Strand-specific deep sequencing of the transcriptome

Methodologies for bacterial ribonuclease characterization using RNA-seq

Bacteria adjust gene expression at the post-transcriptional level through an intricate network of small regulatory RNAs and RNA-binding proteins, including ribonucleases (RNases). RNases play an essential role in RNA metabolism, regulating RNA stability, decay, and activation. These enzymes exhibit species-specific effects on gene expression, bacterial physiology, and different strategies of target recognition. Recent advances in high-throughput RNA sequencing (RNA-seq) approaches have provided a better understanding of the roles and modes of action of bacterial RNases. Global studies aiming to identify direct targets of RNases have highlighted the diversity of RNase activity and RNA-based mechanisms of gene expression regulation. Here, we review recent RNA-seq approaches used to study bacterial RNases, with a focus on the methods for identifying direct RNase targets.

Alternative σ Factors Regulate Overlapping as Well as Distinct Stress Response and Metabolic Functions in Listeria monocytogenes under Stationary Phase Stress Condition

Listeria monocytogenes can regulate and fine-tune gene expression, to adapt to diverse stress conditions encountered during foodborne transmission. To further understand the contributions of alternative sigma (σ) factors to the regulation of L. monocytogenes gene expression, RNA-Seq was performed on L. monocytogenes strain 10403S and five isogenic mutants (four strains bearing in-frame null mutations in three out of four alternative σ factor genes, ΔCHL, ΔBHL, ΔBCL, and ΔBCH, and one strain bearing null mutations in all four genes, ΔBCHL), grown to stationary phase. Our data showed that 184, 35, 34, and 20 genes were positively regulated by σ^B, σ^L, σ^H, and σ^C (posterior probability > 0.9 and Fold Change (FC) > 5.0), respectively. Moreover, σ^B-dependent genes showed the highest FC (based on comparisons between the ΔCHL and the ΔBCHL strain), with 44 genes showing an FC > 100; only four σ^L-dependent, and no σ^H- or σ^C-dependent genes showed FC >100. While σ^B-regulated genes identified in this study are involved in stress-associated functions and metabolic pathways, σ^L appears to largely regulate genes involved in a few specific metabolic pathways, including positive regulation of operons encoding phosphoenolpyruvate (PEP)-dependent phosphotransferase systems (PTSs). Overall, our data show that (i) σ^B and σ^L directly and indirectly regulate genes involved in several energy metabolism-related functions; (ii) alternative σ factors are involved in complex regulatory networks and appear to have epistatic effects in stationary phase cells; and (iii) σ^B regulates multiple stress response pathways, while σ^L and σ^H positively regulate a smaller number of specific pathways.

Comparative Transcriptome Analysis of Streptomyces Clavuligerus in Response to Favorable and Restrictive Nutritional Conditions

Background: Clavulanic acid (CA), a β-lactamase inhibitor, is industrially produced by the fermentation of Streptomyces clavuligerus. The efficiency of CA production is associated with media composition, culture conditions and physiological and genetic strain characteristics. However, the molecular pathways that govern CA regulation in S. clavuligerus remain unknown. Methods and Results: Here we used RNA-seq to perform a comparative transcriptome analysis of S. clavuligerus ATCC 27064 wild-type strain grown in both a favorable soybean-based medium and in limited media conditions to further contribute to the understanding of S. clavuligerus metabolism and its regulation. A total of 350 genes were found to be differentially expressed between conditions; 245 genes were up-regulated in favorable conditions compared to unfavorable. Conclusion: The up-regulated expression of many regulatory and biosynthetic CA genes was positively associated with the favorable complex media condition along with pleiotropic regulators, including proteases and some genes whose biological function have not been previously reported. Knowledge from differences between transcriptomes from complex/defined media represents an advance in the understanding of regulatory paths involved in S. clavuligerus’ metabolic response, enabling the rational design of future experiments.

RNA-sequencing in ophthalmology research: considerations for experimental design and analysis

High-throughput, massively parallel sequence analysis has revolutionized the way that researchers design and execute scientific investigations. Vast amounts of sequence data can be generated in short periods of time. Regarding ophthalmology and vision research, extensive interrogation of patient samples for underlying causative DNA mutations has resulted in the discovery of many new genes relevant to eye disease. However, such analysis remains functionally limited. RNA-sequencing accurately snapshots thousands of genes, capturing many subtypes of RNA molecules, and has become the gold standard for transcriptome gene expression quantification. RNA-sequencing has the potential to advance our understanding of eye development and disease; it can reveal new candidates to improve our molecular diagnosis rates and highlight therapeutic targets for intervention. But with a wide range of applications, the design of such experiments can be problematic, no single optimal pipeline exists, and therefore, several considerations must be undertaken for optimal study design. We review the key steps involved in RNA-sequencing experimental design and the downstream bioinformatic pipelines used for differential gene expression. We provide guidance on the application of RNA-sequencing to ophthalmology and sources of open-access eye-related data sets.

Hidden Gems in the Transcriptome Maps of Competent Streptococci

Natural transformation is regarded as an important mechanism in bacteria that allows for adaptation to different environmental stressors by ensuring genome plasticity. Since the discovery of this phenomenon in Streptococcus pneumoniae, remarkable progress has been made in the understanding of the molecular mechanisms and pathways coordinating this process. Recently, the advent of high-throughput sequencing allows the posing of questions that address the system at a larger scale but also allow for the creation of high-resolution maps of transcription. Thus, while much is already known about genetic competence in streptococci, recent studies continue to reveal intricate novel regulation pathways and components. In this perspective article, we highlight the use of transcriptional profiling and mapping as a valuable resource in the identification and characterization of “hidden gems” pertinent to the natural transformation system. Such strategies have recently been employed in a variety of different species. In S. mutans, for example, genome editing combined with the power of promoter mapping and RNA-Seq allowed for the identification of a link between the ComCDE and the ComRS systems, a ComR positive feedback loop mediated by SigX, and the XrpA peptide, encoded within sigX, which inhibits competence. In S. pneumoniae, a novel member of the competence regulon termed BriC was found to be directly under control of ComE and to promote biofilm formation and nasopharyngeal colonization but not competence. Together these new technologies enable us to discover new links and to revisit old pathways in the compelling study of natural genetic transformation.

Circular RNA: New Regulatory Molecules

Circular RNA are a family of covalently closed circular RNA molecules, formed from pre-mRNA of coding genes by means of splicing (canonical and alternative noncanonical splicing). Maturation of circular RNA is regulated by cis- and trans-elements. Complete list of biological functions of these RNA is not yet compiled; however, their capacity to interact with specific microRNA and play a role of a depot attracts the greatest interest. This property makes circular RNA active regulatory transcription factors. Circular RNA have many advantages over their linear analogs: synthesis of these molecules is conservative, they are universal, characterized by clearly determined specificity, and are resistant to exonucleases. In addition, the level of their expression is often higher than that of their linear forms. It should be noted that expression of circular RNA is tissue-specific. Moreover, some correlations between changes in the repertoire and intensity of expression of circular RNA and the development of some pathologies have been detected. Circular RNA have certain advantages and can serve as new biomarkers for the diagnosis, prognosis, and evaluation of response to therapy.

Capturing the 'ome': the expanding molecular toolbox for RNA and DNA library construction

All sequencing experiments and most functional genomics screens rely on the generation of libraries to comprehensively capture pools of targeted sequences. In the past decade especially, driven by the progress in the field of massively parallel sequencing, numerous studies have comprehensively assessed the impact of particular manipulations on library complexity and quality, and characterized the activities and specificities of several key enzymes used in library construction. Fortunately, careful protocol design and reagent choice can substantially mitigate many of these biases, and enable reliable representation of sequences in libraries. This review aims to guide the reader through the vast expanse of literature on the subject to promote informed library generation, independent of the application.

The Listeria monocytogenes Bile Stimulon under Acidic Conditions Is Characterized by Strain-Specific Patterns and the Upregulation of Motility, Cell Wall Modification Functions, and the PrfA Regulon

Listeria monocytogenes uses a variety of transcriptional regulation strategies to adapt to the extra-host environment, the gastrointestinal tract, and the intracellular host environment. While the alternative sigma factor SigB has been proposed to be a key transcriptional regulator that facilitates L. monocytogenes adaptation to the gastrointestinal environment, the L. monocytogenes' transcriptional response to bile exposure is not well-understood. RNA-seq characterization of the bile stimulon was performed in two L. monocytogenes strains representing lineages I and II. Exposure to bile at pH 5.5 elicited a large transcriptomic response with ~16 and 23% of genes showing differential transcription in 10403S and H7858, respectively. The bile stimulon includes genes involved in motility and cell wall modification mechanisms, as well as genes in the PrfA regulon, which likely facilitate survival during the gastrointestinal stages of infection that follow bile exposure. The fact that bile exposure induced the PrfA regulon, but did not induce further upregulation of the SigB regulon (beyond that expected by exposure to pH 5.5), suggests a model where at the earlier stages of gastrointestinal infection (e.g., acid exposure in the stomach), SigB-dependent gene expression plays an important role. Subsequent exposure to bile induces the PrfA regulon, potentially priming L. monocytogenes for subsequent intracellular infection stages. Some members of the bile stimulon showed lineage- or strain-specific distribution when 27 Listeria genomes were analyzed. Even though sigB null mutants showed increased sensitivity to bile, the SigB regulon was not found to be upregulated in response to bile beyond levels expected by exposure to pH 5.5. Comparison of wildtype and corresponding ΔsigB strains newly identified 26 SigB-dependent genes, all with upstream putative SigB-dependent promoters.

RNA Sequencing and Analysis in Microorganisms for Metabolic Network Reconstruction

There is a strict interplay between metabolic networks and transcriptional regulation in bacteria; indeed, the transcriptome regulation, affecting the expression of large gene sets, can be used to predict the likely "on" or "off" state of metabolic genes as a function of environmental factors. Up to date, many bacterial transcriptomes have been studied by RNAseq, hundreds of experiments have been performed, and Giga bases of sequences have been produced. All this transcriptional information could potentially be integrated into metabolic networks in order to obtain a more comprehensive view of their regulation and to increase their prediction power.To get high-quality transcriptomic data, to be integrated into metabolic networks, it is paramount to clearly know how to produce highly informative RNA sequencing libraries and how to manage RNA sequencing data.In this chapter, we will get across the main steps of an RNAseq experiment: from removal of ribosomal RNAs, to strand-specific library preparation, till data analysis and integration. We will try to share our experience and know-how, to give you a precise protocol to follow, and some useful recommendations or tips and tricks to adopt in order to go straightforward toward a successful RNAseq experiment.

Bursal transcriptome profiling of different inbred chicken lines reveals key differentially expressed genes at 3 days post-infection with very virulent infectious bursal disease virus

Infectious bursal disease is a highly contagious disease in the poultry industry and causes immunosuppression in chickens. Genome-wide regulations of immune response genes of inbred chickens with different genetic backgrounds, following very virulent infectious bursal disease virus (vvIBDV) infection are poorly characterized. Therefore, this study aims to analyse the bursal tissue transcriptome of six inbred chicken lines 6, 7, 15, N, O and P following infection with vvIBDV strain UK661 using strand-specific next-generation sequencing, by highlighting important genes and pathways involved in the infected chicken during peak infection at 3 days post-infection. All infected chickens succumbed to the infection without major variations among the different lines. However, based on the viral loads and bursal lesion scoring, lines P and 6 can be considered as the most susceptible lines, while lines 15 and N were regarded as the least affected lines. Transcriptome profiling of the bursa identified 4588 genes to be differentially expressed, with 2985 upregulated and 1642 downregulated genes, in which these genes were commonly or uniquely detected in all or several infected lines. Genes that were upregulated are primarily pro-inflammatory cytokines, chemokines and IFN-related. Various genes that are associated with B-cell functions and genes related to apoptosis were downregulated, together with the genes involved in p53 signalling. In conclusion, bursal transcriptome profiles of different inbred lines showed differential expressions of pro-inflammatory cytokines and chemokines, Th1 cytokines, JAK-STAT signalling genes, MAPK signalling genes, and their related pathways following vvIBDV infection.

UClncR: Ultrafast and comprehensive long non-coding RNA detection from RNA-seq

Long non-coding RNA (lncRNA) is a large class of gene transcripts with regulatory functions discovered in recent years. Many more are expected to be revealed with accumulation of RNA-seq data from diverse types of normal and diseased tissues. However, discovering novel lncRNAs and accurately quantifying known lncRNAs is not trivial from massive RNA-seq data. Herein we describe UClncR, an Ultrafast and Comprehensive lncRNA detection pipeline to tackle the challenge. UClncR takes standard RNA-seq alignment file, performs transcript assembly, predicts lncRNA candidates, quantifies and annotates both known and novel lncRNA candidates, and generates a convenient report for downstream analysis. The pipeline accommodates both un-stranded and stranded RNA-seq so that lncRNAs overlapping with other genes can be predicted and quantified. UClncR is fully parallelized in a cluster environment yet allows users to run samples sequentially without a cluster. The pipeline can process a typical RNA-seq sample in a matter of minutes and complete hundreds of samples in a matter of hours. Analysis of predicted lncRNAs from two test datasets demonstrated UClncR’s accuracy and their relevance to sample clinical phenotypes. UClncR would facilitate researchers’ novel lncRNA discovery significantly and is publically available at http://bioinformaticstools.mayo.edu/research/UClncR.

Home Alone: Elimination of All but One Alternative Sigma Factor in Listeria monocytogenes Allows Prediction of New Roles for σB

Among Listeria monocytogenes' four alternative σ factors, σ^B controls the largest regulon. As σ^B-dependent transcription of some genes may be masked by overlaps among regulons, and as some σ^B-dependent genes are expressed only under very specific conditions, we hypothesized that the σ^B regulon is not yet fully defined. To further extend our understanding of the σ^B regulon, we used RNA-seq to identify σ^B-dependent genes in an L. monocytogenes strain that expresses σ^B following rhamnose induction, and in which genes encoding the other alternative sigma factors have been deleted. Analysis of RNA-seq data with multiple bioinformatics approaches, including a sliding window method that detects differentially transcribed 5' untranslated regions (UTRs), identified 105 σ^B-dependent transcription units (TUs) comprising 201 genes preceded by σ^B-dependent promoters. Of these 105 TUs, 7 TUs comprising 15 genes had not been identified previously as σ^B-dependent. An additional 23 genes not reported previously as σ^B-dependent were identified in 9 previously recognized σ^B-dependent TUs. Overall, 38 of these 201 genes had not been identified previously as members of the L. monocytogenes σ^B regulon. These newly identified σ^B-dependent genes encode proteins annotated as being involved in transcriptional regulation, oxidative and osmotic stress response, and in metabolism of energy, carbon and nucleotides. In total, 18 putative σ^B-dependent promoters were newly identified. Interestingly, a number of genes previously identified as σ^B-dependent did not show significant evidence for σ^B-dependent transcription in our experiments. Based on promoter analyses, a number of these genes showed evidence for co-regulation by σ^B and other transcriptional factors, suggesting that some σ^B-dependent genes require additional transcriptional regulators along with σ^B for transcription. Over-expression of a single alternative sigma factor in the absence of all other alternative sigma factors allowed us to: (i) identify new σ^B-dependent functions in L. monocytogenes, such as regulation of genes involved in 1,2-propanediol utilization (LMRG_00594-LMRG_00611) and biosynthesis of pyrimidine nucleotides (LMRG_00978-LMRG_00985); and (ii) identify new σ^B-dependent genes involved in stress response and pathogenesis functions. These data further support that σ^B not only regulates stress response functions, but also plays a broad role in L. monocytogenes homeostasis and resilience.

Deep sequencing approaches for the analysis of prokaryotic transcriptional boundaries and dynamics

The identification of the protein-coding regions of a genome is straightforward due to the universality of start and stop codons. However, the boundaries of the transcribed regions, conditional operon structures, non-coding RNAs and the dynamics of transcription, such as pausing of elongation, are non-trivial to identify, even in the comparatively simple genomes of prokaryotes. Traditional methods for the study of these areas, such as tiling arrays, are noisy, labour-intensive and lack the resolution required for densely-packed bacterial genomes. Recently, deep sequencing has become increasingly popular for the study of the transcriptome due to its lower costs, higher accuracy and single nucleotide resolution. These methods have revolutionised our understanding of prokaryotic transcriptional dynamics. Here, we review the deep sequencing and data analysis techniques that are available for the study of transcription in prokaryotes, and discuss the bioinformatic considerations of these analyses.

Strand-specific RNA-seq analysis of the Lactobacillus delbrueckii subsp. bulgaricus transcriptome

Lactobacillus delbrueckii subsp. bulgaricus 2038 (Lb. bulgaricus 2038) is an industrial bacterium that is used as a starter for dairy products. We proposed several hypotheses concerning its industrial features previously. Here, we utilized RNA-seq to explore the transcriptome of Lb. bulgaricus 2038 from four different growth phases under whey conditions. The most abundantly expressed genes in the four stages were mainly involved in translation (for the logarithmic stage), glycolysis (for control/lag stages), lactic acid production (all the four stages), and 10-formyl tetrahydrofolate production (for the stationary stage). The high expression of genes like d-lactate dehydrogenase was thought as a result of energy production, and consistent expression of EPS synthesis genes, the restriction-modification (RM) system and the CRISPR/Cas system were validated for explaining the advantage of this strain in yoghurt production. Several postulations, like NADPH production through GapN bypass, converting aspartate into carbon-skeleton intermediates, and formate production through degrading GTP, were proved not working under these culture conditions. The high expression of helicase genes and co-expressed amino acids/oligopeptides transporting proteins indicated that the helicase might mediate the strain obtaining nitrogen source from the environment. The transport system of Lb. bulgaricus 2038 was found to be regulated by antisense RNA, hinting the potential application of non-coding RNA in regulating lactic acid bacteria (LAB) gene expression. Our study has primarily uncovered Lb. bulgaricus 2038 transcriptome, which could gain a better understanding of the regulation system in Lb. bulgaricus and promote its industrial application.

Avoidance of stochastic RNA interactions can be harnessed to control protein expression levels in bacteria and archaea

A critical assumption of gene expression analysis is that mRNA abundances broadly correlate with protein abundance, but these two are often imperfectly correlated. Some of the discrepancy can be accounted for by two important mRNA features: codon usage and mRNA secondary structure. We present a new global factor, called mRNA:ncRNA avoidance, and provide evidence that avoidance increases translational efficiency. We also demonstrate a strong selection for the avoidance of stochastic mRNA:ncRNA interactions across prokaryotes, and that these have a greater impact on protein abundance than mRNA structure or codon usage. By generating synonymously variant green fluorescent protein (GFP) mRNAs with different potential for mRNA:ncRNA interactions, we demonstrate that GFP levels correlate well with interaction avoidance. Therefore, taking stochastic mRNA:ncRNA interactions into account enables precise modulation of protein abundance.

DOI:http://dx.doi.org/10.7554/eLife.13479.001

Many genes carry information for making proteins. To make a protein, a working copy of the information stored in DNA is first copied into a molecule of messenger RNA. These RNA messages are then interpreted by the ribosome, the molecular machine that makes proteins. Many messages are produced from each gene, and each message can be read multiple times. Thus, it should follow that the number of messages produced dictates the number of proteins made. However, this is not the case and the number of proteins produced cannot be completely predicted from knowing the number of messenger RNAs.

Cells control how much of a given protein they produce through interactions between the messenger RNAs and other regulatory RNAs. The regulatory RNAs bind directly to a message and impede protein production. Because there are millions of RNAs in a cell, these interactions have evolved to be highly specific. Nevertheless, it seems inevitable that messenger RNAs would encounter other RNAs too, which could short-circuit gene regulation and lead to less protein being produced.

Umu et al. have now asked if such short-circuit events are selected against during evolution. Computational tools were used to predict the strength of binding between the RNAs found in the dominant forms of microbial life on Earth: the bacteria and the archaea. This approach revealed that the majority of messenger RNAs bind more weakly to the most common RNA molecules found in cells than would be expected by chance. Weakened binding should prevent the RNA molecules from becoming tangled with each other and ensure that protein levels are not perturbed by unintended interactions between highly expressed messages and other RNAs.

To test this hypothesis further, Umu et al. generated versions of the gene for a green fluorescent protein that differed only in how well their messenger RNAs could avoid interacting with the most abundant RNAs in E. coli cells. Those messengers that were designed to avoid interacting with other RNAs yielded far more protein than those that were not. The findings show that taking this kind of avoidance into account can improve predictions about how much protein will be produced and should therefore make it easier to control protein production in experimental systems.

Finally, the messenger RNAs of some bacteria do not show such clear avoidance. However, these bacteria have a more complex internal cell structure. This finding hints at an alternative means for avoiding short-circuiting events that could be used by more complicated cells, such of those of animals and plants, which also contain much larger numbers of RNAs.

DOI:http://dx.doi.org/10.7554/eLife.13479.002

On the study of microbial transcriptomes using second- and third-generation sequencing technologies

Second-generation sequencing technologies transformed the study of microbial transcriptomes. They helped reveal the transcription start sites and antisense transcripts of microbial species, improving the microbial genome annotation. Quantification of genome-wide gene expression levels allowed for functional studies of microbial research. Ever-evolving sequencing technologies are reshaping approaches to studying microbial transcriptomes. Recently, Oxford Nanopore Technologies delivered a sequencing platform called MinION, a third-generation sequencing technology, to the research community. We expect it to be the next sequencing technology that enables breakthroughs in life science fields. The studies of microbial transcriptomes will be no exception. In this paper, we review microbial transcriptomics studies using second- generation sequencing technology. We also discuss the prospect of microbial transcriptomics studies with thirdgeneration sequencing.

Transcriptome sequencing analysis of novel sRNAs of Kineococcus radiotolerans in response to ionizing radiation

Kineococcus radiotolerans is a Gram-positive, radio-resistant bacterium isolated from a radioactive environment. The small noncoding RNAs (sRNAs) in bacteria are reported to play roles in the immediate response to stress and/or the recovery from stress. The analysis of K. radiotolerans transcriptome sequencing results can identify these sRNAs in a genome-wide detection, using RNA sequencing (RNA-seq) by the deep sequencing technique. In this study, the raw data of radiation-exposed samples (RS) and control samples (CS) were acquired separately from the sequencing platform. There were 217 common sRNA candidates in the two samples screened in the genome-wide scale by bioinformatics analysis. There were 43 differentially expressed sRNA candidates, including 28 up-regulated and 15 down-regulated ones. The down-regulated sRNAs were selected for the sRNA target prediction, of which 12 sRNAs that may modulate the genes related to the transcription regulation and DNA repair were considered as the candidates involved in the radio-resistance regulation system.

Integration of multi-omics data of a genome-reduced bacterium: Prevalence of post-transcriptional regulation and its correlation with protein abundances

We developed a comprehensive resource for the genome-reduced bacterium Mycoplasma pneumoniae comprising 1748 consistently generated ‘-omics’ data sets, and used it to quantify the power of antisense non-coding RNAs (ncRNAs), lysine acetylation, and protein phosphorylation in predicting protein abundance (11%, 24% and 8%, respectively). These factors taken together are four times more predictive of the proteome abundance than of mRNA abundance. In bacteria, post-translational modifications (PTMs) and ncRNA transcription were both found to increase with decreasing genomic GC-content and genome size. Thus, the evolutionary forces constraining genome size and GC-content modify the relative contributions of the different regulatory layers to proteome homeostasis, and impact more genomic and genetic features than previously appreciated. Indeed, these scaling principles will enable us to develop more informed approaches when engineering minimal synthetic genomes.

Transcriptome profiling of a spirodiclofen susceptible and resistant strain of the European red mite Panonychus ulmi using strand-specific RNA-seq

BACKGROUND

The European red mite, Panonychus ulmi, is among the most important mite pests in fruit orchards, where it is controlled primarily by acaricide application. However, the species rapidly develops pesticide resistance, and the elucidation of resistance mechanisms for P. ulmi has not kept pace with insects or with the closely related spider mite Tetranychus urticae. The main reason for this lack of knowledge has been the absence of genomic resources needed to investigate the molecular biology of resistance mechanisms.

RESULTS

Here, we provide a comprehensive strand-specific RNA-seq based transcriptome resource for P. ulmi derived from strains susceptible and resistant to the widely used acaricide spirodiclofen. From a de novo assembly of the P. ulmi transcriptome, we manually annotated detoxification enzyme families, target-sites of commonly used acaricides, and horizontally transferred genes implicated in plant-mite interactions and pesticide resistance. In a comparative analysis that incorporated sequences available for Panonychus citri, T. urticae, and insects, we identified radiations for detoxification gene families following the divergence of Panonychus and Tetranychus genera. Finally, we used the replicated RNA-seq data from the spirodiclofen susceptible and resistant strains to describe gene expression changes associated with resistance. A cytochrome P450 monooxygenase, as well as multiple carboxylcholinesterases, were differentially expressed between the susceptible and resistant strains, and provide a molecular entry point for understanding resistance to spirodiclofen, widely used to control P. ulmi populations.

CONCLUSIONS

The new genomic resources and data that we present in this study for P. ulmi will substantially facilitate molecular studies of underlying mechanisms involved in acaricide resistance.

Spatio-temporal regulation of circular RNA expression during porcine embryonic brain development

Background

Recently, thousands of circular RNAs (circRNAs) have been discovered in various tissues and cell types from human, mouse, fruit fly and nematodes. However, expression of circRNAs across mammalian brain development has never been examined.

Results

Here we profile the expression of circRNA in five brain tissues at up to six time-points during fetal porcine development, constituting the first report of circRNA in the brain development of a large animal. An unbiased analysis reveals a highly complex regulation pattern of thousands of circular RNAs, with a distinct spatio-temporal expression profile. The amount and complexity of circRNA expression was most pronounced in cortex at day 60 of gestation. At this time-point we find 4634 unique circRNAs expressed from 2195 genes out of a total of 13,854 expressed genes. Approximately 20 % of the porcine splice sites involved in circRNA production are functionally conserved between mouse and human. Furthermore, we observe that “hot-spot” genes produce multiple circRNA isoforms, which are often differentially expressed across porcine brain development. A global comparison of porcine circRNAs reveals that introns flanking circularized exons are longer than average and more frequently contain proximal complementary SINEs, which potentially can facilitate base pairing between the flanking introns. Finally, we report the first use of RNase R treatment in combination with in situ hybridization to show dynamic subcellular localization of circRNA during development.

Conclusions

These data demonstrate that circRNAs are highly abundant and dynamically expressed in a spatio-temporal manner in porcine fetal brain, suggesting important functions during mammalian brain development.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0801-3) contains supplementary material, which is available to authorized users.

External guide sequence technology: a path to development of novel antimicrobial therapeutics

RNase P is a ribozyme originally identified for its role in maturation of tRNAs by cleavage of precursor tRNAs (pre-tRNAs) at the 5'-end termini. RNase P is a ribonucleoprotein consisting of a catalytic RNA molecule and, depending on the organism, one or more cofactor proteins. The site of cleavage of a pre-tRNA is identified by its tertiary structure; and any RNA molecule can be cleaved by RNase P as long as the RNA forms a duplex that resembles the regional structure in the pre-tRNA. When the antisense sequence that forms the duplex with the strand that is subsequently cleaved by RNase P is in a separate molecule, it is called an external guide sequence (EGS). These fundamental observations are the basis for EGS technology, which consists of inhibiting gene expression by utilizing an EGS that elicits RNase P-mediated cleavage of a target mRNA molecule. EGS technology has been used to inhibit expression of a wide variety of genes, and may help development of novel treatments of diseases, including multidrug-resistant bacterial and viral infections.

Sequence-independent characterization of viruses based on the pattern of viral small RNAs produced by the host

Virus surveillance in vector insects is potentially of great benefit to public health. Large-scale sequencing of small and long RNAs has previously been used to detect viruses, but without any formal comparison of different strategies. Furthermore, the identification of viral sequences largely depends on similarity searches against reference databases. Here, we developed a sequence-independent strategy based on virus-derived small RNAs produced by the host response, such as the RNA interference pathway. In insects, we compared sequences of small and long RNAs, demonstrating that viral sequences are enriched in the small RNA fraction. We also noted that the small RNA size profile is a unique signature for each virus and can be used to identify novel viral sequences without known relatives in reference databases. Using this strategy, we characterized six novel viruses in the viromes of laboratory fruit flies and wild populations of two insect vectors: mosquitoes and sandflies. We also show that the small RNA profile could be used to infer viral tropism for ovaries among other aspects of virus biology. Additionally, our results suggest that virus detection utilizing small RNAs can also be applied to vertebrates, although not as efficiently as to plants and insects.

RNA Sequencing and Analysis

RNA sequencing (RNA-Seq) uses the capabilities of high-throughput sequencing methods to provide insight into the transcriptome of a cell. Compared to previous Sanger sequencing- and microarray-based methods, RNA-Seq provides far higher coverage and greater resolution of the dynamic nature of the transcriptome. Beyond quantifying gene expression, the data generated by RNA-Seq facilitate the discovery of novel transcripts, identification of alternatively spliced genes, and detection of allele-specific expression. Recent advances in the RNA-Seq workflow, from sample preparation to library construction to data analysis, have enabled researchers to further elucidate the functional complexity of the transcription. In addition to polyadenylated messenger RNA (mRNA) transcripts, RNA-Seq can be applied to investigate different populations of RNA, including total RNA, pre-mRNA, and noncoding RNA, such as microRNA and long ncRNA. This article provides an introduction to RNA-Seq methods, including applications, experimental design, and technical challenges.

Identification of protein coding regions in RNA transcripts

Massive parallel sequencing of RNA transcripts by next-generation technology (RNA-Seq) generates critically important data for eukaryotic gene discovery. Gene finding in transcripts can be done by statistical (alignment-free) as well as by alignment-based methods. We describe a new tool, GeneMarkS-T, for ab initio identification of protein-coding regions in RNA transcripts. The algorithm parameters are estimated by unsupervised training which makes unnecessary manually curated preparation of training sets. We demonstrate that (i) the unsupervised training is robust with respect to the presence of transcripts assembly errors and (ii) the accuracy of GeneMarkS-T in identifying protein-coding regions and, particularly, in predicting translation initiation sites in modelled as well as in assembled transcripts compares favourably to other existing methods.

Evaluation and application of the strand-specific protocol for next-generation sequencing

Next-generation sequencing (NGS) has become a powerful sequencing tool, applied in a wide range of biological studies. However, the traditional sample preparation protocol for NGS is non-strand-specific (NSS), leading to biased estimates of expression for transcripts overlapped at the antisense strand. Strand-specific (SS) protocols have recently been developed. In this study, we prepared the same RNA sample by using the SS and NSS protocols, followed by sequencing with Illumina HiSeq platform. Using real-time quantitative PCR as a standard, we first proved that the SS protocol more precisely estimates gene expressions compared with the NSS protocol, particularly for those overlapped at the antisense strand. In addition, we also showed that the sequence reads from the SS protocol are comparable with those from conventional NSS protocols in many aspects. Finally, we also mapped a fraction of sequence reads back to the antisense strand of the known genes, originally without annotated genes located. Using sequence assembly and PCR validation, we succeeded in identifying and characterizing the novel antisense genes. Our results show that the SS protocol performs more accurately than the traditional NSS protocol and can be applied in future studies.

An optimized kit-free method for making strand-specific deep sequencing libraries from RNA fragments

Deep sequencing of strand-specific cDNA libraries is now a ubiquitous tool for identifying and quantifying RNAs in diverse sample types. The accuracy of conclusions drawn from these analyses depends on precise and quantitative conversion of the RNA sample into a DNA library suitable for sequencing. Here, we describe an optimized method of preparing strand-specific RNA deep sequencing libraries from small RNAs and variably sized RNA fragments obtained from ribonucleoprotein particle footprinting experiments or fragmentation of long RNAs. Our approach works across a wide range of input amounts (400 pg to 200 ng), is easy to follow and produces a library in 2–3 days at relatively low reagent cost, all while giving the user complete control over every step. Because all enzymatic reactions were optimized and driven to apparent completion, sequence diversity and species abundance in the input sample are well preserved.

circBase: a database for circular RNAs

Recently, several laboratories have reported thousands of circular RNAs (circRNAs) in animals. Numerous circRNAs are highly stable and have specific spatiotemporal expression patterns. Even though a function for circRNAs is unknown, these features make circRNAs an interesting class of RNAs as possible biomarkers and for further research. We developed a database and website, "circBase," where merged and unified data sets of circRNAs and the evidence supporting their expression can be accessed, downloaded, and browsed within the genomic context. circBase also provides scripts to identify known and novel circRNAs in sequencing data. The database is freely accessible through the web server at http://www.circbase.org/.

Assessing the hodgepodge of non-mapped reads in bacterial transcriptomes: real or artifactual RNA chimeras?

BACKGROUND

RNA sequencing methods have already altered our view of the extent and complexity of bacterial and eukaryotic transcriptomes, revealing rare transcript isoforms (circular RNAs, RNA chimeras) that could play an important role in their biology.

RESULTS

We performed an analysis of chimera formation by four different computational approaches, including a custom designed pipeline, to study the transcriptomes of M. pneumoniae and P. aeruginosa, as well as mixtures of both. We found that rare transcript isoforms detected by conventional pipelines of analysis could be artifacts of the experimental procedure used in the library preparation, and that they are protocol-dependent.

CONCLUSION

By using a customized pipeline we show that optimal library preparation protocol and the pipeline to analyze the results are crucial to identify real chimeric RNAs.

Characterization of natural antisense transcript, sclerotia development and secondary metabolism by strand-specific RNA sequencing of Aspergillus flavus

Aspergillus flavus has received much attention owing to its severe impact on agriculture and fermented products induced by aflatoxin. Sclerotia morphogenesis is an important process related to A. flavus reproduction and aflatoxin biosynthesis. In order to obtain an extensive transcriptome profile of A. flavus and provide a comprehensive understanding of these physiological processes, the isolated mRNA of A. flavus CA43 cultures was subjected to high-throughput strand-specific RNA sequencing (ssRNA-seq). Our ssRNA-seq data profiled widespread transcription across the A. flavus genome, quantified vast transcripts (73% of total genes) and annotated precise transcript structures, including untranslated regions, upstream open reading frames (ORFs), alternative splicing variants and novel transcripts. We propose natural antisense transcripts in A. flavus might regulate gene expression mainly on the post-transcriptional level. This regulation might be relevant to tune biological processes such as aflatoxin biosynthesis and sclerotia development. Gene Ontology annotation of differentially expressed genes between the mycelia and sclerotia cultures indicated sclerotia development was related closely to A. flavus reproduction. Additionally, we have established the transcriptional profile of aflatoxin biosynthesis and its regulation model. We identified potential genes linking sclerotia development and aflatoxin biosynthesis. These genes could be used as targets for controlled regulation of aflatoxigenic strains of A. flavus.

Comparison of strand-specific transcriptomes of enterohemorrhagic Escherichia coli O157:H7 EDL933 (EHEC) under eleven different environmental conditions including radish sprouts and cattle feces

Background

Multiple infection sources for enterohemorrhagic Escherichia coli O157:H7 (EHEC) are known, including animal products, fruit and vegetables. The ecology of this pathogen outside its human host is largely unknown and one third of its annotated genes are still hypothetical. To identify genetic determinants expressed under a variety of environmental factors, we applied strand-specific RNA-sequencing, comparing the SOLiD and Illumina systems.

Results

Transcriptomes of EHEC were sequenced under 11 different biotic and abiotic conditions: LB medium at pH4, pH7, pH9, or at 15°C; LB with nitrite or trimethoprim-sulfamethoxazole; LB-agar surface, M9 minimal medium, spinach leaf juice, surface of living radish sprouts, and cattle feces. Of 5379 annotated genes in strain EDL933 (genome and plasmid), a surprising minority of only 144 had null sequencing reads under all conditions. We therefore developed a statistical method to distinguish weakly transcribed genes from background transcription. We find that 96% of all genes and 91.5% of the hypothetical genes exhibit a significant transcriptional signal under at least one condition. Comparing SOLiD and Illumina systems, we find a high correlation between both approaches for fold-changes of the induced or repressed genes. The pathogenicity island LEE showed highest transcriptional activity in LB medium, minimal medium, and after treatment with antibiotics. Unique sets of genes, including many hypothetical genes, are highly up-regulated on radish sprouts, cattle feces, or in the presence of antibiotics. Furthermore, we observed induction of the shiga-toxin carrying phages by antibiotics and confirmed active biofilm related genes on radish sprouts, in cattle feces, and on agar plates.

Conclusions

Since only a minority of genes (2.7%) were not active under any condition tested (null reads), we suggest that the assumption of significant genome over-annotations is wrong. Environmental transcriptomics uncovered hitherto unknown gene functions and unique regulatory patterns in EHEC. For instance, the environmental function of azoR had been elusive, but this gene is highly active on radish sprouts. Thus, NGS-transcriptomics is an appropriate technique to propose new roles of hypothetical genes and to guide future research.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-353) contains supplementary material, which is available to authorized users.

Strand-Specific RNA-Seq Provides Greater Resolution of Transcriptome Profiling

RNA-Seq is a recently developed sequencing technology, that through the analysis of cDNA allows for unique insights into the transcriptome of a cell. The data generated by RNA-Seq provides information on gene expression, alternative splicing events and the presence of non-coding RNAs. It has been realised non-coding RNAs are more then just artefacts of erroneous transcription and play vital regulatory roles at the genomic, transcriptional and translational level. Transcription of the DNA sense strand produces antisense transcripts. This is known as antisense transcription and often results in the production of non-coding RNAs that are complementary to their associated sense transcripts. Antisense tran-scription has been identified in bacteria, fungi, protozoa, plants, invertebrates and mammals. It seems that antisense tran-scriptional ‘hot spots’ are located around nucleosome-free regions such as those associated with promoters, indicating that it is likely that antisense transcripts carry out important regulatory functions. This underlines the importance of identifying the presence and understanding the function of these antisense non-coding RNAs. The information concerning strand ori-gin is often lost during conventional RNA-Seq; capturing this information would substantially increase the worth of any RNA-Seq experiment. By manipulating the input cDNA during the template preparation stage it is possible to retain this vital information. This forms the basis of strand-specific RNA-Seq. With an ability to unlock immense portions of new in-formation surrounding the transcriptome, this cutting edge technology may hold the key to developing a greater under-standing of the transcriptome.

RNA-Seq of Bacillus licheniformis: active regulatory RNA features expressed within a productive fermentation

BACKGROUND

The production of enzymes by an industrial strain requires a complex adaption of the bacterial metabolism to the conditions within the fermenter. Regulatory events within the process result in a dynamic change of the transcriptional activity of the genome. This complex network of genes is orchestrated by proteins as well as regulatory RNA elements. Here we present an RNA-Seq based study considering selected phases of an industry-oriented fermentation of Bacillus licheniformis.

RESULTS

A detailed analysis of 20 strand-specific RNA-Seq datasets revealed a multitude of transcriptionally active genomic regions. 3314 RNA features encoded by such active loci have been identified and sorted into ten functional classes. The identified sequences include the expected RNA features like housekeeping sRNAs, metabolic riboswitches and RNA switches well known from studies on Bacillus subtilis as well as a multitude of completely new candidates for regulatory RNAs. An unexpectedly high number of 855 RNA features are encoded antisense to annotated protein and RNA genes, in addition to 461 independently transcribed small RNAs. These antisense transcripts contain molecules with a remarkable size range variation from 38 to 6348 base pairs in length. The genome of the type strain B. licheniformis DSM13 was completely reannotated using data obtained from RNA-Seq analyses and from public databases.

CONCLUSION

The hereby generated data-sets represent a solid amount of knowledge on the dynamic transcriptional activities during the investigated fermentation stages. The identified regulatory elements enable research on the understanding and the optimization of crucial metabolic activities during a productive fermentation of Bacillus licheniformis strains.

Directional RNA-seq reveals highly complex condition-dependent transcriptomes in E. coli K12 through accurate full-length transcripts assembling

BACKGROUND

Although prokaryotic gene transcription has been studied over decades, many aspects of the process remain poorly understood. Particularly, recent studies have revealed that transcriptomes in many prokaryotes are far more complex than previously thought. Genes in an operon are often alternatively and dynamically transcribed under different conditions, and a large portion of genes and intergenic regions have antisense RNA (asRNA) and non-coding RNA (ncRNA) transcripts, respectively. Ironically, similar studies have not been conducted in the model bacterium E coli K12, thus it is unknown whether or not the bacterium possesses similar complex transcriptomes. Furthermore, although RNA-seq becomes the major method for analyzing the complexity of prokaryotic transcriptome, it is still a challenging task to accurately assemble full length transcripts using short RNA-seq reads.

RESULTS

To fill these gaps, we have profiled the transcriptomes of E. coli K12 under different culture conditions and growth phases using a highly specific directional RNA-seq technique that can capture various types of transcripts in the bacterial cells, combined with a highly accurate and robust algorithm and tool TruHMM (http://bioinfolab.uncc.edu/TruHmm_package/) for assembling full length transcripts. We found that 46.9 ~ 63.4% of expressed operons were utilized in their putative alternative forms, 72.23 ~ 89.54% genes had putative asRNA transcripts and 51.37 ~ 72.74% intergenic regions had putative ncRNA transcripts under different culture conditions and growth phases.

CONCLUSIONS

As has been demonstrated in many other prokaryotes, E. coli K12 also has a highly complex and dynamic transcriptomes under different culture conditions and growth phases. Such complex and dynamic transcriptomes might play important roles in the physiology of the bacterium. TruHMM is a highly accurate and robust algorithm for assembling full-length transcripts in prokaryotes using directional RNA-seq short reads.

Analysis and design of RNA sequencing experiments for identifying RNA editing and other single-nucleotide variants

RNA-sequencing (RNA-Seq) technologies hold enormous promise for novel discoveries in genomics and transcriptomics. In the past year, a surge of reports has analyzed RNA-Seq data to gain a global view of the RNA editome. Opposing results have been presented, giving rise to extensive debate surrounding one of the first such studies in which a daunting list of all 12 types of RNA-DNA differences (RDDs) were identified. Although a consensus is forming that some of the initial "paradigm-shifting" results of this study may be questionable, recent reports on this topic differed in terms of the number and relative abundance of each type of RDD. Many outstanding issues exist, most importantly, the choice of bioinformatic approaches. Here we discuss the critical data analysis and experimental design issues of such studies to enable improved systematic investigation of the largely unexplored frontier of single-nucleotide variants in RNA.

Research progress in allele-specific expression and its regulatory mechanisms

Although the majority of genes are expressed equally from both alleles, some genes are differentially expressed. Organisms possess characteristics to preferentially express a particular allele under regulatory factors, which is termed allele-specific expression (ASE). It is one of the important genetic factors that lead to phenotypic variation and can be used to identify the variance of gene regulation factors. ASE indicates mechanisms such as DNA methylation, histone modifications, and non-coding RNAs function. Here, we review a broad survey of progress in ASE studies, and what this simple yet very effective approach can offer in functional genomics, and possible implications toward our better understanding of the underlying mechanisms of complex traits.

cDNA library construction for next-generation sequencing to determine the transcriptional landscape of Legionella pneumophila

The adaptation of Legionella pneumophila to the different conditions it encounters in the environment and in the host is governed by a complex regulatory system. Current knowledge of these regulatory networks and the transcriptome responses of L. pneumophila is mainly based on microarray analysis and limited to transcriptional products of annotated protein-coding genes. The application of the Next-Generation Sequencing (NGS) technology allows now genome-wide strand-specific sequencing and accurate determination of all expressed regions of the genome to reveal the complete transcriptional network and the dynamic interplay of specific regulators on a genome-wide level. NGS-based techniques promote deeper understanding of the global transcriptional organization of L. pneumophila by identifying transcription start sites (TSS), alternative TSS and operon organization, noncoding RNAs, antisense RNAs, and 5'-/3'-untranslated regions. In this chapter we describe the construction of cDNA libraries for (1) RNA deep sequencing (RNA-seq) and (2) TSS mapping using the Illumina technology.

Next-generation annotation of prokaryotic genomes with EuGene-P: application to Sinorhizobium meliloti 2011

The availability of next-generation sequences of transcripts from prokaryotic organisms offers the opportunity to design a new generation of automated genome annotation tools not yet available for prokaryotes. In this work, we designed EuGene-P, the first integrative prokaryotic gene finder tool which combines a variety of high-throughput data, including oriented RNA-Seq data, directly into the prediction process. This enables the automated prediction of coding sequences (CDSs), untranslated regions, transcription start sites (TSSs) and non-coding RNA (ncRNA, sense and antisense) genes. EuGene-P was used to comprehensively and accurately annotate the genome of the nitrogen-fixing bacterium Sinorhizobium meliloti strain 2011, leading to the prediction of 6308 CDSs as well as 1876 ncRNAs. Among them, 1280 appeared as antisense to a CDS, which supports recent findings that antisense transcription activity is widespread in bacteria. Moreover, 4077 TSSs upstream of protein-coding or non-coding genes were precisely mapped providing valuable data for the study of promoter regions. By looking for RpoE2-binding sites upstream of annotated TSSs, we were able to extend the S. meliloti RpoE2 regulon by ∼3-fold. Altogether, these observations demonstrate the power of EuGene-P to produce a reliable and high-resolution automatic annotation of prokaryotic genomes.

Circular RNAs are a large class of animal RNAs with regulatory potency

Circular RNAs (circRNAs) in animals are an enigmatic class of RNA with unknown function. To explore circRNAs systematically, we sequenced and computationally analysed human, mouse and nematode RNA. We detected thousands of well-expressed, stable circRNAs, often showing tissue/developmental-stage-specific expression. Sequence analysis indicated important regulatory functions for circRNAs. We found that a human circRNA, antisense to the cerebellar degeneration-related protein 1 transcript (CDR1as), is densely bound by microRNA (miRNA) effector complexes and harbours 63 conserved binding sites for the ancient miRNA miR-7. Further analyses indicated that CDR1as functions to bind miR-7 in neuronal tissues. Human CDR1as expression in zebrafish impaired midbrain development, similar to knocking down miR-7, suggesting that CDR1as is a miRNA antagonist with a miRNA-binding capacity ten times higher than any other known transcript. Together, our data provide evidence that circRNAs form a large class of post-transcriptional regulators. Numerous circRNAs form by head-to-tail splicing of exons, suggesting previously unrecognized regulatory potential of coding sequences.

An efficient rRNA removal method for RNA sequencing in GC-rich bacteria

Background

Next generation sequencing (NGS) technologies have revolutionized gene expression studies and functional genomics analysis. However, further improvement of RNA sequencing protocols is still desirable, in order to reduce NGS costs and to increase its accuracy. In bacteria, a major problem in RNA sequencing is the abundance of ribosomal RNA (rRNA), which accounts for 95-98% of total RNA and can therefore hinder sufficient coverage of mRNA, the main focus of transcriptomic studies. Thus, efficient removal of rRNA is necessary to achieve optimal coverage, good detection sensitivity and reliable results. An additional challenge is presented by microorganisms with GC-rich genomes, in which rRNA removal is less efficient.

Results

In this work, we tested two commercial kits for rRNA removal, either alone or in combination, on Burkholderia thailandensis. This bacterium, chosen as representative of the important Burkholderia genus, which includes both pathogenic and environmental bacteria, has a rather large (6.72 Mb) and GC-rich (67.7%) genome. Each enriched mRNA sample was sequenced through paired-end Illumina GAIIx run in duplicate, yielding between 10 and 40 million reads. We show that combined treatment with both kits allows an mRNA enrichment of more than 238-fold, enabling the sequencing of almost all (more than 90%) B. thailandensis transcripts from less than 10 million reads, without introducing any bias in mRNA relative abundance, thus preserving differential expression profile.

Conclusions

The mRNA enrichment protocol presented in this work leads to an increase in detection sensitivity up to 770% compared to total RNA; such increased sensitivity allows for a corresponding reduction in the number of sequencing reads necessary for the complete analysis of whole transcriptome expression profiling. Thus we can conclude that the MICROBExpress/Ovation combined rRNA removal method could be suitable for RNA sequencing of whole transcriptomes of microorganisms with high GC content and complex genomes enabling at the same time an important scaling down of sequencing costs.

Inhibition of cell division induced by external guide sequences (EGS Technology) targeting ftsZ

EGS (external guide sequence) technology is a promising approach to designing new antibiotics. EGSs are short antisense oligoribonucleotides that induce RNase P-mediated cleavage of a target RNA by forming a precursor tRNA-like complex. The ftsZ mRNA secondary structure was modeled and EGSs complementary to two regions with high probability of being suitable targets were designed. In vitro reactions showed that EGSs targeting these regions bound ftsZ mRNA and elicited RNase P-mediated cleavage of ftsZ mRNA. A recombinant plasmid, pEGSb1, coding for an EGS that targets region “b” under the control of the T7 promoter was generated. Upon introduction of this plasmid into Escherichia coli BL21(DE3)(pLysS) the transformant strain formed filaments when expression of the EGS was induced. Concomitantly, E. coli harboring pEGSb1 showed a modest but significant inhibition of growth when synthesis of the EGSb1 was induced. Our results indicate that EGS technology could be a viable strategy to generate new antimicrobials targeting ftsZ.

Transcription start site associated RNAs in bacteria

A new class of small RNA (~45 bases long) is identified in gram positive and negative bacteria. These tssRNAs are associated with RNA polymerase pausing some 45 bases downstream of the transcription start site and show global changes in expression during the growth cycle.

A new class of bacterial small RNAs have been identified. They are related to eukaryotic tiRNAs in their localization (transcription start sites, TSS) but not in their biogenesis.

tssRNAs are generated at the same positions as long transcripts, as well as at independent positions, but both seem to have promoter-like characteristics (Pribnow box).

We provide compelling evidence that tssRNAs are not mRNA degradation products and neither abortive transcripts; rather, they are newly synthesized transcripts and require more factors than the basal transcription machinery (i.e., RNA polymerase subunits)

tssRNAs show dynamic behavior dependent on the growth phase.

We show that RNA polymerase is halted at tssRNAs positions, both in bona fide genes and in positions where no long transcript is produced. This indicates that tssRNAs could be generated by RNA polymerase pausing to ensure that no spurious long RNA is generated by random appearance of Pribnow sequences in the genome.

Here, we report the genome-wide identification of small RNAs associated with transcription start sites (TSSs), termed tssRNAs, in Mycoplasma pneumoniae. tssRNAs were also found to be present in a different bacterial phyla, Escherichia coli. Similar to the recently identified promoter-associated tiny RNAs (tiRNAs) in eukaryotes, tssRNAs are associated with active promoters. Evidence suggests that these tssRNAs are distinct from previously described abortive transcription RNAs. ssRNAs have an average size of 45 bases and map exactly to the beginning of cognate full-length transcripts and to cryptic TSSs. Expression of bacterial tssRNAs requires factors other than the standard RNA polymerase holoenzyme. We have found that the RNA polymerase is halted at tssRNA positions in vivo, which may indicate that a pausing mechanism exists to prevent transcription in the absence of genes. These results suggest that small RNAs associated with TSSs could be a universal feature of bacterial transcription.

Multiple insert size paired-end sequencing for deconvolution of complex transcriptomes

Deep sequencing of transcriptomes allows quantitative and qualitative analysis of many RNA species in a sample, with parallel comparison of expression levels, splicing variants, natural antisense transcripts, RNA editing and transcriptional start and stop sites the ideal goal. By computational modeling, we show how libraries of multiple insert sizes combined with strand-specific, paired-end (SS-PE) sequencing can increase the information gained on alternative splicing, especially in higher eukaryotes. Despite the benefits of gaining SS-PE data with paired ends of varying distance, the standard Illumina protocol allows only non-strand-specific, paired-end sequencing with a single insert size. Here, we modify the Illumina RNA ligation protocol to allow SS-PE sequencing by using a custom pre-adenylated 3' adaptor. We generate parallel libraries with differing insert sizes to aid deconvolution of alternative splicing events and to characterize the extent and distribution of natural antisense transcription in C. elegans. Despite stringent requirements for detection of alternative splicing, our data increases the number of intron retention and exon skipping events annotated in the Wormbase genome annotations by 127% and 121%, respectively. We show that parallel libraries with a range of insert sizes increase transcriptomic information gained by sequencing and that by current established benchmarks our protocol gives competitive results with respect to library quality.

Comparative omics-driven genome annotation refinement: application across Yersiniae

Genome sequencing continues to be a rapidly evolving technology, yet most downstream aspects of genome annotation pipelines remain relatively stable or are even being abandoned. The annotation process is now performed almost exclusively in an automated fashion to balance the large number of sequences generated. One possible way of reducing errors inherent to automated computational annotations is to apply data from omics measurements (i.e. transcriptional and proteomic) to the un-annotated genome with a proteogenomic-based approach. Here, the concept of annotation refinement has been extended to include a comparative assessment of genomes across closely related species. Transcriptomic and proteomic data derived from highly similar pathogenic Yersiniae (Y. pestis CO92, Y. pestis Pestoides F, and Y. pseudotuberculosis PB1/+) was used to demonstrate a comprehensive comparative omic-based annotation methodology. Peptide and oligo measurements experimentally validated the expression of nearly 40% of each strain's predicted proteome and revealed the identification of 28 novel and 68 incorrect (i.e., observed frameshifts, extended start sites, and translated pseudogenes) protein-coding sequences within the three current genome annotations. Gene loss is presumed to play a major role in Y. pestis acquiring its niche as a virulent pathogen, thus the discovery of many translated pseudogenes, including the insertion-ablated argD, underscores a need for functional analyses to investigate hypotheses related to divergence. Refinements included the discovery of a seemingly essential ribosomal protein, several virulence-associated factors, a transcriptional regulator, and many hypothetical proteins that were missed during annotation.

Grinder: a versatile amplicon and shotgun sequence simulator

We introduce Grinder (http://sourceforge.net/projects/biogrinder/), an open-source bioinformatic tool to simulate amplicon and shotgun (genomic, metagenomic, transcriptomic and metatranscriptomic) datasets from reference sequences. This is the first tool to simulate amplicon datasets (e.g. 16S rRNA) widely used by microbial ecologists. Grinder can create sequence libraries with a specific community structure, α and β diversities and experimental biases (e.g. chimeras, gene copy number variation) for commonly used sequencing platforms. This versatility allows the creation of simple to complex read datasets necessary for hypothesis testing when developing bioinformatic software, benchmarking existing tools or designing sequence-based experiments. Grinder is particularly useful for simulating clinical or environmental microbial communities and complements the use of in vitro mock communities.

Targeted enrichment strategies for next-generation plant biology

PREMISE OF THE STUDY

The dramatic advances offered by modern DNA sequencers continue to redefine the limits of what can be accomplished in comparative plant biology. Even with recent achievements, however, plant genomes present obstacles that can make it difficult to execute large-scale population and phylogenetic studies on next-generation sequencing platforms. Factors like large genome size, extensive variation in the proportion of organellar DNA in total DNA, polyploidy, and gene number/redundancy contribute to these challenges, and they demand flexible targeted enrichment strategies to achieve the desired goals.

METHODS

In this article, we summarize the many available targeted enrichment strategies that can be used to target partial-to-complete organellar genomes, as well as known and anonymous nuclear targets. These methods fall under four categories: PCR-based enrichment, hybridization-based enrichment, restriction enzyme-based enrichment, and enrichment of expressed gene sequences.

KEY RESULTS

Examples of plant-specific applications exist for nearly all methods described. While some methods are well established (e.g., transcriptome sequencing), other promising methods are in their infancy (hybridization enrichment). A direct comparison of methods shows that PCR-based enrichment may be a reasonable strategy for accessing small genomic targets (e.g., ≤50 kbp), but that hybridization and transcriptome sequencing scale more efficiently if larger targets are desired.

CONCLUSIONS

While the benefits of targeted sequencing are greatest in plants with large genomes, nearly all comparative projects can benefit from the improved throughput offered by targeted multiplex DNA sequencing, particularly as the amount of data produced from a single instrument approaches a trillion bases per run.

Coupled transcriptome and proteome analysis of human lymphotropic tumor viruses: insights on the detection and discovery of viral genes

Background

Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV) are related human tumor viruses that cause primary effusion lymphomas (PEL) and Burkitt's lymphomas (BL), respectively. Viral genes expressed in naturally-infected cancer cells contribute to disease pathogenesis; knowing which viral genes are expressed is critical in understanding how these viruses cause cancer. To evaluate the expression of viral genes, we used high-resolution separation and mass spectrometry coupled with custom tiling arrays to align the viral proteomes and transcriptomes of three PEL and two BL cell lines under latent and lytic culture conditions.

Results

The majority of viral genes were efficiently detected at the transcript and/or protein level on manipulating the viral life cycle. Overall the correlation of expressed viral proteins and transcripts was highly complementary in both validating and providing orthogonal data with latent/lytic viral gene expression. Our approach also identified novel viral genes in both KSHV and EBV, and extends viral genome annotation. Several previously uncharacterized genes were validated at both transcript and protein levels.

Conclusions

This systems biology approach coupling proteome and transcriptome measurements provides a comprehensive view of viral gene expression that could not have been attained using each methodology independently. Detection of viral proteins in combination with viral transcripts is a potentially powerful method for establishing virus-disease relationships.

Low-bias, strand-specific transcriptome Illumina sequencing by on-flowcell reverse transcription (FRT-seq)

The unifying feature of second-generation sequencing technologies is that single template strands are amplified clonally onto a solid surface prior to the sequencing reaction. To convert template strands into a compatible state for attachment to this surface, a multistep library preparation is required, which typically culminates in amplification by the PCR. PCR is an inherently biased process, which decreases the efficiency of data acquisition. Flowcell reverse transcription sequencing is a method of transcriptome sequencing for Illumina sequencers in which the reverse transcription reaction is performed on the flowcell by using unamplified, adapter-ligated mRNA as a template. This approach removes PCR biases and duplicates, generates strand-specific paired-end data and is highly reproducible. The procedure can be performed quickly, taking 2 d to generate clusters from mRNA.