution of both SH3BP2 and MITF restores cell viability. Furthermore, SH3BP2 silencing significantly reduces cell migration and tumor growth of imatinib-sensitive and imatinib-resistant cells in vivo. Altogether, SH3BP2 regulates KIT and PDGFRA expression and cell viability, indicating a role as a potential target in imatinib-sensitive and imatinib-resistant GISTs.

BRCA1 and BRCA2 gene variants and nonsyndromic cleft lip/palate

BACKGROUND

Nonsyndromic cleft lip with or without cleft palate (NSCL/P) is a debilitating condition that not only affects the individual, but the entire family. The purpose of this study was to investigate the association of BRCA1 and BRCA2 genes with NSCL/P.

METHODS

Twelve polymorphisms in/nearby BRCA1 and BRCA2 were genotyped using Taqman chemistry. Our data set consisted of 3,473 individuals including 2,191 nonHispanic white (NHW) individuals (from 151 multiplex and 348 simplex families) and 1,282 Hispanic individuals (from 92 multiplex and 216 simplex families). Data analysis was performed using Family-Based Association Test (FBAT), stratified by ethnicity and family history of NSCL/P.

RESULTS

Nominal associations were found between NSCL/P and BRCA1 in Hispanics and BRCA2 in NHW and Hispanics (p < .05). Significant haplotype associations were found between NSCL/P and both BRCA1 and BRCA2 (p ≤ .004).

CONCLUSIONS

Our results suggest a modest association between BRCA1 and BRCA2 and NSCL/P. Further studies in additional populations and functional studies are needed to elucidate the role of these genes in developmental processes and signaling pathways contributing to NSCL/P.

Transcription Factor Binding Site Enrichment Analysis in Co-Expression Modules in Celiac Disease

The aim of this study was to construct celiac co-expression patterns at a whole genome level and to identify transcription factors (TFs) that could drive the gliadin-related changes in coordination of gene expression observed in celiac disease (CD). Differential co-expression modules were identified in the acute and chronic responses to gliadin using expression data from a previous microarray study in duodenal biopsies. Transcription factor binding site (TFBS) and Gene Ontology (GO) annotation enrichment analyses were performed in differentially co-expressed genes (DCGs) and selection of candidate regulators was performed. Expression of candidates was measured in clinical samples and the activation of the TFs was further characterized in C2BBe1 cells upon gliadin challenge. Enrichment analyses of the DCGs identified 10 TFs and five were selected for further investigation. Expression changes related to active CD were detected in four TFs, as well as in several of their in silico predicted targets. The activation of TFs was further characterized in C2BBe1 cells upon gliadin challenge, and an increase in nuclear translocation of CAMP Responsive Element Binding Protein 1 (CREB1) and IFN regulatory factor-1 (IRF1) in response to gliadin was observed. Using transcriptome-wide co-expression analyses we are able to propose novel genes involved in CD pathogenesis that respond upon gliadin stimulation, also in non-celiac models.

MiR-23a transcriptional activated by Runx2 increases metastatic potential of mouse hepatoma cell via directly targeting Mgat3

MicroRNAs (miRNAs) and aberrant glycosylation both play important roles in tumor metastasis. In this study, the role of miR-23a in N-glycosylation and the metastasis of mouse hepatocellular carcinoma (HCC) cells was investigated. The miRNA expression array profiles that were confirmed by qPCR and Western blot analyses revealed higher miR-23a expression levels in Hca-P cells (with lymphatic metastasis potential) than in Hepa1-6 cells (with no lymphatic metastasis potential), while the expression of mannoside acetylglucosaminyltransferase 3 (Mgat3) was negatively associated with metastasis potential. Mgat3 is a key glycosyltransferase in the synthesis of the bisecting (β1,4GlcNAc branching) N-glycan structure. Bioinformatics analysis indicated that Mgat3 may be a target of miR-23a, and this hypothesis was verified by dual-luciferase reporter gene assays. Furthermore, we found that the transcription factor Runx2 can directly bind to the miR-23a gene promoter and promote its expression, as shown in dual-luciferase reporter gene assays and ChIP assays. Collectively, these results indicate that miR-23a might increase the metastatic potential of mouse HCC by affecting the branch formation of N-glycan chains presented on the cell surface through the targeting of the glycosyltransferase Mgat3. These findings may provide insight into the relationship between abnormal miRNA expression and aberrant glycosylation during tumor lymphatic metastasis.

Automated transition analysis of activated gene regulation during diauxic nutrient shift in Escherichia coli and adipocyte differentiation in mouse cells

Background

Comprehensively understanding the dynamics of biological systems is among the biggest current challenges in biology and medicine. To acquire this understanding, researchers have measured the time-series expression profiles of cell lines of various organisms. Biological technologies have also drastically improved, providing a huge amount of information with support from bioinformatics and systems biology. However, the transitions between the activation and inactivation of gene regulations, at the temporal resolution of single time points, are difficult to extract from time-course gene expression profiles.

Results

Our proposed method reports the activation period of each gene regulation from gene expression profiles and a gene regulatory network. The correctness and effectiveness of the method were validated by analyzing the diauxic shift from glucose to lactose in Escherichia coli. The method completely detected the three periods of the shift; 1) consumption of glucose as nutrient source, 2) the period of seeking another nutrient source and 3) consumption of lactose as nutrient source. We then applied the method to mouse adipocyte differentiation data. Cell differentiation into adipocytes is known to involve two waves of the gene regulation cascade, and sub-waves are predicted. From the gene expression profiles of the cell differentiation process from ES to adipose cells (62 time points), our method acquired four periods; three periods covering the two known waves of the cascade, and a final period of gene regulations when the differentiation to adipocytes was completed.

Conclusions

Our proposed method identifies the transitions of gene regulations from time-series gene expression profiles. Dynamic analyses are essential for deep understanding of biological systems and for identifying the causes of the onset of diseases such as diabetes and osteoporosis. The proposed method can greatly contribute to the progress of biology and medicine.

PCR Assembly of Synthetic Promoters

In this chapter, we describe a two-step assembly PCR method to construct synthetic promoters. Essentially, this method takes advantage of specific annealing between complimentary DNA sequences to build random TFBS combinations within the assembled PCR products. A DNA polymerase is then employed to fill in the unpaired nucleotides in the generated sequences and also to amplify the assembled PCR products. We have used this method to generate synthetic promoters whereby the orientation of the TFBS can be controlled, the spacing between TFBS can be predetermined, and also the full diversity of the consensus TFBS can be covered through the use of degenerate oligonucleotides .

Uncovering transcription factor and microRNA risk regulatory pathways associated with osteoarthritis by network analysis

Osteoarthritis (OA) is the most common form of joint disease. The development of inflammation have been considered to play a key role during the progression of OA. Regulatory pathways are known to play crucial roles in many pathogenic processes. Thus, deciphering these risk regulatory pathways is critical for elucidating the mechanisms underlying OA. We constructed an OA-specific regulatory network by integrating comprehensive curated transcription and post-transcriptional resource involving transcription factor (TF) and microRNA (miRNA). To deepen our understanding of underlying molecular mechanisms of OA, we developed an integrated systems approach to identify OA-specific risk regulatory pathways. In this study, we identified 89 significantly differentially expressed genes between normal and inflamed areas of OA patients. We found the OA-specific regulatory network was a standard scale-free network with small-world properties. It significant enriched many immune response-related functions including leukocyte differentiation, myeloid differentiation and T cell activation. Finally, 141 risk regulatory pathways were identified based on OA-specific regulatory network, which contains some known regulator of OA. The risk regulatory pathways may provide clues for the etiology of OA and be a potential resource for the discovery of novel OA-associated disease genes.

HPV-16 E7 expression up-regulates phospholipase D activity and promotes rapamycin resistance in a pRB-dependent manner

Background

Human Papillomavirus (HPV) infection is the main risk factor for the development and progression of cervical cancer. HPV-16 E6 and E7 expression is essential for induction and maintenance of the transformed phenotype. These oncoproteins interfere with the function of several intracellular proteins, including those controlling the PI3K/AKT/mTOR pathway in which Phospolipase D (PLD) and Phosphatidic acid (PA) play a critical role.

Methods

PLD activity was measured in primary human keratinocytes transduced with retroviruses expressing HPV-16 E6, E7 or E7 mutants. The cytostatic effect of rapamycin, a well-known mTOR inhibitor with potential clinical applications, was evaluated in monolayer and organotypic cultures.

Results

HPV-16 E7 expression in primary human keratinocytes leads to an increase in PLD expression and activity. Moreover, this activation is dependent on the ability of HPV-16 E7 to induce retinoblastoma protein (pRb) degradation. We also show that cells expressing HPV-16 E7 or silenced for pRb acquire resistance to the antiproliferative effect of rapamycin.

Conclusion

This is the first indication that HPV oncoproteins can affect PLD activity. Since PA can interfere with the ability of rapamycin to bind mTOR, the use of combined strategies to target mTOR and PLD activity might be considered to treat HPV-related malignancies.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4392-8) contains supplementary material, which is available to authorized users.

Evolution of DNAase I Hypersensitive Sites in MHC Regulatory Regions of Primates

It has been challenging to determine the disease-causing variant(s) for most major histocompatibility complex (MHC)-associated diseases. However, it is becoming increasingly clear that regulatory variation is pervasive and a fundamentally important mechanism governing phenotypic diversity and disease susceptibility. We gathered DNase I data from 136 human cells to characterize the regulatory landscape of the MHC region, including 4867 DNase I hypersensitive sites (DHSs). We identified thousands of regulatory elements that have been gained or lost in the human or chimpanzee genomes since their evolutionary divergence. We compared alignments of the DHS across six primates and found 149 DHSs with convincing evidence of positive and/or purifying selection. Of these DHSs, compared to neutral sequences, 24 evolved rapidly in the human lineage. We identified 15 instances of transcription-factor-binding motif gains, such as USF, MYC, MAX, MAFK, STAT1, PBX3, etc, and observed 16 GWAS (genome-wide association study) SNPs associated with diseases within these 24 DHSs using FIMO (Find Individual Motif Occurrences) and UCSC (University of California, Santa Cruz) ChIP-seq data. Combining eQTL and Hi-C data, our results indicated that there were five SNPs located in human gains motifs affecting the corresponding gene's expression, two of which closely matched DHS target genes. In addition, a significant SNP, rs7756521, at genome-wide significant level likely affects DDR expression and represents a causal genetic variant for HIV-1 control. These results indicated that species-specific motif gains or losses of rapidly evolving DHSs in the primate genomes might play a role during adaptation evolution and provided some new evidence for a potentially causal role for these GWAS SNPs.

Selection on the regulation of sympathetic nervous activity in humans and chimpanzees

Adrenergic α2C receptor (ADRA2C) is an inhibitory modulator of the sympathetic nervous system. Knockout mice for this gene show physiological and behavioural alterations that are associated with the fight-or-flight response. There is evidence of positive selection on the regulation of this gene during chicken domestication. Here, we find that the neuronal expression of ADRA2C is lower in human and chimpanzee than in other primates. On the basis of three-dimensional chromatin structure, we identified a cis-regulatory region whose DNA sequences have been significantly accelerated in human and chimpanzee. Active histone modification marks this region in rhesus macaque but not in human and chimpanzee; instead, repressive marks are enriched in various human brain samples. This region contains two neuron-restrictive silencer factor (NRSF) binding motifs, each of which harbours a polymorphism. Our genotyping and analysis of population genome data indicate that at both polymorphic sites, the derived allele has reached fixation in humans and chimpanzees but not in bonobos, whereas only the ancestral allele is present among macaques. Our CRISPR/Cas9 genome editing and reporter assays show that both derived nucleotides repress ADRA2C, most likely by increasing NRSF binding. In addition, we detected signatures of recent positive selection for lower neuronal ADRA2C expression in humans. Our findings indicate that there has been selective pressure for enhanced sympathetic nervous activity in the evolution of humans and chimpanzees.

Clinical and Functional Characterization of a Missense ELF2 Variant in a CANVAS Family

Cerebellar ataxia with neuropathy and bilateral vestibular areflexia syndrome (CANVAS) is a rare disorder with an unknown etiology. We present a British family with presumed autosomal dominant CANVAS with incomplete penetrance and variable expressivity. Exome sequencing identified a rare missense variant in the ELF2 gene at chr4:g.140058846 C > T, c.10G > A, p.A4T which segregated in all affected patients. By using transduced BE (2)-M17 cells, we found that the mutated ELF2 (mt-ELF2) gene increased ATXN2 and reduced ELOVL5 gene expression, the causal genes of type 2 and type 38 spinocerebellar ataxias. Both, western blot and confocal microscopy confirmed an increase of ataxin-2 in BE(2)-M17 cells transduced with lentivirus expressing mt-ELF2 (CEE-mt-ELF2), which was not observed in cells transduced with lentivirus expressing wt-ELF2 (CEE-wt-ELF2). Moreover, we observed a significant decrease in the number and size of lipid droplets in the CEE-mt-ELF2-transduced BE (2)-M17 cells, but not in the CEE-wt-ELF2-transduced BE (2)-M17. Furthermore, changes in the expression of ELOVL5 could be related with the reduction of lipid droplets in BE (2)-M17 cells. This work supports that ELF2 gene regulates the expression of ATXN2 and ELOVL5 genes, and defines new molecular links in the pathophysiology of cerebellar ataxias.

TACC3 transcriptionally upregulates E2F1 to promote cell growth and confer sensitivity to cisplatin in bladder cancer

Accumulating evidence has shown that transforming acidic coiled-coil 3 (TACC3) is deregulated in a broad spectrum of cancers. In the present study, we reported that TACC3 was markedly elevated in bladder cancer, especially in muscle-invasive bladder cancers (MIBCs). The upregulation of TACC3 was positively associated with tumor invasiveness, grade, T stage, and progression in patients with bladder cancer. Furthermore, a Kaplan-Meier survival analysis showed that patients with bladder cancer whose tumors had high TACC3 expression experienced a dismal prognosis compared with patients whose tumors had low TACC3 expression. Functional studies have found that TACC3 is a prerequisite for the development of malignant characteristics of bladder cancer cells, including cell proliferation and invasion. Moreover, TACC3 promoted G1/S transition, which was mediated via activation of the transcription of E2F1, eventually enhancing cell proliferation. Notably, the overexpression of TACC3 or E2F1 indicates a high sensitivity to cisplatin. Taken together, these findings define a tumor-supportive role for TACC3, which may also serve as a prognostic and therapeutic indicator in bladder cancers.

Deep sequencing of the mouse lung transcriptome reveals distinct long non-coding RNAs expression associated with the high virulence of H5N1 avian influenza virus in mice

Long non-coding RNAs (lncRNAs) play multiple key regulatory roles in various biological processes. However, their function in influenza A virus (IAV) pathogenicity remains largely unexplored. Here, using next generation sequencing, we systemically compared the whole-transcriptome response of the mouse lung infected with either the highly pathogenic (A/Chicken/Jiangsu/k0402/2010, CK10) or the nonpathogenic (A/Goose/Jiangsu/k0403/2010, GS10) H5N1 virus. A total of 126 significantly differentially expressed (SDE) lncRNAs from three replicates were identified to be associated with the high virulence of CK10, whereas 94 SDE lncRNAs were related with GS10. Functional category analysis suggested that the SDE lncRNAs-coexpressed mRNAs regulated by CK10 were highly related with aberrant and uncontrolled inflammatory responses. Further canonical pathway analysis also confirmed that these targets were highly enriched for inflammatory-related pathways. Moreover, 9 lncRNAs and 17 lncRNAs-coexpressed mRNAs associated with a large number of targeted genes were successfully verified by qRT-PCR. One targeted lncRNA (NONMMUT011061) that was markedly activated and correlated with a great number of mRNAs was selected for further in-depth analysis, including predication of transcription factors, potential interacting proteins, genomic location, coding ability and construction of the secondary structure. More importantly, NONMMUT011061 was also distinctively stimulated during the highly pathogenic H5N8 virus infection in mice, suggesting a potential universal role of NONMMUT011061 in the pathogenesis of different H5 IAV. Altogether, these results provide a subset of lncRNAs that might play important roles in the pathogenesis of influenza virus and add the lncRNAs to the vast repertoire of host factors utilized by IAV for infection and persistence.

A novel approach to identify the miRNA-mRNA causal regulatory modules in Cancer

MicroRNAs (miRNAs) play an essential role in many biological processes by regulating the target genes, especially in the initiation and development of cancers. Therefore, the identification of the miRNA-mRNA regulatory modules is important for understanding the regulatory mechanisms. Most computational methods only used statistical correlations in predicting miRNA-mRNA modules, and neglected the fact there are causal relationships between miRNAs and their target genes. In this paper, we propose a novel approach called CALM(the causal regulatory modules) to identify the miRNA-mRNA regulatory modules through integrating the causal interactions and statistical correlations between the miRNAs and their target genes. Our algorithm largely consists of three steps: it first forms the causal regulatory relationships of miRNAs and genes from gene expression profiles and detects the miRNA clusters according to the GO function information of their target genes, then expands each miRNA cluster by greedy adding(discarding) the target genes to maximize the modularity score. To show the performance of our method, we apply CALM on four datasets including EMT, breast, ovarian, thyroid cancer and validate our results. The experiment results show that our method can not only outperform the compared method, but also achieve ideal overall performance in terms of the functional enrichment.

Expression profiling of Tas2r genes reveals a complex pattern along the mouse GI tract and the presence of Tas2r131 in a subset of intestinal Paneth cells

The chemical variability of the intestinal lumen requires the presence of molecular receptors detecting the various substances naturally occurring in the diet and as a result of the activity of the microbiota. Despite their early discovery, intestinal bitter taste receptors (Tas2r) have not yet been assigned an unambiguous physiological function. Recently, using a CRE-recombinant approach we showed that the Tas2r131 gene is expressed in a subset of mucin-producing goblet cells in the colon of mice. Moreover, we also demonstrated that the expression of the Tas2r131 locus is not restricted to this region. In the present study we aimed at characterizing the presence of positive cells also in other gastrointestinal regions. Our results show that Tas2r131+ cells appear in the jejunum and the ileum, and are absent from the stomach and the duodenum. We identified the positive cells as a subpopulation of deep-crypt Paneth cells in the ileum, strengthening the notion of a defensive role for Tas2rs in the gut. To get a broader perspective on the expression of bitter taste receptors in the alimentary canal, we quantified the expression of all 35 Tas2r genes along the gastrointestinal tract by qRT-PCR. We discovered that the number and expression level of Tas2r genes profoundly vary along the alimentary canal, with the stomach and the colon expressing the largest subsets.

RNA-Seq analysis reveals new evidence for inflammation-related changes in aged kidney

Age-related dysregulated inflammation plays an essential role as a major risk factor underlying the pathophysiological aging process. To better understand how inflammatory processes are related to aging at the molecular level, we sequenced the transcriptome of young and aged rat kidney using RNA-Seq to detect known genes, novel genes, and alternative splicing events that are differentially expressed. By comparing young (6 months of age) and old (25 months of age) rats, we detected 722 up-regulated genes and 111 down-regulated genes. In the aged rats, we found 32 novel genes and 107 alternatively spliced genes. Notably, 6.6% of the up-regulated genes were related to inflammation (P < 2.2 × 10-16, Fisher exact t-test); 15.6% were novel genes with functional protein domains (P = 1.4 × 10-5); and 6.5% were genes showing alternative splicing events (P = 3.3 × 10-4). Based on the results of pathway analysis, we detected the involvement of inflammation-related pathways such as cytokines (P = 4.4 × 10-16), which were found up-regulated in the aged rats. Furthermore, an up-regulated inflammatory gene analysis identified the involvement of transcription factors, such as STAT4, EGR1, and FOSL1, which regulate cancer as well as inflammation in aging processes. Thus, RNA changes in these pathways support their involvement in the pro-inflammatory status during aging. We propose that whole RNA-Seq is a useful tool to identify novel genes and alternative splicing events by documenting broadly implicated inflammation-related genes involved in aging processes.

Model-Based Clustering With Data Correction For Removing Artifacts In Gene Expression Data

The NIH Library of Integrated Network-based Cellular Signatures (LINCS) contains gene expression data from over a million experiments, using Luminex Bead technology. Only 500 colors are used to measure the expression levels of the 1,000 landmark genes measured, and the data for the resulting pairs of genes are deconvolved. The raw data are sometimes inadequate for reliable deconvolution, leading to artifacts in the final processed data. These include the expression levels of paired genes being flipped or given the same value, and clusters of values that are not at the true expression level. We propose a new method called model-based clustering with data correction (MCDC) that is able to identify and correct these three kinds of artifacts simultaneously. We show that MCDC improves the resulting gene expression data in terms of agreement with external baselines, as well as improving results from subsequent analysis.

Positive selection of the TRIM family regulatory region in primate genomes

Viral selection pressure has acted on restriction factors that play an important role in the innate immune system by inhibiting the replication of viruses during primate evolution. Tripartite motif-containing (TRIM) family members are some of these restriction factors. It is becoming increasingly clear that gene expression differences, rather than protein-coding regions changes, could play a vital role in the anti-retroviral immune mechanism. Increasingly, recent studies have created genome-scale catalogues of DNase I hypersensitive sites (DHSs), which demark potentially functional regulatory DNA. To improve our understanding of the molecular evolution mechanism of antiviral differences between species, we leveraged 14 130 DHSs derived from 145 cell types to characterize the regulatory landscape of the TRIM region. Subsequently, we compared the alignments of the DHSs across six primates and found 375 DHSs that are conserved in non-human primates but exhibit significantly accelerated rates of evolution in the human lineage (haDHSs). Furthermore, we discovered 31 human-specific potential transcription factor motifs within haDHSs, including the KROX and SP1, that both interact with HIV-1 Importantly, the corresponding haDHS was correlated with antiviral factor TRIM23 Thus, our results suggested that some viruses may contribute, through regulatory DNA differences, to organismal evolution by mediating TRIM gene expression to escape immune surveillance.

GSMC: Combining Parallel Gibbs Sampling with Maximal Cliques for Hunting DNA Motif

Regulatory elements are responsible for regulating gene transcription. Therefore, identification of these elements is a tremendous challenge in the field of gene expression. Transcription factors (TFs) play a key role in gene regulation by binding to target promoter sequences. A set of conserved sequence patterns with a highly similar structure that is bound by a TF is called a motif. Motif discovery has been a difficult problem over the past decades. Meanwhile, it is a foundation stone in meeting this challenge. Recent advances in obtaining genomic sequences and high-throughput gene expression analysis techniques have enabled the rapid development of computational methods for motif discovery. As a result, a large number of motif-finding algorithms aiming at various motif models have sprung up in the past few years. However, most of them are not suitable for analysis of the large data sets generated by next-generation sequencing. To better handle large-scale ChIP-Seq data and achieve better performance in computational time and motif detection accuracy, we propose an excellent motif-finding algorithm known as GSMC (Combining Parallel Gibbs Sampling with Maximal Cliques for hunting DNA Motif). The GSMC algorithm consists of two steps. First, we employ the commonly used Gibbs sampling to generating initial motifs. Second, we utilize maximal cliques to cluster motifs according to Similarity with Position Information Contents (SPIC). Consequently, we raise the detection accuracy in a great degree, in the meantime holding comparative computation efficiency. In addition, we can find much more credible cofactor interacting motifs.

CsGOGAT Is Important in Dynamic Changes of Theanine Content in Postharvest Tea Plant Leaves under Different Temperature and Shading Spreadings

We analyzed the changes of theanine content in postharvest tea leaves under high temperature (38 °C), low temperature (4 °C), and shading spreadings by using ultrahigh-performance liquid chromatography. The differentially expressed proteins (DEPs), CsFd-GOGAT and CsNADH-GOGAT, which are involved in theanine biosynthesis pathway, were identified from the corresponding proteome data. The protein-protein interactions of CsFd-GOGAT and CsNADH-GOGAT, CsTS1, or CsNiR were verified by yeast two-hybrid technology. The expression profiles of 17 genes in theanine metabolism, including CsFd-GOGAT and CsNADH-GOGAT, were analyzed by quantitative real-time polymerase chain reaction. The correlations between the dynamic changes of theanine content and expression profiles of related genes and DEPs were analyzed. This study preliminarily proved the importance of CsGOGAT in dynamic changes of theanine content in postharvest tea leaves during spreading.

Hyperactive mTOR induces neuroendocrine differentiation in prostate cancer cell with concurrent up-regulation of IRF1

BACKGROUND

Neuroendocrine-differentiated prostate cancer (NEPCa) is refractory to androgen deprivation therapy and shows a poor prognosis. The underlying mechanisms responsible for neuroendocrine differentiation (NED) are yet to be clarified. In this study, we investigated the role of mammalian target of rapamycin (mTOR) in NEPCa.

METHODS

We utilized a gain-of-function analysis by establishing a human PCa LNCaP stable line that expresses hyperactive mTOR (LNCaP-mTOR). Then, we employed a comprehensive mass spectrometric analysis to identify a key transcription factor in LNCaP-mTOR, followed by a loss-of-function analysis using CRISPR/Cas system.

RESULTS

The activation of mTOR induced NED. We observed significant cell growth arrest in NED of LNCaP-mTOR, which accompanied increased expression of p21^WAF1/CIP1 . A comprehensive mass spectrometric analysis identified interferon regulatory factor 1 (IRF1) as a key transcription factor in growth arrest of LNCaP-mTOR. The disruption of IRF1 gene in LNCaP-mTOR reversed cell growth arrest along with the suppression of its target p21^WAF1/CIP1 . These results indicate that the growth arrest in NED is at least in part dependent on IRF1 through the induction of p21^WAF1/CIP1 .

CONCLUSIONS

We identified active mTOR as a novel inducer of NED, and elucidated a mechanism underlying the malignant transformation of NEPCa by recapitulating NED in vitro.

Investigating transcription factor synergism in humans

Proteins are the core and the engine of every process in cells thus the study of mechanisms that drive the regulation of protein expression, is essential. Transcription factors play a central role in this extremely complex task and they synergically co-operate in order to provide a fine tuning of protein expressions. In the present study, we designed a mathematically well-founded procedure to investigate the mutual positioning of transcription factors binding sites related to a given couple of transcription factors in order to evaluate the possible association between them. We obtained a list of highly related transcription factors couples, whose binding site occurrences significantly group together for a given set of gene promoters, identifying the biological contexts in which the couples are involved in and the processes they should contribute to regulate.

NFIA co-localizes with PPARγ and transcriptionally controls the brown fat gene program

Brown fat dissipates energy as heat and protects against obesity. Here, we identified nuclear factor I-A (NFIA) as a transcriptional regulator of brown fat by a genome-wide open chromatin analysis of murine brown and white fat followed by motif analysis of brown-fat-specific open chromatin regions. NFIA and the master transcriptional regulator of adipogenesis, PPARγ, co-localize at the brown-fat-specific enhancers. Moreover, the binding of NFIA precedes and facilitates the binding of PPARγ, leading to increased chromatin accessibility and active transcription. Introduction of NFIA into myoblasts results in brown adipocyte differentiation. Conversely, the brown fat of NFIA-knockout mice displays impaired expression of the brown-fat-specific genes and reciprocal elevation of muscle genes. Finally, expression of NFIA and the brown-fat-specific genes is positively correlated in human brown fat. These results indicate that NFIA activates the cell-type-specific enhancers and facilitates the binding of PPARγ to control the brown fat gene program.

Unraveling a tumor type-specific regulatory core underlying E2F1-mediated epithelial-mesenchymal transition to predict receptor protein signatures

Cancer is a disease of subverted regulatory pathways. In this paper, we reconstruct the regulatory network around E2F, a family of transcription factors whose deregulation has been associated to cancer progression, chemoresistance, invasiveness, and metastasis. We integrate gene expression profiles of cancer cell lines from two E2F1-driven highly aggressive bladder and breast tumors, and use network analysis methods to identify the tumor type-specific core of the network. By combining logic-based network modeling, in vitro experimentation, and gene expression profiles from patient cohorts displaying tumor aggressiveness, we identify and experimentally validate distinctive, tumor type-specific signatures of receptor proteins associated to epithelial-mesenchymal transition in bladder and breast cancer. Our integrative network-based methodology, exemplified in the case of E2F1-induced aggressive tumors, has the potential to support the design of cohort- as well as tumor type-specific treatments and ultimately, to fight metastasis and therapy resistance.Deregulation of E2F family transcription factors is associated with cancer progression and metastasis. Here, the authors construct a map of the regulatory network around the E2F family, and using gene expression profiles, identify tumour type-specific regulatory cores and receptor expression signatures associated with epithelial-mesenchymal transition in bladder and breast cancer.

Assessing the model transferability for prediction of transcription factor binding sites based on chromatin accessibility

Background

Computational prediction of transcription factor (TF) binding sites in different cell types is challenging. Recent technology development allows us to determine the genome-wide chromatin accessibility in various cellular and developmental contexts. The chromatin accessibility profiles provide useful information in prediction of TF binding events in various physiological conditions. Furthermore, ChIP-Seq analysis was used to determine genome-wide binding sites for a range of different TFs in multiple cell types. Integration of these two types of genomic information can improve the prediction of TF binding events.

Results

We assessed to what extent a model built upon on other TFs and/or other cell types could be used to predict the binding sites of TFs of interest. A random forest model was built using a set of cell type-independent features such as specific sequences recognized by the TFs and evolutionary conservation, as well as cell type-specific features derived from chromatin accessibility data. Our analysis suggested that the models learned from other TFs and/or cell lines performed almost as well as the model learned from the target TF in the cell type of interest. Interestingly, models based on multiple TFs performed better than single-TF models. Finally, we proposed a universal model, BPAC, which was generated using ChIP-Seq data from multiple TFs in various cell types.

Conclusion

Integrating chromatin accessibility information with sequence information improves prediction of TF binding.The prediction of TF binding is transferable across TFs and/or cell lines suggesting there are a set of universal “rules”. A computational tool was developed to predict TF binding sites based on the universal “rules”.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1769-7) contains supplementary material, which is available to authorized users.

A data analysis framework for biomedical big data: Application on mesoderm differentiation of human pluripotent stem cells

The development of high-throughput biomolecular technologies has resulted in generation of vast omics data at an unprecedented rate. This is transforming biomedical research into a big data discipline, where the main challenges relate to the analysis and interpretation of data into new biological knowledge. The aim of this study was to develop a framework for biomedical big data analytics, and apply it for analyzing transcriptomics time series data from early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. To this end, transcriptome profiling by microarray was performed on differentiating human pluripotent stem cells sampled at eleven consecutive days. The gene expression data was analyzed using the five-stage analysis framework proposed in this study, including data preparation, exploratory data analysis, confirmatory analysis, biological knowledge discovery, and visualization of the results. Clustering analysis revealed several distinct expression profiles during differentiation. Genes with an early transient response were strongly related to embryonic- and mesendoderm development, for example CER1 and NODAL. Pluripotency genes, such as NANOG and SOX2, exhibited substantial downregulation shortly after onset of differentiation. Rapid induction of genes related to metal ion response, cardiac tissue development, and muscle contraction were observed around day five and six. Several transcription factors were identified as potential regulators of these processes, e.g. POU1F1, TCF4 and TBP for muscle contraction genes. Pathway analysis revealed temporal activity of several signaling pathways, for example the inhibition of WNT signaling on day 2 and its reactivation on day 4. This study provides a comprehensive characterization of biological events and key regulators of the early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. The proposed analysis framework can be used to structure data analysis in future research, both in stem cell differentiation, and more generally, in biomedical big data analytics.

Non-canonical Glucocorticoid Receptor Transactivation of gilz by Alcohol Suppresses Cell Inflammatory Response

Acute alcohol exposure suppresses cell inflammatory response. The underlying mechanism has not been fully defined. Here we report that alcohol was able to activate glucocorticoid receptor (GR) signaling in the absence of glucocorticoids (GCs) and upregulated glucocorticoid-induced leucine zipper (gilz), a prominent GC-responsive gene. Such a non-canonical activation of GR was not blocked by mifepristone, a potent GC competitor. The proximal promoter of gilz, encompassing five GC-responsive elements (GREs), was incorporated and tested in a luciferase reporter system. Deletion and/or mutation of the GREs abrogated the promoter responsiveness to alcohol. Thus, the GR–GRE interaction transduced the alcohol action on gilz. Alcohol induced GR nuclear translocation, which was enhanced by the alcohol dehydrogenase inhibitor fomepizole, suggesting that it was alcohol, not its metabolites, that engendered the effect. Gel mobility shift assay showed that unliganded GR was able to bind GREs and such interaction withstood clinically relevant levels of alcohol. GR knockout via CRISPR/Cas9 gene targeting or GILZ depletion via small RNA interference diminished alcohol suppression of cell inflammatory response to LPS. Thus, a previously unrecognized, non-canonical GR activation of gilz is involved in alcohol modulation of cell immune response.

Molecular mechanisms underlying noncoding risk variations in psychiatric genetic studies

Recent large-scale genetic approaches such as genome-wide association studies have allowed the identification of common genetic variations that contribute to risk architectures of psychiatric disorders. However, most of these susceptibility variants are located in noncoding genomic regions that usually span multiple genes. As a result, pinpointing the precise variant(s) and biological mechanisms accounting for the risk remains challenging. By reviewing recent progresses in genetics, functional genomics and neurobiology of psychiatric disorders, as well as gene expression analyses of brain tissues, here we propose a roadmap to characterize the roles of noncoding risk loci in the pathogenesis of psychiatric illnesses (that is, identifying the underlying molecular mechanisms explaining the genetic risk conferred by those genomic loci, and recognizing putative functional causative variants). This roadmap involves integration of transcriptomic data, epidemiological and bioinformatic methods, as well as in vitro and in vivo experimental approaches. These tools will promote the translation of genetic discoveries to physiological mechanisms, and ultimately guide the development of preventive, therapeutic and prognostic measures for psychiatric disorders.