TRANSFAC: an integrated system for gene expression regulation

Impairment of DYRK2 augments stem-like traits by promoting KLF4 expression in breast cancer

Whereas accumulating studies have supported the cancer stem cell theory, a specific therapy targeting a cancer stem cell subpopulation has not been established. Here, we show that dual-specificity tyrosine phosphorylation-kinase 2 (DYRK2) is a novel negative regulator for formation of breast cancer stem cells. Downregulation of DYRK2 promotes cancer stem-like traits in vitro, tumourigenesis in vivo and the proportion of the cancer stem cell population in human breast cancer tissues. We found that Krupple-like factor 4 (KLF4) serves as a key mediator of DYRK2's control over the cancer stem phenotype. Reduced DYRK2 expression increases KLF4 expression, which induces cancer stem-like properties. We identified androgen receptor (AR) as a transcription factor binding to the KLF4 promoter region; this process is dependent on DYRK2 kinase activity. Our findings delineate a mechanism of cancer stem cell regulation by the DYRK2-AR-KLF4 axis in breast cancer. Targeting of this pathway may be a promising strategy against breast cancer stem cells.

Functional cis-regulatory modules encoded by mouse-specific endogenous retrovirus

Cis-regulatory modules contain multiple transcription factor (TF)-binding sites and integrate the effects of each TF to control gene expression in specific cellular contexts. Transposable elements (TEs) are uniquely equipped to deposit their regulatory sequences across a genome, which could also contain cis-regulatory modules that coordinate the control of multiple genes with the same regulatory logic. We provide the first evidence of mouse-specific TEs that encode a module of TF-binding sites in mouse embryonic stem cells (ESCs). The majority (77%) of the individual TEs tested exhibited enhancer activity in mouse ESCs. By mutating individual TF-binding sites within the TE, we identified a module of TF-binding motifs that cooperatively enhanced gene expression. Interestingly, we also observed the same motif module in the in silico constructed ancestral TE that also acted cooperatively to enhance gene expression. Our results suggest that ancestral TE insertions might have brought in cis-regulatory modules into the mouse genome.

Exploring the FGFR3-related oncogenic mechanism in bladder cancer using bioinformatics strategy

Background

Aberrant activation of fibroblast growth factor receptor 3 (FGFR3) is frequently observed in bladder cancer, but how it involved in carcinogenesis is not well understood. The current study was aimed to investigate the underlying mechanism on the progression of bladder cancer.

Methods

The GSE41035 dataset downloaded from Gene Expression Omnibus was used to identify the differentially expressed genes (DEGs) between bladder cancer cell line RT112 with or without depletion of FGFR3, and gene ontology enrichment analysis was performed. Then, FGFR3-centered protein–protein interaction (PPI) and regulatory networks were constructed. Combined with the data retrieved from GSE31684, prognostic makers for bladder cancer were predicted.

Results

We identified a total of 2855 DEGs, and most of them were associated with blood vessel morphogenesis and cell division. In addition, KIAA1377, POLA2, FGFR3, and EPHA4 were the hub genes with high degree in the FGFR3-centered PPI network. Besides, 17 microRNAs (miRNAs) and 6 transcriptional factors (TFs) were predicted to be the regulators of the nodes in PPI network. Moreover, CSTF2, POLA1, HMOX2, and EFNB2 may be associated with the prognosis of bladder cancer patient.

Conclusions

The current study may provide some insights into the molecular mechanism of FGFR3 as a mediator in bladder cancer.

HOP expression is regulated by p53 and RAS and characteristic of a cancer gene signature

The Hsp70/Hsp90 organising protein (HOP) is a co-chaperone essential for client protein transfer from Hsp70 to Hsp90 within the Hsp90 chaperone machine. Although HOP is upregulated in various cancers, there is limited information from in vitro studies on how HOP expression is regulated in cancer. The main objective of this study was to identify the HOP promoter and investigate its activity in cancerous cells. Bioinformatic analysis of the -2500 to +16 bp region of the HOP gene identified a large CpG island and a range of putative cis-elements. Many of the cis-elements were potentially bound by transcription factors which are activated by oncogenic pathways. Luciferase reporter assays demonstrated that the upstream region of the HOP gene contains an active promoter in vitro. Truncation of this region suggested that the core HOP promoter region was -855 to +16 bp. HOP promoter activity was highest in Hs578T, HEK293T and SV40- transformed MEF1 cell lines which expressed mutant or inactive p53. In a mutant p53 background, expression of wild-type p53 led to a reduction in promoter activity, while inhibition of wild-type p53 in HeLa cells increased HOP promoter activity. Additionally, in Hs578T and HEK293T cell lines containing inactive p53, expression of HRAS increased HOP promoter activity. However, HRAS activation of the HOP promoter was inhibited by p53 overexpression. These findings suggest for the first time that HOP expression in cancer may be regulated by both RAS activation and p53 inhibition. Taken together, these data suggest that HOP may be part of the cancer gene signature induced by a combination of mutant p53 and mutated RAS that is associated with cellular transformation.

Leveraging Online Resources to Prioritize Candidate Genes for Functional Analyses: Using the Fetal Testis as a Test Case

With each new microarray or RNA-seq experiment, massive quantities of transcriptomic information are generated with the purpose to produce a list of candidate genes for functional analyses. Yet an effective strategy remains elusive to prioritize the genes on these candidate lists. In this review, we outline a prioritizing strategy by taking a step back from the bench and leveraging the rich range of public databases. This in silico approach provides an economical, less biased, and more effective solution. We discuss the publicly available online resources that can be used to answer a range of questions about a gene. Is the gene of interest expressed in the system of interest (using expression databases)? Where else is this gene expressed (using added-value transcriptomic resources)? What pathways and processes is the gene involved in (using enriched gene pathway analysis and mouse knockout databases)? Is this gene correlated with human diseases (using human disease variant databases)? Using mouse fetal testis as an example, our strategies identified 298 genes annotated as expressed in the fetal testis. We cross-referenced these genes to existing microarray data and narrowed the list down to cell-type-specific candidates (35 for Sertoli cells, 11 for Leydig cells, and 25 for germ cells). Our strategies can be customized so that they allow researchers to effectively and confidently prioritize genes for functional analysis.

In Vivo Hepatic Enhancer Elements in the Human ABCG2 Locus

ABCG2 encodes the mitoxantrone resistance protein (MXR; breast cancer resistance protein), an ATP-binding cassette (ABC) efflux membrane transporter. Computational analysis of the ∼300 kb region of DNA surrounding ABCG2 (chr4:88911376-89220011, hg19) identified 30 regions with potential cis-regulatory capabilities. These putative regulatory regions were tested for their enhancer and suppressor activity in a human liver cell line using luciferase reporter assays. The in vitro enhancer and suppressor assays identified four regions that decreased gene expression and five regions that increased expression >1.6-fold. Four of five human hepatic in vitro enhancers were confirmed as in vivo liver enhancers using the mouse hydrodynamic tail vein injection assay. Two of the in vivo liver enhancers (ABCG2RE1 and ABCG2RE9) responded to 17β-estradiol or rifampin in human cell lines, and ABCG2RE9 had ChIP-seq evidence to support the binding of several transcription factors and the transcriptional coactivator p300 in human hepatocytes. This study identified genomic regions surrounding human ABCG2 that can function as regulatory elements, some with the capacity to alter gene expression upon environmental stimulus. The results from this research will drive future investigations of interindividual variation in ABCG2 expression and function that contribute to differences in drug response.

Contextual Refinement of Regulatory Targets Reveals Effects on Breast Cancer Prognosis of the Regulome

Gene expression regulators, such as transcription factors (TFs) and microRNAs (miRNAs), have varying regulatory targets based on the tissue and physiological state (context) within which they are expressed. While the emergence of regulator-characterizing experiments has inferred the target genes of many regulators across many contexts, methods for transferring regulator target genes across contexts are lacking. Further, regulator target gene lists frequently are not curated or have permissive inclusion criteria, impairing their use. Here, we present a method called iterative Contextual Transcriptional Activity Inference of Regulators (icTAIR) to resolve these issues. icTAIR takes a regulator’s previously-identified target gene list and combines it with gene expression data from a context, quantifying that regulator’s activity for that context. It then calculates the correlation between each listed target gene’s expression and the quantitative score of regulatory activity, removes the uncorrelated genes from the list, and iterates the process until it derives a stable list of refined target genes. To validate and demonstrate icTAIR’s power, we use it to refine the MSigDB c3 database of TF, miRNA and unclassified motif target gene lists for breast cancer. We then use its output for survival analysis with clinicopathological multivariable adjustment in 7 independent breast cancer datasets covering 3,430 patients. We uncover many novel prognostic regulators that were obscured prior to refinement, in particular NFY, and offer a detailed look at the composition and relationships among the breast cancer prognostic regulome. We anticipate icTAIR will be of general use in contextually refining regulator target genes for discoveries across many contexts. The icTAIR algorithm can be downloaded from https://github.com/icTAIR.

Gene expression regulators, such as transcription factors and microRNAs, are critical actors in cellular physiology and pathophysiology and act by modulating the expression levels of sets of target genes. Given their significance, numerous experiments have sought to characterize the specific target genes of specific regulators, which in turn has led to regulator target gene list databases. Unfortunately, these lists are plagued by poor curation and validation. Further, all lists suffer from the fundamental issue that regulator targets vary across tissue type and physiological state, or “context”, making them poor for conducting downstream, context-specific analyses. To address this issue, here we present a method called icTAIR that contextually-refines regulator target gene lists. To demonstrate its value, we use icTAIR to take the largest-available database of regulator target gene lists, refine it for the breast cancer context, and use both the pre-refined and refined lists for downstream survival analyses in over 3,400 tumors. We find that icTAIR improves the statistical power of the analyses by multiple orders of magnitude. This in turn lets us map the relational network of breast cancer regulators and identify regulators with prognostic effects even after clinicopathological adjustment. We anticipate icTAIR will be broadly useful in regulator studies.

Identifying key stage-specific genes and transcription factors for gastric cancer based on RNA-sequencing data

BACKGROUND

To identify gastric cancer (GC)-associated genes and transcription factors (TFs) using RNA-sequencing (RNA-seq) data of Asians.

MATERIALS AND METHODS

The RNA-seq data (GSE36968) were downloaded from Gene Expression Omnibus database, including 6 noncancerous gastric tissue samples, 5 stage I GC samples, 5 stage II GC samples, 8 stage III GC samples, and 6 stage IV GC samples. The gene expression values in each sample were calculated using Cuffdiff. Following, stage-specific genes were identified by 1-way analysis of variance and hierarchical clustering analysis. Upstream TFs were identified using Seqpos. Besides, functional enrichment analysis of stage-specific genes was performed by DAVID. In addition, the underlying protein-protein interactions (PPIs) information among stage IV-specific genes were extracted from STRING database and PPI network was constructed using Cytoscape software.

RESULTS

A total of 3576 stage-specific genes were identified, including 813 specifically up-regulated genes in the normal gastric tissues, 2224 stage I and II-specific genes, and 539 stage IV-specific genes. Also, a total of 9 and 11 up-regulated TFs were identified for the stage I and II-specific genes and stage IV-specific genes, respectively. Functional enrichment showed SPARC, MMP17, and COL6A3 were related to extracellular matrix. Notably, 2 regulatory pathways HOXA4-GLI3-RUNX2-FGF2 and HMGA2-PRKCA were obtained from the PPI network for stage IV-specific genes. In the PPI network, TFs HOXA4 and HMGA2 might function via mediating other genes.

CONCLUSION

These stage-specific genes and TFs might act in the pathogenesis of GC in Asians.

Diminished DYRK2 sensitizes hormone receptor-positive breast cancer to everolimus by the escape from degrading mTOR

Mammalian target of rapamycin (mTOR) inhibitor, everolimus, provides benefit for metastatic hormone receptor positive breast cancer after failure of the endocrine therapy. The present report highlights Dual Specificity Tyrosine Phosphorylation Regulated Kinase 2 (DYRK2) as a predictive marker for everolimus sensitivity. The key node and KEGG pathway analyses revealed that mTORC1 pathway is activated in DYRK2-depleted cells. Everolimus was more effective in DYRK2-depleted cells compared with control cells. In xenograft model, everolimus treatment significantly inhibited tumor growth compared with vehicle or eribulin treatment. In clinical analysis, patients with low DYRK2 expression acquired longer treatment period and had higher clinical benefit rate than those with high DYRK2 expression (171 vs 82 days; P < 0.05 and 50% vs 12.5%, respectively). We further investigated the underlying mechanism by which DYRK2 regulates mTORC1 pathway. The ectopic expression of DYRK2 promoted phosphorylation of Thr631 for the ubiquitination and degradation of mTOR. DYRK2 expression levels may thus predict clinical responses to everolimus.

Genomic analysis of hepatoblastoma identifies distinct molecular and prognostic subgroups

Despite being the most common liver cancer in children, hepatoblastoma (HB) is a rare neoplasm. Consequently, few pretreatment tumors have been molecularly profiled, and there are no validated prognostic or therapeutic biomarkers for HB patients. We report on the first large-scale effort to profile pretreatment HBs at diagnosis. Our analysis of 88 clinically annotated HBs revealed three risk-stratifying molecular subtypes that are characterized by differential activation of hepatic progenitor cell markers and metabolic pathways: high-risk tumors were characterized by up-regulated nuclear factor, erythroid 2-like 2 activity; high lin-28 homolog B, high mobility group AT-hook 2, spalt-like transcription factor 4, and alpha-fetoprotein expression; and high coordinated expression of oncofetal proteins and stem-cell markers, while low-risk tumors had low lin-28 homolog B and lethal-7 expression and high hepatic nuclear factor 1 alpha activity.

CONCLUSION

Analysis of immunohistochemical assays using antibodies targeting these genes in a prospective study of 35 HBs suggested that these candidate biomarkers have the potential to improve risk stratification and guide treatment decisions for HB patients at diagnosis; our results pave the way for clinical collaborative studies to validate candidate biomarkers and test their potential to improve outcome for HB patients. (Hepatology 2017;65:104-121).

Non-Coding RNAs in Lung Cancer: Contribution of Bioinformatics Analysis to the Development of Non-Invasive Diagnostic Tools

Lung cancer is currently the leading cause of cancer related mortality due to late diagnosis and limited treatment intervention. Non-coding RNAs are not translated into proteins and have emerged as fundamental regulators of gene expression. Recent studies reported that microRNAs and long non-coding RNAs are involved in lung cancer development and progression. Moreover, they appear as new promising non-invasive biomarkers for early lung cancer diagnosis. Here, we highlight their potential as biomarker in lung cancer and present how bioinformatics can contribute to the development of non-invasive diagnostic tools. For this, we discuss several bioinformatics algorithms and software tools for a comprehensive understanding and functional characterization of microRNAs and long non-coding RNAs.

Transcriptome and Metabolome Analyses in Exogenous FABP4- and FABP5-Treated Adipose-Derived Stem Cells

Adipose-derived stem cells (ADSC), which exist near adipocytes in adipose tissue, have been used as a potential tool of regenerative medicine. Lipid chaperones, fatty acid-binding protein 4 (FABP4) and 5 (FABP5), are abundantly expressed in adipocytes. FABP4 has recently been shown to be secreted from adipocytes during lipolysis in a non-classical pathway and may act as an adipokine. Here, we investigated the role of exogenous FABP4 and FABP5 in transcriptional and metabolic regulation in ADSC. FABP4 and FABP5 were little expressed in ADSC. However, both FABP4 and FABP5 were significantly induced after adipocyte differentiation of ADSC and were secreted from the differentiated adipocytes. Analysis of microarray data, including gene ontology enrichment analysis and cascade analysis of the protein-protein interaction network using a transcription factor binding site search, demonstrated that treatment of ADSC with FABP4 or FABP5 affected several kinds of genes related to inflammatory and metabolic responses and the process of cell differentiation. Notably, myogenic factors, including myocyte enhancer factors, myogenic differentiation 1 and myogenin, were modulated by treatment of ADSC with FABP4, indicating that exogenous FABP4 treatment is partially associated with myogenesis in ADSC. Metabolome analysis showed that treatment of ADSC with FABP4 and with FABP5 similarly, but differently in extent, promoted hydrolysis and/or uptake of lipids, consequentially together with enhancement of β oxidation, inhibition of downstream of the glycolysis pathway, accumulation of amino acids, reduction of nucleic acid components and increase in the ratio of reduced and oxidized nicotinamide adenine dinucleotide phosphates (NADPH/NADP+), an indicator of reducing power, and the ratio of adenosine triphosphate and adenosine monophosphate (ATP/AMP), an indicator of the energy state, in ADSC. In conclusion, secreted FABP4 and FABP5 from adipocytes as adipokines differentially affect transcriptional and metabolic regulation in ADSC near adipocytes. The adiposity condition in the host of regenerative medicine may affect characteristics of ADSC by exposure of the balance of FABP4 and FABP5.

Transcriptional Regulation of Notch1 Expression by Nkx6.1 in Neural Stem/Progenitor Cells during Ventral Spinal Cord Development

Notch1 signaling plays a critical role in maintaining and determining neural stem/progenitor cell (NSPC) fate, yet the transcriptional mechanism controlling Notch1 specific expression in NSPCs remains incomplete. Here, we show transcription factor Nkx6.1 interacts with a cis-element (CR2, an evolutionarily conserved non-coding fragment in the second intron of Notch1 locus) and regulates the expression of Notch1 in ventral NSPCs of the developing spinal cord. We show that the Notch1 expression is modulated by the interaction of Nkx6.1 with a 139 bp enhancer sequence within CR2. Knockdown or overexpression of Nkx6.1 leads to down- or up-regulated Notch1 expression, respectively. In CR2-GFP transgenic mouse, GFP expression was found prominent in the ventricular zone and neural progenitor cells from embryonic day 9.5 to postnatal day 7. GFP+ cells were mainly neural progenitors for interneurons and not for motoneurons or glial cells. Moreover, GFP expression persisted in a subset of ependymal cells in the adult spinal cord, suggesting that CR2 is active in both embryonic and adult NSPCs. Together our data reveal a novel mechanism of Notch1 transcriptional regulation in the ventral spinal cord by Nkx6.1 via its binding with Notch1 enhancer CR2 during embryonic development.

A posterior probability approach for gene regulatory network inference in genetic perturbation data

Inferring gene regulatory networks is an important problem in systems biology. However, these networks can be hard to infer from experimental data because of the inherent variability in biological data as well as the large number of genes involved. We propose a fast, simple method for inferring regulatory relationships between genes from knockdown experiments in the NIH LINCS dataset by calculating posterior probabilities, incorporating prior information. We show that the method is able to find previously identified edges from TRANSFAC and JASPAR and discuss the merits and limitations of this approach.

Fra-1 Regulates the Expression of HMGA1, Which is Associated with a Poor Prognosis in Human Esophageal Squamous Cell Carcinoma

BACKGROUND

The expression of Fos-related antigen 1 (Fra-1) affects tumor progression, migration, and invasion. In this study, we identified the genes regulated by Fra-1 in esophageal squamous cell carcinoma (ESCC).

METHODS

We constructed Fra-1 knockdown models via the transfection of small interfering RNA (siRNA) into ESCC cell lines (TE10, TE11). The expression levels of the genes in the knockdown models were analyzed using a microarray and a Biobase Upstream Analysis, while the expression levels of the candidate genes in the primary tumors of surgical specimens obtained from ESCC patients were determined using real-time polymerase chain reaction (PCR) and immunohistochemical staining. The clinicopathological features were then analyzed.

RESULTS

The Biobase Upstream Analysis showed the high-mobility-group protein-1 (HMGA1) to be a significant gene regulated by Fra-1. Actual binding of Fra-1 to the promotor region of HMGA1 was revealed in subsequent chromatin immunoprecipitation PCR experiments. Patients with a positive HMGA1 expression had a poor prognosis, and a multivariate analysis demonstrated a positive HMGA1 expression to be a significant independent prognostic factor.

CONCLUSION

HMGA1 is regulated by Fra-1 in ESCC, and the HMGA1 expression is significantly associated with a poor prognosis in ESCC patients. Downregulation of the HMGA1 expression may become a practical treatment strategy against ESCC in the future.

An Empirical Prior Improves Accuracy for Bayesian Estimation of Transcription Factor Binding Site Frequencies within Gene Promoters

A Bayesian method for sampling from the distribution of matches to a precompiled transcription factor binding site (TFBS) sequence pattern (conditioned on an observed nucleotide sequence and the sequence pattern) is described. The method takes a position frequency matrix as input for a set of representative binding sites for a transcription factor and two sets of noncoding, 5′ regulatory sequences for gene sets that are to be compared. An empirical prior on the frequency A (per base pair of gene-vicinal, noncoding DNA) of TFBSs is developed using data from the ENCODE project and incorporated into the method. In addition, a probabilistic model for binding site occurrences conditioned on λ is developed analytically, taking into account the finite-width effects of binding sites. The count of TFBS β (conditioned on the observed sequence) is sampled using Metropolis–Hastings with an information entropy-based move generator. The derivation of the method is presented in a step-by-step fashion, starting from specific conditional independence assumptions. Empirical results show that the newly proposed prior on β improves accuracy for estimating the number of TFBS within a set of promoter sequences.

Understanding the combinatorial action of transcription factors and microRNA regulation from regions of open chromatin

Transcriptional regulatory cascades are always triggered through the combinatorial interplay between transcription factors (TFs) and microRNAs (miRNAs) in eukaryotes. However, it is still a very substantial undertaking to dynamically profile their coordinated actions. In this work, we compared the differences in TFBS numbers between miRNA targets and non-targets, and found that miRNA targets tend to have more TFBS numbers. With the attempt to comprehensively understand the combinatorial action of TF and miRNA regulation from regions of open chromatin, we retrieved recently published DNase I hypersensitive sites (DHSs) across different human cell lines. The result showed that the differences are more statistically significant in DHS regions than non-DHS regions. Next, we trained classifiers for miRNA targets and non-targets. The result showed that TFBSs located in DHS regions achieved a competitive performance when discriminating miRNA targets and non-targets, whereas the performance of classifiers using TFBSs located in non-DHS regions is close to that of a random classifier. After the DHSs were divided into intergenic, transcription start sites (TSSs) and gene body DHS regions based on their genomic locations, only TFBSs located in TSS DHS regions provided a competitive performance. Our results provide us a clue that the coordinated activity of miRNAs and TFs describing the mechanism of gene expression control should be examined in a dynamic perspective.

New Wnt/β-catenin target genes promote experimental metastasis and migration of colorectal cancer cells through different signals

OBJECTIVES

We have previously identified a 115-gene signature that characterises the metastatic potential of human primary colon cancers. The signature included the canonical Wnt target gene BAMBI, which promoted experimental metastasis in mice. Here, we identified three new direct Wnt target genes from the signature, and studied their functions in epithelial-mesenchymal transition (EMT), cell migration and experimental metastasis.

DESIGN

We examined experimental liver metastases following injection of selected tumour cells into spleens of NOD/SCID mice. Molecular and cellular techniques were used to identify direct transcription target genes of Wnt/β-catenin signals. Microarray analyses and experiments that interfered with cell migration through inhibitors were performed to characterise downstream signalling systems.

RESULTS

Three new genes from the colorectal cancer (CRC) metastasis signature, BOP1, CKS2 and NFIL3, were identified as direct transcription targets of β-catenin/TCF4. Overexpression and knocking down of these genes in CRC cells promoted and inhibited, respectively, experimental metastasis in mice, EMT and cell motility in culture. Cell migration was repressed by interfering with distinct signalling systems through inhibitors of PI3K, JNK, p38 mitogen-activated protein kinase and/or mTOR. Gene expression profiling identified a series of migration-promoting genes, which were induced by BOP1, CKS2 and NFIL3, and could be repressed by inhibitors that are specific to these pathways.

CONCLUSIONS

We identified new direct Wnt/β-catenin target genes, BOP1, CKS2 and NFIL3, which induced EMT, cell migration and experimental metastasis of CRC cells. These genes crosstalk with different downstream signalling systems, and activate migration-promoting genes. These pathways and downstream genes may serve as therapeutic targets in the treatment of CRC metastasis.

Integrating Multi-omics Data to Dissect Mechanisms of DNA repair Dysregulation in Breast Cancer

DNA repair genes and pathways that are transcriptionally dysregulated in cancer provide the first line of evidence for the altered DNA repair status in tumours, and hence have been explored intensively as a source for biomarker discovery. The molecular mechanisms underlying DNA repair dysregulation, however, have not been systematically investigated in any cancer type. In this study, we performed a statistical analysis to dissect the roles of DNA copy number alteration (CNA), DNA methylation (DM) at gene promoter regions and the expression changes of transcription factors (TFs) in the differential expression of individual DNA repair genes in normal versus tumour breast samples. These gene-level results were summarised at pathway level to assess whether different DNA repair pathways are affected in distinct manners. Our results suggest that CNA and expression changes of TFs are major causes of DNA repair dysregulation in breast cancer, and that a subset of the identified TFs may exert global impacts on the dysregulation of multiple repair pathways. Our work hence provides novel insights into DNA repair dysregulation in breast cancer. These insights improve our understanding of the molecular basis of the DNA repair biomarkers identified thus far, and have potential to inform future biomarker discovery.

Distinct global binding patterns of the Wilms tumor gene 1 (WT1) -KTS and +KTS isoforms in leukemic cells

The zinc finger transcription factor Wilms tumor gene 1 (WT1) acts as an oncogene in acute myeloid leukemia. A naturally occurring alternative splice event between zinc fingers three and four, removing or retaining three amino acids (±KTS), is believed to change the DNA binding affinity of WT1, although there are conflicting data regarding the binding affinity and motifs of the different isoforms. Increased expression of the WT1 -KTS isoform at the expense of the WT1 +KTS isoform is associated with poor prognosis in acute myeloid leukemia. We determined the genome-wide binding pattern of WT1 -KTS and WT1 +KTS in leukemic K562 cells by chromatin immunoprecipitation and deep sequencing. We discovered that the WT1 -KTS isoform predominantly binds close to transcription start sites and to enhancers, in a similar fashion to other transcription factors, whereas WT1 +KTS binding is enriched within gene bodies. We observed a significant overlap between WT1 -KTS and WT1 +KTS target genes, despite the binding sites being distinct. Motif discovery revealed distinct binding motifs for the isoforms, some of which have been previously reported as WT1 binding sites. Additional analyses showed that both WT1 -KTS and WT1 +KTS target genes are more likely to be transcribed than non-targets, and are involved in cell proliferation, cell death, and development. Our study provides evidence that WT1 -KTS and WT1 +KTS share target genes yet still bind distinct locations, indicating isoform-specific regulation in transcription of genes related to cell proliferation and differentiation, consistent with the involvement of WT1 in acute myeloid leukemia.

Systems Analysis of the Complement-Induced Priming Phase of Liver Regeneration

Liver regeneration is a well-orchestrated process in the liver that allows mature hepatocytes to reenter the cell cycle to proliferate and replace lost or damaged cells. This process is often impaired in fatty or diseased livers, leading to cirrhosis and other deleterious phenotypes. Prior research has established the role of the complement system and its effector proteins in the progression of liver regeneration; however, a detailed mechanistic understanding of the involvement of complement in regeneration is yet to be established. In this study, we have examined the role of the complement system during the priming phase of liver regeneration through a systems level analysis using a combination of transcriptomic and metabolomic measurements. More specifically, we have performed partial hepatectomy on mice with genetic deficiency in C3, the major component of the complement cascade, and collected their livers at various time points. Based on our analysis, we show that the C3 cascade activates c-fos and promotes the TNF-α signaling pathway, which then activates acute-phase genes such as serum amyloid proteins and orosomucoids. The complement activation also regulates the efflux and the metabolism of cholesterol, an important metabolite for cell cycle and proliferation. Based on our systems level analysis, we provide an integrated model for the complement-induced priming phase of liver regeneration.

Electromobility Shift Assay Reveals Evidence in Favor of Allele-Specific Binding of RUNX1 to the 5' Hypersensitive Site 4-Locus Control Region

In our previous studies on the Iranian β-thalassemia (β-thal) patients, we identified an association between the severity of the β-thal phenotype and the polymorphic palindromic site at the 5' hypersensitive site 4-locus control region (5'HS4-LCR) of the β-globin gene cluster. Furthermore, a linkage disequilibrium was observed between this region and XmnI-HBG2 in the patient population. Based on this data, it was suggested that the well-recognized phenotype-ameliorating role assigned to positive XmnI could be associated with its linked elements in the LCR. To investigate the functional significance of polymorphisms at the 5'HS4-LCR, we studied its influence on binding of transcription factors. Web-based predictions of transcription factor binding revealed a binding site for runt-related transcription factor 1 (RUNX1), when the allele at the center of the palindrome (TGGGG(A/G)CCCCA) was A but not when it was G. Furthermore, electromobility shift assay (EMSA) presented evidence in support of allele-specific binding of RUNX1 to 5'HS4. Considering that RUNX1 is a well-known regulator of hematopoiesis, these preliminary data suggest the importance of further studies to confirm this interaction and consequently investigate its functional and phenotypical relevance. These studies could help us to understand the molecular mechanism behind the phenotype modifying role of the 5'HS4-LCR polymorphic palindromic region (rs16912979), which has been observed in previous studies.

An integrated network platform for contextual prioritization of drugs and pathways

Repurposing of drugs to novel disease indications has promise for faster clinical translation. However, identifying the best drugs for a given pathological context is not trivial. We developed an integrated random walk-based network framework that combines functional biomolecular relationships and known drug-target interactions as a platform for contextual prioritization of drugs, genes and pathways. We show that the use of gene-centric or drug-centric data, such as gene expression data or a phenotypic drug screen, respectively, within this network platform can effectively prioritize drugs and pathways, respectively, to the studied biological context. We demonstrate that various genomic data can be used as contextual cues to effectively prioritize drugs to the studied context, while similarly, phenotypic drug screen data can be used to effectively prioritize genes and pathways to the studied phenotypic context. As a proof-of-principle, we showcase the use of our platform to identify known and novel drug indications against different subsets of breast cancers through contextual prioritization based on genome-wide gene expression, shRNA and drug screen and clinical survival data. The integrated network and associated methods are incorporated into the NetWalker suite for functional genomics analysis ().

Selected heterozygosity at cis-regulatory sequences increases the expression homogeneity of a cell population in humans

Background

Examples of heterozygote advantage in humans are scarce and limited to protein-coding sequences. Here, we attempt a genome-wide functional inference of advantageous heterozygosity at cis-regulatory regions.

Results

The single-nucleotide polymorphisms bearing the signatures of balancing selection are enriched in active cis-regulatory regions of immune cells and epithelial cells, the latter of which provide barrier function and innate immunity. Examples associated with ancient trans-specific balancing selection are also discovered. Allelic imbalance in chromatin accessibility and divergence in transcription factor motif sequences indicate that these balanced polymorphisms cause distinct regulatory variation. However, a majority of these variants show no association with the expression level of the target gene. Instead, single-cell experimental data for gene expression and chromatin accessibility demonstrate that heterozygous sequences can lower cell-to-cell variability in proportion to selection strengths. This negative correlation is more pronounced for highly expressed genes and consistently observed when using different data and methods. Based on mathematical modeling, we hypothesize that extrinsic noise from fluctuations in transcription factor activity may be amplified in homozygotes, whereas it is buffered in heterozygotes. While high expression levels are coupled with intrinsic noise reduction, regulatory heterozygosity can contribute to the suppression of extrinsic noise.

Conclusions

This mechanism may confer a selective advantage by increasing cell population homogeneity and thereby enhancing the collective action of the cells, especially of those involved in the defense systems in humans.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-016-1027-8) contains supplementary material, which is available to authorized users.

Negative selection maintains transcription factor binding motifs in human cancer

Background

Somatic mutations in cancer cells affect various genomic elements disrupting important cell functions. In particular, mutations in DNA binding sites recognized by transcription factors can alter regulator binding affinities and, consequently, expression of target genes. A number of promoter mutations have been linked with an increased risk of cancer. Cancer somatic mutations in binding sites of selected transcription factors have been found under positive selection. However, action and significance of negative selection in non-coding regions remain controversial.

Results

Here we present analysis of transcription factor binding motifs co-localized with non-coding variants. To avoid statistical bias we account for mutation signatures of different cancer types. For many transcription factors, including multiple members of FOX, HOX, and NR families, we show that human cancers accumulate fewer mutations than expected by chance that increase or decrease affinity of predicted binding sites. Such stability of binding motifs is even more exhibited in DNase accessible regions.

Conclusions

Our data demonstrate negative selection against binding sites alterations and suggest that such selection pressure protects cancer cells from rewiring of regulatory circuits. Further analysis of transcription factors with conserved binding motifs can reveal cell regulatory pathways crucial for the survivability of various human cancers.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2728-9) contains supplementary material, which is available to authorized users.

A Novel Method to Detect Functional microRNA Regulatory Modules by Bicliques Merging

MicroRNAs (miRNAs) are post-transcriptional regulators that repress the expression of their targets. They are known to work cooperatively with genes and play important roles in numerous cellular processes. Identification of miRNA regulatory modules (MRMs) would aid deciphering the combinatorial effects derived from the many-to-many regulatory relationships in complex cellular systems. Here, we develop an effective method called BiCliques Merging (BCM) to predict MRMs based on bicliques merging. By integrating the miRNA/mRNA expression profiles from The Cancer Genome Atlas (TCGA) with the computational target predictions, we construct a weighted miRNA regulatory network for module discovery. The maximal bicliques detected in the network are statistically evaluated and filtered accordingly. We then employed a greedy-based strategy to iteratively merge the remaining bicliques according to their overlaps together with edge weights and the gene-gene interactions. Comparing with existing methods on two cancer datasets from TCGA, we showed that the modules identified by our method are more densely connected and functionally enriched. Moreover, our predicted modules are more enriched for miRNA families and the miRNA-mRNA pairs within the modules are more negatively correlated. Finally, several potential prognostic modules are revealed by Kaplan-Meier survival analysis and breast cancer subtype analysis.

AVAILABILITY

BCM is implemented in Java and available for download in the supplementary materials, which can be found on the Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/ TCBB.2015.2462370.

In silico transcriptional regulation and functional analysis of dengue shock syndrome associated SNPs in PLCE1 and MICB genes

Single nucleotide polymorphisms (SNPs) in PLCE1 and MICB genes increase risk for the development of dengue shock syndrome (DSS). We used Bioinformatics tools to predict alterations at the transcriptional and posttranslational levels driven by PLCE1 and MICB SNPs associated with DSS. Functional and phenotypic analysis conducted to determine deleterious SNPs and impact of amino acid substitution on the structure and function of proteins identified rs2274223 (H1619R) as deleterious to protein coding as it induces structural change in the C2 domain of PLCε, with the mutant residue more positively charged than the wild-type residue (RMSD score, 1.75 Å). Moreover, rs2274223 condenses the chromatin-repressing PLCε expression in DSS. Briefly, this study presents the impact of a single nucleotide transition at SNPs associated with DSS on differential protein binding patterns with PLCE1 and MICB genes and on protein structure modification and their possible role in the pathogenesis of DSS.

Abundance of LRP12 C-rs9694676 allelic promoter variant in epilepsy-associated gangliogliomas

AIMS

Chronic epilepsy associated gangliogliomas (GGs) represent tumors composed of irregularly distributed, often dysmorphic, neurons and neoplastic astroglia. The pathogenesis of GGs is largely unknown. Low-density lipoprotein receptor-related protein 12 (LRP12) is critical for brain development and involved in tumorigenesis of non-cerebral neoplasms.

MAIN METHODS

Here, we have examined a potential role of LRP12 in the pathogenesis of GGs by a combination of mRNA quantification and molecular-biological in vitro assays.

KEY FINDINGS

We observed a significant increase of the single nucleotide polymorphism (SNP) rs9694676 C-allele, located in the LRP12 promoter, in GGs compared to normal control individuals. C-allele expression is correlated with abundant seizure frequency. Expression of LRP12 was lower in GGs than in control brain. In luciferase assays, the C-allele of rs9694676 decreases both, the basal LRP12 core promoter activity and the stimulatory effect of the transcription factor (TF) STAT5a.

SIGNIFICANCE

Accumulation of functional promoter-associated allelic variants with impact on the transcriptional regulation of LRP12 provides a new pathomechanism for GGs, i.e. highly differentiated epileptogenic brain tumors.

Transcription Factors Expressed in Mouse Cochlear Inner and Outer Hair Cells

Regulation of gene expression is essential to determining the functional complexity and morphological diversity seen among different cells. Transcriptional regulation is a crucial step in gene expression regulation because the genetic information is directly read from DNA by sequence-specific transcription factors (TFs). Although several mouse TF databases created from genome sequences and transcriptomes are available, a cell type-specific TF database from any normal cell populations is still lacking. We identify cell type-specific TF genes expressed in cochlear inner hair cells (IHCs) and outer hair cells (OHCs) using hair cell-specific transcriptomes from adult mice. IHCs and OHCs are the two types of sensory receptor cells in the mammalian cochlea. We show that 1,563 and 1,616 TF genes are respectively expressed in IHCs and OHCs among 2,230 putative mouse TF genes. While 1,536 are commonly expressed in both populations, 73 genes are differentially expressed (with at least a twofold difference) in IHCs and 13 are differentially expressed in OHCs. Our datasets represent the first cell type-specific TF databases for two populations of sensory receptor cells and are key informational resources for understanding the molecular mechanism underlying the biological properties and phenotypical differences of these cells.

PAX6 Isoforms, along with Reprogramming Factors, Differentially Regulate the Induction of Cornea-specific Genes

PAX6 is the key transcription factor involved in eye development in humans, but the differential functions of the two PAX6 isoforms, isoform-a and isoform-b, are largely unknown. To reveal their function in the corneal epithelium, PAX6 isoforms, along with reprogramming factors, were transduced into human non-ocular epithelial cells. Herein, we show that the two PAX6 isoforms differentially and cooperatively regulate the expression of genes specific to the structure and functions of the corneal epithelium, particularly keratin 3 (KRT3) and keratin 12 (KRT12). PAX6 isoform-a induced KRT3 expression by targeting its upstream region. KLF4 enhanced this induction. A combination of PAX6 isoform-b, KLF4, and OCT4 induced KRT12 expression. These new findings will contribute to furthering the understanding of the molecular basis of the corneal epithelium specific phenotype.

Identification of Gender-Specific Genetic Variants in Patients With Bicuspid Aortic Valve

Bicuspid aortic valve (BAV) is the most frequent congenital heart defect and has a male predominance of 3 to 1. A large proportion of patients develop valvular and aortic complications. Despite the high prevalence of BAV, its cause and genetic origins remain elusive. The goal of this study was to identify genetic variants associated with BAV. Nine genes previously associated with BAV (NOTCH1, AXIN1, EGFR, ENG, GATA5, NKX2-5, NOS3, PDIA2, and TGFBR2) were sequenced in 48 patients with BAV using the Ion Torrent Personal Genome Machine. Pathogenicity of genetic variants was evaluated with the Combined Annotation Dependent Depletion framework. A selection of 89 variants identified by sequencing or in previous BAV genetic studies was genotyped, and allele frequencies were compared in 323 patients with BAV confirmed at surgery and 584 controls. Analyses were also performed by gender. Nine novel and 19 potentially pathogenic variants were identified by next-generation sequencing and confirmed by Sanger sequencing, but they were not associated with BAV in the case-control population. A significant association was observed between an in silico-predicted benign EGFR intronic variant (rs17290301) and BAV. Analyses performed by gender revealed different variants associated with BAV in men (EGFR rs533525993 and TEX26 rs12857479) and women (NOTCH1 rs61751489, TGFBR2 rs1155705, and NKX2-5 rs2277923). In conclusion, these results constitute the first association between EGFR genetic variants and BAV in humans and support a possible role of gender-specific polymorphisms in the development of BAV.

Genomic sequencing of a dyslexia susceptibility haplotype encompassing ROBO1

Background

The DYX5 locus for developmental dyslexia was mapped to chromosome 3 by linkage study of a large Finnish family, and later, roundabout guidance receptor 1 (ROBO1) was implicated as a candidate gene at DYX5 with suppressed expression from the segregating rare haplotype. A functional magnetoencephalographic study of several family members revealed abnormal auditory processing of interaural interaction, supporting a defect in midline crossing of auditory pathways. In the current study, we have characterized genetic variation in the broad ROBO1 gene region in the DYX5-linked family, aiming to identify variants that would increase our understanding of the altered expression of ROBO1.

Methods

We have used a whole genome sequencing strategy on a pooled sample of 19 individuals in combination with two individually sequenced genomes. The discovered genetic variants were annotated and filtered. Subsequently, the most interesting variants were functionally tested using relevant methods, including electrophoretic mobility shift assay (EMSA), luciferase assay, and gene knockdown by lentiviral small hairpin RNA (shRNA) in lymphoblasts.

Results

We found one novel intronic single nucleotide variant (SNV) and three novel intergenic SNVs in the broad region of ROBO1 that were specific to the dyslexia susceptibility haplotype. Functional testing by EMSA did not support the binding of transcription factors to three of the SNVs, but one of the SNVs was bound by the LIM homeobox 2 (LHX2) protein, with increased binding affinity for the non-reference allele. Knockdown of LHX2 in lymphoblast cell lines extracted from subjects from the DYX5-linked family showed decreasing expression of ROBO1, supporting the idea that LHX2 regulates ROBO1 also in human.

Conclusions

The discovered variants may explain the segregation of dyslexia in this family, but the effect appears subtle in the experimental settings. Their impact on the developing human brain remains suggestive based on the association and subtle experimental support.

Electronic supplementary material

The online version of this article (doi:10.1186/s11689-016-9136-y) contains supplementary material, which is available to authorized users.

Clinically relevant genes and regulatory pathways associated with NRASQ61 mutations in melanoma through an integrative genomics approach

Therapies such as BRAF inhibitors have become standard treatment for melanoma patients whose tumors harbor activating BRAFV600 mutations. However, analogous therapies for inhibiting NRAS mutant signaling have not yet been well established. In this study, we performed an integrative analysis of DNA methylation, gene expression, and microRNA expression data to identify potential regulatory pathways associated with the most common driver mutations in NRAS (Q61K/L/R) through comparison of NRASQ61-mutated melanomas with pan-negative melanomas. Surprisingly, we found dominant hypomethylation (98.03%) in NRASQ61-mutated melanomas. We identified 1,150 and 49 differentially expressed genes and microRNAs, respectively. Integrated functional analyses of alterations in all three data types revealed important signaling pathways associated with NRASQ61 mutations, such as the MAPK pathway, as well as other novel cellular processes, such as axon guidance. Further analysis of the relationship between DNA methylation and gene expression changes revealed 9 hypermethylated and down-regulated genes and 112 hypomethylated and up-regulated genes in NRASQ61 melanomas. Finally, we identified 52 downstream regulatory cascades of three hypomethylated and up-regulated genes (PDGFD, ZEB1, and THRB). Collectively, our observation of predominant gene hypomethylation in NRASQ61 melanomas and the identification of NRASQ61-linked pathways will be useful for the development of targeted therapies against melanomas harboring NRASQ61 mutations.

Identification of miRNA-mRNA regulatory modules by exploring collective group relationships

Background

microRNAs (miRNAs) play an essential role in the post-transcriptional gene regulation in plants and animals. They regulate a wide range of biological processes by targeting messenger RNAs (mRNAs). Evidence suggests that miRNAs and mRNAs interact collectively in gene regulatory networks. The collective relationships between groups of miRNAs and groups of mRNAs may be more readily interpreted than those between individual miRNAs and mRNAs, and thus are useful for gaining insight into gene regulation and cell functions. Several computational approaches have been developed to discover miRNA-mRNA regulatory modules (MMRMs) with a common aim to elucidate miRNA-mRNA regulatory relationships. However, most existing methods do not consider the collective relationships between a group of miRNAs and the group of targeted mRNAs in the process of discovering MMRMs. Our aim is to develop a framework to discover MMRMs and reveal miRNA-mRNA regulatory relationships from the heterogeneous expression data based on the collective relationships.

Results

We propose DIscovering COllective group RElationships (DICORE), an effective computational framework for revealing miRNA-mRNA regulatory relationships. We utilize the notation of collective group relationships to build the computational framework. The method computes the collaboration scores of the miRNAs and mRNAs on the basis of their interactions with mRNAs and miRNAs, respectively. Then it determines the groups of miRNAs and groups of mRNAs separately based on their respective collaboration scores. Next, it calculates the strength of the collective relationship between each pair of miRNA group and mRNA group using canonical correlation analysis, and the group pairs with significant canonical correlations are considered as the MMRMs. We applied this method to three gene expression datasets, and validated the computational discoveries.

Conclusions

Analysis of the results demonstrates that a large portion of the regulatory relationships discovered by DICORE is consistent with the experimentally confirmed databases. Furthermore, it is observed that the top mRNAs that are regulated by the miRNAs in the identified MMRMs are highly relevant to the biological conditions of the given datasets. It is also shown that the MMRMs identified by DICORE are more biologically significant and functionally enriched.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2300-z) contains supplementary material, which is available to authorized users.

Inference of hierarchical regulatory network of TCF7L2 binding sites in MCF7 cell line

The TCF7L2 transcription factor (TF) is a member of Wnt signalling pathway, and may influence transcription of several genes by binding to distinct regulatory regions. Genome-wide studies have identified thousands of TCF7L2 binding sites and have revealed some associated TF partners. However, there is still a large uncharted region in the hierarchical regulatory network for TCF7L2 and the partner TFs in MCF7 cells. We analysed ChIP-seq data by searching for motifs in the enriched peak region based on TF-specific position weight matrix (PWM). We found association of FOXO1 and CAD with up-regulated genes, AP2α, PBF and AP1 with down-regulated genes. TCF7L2 and GATA3 were found to be associated with both up and down-regulated genes. Our study uncovers new TCF7L2 associated regulatory networks by mining ChIP-seq data in MCF7 cell, which may contribute to further study of the mechanisms related to Wnt pathway in breast cancer or other diseases.

From System-Wide Differential Gene Expression to Perturbed Regulatory Factors: A Combinatorial Approach

High-throughput experiments such as microarrays and deep sequencing provide large scale information on the pattern of gene expression, which undergoes extensive remodeling as the cell dynamically responds to varying environmental cues or has its function disrupted under pathological conditions. An important initial step in the systematic analysis and interpretation of genome-scale expression alteration involves identification of a set of perturbed transcriptional regulators whose differential activity can provide a proximate hypothesis to account for these transcriptomic changes. In the present work, we propose an unbiased and logically natural approach to transcription factor enrichment. It involves overlaying a list of experimentally determined differentially expressed genes on a background regulatory network coming from e.g. literature curation or computational motif scanning, and identifying that subset of regulators whose aggregated target set best discriminates between the altered and the unaffected genes. In other words, our methodology entails testing of all possible regulatory subnetworks, rather than just the target sets of individual regulators as is followed in most standard approaches. We have proposed an iterative search method to efficiently find such a combination, and benchmarked it on E. coli microarray and regulatory network data available in the public domain. Comparative analysis carried out on artificially generated differential expression profiles, as well as empirical factor overexpression data for M. tuberculosis, shows that our methodology provides marked improvement in accuracy of regulatory inference relative to the standard method that involves evaluating factor enrichment in an individual manner.

E2F1 Transcription Factor Regulates O-linked N-acetylglucosamine (O-GlcNAc) Transferase and O-GlcNAcase Expression

Protein O-GlcNAcylation, which is controlled by O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA), has emerged as an important posttranslational modification that may factor in multiple diseases. Until recently, it was assumed that OGT/OGA protein expression was relatively constant. Several groups, including ours, have shown that OGT and/or OGA expression changes in several pathologic contexts, yet the cis and trans elements that regulate the expression of these enzymes remain essentially unexplored. Here, we used a reporter-based assay to analyze minimal promoters and leveraged in silico modeling to nominate several candidate transcription factor binding sites in both Ogt (i.e. the gene for OGT protein) and Mgea5 (i.e. the gene for OGA protein). We noted multiple E2F binding site consensus sequences in both promoters. We performed chromatin immunoprecipitation in both human and mouse cells and found that E2F1 bound to candidate E2F binding sites in both promoters. In HEK293 cells, we overexpressed E2F1, which significantly reduced OGT and MGEA5 expression. Conversely, E2F1-deficient mouse fibroblasts had increased Ogt and Mgea5 expression. Of the known binding partners for E2F1, we queried whether retinoblastoma 1 (Rb1) might be involved. Rb1-deficient mouse embryonic fibroblasts showed increased levels of Ogt and Mgea5 expression, yet overexpression of E2F1 in the Rb1-deficient cells did not alter Ogt and Mgea5 expression, suggesting that Rb1 is required for E2F1-mediated suppression. In conclusion, this work identifies and validates some of the promoter elements for mouse Ogt and Mgea5 genes. Specifically, E2F1 negatively regulates both Ogt and Mgea5 expression in an Rb1 protein-dependent manner.

Detecting shifts in gene regulatory networks during time-course experiments at single-time-point temporal resolution

Comprehensively understanding the dynamics of biological systems is one of the greatest challenges in biology. Vastly improved biological technologies have provided vast amounts of information that must be understood by bioinformatics and systems biology researchers. Gene regulations have been frequently modeled by ordinary differential equations or graphical models based on time-course gene expression profiles. The state-of-the-art computational approaches for analyzing gene regulations assume that their models are same throughout time-course experiments. However, these approaches cannot easily analyze transient changes at a time point, such as diauxic shift. We propose a score that analyzes the gene regulations at each time point. The score is based on the information gains of information criterion values. The method detects the shifts in gene regulatory networks (GRNs) during time-course experiments with single-time-point resolution. The effectiveness of the method is evaluated on the diauxic shift from glucose to lactose in Escherichia coli. Gene regulation shifts were detected at two time points: the first corresponding to the time at which the growth of E. coli ceased and the second corresponding to the end of the experiment, when the nutrient sources (glucose and lactose) had become exhausted. According to these results, the proposed score and method can appropriately detect the time of gene regulation shifts. The method based on the proposed score provides a new tool for analyzing dynamic biological systems. Because the score value indicates the strength of gene regulation at each time point in a gene expression profile, it can potentially infer hidden GRNs from time-course experiments.

Decreased MicroRNA-26a expression causes cisplatin resistance in human non-small cell lung cancer

BACKGROUND

Lung cancer is the most common cancer that is caused by perturbation of regulatory pathways rather than dysfunction of a single gene. Cisplatin (CDDP; cis-diamminedichloroplatinum II) is the first member of a class of platinum-containing anti-cancer medication, which binds to DNA and triggers apoptosis. CDDP-based chemotherapy is used to treat various types of cancers. However, the efficacy of CDDP in the treatment of non-small-cell lung cancer (NSCLC) is limited by acquired drug resistance. MicroRNAs have recently emerged as key regulators of cancers, and miR-26a is one of down-regulated miRNAs in A549/CDDPres cell line. This study aimed to investigate the role of miR-26a in CDDP resistance in NSCLC as well as the underlying mechanisms.

METHODS

In this study, we analyzed expressional profiles of CDDP resistance-related mRNA, miRNA, and transcription factors (TF) that regulate miRNA expression in NSCLC. A549 cells were treated with CDDP, miR-26a mimic, or miR-26a inhibitor, and followed by biological analysis including drug sensitivity assay, colony formation assay, terminal-deoxynucleoitidyl Transferase Mediated Nick End Labeling (TUNEL) assay, and cell cycle analysis. Luciferase assay was used to determine the target of miR-26a. The regulation of miR-26a in Akt pathway was measured by western blot.

RESULTS

High mobility group A (HMGA) 2 was identified as the target of miR-26a. Overexpression of miR-26a in A549 cells inhibited G1-S transition, increased cell death in response to CDDP treatment, and decreased the colony formation of A549 cells. MiR-26a significantly decreased the expression of E2F1, diminished Akt phosphorylation, and downregulated Bcl2 expression. Cell growth was suppressed by inhibiting HMGA2-mediated E2F1-Akt pathway.

CONCLUSION

MiR-26a is responsible for A549 cell sensitivity in the treatment of CDDP through regulating HMGA2-mediated E2F1-Akt pathway.

Differences in the Early Development of Human and Mouse Embryonic Stem Cells

We performed a systematic analysis of gene expression features in early (10–21 days) development of human vs mouse embryonic cells (hESCs vs mESCs). Many development features were found to be conserved, and a majority of differentially regulated genes have similar expression change in both organisms. The similarity is especially evident, when gene expression profiles are clustered together and properties of clustered groups of genes are compared. First 10 days of mESC development match the features of hESC development within 21 days, in accordance with the differences in population doubling time in human and mouse ESCs. At the same time, several important differences are seen. There is a clear difference in initial expression change of transcription factors and stimulus responsive genes, which may be caused by the difference in experimental procedures. However, we also found that some biological processes develop differently; this can clearly be shown, for example, for neuron and sensory organ development. Some groups of genes show peaks of the expression levels during the development and these peaks cannot be claimed to happen at the same time points in the two organisms, as well as for the same groups of (orthologous) genes. We also detected a larger number of upregulated genes during development of mESCs as compared to hESCs. The differences were quantified by comparing promoters of related genes. Most of gene groups behave similarly and have similar transcription factor (TF) binding sites on their promoters. A few groups of genes have similar promoters, but are expressed differently in two species. Interestingly, there are groups of genes expressed similarly, although they have different promoters, which can be shown by comparing their TF binding sites. Namely, a large group of similarly expressed cell cycle-related genes is found to have discrepant TF binding properties in mouse vs human.

Disruptions in a cluster of computationally identified enhancers near FOXC1 and GMDS may influence brain development

Regulatory elements are more evolutionarily conserved and provide a larger mutational target than coding regions of the human genome, suggesting that mutations in non-coding regions contribute significantly to development and disease. Using a computational approach to predict gene regulatory enhancers, we found that many known and predicted embryonic enhancers cluster in genomic loci harboring development-associated genes. One of the densest clusters of predicted enhancers in the human genome is near the genes GMDS and FOXC1. GMDS encodes a short-chain mannose dehydrogenase enzyme involved in the regulation of hindbrain neural migration, and FOXC1 encodes a developmental transcription factor required for brain, heart, and eye development. We experimentally validate four novel enhancers in this locus and demonstrate that these enhancers show consistent activity during embryonic development in domains that overlap with the expression of FOXC1 and GMDS. These four enhancers contain binding motifs for several transcription factors, including the ZIC family of transcription factors. Removal of the ZIC binding sites significantly alters enhancer activity in three of these enhancers, reducing expression in the eye, hindbrain, and limb, suggesting a mechanism whereby ZIC family members may transcriptionally regulate FOXC1 and/or GMDS expression. Our findings uncover novel enhancer regions that may control transcription in a topological domain important for embryonic development.

Methylation of the Gpat2 promoter regulates transient expression during mouse spermatogenesis

We studied the expression pattern and the mechanisms governing the transcription of GPAT2, an enzyme that is highly expressed in testis. GPAT2 is regulated epigenetically and its expression correlates with the initiation of meiosis.

Spermatogenesis is a highly regulated process that involves both mitotic and meiotic divisions, as well as cellular differentiation to yield mature spermatozoa from undifferentiated germinal stem cells. Although Gpat2 was originally annotated as encoding a glycerol-3-phosphate acyltransferase by sequence homology to Gpat1, GPAT2 is highly expressed in testis but not in lipogenic tissues and is not up-regulated during adipocyte differentiation. New data show that GPAT2 is required for the synthesis of piRNAs (piwi-interacting RNAs), a group of small RNAs that protect the germ cell genome from retrotransposable elements. In order to understand the relationship between GPAT2 and its role in the testis, we focused on Gpat2 expression during the first wave of mouse spermatogenesis. Gpat2 expression was analysed by qPCR (quantitative real-time PCR), in situ hybridization, immunohistochemistry and Western blotting. Gpat2 mRNA content and protein expression were maximal at 15 dpp (days post-partum) and were restricted to pachytene spermatocytes. To achieve this transient expression, both epigenetic mechanisms and trans-acting factors are involved. In vitro assays showed that Gpat2 expression correlates with DNA demethylation and histone acetylation and that it is up-regulated by retinoic acid. Epigenetic regulation by DNA methylation was confirmed in vivo in germ cells by bisulfite sequencing of the Gpat2 promoter. Consistent with the initiation of meiosis at 11 dpp, methylation decreased dramatically. Thus, Gpat2 is expressed at a specific stage of spermatogenesis, consistent with piRNA synthesis and meiosis I prophase, and its on–off expression pattern responds predominantly to epigenetic modifications.

Integrated systems approach identifies risk regulatory pathways and key regulators in coronary artery disease

Coronary artery disease (CAD) is the most common type of heart disease. However, the molecular mechanisms of CAD remain elusive. Regulatory pathways are known to play crucial roles in many pathogenic processes. Thus, inferring risk regulatory pathways is an important step toward elucidating the mechanisms underlying CAD. With advances in high-throughput data, we developed an integrated systems approach to identify CAD risk regulatory pathways and key regulators. Firstly, a CAD-related core subnetwork was identified from a curated transcription factor (TF) and microRNA (miRNA) regulatory network based on a random walk algorithm. Secondly, candidate risk regulatory pathways were extracted from the subnetwork by applying a breadth-first search (BFS) algorithm. Then, risk regulatory pathways were prioritized based on multiple CAD-associated data sources. Finally, we also proposed a new measure to prioritize upstream regulators. We inferred that phosphatase and tensin homolog (PTEN) may be a key regulator in the dysregulation of risk regulatory pathways. This study takes a closer step than the identification of disease subnetworks or modules. From the risk regulatory pathways, we could understand the flow of regulatory information in the initiation and progression of the disease. Our approach helps to uncover its potential etiology.

KEY MESSAGES

We developed an integrated systems approach to identify risk regulatory pathways. We proposed a new measure to prioritize the key regulators in CAD. PTEN may be a key regulator in dysregulation of the risk regulatory pathways.

Using prior knowledge from cellular pathways and molecular networks for diagnostic specimen classification

For many complex diseases, an earlier and more reliable diagnosis is considered a key prerequisite for developing more effective therapies to prevent or delay disease progression. Classical statistical learning approaches for specimen classification using omics data, however, often cannot provide diagnostic models with sufficient accuracy and robustness for heterogeneous diseases like cancers or neurodegenerative disorders. In recent years, new approaches for building multivariate biomarker models on omics data have been proposed, which exploit prior biological knowledge from molecular networks and cellular pathways to address these limitations. This survey provides an overview of these recent developments and compares pathway- and network-based specimen classification approaches in terms of their utility for improving model robustness, accuracy and biological interpretability. Different routes to translate omics-based multifactorial biomarker models into clinical diagnostic tests are discussed, and a previous study is presented as example.

Compound hierarchical correlated beta mixture with an application to cluster mouse transcription factor DNA binding data

Modeling correlation structures is a challenge in bioinformatics, especially when dealing with high throughput genomic data. A compound hierarchical correlated beta mixture (CBM) with an exchangeable correlation structure is proposed to cluster genetic vectors into mixture components. The correlation coefficient, [Formula: see text], is homogenous within a mixture component and heterogeneous between mixture components. A random CBM with [Formula: see text] brings more flexibility in explaining correlation variations among genetic variables. Expectation-Maximization (EM) algorithm and Stochastic Expectation-Maximization (SEM) algorithm are used to estimate parameters of CBM. The number of mixture components can be determined using model selection criteria such as AIC, BIC and ICL-BIC. Extensive simulation studies were conducted to compare EM, SEM and model selection criteria. Simulation results suggest that CBM outperforms the traditional beta mixture model with lower estimation bias and higher classification accuracy. The proposed method is applied to cluster transcription factor-DNA binding probability in mouse genome data generated by Lahdesmaki and others (2008, Probabilistic inference of transcription factor binding from multiple data sources. PLoS One, 3: , e1820). The results reveal distinct clusters of transcription factors when binding to promoter regions of genes in JAK-STAT, MAPK and other two pathways.

Endothelial inflammatory transcriptional responses to an altered plasma exposome following inhalation of diesel emissions

BACKGROUND

Air pollution, especially emissions derived from traffic sources, is associated with adverse cardiovascular outcomes. However, it remains unclear how inhaled factors drive extrapulmonary pathology.

OBJECTIVES

Previously, we found that canonical inflammatory response transcripts were elevated in cultured endothelial cells treated with plasma obtained after exposure compared with pre-exposure samples or filtered air (sham) exposures. While the findings confirmed the presence of bioactive factor(s) in the plasma after diesel inhalation, we wanted to better examine the complete genomic response to investigate (1) major responsive transcripts and (2) collected response pathways and ontogeny that may help to refine this method and inform the pathogenesis.

METHODS

We assayed endothelial RNA with gene expression microarrays, examining the responses of cultured endothelial cells to plasma obtained from six healthy human subjects exposed to 100 μg/m(3) diesel exhaust or filtered air for 2 h on separate occasions. In addition to pre-exposure baseline samples, we investigated samples obtained immediately-post and 24 h-post exposure.

RESULTS

Microarray analysis of the coronary artery endothelial cells challenged with plasma identified 855 probes that changed over time following diesel exhaust exposure. Over-representation analysis identified inflammatory cytokine pathways were upregulated both at the 2 and 24 h conditions. Novel pathways related to FOXO transcription factors and secreted extracellular factors were also identified in the microarray analysis.

CONCLUSIONS

These outcomes are consistent with our recent findings that plasma contains bioactive and inflammatory factors following pollutant inhalation and provide a novel pathway to explain the well-reported extrapulmonary toxicity of ambient air pollutants.

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

Multiple functional variants in long-range enhancer elements contribute to the risk of SNP rs965513 in thyroid cancer

The [A] allele of SNP rs965513 in 9q22 has been consistently shown to be highly associated with increased papillary thyroid cancer (PTC) risk with an odds ratio of ∼1.8 as determined by genome-wide association studies, yet the molecular mechanisms remain poorly understood. Previously, we noted that the expression of two genes in the region, forkhead box E1 (FOXE1) and PTC susceptibility candidate 2 (PTCSC2), is regulated by rs965513 in unaffected thyroid tissue, but the underlying mechanisms were not elucidated. Here, we fine-mapped the 9q22 region in PTC and controls and detected an ∼33-kb linkage disequilibrium block (containing the lead SNP rs965513) that significantly associates with PTC risk. Chromatin characteristics and regulatory element signatures in this block disclosed at least three regulatory elements functioning as enhancers. These enhancers harbor at least four SNPs (rs7864322, rs12352658, rs7847449, and rs10759944) that serve as functional variants. The variant genotypes are associated with differential enhancer activities and/or transcription factor binding activities. Using the chromosome conformation capture methodology, long-range looping interactions of these elements with the promoter region shared by FOXE1 and PTCSC2 in a human papillary thyroid carcinoma cell line (KTC-1) and unaffected thyroid tissue were found. Our results suggest that multiple variants coinherited with the lead SNP and located in long-range enhancers are involved in the transcriptional regulation of FOXE1 and PTCSC2 expression. These results explain the mechanism by which the risk allele of rs965513 predisposes to thyroid cancer.

Involvement of cysteine-rich protein 61 in the epidermal growth factor-induced migration of human anaplastic thyroid cancer cells

Anaplastic thyroid cancer (ATC) is among the most aggressive types of malignant cancer. Epidermal growth factor (EGF) plays a crucial role in the pathogenesis of ATC, and patients with thyroid carcinoma typically exhibit increased cysteine-rich protein 61 (Cyr61). In this study, we found that EGF treatment induced cell migration, stress fiber formation, Cyr61 mRNA and protein expressions, and Cyr61 protein secretion in ATC cells. The recombinant Cyr61 protein significantly induced cell migration; however, inhibition of Cyr61 activity by a Cyr61-specific antibody abrogated EGF-induced cell migration. EGF treatment also affected epithelial-to-mesenchymal transition (EMT)-related marker protein expression, as evidenced by an increase in vimentin and a decrease in E-cadherin expression. Inhibition of Cyr61 expression by Cyr61 siRNA decreased cell migration and reversed the EMT-related marker protein expression. EGF treatment increased the phosphorylation of the extracellular signal-regulated kinase (ERK) and cAMP response element-binding protein (CREB), and finally activated Cyr61 promoter plasmid activity. Our results suggest that Cyr61 is induced by EGF through the ERK/CREB signal pathway and that it plays a crucial role in the migration and invasion of ATC cells; moreover, Cyr61 might be a therapeutic target for metastatic ATC.