Identification Of Transcription Start Sites Research Articles

Simultaneous mapping of transcript ends at single-nucleotide resolution and identification of widespread promoter-associated non-coding RNA governed by TATA elements

Understanding the relationships between regulatory factor binding, chromatin structure, cis-regulatory elements and RNA-regulation mechanisms relies on accurate information about transcription start sites (TSS) and polyadenylation sites (PAS). Although several approaches have identified transcript ends in yeast, limitations of resolution and coverage have remained, and definitive identification of TSS and PAS with single-nucleotide resolution has not yet been achieved. We developed SMORE-seq (simultaneous mapping of RNA ends by sequencing) and used it to simultaneously identify the strongest TSS for 5207 (90%) genes and PAS for 5277 (91%) genes. The new transcript annotations identified by SMORE-seq showed improved distance relationships with TATA-like regulatory elements, nucleosome positions and active RNA polymerase. We found 150 genes whose TSS were downstream of the annotated start codon, and additional analysis of evolutionary conservation and ribosome footprinting suggests that these protein-coding sequences are likely to be mis-annotated. SMORE-seq detected short non-coding RNAs transcribed divergently from more than a thousand promoters in wild-type cells under normal conditions. These divergent non-coding RNAs were less evident at promoters containing canonical TATA boxes, suggesting a model where transcription initiation at promoters by RNAPII is bidirectional, with TATA elements serving to constrain the directionality of initiation.

Riboswitch discovery by combining RNA-seq and genome-wide identification of transcriptional start sites.

Deep-sequencing technologies applied to RNA have tremendous potential to identify novel transcripts with single-nucleotide resolution. By combining whole-transcript cDNA sequencing (RNA-seq) and genome-wide identification of transcription start sites (dRNA-seq), it is possible to characterize long 5'-untranslated regions potentially endowed with regulatory capacities and to detect premature termination of transcription. This can be used to identify new potential riboswitches. In this chapter, we provide a detailed protocol of the dRNA-seq method based on differential pretreatment of RNAs with tobacco acid pyrophosphatase to differentiate between 5'-ends of primary and processed RNAs. We also give a briefer protocol of the preparation of RNA-seq libraries and of how to go through data bioinformatics analysis and data visualization using genome browsers. This approach is powerful to identify novel riboswitches and to demonstrate the functionality of riboswitches predicted in silico.

TSSer: an automated method to identify transcription start sites in prokaryotic genomes from differential RNA sequencing data

Accurate identification of transcription start sites (TSSs) is an essential step in the analysis of transcription regulatory networks. In higher eukaryotes, the capped analysis of gene expression technology enabled comprehensive annotation of TSSs in genomes such as those of mice and humans. In bacteria, an equivalent approach, termed differential RNA sequencing (dRNA-seq), has recently been proposed, but the application of this approach to a large number of genomes is hindered by the paucity of computational analysis methods. With few exceptions, when the method has been used, annotation of TSSs has been largely done manually. In this work, we present a computational method called 'TSSer' that enables the automatic inference of TSSs from dRNA-seq data. The method rests on a probabilistic framework for identifying both genomic positions that are preferentially enriched in the dRNA-seq data as well as preferentially captured relative to neighboring genomic regions. Evaluating our approach for TSS calling on several publicly available datasets, we find that TSSer achieves high consistency with the curated lists of annotated TSSs, but identifies many additional TSSs. Therefore, TSSer can accelerate genome-wide identification of TSSs in bacterial genomes and can aid in further characterization of bacterial transcription regulatory networks. TSSer is freely available under GPL license at http://www.clipz.unibas.ch/TSSer/index.php

RAMPAGE: Promoter Activity Profiling by Paired‐End Sequencing of 5′‐Complete cDNAs

RNA annotation and mapping of promoters for analysis of gene expression (RAMPAGE) is a method that harnesses highly specific sequencing of 5'-complete complementary DNAs to identify transcription start sites (TSSs) genome-wide. Although TSS mapping has historically relied on detection of 5'-complete cDNAs, current genome-wide approaches typically have limited specificity and provide only scarce information regarding transcript structure. RAMPAGE allows for highly stringent selection of 5'-complete molecules, thus allowing base-resolution TSS identification with a high signal-to-noise ratio. Paired-end sequencing of medium-length cDNAs yields transcript structure information that is essential to interpreting the relationship of TSSs to annotated genes and transcripts. As opposed to standard RNA-seq, RAMPAGE explicitly yields accurate and highly reproducible expression level estimates for individual promoters. Moreover, this approach offers a streamlined 2- to 3-day protocol that is optimized for extensive sample multiplexing, and is therefore adapted for large-scale projects. This method has been applied successfully to human and Drosophila samples, and in principle should be applicable to any eukaryotic system.

NPEST: a nonparametric method and a database for transcription start site prediction.

In this paper we present NPEST, a novel tool for the analysis of expressed sequence tags (EST) distributions and transcription start site (TSS) prediction. This method estimates an unknown probability distribution of ESTs using a maximum likelihood (ML) approach, which is then used to predict positions of TSS. Accurate identification of TSS is an important genomics task, since the position of regulatory elements with respect to the TSS can have large effects on gene regulation, and performance of promoter motif-finding methods depends on correct identification of TSSs. Our probabilistic approach expands recognition capabilities to multiple TSS per locus that may be a useful tool to enhance the understanding of alternative splicing mechanisms. This paper presents analysis of simulated data as well as statistical analysis of promoter regions of a model dicot plant Arabidopsis thaliana. Using our statistical tool we analyzed 16520 loci and developed a database of TSS, which is now publicly available at www.glacombio.net/NPEST.

Transcriptome profile of a bovine respiratory disease pathogen: Mannheimia haemolytica PHL213

BackgroundComputational methods for structural gene annotation have propelled gene discovery but face certain drawbacks with regards to prokaryotic genome annotation. Identification of transcriptional start sites, demarcating overlapping gene boundaries, and identifying regulatory elements such as small RNA are not accurate using these approaches. In this study, we re-visit the structural annotation of Mannheimia haemolytica PHL213, a bovine respiratory disease pathogen. M. haemolytica is one of the causative agents of bovine respiratory disease that results in about $3 billion annual losses to the cattle industry. We used RNA-Seq and analyzed the data using freely-available computational methods and resources. The aim was to identify previously unannotated regions of the genome using RNA-Seq based expression profile to complement the existing annotation of this pathogen.ResultsUsing the Illumina Genome Analyzer, we generated 9,055,826 reads (average length ~76 bp) and aligned them to the reference genome using Bowtie. The transcribed regions were analyzed using SAMTOOLS and custom Perl scripts in conjunction with BLAST searches and available gene annotation information. The single nucleotide resolution map enabled the identification of 14 novel protein coding regions as well as 44 potential novel sRNA. The basal transcription profile revealed that 2,506 of the 2,837 annotated regions were expressed in vitro, at 95.25% coverage, representing all broad functional gene categories in the genome. The expression profile also helped identify 518 potential operon structures involving 1,086 co-expressed pairs. We also identified 11 proteins with mutated/alternate start codons.ConclusionsThe application of RNA-Seq based transcriptome profiling to structural gene annotation helped correct existing annotation errors and identify potential novel protein coding regions and sRNA. We used computational tools to predict regulatory elements such as promoters and terminators associated with the novel expressed regions for further characterization of these novel functional elements. Our study complements the existing structural annotation of Mannheimia haemolytica PHL213 based on experimental evidence. Given the role of sRNA in virulence gene regulation and stress response, potential novel sRNA described in this study can form the framework for future studies to determine the role of sRNA, if any, in M. haemolytica pathogenesis.

TSSi—an R package for transcription start site identification from 5′ mRNA tag data

High-throughput sequencing has become an essential experimental approach for the investigation of transcriptional mechanisms. For some applications like ChIP-seq, several approaches for the prediction of peak locations exist. However, these methods are not designed for the identification of transcription start sites (TSSs) because such datasets contain qualitatively different noise. In this application note, the R package TSSi is presented which provides a heuristic framework for the identification of TSSs based on 5' mRNA tag data. Probabilistic assumptions for the distribution of the data, i.e. for the observed positions of the mapped reads, as well as for systematic errors, i.e. for reads which map closely but not exactly to a real TSS, are made and can be adapted by the user. The framework also comprises a regularization procedure which can be applied as a preprocessing step to decrease the noise and thereby reduce the number of false predictions. The R package TSSi is available from the Bioconductor web site: www.bioconductor.org/packages/release/bioc/html/TSSi.html.

ARF-TSS: an alternative method for identification of transcription start site in bacteria.

Current methods for identifying transcription start sites (TSSs) of specific genes in bacteria usually require adaptors or radioactive labeling. These approaches can be technically demanding and environmentally unfriendly. Here we present a method for identifying TSS called ARF-TSS, which is based on cDNA generation, circularization, PCR amplification, and DNA sequencing to determine the 5'-end of transcripts, thus circumventing the need for adaptors and radioactive labeling. We validated the method using the gene lasI from the bacterial pathogen Pseudomonas aeruginosa. Our results show that ARF-TSS could be a good alternative to traditional methods for bacterial TSS analysis.

Genome-Wide Identification of Transcription Start Sites Yields a Novel Thermosensing RNA and New Cyclic AMP Receptor Protein-Regulated Genes in Escherichia coli

Intergenic regions often contain regulatory elements that control the expression of flanking genes. Using a deep-sequencing approach, we identified numerous new transcription start sites in Escherichia coli, yielding a new thermosensing regulatory RNA and seven genes previously unknown to be under the control of the global regulator CRP.

Identification of transcription start sites of trans-spliced genes: Uncovering unusual operon arrangements

In Caenorhabditis elegans, the transcripts of many genes are trans-spliced to an SL1 spliced leader, a process that removes the RNA extending from the transcription start site to the trans-splice site, thereby making it difficult to determine the position of the promoter. Here we use RT-PCR to identify promoters of trans-spliced genes. Many genes in C. elegans are organized in operons where genes are closely clustered, typically separated by only ~100 nucleotides, and transcribed by an upstream promoter. The transcripts of downstream genes are trans-spliced to an SL2 spliced leader. The polycistronic precursor RNA is processed into individual transcripts by 3' end formation and trans-splicing. Although the SL2 spliced leader does not appear to be used for other gene arrangements, there is a relatively small number of genes whose transcripts are processed by SL2 but are not close to another gene in the same orientation. Although these genes do not appear to be members of classical C. elegans operons, we investigated whether these might represent unusual operons with long spacing or a different, nonoperon mechanism for specifying SL2 trans-splicing. We show transcription of the entire region between the SL2 trans-spliced gene and the next upstream gene, sometimes several kilobases distant, suggesting that these represent exceptional operons. We also report a second type of atypical "alternative" operon, in which 3' end formation and trans-splicing by SL2 occur within an intron. In this case, the processing sometimes results in a single transcript, and sometimes in two separate mRNAs.

Ab initio identification of transcription start sites in the Rhesus macaque genome by histone modification and RNA-Seq

Rhesus macaque is a widely used primate model organism. Its genome annotations are however still largely comparative computational predictions derived mainly from human genes, which precludes studies on the macaque-specific genes, gene isoforms or their regulations. Here we took advantage of histone H3 lysine 4 trimethylation (H3K4me3)’s ability to mark transcription start sites (TSSs) and the recently developed ChIP-Seq and RNA-Seq technology to survey the transcript structures. We generated 14 013 757 sequence tags by H3K4me3 ChIP-Seq and obtained 17 322 358 paired end reads for mRNA, and 10 698 419 short reads for sRNA from the macaque brain. By integrating these data with genomic sequence features and extending and improving a state-of-the-art TSS prediction algorithm, we ab initio predicted and verified 17 933 of previously electronically annotated TSSs at 500-bp resolution. We also predicted approximately 10 000 novel TSSs. These provide an important rich resource for close examination of the species-specific transcript structures and transcription regulations in the Rhesus macaque genome. Our approach exemplifies a relatively inexpensive way to generate a reasonably reliable TSS map for a large genome. It may serve as a guiding example for similar genome annotation efforts targeted at other model organisms.

Signal Transducers and Activators of Transcription-1 (STAT1) Regulates microRNA Transcription in Interferon γ-Stimulated HeLa Cells

BackgroundConstructing and modeling the gene regulatory network is one of the central themes of systems biology. With the growing understanding of the mechanism of microRNA biogenesis and its biological function, establishing a microRNA-mediated gene regulatory network is not only desirable but also achievable.MethodologyIn this study, we propose a bioinformatics strategy to construct the microRNA-mediated regulatory network using genome-wide binding patterns of transcription factor(s) and RNA polymerase II (RPol II), derived using chromatin immunoprecipitation following next generation sequencing (ChIP-seq) technology. Our strategy includes three key steps, identification of transcription start sites and promoter regions of primary microRNA transcripts using RPol II binding patterns, selection of cooperating transcription factors that collaboratively function with the transcription factors targeted by ChIP-seq assay, and construction of the network that contains regulatory cascades of both transcription factors and microRNAs.Principal FindingsUsing CAMDA (Critical Assessment of Massive Data Analysis) 2009 data set that includes ChIP-seq data on RPol II and STAT1 (signal transducers and activators of transcription 1) in HeLa S3 cells in control condition and with interferon γ stimulation, we first identified promoter regions of 83 microRNAs in HeLa cells. We then identified two potential STAT1 collaborating factors, AP-1 and C/EBP (CCAAT enhancer-binding proteins), and further established eight feedback network elements that may regulate cellular response during interferon γ stimulation.ConclusionsThis study offers a bioinformatics strategy to provide testable hypotheses on the mechanisms of microRNA-mediated transcriptional regulation, based upon genome-wide protein-DNA interaction data derived from ChIP-seq experiments.

Accurate and simple sizing of primer extension products using a non-radioactive approach facilitates identification of transcription initiation sites

An improved method of non-radioactive identification of transcription start sites is presented in which the use of 7-deaza dGTP in the primer extension reaction allows the product to be directly aligned to cycle sequencing traces on an automated sequencer. This removes the documented need to apply corrections for mobility differences.

Comprehensive gene expression analysis of 5′-end of mRNA identified novel intronic transcripts associated with hepatocellular carcinoma

To elucidate the molecular feature of human hepatocellular carcinoma (HCC), we performed 5′-end serial analysis of gene expression (5′SAGE), which allows genome-wide identification of transcription start sites in addition to quantification of mRNA transcripts. Three 5′SAGE libraries were generated from normal human liver (NL), non-B, non-C HCC tumor (T), and background non-tumor tissues (NT). We obtained 226,834 tags from these libraries and mapped them to the genomic sequences of a total of 8,410 genes using RefSeq database. We identified several novel transcripts specifically expressed in HCC including those mapped to the intronic regions. Among them, we confirmed the transcripts initiated from the introns of a gene encoding acyl-coenzyme A oxidase 2 ( ACOX2). The expression of these transcript variants were up-regulated in HCC and showed a different pattern compared with that of ordinary ACOX2 mRNA. The present results indicate that the transcription initiation of a subset of genes may be distinctively altered in HCC, which may suggest the utility of intronic RNAs as surrogate tumor markers.

Genome-Wide Identification of Transcription Start Sites, Promoters and Transcription Factor Binding Sites in E. coli

Despite almost 40 years of molecular genetics research in Escherichia coli a major fraction of its Transcription Start Sites (TSSs) are still unknown, limiting therefore our understanding of the regulatory circuits that control gene expression in this model organism. RegulonDB (http://regulondb.ccg.unam.mx/) is aimed at integrating the genetic regulatory network of E. coli K12 as an entirely bioinformatic project up till now. In this work, we extended its aims by generating experimental data at a genome scale on TSSs, promoters and regulatory regions. We implemented a modified 5′ RACE protocol and an unbiased High Throughput Pyrosequencing Strategy (HTPS) that allowed us to map more than 1700 TSSs with high precision. From this collection, about 230 corresponded to previously reported TSSs, which helped us to benchmark both our methodologies and the accuracy of the previous mapping experiments. The other ca 1500 TSSs mapped belong to about 1000 different genes, many of them with no assigned function. We identified promoter sequences and type of σ factors that control the expression of about 80% of these genes. As expected, the housekeeping σ70 was the most common type of promoter, followed by σ38. The majority of the putative TSSs were located between 20 to 40 nucleotides from the translational start site. Putative regulatory binding sites for transcription factors were detected upstream of many TSSs. For a few transcripts, riboswitches and small RNAs were found. Several genes also had additional TSSs within the coding region. Unexpectedly, the HTPS experiments revealed extensive antisense transcription, probably for regulatory functions. The new information in RegulonDB, now with more than 2400 experimentally determined TSSs, strengthens the accuracy of promoter prediction, operon structure, and regulatory networks and provides valuable new information that will facilitate the understanding from a global perspective the complex and intricate regulatory network that operates in E. coli.

Heterogeneity of Arabidopsis core promoters revealed by high‐density TSS analysis

Our limited understanding of plant promoters does not allow us to recognize any core promoter elements for the majority of plant promoters. To understand the promoter architecture of Arabidopsis, we used the combined approach of in silico detection of novel core promoter elements and large-scale determination of transcription start sites (TSSs). To this end, we developed a novel methodology for TSS identification, using a combination of the cap-trapper and massively parallel signature sequencing methods. This technique, CT-MPSS, allowed us to identify 158 237 Arabidopsis TSS tags corresponding to 38 311 TSS loci, which provides an opportunity for quantitative analysis of plant promoters. The expression characteristics of these promoters were analyzed with respect to core promoter elements detected by our in silico analyses, revealing that Arabidopsis promoters contain two main types of elements with exclusive characteristics, the TATA type and the GA type. The TATA-type promoters tend to be associated with the Y Patch and the Inr motif, and cause high expression with sharp-peak TSS clusters. By contrast, the GA type produces broad-type TSS clusters. Unlike mammalian promoters, plant promoters are not associated with CpG islands. However, plant-specific GA-type promoters share some characteristics with mammalian CpG-type promoters.

Identification of Transcription Start Sites and Preferential Expression of Select CB2 Transcripts in Mouse and Human B Lymphocytes

Marijuana cannabinoids, the endocannabinoids, and cannabinoid cell receptors have been shown to play important roles in immune regulation particularly as potent modulators of anti-inflammatory cytokines. The predominant cannabinoid receptor involved in this immune regulation is cannabinoid receptor 2 (CB(2)), which is predominantly expressed in B lymphocytes. However, the promoter region and mechanisms of CB(2) gene regulation are unknown in this immune cell type. Utilizing a combination of bioinformatics, 5' rapid amplification of cDNA ends (5' RACE), real-time reverse transcription-polymerase chain reaction, DNA sequencing, and luciferase reporter assays, we show that human B cells express one CB(2) transcript while mouse B cells express three CB(2) transcripts, with specific transcript selection occurring during B cell activation by lipopolysaccharide. Alignment of our sequenced RACE products to either the mouse or human genome, along with the GenBank submitted mRNA sequences, revealed that the transcripts we isolated contained previously unidentified transcriptional start sites (TSS). In addition, expression construct testing of the genomic region containing the TSSs of the mouse CB(2) exon 1 transcripts showed an eightfold increase of promoter activity over baseline. These data show for the first time that human B cells use only one TSS for CB(2) while mouse B cells use multiple TSSs and that the mouse TSSs are in a genomic area with promoter activity, thus suggesting the location of the gene promoter region. Defining these TSSs also provides clues to the various gene regulatory factors involved in the expression of CB(2) during B cell activation.

Genome-Wide Discovery of cis-Elements in Promoter Sequences Using Gene Expression

The availability of complete or nearly complete genome sequences, a large number of 5' expressed sequence tags, and significant public expression data allow for a more accurate identification of cis-elements regulating gene expression. We have implemented a global approach that takes advantage of available expression data, genomic sequences, and transcript information to predict cis-elements associated with specific expression patterns. The key components of our approach are: (1) precise identification of transcription start sites, (2) specific locations of cis-elements relative to the transcription start site, and (3) assessment of statistical significance for all sequence motifs. By applying our method to promoters of Arabidopsis thaliana and Mus musculus, we have identified motifs that affect gene expression under specific environmental conditions or in certain tissues. We also found that the presence of the TATA box is associated with increased variability of gene expression. Strong correlation between our results and experimentally determined motifs shows that the method is capable of predicting new functionally important cis-elements in promoter sequences.

Transcript analysis of nrrF, a Fur repressed sRNA of Neisseria gonorrhoeae

Like most microorganisms, Neisseria gonorrhoeae alters gene expression in response to iron availability. The ferric uptake regulator Fur has been shown to be involved in controlling this response, but the extent of this involvement remains unknown. It is known that in addition to working directly to repress gene expression, Fur may also work indirectly by controlling additional regulatory elements. Using in silico analysis, we identified a putative small RNA (sRNA) homolog of the meningococcal nrrF locus, and demonstrate that this sRNA is iron-repressible, suggesting that this is the gonococcal analog of the rhyB locus in Escherichia coli. Quantitative real-time RT-PCR analysis indicates that this transcript may also be temporally regulated. Transcript analysis identified the 5′ start of the transcript, using a single reaction, fluorescent-based, primer extension assay. This protocol allows for the rapid identification of transcriptional start sites of RNA transcripts, and could be used for high-throughput transcript mapping.

Noncoding transcription controls downstream promoters to regulate T-cell receptor α recombination

The T early alpha (TEA) promoter in the murine Tcra locus generates noncoding transcripts that extend across the 65 kb Jalpha array. Here, we have analyzed the significance of TEA transcription for Tcra locus regulation through the targeted introduction of a transcription terminator downstream of the TEA promoter. We demonstrate that noncoding transcription driven by this single promoter can instruct both positively and negatively the activity of downstream Jalpha promoters, and can similarly instruct alterations in Jalpha chromatin structure and Jalpha recombination. TEA transcription activates promoters associated with relatively proximal Jalpha segments and stimulates histone acetylation, histone methylation and chromatin accessibility in this region. In contrast, at more distal locations, TEA transcription inhibits promoter activity through transcriptional interference and suppresses chromatin accessibility. In combination, these effects target initial Valpha-to-Jalpha recombination to TEA-proximal Jalpha segments and promote the ordered usage of the Jalpha array. The ability of TEA transcription to coordinate the activity of multiple downstream promoters maximizes the biological potential of the Jalpha array and diversifies the Tcra repertoire.