Inferring condition-specific targets of human tf-tf complexes using chip-seq data _ bmc genomics _ full text

Transcription factors (TFs) interact with one another and with their co-factors to form TF complexes, with constituents that vary in different cell types or under different cellular conditions. 10k database These TF complexes regulate different sets of target genes to determine cellular state [ 1]. Data recovery software mac Given the high variability of TF complex composition, it is critical to examine TF complexes and their target genes in a condition-specific manner to accurately reveal their regulatory activities.

TF-TF interactions can be experimentally identified using electrophoretic mobility shift assays (EMSAs), X-ray crystallography, immunoprecipitation, yeast two-hybrid systems, mammalian two-hybrid systems and luciferase assays. Cost of data recovery from hard drive Because of technical limitations, most human TF-TF interactions represent potentials of physical binding rather than physiological interactions under specific conditions.

S cerevisiae database For example, Ravasi et al. Snl database developed a database of physical TF-TF interactions using a mammalian two-hybrid system in hamster cells [ 2], in which approximately 1,600 TF-TF interactions were identified among human and mouse TFs. Database 4500 However, these data merely indicated the potential interactions amid the pertinent TF pairs in the experimental model. Data recovery miami fl These data did not reflect the condition-specific target genes of TF-TF complexes, which are essential for understanding their regulatory mechanisms.

Chromatin immunoprecipitation followed by DNA microarray or high-throughput sequencing (ChIP-chip/ChIP-seq) techniques are powerful for identifying TF binding sites. Data recovery sd card These approaches discover binding “peaks”, i.e. Uottawa database regions of chromatin and the corresponding sequences enriched for TFs. Top 10 data recovery software free download Consequently, condition-specific TF peaks can be identified by altering cellular conditions, which further reveal motifs recognized by DNA-binding TFs or their co-regulatory counterparts. Database query optimization For example, the CENTDIST web server identifies co-regulatory TFs in complexes by investigating TF motifs enriched in the ChIP-seq peaks for a TF [ 3]. Qmobile data recovery In addition, the spacing of TF-pair binding motifs is often inflexible [ 4], allowing the SpaMo algorithm to identify TF-TF pairs by interrogating motif spacings [ 5]. No 1 data recovery software However, in light of many binding peaks having been shown to be non-functional [ 6, 7], such methods may not be informative for identifying functional binding sites.

Thanks to a comprehensive TF motif database, CST is the first pipeline that uses data from a single ChIP-seq experiment to predict both TF partners and their target genes. Data recovery iphone free Chen et al. Database 11g predicted TF complexes and their target genes using yeast TF ChIP-chip data [ 8], but their method required paired ChIP-chip data: one assay to determine the binding sites of a primary TF and the other the binding sites of a partner TF. Data recovery thumb drive Therefore, we believe CST will lower the cost of using ChIP-seq for these purposes and be valuable to the community.

CST uses ChIP-seq data after immunoprecipitation of the primary TF along with a database containing known TF binding sequence motifs to identify partner TFs. Data recovery hardware tools Finally, we integrated the predicted results and constructed a database called DBCST. Os x data recovery DBCST allows users to upload their own ChIP-seq data and analyse them for TF complexes and their regulatory targets. R studio data recovery download DBCST is freely available at Data recovery western digital Results

Using high-confidence criteria (see Methods and Fig. Top 5 data recovery software 1); our pipeline identified 13,504 relationships between 2,392 predicted TF complexes and 3,272 predicted target genes. Data recovery mac By contrast, when using low-confidence criteria (see Methods and Fig. Database website 1), we identified 127,994 relationships. Data recovery denver In addition, the correlation between gene expression and TF binding was highly significant ( P = 2.2× 10 −16, see Additional file 1 Supplementary Methods) and the likelihood of a TF complex near transcriptionally active genes showed that the TF complexes are most likely located -1kbp to 0.5kbp around TSS (Fig. Data recovery galaxy s4 S1). R studio data recovery free full version The numbers of ChIP-seq datasets for each cell line used in our database are provided in Additional file 1: Table S1. Data recovery equipment The high-confidence and low-confidence target genes of the predicted USF2-NFYA complex using the ChIP-seq data for USF2 in K562 cells are partially listed in Fig. Database primary key S2. Database link oracle Brief instructions for users and a detailed tutorial of DBCST can be found in the Additional file 1 Supplementary Information and on the web page, respectively.

Overview of the CST pipeline. 7 data recovery key a Given a ChIP-seq sample, primary TF target genes are identified using the TIP algorithm. Database manager salary b For motif discovery, the binding peaks on target gene promoters are first identified using the narrow peaks located in the putative promoters of the TIP-predicted target genes. Database processing c For binding motif discovery, the binding peaks on the target genes are selected, and MEME is used to discover primary TF binding motifs. Database xcode d FIMO is used to locate the primary TF binding motifs in the binding peaks of the primary TF target genes. Database administrator salary e Using the binding motifs generated from MEME for all TFs and adding in motifs from the JASPAR database, SpaMo is used to search for binding motifs of potential partner TFs and to analyse their statistical significances based on their spacings. Data recovery iphone 4s f The resulting predicted TF complexes and their target genes are reported with GO enrichment results. Fundamentals of database systems Target genes are stratified into high- and low-confidence groups based on the SpaMo-calculated statistical significance of their TF complex binding motif spacing Validation of CST-predicted TF complexes by comparison to other databases

Comparison and validation of CST-predicted TF complexes. Database er diagram In ( a) and ( b), we compared the presence of CST-predicted TF complexes relative to SpaMo-predicted TF complexes in an external, experimentally derived database of TF complexes to demonstrate the performance of CST. Data recovery tools linux a The x-axis represents the TF complexes ordered by their SpaMo-calculated p-values (from most to least significant), and the y-axis represents the enrichment ratio. Data recovery wizard for mac The best enrichment ratios of CST and SpaMo were approximately 32 and 18, respectively. Database etl CST has greater enrichment than SpaMo across all p-values. Database lock The enrichment ratio was calculated as the ratio of predicted TF complexes in the database relative to the number of 1000 randomly generated TF complexes in the database. Data recovery reviews b Similar to ( a), the top N of TF complexes calculated by p-values are used. Database d b The best enrichment ratios of CST and SpaMo were approximately 32 and 14, respectively. Ads b database CST demonstrated greater enrichment than SpaMo across the entire N range. Database denormalization In ( c) and ( d), we validated the condition-specific TF-TF interactions using TRMs to demonstrate the condition-specific accuracy. Pokemon y database The nodes are TFs, and the edges indicate interactions. Data recovery icon GATA2 and TAL1 (grey colour) are present in both TRM and ENCODE ChIP-seq data. Fda 510 k database Combined GATA2 and TAL1 TRMs in HSCs contained 16 TF-TF interactions ( c), whereas 10 predicted TF-TF interactions were identified in CST using GATA2 and TAL1 ChIP-seq data in K562 cells ( d). Google hacking database The bold edges indicate TF-TF interactions common between TRMs and CST. Database concepts 6th edition pdf Four significant TF complexes between TRMs and CST are indicated with bold edges ( P = 3*10 −4; Fisher’s exact test), suggesting the consistency of TRM and CST

For the first validation, we compared the degree of enrichment for the CST-predicted TF complexes present in an empirically determined TF complex database (see Methods) against that of TF complexes created randomly among potential TF pairs in the CST pipeline (i.e. Data recovery utility a background). Data recovery from hard drive We also included TF complexes predicted by SpaMo [ 5] for a fair comparison (Fig. Database objects 2a and b). Data recovery raid 5 After ordering the TF complexes by p-values in an ascending manner and calculating enrichment ratios, we discovered that TF complexes identified by CST were highly enriched compared with those by SpaMo. Database architect The peak enrichment for CST was approximately 32 (at the 40% confidence decile), whereas that for SpaMo was approximately 18 (at the 60% decile). Data recovery options These results indicated that Target Identification from Profiles (TIP) method [ 9] together with SpaMo, equivalent to CST, significantly improved the prediction of TF complexes over the use of SpaMo alone. Database jobs Similar results are suggested in Fig. H2 database file 2b, in which the top N of TF complexes are selected.

For the second validation, we compared the CST-predicted TF complexes to the TF-specific transcriptional regulatory modules (TRMs) in haematopoietic stem cells (HSCs) proposed by Diez et al. R studio data recovery serial key (see Methods) [ 10]. Database query languages Briefly, Diez et al. P d database used ChIP-seq to identify condition-specific binding sites. Database 101 After scanning enriched motifs in these binding sites and integrating protein-protein interaction data, the authors discovered condition-specific TRMs for each immunoprecipitated TF. M power database Although there were 9 TRMs in HSCs (ERG, FLI1, GATA2, GFI1B, LMO2, MEIS1, SFPI1, RUNX1 and TAL1), two TRMs were observed in CST (including GATA2 and TAL1 in K562 cells). Data recovery from external hard drive Four significant TF complexes were observed in both TRM and CST (3 in the TAL1 and 1 in the GATA2 datasets; P = 3*10 −4; Fisher’s exact test) after further comparisons for the TRM-predicted TF complexes (Fig. Database join types 2c) and for the CST-predicted TF complexes (Fig. Section 8 database 2d). Icd 9 database In order to compare CST and SpaMo predictions, Additional file 1: Figure S3 shows SpaMo-predicted TF complexes from GATA2 and TAL1 ChIP-seq data in K562 cells. Database xampp The result of CST is more significant than the SpaMo prediction (P = 0.02; Fisher’s exact test). Database administrator jobs Notably, the predicted motif spacings of TAL1-STAT1 and TAL1-GATA1 interactions in CST are 85 and 23 bps, respectively (Additional file 1: Table S2). Data recovery joondalup According to a previous study claiming that a TF-TF interaction is likely indirect if the spacing of the interaction exceeds 30 bps [ 11], we speculated that interactions between TAL1 and STAT1 are indirect, whereas between TAL1 and GATA1 are direct. Database of genomic variants This result is consistent with the TRM database, in which TAL1 indirectly interacts with STAT1 by the WDR5 bridge protein, whereas TAL1 directly interacts with GATA1. Database viewer Validation of CST-predicted target genes using ChIP-qPCR and RT-PCR

To experimentally validate the interactions between the predicted USF2-NFYA TF complex and its targets, we used ChIP-qPCR in K562 and HeLa cells for in vitro validation. H data recovery registration code free download For qPCR amplification targets, we selected the promoters of high-confidence target genes (EIF4E and GLYR1), a low-confidence target gene (HoxB7) and HoxB4 (a positive control according to Zhu et al.). Database hardware To ensure PCR accuracy, we designed two primer sets for HoxB7 (see Additional file 1: Table S3). Database roles Relative to IgG-IP normalization, the qPCR fold enrichment of all targets was large and highly significant for both NFYA (Fig. B tree database management system 3a) and USF2 (Fig. Database file 3b) in both K562 and HeLa cell lines. Data recovery near me In addition, the regular PCR amplification from USF2-IP and NFYA-IP DNA also demonstrated the interaction between the USF2-NFYA complex and the promoter of the target genes (Additional file 1: Fig. Database job description S4). Data recovery 94fbr Although these ChIPs against USF2 and NFYA were independent of one another, the results supported the conclusion that both TFs bind to the same target sequences on target genes predicted in CST.

ChIP-seq/ChIP-chip techniques are powerful methods for identifying TF binding sites. Database foreign key However, these approaches currently are prone to a high false positive rate in predicting target genes [ 6, 7]. Database as a service Therefore, we employed TIP [ 9] to remove binding peaks not located in predicted target genes and obtain better results than SpaMo [ 5] (Fig. Iphone 6 data recovery 2a and b). Database google drive Due to CST predicting TF complexes based on SpaMo, CST and SpaMo have similar curve treads in Fig. Data recovery geek squad 2a. Database recovery pending Other than TIP, many other methods exist for scoring target genes, such as TFAS [ 15] and ClosestGene [ 16], which can also be used to predict rankings. Data recovery prices These methods all require binding peaks from a peak-calling algorithm [ 17– 19]. Database sharding Notably, the number of binding peaks is sensitive to the parameters of the peak-calling algorithm and thus can affect the accuracy and consistency of target gene prediction.

A previous study showed that USF2 and NFYA form TF complexes on the HoxB4 promoter in the K562 cell line [ 12], but this observation was not detected by CST. Database keys with example Our further scrutiny found that, among 9,428 narrow peaks from ENCODE K562 USF2 ChIP-seq data [ 20], there are no narrow peaks on the HoxB4 putative promoter (+/-3kbp around the TSS). Data recovery xfs We postulated that this is why CST was not able to detect it. Database management systems 3rd edition To prevent such incidents from occurring, we suggest that the criteria for calling narrow peaks should be loosened. Database engineer salary In CST, we used SpaMo to facilitate the prediction of TF complexes. Jstor database SpaMo can predict whether two TFs belong to the same complex [ 5], but cannot confirm whether the interactions of the TF pair are direct or indirect. E m database For example, the different motif spacings of the USF2-NFYA complex on different promoters (HoxB7, 21 bps; and HoxB4, 10 bps [ 12]) in K562 cells may arise from different interactions or conditions. Data recovery richmond va USF2 and NFYA may interact indirectly when binding to HoxB7 but directly when binding to HoxB4, indicating that binding to HoxB7 may require more protein components than binding to HoxB4. Data recovery software This rationale may explain the observation in our qPCR experiments that the USF2-NFYA complex exhibited a higher binding affinity and enrichment on the HoxB7 promoter than on the HoxB4 promoter (Fig. Data recovery advisor 3a and b).