scholarly journals Transcriptome-wide analysis of microRNA-mRNA correlations in unperturbed tissue transcriptomes identifies microRNA targeting determinants.

2021 ◽  
Author(s):  
Juan Manuel Trinidad ◽  
Rafael Sebastian Fort ◽  
Guillermo Trinidad ◽  
Beatriz Garat ◽  
Maria A Duhagon
Keyword(s):  
Gene Expression ◽  
Small Rna ◽  
Current Knowledge ◽  
Gc Content ◽  
Sequence Motif ◽  
Z Score ◽  
Rna Seq ◽  
Microrna Target ◽  
Candidate Sequence ◽  
Interaction Sites

MicroRNAs are small RNAs that regulate gene expression through complementary base pairing with their target mRNAs. Given the small size of the pairing region and the large number of mRNAs that each microRNA can control, the identification of biologically relevant targets is difficult. Since current knowledge of target recognition and repression has mainly relied on in vitro studies, we sought to determine if the interrogation of gene expression data of unperturbed tissues could yield new insight into these processes. The transcriptome-wide repression at the microRNA-mRNA canonical interaction sites (seed and 3'-supplementary region, identified by sole base complementarity) was calculated as a normalized Spearman correlation (Z-score) between the abundance of the transcripts in the PRAD-TCGA tissues (RNA-seq and small RNA-seq data of 546 samples). Using the repression values obtained we confirmed established properties or microRNA targeting efficacy, such as the preference for gene regions (3'UTR>CDS>5'UTR), the proportionality between repression and seed length (6mer<7mer<8mer) and the contribution to the repression exerted by the supplementary pairing at 13-16nt of the microRNA. Our results suggest that the 7mer-m8 seed could be more repressive than the 7mer-A1, while they have similar efficacy when they interact using the 3'-supplementary pairing. Strikingly, the 6mer+suppl sites yielded normalized Z-score of repression similar to the sole 7mer-m8 or 7mer-A1 seeds, which raise awareness of its potential biological relevance. We then used the approach to further characterize the 3'-supplementary pairing, using 39 microRNAs that hold repressive 3'-supplementary interactions. The analysis of the bridge between seed and 3'-supplementary pairing site confirmed the optimum +1 offset previously evidenced, but higher offsets appear to hold similar repressive strength. In addition, they show a low GC content at position 13-16, and base preferences that allow the selection of a candidate sequence motif. Overall, our study demonstrates that transcriptome-wide analysis of microRNA-mRNA correlations in large, matched RNA-seq and small-RNA-seq data has the power to uncover hints of microRNA targeting determinants operating in the in vivo unperturbed set. Finally, we made available a bioinformatic tool to analyze microRNA-target mRNA interactions using our approach.

scholarly journals Identification and validation of miRNA reference genes in poplar under pathogen stress

2021 ◽  
Author(s):  
Lichun Zhang ◽  
Xiaoqian Yang ◽  
Yiyi Yin ◽  
Jinxing Wang ◽  
Yanwei Wang
Keyword(s):  
Gene Expression ◽  
Reference Gene ◽  
Small Rna ◽  
Reference Genes ◽  
Expression Profiles ◽  
Small Rna Sequencing ◽  
Rna Seq ◽  
Internal Standards ◽  
Qrt Pcr ◽  
Canker Pathogen

Abstract Quantitative real time polymerase chain reaction (qRT-PCR) is a common method to analyze gene expression. Due to differences in RNA quantity, quality, and reverse transcription efficiency between qRT-PCR samples, reference genes are used as internal standards to normalize gene expression. However, few universal genes especially miRNAs have been identified as reference so far. Therefore, it is essential to identify reference genes that can be used across various experimental conditions, stress treatments, or tissues. In this study, 14 microRNAs (miRNAs) and 5.8S rRNA were assessed for expression stability in poplar trees infected with canker pathogen. Using three reference gene analysis programs, we found that miR156g and miR156a exhibited stable expression throughout the infection process. miR156g and miR156a were then tested as internal standards to measure the expression of miR1447 and miR171c, and the results were compared to small RNA sequencing (RNA-seq) data. We found that when miR156a was used as the reference gene, the expression of miR1447 and miR171c were consistent with the small RNA-seq expression profiles. Therefore, miR156a was the most stable miRNAs examined in this study, and could be used as a reference gene in poplar under canker pathogen stress, which should enable comprehensive comparisons of miRNAs expression and avoid the bias caused by different lenth between detected miRNAs and traditional referece genes. The present study has expanded the miRNA reference genes available for gene expression studies in trees under biotic stress.

scholarly journals Analysis of RDR1/RDR2/RDR6-independent small RNAs in Arabidopsis thaliana improves MIRNA annotations and reveals novel siRNA loci

2017 ◽  
Author(s):  
Seth Polydore ◽  
Michael J. Axtell
Keyword(s):  
Gene Expression ◽  
Arabidopsis Thaliana ◽  
Small Rna ◽  
Small Rnas ◽  
Rna Seq ◽  
Triple Mutant ◽  
Physiological Mechanisms ◽  
Protein Coding ◽  
Regulate Gene Expression ◽  
Rna Biogenesis

SummaryPlant small RNAs regulate key physiological mechanisms through post-transcriptional and transcriptional silencing of gene expression. sRNAs fall into two major categories: those that are reliant on RNA Dependent RNA Polymerases (RDRs) for biogenesis and those that aren’t. Known RDR-dependent sRNAs include phased and repeat-associated short interfering RNAs, while known RDR-independent sRNAs are primarily microRNAs and other hairpin-derived sRNAs. In this study, we produced and analyzed small RNA-seq libraries from rdr1/rdr2/rdr6 triple mutant plants. Only a small fraction of all sRNA loci were RDR1/RDR2/RDR6-independent; most of these were microRNA loci or associated with predicted hairpin precursors. We found 58 previously annotated microRNA loci that were reliant on RDR1, −2, or −6 function, casting doubt on their classification. We also found 38 RDR1/2/6-independent small RNA loci that are not MIRNAs or otherwise hairpin-derived, and did not fit into other known paradigms for small RNA biogenesis. These 38 small RNA-producing loci have novel biogenesis mechanisms, and are frequently located in the vicinity of protein-coding genes. Altogether, our analysis suggest that these 38 loci represent one or more new types of small RNAs in Arabidopsis thaliana.Significance StatementSmall RNAs regulate gene expression in plants and are produced through a variety of previously-described mechanisms. Here, we examine a set of previously undiscovered small RNA-producing loci that are produced by novel mechanisms.

scholarly journals Integrative RNA-seq and microarray data analysis reveals GC content and gene length biases in the psoriasis transcriptome

2014 ◽  
Vol 46 (15) ◽  
pp. 533-546 ◽  
Author(s):  
William R. Swindell ◽  
Xianying Xing ◽  
John J. Voorhees ◽  
James T. Elder ◽  
Andrew Johnston ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiling ◽  
Gc Content ◽  
Microarray Data Analysis ◽  
Gene Length ◽  
Rna Seq ◽  
Data Types ◽  
Factors Affecting ◽  
Microarray Studies ◽  
Microarray Datasets

Gene expression profiling of psoriasis has driven research advances and may soon provide the basis for clinical applications. For expression profiling studies, RNA-seq is now a competitive technology, but RNA-seq results may differ from those obtained by microarray. We therefore compared findings obtained by RNA-seq with those from eight microarray studies of psoriasis. RNA-seq and microarray datasets identified similar numbers of differentially expressed genes (DEGs), with certain genes uniquely identified by each technology. Correspondence between platforms and the balance of increased to decreased DEGs was influenced by mRNA abundance, GC content, and gene length. Weakly expressed genes, genes with low GC content, and long genes were all biased toward decreased expression in psoriasis lesions. The strength of these trends differed among array datasets, most likely due to variations in RNA quality. Gene length bias was by far the strongest trend and was evident in all datasets regardless of the expression profiling technology. The effect was due to differences between lesional and uninvolved skin with respect to the genome-wide correlation between gene length and gene expression, which was consistently more negative in psoriasis lesions. These findings demonstrate the complementary nature of RNA-seq and microarray technology and show that integrative analysis of both data types can provide a richer view of the transcriptome than strict reliance on a single method alone. Our results also highlight factors affecting correspondence between technologies, and we have established that gene length is a major determinant of differential expression in psoriasis lesions.

Transcriptomics: Quantifying Non-Uniform Read Distribution Using MapReduce

2018 ◽  
Vol 29 (08) ◽  
pp. 1355-1372
Author(s):  
Jamie J. Alnasir ◽  
Hugh P. Shanahan
Keyword(s):  
Service Providers ◽  
Gc Content ◽  
Cloud Service ◽  
Sequence Motif ◽  
Rna Seq ◽  
Motif Pair ◽  
Pair Correlations ◽  
Two Samples ◽  
In The Wild ◽  
Exon Level

RNA-seq is a high-throughput Next-sequencing technique for estimating the concentration of all transcripts in a transcriptome. The method involves complex preparatory and post-processing steps which can introduce bias, and the technique produces a large amount of data [7, 19]. Two important challenges in processing RNA-seq data are therefore the ability to process a vast amount of data, and methods to quantify the bias in public RNA-seq datasets. We describe a novel analysis method, based on analysing sequence motif correlations, that employs MapReduce on Apache Spark to quantify bias in Next-generation sequencing (NGS) data at the deep exon level. Our implementation is designed specifically for processing large datasets and allows for scalability and deployment on cloud service providers offering MapReduce. In investigating the wild and mutant organism types in the species D. melanogaster we have found that motifs with runs of Gs (or their complement) exhibit low motif-pair correlations in comparison with other motif-pairs. This is independent of the mean exon GC content in the wild type data, but there is a mild dependence in the mutant data. Hence, whilst both datasets show the same trends, there is however significant variation between the two samples.

scholarly journals Small RNAs Are Implicated in Regulation of Gene and Transposable Element Expression in the Protist Trichomonas vaginalis

mSphere ◽  
2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Sally D. Warring ◽  
Frances Blow ◽  
Grace Avecilla ◽  
Jordan C. Orosco ◽  
Steven A. Sullivan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Small Rna ◽  
Trichomonas Vaginalis ◽  
Repetitive Elements ◽  
Rna Seq ◽  
Transmitted Infection ◽  
Protein Coding ◽  
Content Type ◽  
Rna Molecules ◽  
Sexually Transmitted

ABSTRACT Trichomonas vaginalis is the causative agent of trichomoniasis, the most prevalent nonviral sexually transmitted infection worldwide. Repetitive elements, including transposable elements (TEs) and virally derived repeats, comprise more than half of the ∼160-Mb T. vaginalis genome. An intriguing question is how the parasite controls its potentially lethal complement of mobile elements, which can disrupt transcription of protein-coding genes and genome functions. In this study, we generated high-throughput RNA sequencing (RNA-Seq) and small RNA-Seq data sets in triplicate for the T. vaginalis G3 reference strain and characterized the mRNA and small RNA populations and their mapping patterns along all six chromosomes. Mapping the RNA-Seq transcripts to the genome revealed that the majority of genes predicted within repetitive elements are not expressed. Interestingly, we identified a novel species of small RNA that maps bidirectionally along the chromosomes and is correlated with reduced protein-coding gene expression and reduced RNA-Seq coverage in repetitive elements. This novel small RNA family may play a regulatory role in gene and repetitive element expression. Our results identify a possible small RNA pathway mechanism by which the parasite regulates expression of genes and TEs and raise intriguing questions as to the role repeats may play in shaping T. vaginalis genome evolution and the diversity of small RNA pathways in general. IMPORTANCE Trichomoniasis, caused by the protozoan Trichomonas vaginalis, is the most common nonviral sexually transmitted infection in humans. The millions of cases each year have sequelae that may include complications during pregnancy and increased risk of HIV infection. Given its evident success in this niche, it is paradoxical that T. vaginalis harbors in its genome thousands of transposable elements that have the potential to be extremely detrimental to normal genomic function. In many organisms, transposon expression is regulated by the activity of endogenously expressed short (∼21 to 35 nucleotides [nt]) small RNA molecules that effect gene silencing by targeting mRNAs for degradation or by recruiting epigenetic silencing machinery to locations in the genome. Our research has identified small RNA molecules correlated with reduced expression of T. vaginalis genes and transposons. This suggests that a small RNA pathway is a major contributor to gene expression patterns in the parasite and opens up new avenues for investigation into small RNA biogenesis, function, and diversity.

scholarly journals MO072APABETALONE DOWNREGULATES FIBROTIC, INFLAMMATORY AND CALCIFIC PROCESSES IN RENAL MESANGIAL CELLS WHICH MAY CONTRIBUTE TO REDUCED CARDIAC EVENTS OBSERVED IN CKD PATIENTS

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Dean Gilham ◽  
Li Fu ◽  
Brooke Rakai ◽  
Sylwia Wasiak ◽  
Laura Tsujikawa ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alkaline Phosphatase ◽  
Mesangial Cells ◽  
Z Score ◽  
Rna Seq ◽  
Cardiac Events ◽  
Kidney Dysfunction ◽  
Phase 3 ◽  
Go Enrichment ◽  
Tgf Β1

Abstract Background and Aims Major adverse cardiac events (MACE) remain a leading cause of mortality in chronic kidney disease (CKD). Apabetalone is an orally available inhibitor of bromodomain & extraterminal (BET) proteins – epigenetic readers that modulate gene expression involved in fibrosis, inflammation and calcification. In the phase 3 BETonMACE trial, apabetalone treatment was associated with reduction in MACE in the subpopulation with CKD (eGFR &lt; 60 mL/min/1.73m2; HR 0.50 95% CI 0.26,0.96 p=0.04]) implying favorable effects of apabetalone on cellular responses along the kidney-heart axis. This study examines effects of apabetalone on primary human renal mesangial cells (HRMCs) in culture on fibrosis, inflammation, reactive oxygen species (ROS) and calcification pathways that contribute to renal pathology. Method HRMCs from donors without kidney dysfunction were stimulated with TGF-β1 or lipopolysaccharide (LPS) ± 1-25µM apabetalone, 0.15-0.5µM JQ1 or 0.1µM MZ1 (BET inhibitors [BETi] with chemical scaffolds different than apabetalone). Gene expression was measured by real-time PCR and RNA-seq. Smooth muscle actin (α-SMA) was examined by immunofluorescence microscopy, and alkaline phosphatase enzyme activity in a biochemical assay. RNA-seq from TGF-β1 treated HRMC ± BETi was evaluated by Gene Ontology (GO) Enrichment and Ingenuity Pathway Analysis (IPA). Results TGF-β1 is a pro-fibrotic cytokine that activates HRMC to a fibroblast-like state which over-produces extracellular matrix (ECM). Apabetalone dose dependently suppressed TGF-β1 induced gene expression of (a) α-SMA, a marker of fibrotic activation, up to 90% p&lt;0.001 and de novo α-SMA protein production (b) fibronectin, a key ECM component, up to 44% p&lt;0.001 (c) NADPH oxidase 4 (NOX4), involved in production of pro-fibrotic ROS, up to 82% p&lt;0.001 (d) tissue non-specific alkaline phosphatase (TNALP), associated with reduced glomerular function & extracellular calcification, up to 96% as well as TNALP enzyme activity up to 96% p&lt;0.001. An inhibitor of TGF-β receptors reduced or abolished TGF-β1 responses, indicating the expected signal transduction pathways mediated its downstream effects. Apabetalone dose dependently opposed LPS stimulated expression of inflammatory genes: IL6 up to 94%, IL1B up to 95% & PTGS2 (COX2) up to 94% p&lt;0.001, suggesting downregulation of inflammatory processes. In all studies, JQ1 and / or MZ1 had similar activity as apabetalone, confirming on-target BETi effects. In GO Enrichment analysis of RNA-seq from TGF-β1 stimulated HRMCs, multiple gene sets associated with ECM were in the top 20 affected by BETi, supporting anti-fibrotic properties. IPA predicted NfkB-RelA and NFkB (complex) were upstream regulators inhibited by apabetalone, indicating suppression of NF-kB mediated inflammation. IPA also predicted apabetalone activated canonical pathways of glucose utilization & tolerance of ROS production, including Oxidative Phosphorylation (z-score 5.7, p&lt;0.01 at 25µM; z-score 3.5, p&gt;0.05 at 5µM) and NRF2-Mediated Oxidative Stress Response (z score 2.3, p&lt;0.001 at 25µM; z-score 1.6, p&lt;0.001 at 5µM). PGC-1α, a key upstream regulator of the Oxidative Phosphorylation pathway, was also predicted to be activated by apabetalone (z score 4.2, p&lt;0.001 at 25µM; z-score 2.3, p&lt;0.001 at 5µM). These changes in energy metabolism pathways may allow HRMC to cope with elevated glucose. Conclusion Apabetalone downregulated responses to TGF-β1 or LPS in HRMCs that promote fibrotic, inflammatory and calcific processes which exacerbate kidney dysfunction. Changes in energy metabolism pathways predicted apabetalone facilitates adaptation to high glucose in the kidney. Together, our results provide mechanistic insight into reductions in MACE in CKD patients receiving apabetalone in the phase 3 BETonMACE trial. The effect of apabetalone on MACE in patients with diabetes and CKD will be further evaluated in the upcoming BETonMACE2 trial.

scholarly journals Enjoy the Silence: Nearly Half of Human tRNA Genes Are Silent

2019 ◽  
Vol 13 ◽  
pp. 117793221986845 ◽  
Author(s):  
Adrian Gabriel Torres
Keyword(s):  
Gene Expression ◽  
Small Rna ◽  
Trna Gene ◽  
Trna Genes ◽  
Messenger Rnas ◽  
Rna Seq ◽  
Cell Type ◽  
Transfer Rnas ◽  
Gene Contribution ◽  
Generation Sequencing

Transfer RNAs (tRNAs) are key components of the translation machinery. They read codons on messenger RNAs (mRNAs) and deliver the appropriate amino acid to the ribosome for protein synthesis. The human genome encodes more than 500 tRNA genes but their individual contribution to the cellular tRNA pool is unclear. In recent years, novel methods were developed to improve the quantification of tRNA gene expression, most of which rely on next-generation sequencing such as small RNA-Seq applied to tRNAs (tRNA-Seq). In a previous study, we presented a bioinformatics strategy to analyse tRNA-Seq datasets that we named ‘isodecoder-specific tRNA gene contribution profiling’ (Iso-tRNA-CP). Using Iso-tRNA-CP, we showed that tRNA gene expression is cell type- and tissue-specific and that this process can regulate tRNA-derived fragments abundance. An additional observation that stems from that work is that approximately half of human tRNA genes appeared silent or poorly expressed. In this commentary, I discuss this finding in light of the current literature and speculate on potential functions that transcriptionally silent tRNA genes may play. Studying silent tRNA genes may offer a unique opportunity to unravel novel mechanisms of cell regulation associated to tRNA biology.

scholarly journals Computational approaches for the analysis of epigenome and transcriptome characterisation in Paramecium tetraurelia

2021 ◽  
Author(s):  
◽  
Sivarajan Karunanithi
Keyword(s):  
Gene Expression ◽  
Small Rna ◽  
Gc Content ◽  
Model Organisms ◽  
Rnai Pathway ◽  
Paramecium Tetraurelia ◽  
Gene Length ◽  
Histone Marks ◽  
In Cis ◽  
Regulatory Landscape

In the last two decades, our understanding of human gene regulation has improved tremendously. There are plentiful computational methods which focus on integrative data analysis of humans, and model organisms, like mouse and drosophila. However, these tools are not directly employable by researchers working on non-model organisms to answer fundamental biological, and evolutionary questions. We aimed to develop new tools, and adapt existing software for the analysis of transcriptomic and epigenomic data of one such non-model organism, Paramecium tetraurelia, an unicellular eukaryote. Paramecium contains two diploid (2n) germline micronuclei (MIC) and a polyploid (800n) somatic macronuclei (MAC). The transcriptomic and epigenomic regulatory landscape of the MAC genome, which has 80% protein-coding genes and short intergenic regions, is poorly understood. We developed a generic automated eukaryotic short interfering RNA (siRNA) analysis tool, called RAPID. Our tool captures diverse siRNA characteristics from small RNA sequencing data and provides easily navigable visualisations. We also introduced a normalisation technique to facilitate comparison of multiple siRNA-based gene knockdown studies. Further, we developed a pipeline to characterise novel genome-wide endogenous short interfering RNAs (endo-siRNAs). In contrary to many organisms, we found that the endo-siRNAs are not acting in cis, to silence their parent mRNA. We also predicted phasing of siRNAs, which are regulated by the RNA interference (RNAi) pathway. Further, using RAPID, we investigated the aberrations of endo-siRNAs, and their respective transcriptomic alterations caused by an RNAi pathway triggered by feeding small RNAs against a target gene. We find that the small RNA transcriptome is altered, even if a gene unrelated to RNAi pathway is targeted. This is important in the context of investigations of genetically modified organisms (GMOs). We suggest that future studies need to distinguish transcriptomic changes caused by RNAi inducing techniques and actual regulatory changes. Subsequently, we adapted existing epigenomics analysis tools to conduct the first comprehensive epigenomic characterisation of nucleosome positioning and histone modifications of the Paramecium MAC. We identified well positioned nucleosomes shifted downstream of the transcription start site. GC content seems to dictate, in cis, the positioning of nucleosomes, histone marks (H3K4me3, H3K9ac, and H3K27me3), and Pol II in the AT-rich Paramecium genome. We employed a chromatin state segmentation approach, on nucleosomes and histone marks, which revealed genes with active, repressive, and bivalent chromatin states. Further, we constructed a regulatory association network of all the aforementioned data, using the sparse partial correlation network technique. Our analysis revealed subsets of genes, whose expression is positively associated with H3K27me3, different to the otherwise reported negative association with gene expression in many other organisms. Further, we developed a Random Forests classifier to predict gene expression using genic (gene length, intron frequency, etc.) and epigenetic features. Our model has a test performance (PR-AUC) of 0.83. Upon evaluating different feature sets, we found that genic features are as predictive, of gene expression, as the epigenetic features. We used Shapley local feature explanation values, to suggest that high H3K4me3, high intron frequency, low gene length, high sRNA, and high GC content are the most important elements for determining gene expression status. In this thesis, we developed novel tools, and employed several bioinformatics and machine learning methods to characterise the regulatory landscape of the Paramecium’s (epi)genome.

scholarly journals Genome-wide Annotation, Identification, and Global Transcriptomic Analysis of Regulatory or Small RNA Gene Expression inStaphylococcus aureus

mBio ◽  
2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Ronan K. Carroll ◽  
Andy Weiss ◽  
William H. Broach ◽  
Richard E. Wiemels ◽  
Austin B. Mogen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Staphylococcus Aureus ◽  
Human Serum ◽  
Small Rna ◽  
Genome Annotation ◽  
Small Rnas ◽  
Global Analysis ◽  
Rna Seq ◽  
Srna Gene ◽  
Genome Wide

ABSTRACTInStaphylococcus aureus, hundreds of small regulatory or small RNAs (sRNAs) have been identified, yet this class of molecule remains poorly understood and severely understudied. sRNA genes are typically absent from genome annotation files, and as a consequence, their existence is often overlooked, particularly in global transcriptomic studies. To facilitate improved detection and analysis of sRNAs inS. aureus, we generated updated GenBank files for three commonly usedS. aureusstrains (MRSA252, NCTC 8325, and USA300), in which we added annotations for >260 previously identified sRNAs. These files, the first to include genome-wide annotation of sRNAs inS. aureus, were then used as a foundation to identify novel sRNAs in the community-associated methicillin-resistant strain USA300. This analysis led to the discovery of 39 previously unidentified sRNAs. Investigating the genomic loci of the newly identified sRNAs revealed a surprising degree of inconsistency in genome annotation inS. aureus, which may be hindering the analysis and functional exploration of these elements. Finally, using our newly created annotation files as a reference, we perform a global analysis of sRNA gene expression inS. aureusand demonstrate that the newly identifiedtsr25is the most highly upregulated sRNA in human serum. This study provides an invaluable resource to theS. aureusresearch community in the form of our newly generated annotation files, while at the same time presenting the first examination of differential sRNA expression in pathophysiologically relevant conditions.IMPORTANCEDespite a large number of studies identifying regulatory or small RNA (sRNA) genes inStaphylococcus aureus, their annotation is notably lacking in available genome files. In addition to this, there has been a considerable lack of cross-referencing in the wealth of studies identifying these elements, often leading to the same sRNA being identified multiple times and bearing multiple names. In this work, we have consolidated and curated known sRNA genes from the literature and mapped them to their position on theS. aureusgenome, creating new genome annotation files. These files can now be used by the scientific community at large in experiments to search for previously undiscovered sRNA genes and to monitor sRNA gene expression by transcriptome sequencing (RNA-seq). We demonstrate this application, identifying 39 new sRNAs and studying their expression duringS. aureusgrowth in human serum.

Sign in / Sign up

Export Citation Format

Share Document