Showing papers in "Non-Coding RNA in 2017"
TL;DR: The demonstration that miR-155 overexpression plays a key pathogenic role in some lymphomas and acute myeloid leukemias has led to the development of an antagomir-based approach as a new promising therapeutic strategy.
Abstract: MicroRNAs (miRNAs or miRs) are a class of evolutionarily-conserved small, regulatory non-coding RNAs, 19–3 nucleotides in length, that negatively regulate protein coding gene transcripts’ expression. miR-146 (146a and 146b) and miR-155 are among the first and most studied miRs for their multiple roles in the control of the innate and adaptive immune processes and for their deregulation and oncogenic role in some tumors. In the present review, we have focused on the recent acquisitions about the key role played by miR-146a, miR-146b and miR-155 in the control of the immune system and in myeloid tumorigenesis. Growing experimental evidence indicates an opposite role of miR-146a with respect to miR-155 in the fine regulation of many steps of the immune response, acting at the level of the various cell types involved in innate and adaptive immune mechanisms. The demonstration that miR-155 overexpression plays a key pathogenic role in some lymphomas and acute myeloid leukemias has led to the development of an antagomir-based approach as a new promising therapeutic strategy.
159 citations
TL;DR: Understanding the regulatory roles of EV-linked ncRNAs could be of great value to EV-based RNA therapeutics achieved through gene manipulation within cancer cells, whereas the ncRNA content of EVs from cancer patients could serve as non-invasive source of diagnostic biomarkers and prognostic indicators in response to therapies.
Abstract: Extracellular vesicles (EVs) are nanosized vesicles secreted from virtually all cell types and are thought to transport proteins, lipids and nucleic acids including non-coding RNAs (ncRNAs) between cells. Since, ncRNAs are central to transcriptional regulation during developmental processes; eukaryotes might have evolved novel means of post-transcriptional regulation by trans-locating ncRNAs between cells. EV-mediated transportation of regulatory elements provides a novel source of trans-regulation between cells. In the last decade, studies were mainly focused on microRNAs; however, functions of long ncRNA (lncRNA) have been much less studied. Here, we review the regulatory roles of EV-linked ncRNAs, placing a particular focus on lncRNAs, how they can foster dictated patterns of trans-regulation in recipient cells. This refers to envisaging novel mechanisms of epigenetic regulation, cellular reprogramming and genomic instability elicited in recipient cells, ultimately permitting the generation of cancer initiating cell phenotypes, senescence and resistance to chemotherapies. Conversely, such trans-regulation may introduce RNA interference in recipient cancer cells causing the suppression of oncogenes and anti-apoptotic proteins; thus favoring tumor inhibition. Collectively, understanding these mechanisms could be of great value to EV-based RNA therapeutics achieved through gene manipulation within cancer cells, whereas the ncRNA content of EVs from cancer patients could serve as non-invasive source of diagnostic biomarkers and prognostic indicators in response to therapies.
116 citations
TL;DR: The latest studies on various types of RNA biomarkers, especially extracellular RNAs, in cancer diagnosis and prognosis are summarized, and several well-known RNA biomarker of clinical utility are illustrated.
Abstract: As an essential part of central dogma, RNA delivers genetic and regulatory information and reflects cellular states. Based on high-throughput sequencing technologies, cumulating data show that various RNA molecules are able to serve as biomarkers for the diagnosis and prognosis of various diseases, for instance, cancer. In particular, detectable in various bio-fluids, such as serum, saliva and urine, extracellular RNAs (exRNAs) are emerging as non-invasive biomarkers for earlier cancer diagnosis, tumor progression monitor, and prediction of therapy response. In this review, we summarize the latest studies on various types of RNA biomarkers, especially extracellular RNAs, in cancer diagnosis and prognosis, and illustrate several well-known RNA biomarkers of clinical utility. In addition, we describe and discuss general procedures and issues in investigating exRNA biomarkers, and perspectives on utility of exRNAs in precision medicine.
103 citations
TL;DR: Significant amounts of data have been produced regarding plant lncRNAs, and this amount is likely to increase in the subsequent years, and the plant-specific resources/databases for information retrieval on lnc RNA are documented.
Abstract: Small non-coding RNAs have been extensively studied in plants over the last decade. In contrast, genome-wide identification of plant long non-coding RNAs (lncRNAs) has recently gained momentum. LncRNAs are now being recognized as important players in gene regulation, and their potent regulatory roles are being studied comprehensively in eukaryotes. LncRNAs were first reported in humans in 1992. Since then, research in animals, particularly in humans, has rapidly progressed, and a vast amount of data has been generated, collected, and organized using computational approaches. Additionally, numerous studies have been conducted to understand the roles of these long RNA species in several diseases. However, the status of lncRNA investigation in plants lags behind that in animals (especially humans). Efforts are being made in this direction using computational tools and high-throughput sequencing technologies, such as the lncRNA microarray technique, RNA-sequencing (RNA-seq), RNA capture sequencing, (RNA CaptureSeq), etc. Given the current scenario, significant amounts of data have been produced regarding plant lncRNAs, and this amount is likely to increase in the subsequent years. In this review we have documented brief information about lncRNAs and their status of research in plants, along with the plant-specific resources/databases for information retrieval on lncRNAs.
58 citations
TL;DR: CirComPara is presented, an automated bioinformatics pipeline, to detect, quantify and annotate circRNAs from RNA-seq data using in parallel four different methods for back-splice identification and provides quantification of linear RNAs and gene expression.
Abstract: Circular RNAs (circRNAs) are generated by backsplicing of immature RNA forming covalently closed loops of intron/exon RNA molecules. Pervasiveness, evolutionary conservation, massive and regulated expression, and posttranscriptional regulatory roles of circRNAs in eukaryotes have been appreciated and described only recently. Moreover, being easily detectable disease markers, circRNAs undoubtedly represent a molecular class with high bearing on molecular pathobiology. CircRNAs can be detected from RNAseq data using appropriate computational methods to identify the sequence reads spanning backsplice junctions that do not colinearly map to the reference genome. To this end, several programs were developed and critical assessment of various strategies and tools suggested the combination of at least two methods as good practice to guarantee robust circRNA detection. Here,we present CirComPara (http://github.com/egaffo/CirComPara), an automated bioinformatics pipeline, to detect, quantify and annotate circRNAs from RNAseq data using in parallel four different methods for backsplice identification. CirComPara also provides quantification of linear RNAs and gene expression, ultimately comparing and correlating circRNA and gene/transcript expression level. We applied our method to RNAseqdata of monocyte and macrophage samples in relation to haploinsufficiency of the RNAbinding splicing factor Quaking (QKI). The biological relevance of the results, in terms of number, types and variations of circRNAs expressed, illustrates CirComPara potential to enlarge the knowledge of the transcriptome, adding details on the circRNAome, and facilitating further computational and experimental studies.
41 citations
TL;DR: It is found that although these miRNA qPCR methods possess high sensitivity for specific sequences, they also pick up background signals from closely related isomiRs, which influences the reliable quantification of individual isomiR.
Abstract: We sought to determine whether commercial quantitative polymerase chain reaction (qPCR) methods are capable of distinguishing isomiRs: variants of mature microRNAs (miRNAs) with sequence endpoint differences. We used two commercially available miRNA qPCR methods to quantify miR-21-5p in both synthetic and real cell contexts. We find that although these miRNA qPCR methods possess high sensitivity for specific sequences, they also pick up background signals from closely related isomiRs, which influences the reliable quantification of individual isomiRs. We conclude that these methods do not possess the requisite specificity for reliable isomiR quantification.
39 citations
TL;DR: Observations into hTAPAS as a novel player that negatively regulates hTERT expression and may be involved in telomere length homeostasis are provided.
Abstract: A novel antisense transcript was identified in the human telomerase reverse transcriptase (hTERT) promoter region, suggesting that the hTERT promoter is bidirectional. This transcript, named hTERT antisense promoter-associated (hTAPAS) RNA, is a 1.6 kb long non-coding RNA. hTAPAS transcription is initiated 167 nucleotides upstream of the hTERT transcription start site and is present in both the nucleus and the cytoplasm. Surprisingly, we observed that a large fraction of the hTERT polyadenylated RNA is localized in the nucleus, suggesting this might be an additional means of regulating the cellular abundance of hTERT protein. Both hTAPAS and hTERT are expressed in immortalized B-cells and human embryonic stem cells but are not detected in normal somatic cells. hTAPAS expression inversely correlates with hTERT expression in different types of cancer samples. Moreover, hTAPAS expression is not promoted by an hTERT promoter mutation (-124 C>T). Antisense-oligonucleotide mediated knockdown of hTAPAS results in an increase in hTERT expression. Conversely, ectopic overexpression of hTAPAS down regulates hTERT expression, suggesting a negative role in hTERT gene regulation. These observations provide insights into hTAPAS as a novel player that negatively regulates hTERT expression and may be involved in telomere length homeostasis.
36 citations
TL;DR: The expression of lncRNAs that are deregulated in patients with sepsis are reported, including subsets that display hub properties in molecular pathways relevant to the disease pathogenesis and that may participate in gene expression regulatory circuits related to the poorer disease outcome observed in elderly subjects.
Abstract: Sepsis is a major cause of death and its incidence and mortality increase exponentially with age. Most gene expression studies in sepsis have focused in protein-coding genes and the expression patterns, and potential roles of long noncoding RNAs (lncRNAs) have not been investigated yet. In this study, we performed co-expression network analysis of protein-coding and lncRNAs measured in neutrophil granulocytes from adult and elderly septic patients, along with age-matched healthy controls. We found that the genes displaying highest network similarity are predominantly differently expressed in sepsis and are enriched in loci encoding proteins with structural or regulatory functions related to protein translation and mitochondrial energetic metabolism. A number of lncRNAs are strongly connected to genes from these pathways and may take part in regulatory loops that are perturbed in sepsis. Among those, the ribosomal pseudogenes RP11-302F12.1 and RPL13AP7 are differentially expressed and appear to have a regulatory role on protein translation in both the elderly and adults, and lncRNAs MALAT1, LINC00355, MYCNOS, and AC010970.2 display variable connection strength and inverted expression patterns between adult and elderly networks, suggesting that they are the best candidates to be further studied to understand the mechanisms by which the immune response is impaired by age. In summary, we report the expression of lncRNAs that are deregulated in patients with sepsis, including subsets that display hub properties in molecular pathways relevant to the disease pathogenesis and that may participate in gene expression regulatory circuits related to the poorer disease outcome observed in elderly subjects.
27 citations
TL;DR: An attempt has been made to view the role of lncRNAs regulating immune responses in insects and evidence shows the importance of lNCRNAs in the regulation of host–pathogen interactions.
Abstract: Recent advances in modern technology have led to the understanding that not all genetic information is coded into protein and that the genomes of each and every organism including insects produce non-coding RNAs that can control different biological processes. Among RNAs identified in the last decade, long non-coding RNAs (lncRNAs) represent a repertoire of a hidden layer of internal signals that can regulate gene expression in physiological, pathological, and immunological processes. Evidence shows the importance of lncRNAs in the regulation of host–pathogen interactions. In this review, an attempt has been made to view the role of lncRNAs regulating immune responses in insects.
25 citations
TL;DR: This paper presents a network-based systems biology approach capable of extracting disease-perturbed subpathways within pathway networks in connection with expression data taken from The Cancer Genome Atlas (TCGA).
Abstract: In the era of network medicine, pathway analysis methods play a central role in the prediction of phenotype from high throughput experiments. In this paper, we present a network-based systems biology approach capable of extracting disease-perturbed subpathways within pathway networks in connection with expression data taken from The Cancer Genome Atlas (TCGA). Our system extends pathways with missing regulatory elements, such as microRNAs, and their interactions with genes. The framework enables the extraction, visualization, and analysis of statistically significant disease-specific subpathways through an easy to use web interface. Our analysis shows that the methodology is able to fill the gap in current techniques, allowing a more comprehensive analysis of the phenomena underlying disease states.
23 citations
TL;DR: The tools and databases for tDR identification and collection are summarized, with the aim of helping researchers choose the best tools for their analysis and inspiring the invention or improvement of tools in the field.
Abstract: tRNA-derived small RNAs (tDRs) are a group of small, non-coding RNAs derived from transfer RNAs (tRNAs). They can be classified as tRNA halves and tRNA-derived small RNA fragments (tRFs). Accumulating experimental evidence suggests their functional roles in cells and in various biological processes. Advances in next-generation sequencing (NGS) techniques allow a large amount of small RNA deep-sequencing data to be generated. To investigate tDRs from these data, software to identify tDRs and databases to retrieve or manage tDR data have been devised. In this review, we summarized the tools and databases for tDR identification and collection, with the aim of helping researchers choose the best tools for their analysis and inspiring the invention or improvement of tools in the field.
TL;DR: Cumulus cells play an essential role during oocyte maturation and the acquisition of fertilizability and developmental competence and it is concluded that miRNA expression in cumulus cells cannot be used as an oocyte quality marker.
Abstract: Cumulus cells play an essential role during oocyte maturation and the acquisition of fertilizability and developmental competence. Micro(mi)RNAs can post-transcriptionally regulate mRNA expression, and we hypothesized that miRNA profiles in cumulus cells could serve as an indicator of oocyte quality. Cumulus cell biopsies from cumulus-oocyte-complexes that either yielded a blastocyst or failed to cleave after exposure to sperm cells were analyzed for miRNA expression. On average, 332 miRNA species with more than 10 reads and 240 miRNA species with more than 50 reads were identified in cumulus cells; this included nine previously undescribed microRNAs. The most highly expressed miRNAs in cumulus cells were miR-21, members of the let-7 family and miR-155. However, no repeatable differences in miRNA expression between the cumulus cells from oocytes that became blastocysts versus those from non-cleaved oocytes were identified. Further examination of individual cumulus cell samples showed a wide variability in miRNA expression level. We therefore conclude that miRNA expression in cumulus cells cannot be used as an oocyte quality marker.
TL;DR: Analysis of TUG1 expression in 796 invasive breast carcinoma and 105 normal samples of RNA sequencing datasets from The Cancer Genome Atlas is described and it is described that Tug1 expression is increased in HER2-enriched and basal-like subtypes compared to luminal A.
Abstract: Taurine upregulated 1 gene (TUG1) is a long non-coding RNA associated with several types of cancer. Recently, differential expression of TUG1 was found in cancerous breast tissues and associated with breast cancer malignancy features. Although this is evidence of a potential role in breast cancer, TUG1 expression could not be associated with different subtypes, possibly due to the small number of samples analyzed. Breast cancer is a heterogeneous disease and, based on molecular signatures, may be classified into different subtypes with prognostic implications. In the present study, we include analysis of TUG1 expression in 796 invasive breast carcinoma and 105 normal samples of RNA sequencing (RNA-seq) datasets from The Cancer Genome Atlas (TCGA) and describe that TUG1 expression is increased in HER2-enriched and basal-like subtypes compared to luminal A. Additionally, TUG1 expression is associated with survival in HER2-enriched patients. These results reinforce the importance of TUG1 in breast cancer and outline its potential impact on specific subtypes.
TL;DR: The expression of HNRNPU processed transcript was increased in PDAC cell lines compared to noncancerous pancreatic cell lines; knockdown of this lncRNA further reduces proliferation and invasion/migration of pancreatic carcinoma cells.
Abstract: A gene array was used to profile the expression of 22,875 long non-coding RNAs (lncRNAs) and a large number of protein coding genes in 47 specimens of pancreatic ductal adenocarcinoma (PDAC), adjacent benign pancreas and the pancreas from patients without pancreatic disease. Of the lncRNAs profiled, the expression of 126 were significantly increased and 260 were decreased in the tumors (p < 0.05, 2-fold). The expression of one lncRNA in particular, heterogeneous nuclear ribonucleoprotein U (HNRNPU) processed transcript (also known as ncRNA00201) was among the most significantly deregulated (increased four-fold) in the tumors compared to normal/adjacent benign tissues. Increased expression of HNRNPU processed transcript was associated with poor prognosis for patients with PDAC. The expression of HNRNPU processed transcript was increased in PDAC cell lines compared to noncancerous pancreatic cell lines. LNATM gapmer mediated inhibition of HNRNPU processed transcript reduced cell proliferation in Patu-T and PL45 pancreatic cancer cell lines. Reduced invasion and migration was reported upon HNRNPU processed transcript knockdown in Patu-T cells. Small interfering RNA (siRNA) knockdown of the HNRNPU protein coding gene correlated with a 55% reduction in the HNRNPU processed transcript expression and a corresponding reduction in proliferation of Patu-T and PL45 cells. However, gapmer inhibition of HNRNPU processed transcript did not affect HNRNPU mRNA levels. The lncRNA HNRNPU processed transcript expression is increased in both PDAC tissues and cell lines; knockdown of this lncRNA further reduces proliferation and invasion/migration of pancreatic carcinoma cells.
TL;DR: This work proposes a workflow to predict lincRNAs on plants, considering a workflow that includes known bioinformatics tools together with machine learning techniques, here a support vector machine (SVM).
Abstract: Non-coding RNAs (ncRNAs) constitute an important set of transcripts produced in the cells of organisms. Among them, there is a large amount of a particular class of long ncRNAs that are difficult to predict, the so-called long intergenic ncRNAs (lincRNAs), which might play essential roles in gene regulation and other cellular processes. Despite the importance of these lincRNAs, there is still a lack of biological knowledge and, currently, the few computational methods considered are so specific that they cannot be successfully applied to other species different from those that they have been originally designed to. Prediction of lncRNAs have been performed with machine learning techniques. Particularly, for lincRNA prediction, supervised learning methods have been explored in recent literature. As far as we know, there are no methods nor workflows specially designed to predict lincRNAs in plants. In this context, this work proposes a workflow to predict lincRNAs on plants, considering a workflow that includes known bioinformatics tools together with machine learning techniques, here a support vector machine (SVM). We discuss two case studies that allowed to identify novel lincRNAs, in sugarcane (Saccharum spp.) and in maize (Zea mays). From the results, we also could identify differentially-expressed lincRNAs in sugarcane and maize plants submitted to pathogenic and beneficial microorganisms.
TL;DR: These RNA–Protein interaction database resources are continually updated, but the current state shows the efforts to identify and analyze the large amount of RNA-Protein interactions.
Abstract: RNA-protein interactions play critical roles in various biological processes. By collecting and analyzing the RNA-protein interactions and binding sites from experiments and predictions, RNA-protein interaction databases have become an essential resource for the exploration of the transcriptional and post-transcriptional regulatory network. Here, we briefly review several widely used RNA-protein interaction database resources developed in recent years to provide a guide of these databases. The content and major functions in databases are presented. The brief description of database helps users to quickly choose the database containing information they interested. In short, these RNA-protein interaction database resources are continually updated, but the current state shows the efforts to identify and analyze the large amount of RNA-protein interactions.
TL;DR: For the first time in a non-model plant, the global profiling to characterize the miRNAs and their associated pre-miRNAs are reported by applying a next generation sequencing approach.
Abstract: MicroRNAs (miRNAs) are crucial regulatory RNAs, originated from hairpin precursors. For the past decade, researchers have been focusing extensively on miRNA profiles in various plants. However, there have been few studies on the global profiling of precursor miRNAs (pre-miRNAs), even in model plants. Here, for the first time in a non-model plant-Abelmoschus esculentus with negligible genome information-we are reporting the global profiling to characterize the miRNAs and their associated pre-miRNAs by applying a next generation sequencing approach. Preliminarily, we performed small RNA (sRNA) sequencing with five biological replicates of leaf samples to attain 207,285,863 reads; data analysis using miRPlant revealed 128 known and 845 novel miRNA candidates. With the objective of seizing their associated hairpin precursors, we accomplished pre-miRNA sequencing to attain 83,269,844 reads. The paired end reads are merged and adaptor trimmed, and the resulting 40-241 nt (nucleotide) sequences were picked out for analysis by using perl scripts from the miRGrep tool and an in-house built shell script for Minimum Fold Energy Index (MFEI) calculation. Applying the stringent criteria of the Dicer cleavage pattern and the perfect stem loop structure, precursors for 57 known miRNAs of 15 families and 18 novel miRNAs were revealed. Quantitative Real Time (qRT) PCR was performed to determine the expression of selected miRNAs.
TL;DR: In this paper, the composition of ncRNAs and the fragments that derive from them in various tissues of Brassica rapa plants, including leaves, meristem tissue, pollen, unfertilized and fertilized ova, embryo and endosperm were analyzed.
Abstract: Recently, a novel type of non-coding RNA (ncRNA), known as ncRNA fragments or ncRFs, has been characterised in various organisms, including plants. The biogenesis mechanism, function and abundance of ncRFs stemming from various ncRNAs are poorly understood, especially in plants. In this work, we have computationally analysed the composition of ncRNAs and the fragments that derive from them in various tissues of Brassica rapa plants, including leaves, meristem tissue, pollen, unfertilized and fertilized ova, embryo and endosperm. Detailed analysis of transfer RNA (tRNA) fragments (tRFs), ribosomal RNA (rRNA) fragments (rRFs), small nucleolar RNA (snoRNA) fragments (snoRFs) and small nuclear RNA (snRNA) fragments (snRFs) showed a predominance of tRFs, with the 26 nucleotides (nt) fraction being the largest. Mapping ncRF reads to full-length mature ncRNAs showed a strong bias for one or both termini. tRFs mapped predominantly to the 5′ end, whereas snRFs mapped to the 3′ end, suggesting that there may be specific biogenesis and retention mechanisms. In the case of tRFs, specific isoacceptors were enriched, including tRNAGly(UCC) and tRFAsp(GUC). The analysis showed that the processing of 26-nt tRF5′ occurred by cleavage at the last unpaired nucleotide of the loop between the D arm and the anticodon arm. Further support for the functionality of ncRFs comes from the analysis of binding between ncRFs and their potential targets. A higher average percentage of binding at the first half of fragments was observed, with the highest percentage being at 2–6 nt. To summarise, our analysis showed that ncRFs in B. rapa are abundantly produced in a tissue-specific manner, with bias toward a terminus, the bias toward the size of generated fragments and the bias toward the targeting of specific biological processes.
TL;DR: It is concluded that the human transcriptome produces virtually no background of RNAs that are processed at effectively random positions, but is—under normal circumstances—confined to a well defined set of splice variants.
Abstract: Long non-coding RNAs (lncRNAs) form a substantial component of the transcriptome and are involved in a wide variety of regulatory mechanisms. Compared to protein-coding genes, they are often expressed at low levels and are restricted to a narrow range of cell types or developmental stages. As a consequence, the diversity of their isoforms is still far from being recorded and catalogued in its entirety, and the debate is ongoing about what fraction of non-coding RNAs truly conveys biological function rather than being “junk”. Here, using a collection of more than 100 transcriptomes from related B cell lymphoma, we show that lncRNA loci produce a very defined set of splice variants. While some of them are so rare that they become recognizable only in the superposition of dozens or hundreds of transcriptome datasets and not infrequently include introns or exons that have not been included in available genome annotation data, there is still a very limited number of processing products for any given locus. The combined depth of our sequencing data is large enough to effectively exhaust the isoform diversity: the overwhelming majority of splice junctions that are observed at all are represented by multiple junction-spanning reads. We conclude that the human transcriptome produces virtually no background of RNAs that are processed at effectively random positions, but is—under normal circumstances—confined to a well defined set of splice variants.
TL;DR: The results suggest that regulation by miR408 is important in sugarcane sensing whether microorganisms are either pathogenic or beneficial, triggering specific miRNA-mediated regulatory mechanisms accordingly.
Abstract: Studies have highlighted the importance of non-coding RNA regulation in plant-microbe interaction. However, the roles of sugarcane microRNAs (miRNAs) in the regulation of disease responses have not been investigated. Firstly, we screened the sRNA transcriptome of sugarcane infected with Acidovorax avenae. Conserved and novel miRNAs were identified. Additionally, small interfering RNAs (siRNAs) were aligned to differentially expressed sequences from the sugarcane transcriptome. Interestingly, many siRNAs aligned to a transcript encoding a copper-transporter gene whose expression was induced in the presence of A. avenae, while the siRNAs were repressed in the presence of A. avenae. Moreover, a long intergenic non-coding RNA was identified as a potential target or decoy of miR408. To extend the bioinformatics analysis, we carried out independent inoculations and the expression patterns of six miRNAs were validated by quantitative reverse transcription-PCR (qRT-PCR). Among these miRNAs, miR408-a copper-microRNA-was downregulated. The cleavage of a putative miR408 target, a laccase, was confirmed by a modified 5'RACE (rapid amplification of cDNA ends) assay. MiR408 was also downregulated in samples infected with other pathogens, but it was upregulated in the presence of a beneficial diazotrophic bacteria. Our results suggest that regulation by miR408 is important in sugarcane sensing whether microorganisms are either pathogenic or beneficial, triggering specific miRNA-mediated regulatory mechanisms accordingly.
TL;DR: A bioinformatic pipeline has been recently set up that, by exploiting RNA-seq features and knowledge of SINE transcription mechanisms, allows for easy identification and profiling of transcriptionally active genomic loci which are a source of genuine Pol III SINE transcripts.
Abstract: Short Interspersed Element (SINE) retrotransposons are one of the most abundant DNA repeat elements in the human genome. They have been found to impact the expression of protein-coding genes, but the possible roles in cell physiology of their noncoding RNAs, generated by RNA polymerase (Pol) III, are just starting to be elucidated. For this reason, Short Interspersed Element (SINE) expression profiling is becoming mandatory to obtain a comprehensive picture of their regulatory roles. However, their repeated nature and frequent location within Pol II-transcribed genes represent a serious obstacle to the identification and quantification of genuine, Pol III-derived SINE transcripts at single-locus resolution on a genomic scale. Among the recent Next Generation Sequencing technologies, only RNA sequencing (RNA-Seq) holds the potential to solve these issues, even though both technical and biological matters need to be taken into account. A bioinformatic pipeline has been recently set up that, by exploiting RNA-seq features and knowledge of SINE transcription mechanisms, allows for easy identification and profiling of transcriptionally active genomic loci which are a source of genuine Pol III SINE transcripts.
TL;DR: OncoNcRNA, a user-friendly web portal to explore ncRNAs with oncogenic potential in human cancers, and Correlations, a web-based tool to explore the relationships between gene expression and copy number from ~10,000 tumor samples in 36 cancer types identified by The Cancer Genome Atlas.
Abstract: Non-coding RNAs (ncRNAs) have been shown to contribute to tumorigenesis and progression. However, the functions of the majority of ncRNAs remain unclear. Through integrating published large-scale somatic copy number alterations (SCNAs) data from various human cancer types, we have developed oncoNcRNA, a user-friendly web portal to explore ncRNAs with oncogenic potential in human cancers. The portal characterizes the SCNAs of over 58,000 long non-coding RNAs (lncRNAs), 34,000 piwi-interacting RNAs (piRNAs), 2700 microRNAs (miRNAs), 600 transfer RNAs (tRNAs) and 400 small nucleolar RNAs (snoRNAs) in 64 human cancer types. It enables researchers to rapidly and intuitively analyze the oncogenic potential of ncRNAs of interest. Indeed, we have discovered a large number of ncRNAs which are frequently amplified or deleted within and across tumor types. Moreover, we built a web-based tool, Correlations, to explore the relationships between gene expression and copy number from ~10,000 tumor samples in 36 cancer types identified by The Cancer Genome Atlas (TCGA). oncoNcRNA is a valuable tool for investigating the function and clinical relevance of ncRNAs in human cancers. oncoNcRNA is freely available at http://rna.sysu.edu.cn/onconcrna/.
TL;DR: The development of MicroRNA MultiTool is detailed, a software for the identification of miRNA from mass spectrometric data interpretation that includes capabilities such as miRNA search and mass calculator, modified miRNA mass Calculator, and miRNA fragment search.
Abstract: microRNA (miRNA) are short endogenous non-coding RNA that play a crucial role in post-transcriptional gene regulation and have been implicated in the initiation and progression of 160+ human diseases. Excellent analytical methods have been developed for the measurement of miRNA by mass spectrometry. However, interpretation of mass spectrometric data has been an incapacitating bottleneck in miRNA identification. This study details the development of MicroRNA MultiTool, a software for the identification of miRNA from mass spectrometric data. The software includes capabilities such as miRNA search and mass calculator, modified miRNA mass calculator, and miRNA fragment search. MicroRNA MultiTool bridges the gap between experimental data and identification of miRNA by providing a rapid means of mass spectrometric data interpretation.
TL;DR: A comprehensive homology search and detailed analysis of the evolution of sequence and secondary structure features covering the entire kingdom Fungi is reported on.
Abstract: The U3 small nucleolar RNA (snoRNA) is an essential player in the initial steps of ribosomal RNA biogenesis which is ubiquitously present in Eukarya. It is exceptional among the small nucleolar RNAs in its size, the presence of multiple conserved sequence boxes, a highly conserved secondary structure core, its biogenesis as an independent gene transcribed by polymerase III, and its involvement in pre-rRNA cleavage rather than chemical modification. Fungal U3 snoRNAs share many features with their sisters from other eukaryotic kingdoms but differ from them in particular in their 5' regions, which in fungi has a distinctive consensus structure and often harbours introns. Here we report on a comprehensive homology search and detailed analysis of the evolution of sequence and secondary structure features covering the entire kingdom Fungi.