Motif Databases Research Articles

Quantitative Dissection of the Proximal Ciona brachyury Enhancer.

A major goal in biology is to understand the rules by which cis-regulatory sequences control spatially and temporally precise expression patterns. Here we present a systematic dissection of the proximal enhancer for the notochord-specific transcription factor brachyury in the ascidian chordate Ciona. The study uses a quantitative image-based reporter assay that incorporates a dual-reporter strategy to control for variable electroporation efficiency. We identified and mutated multiple predicted transcription factor binding sites of interest based on statistical matches to the JASPAR binding motif database. Most sites (Zic, Ets, FoxA, RBPJ) were selected based on prior knowledge of cell fate specification in both the primary and secondary notochord. We also mutated predicted Brachyury sites to investigate potential autoregulation as well as Fos/Jun (AP1) sites that had very strong matches to JASPAR. Our goal was to quantitatively define the relative importance of these different sites, to explore the importance of predicted high-affinity versus low-affinity motifs, and to attempt to design mutant enhancers that were specifically expressed in only the primary or secondary notochord lineages. We found that the mutation of all predicted high-affinity sites for Zic, FoxA or Ets led to quantifiably distinct effects. The FoxA construct caused a severe loss of reporter expression whereas the Ets construct had little effect. A strong Ets phenotype was only seen when much lower-scoring binding sites were also mutated. This supports the enhancer suboptimization hypothesis proposed by Farley and Levine but suggests that it may only apply to some but not all transcription factor families. We quantified reporter expression separately in the two notochord lineages with the expectation that Ets mutations and RBPJ mutations would have distinct effects given that primary notochord is induced by Ets-mediated FGF signaling whereas secondary notochord is induced by RBPJ/Su(H)-mediated Notch/Delta signaling. We found, however, that ETS mutations affected primary and secondary notochord expression relatively equally and that RBPJ mutations were only moderately more severe in their effect on secondary versus primary notochord. Our results point to the promise of quantitative reporter assays for understanding cis-regulatory logic but also highlight the challenge of arbitrary statistical thresholds for predicting potentially important sites.

Factorbook: an updated catalog of transcription factor motifs and candidate regulatory motif sites.

The human genome contains ∼2000 transcriptional regulatory proteins, including ∼1600 DNA-binding transcription factors (TFs) recognizing characteristic sequence motifs to exert regulatory effects on gene expression. The binding specificities of these factors have been profiled both in vitro, using techniques such as HT-SELEX, and in vivo, using techniques including ChIP-seq. We previously developed Factorbook, a TF-centric database of annotations, motifs, and integrative analyses based on ChIP-seq data from Phase II of the ENCODE Project. Here we present an update to Factorbook which significantly expands the breadth of cell type and TF coverage. The update includes an expanded motif catalog derived from thousands of ENCODE Phase II and III ChIP-seq experiments and HT-SELEX experiments; this motif catalog is integrated with the ENCODE registry of candidate cis-regulatory elements to annotate a comprehensive collection of genome-wide candidate TF binding sites. The database also offers novel tools for applying the motif models within machine learning frameworks and using these models for integrative analysis, including annotation of variants and disease and trait heritability. Factorbook is publicly available at www.factorbook.org; we will continue to expand the resource as ENCODE Phase IV data are released.

RNALigands: a database and web server for RNA-ligand interactions.

RNA molecules can fold into complex and stable 3D structures, allowing them to carry out important genetic, structural, and regulatory roles inside the cell. These complex structures often contain 3D pockets made up of secondary structural motifs that can be potentially targeted by small molecule ligands. Indeed, many RNA structures in PDB contain bound small molecules, and high-throughput experimental studies have generated a large number of interacting RNA and ligand pairs. There is considerable interest in developing small molecule lead compounds targeting viral RNAs or those RNAs implicated in neurological diseases or cancer. We hypothesize that RNAs that have similar secondary structural motifs may bind to similar small molecule ligands. Toward this goal, we established a database collecting RNA secondary structural motifs and bound small molecule ligands. We further developed a computational pipeline, which takes as input an RNA sequence, predicts its secondary structure, extracts structural motifs, and searches the database for similar secondary structure motifs and interacting small molecule. We demonstrated the utility of the server by querying α-synuclein mRNA 5' UTR sequence and finding potential matches which were validated as correct. The server is publicly available at http://RNALigands.ccbr.utoronto.ca The source code can also be downloaded at https://github.com/SaisaiSun/RNALigands.

Match_Motif: A rapid computational tool to assist in protein-protein interaction design.

In order to generate protein assemblies with a desired function, the rational design of protein–protein binding interfaces is of significant interest. Approaches based on random mutagenesis or directed evolution may involve complex experimental selection procedures. Also, molecular modeling approaches to design entirely new proteins and interactions with partner molecules can involve large computational efforts and screening steps. In order to simplify at least the initial effort for designing a putative binding interface between two proteins the Match_Motif approach has been developed. It employs the large collection of known protein–protein complex structures to suggest interface modifications that may lead to improved binding for a desired input interaction geometry. The approach extracts interaction motifs based on the backbone structure of short (four residues) segments and the relative arrangement with respect to short segments on the partner protein. The interaction geometry is used to search through a database of such motifs in known stable bound complexes. All matches are rapidly identified (within a few seconds) and collected and can be used to guide changes in the interface that may lead to improved binding. In the output, an alternative interface structure is also proposed based on the frequency of occurrence of side chains at a given interface position in all matches and based on sterical considerations. Applications of the procedure to known complex structures and alternative arrangements are presented and discussed. The program, data files, and example applications can be downloaded from https://www.groups.ph.tum.de/t38/downloads/.

Profiling of chromatin accessibility identifies transcription factor binding sites across the genome of Aspergillus species

BackgroundThe identification of open chromatin regions and transcription factor binding sites (TFBs) is an important step in understanding the regulation of gene expression in diverse species. ATAC-seq is a technique used for such purpose by providing high-resolution measurements of chromatin accessibility revealed through integration of Tn5 transposase. However, the existence of cell walls in filamentous fungi and associated difficulty in purifying nuclei have precluded the routine application of this technique, leading to a lack of experimentally determined and computationally inferred data on the identity of genome-wide cis-regulatory elements (CREs) and TFBs. In this study, we constructed an ATAC-seq platform suitable for filamentous fungi and generated ATAC-seq libraries of Aspergillus niger and Aspergillus oryzae grown under a variety of conditions.ResultsWe applied the ATAC-seq assay for filamentous fungi to delineate the syntenic orthologue and differentially changed chromatin accessibility regions among different Aspergillus species, during different culture conditions, and among specific TF-deleted strains. The syntenic orthologues of accessible regions were responsible for the conservative functions across Aspergillus species, while regions differentially changed between culture conditions and TFs mutants drove differential gene expression programs. Importantly, we suggest criteria to determine TFBs through the analysis of unbalanced cleavage of distinct TF-bound DNA strands by Tn5 transposase. Based on this criterion, we constructed data libraries of the in vivo genomic footprint of A. niger under distinct conditions, and generated a database of novel transcription factor binding motifs through comparison of footprints in TF-deleted strains. Furthermore, we validated the novel TFBs in vivo through an artificial synthetic minimal promoter system.ConclusionsWe characterized the chromatin accessibility regions of filamentous fungi species, and identified a complete TFBs map by ATAC-seq, which provides valuable data for future analyses of transcriptional regulation in filamentous fungi.

FPMD-FUNGAL PROMOTER MOTIF DATABASE: A DATABASE FOR THE OF THE PROMOTER MOTIFS REGIONS IN FUNGAL GENOMES

Fungal promoter motif database is the collection of promoter motifs from fully sequenced fungal genomes. Promoter sequences and its frequency are analyzed by the positions of nucleotide sequence and its repetition. The fungal promoter motif database holds the promoter sequence motifs identified by genome wide motif discovery, similarity studies and clustering. These data sets are typically 6 to 10 bp long, that have been extracted from the promoter regions. These promoter regions extend from 1.5 kb upstream to 200bp downstream of a transcription start site. We believe that the availability of these promoter motifs will be a valuable resource for researchers for comparative sequence analysis and evolutionary studies.

Predicted Cellular Interactors of the Endogenous Retrovirus-K Integrase Enzyme.

Integrase (IN) enzymes are found in all retroviruses and are crucial in the retroviral integration process. Many studies have revealed how exogenous IN enzymes, such as the human immunodeficiency virus (HIV) IN, contribute to altered cellular function. However, the same consideration has not been given to viral IN originating from symbionts within our own DNA. Endogenous retrovirus-K (ERVK) is pathologically associated with neurological and inflammatory diseases along with several cancers. The ERVK IN interactome is unknown, and the question of how conserved the ERVK IN protein–protein interaction motifs are as compared to other retroviral integrases is addressed in this paper. The ERVK IN protein sequence was analyzed using the Eukaryotic Linear Motif (ELM) database, and the results are compared to ELMs of other betaretroviral INs and similar eukaryotic INs. A list of putative ERVK IN cellular protein interactors was curated from the ELM list and submitted for STRING analysis to generate an ERVK IN interactome. KEGG analysis was used to identify key pathways potentially influenced by ERVK IN. It was determined that the ERVK IN potentially interacts with cellular proteins involved in the DNA damage response (DDR), cell cycle, immunity, inflammation, cell signaling, selective autophagy, and intracellular trafficking. The most prominent pathway identified was viral carcinogenesis, in addition to select cancers, neurological diseases, and diabetic complications. This potentiates the role of ERVK IN in these pathologies via protein–protein interactions facilitating alterations in key disease pathways.

CatRAPID omics v2.0: going deeper and wider in the prediction of protein-RNA interactions.

Prediction of protein–RNA interactions is important to understand post-transcriptional events taking place in the cell. Here we introduce catRAPID omics v2.0, an update of our web server dedicated to the computation of protein–RNA interaction propensities at the transcriptome- and RNA-binding proteome-level in 8 model organisms. The server accepts multiple input protein or RNA sequences and computes their catRAPID interaction scores on updated precompiled libraries. Additionally, it is now possible to predict the interactions between a custom protein set and a custom RNA set. Considerable effort has been put into the generation of a new database of RNA-binding motifs that are searched within the predicted RNA targets of proteins. In this update, the sequence fragmentation scheme of the catRAPID fragment module has been included, which allows the server to handle long linear RNAs and to analyse circular RNAs. For the top-scoring protein–RNA pairs, the web server shows the predicted binding sites in both protein and RNA sequences and reports whether the predicted interactions are conserved in orthologous protein–RNA pairs. The catRAPID omics v2.0 web server is a powerful tool for the characterization and classification of RNA-protein interactions and is freely available at http://service.tartaglialab.com/page/catrapid_omics2_group along with documentation and tutorial.

Genomic analysis uncovers functional variation in the C-terminus of anthocyanin-activating MYB transcription factors

MYB transcription factors regulate diverse aspects of plant development and secondary metabolism, often by partnering in transcriptional regulatory complexes. Here, we harness genomic resources to identify novel MYBs, thereby producing an updated eudicot MYB phylogeny with revised relationships among subgroups as well as new information on sequence variation in the disordered C-terminus of anthocyanin-activating MYBs. BLAST® and hidden Markov model scans of gene annotations identified a total of 714 MYB transcription factors across the genomes of four crops that span the eudicots: apple, grape, kiwifruit and tomato. Codon model-based phylogenetic inference identified novel members of previously defined subgroups, and the function of specific anthocyanin-activating subgroup 6 members was assayed transiently in tobacco leaves. Sequence conservation within subgroup 6 highlighted one previously described and two novel short linear motifs in the disordered C-terminal region. The novel motifs have a mix of hydrophobic and acidic residues and are predicted to be relatively ordered compared with flanking protein sequences. Comparison of motifs with the Eukaryotic Linear Motif database suggests roles in protein–protein interaction. Engineering of motifs and their flanking regions from strong anthocyanin activators into weak activators, and vice versa, affected function. We conclude that, although the MYB C-terminal sequence diverges greatly even within MYB clades, variation within the C-terminus at and near relatively ordered regions offers opportunities for exploring MYB function and developing superior alleles for plant breeding.

PRESnovo: Prescreening Prior to de novo Sequencing to Improve Accuracy and Sensitivity of Neuropeptide Identification.

Identification of peptides in species lacking fully sequenced genomes is challenging due to the lack of prior knowledge. De novo sequencing is the method of choice, but its performance is less than satisfactory due to algorithmic bias and interference in complex MS/MS spectra. The task becomes even more challenging for endogenous peptides that do not involve an enzymatic digestion step, such as neuropeptides. However, many neuropeptides possess common sequence motifs that are conserved across members of the same family. Taking advantage of this feature to improve de novo sequencing of neuropeptides, we have developed a method named PRESnovo (prescreening precursors prior to de novo sequencing) to predict the motif from a MS/MS spectrum. A neuropeptide sequence is broken into a motif with conserved amino acid residues and the remaining partial sequence. By searching against a predefined motif database constructed from known homologous sequences, PRESnovo assigns the most probable motif to each precursor via a sophisticated scoring function. Performance analysis was conducted with 15 neuropeptide standards, and 11 neuropeptides were correctly identified with PRESnovo compared to 1 identification by PEAKS only. We applied PRESnovo to assign motifs to peptide sequences in conjunction with PEAKS for assigning the rest of the peptide sequence in order to discover neuropeptides in tissue samples of green crab, C. maenas, and Jonah crab, C. borealis. Collectively, a large number of neuropeptides were identified, including 13 putative neuropeptides identified in green crab brain, 77 in Jonah crab brain, and 47 in Jonah crab sinus glands for the first time. This PRESnovo strategy greatly simplifies de novo sequencing and enhances the accuracy and sensitivity of neuropeptide identification when common motifs are present.

RNA CoSSMos 2.0: an improved searchable database of secondary structure motifs in RNA three-dimensional structures.

The RNA Characterization of Secondary Structure Motifs, RNA CoSSMos, database is a freely accessible online database that allows users to identify secondary structure motifs among RNA 3D structures and explore their structural features. RNA CoSSMos 2.0 now requires two closing base pairs for all RNA loop motifs to create a less redundant database of secondary structures. Furthermore, RNA CoSSMos 2.0 represents an upgraded database with new features that summarize search findings and aid in the search for 3D structural patterns among RNA secondary structure motifs. Previously, users were limited to viewing search results individually, with no built-in tools to compare search results. RNA CoSSMos 2.0 provides two new features, allowing users to summarize, analyze and compare their search result findings. A function has been added to the website that calculates the average and representative structures of the search results. Additionally, users can now view a summary page of their search results that reports percentages of each structural feature found, including sugar pucker, glycosidic linkage, hydrogen bonding patterns and stacking interactions. Other upgrades include a newly embedded NGL structural viewer, the option to download the clipped structure coordinates in *.pdb format and improved NMR structure results. RNA CoSSMos 2.0 is no longer simply a search engine for a structure database; it now has the capability of analyzing, comparing and summarizing search results.Database URL: http://rnacossmos.com

TFBSshape: an expanded motif database for DNA shape features of transcription factor binding sites.

TFBSshape (https://tfbsshape.usc.edu) is a motif database for analyzing structural profiles of transcription factor binding sites (TFBSs). The main rationale for this database is to be able to derive mechanistic insights in protein–DNA readout modes from sequencing data without available structures. We extended the quantity and dimensionality of TFBSshape, from mostly in vitro to in vivo binding and from unmethylated to methylated DNA. This new release of TFBSshape improves its functionality and launches a responsive and user-friendly web interface for easy access to the data. The current expansion includes new entries from the most recent collections of transcription factors (TFs) from the JASPAR and UniPROBE databases, methylated TFBSs derived from in vitro high-throughput EpiSELEX-seq binding assays and in vivo methylated TFBSs from the MeDReaders database. TFBSshape content has increased to 2428 structural profiles for 1900 TFs from 39 different species. The structural profiles for each TFBS entry now include 13 shape features and minor groove electrostatic potential for standard DNA and four shape features for methylated DNA. We improved the flexibility and accuracy for the shape-based alignment of TFBSs and designed new tools to compare methylated and unmethylated structural profiles of TFs and methods to derive DNA shape-preserving nucleotide mutations in TFBSs.

SalMotifDB: a tool for analyzing putative transcription factor binding sites in salmonid genomes

BackgroundRecently developed genome resources in Salmonid fish provides tools for studying the genomics underlying a wide range of properties including life history trait variation in the wild, economically important traits in aquaculture and the evolutionary consequences of whole genome duplications. Although genome assemblies now exist for a number of salmonid species, the lack of regulatory annotations are holding back our mechanistic understanding of how genetic variation in non-coding regulatory regions affect gene expression and the downstream phenotypic effects.ResultsWe present SalMotifDB, a database and associated web and R interface for the analysis of transcription factors (TFs) and their cis-regulatory binding sites in five salmonid genomes. SalMotifDB integrates TF-binding site information for 3072 non-redundant DNA patterns (motifs) assembled from a large number of metazoan motif databases. Through motif matching and TF prediction, we have used these multi-species databases to construct putative regulatory networks in salmonid species. The utility of SalMotifDB is demonstrated by showing that key lipid metabolism regulators are predicted to regulate a set of genes affected by different lipid and fatty acid content in the feed, and by showing that our motif database explains a significant proportion of gene expression divergence in gene duplicates originating from the salmonid specific whole genome duplication.ConclusionsSalMotifDB is an effective tool for analyzing transcription factors, their binding sites and the resulting gene regulatory networks in salmonid species, and will be an important tool for gaining a better mechanistic understanding of gene regulation and the associated phenotypes in salmonids. SalMotifDB is available at https://salmobase.org/apps/SalMotifDB.

Prediction and Analysis of Three-Dimensional Structure of the p7- Transactivated Protein1 of Hepatitis C Virus.

The p7-transactivated protein1 of Hepatitis C virus is a small integral membrane protein of 127 amino acids, which is crucial for assembly and release of infectious virions. Ab initio or comparative modelling, is an essential tool to solve the problem of protein structure prediction and to comprehend the physicochemical fundamental of how proteins fold in nature. Only one domain (1-127) of p7-transactivated protein1 has been predicted using the systematic in silico approach, ThreaDom. I-TASSER was ranked as the best server for full-length 3-D protein structural predictions of p7-transactivated protein1 where the benchmarked scoring system such as C-score, TM-score, RMSD and Z-score are used to obtain quantitative assessments of the I-TASSER models. Scanning protein motif databases, along with secondary and surface accessibility predictions integrated with post translational modification sites (PTMs) prediction revealed functional and protein binding motifs. Three protein binding motifs (two Asp/Glutamnse, CTNNB1- bd_N) with high sequence conservation and two PTMs prediction: Camp_phospho_site and Myristyl site were predicted using BLOCKS and PROSITE scan. These motifs and PTMs were related to the function of p7-transactivated protein1 protein in inducing ion channel/pore and release of infectious virions. Using SCOP, only one hit matched protein sequence at 71-120 was classified as small proteins and FYVE/PHD zinc finger superfamily. Integrating this information about the p7-transactivated protein1 with SCOP and CATH annotations of the templates facilitates the assignment of structure-function/ evolution relationships to the known and the newly determined protein structures.

RRMdb-an evolutionary-oriented database of RNA recognition motif sequences.

RNA-recognition motif (RRM) is an RNA-interacting protein domain that plays an important role in the processes of RNA metabolism such as the splicing, editing, export, degradation, and regulation of translation. Here, we present the RNA-recognition motif database (RRMdb), which affords rapid identification and annotation of RRM domains in a given protein sequence. The RRMdb database is compiled from ~57 000 collected representative RRM domain sequences, classified into 415 families. Whenever possible, the families are associated with the available literature and structural data. Moreover, the RRM families are organized into a network of sequence similarities that allows for the assessment of the evolutionary relationships between them.

Bioinformatics Approaches to Gain Insights into cis-Regulatory Motifs Involved in mRNA Localization.

Messenger RNA (mRNA) is a fundamental intermediate in the expression of proteins. As an integral part of this important process, protein production can be localized by the targeting of mRNA to a specific subcellular compartment. The subcellular destination of mRNA is suggested to be governed by a region of its primary sequence or secondary structure, which consequently dictates the recruitment of trans-acting factors, such as RNA-binding proteins or regulatory RNAs, to form a messenger ribonucleoprotein particle. This molecular ensemble is requisite for precise and spatiotemporal control of gene expression. In the context of RNA localization, the description of the binding preferences of an RNA-binding protein defines a motif, and one, or more, instance of a given motif is defined as a localization element (zip code). In this chapter, we first discuss the cis-regulatory motifs previously identified as mRNA localization elements. We then describe motif representation in terms of entropy and information content and offer an overview of motif databases and search algorithms. Finally, we provide an outline of the motif topology of asymmetrically localized mRNA molecules.

MethMotif: an integrative cell specific database of transcription factor binding motifs coupled with DNA methylation profiles.

Several recent studies have portrayed DNA methylation as a new player in the recruitment of transcription factors (TF) within chromatin, highlighting a need to connect TF binding sites (TFBS) with their respective DNA methylation profiles. However, current TFBS databases are restricted to DNA binding motif sequences. Here, we present MethMotif, a two-dimensional TFBS database that records TFBS position weight matrices along with cell type specific CpG methylation information computed from a combination of ChIP-seq and whole genome bisulfite sequencing datasets. Integrating TFBS motifs with TFBS DNA methylation better portrays the features of DNA loci recognised by TFs. In particular, we found that DNA methylation patterns within TFBS can be cell specific (e.g. MAFF). Furthermore, for a given TF, different DNA methylation profiles are associated with different DNA binding motifs (e.g. REST). To date, MethMotif database records over 500 TFBSs computed from over 2000 ChIP-seq datasets in 11 different cell types. MethMotif portal is accessible through an open source web interface (https://bioinfo-csi.nus.edu.sg/methmotif) that allows users to intuitively explore the entire dataset and perform both single, and batch queries.

Abstract 1221: Chronic lymphocytic leukemia risk variants are associated with alteration of epigenetic states in regulatory regions

Abstract Chronic lymphocytic leukemia risk variants are associated with alteration of epigenetic state in regulatory regions The vast majority of disease-associated single-nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWASs) reside in noncoding genomic regions. Functional impact of noncoding casual variants on target gene expression often involves regulatory mechanisms, typically through altering local chromatin accessibility, histone modifications, transcription factor (TF) binding affinity and chromatin interactions. In chronic lymphocytic leukemia (CLL), we and others have identified 41 GWAS risk variants, whose mechanism of action in CLL etiology remains largely unknown. In this study, we aim to decipher the regulatory potential of these variants and to better understand the mechanisms contributing to dysregulation of genes implicated in CLL pathogenesis. We performed ChIP-seq for H3K4me3, H3K4me1, H3K27ac and H3K27me3 in CLL. In addition, we also analyzed over 250 public ChIP-seq, ATAC-seq, DNase-seq, FAIRE-seq, and chromatin interaction data in CLL, B cells and/or lymphoblastoid cell lines. Comparing the 41 index SNPs and the nearby SNPs they associated with in linkage disequilibrium (R2 at least 0.5 in the EUR ethnic group in 1000 Genomes Project) to the above epigenetic data sets revealed overlaps with regulatory regions in 38 of the risk loci, with 28 of the loci overlapping super-enhancers. We used two approaches to elucidate the mechanisms of potential SNP causality. First, we used GATK UnifiedGenotyper to infer genotype for the SNPs that overlapped open chromatin regions and ChIP-seq peaks, by which evidence of imbalance between reference and alternative allele was identified at heterozygous sites. Second, for SNPs located within open chromatin regions or ChIP-seq peaks, we used FIMO program to scan the 100bp sequences centered on the SNPs for significant matches (p=1e-05) to the position weight matrices in five TF binding motif databases; SNPs that had TF motifs altered by the alternative alleles were retained. Together, these two approaches revealed evidence for allele imbalance or TF binding motif alterations at 36 of the 38 CLL risk loci, suggesting the generality of epigenetic regulation in CLL pathogenesis. Further analysis of chromatin interaction, gene expression and expression quantitative trait loci data will likely link the casual SNPs to their target genes. Citation Format: Huihuang Yan, Shulan Tian, Geffen Kleinstern, Susan Slager. Chronic lymphocytic leukemia risk variants are associated with alteration of epigenetic states in regulatory regions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1221.

The BaMM web server for de-novo motif discovery and regulatory sequence analysis.

The BaMM web server offers four tools: (i) de-novo discovery of enriched motifs in a set of nucleotide sequences, (ii) scanning a set of nucleotide sequences with motifs to find motif occurrences, (iii) searching with an input motif for similar motifs in our BaMM database with motifs for >1000 transcription factors, trained from the GTRD ChIP-seq database and (iv) browsing and keyword searching the motif database. In contrast to most other servers, we represent sequence motifs not by position weight matrices (PWMs) but by Bayesian Markov Models (BaMMs) of order 4, which we showed previously to perform substantially better in ROC analyses than PWMs or first order models. To address the inadequacy of P- and E-values as measures of motif quality, we introduce the AvRec score, the average recall over the TP-to-FP ratio between 1 and 100. The BaMM server is freely accessible without registration at https://bammmotif.mpibpc.mpg.de.

Analysis of Pig Vomeronasal Receptor Type 1 (V1R) Promoter Region Reveals a Common Promoter Motif but Poor CpG Islands

ABSTRACTPromoters are, generally, located immediately upstream of a transcription start site (TSS) and have a variety of regulatory motifs, such as transcription factors (TFs) and CpG islands (CGIs), that participate in the regulation of gene expression. Here analysis of the promoter region for pig vomeronasal receptor type 1 (V1R) was described. In the analysis, TSSs for pig V1R genes was first identified and five motifs (MV1, MV2, MV3, MV4, and MV5) were found that are shared by at least 50% of the pig V1R promoter input sequences from both strands. Among the five motifs, MV2 was identified as a common promoter motif shared by all (100%) pig V1R promoters. For further analysis, to better characterize and get deeper biological insight associated with MV2, TOMTOM web application was used. MV2 was compared to the known motif databases (such as JASPAR) to see if they are similar to a known regulatory motif (transcription factor). Hence, it was revealed that MV2 serves as the binding site mainly for the BetaBetaAlpha-zinc finger (BTB-ZF) transcription factor gene family to regulate expression of pig V1R genes. Moreover, it was shown that pig V1R promoters are CpG poor, suggesting that their gene expression regulation pattern is in tissue specific manner.