Systematic identification and annotation of multiple-variant compound effects at transcription factor binding sites in human genome

Understanding the functional effects of genetic variants is crucial in modern genomics and genetics. Transcription factor binding sites （TFBSs） are one of the most important cis-regulatory elements. While multiple tools have been developed to assess functional effects of genetic variants at TFBSs, they usually assume that each variant works in isolation and neglect the potential ＂interference＂ among multiple variants within the same TFBS. In this study, we presented COPE-TFBS （Context-Oriented Predictor for variant Effect on Transcription Factor Binding Site）, a novel method that considers sequence context to accurately predict variant effects on TFBSs. We systematically re-analyzed the sequencing data from both the 1000 Genomes Project and the Genotype-Tissue Expression （GTEx） Project via COPE-TFBS, and identified numbers of novel TFBSs, transformed TFBSs and discordantly annotated TFBSs resulting from multiple variants, further highlighting the necessity of sequence context in accurately annotating genetic variants.

Structure-Based Prediction of Transcription Factor Binding Sites

Transcription Factors（TFs） are a very diverse family of DNA-binding proteins that play essential roles in the regulation of gene expression through binding to specific DNA sequences. They are considered as one of the prime drug targets since mutations and aberrant TF-DNA interactions are implicated in many diseases.Identification of TF-binding sites on a genomic scale represents a critical step in delineating transcription regulatory networks and remains a major goal in genomic annotations. Recent development of experimental high-throughput technologies has provided valuable information about TF-binding sites at genome scale under various physiological and developmental conditions. Computational approaches can provide a cost-effective alternative and complement the experimental methods by using the vast quantities of available sequence or structural information. In this review we focus on structure-based prediction of transcription factor binding sites. In addition to its potential in genomescale predictions, structure-based approaches can help us better understand the TF-DNA interaction mechanisms and the evolution of transcription factors and their target binding sites. The success of structure-based methods also bears a translational impact on targeted drug design in medicine and biotechnology.

TrFAST: A Tool to Predict Signaling Pathway-specific Transcription Factor Binding Sites

Recent advances in the development of high-throughput tools have significantly revolutionized our understanding of molecular mech- anisms underlying normal and dysfunctional biological processes. Here we present a novel computational tool, transcription factor search and analysis tool （TrFAST）, which was developed for the in silico analysis of transcription factor binding sites （TFBSs） of sig- naling pathway-specific TFs. TrFAST facilitates searching as well as comparative analysis of regulatory motifs through an exact pattern matching algorithm followed by the graphical representation of matched binding sites in multiple sequences up to 50 kb in length. TrFAST is proficient in reducing the number of comparisons by the exact pattern matching strategy. In contrast to the pre-existing tools that find TFBS in a single sequence, TrFAST seeks out the desired pattern in multiple sequences simultaneously. It counts the GC con- tent within the given multiple sequence data set and assembles the combinational details of consensus sequence（s） located at these regions, thereby generating a visual display based on the abundance of unique pattern. Comparative regulatory region analysis of multi- ple orthologous sequences simultaneously enhances the features of TrFAST and provides a significant insight into study of conservation of non-coding cis-regulatory elements. TrFAST is freely available at http：//www.fi-pk.com/trfast.html.

Nucleosomal Context of Binding Sites Influences Transcription Factor Binding Affinity and Gene Regulation

Transcription factor （TF） binding to its DNA target site plays an essential role in gene regulation. The location, orientation and spacing of transcription factor binding sites （TFBSs） also affect regulatory function of the TF. However, how nucleosomal context of TFBSs influences TF binding and subsequent gene regulation remains to be elucidated. Using genome-wide nucleosome positioning and TF binding data in budding yeast, we found that binding affinities of TFs to DNA tend to decrease with increasing nucleosome occupancy of the associated binding sites. We further demonstrated that nucleosomal context of binding sites is correlated with gene regulation of the corresponding TF. Nucleosome-depleted TFBSs are linked to high gene activity and low expression noise, whereas nucleosome-covered TFBSs are associated with low gene activity and high expression noise. Moreover, nucleosome-covered TFBSs tend to disrupt coexpression of the corresponding TF target genes. We conclude that nucleosomal context of binding sites influences TF binding affinity, subsequently affecting the regulation of TFs on their target genes. This emphasizes the need to include nucleosomal context of TFBSs in modeling gene regulation.

Expression of COX-2 and transcription factor CCAAT enhancer binding proteinβin refractory sinusitis with nasal polyps and its significance

Objective To study the expression and significance of COX-2 and C/EBP-βin refractory sinusitis with nasal polyps,and to explore the relationship between them and the recurrence of sinusitis with nasal polyps.Methods The protein expression of COX-2 and C/EBP-βin 20 cases of refractory sinusitis with nasal polyps,20 cases of sinusitis with nasal polyps and 20 cases of normal nasal mucosa were detected by western blot,and the relationship between the two was compared.Results The expression levels of COX-2 and C/EBP-βin refractory sinusitis with nasal polyps were significantly different from those in refractory sinusitis with nasal polyps(P<0.05);The expression levels of COX-2 and C/EBP-βin sinusitis tissues with nasal polyps were significantly different from those in normal nasal mucosa tissues(P<0.05);The expression levels of COX-2 and C/EBP-βin each group were significantly correlated(P<0.05).Conclusions The high expression of COX-2 and C/EBP-βmay be closely related to postoperative recurrence of sinusitis patients with nasal polyps.Both may be used as objective indicators to judge the postoperative follow-up and recurrence tendency of patients with sinusitis with nasal polyps..

A combined statistical model for multiple motifs search

Transcription factor binding sites （TFBS） play key roles in genebior 6.8 wavelet expression and regulation. They are short sequence segments with definite structure and can be recognized by the corresponding transcription factors correctly. From the viewpoint of statistics, the candidates of TFBS should be quite different from the segments that are randomly combined together by nucleotide. This paper proposes a combined statistical model for finding over- represented short sequence segments in different kinds of data set. While the over-represented short sequence segment is described by position weight matrix, the nucleotide distribution at most sites of the segment should be far from the background nucleotide distribution. The central idea of this approach is to search for such kind of signals. This algorithm is tested on 3 data sets, including binding sites data set of cyclic AMP receptor protein in E.coli, PlantProm DB which is a non-redundant collection of proximal promoter sequences from different species, collection of the intergenic sequences of the whole genome of E.Coli. Even though the complexity of these three data sets is quite different, the results show that this model is rather general and sensible.

Bioinformatics Analysis of the Human TCF7L2 Gene Promoter Region

[Objectives]This study was conducted to investigate characteristics of the human TCF7 L2 gene promoter.[Methods]The 2000 bp sequence of the 5’regulatory region of the human TCF7 L2 gene was obtained from the UCSC genome database.The promoter,transcription factor binding sites,CpG islands,SNPs and so on were analyzed by a variety of online softwares.[Results]The bioinformatics analysis results showed there were at least 5 potential promoters in the positive-sense strand of the 2000 bp sequence,among which-242--192 bp,-853--803 bp might contain core promoters.A TATA box and a CpG island with a length of 499 bp were found.241,944 and 1035(positive-sense strand)transcription factor binding sites were predicted by the AliBaba2.1,PROMO and JASPAR softwares,respectively.207 common transcription factor binding sites in the conserved region of human and mouse homologous TCF7 L2 gene promoter were identified with CONREAL program,involving 66 kinds of transcription factors.Two SNPs were found in the promoter region.[Conclusions]The promoter of the human TCF7 L2 gene was analyzed by bioinformatics,and the promoter characteristics were obtained.

Endoplasmic reticulum stress transducer old astrocyte specifically induced substance contributes to astrogliosis after spinal cord injury

Old astrocyte specifically induced substance （OASIS） is an endoplasmic reticulum （ER） stress transducer specifically expressed in astrocytes and osteoblasts. OASIS regulates the differentiation of neural precursor cells into astrocytes in the central nervous system. This study aimed to elucidate the involvement of ER stress responses stimulated via OASIS in astrogliosis following spinal cord injury. In a mouse model of spinal cord contusion injury, OASIS mRNA and protein expression were evaluated at days 7 and 14. A significant increase in OASIS mRNA on day 7 and an increase in protein on days 7 and 14 was observed in injured spinal cords. Immunostaining on day 7 revealed co-localization of OASIS and astrocytes in the periphery of the injury site. Furthermore, anti-OASIS small interfering RNA （siRNA） was injected at the injury sites on day 5 to elucidate the function of OASIS. Treatment with anti-OASIS siRNA caused a significant decrease in OASIS mRNA on day 7 and protein on days 7 and 14, and was associated with the inhibition of astrogliosis and hindlimb motor function recovery. Results of our study show that OASIS expression synchronizes with astrogliosis and is functionally associated with astrogliosis after spinal cord injury.

Edaravone protects against oxygen-glucose-serum deprivation/restoration-induced apoptosis in spinal cord astrocytes by inhibiting integrated stress response

We previously found that oxygen-glucose-serum deprivation/restoration（OGSD/R） induces apoptosis of spinal cord astrocytes, possibly via caspase-12 and the integrated stress response, which involves protein kinase R-like endoplasmic reticulum kinase（PERK）, eukaryotic initiation factor 2-alpha（eIF2α） and activating transcription factor 4（ATF4）. We hypothesized that edaravone, a low molecular weight, lipophilic free radical scavenger, would reduce OGSD/R-induced apoptosis of spinal cord astrocytes. To test this, we established primary cultures of rat astrocytes, and exposed them to 8 hours/6 hours of OGSD/R with or without edaravone（0.1, 1, 10, 100 μM） treatment. We found that 100 μM of edaravone significantly suppressed astrocyte apoptosis and inhibited the release of reactive oxygen species. It also inhibited the activation of caspase-12 and caspase-3, and reduced the expression of homologous CCAAT/enhancer binding protein, phosphorylated（p）-PERK, p-eIF2α, and ATF4. These results point to a new use of an established drug in the prevention of OGSD/R-mediated spinal cord astrocyte apoptosis via the integrated stress response.

DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers

The establishment of a landscape of enhancers across human cells is crucial to deciphering the mechanism of gene regulation,cell differentiation,and disease development.High-throughput experimental approaches,which contain successfully reported enhancers in typical cell lines,are still too costly and time-consuming to perform systematic identification of enhancers specific to different cell lines.Existing computational methods,capable of predicting regulatory elements purely relying on DNA sequences,lack the power of cell line-specific screening.Recent studies have suggested that chromatin accessibility of a DNA segment is closely related to its potential function in regulation,and thus may provide useful information in identifying regulatory elements.Motivated by the aforementioned understanding,we integrate DNA sequences and chromatin accessibility data to accurately predict enhancers in a cell line-specific manner.We proposed Deep CAPE,a deep convolutional neural network to predict enhancers via the integration of DNA sequences and DNase-seq data.Benefitting from the well-designed feature extraction mechanism and skip connection strategy,our model not only consistently outperforms existing methods in the imbalanced classification of cell line-specific enhancers against background sequences,but also has the ability to self-adapt to different sizes of datasets.Besides,with the adoption of autoencoder,our model is capable of making cross-cell line predictions.We further visualize kernels of the first convolutional layer and show the match of identified sequence signatures and known motifs.We finally demonstrate the potential ability of our model to explain functional implications of putative disease-associated genetic variants and discriminate diseaserelated enhancers.The source code and detailed tutorial of Deep CAPE are freely available at https://github.com/Shengquan Chen/DeepCAPE.

Identification of SNPs involved in regulating a novel alternative transcript of P450 CYP6ER1 in the brown planthopper

Cytochrome P450-mediated metabolic resistance is one of the major mecha- nisms involved in insecticide resistance. Although the up-regulation of cytochrome P450 plays a vital role in insecticide metabolism, the molecular basis for the transcriptional regulation of cytochrome P450 remains largely unknown. The P450 gene CYP6ERI, has been reported to confer imidacloprid resistance to the brown planthopper, Nilaparvata lugens. Here, we identified a novel alternative transcript of CYP6ER1 （transcript A2） that had different expression patterns between resistant and susceptible populations, and was more stable after insecticide induction. The promoter of this transcript was sequenced and multiple single nucleotide polymorphisms （SNPs） were detected in individuals from susceptible and resistant field-collected populations. Resistant alleles of four SNPs were found to significantly enhance the promoter activity of the CYP6ER1 transcript A2. Elec- trophoretic mobility shift assays （EMSAs） revealed that these SNPs might regulate the binding of transcription factors to the promoter. Our findings provide novel evidence re- garding the transcriptional regulation of a metabolic resistance-related gene and may be useful to understand the resistance mechanism ofN. lugens in the field.

Evolutionary direction of processed pseudogenes

While some pseudogenes have been reported to play important roles in gene regulation, little is known about the possible relationship between pseudogene functions and evolutionary process of pseudogenes, or about the forces responsible for the pseudogene evolution. In this study, we characterized human processed pseudogenes in terms of evolutionary dynamics. Our results show that pseudogenes tend to evolve toward: lower GC content, strong dinucleotide bias, reduced abundance of transcription factor binding motifs and short palindromes, and decreased ability to form nucleosomes. We explored possible evolutionary forces that shaped the evolution pattern of pseudogenes, and concluded that mutations in pseudogenes are likely determined, at least partially, by neighbor-dependent mutational bias and recombination-associated selection.

Identification of Conserved Regulatory Elements in Mammalian Promoter Regions:A Case Study Using the PCK1 Promoter

A systematic phylogenetic footprinting approach was performed to identify conserved transcription factor binding sites （TFBSs） in mammalian promoter regions using human, mouse and rat sequence alignments. We found that the score distributions of most binding site models did not follow the Gaussian distribution required by many statistical methods. Therefore, we performed an empirical test to establish the optimal threshold for each model. We gauged our computational predictions by comparing with previously known TFBSs in the PCK1 gene promoter of the cytosolic isoform of phosphoenolpyruvate carboxykinase, and achieved a sensitivity of 75% and a specificity of approximately 32% Almost all known sites overlapped with predicted sites, and several new putative TFBSs were also identified. We validated a predicted SP1 binding site in the control of PCK1 transcription using gel shift and reporter assays. Finally, we applied our computational approach to the prediction of putative TFBSs within the promoter regions of all available RefSeq genes. Our full set of TFBS predictions is freely available at http：//bfgl.anri.barc.usda.gov/tfbsConsSites.

Differential signaling regulatory networks governing hormone refractory prostate cancers

To understand the organization of the biological networks that might potentially govern the pathogenesis of hormone refractory prostate cancer （HRPC）, we investigated the transcriptional circuitry and signaling in androgen-dependent 22Rvl and MDA PCa 2b cells, androgen- and estrogen-dependent LNCaP cells, and androgen-independent DU 145 and PC-3 prostate cancer （PCa） cell lines. We used microarray analyses, quantitative real-time PCR, pathway prediction analyses, and determination of Transcription Factor Binding Site （TFBS） signatures to dissect HRPC regulatory networks. We generated graphical representations of global topology and local network motifs that might be important in prostate carcinogenesis. Many important putative biomarker ＇target hubs＇ were identified in the current study including AP-1, NF-KB, EGFR, ERK1/2, JNK, p38 MAPK, TGF beta, VEGF, PDGF, CD44, Akt, PI3K, NOTCH1, CASP1, MMP2 and AR. Our results suggest that complex cellular events including autoregulation, feedback loops and cross-talk might govern progression from early lesion to clinically diagnosed PCa, as well as metastatic potential of pre-existent high-grade prostate intraepithelial neoplasia （HG-PIN） and/or advancement to HRPC. The identification of TFBS signatures for TCF/LEF, SOX9 and ELK1 in the regulatory elements suggests additional biomarkers for the potential development of chemopreventive/therapeutic strategies against PCa. Taken together, in this study, we have identified putative biomarker ＇target hubs＇ in the architecture of PCa signaling networks, and investigated TFBS signatures that might enhance our understanding of key regulatory nodes in the progression and pathogenesis of HRPC.