MatrixCatch--a novel tool for the recognition of composite regulatory elements in promoters

BestCRM: An Exhaustive Search for Optimal Cis-Regulatory Modules in Promoters Accelerated by the Multidimensional Hash Function

The concept of cis-regulatory modules located in gene promoters represents today's vision of the organization of gene transcriptional regulation. Such modules are a combination of two or more single, short DNA motifs. The bioinformatic identification of such modules belongs to so-called NP-hard problems with extreme computational complexity, and therefore, simplifications, assumptions, and heuristics are usually deployed to tackle the problem. In practice, this requires, first, many parameters to be set before the search, and second, it leads to the identification of locally optimal results. Here, a novel method is presented, aimed at identifying the cis-regulatory elements in gene promoters based on an exhaustive search of all the feasible modules' configurations. All required parameters are automatically estimated using positive and negative datasets. To be computationally efficient, the search is accelerated using a multidimensional hash function, allowing the search to complete in a few hours on a regular laptop (for example, a CPU Intel i7, 3.2 GH, 32 Gb RAM). Tests on an established benchmark and real data show better performance of BestCRM compared to the available methods according to several metrics like specificity, sensitivity, AUC, etc. A great practical advantage of the method is its minimum number of input parameters-apart from positive and negative promoters, only a desired level of module presence in promoters is required.

Peak Scores Significantly Depend on the Relationships between Contextual Signals in ChIP-Seq Peaks

Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) is a central genome-wide method for in vivo analyses of DNA-protein interactions in various cellular conditions. Numerous studies have demonstrated the complex contextual organization of ChIP-seq peak sequences and the presence of binding sites for transcription factors in them. We assessed the dependence of the ChIP-seq peak score on the presence of different contextual signals in the peak sequences by analyzing these sequences from several ChIP-seq experiments using our fully enumerative GPU-based de novo motif discovery method, Argo_CUDA. Analysis revealed sets of significant IUPAC motifs corresponding to the binding sites of the target and partner transcription factors. For these ChIP-seq experiments, multiple regression models were constructed, demonstrating a significant dependence of the peak scores on the presence in the peak sequences of not only highly significant target motifs but also less significant motifs corresponding to the binding sites of the partner transcription factors. A significant correlation was shown between the presence of the target motifs FOXA2 and the partner motifs HNF4G, which found experimental confirmation in the scientific literature, demonstrating the important contribution of the partner transcription factors to the binding of the target transcription factor to DNA and, consequently, their important contribution to the peak score.

ErbB4 Is a Potential Key Regulator of the Pathways Activated by NTRK-Fusions in Thyroid Cancer

NTRK gene fusions are drivers of tumorigenesis events that specific Trk-inhibitors can target. Current knowledge of the downstream pathways activated has been previously limited to the pathways of regulator proteins phosphorylated directly by Trk receptors. Here, we aimed to detect genes whose expression is increased in response to the activation of these pathways. We identified and analyzed differentially expressed genes in thyroid cancer samples with NTRK1 or NTRK3 gene fusions, and without any NTRK fusions, versus normal thyroid gland tissues, using data from the Cancer Genome Atlas, the DESeq2 tool, and the Genome Enhancer and geneXplain platforms. Searching for the genes activated only in samples with an NTRK fusion as opposed to those without NTRK fusions, we identified 29 genes involved in nervous system development, including AUTS2, DTNA, ERBB4, FLRT2, FLRT3, RPH3A, and SCN4A. We found that genes regulating the expression of the upregulated genes (i.e., upstream regulators) were enriched in the “signaling by ERBB4” pathway. ERBB4 was also one of three genes encoding master regulators whose expression was increased only in samples with an NTRK fusion. Moreover, the algorithm searching for positive feedback loops for gene promoters and transcription factors (a so-called “walking pathways” algorithm) identified the ErbB4 protein as the key master regulator. ERBB4 upregulation (p-value = 0.004) was confirmed in an independent sample of ETV6-NTRK3-positive FFPE specimens. Thus, ErbB4 is the potential key regulator of the pathways activated by NTRK gene fusions in thyroid cancer. These results are preliminary and require additional biochemical validation.

First insights into the molecular basis association between promoter polymorphisms of the IL1B gene and Helicobacter pylori infection in the Sudanese population: computational approach

BACKGROUND

Helicobacter pylori (H. pylori) infects nearly half of the world's population with a variation in incidence among different geographic regions. Genetic variants in the promoter regions of the IL1B gene can affect cytokine expression and creates a condition of hypoacidity which favors the survival and colonization of H. pylori. Therefore, the aim of this study was to characterize the polymorphic sites in the 5'- region [-687_ + 297] of IL1B in H. pylori infection using in silico tools.

RESULTS

A total of five nucleotide variations were detected in the 5'-regulatory region [-687_ + 297] of IL1B which led to the addition or alteration of transcription factor binding sites (TFBSs) or composite regulatory elements (CEs). Genotyping of IL1B - 31 C > T revealed a significant association between -31 T and susceptibility to H. pylori infection in the studied population (P = 0.0363). Comparative analysis showed conservation rates of IL1B upstream [-368_ + 10] region above 70% in chimpanzee, rhesus monkey, a domesticated dog, cow and rat.

CONCLUSIONS

In H. pylori-infected patients, three detected SNPs (- 338, - 155 and - 31) located in the IL1B promoter were predicted to alter TFBSs and CE, which might affect the gene expression. These in silico predictions provide insight for further experimental in vitro and in vivo studies of the regulation of IL1B expression and its relationship to H. pylori infection. However, the recognition of regulatory motifs by computer algorithms is fundamental for understanding gene expression patterns.

A single ChIP-seq dataset is sufficient for comprehensive analysis of motifs co-occurrence with MCOT package

Recognition of composite elements consisting of two transcription factor binding sites gets behind the studies of tissue-, stage- and condition-specific transcription. Genome-wide data on transcription factor binding generated with ChIP-seq method facilitate an identification of composite elements, but the existing bioinformatics tools either require ChIP-seq datasets for both partner transcription factors, or omit composite elements with motifs overlapping. Here we present an universal Motifs Co-Occurrence Tool (MCOT) that retrieves maximum information about overrepresented composite elements from a single ChIP-seq dataset. This includes homo- and heterotypic composite elements of four mutual orientations of motifs, separated with a spacer or overlapping, even if recognition of motifs within composite element requires various stringencies. Analysis of 52 ChIP-seq datasets for 18 human transcription factors confirmed that for over 60% of analyzed datasets and transcription factors predicted co-occurrence of motifs implied experimentally proven protein-protein interaction of respecting transcription factors. Analysis of 164 ChIP-seq datasets for 57 mammalian transcription factors showed that abundance of predicted composite elements with an overlap of motifs compared to those with a spacer more than doubled; and they had 1.5-fold increase of asymmetrical pairs of motifs with one more conservative 'leading' motif and another one 'guided'.

An Intergenic rs9275596 Polymorphism on Chr. 6p21 Is Associated with Multiple Sclerosis in Latvians

Background and objectives: Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system, leading to demyelination of neurons and potentially debilitating physical and mental symptoms. The disease is more prevalent in women than in men. The major histocompatibility complex (MHC) region has been identified as a major genetic determinant for autoimmune diseases, and its role in some neurological disorders including MS was evaluated. An intergenic single-nucleotide polymorphism (SNP), rs9275596, located between the HLA-DQB1 and HLA-DQA2 genes, is in significant association with various autoimmune diseases according to genome-wide association studies (GWASs). A cumulative effect of this SNP with other polymorphisms from this region was revealed. The aim of the study was to verify the data on rs9275596 association in multiple sclerosis in a case/control study of the Latvian population and to evaluate eventual functional significance of allele substitutions. Materials and Methods: rs9275596 (chr6:32713854; GRCh38.p12) was genotyped in 273 MS patients and 208 controls on main and sex-specific associations. Eventual functional significance of allele substitutions was evaluated in silico using publicly available tools. Results: The rs9275596 rare alleles were identified as a disease susceptibility factor in association with the MS main group and in affected females (p < 0.001 and p < 0.01, respectively). Risk factor genotypes with rare alleles included were associated with the MS common cohort (p < 0.002) and female cohort (odds ratio, OR = 2.24) and were identified as disease susceptible in males (OR = 2.41). It was shown that structural changes of rs9275596 affect the secondary structure of DNA. Functional significance of allele substitutions was evaluated on the eventual sequence affinity to transcription factors (TFs) and splicing signals similarity. A possible impact of the particular polymorphisms on the transcription and splicing efficiency is discussed. Conclusions: Our results suggest susceptibility of rs9275596 to multiple sclerosis in Latvians.

Removing Background Co-occurrences of Transcription Factor Binding Sites Greatly Improves the Prediction of Specific Transcription Factor Cooperations

Today, it is well-known that in eukaryotic cells the complex interplay of transcription factors (TFs) bound to the DNA of promoters and enhancers is the basis for precise and specific control of transcription. Computational methods have been developed for the identification of potentially cooperating TFs through the co-occurrence of their binding sites (TFBSs). One challenge of these methods is the differentiation of TFBS pairs that are specific for a given sequence set from those that are ubiquitously appearing, rendering the results highly dependent on the choice of a proper background set. Here, we present an extension of our previous PC-TraFF approach that estimates the background co-occurrence of any TF pair by preserving the (oligo-) nucleotide composition and, thus, the core of TFBSs in the sequences of interest. Applying our approach to a simulated data set with implanted TFBS pairs, we could successfully identify them as sequence-set specific under a variety of conditions. When we analyzed the gene expression data sets of five breast cancer associated subtypes, the number of overlapping pairs could be dramatically reduced in comparison to our previous approach. As a result, we could identify potentially cooperating transcriptional regulators that are characteristic for each of the five breast cancer subtypes. This indicates that our approach is able to discriminate specific potential TF cooperations against ubiquitously occurring combinations. The results obtained with our method may help to understand the genetic programs governing specific biological processes such as the development of different tumor types.

Structural and developmental expression of Ss-riok-2, an RIO protein kinase encoding gene of Strongyloides stercoralis

RIO kinases are essential atypical protein kinases in diverse prokaryotic and eukaryotic organisms, playing significant roles in yeast and humans. However, little is known about their functions in parasitic nematodes. In the present study, we have isolated and characterized the full-length cDNA, gDNA and a putative promoter of a RIOK-2 protein kinase (Ss-RIOK-2) encoding gene (Ss-riok-2) from Strongyloides stercoralis, a medically important parasitic nematode (Order Rhabditida). A three-dimensional structure (3D) model of Ss-RIOK-2 was generated using the Chaetomium thermophilum RIOK-2 protein kinase (Ct-RIOK-2) crystal structure 4GYG as a template. A docking study revealed some critical sites for ATP binding and metal binding. The putative promoter of Ss-riok-2 contains a number of conserved elements. RNAseq analysis revealed the highest levels of the Ss-riok-2 transcript in free-living females and parasitic females. To identify anatomical patterns of Ss-riok-2 expression in S. stercoralis, we observed expression patterns of a transgene construct encoding green fluorescent protein under the Ss-riok-2 promoter in post free-living S. stercoralis. Expression driven by this promoter predominated in intestinal cells. This study demonstrates significant advancement in molecular and cellular biological study of S. stercoralis and of parasitic nematodes generally, and provides a foundation for further functional genomic studies.

c-Jun Contributes to Transcriptional Control of GNA12 Expression in Prostate Cancer Cells

GNA12 is the α subunit of a heterotrimeric G protein that possesses oncogenic potential. Activated GNA12 also promotes prostate and breast cancer cell invasion in vitro and in vivo, and its expression is up-regulated in many tumors, particularly metastatic tissues. In this study, we explored the control of expression of GNA12 in prostate cancer cells. Initial studies on LnCAP (low metastatic potential, containing low levels of GNA12) and PC3 (high metastatic potential, containing high GNA12 levels) cells revealed that GNA12 mRNA levels correlated with protein levels, suggesting control at the transcriptional level. To identify potential factors controlling GNA12 transcription, we cloned the upstream 5′ regulatory region of the human GNA12 gene and examined its activity using reporter assays. Deletion analysis revealed the highest level of promoter activity in a 784 bp region, and subsequent in silico analysis indicated the presence of transcription factor binding sites for C/EBP (CCAAT/enhancer binding protein), CREB1 (cAMP-response-element-binding protein 1), and c-Jun in this minimal element for transcriptional control. A small interfering RNA (siRNA) knockdown approach revealed that silencing of c-Jun expression significantly reduced GNA12 5′ regulatory region reporter activity. In addition, chromatin immunoprecipitation assays confirmed that c-Jun binds to the GNA12 5′ regulatory region in PC3 cells. Silencing of c-Jun expression reduced mRNA and protein levels of GNA12, but not the closely-related GNA13, in prostate cancer cells. Understanding the mechanisms by which GNA12 expression is controlled may aid in the development of therapies that target key elements responsible for GNA12-mediated tumor progression.

Candidate SNP Markers of Gender-Biased Autoimmune Complications of Monogenic Diseases Are Predicted by a Significant Change in the Affinity of TATA-Binding Protein for Human Gene Promoters

Some variations of human genome [for example, single nucleotide polymorphisms (SNPs)] are markers of hereditary diseases and drug responses. Analysis of them can help to improve treatment. Computer-based analysis of millions of SNPs in the 1000 Genomes project makes a search for SNP markers more targeted. Here, we combined two computer-based approaches: DNA sequence analysis and keyword search in databases. In the binding sites for TATA-binding protein (TBP) in human gene promoters, we found candidate SNP markers of gender-biased autoimmune diseases, including rs1143627 [cachexia in rheumatoid arthritis (double prevalence among women)]; rs11557611 [demyelinating diseases (thrice more prevalent among young white women than among non-white individuals)]; rs17231520 and rs569033466 [both: atherosclerosis comorbid with related diseases (double prevalence among women)]; rs563763767 [Hughes syndrome-related thrombosis (lethal during pregnancy)]; rs2814778 [autoimmune diseases (excluding multiple sclerosis and rheumatoid arthritis) underlying hypergammaglobulinemia in women]; rs72661131 and rs562962093 (both: preterm delivery in pregnant diabetic women); and rs35518301, rs34166473, rs34500389, rs33981098, rs33980857, rs397509430, rs34598529, rs33931746, rs281864525, and rs63750953 (all: autoimmune diseases underlying hypergammaglobulinemia in women). Validation of these predicted candidate SNP markers using the clinical standards may advance personalized medicine.

Computational Detection of Stage-Specific Transcription Factor Clusters during Heart Development

Transcription factors (TFs) regulate gene expression in living organisms. In higher organisms, TFs often interact in non-random combinations with each other to control gene transcription. Understanding the interactions is key to decipher mechanisms underlying tissue development. The aim of this study was to analyze co-occurring transcription factor binding sites (TFBSs) in a time series dataset from a new cell-culture model of human heart muscle development in order to identify common as well as specific co-occurring TFBS pairs in the promoter regions of regulated genes which can be essential to enhance cardiac tissue developmental processes. To this end, we separated available RNAseq dataset into five temporally defined groups: (i) mesoderm induction stage; (ii) early cardiac specification stage; (iii) late cardiac specification stage; (iv) early cardiac maturation stage; (v) late cardiac maturation stage, where each of these stages is characterized by unique differentially expressed genes (DEGs). To identify TFBS pairs for each stage, we applied the MatrixCatch algorithm, which is a successful method to deduce experimentally described TFBS pairs in the promoters of the DEGs. Although DEGs in each stage are distinct, our results show that the TFBS pair networks predicted by MatrixCatch for all stages are quite similar. Thus, we extend the results of MatrixCatch utilizing a Markov clustering algorithm (MCL) to perform network analysis. Using our extended approach, we are able to separate the TFBS pair networks in several clusters to highlight stage-specific co-occurences between TFBSs. Our approach has revealed clusters that are either common (NFAT or HMGIY clusters) or specific (SMAD or AP-1 clusters) for the individual stages. Several of these clusters are likely to play an important role during the cardiomyogenesis. Further, we have shown that the related TFs of TFBSs in the clusters indicate potential synergistic or antagonistic interactions to switch between different stages. Additionally, our results suggest that cardiomyogenesis follows the hourglass model which was already proven for Arabidopsis and some vertebrates. This investigation helps us to get a better understanding of how each stage of cardiomyogenesis is affected by different combination of TFs. Such knowledge may help to understand basic principles of stem cell differentiation into cardiomyocytes.

Analysis of Genomic Sequence Motifs for Deciphering Transcription Factor Binding and Transcriptional Regulation in Eukaryotic Cells

Eukaryotic genomes contain a variety of structured patterns: repetitive elements, binding sites of DNA and RNA associated proteins, splice sites, and so on. Often, these structured patterns can be formalized as motifs and described using a proper mathematical model such as position weight matrix and IUPAC consensus. Two key tasks are typically carried out for motifs in the context of the analysis of genomic sequences. These are: identification in a set of DNA regions of over-represented motifs from a particular motif database, and de novo discovery of over-represented motifs. Here we describe existing methodology to perform these two tasks for motifs characterizing transcription factor binding. When applied to the output of ChIP-seq and ChIP-exo experiments, or to promoter regions of co-modulated genes, motif analysis techniques allow for the prediction of transcription factor binding events and enable identification of transcriptional regulators and co-regulators. The usefulness of motif analysis is further exemplified in this review by how motif discovery improves peak calling in ChIP-seq and ChIP-exo experiments and, when coupled with information on gene expression, allows insights into physical mechanisms of transcriptional modulation.

Obesity-related known and candidate SNP markers can significantly change affinity of TATA-binding protein for human gene promoters

BACKGROUND

Obesity affects quality of life and life expectancy and is associated with cardiovascular disorders, cancer, diabetes, reproductive disorders in women, prostate diseases in men, and congenital anomalies in children. The use of single nucleotide polymorphism (SNP) markers of diseases and drug responses (i.e., significant differences of personal genomes of patients from the reference human genome) can help physicians to improve treatment. Clinical research can validate SNP markers via genotyping of patients and demonstration that SNP alleles are significantly more frequent in patients than in healthy people. The search for biomedical SNP markers of interest can be accelerated by computer-based analysis of hundreds of millions of SNPs in the 1000 Genomes project because of selection of the most meaningful candidate SNP markers and elimination of neutral SNPs.

RESULTS

We cross-validated the output of two computer-based methods: DNA sequence analysis using Web service SNP_TATA_Comparator and keyword search for articles on comorbidities of obesity. Near the sites binding to TATA-binding protein (TBP) in human gene promoters, we found 22 obesity-related candidate SNP markers, including rs10895068 (male breast cancer in obesity); rs35036378 (reduced risk of obesity after ovariectomy); rs201739205 (reduced risk of obesity-related cancers due to weight loss by diet/exercise in obese postmenopausal women); rs183433761 (obesity resistance during a high-fat diet); rs367732974 and rs549591993 (both: cardiovascular complications in obese patients with type 2 diabetes mellitus); rs200487063 and rs34104384 (both: obesity-caused hypertension); rs35518301, rs72661131, and rs562962093 (all: obesity); and rs397509430, rs33980857, rs34598529, rs33931746, rs33981098, rs34500389, rs63750953, rs281864525, rs35518301, and rs34166473 (all: chronic inflammation in comorbidities of obesity). Using an electrophoretic mobility shift assay under nonequilibrium conditions, we empirically validated the statistical significance (α < 0.00025) of the differences in TBP affinity values between the minor and ancestral alleles of 4 out of the 22 SNPs: rs200487063, rs201381696, rs34104384, and rs183433761. We also measured half-life (t1/2), Gibbs free energy change (ΔG), and the association and dissociation rate constants, ka and kd, of the TBP-DNA complex for these SNPs.

CONCLUSIONS

Validation of the 22 candidate SNP markers by proper clinical protocols appears to have a strong rationale and may advance postgenomic predictive preventive personalized medicine.

PC-TraFF: identification of potentially collaborating transcription factors using pointwise mutual information

Background

Transcription factors (TFs) are important regulatory proteins that govern transcriptional regulation. Today, it is known that in higher organisms different TFs have to cooperate rather than acting individually in order to control complex genetic programs. The identification of these interactions is an important challenge for understanding the molecular mechanisms of regulating biological processes. In this study, we present a new method based on pointwise mutual information, PC-TraFF, which considers the genome as a document, the sequences as sentences, and TF binding sites (TFBSs) as words to identify interacting TFs in a set of sequences.

Results

To demonstrate the effectiveness of PC-TraFF, we performed a genome-wide analysis and a breast cancer-associated sequence set analysis for protein coding and miRNA genes. Our results show that in any of these sequence sets, PC-TraFF is able to identify important interacting TF pairs, for most of which we found support by previously published experimental results. Further, we made a pairwise comparison between PC-TraFF and three conventional methods. The outcome of this comparison study strongly suggests that all these methods focus on different important aspects of interaction between TFs and thus the pairwise overlap between any of them is only marginal.

Conclusions

In this study, adopting the idea from the field of linguistics in the field of bioinformatics, we develop a new information theoretic method, PC-TraFF, for the identification of potentially collaborating transcription factors based on the idiosyncrasy of their binding site distributions on the genome. The results of our study show that PC-TraFF can succesfully identify known interacting TF pairs and thus its currently biologically uncorfirmed predictions could provide new hypotheses for further experimental validation. Additionally, the comparison of the results of PC-TraFF with the results of previous methods demonstrates that different methods with their specific scopes can perfectly supplement each other. Overall, our analyses indicate that PC-TraFF is a time-efficient method where its algorithm has a tractable computational time and memory consumption.

The PC-TraFF server is freely accessible at http://pctraff.bioinf.med.uni-goettingen.de/

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0827-2) contains supplementary material, which is available to authorized users.

Exploring features and function of Ss-riok-3, an enigmatic kinase gene from Strongyloides stercoralis

Background

Right open reading frame protein kinase 3 (RIOK-3) belongs to the atypical kinase family. Unlike the other two members, RIOK-1 and RIOK-2, which are conserved from Archaea to humans, RIOK-3 occurs only in multicellular organisms. Studies on HeLa cells indicate that human RIOK-3 is a component of the 40S small ribosome subunit and supports cancer cell growth and survival. However, almost nothing is known about the function of RIOK-3. We explored the functional role of RIOK-3 encoding gene from Strongyloides stercoralis, a parasitic nematode of humans and dogs.

Methods

To analyze the gene and promoter structure of Ss-riok-3, RACE-PCR and Genome-walker PCR were performed to isolate the full length cDNA, gDNA and promoter region of Ss-riok-3. RNA-seq was conducted to assess the transcript abundance of Ss-riok-3 in different stages of S. stercoralis. Transgenesis was employed to determine the anatomic expression patterns of Ss-riok-3.

Results

The RIOK-3 protein-encoding gene (designated Ss-riok-3) of S. stercoralis was characterized. The full-length complementary and genomic DNAs of the RIOK-3 encoding gene (riok-3) were isolated from this nematode. The cDNA of Ss-riok-3 is 1,757 bp in length, including a 23 bp 5’-UTR, a 36 bp 3’-UTR and a 1,698 bp coding region encoding a protein of 565 amino acids (aa) containing a RIO kinase domain. RNA sequencing (RNA-seq) analysis revealed that Ss-riok-3 is transcribed in all developmental stages of S. stercoralis assessed, with transcripts being particularly abundant in parasitic females. Gene structure analysis revealed that Ss-riok-3 contains no intron. The putative promoter contains conserved promoter elements, including four TATA, two GATA, one inverse GATA and one inverse CAAT boxes. The promoter of Ss-riok-3 drives GFP expression in the head neuron, intestine and body wall muscle of transgenic S. stercoralis larvae, and the TATA boxes present in the 3’-UTR of the gene immediately upstream of Ss-riok-3 initiate transcription.

Conclusions

The characterization of the RIOK-3 encoding gene from S. stercoralis provides a sound foundation for investigating in detail its function in the development and reproduction of this important pathogen.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-014-0561-z) contains supplementary material, which is available to authorized users.

CisMiner: genome-wide in-silico cis-regulatory module prediction by fuzzy itemset mining

Eukaryotic gene control regions are known to be spread throughout non-coding DNA sequences which may appear distant from the gene promoter. Transcription factors are proteins that coordinately bind to these regions at transcription factor binding sites to regulate gene expression. Several tools allow to detect significant co-occurrences of closely located binding sites (cis-regulatory modules, CRMs). However, these tools present at least one of the following limitations: 1) scope limited to promoter or conserved regions of the genome; 2) do not allow to identify combinations involving more than two motifs; 3) require prior information about target motifs. In this work we present CisMiner, a novel methodology to detect putative CRMs by means of a fuzzy itemset mining approach able to operate at genome-wide scale. CisMiner allows to perform a blind search of CRMs without any prior information about target CRMs nor limitation in the number of motifs. CisMiner tackles the combinatorial complexity of genome-wide cis-regulatory module extraction using a natural representation of motif combinations as itemsets and applying the Top-Down Fuzzy Frequent- Pattern Tree algorithm to identify significant itemsets. Fuzzy technology allows CisMiner to better handle the imprecision and noise inherent to regulatory processes. Results obtained for a set of well-known binding sites in the S. cerevisiae genome show that our method yields highly reliable predictions. Furthermore, CisMiner was also applied to putative in-silico predicted transcription factor binding sites to identify significant combinations in S. cerevisiae and D. melanogaster, proving that our approach can be further applied genome-wide to more complex genomes. CisMiner is freely accesible at: http://genome2.ugr.es/cisminer. CisMiner can be queried for the results presented in this work and can also perform a customized cis-regulatory module prediction on a query set of transcription factor binding sites provided by the user.

Toward understanding the functional role of Ss-RIOK-1, a RIO protein kinase-encoding gene of Strongyloides stercoralis

BACKGROUND

Some studies of Saccharomyces cerevisiae and mammals have shown that RIO protein kinases (RIOKs) are involved in ribosome biogenesis, cell cycle progression and development. However, there is a paucity of information on their functions in parasitic nematodes. We aimed to investigate the function of RIOK-1 encoding gene from Strongyloides stercoralis, a nematode parasitizing humans and dogs.

METHODOLOGY/PRINCIPAL FINDINGS

The RIOK-1 protein-encoding gene Ss-riok-1 was characterized from S. stercoralis. The full-length cDNA, gDNA and putative promoter region of Ss-riok-1 were isolated and sequenced. The cDNA comprises 1,828 bp, including a 377 bp 5'-UTR, a 17 bp 3'-UTR and a 1,434 bp ORF encoding a protein of 477 amino acids containing a RIOK-1 signature motif. The genomic sequence of the Ss-riok-1 coding region is 1,636 bp in length and has three exons and two introns. The putative promoter region comprises 4,280 bp and contains conserved promoter elements, including four CAAT boxes, 12 GATA boxes, eight E-boxes (CANNTG) and 38 TATA boxes. The Ss-riok-1 gene is transcribed throughout all developmental stages with the highest transcript abundance in the infective third-stage larva (iL3). Recombinant Ss-RIOK-1 is an active kinase, capable of both phosphorylation and auto-phosphorylation. Patterns of transcriptional reporter expression in transgenic S. stercoralis larvae indicated that Ss-RIOK-1 is expressed in neurons of the head, body and tail as well as in pharynx and hypodermis.

CONCLUSIONS/SIGNIFICANCE

The characterization of the molecular and the temporal and spatial expression patterns of the encoding gene provide first clues as to functions of RIOKs in the biological processes of parasitic nematodes.