Genome-wide maps of rare and atypical UV photoproducts reveal distinct patterns of damage formation and mutagenesis in yeast chromatin.

Ultraviolet (UV) light induces different classes of mutagenic photoproducts in DNA, namely cyclobutane pyrimidine dimers (CPDs), 6-4 photoproducts (6-4PPs), and atypical thymine-adenine photoproducts (TA-PPs). CPD formation is modulated by nucleosomes and transcription factors (TFs), which has important ramifications for Ultraviolet (UV) mutagenesis. How chromatin affects the formation of 6-4PPs and TA-PPs is unclear. Here, we use UV damage endonuclease-sequencing (UVDE-seq) to map these UV photoproducts across the yeast genome. Our results indicate that nucleosomes, the fundamental building block of chromatin, have opposing effects on photoproduct formation. Nucleosomes induce CPDs and 6-4PPs at outward rotational settings in nucleosomal DNA but suppress TA-PPs at these settings. Our data also indicate that DNA binding by different classes of yeast TFs causes lesion-specific hotspots of 6-4PPs or TA-PPs. For example, DNA binding by the TF Rap1 generally suppresses CPD and 6-4PP formation but induces a TA-PP hotspot. Finally, we show that 6-4PP formation is strongly induced at the binding sites of TATA-binding protein (TBP), which is correlated with higher mutation rates in UV-exposed yeast. These results indicate that the formation of 6-4PPs and TA-PPs is modulated by chromatin differently than CPDs and that this may have important implications for UV mutagenesis.

Notch-dependent DNA cis-regulatory elements and their dose-dependent control of C. elegans stem cell self-renewal.

A long-standing biological question is how DNA cis-regulatory elements shape transcriptional patterns during metazoan development. Reporter constructs, cell culture assays and computational modeling have made major contributions to answering this question, but analysis of elements in their natural context is an important complement. Here, we mutate Notch-dependent LAG-1 binding sites (LBSs) in the endogenous Caenorhabditis elegans sygl-1 gene, which encodes a key stem cell regulator, and analyze the consequences on sygl-1 expression (nascent transcripts, mRNA, protein) and stem cell maintenance. Mutation of one LBS in a three-element cluster approximately halved both expression and stem cell pool size, whereas mutation of two LBSs essentially abolished them. Heterozygous LBS mutant clusters provided intermediate values. Our results lead to two major conclusions. First, both LBS number and configuration impact cluster activity: LBSs act additively in trans and synergistically in cis. Second, the SYGL-1 gradient promotes self-renewal above its functional threshold and triggers differentiation below the threshold. Our approach of coupling CRISPR/Cas9 LBS mutations with effects on both molecular and biological readouts establishes a powerful model for in vivo analyses of DNA cis-regulatory elements.

Quantitative model for genome-wide cyclic AMP receptor protein binding site identification and characteristic analysis.

Cyclic AMP receptor proteins (CRPs) are important transcription regulators in many species. The prediction of CRP-binding sites was mainly based on position-weighted matrixes (PWMs). Traditional prediction methods only considered known binding motifs, and their ability to discover inflexible binding patterns was limited. Thus, a novel CRP-binding site prediction model called CRPBSFinder was developed in this research, which combined the hidden Markov model, knowledge-based PWMs and structure-based binding affinity matrixes. We trained this model using validated CRP-binding data from Escherichia coli and evaluated it with computational and experimental methods. The result shows that the model not only can provide higher prediction performance than a classic method but also quantitatively indicates the binding affinity of transcription factor binding sites by prediction scores. The prediction result included not only the most knowns regulated genes but also 1089 novel CRP-regulated genes. The major regulatory roles of CRPs were divided into four classes: carbohydrate metabolism, organic acid metabolism, nitrogen compound metabolism and cellular transport. Several novel functions were also discovered, including heterocycle metabolic and response to stimulus. Based on the functional similarity of homologous CRPs, we applied the model to 35 other species. The prediction tool and the prediction results are online and are available at: https://awi.cuhk.edu.cn/∼CRPBSFinder.

Polymorphisms in transcription factor binding sites and enhancer regions and pancreatic ductal adenocarcinoma risk.

Genome-wide association studies (GWAS) are a powerful tool for detecting variants associated with complex traits and can help risk stratification and prevention strategies against pancreatic ductal adenocarcinoma (PDAC). However, the strict significance threshold commonly used makes it likely that many true risk loci are missed. Functional annotation of GWAS polymorphisms is a proven strategy to identify additional risk loci. We aimed to investigate single-nucleotide polymorphisms (SNP) in regulatory regions [transcription factor binding sites (TFBSs) and enhancers] that could change the expression profile of multiple genes they act upon and thereby modify PDAC risk. We analyzed a total of 12,636 PDAC cases and 43,443 controls from PanScan/PanC4 and the East Asian GWAS (discovery populations), and the PANDoRA consortium (replication population). We identified four associations that reached study-wide statistical significance in the overall meta-analysis: rs2472632(A) (enhancer variant, OR 1.10, 95%CI 1.06,1.13, p = 5.5 × 10-8), rs17358295(G) (enhancer variant, OR 1.16, 95%CI 1.10,1.22, p = 6.1 × 10-7), rs2232079(T) (TFBS variant, OR 0.88, 95%CI 0.83,0.93, p = 6.4 × 10-6) and rs10025845(A) (TFBS variant, OR 1.88, 95%CI 1.50,1.12, p = 1.32 × 10-5). The SNP with the most significant association, rs2472632, is located in an enhancer predicted to target the coiled-coil domain containing 34 oncogene. Our results provide new insights into genetic risk factors for PDAC by a focused analysis of polymorphisms in regulatory regions and demonstrating the usefulness of functional prioritization to identify loci associated with PDAC risk.

Transcription factor binding specificities of the oomycete Phytophthora infestans reflect conserved and divergent evolutionary patterns and predict function.

BACKGROUND: Identifying the DNA-binding specificities of transcription factors (TF) is central to understanding gene networks that regulate growth and development. Such knowledge is lacking in oomycetes, a microbial eukaryotic lineage within the stramenopile group. Oomycetes include many important plant and animal pathogens such as the potato and tomato blight agent Phytophthora infestans, which is a tractable model for studying life-stage differentiation within the group. RESULTS: Mining of the P. infestans genome identified 197 genes encoding proteins belonging to 22 TF families. Their chromosomal distribution was consistent with family expansions through unequal crossing-over, which were likely ancient since each family had similar sizes in most oomycetes. Most TFs exhibited dynamic changes in RNA levels through the P. infestans life cycle. The DNA-binding preferences of 123 proteins were assayed using protein-binding oligonucleotide microarrays, which succeeded with 73 proteins from 14 families. Binding sites predicted for representatives of the families were validated by electrophoretic mobility shift or chromatin immunoprecipitation assays. Consistent with the substantial evolutionary distance of oomycetes from traditional model organisms, only a subset of the DNA-binding preferences resembled those of human or plant orthologs. Phylogenetic analyses of the TF families within P. infestans often discriminated clades with canonical and novel DNA targets. Paralogs with similar binding preferences frequently had distinct patterns of expression suggestive of functional divergence. TFs were predicted to either drive life stage-specific expression or serve as general activators based on the representation of their binding sites within total or developmentally-regulated promoters. This projection was confirmed for one TF using synthetic and mutated promoters fused to reporter genes in vivo. CONCLUSIONS: We established a large dataset of binding specificities for P. infestans TFs, representing the first in the stramenopile group. This resource provides a basis for understanding transcriptional regulation by linking TFs with their targets, which should help delineate the molecular components of processes such as sporulation and host infection. Our work also yielded insight into TF evolution during the eukaryotic radiation, revealing both functional conservation as well as diversification across kingdoms.

Conservation of the Restricted Expression of Brassicaceae Bsister-Like Genes in Seeds Requires a Transposable Element in Arabidopsis thaliana.

Changes in transcription factor binding sites (TFBSs) can alter the spatiotemporal expression pattern and transcript abundance of genes. Loss and gain of TFBSs were shown to cause shifts in expression patterns in numerous cases. However, we know little about the evolution of extended regulatory sequences incorporating many TFBSs. We compare, across the crucifers (Brassicaceae, cabbage family), the sequences between the translated regions of Arabidopsis Bsister (ABS)-like MADS-box genes (including paralogous GOA-like genes) and the next gene upstream, as an example of family-wide evolution of putative upstream regulatory regions (PURRs). ABS-like genes are essential for integument development of ovules and endothelium formation in seeds of Arabidopsis thaliana. A combination of motif-based gene ontology enrichment and reporter gene analysis using A. thaliana as common trans-regulatory environment allows analysis of selected Brassicaceae Bsister gene PURRs. Comparison of TFBS of transcriptionally active ABS-like genes with those of transcriptionally largely inactive GOA-like genes shows that the number of in silico predicted TFBS) is similar between paralogs, emphasizing the importance of experimental verification for in silico characterization of TFBS activity and analysis of their evolution. Further, our data show highly conserved expression of Brassicaceae ABS-like genes almost exclusively in the chalazal region of ovules. The Arabidopsis-specific insertion of a transposable element (TE) into the ABS PURRs is required for stabilizing this spatially restricted expression, while other Brassicaceae achieve chalaza-specific expression without TE insertion. We hypothesize that the chalaza-specific expression of ABS is regulated by cis-regulatory elements provided by the TE.

MAResNet: predicting transcription factor binding sites by combining multi-scale bottom-up and top-down attention and residual network.

Accurate identification of transcription factor binding sites is of great significance in understanding gene expression, biological development and drug design. Although a variety of methods based on deep-learning models and large-scale data have been developed to predict transcription factor binding sites in DNA sequences, there is room for further improvement in prediction performance. In addition, effective interpretation of deep-learning models is greatly desirable. Here we present MAResNet, a new deep-learning method, for predicting transcription factor binding sites on 690 ChIP-seq datasets. More specifically, MAResNet combines the bottom-up and top-down attention mechanisms and a state-of-the-art feed-forward network (ResNet), which is constructed by stacking attention modules that generate attention-aware features. In particular, the multi-scale attention mechanism is utilized at the first stage to extract rich and representative sequence features. We further discuss the attention-aware features learned from different attention modules in accordance with the changes as the layers go deeper. The features learned by MAResNet are also visualized through the TMAP tool to illustrate that the method can extract the unique characteristics of transcription factor binding sites. The performance of MAResNet is extensively tested on 690 test subsets with an average AUC of 0.927, which is higher than that of the current state-of-the-art methods. Overall, this study provides a new and useful framework for the prediction of transcription factor binding sites by combining the funnel attention modules with the residual network.

Developmental and Housekeeping Genes: Two Types of Genetic Organization in the Drosophila Genome.

We developed a procedure for locating genes on Drosophila melanogaster polytene chromosomes and described three types of chromosome structures (gray bands, black bands, and interbands), which differed markedly in morphological and genetic properties. This was reached through the use of our original methods of molecular and genetic analysis, electron microscopy, and bioinformatics data processing. Analysis of the genome-wide distribution of these properties led us to a bioinformatics model of the Drosophila genome organization, in which the genome was divided into two groups of genes. One was constituted by 65, in which the genome was divided into two groups, 62 genes that are expressed in most cell types during life cycle and perform basic cellular functions (the so-called "housekeeping genes"). The other one was made up of 3162 genes that are expressed only at particular stages of development ("developmental genes"). These two groups of genes are so different that we may state that the genome has two types of genetic organization. Different are the timings of their expression, chromatin packaging levels, the composition of activating and deactivating proteins, the sizes of these genes, the lengths of their introns, the organization of the promoter regions of the genes, the locations of origin recognition complexes (ORCs), and DNA replication timings.

Actors with Multiple Roles: Pleiotropic Enhancers and the Paradigm of Enhancer Modularity.

The current paradigm in the field of gene regulation postulates that regulatory information for generating gene expression is organized into modules (enhancers), each containing the information for driving gene expression in a single spatiotemporal context. This modular organization is thought to facilitate the evolution of gene expression by minimizing pleiotropic effects. Here we review recent studies that provide evidence of quite the opposite: (i) enhancers can function in multiple developmental contexts, implying that enhancers can be pleiotropic, (ii) transcription factor binding sites within pleiotropic enhancers are reused in different contexts, and (iii) pleiotropy impacts the structure and evolution of enhancers. Altogether, this evidence suggests that enhancer pleiotropy is pervasive in animal genomes, challenging the commonly held view of modularity.

Genome-Wide Prediction of Transcription Start Sites in Conifers.

The identification of promoters is an essential step in the genome annotation process, providing a framework for gene regulatory networks and their role in transcription regulation. Despite considerable advances in the high-throughput determination of transcription start sites (TSSs) and transcription factor binding sites (TFBSs), experimental methods are still time-consuming and expensive. Instead, several computational approaches have been developed to provide fast and reliable means for predicting the location of TSSs and regulatory motifs on a genome-wide scale. Numerous studies have been carried out on the regulatory elements of mammalian genomes, but plant promoters, especially in gymnosperms, have been left out of the limelight and, therefore, have been poorly investigated. The aim of this study was to enhance and expand the existing genome annotations using computational approaches for genome-wide prediction of TSSs in the four conifer species: loblolly pine, white spruce, Norway spruce, and Siberian larch. Our pipeline will be useful for TSS predictions in other genomes, especially for draft assemblies, where reliable TSS predictions are not usually available. We also explored some of the features of the nucleotide composition of the predicted promoters and compared the GC properties of conifer genes with model monocot and dicot plants. Here, we demonstrate that even incomplete genome assemblies and partial annotations can be a reliable starting point for TSS annotation. The results of the TSS prediction in four conifer species have been deposited in the Persephone genome browser, which allows smooth visualization and is optimized for large data sets. This work provides the initial basis for future experimental validation and the study of the regulatory regions to understand gene regulation in gymnosperms.

Characterization of genetic-origin-dependent monoallelic expression in mouse embryonic stem cells.

Monoallelic gene expression occurs in various mammalian cells and can be regulated genetically, epigenetically and/or stochastically. We identified 145 monoallelically expressed genes (MoEGs), including seven known imprinted genes, in mouse embryonic stem cells (ESCs) derived from reciprocal F1 hybrid blastocysts and cultured in 2i/LIF. As all MoEGs except for the imprinted genes were expressed in a genetic-origin-dependent manner, we focused on this class of MoEGs for mechanistic studies. We showed that a majority of the genetic-origin-dependent MoEGs identified in 2i/LIF ESCs remain monoallelically expressed in serum/LIF ESCs, but become more relaxed or even biallelically expressed upon differentiation. These MoEGs and their regulatory regions were highly enriched for single nucleotide polymorphisms. In addition, some MoEGs were associated with retrotransposon insertions/deletions, consistent with the fact that certain retrotransposons act as regulatory elements in pluripotent stem cells. Interestingly, most MoEGs showed allelic differences in enrichment of histone H3K27me and H3K4me marks, linking allelic epigenetic differences and monoallelic expression. In contrast, there was little or no allelic difference in CpG methylation or H3K9me. Taken together, our study highlights the impact of genetic variation including single nucleotide polymorphisms and retrotransposon insertions/deletions on monoallelic epigenetic marks and expression in ESCs.

The genetic variability, phylogeny and functional significance of E6, E7 and LCR in human papillomavirus type 52 isolates in Sichuan, China.

BACKGROUND: Variations in human papillomavirus (HPV) E6 and E7 have been shown to be closely related to the persistence of the virus and the occurrence and development of cervical cancer. Long control region (LCR) of HPV has been shown multiple functions on regulating viral transcription. In recent years, there have been reports on E6/E7/LCR of HPV-16 and HPV-58, but there are few studies on HPV-52, especially for LCR. In this study, we focused on gene polymorphism of the HPV-52 E6/E7/LCR sequences, assessed the effects of variations on the immune recognition of viral E6 and E7 antigens, predicted the effect of LCR variations on transcription factor binding sites and provided more basic date for further study of E6/E7/LCR in Chengdu, China. METHODS: LCR/E6/E7 of the HPV-52 were amplified and sequenced to do polymorphic and phylogenetic analysis. Sequences were aligned with the reference sequence by MEGA 7.0 to identify SNP. A neighbor-joining phylogenetic tree was constructed by MEGA 7.0, followed by the secondary structure prediction of the related proteins using PSIPRED 4.0. The selection pressure of E6 and E7 coding regions were estimated by Bayes empirical Bayes analysis of PAML 4.9. The HLA class-I and II binding peptides were predicted by the Immune Epitope Database server. The B cell epitopes were predicted by ABCpred server. Transcription factor binding sites in LCR were predicted by JASPAR database. RESULTS: 50 SNP sites (6 in E6, 10 in E7, 34 in LCR) were found. From the most variable to the least variable, the nucleotide variations were LCR > E7 > E6. Two deletions were found between the nucleotide sites 7387-7391 (TTATG) and 7698-7700 (CTT) in all samples. A deletion was found between the nucleotide sites 7287-7288 (TG) in 97.56% (40/41) of the samples. The combinations of all the SNP sites and deletions resulted in 12 unique sequences. As shown in the neighbor-joining phylogenetic tree, except for one belonging to sub-lineage C2, others sequences clustered into sub-lineage B2. No positive selection was observed in E6 and E7. 8 non-synonymous amino acid substitutions (including E3Q and K93R in the E6, and T37I, S52D, Y59D, H61Y, D64N and L99R in the E7) were potential affecting multiple putative epitopes for both CD4+ and CD8+ T-cells and B-cells. A7168G was the most variable site (100%) and the binding sites for transcription factor VAX1 in LCR. In addition, the prediction results showed that LCR had the high probability binding sites for transcription factors SOX9, FOS, RAX, HOXA5, VAX1 and SRY. CONCLUSION: This study provides basic data for understanding the relation among E6/E7/LCR mutations, lineages and carcinogenesis. Furthermore, it provides an insight into the intrinsic geographical relatedness and biological differences of the HPV-52 variants, and contributes to further research on the HPV-52 therapeutic vaccine development.

Identification of promoter response elements that mediate propionate induction of bovine cytosolic phosphoenolpyruvate carboxykinase (PCK1) gene transcription.

Cytosolic phosphoenolpyruvate carboxykinase (PCK1) is a key enzyme for gluconeogenesis that is positively regulated by propionate in bovines at the transcription level. The specific elements that determine propionate responsiveness within the bovine PCK1 promoter are unknown. In silico promoter analysis of the bovine PCK1 gene revealed several clusters of transcription factor binding sites. In the present study, we determined the essentiality of the putative cyclic AMP response element (CRE) at -94 through -87 bp and the 2 putative hepatic nuclear factor 4α (HNF4α) binding elements at +68 through +72 and -1,078 through -1,074, respectively, in mediating bovine PCK1 promoter responses to propionate and other regulators, including butyrate, cyclic AMP (cAMP), and glucocorticoids. The wild-type bovine PCK1 promoter [PCK1(WT)] was ligated to a luciferase reporter gene and transfected into rat hepatoma (H4IIE) cells. Activities of PCK1(WT) were induced by approximately 2-, 2-, 4-, 8-, 9-, 18-, and 16-fold respectively when exposed to cAMP (as 1.0 mM 8-Br-cAMP), 5.0 µM dexamethasone, cAMP + dexamethasone, 2.5 mM propionate, cAMP + propionate, cAMP + dexamethasone + propionate, and 2.5 mM butyrate. Seven mutants lacking either one single site, 2 of the 3 sites, or all 3 sites, generated by site-directed mutagenesis, were tested. Responses to propionate and all other treatments were completely abolished when CRE at -94 through -87 bp and HNF4α at +68 through +72 bp were both deleted. Our data indicate that these 2 regulatory elements act synergistically to mediate the bovine PCK1 promoter responses to propionate as well as butyrate, cAMP, and dexamethasone. The activation of PCK1 through these regulatory elements serves to activate the metabolic potential of bovine toward gluconeogenesis when the primary substrate for gluconeogenesis, propionate, is also present.

Transcriptomic analysis on the promoter regions discover gene networks involving mastitis in cattle.

Mastitis is one of the costliest diseases in dairy farms caused by infection of different microorganisms such as Escherichia coli, Streptococcus uberis and Staphylococcus aureus. Promoters are significantly involved in regulating gene expression and shedding light on the mechanisms of transcriptional regulation in physiological and immunological processes of the infections. Exploiting regulatory elements such as transcription factor binding sites (TFBSs modules) on the promoter region could reveal co-regulated genes, which allow screating regulatory models and executing a cross-sectional analysis on several databases. In this study, the promoter regions of 11 genes associated with contagious mastitis including CCL4, CXCL8, STAT3, IKBKB, MAPK14, NFKBIA, NFKB1, TNF, IL18, IL6, and HCK were investigated to predict the activating regulatory modules on promoters and to discover the key related transcription factors. By exploring the promoter regions, 228 genes were discovered comprising the same transcription factors modules. Out of 228 genes, 36 were validated using five microarray datasets. The promoter research of these genes revealed that as many as 7 down-regulated and 12 up-regulated genes are predictable in the network. The genes whose functions were associated with the initial gene list (11 genes), were identified by DAVID queries with TFBSs models implying that the approach provides a clear image of the underlying regulatory mechanism of gene expression profile and offers a novel approach in designing gene networks in cattle.

Integrative analysis identifies genetic variant modulating MICA expression and altering susceptibility to persistent HBV infection.

BACKGROUND & AIMS: Genome-wide association studies have identified multiple genetic signals associated with the risk of persistent hepatitis B virus (HBV) infection and HBV-related hepatocellular carcinoma. However, the majority of the associated variants may only be markers of functional variants and the underlying biological mechanisms remain elusive. We hypothesized that the functional variants with modulating transcription factor (TF) binding affinity in genome-wide association studies-identified loci may influence the risk of persistent HBV infection in Chinese people. METHODS: A systematic bioinformatics approach was implemented to prioritize potential functional variants that may influence TF binding. A two-stage case-control study, including 1595 HBV-persistent carriers and 1590 subjects with HBV natural clearance, was conducted to examine the associations between candidate variants and susceptibility to persistent HBV infection. Biological assays were carried out to elucidate the underlying mechanism of the associated genetic variants. RESULTS: Twelve candidate variants were identified, and rs2523454 G > A increased the risk of persistent HBV infection (dominant model: ORcombined  = 1.37, 95% CI = 1.19-1.58, P = 1.610 × 10-5 ). Functional assays indicated that the rs2523454 A allele significantly decreased transcriptional activity compared to the G allele by influencing TF-binding affinity. In addition, expression quantitative trait loci analyses revealed that the A allele was associated with the reduced expression of MICA (P < 0.01). CONCLUSIONS: Our findings suggest that the germline G > A variation at rs2523454 may influence TF-DNA interaction, downregulate the expression of MICA and play an important role in the development of persistent HBV infection in the Chinese population.

Favorable genomic environments for cis-regulatory evolution: A novel theoretical framework.

Cis-regulatory changes are arguably the primary evolutionary source of animal morphological diversity. With the recent explosion of genome-wide comparisons of the cis-regulatory content in different animal species is now possible to infer general principles underlying enhancer evolution. However, these studies have also revealed numerous discrepancies and paradoxes, suggesting that the mechanistic causes and modes of cis-regulatory evolution are still not well understood and are probably much more complex than generally appreciated. Here, we argue that the mutational mechanisms and genomic regions generating new regulatory activities must comply with the constraints imposed by the molecular properties of cis-regulatory elements (CREs) and the organizational features of long-range chromatin interactions. Accordingly, we propose a new integrative evolutionary framework for cis-regulatory evolution based on two major premises for the origin of novel enhancer activity: (i) an accessible chromatin environment and (ii) compatibility with the 3D structure and interactions of pre-existing CREs. Mechanisms and DNA sequences not fulfilling these premises, will be less likely to have a measurable impact on gene expression and as such, will have a minor contribution to the evolution of gene regulation. Finally, we discuss current comparative cis-regulatory data under the light of this new evolutionary model, and propose that the two most prominent mechanisms for the evolution of cis-regulatory changes are the overprinting of ancestral CREs and the exaptation of transposable elements.

TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets.

BACKGROUND: A strong focus of the post-genomic era is mining of the non-coding regulatory genome in order to unravel the function of regulatory elements that coordinate gene expression (Nat 489:57-74, 2012; Nat 507:462-70, 2014; Nat 507:455-61, 2014; Nat 518:317-30, 2015). Whole-genome approaches based on next-generation sequencing (NGS) have provided insight into the genomic location of regulatory elements throughout different cell types, organs and organisms. These technologies are now widespread and commonly used in laboratories from various fields of research. This highlights the need for fast and user-friendly software tools dedicated to extracting cis-regulatory information contained in these regulatory regions; for instance transcription factor binding site (TFBS) composition. Ideally, such tools should not require prior programming knowledge to ensure they are accessible for all users. RESULTS: We present TrawlerWeb, a web-based version of the Trawler_standalone tool (Nat Methods 4:563-5, 2007; Nat Protoc 5:323-34, 2010), to allow for the identification of enriched motifs in DNA sequences obtained from next-generation sequencing experiments in order to predict their TFBS composition. TrawlerWeb is designed for online queries with standard options common to web-based motif discovery tools. In addition, TrawlerWeb provides three unique new features: 1) TrawlerWeb allows the input of BED files directly generated from NGS experiments, 2) it automatically generates an input-matched biologically relevant background, and 3) it displays resulting conservation scores for each instance of the motif found in the input sequences, which assists the researcher in prioritising the motifs to validate experimentally. Finally, to date, this web-based version of Trawler_standalone remains the fastest online de novo motif discovery tool compared to other popular web-based software, while generating predictions with high accuracy. CONCLUSIONS: TrawlerWeb provides users with a fast, simple and easy-to-use web interface for de novo motif discovery. This will assist in rapidly analysing NGS datasets that are now being routinely generated. TrawlerWeb is freely available and accessible at: http://trawler.erc.monash.edu.au .

The polymorphisms of LCR, E6, and E7 of HPV-58 isolates in Yunnan, Southwest China.

BACKGROUD: Variations in HPV LCR/E6/E7 have been shown to be associated with the viral persistence and cervical cancer development. So far, there are few reports about the polymorphisms of the HPV-58 LCR/E6/E7 sequences in Southwest China. This study aims to characterize the gene polymorphisms of the HPV-58 LCR/E6/E7 sequences in women of Southwest China, and assess the effects of variations on the immune recognition of viral E6 and E7 antigens. METHODS: Twelve LCR/E6/E7 of the HPV-58 isolates were amplified and sequenced. A neighbor-joining phylogenetic tree was constructed by MEGA 7.0, followed by the secondary structure prediction of the related proteins using PSIPRED v3.3. The selection pressure acting on the HPV-58 E6 and E7 coding regions was estimated by Bayes empirical Bayes analysis of PAML 4.8. Meanwhile, the MHC class-I and II binding peptides were predicted by the ProPred-I server and ProPred server. The transcription factor binding sites in the HPV-58 LCR were analyzed using the JASPAR database. RESULTS: Twenty nine SNPs (20 in the LCR, 3 in the E6, 6 in the E7) were identified at 27 nucleotide sites across the HPV-58 LCR/E6/E7. From the most variable to the least variable, the nucleotide variations were LCR > E7 > E6. The combinations of all the SNPs resulted in 11 unique sequences, which were clustered into the A lineage (7 belong to A1, 2 belong to A2, and 2 belong to A3). An insertion (TGTCAGTTTCCT) was found between the nucleotide sites 7280 and 7281 in 2 variants, and a deletion (TTTAT) was found between 7429 and 7433 in 1 variant. The most common non-synonymous substitution V77A in the E7 was observed in the sequences encoding the α-helix. 63G in the E7 was determined to be the only one positively selected site in the HPV-58 E6/E7 sequences. Six non-synonymous amino acid substitutions (including S71F and K93 N in the E6, and T20I, G41R, G63S/D, and V77A in the E7) were affecting multiple putative epitopes for both CD4+ and CD8+ T-cells. In the LCR, C7265G and C7266T were the most variable sites and were the potential binding sites for the transcription factor SOX10. CONCLUSION: These results provide an insight into the intrinsic geographical relatedness and biological differences of the HPV-58 variants, and contribute to further research on the HPV-58 epidemiology, carcinogenesis, and therapeutic vaccine development.

Candidate novel long noncoding RNAs, MicroRNAs and putative drugs for Parkinson's disease using a robust and efficient genome-wide association study.

Parkinson's disease (PD) is a neurodegenerative disorder with serious symptoms of which, are not clearly demonstrated at the beginning stages of the disease, making treatment challenging. Understanding the genetic causes of PD can be useful for determining its mechanisms and proposing treatments and preventive methods. For different populations with different genetic backgrounds and lifestyles, genome-wide association studies (GWASs) represent a crucial approach for genetic analysis. In this study, a robust and efficient GWAS without dimensionality reduction applied to evaluate heritability and genetic causes of PD in the German and US populations. The results show higher rate of PD heritability in the German population. Moreover, 25 significant SNPs have been determined, as well as five newly identified candidate genes associated with PD and some potential drug candidates. Analysis also reveals various long noncoding RNAs (lncRNAs), microRNAs and transcription-factor binding sites (TFBSs) with potential in the prevention and treatment of PD.

TIGERi: modeling and visualizing the responses to perturbation of a transcription factor network.

BACKGROUND: Transcription factor (TF) networks play a key role in controlling the transfer of genetic information from gene to mRNA. Much progress has been made on understanding and reverse-engineering TF network topologies using a range of experimental and theoretical methodologies. Less work has focused on using these models to examine how TF networks respond to changes in the cellular environment. METHODS: In this paper, we have developed a simple, pragmatic methodology, TIGERi (Transcription-factor-activity Illustrator for Global Explanation of Regulatory interaction), to model the response of an inferred TF network to changes in cellular environment. The methodology was tested using publicly available data comparing gene expression profiles of a mouse p38α (Mapk14) knock-out line to the original wild-type. RESULTS: Using the model, we have examined changes in the TF network resulting from the presence or absence of p38α. A part of this network was confirmed by experimental work in the original paper. Additional relationships were identified by our analysis, for example between p38α and HNF3, and between p38α and SOX9, and these are strongly supported by published evidence. FXR and MYC were also discovered in our analysis as two novel links of p38α. To provide a computational methodology to the biomedical communities that has more user-friendly interface, we also developed a standalone GUI (graphical user interface) software for TIGERi and it is freely available at https://github.com/namshik/tigeri/ . CONCLUSIONS: We therefore believe that our computational approach can identify new members of networks and new interactions between members that are supported by published data but have not been integrated into the existing network models. Moreover, ones who want to analyze their own data with TIGERi could use the software without any command line experience. This work could therefore accelerate researches in transcriptional gene regulation in higher eukaryotes.