antiCODE: a natural sense-antisense transcripts database

OverGeneDB: a database of 5' end protein coding overlapping genes in human and mouse genomes

Gene overlap plays various regulatory functions on transcriptional and post-transcriptional levels. Most current studies focus on protein-coding genes overlapping with non-protein-coding counterparts, the so called natural antisense transcripts. Considerably less is known about the role of gene overlap in the case of two protein-coding genes. Here, we provide OverGeneDB, a database of human and mouse 5′ end protein-coding overlapping genes. The database contains 582 human and 113 mouse gene pairs that are transcribed using overlapping promoters in at least one analyzed library. Gene pairs were identified based on the analysis of the transcription start site (TSS) coordinates in 73 human and 10 mouse organs, tissues and cell lines. Beside TSS data, resources for 26 human lung adenocarcinoma cell lines also contain RNA-Seq and ChIP-Seq data for seven histone modifications and RNA Polymerase II activity. The collected data revealed that the overlap region is rarely conserved between the studied species and tissues. In ∼50% of the overlapping genes, transcription started explicitly in the overlap regions. In the remaining half of overlapping genes, transcription was initiated both from overlapping and non-overlapping TSSs. OverGeneDB is accessible at http://overgenedb.amu.edu.pl.

Noncoding RNAs Databases: Current Status and Trends

One of the most important resources for researchers of noncoding RNAs is the information available in public databases spread over the internet. However, the effective exploration of this data can represent a daunting task, given the large amount of databases available and the variety of stored data. This chapter describes a classification of databases based on information source, type of RNA, source organisms, data formats, and the mechanisms for information retrieval, detailing the relevance of each of these classifications and its usability by researchers. This classification is used to update a 2012 review, indexing now more than 229 public databases. This review will include an assessment of the new trends for ncRNA research based on the information that is being offered by the databases. Additionally, we will expand the previous analysis focusing on the usability and application of these databases in pathogen and disease research. Finally, this chapter will analyze how currently available database schemas can help the development of new and improved web resources.

Long non-coding RNAs and complex diseases: from experimental results to computational models

LncRNAs have attracted lots of attentions from researchers worldwide in recent decades. With the rapid advances in both experimental technology and computational prediction algorithm, thousands of lncRNA have been identified in eukaryotic organisms ranging from nematodes to humans in the past few years. More and more research evidences have indicated that lncRNAs are involved in almost the whole life cycle of cells through different mechanisms and play important roles in many critical biological processes. Therefore, it is not surprising that the mutations and dysregulations of lncRNAs would contribute to the development of various human complex diseases. In this review, we first made a brief introduction about the functions of lncRNAs, five important lncRNA-related diseases, five critical disease-related lncRNAs and some important publicly available lncRNA-related databases about sequence, expression, function, etc. Nowadays, only a limited number of lncRNAs have been experimentally reported to be related to human diseases. Therefore, analyzing available lncRNA–disease associations and predicting potential human lncRNA–disease associations have become important tasks of bioinformatics, which would benefit human complex diseases mechanism understanding at lncRNA level, disease biomarker detection and disease diagnosis, treatment, prognosis and prevention. Furthermore, we introduced some state-of-the-art computational models, which could be effectively used to identify disease-related lncRNAs on a large scale and select the most promising disease-related lncRNAs for experimental validation. We also analyzed the limitations of these models and discussed the future directions of developing computational models for lncRNA research.

Using the NONCODE Database Resource

NONCODE is a comprehensive database that aims to present the most complete collection and annotation of non-coding RNAs, especially long non-coding RNAs (lncRNA genes), and thus NONCODE is essential to modern biological and medical research. Scientists are producing a flood of new data from which new lncRNA genes and lncRNA-disease relationships are continually being identified. NONCODE assimilates such information from a wide variety of sources including published articles, RNA-seq data, micro-array data and databases on genetic variation (dbSNP) and genome-wide associations (GWAS). NONCODE organizes all this information and makes it freely available to the public via the Internet. The NONCODE protocol provides step-by-step instructions on how to browse and search lncRNA information such as sequence, expression, and disease relationships, how to use the tools for functional prediction, species conservation assays, blast analysis, identifier conversion, and, finally, how to submit sequences to identify lncRNA genes. As of Dec 2016, NONCODE has cataloged 487,851 lncRNA genes sequenced from 16 species. © 2017 by John Wiley & Sons, Inc.

The Evolution and Expression Pattern of Human Overlapping lncRNA and Protein-coding Gene Pairs

Long non-coding RNA overlapping with protein-coding gene (lncRNA-coding pair) is a special type of overlapping genes. Protein-coding overlapping genes have been well studied and increasing attention has been paid to lncRNAs. By studying lncRNA-coding pairs in human genome, we showed that lncRNA-coding pairs were more likely to be generated by overprinting and retaining genes in lncRNA-coding pairs were given higher priority than non-overlapping genes. Besides, the preference of overlapping configurations preserved during evolution was based on the origin of lncRNA-coding pairs. Further investigations showed that lncRNAs promoting the splicing of their embedded protein-coding partners was a unilateral interaction, but the existence of overlapping partners improving the gene expression was bidirectional and the effect was decreased with the increased evolutionary age of genes. Additionally, the expression of lncRNA-coding pairs showed an overall positive correlation and the expression correlation was associated with their overlapping configurations, local genomic environment and evolutionary age of genes. Comparison of the expression correlation of lncRNA-coding pairs between normal and cancer samples found that the lineage-specific pairs including old protein-coding genes may play an important role in tumorigenesis. This work presents a systematically comprehensive understanding of the evolution and the expression pattern of human lncRNA-coding pairs.

Computational Approaches for Revealing the Structure of Membrane Transporters: Case Study on Bilitranslocase

The structural and functional details of transmembrane proteins are vastly underexplored, mostly due to experimental difficulties regarding their solubility and stability. Currently, the majority of transmembrane protein structures are still unknown and this present a huge experimental and computational challenge. Nowadays, thanks to X-ray crystallography or NMR spectroscopy over 3000 structures of membrane proteins have been solved, among them only a few hundred unique ones. Due to the vast biological and pharmaceutical interest in the elucidation of the structure and the functional mechanisms of transmembrane proteins, several computational methods have been developed to overcome the experimental gap. If combined with experimental data the computational information enables rapid, low cost and successful predictions of the molecular structure of unsolved proteins. The reliability of the predictions depends on the availability and accuracy of experimental data associated with structural information. In this review, the following methods are proposed for in silico structure elucidation: sequence-dependent predictions of transmembrane regions, predictions of transmembrane helix–helix interactions, helix arrangements in membrane models, and testing their stability with molecular dynamics simulations. We also demonstrate the usage of the computational methods listed above by proposing a model for the molecular structure of the transmembrane protein bilitranslocase. Bilitranslocase is bilirubin membrane transporter, which shares similar tissue distribution and functional properties with some of the members of the Organic Anion Transporter family and is the only member classified in the Bilirubin Transporter Family. Regarding its unique properties, bilitranslocase is a potentially interesting drug target.

NONCODE 2016: an informative and valuable data source of long non-coding RNAs

NONCODE (http://www.bioinfo.org/noncode/) is an interactive database that aims to present the most complete collection and annotation of non-coding RNAs, especially long non-coding RNAs (lncRNAs). The recently reduced cost of RNA sequencing has produced an explosion of newly identified data. Revolutionary third-generation sequencing methods have also contributed to more accurate annotations. Accumulative experimental data also provides more comprehensive knowledge of lncRNA functions. In this update, NONCODE has added six new species, bringing the total to 16 species altogether. The lncRNAs in NONCODE have increased from 210 831 to 527,336. For human and mouse, the lncRNA numbers are 167,150 and 130,558, respectively. NONCODE 2016 has also introduced three important new features: (i) conservation annotation; (ii) the relationships between lncRNAs and diseases; and (iii) an interface to choose high-quality datasets through predicted scores, literature support and long-read sequencing method support. NONCODE is also accessible through http://www.noncode.org/.

Evolutionary annotation of conserved long non-coding RNAs in major mammalian species

Mammalian genomes contain tens of thousands of long non-coding RNAs (lncRNAs) that have been implicated in diverse biological processes. However, the lncRNA transcriptomes of most mammalian species have not been established, limiting the evolutionary annotation of these novel transcripts. Based on RNA sequencing data from six tissues of nine species, we built comprehensive lncRNA catalogs (4,142–42,558 lncRNAs) covering the major mammalian species. Compared to protein- coding RNAs, expression of lncRNAs exhibits striking lineage specificity. Notably, although 30%–99% human lncRNAs are conserved across different species on DNA locus level, only 20%–27% of these conserved lncRNA loci are detected to transcription, which represents a stark contrast to the proportion of conserved protein-coding genes (48%–80%). This finding provides a valuable resource for experimental scientists to study the mechanisms of lncRNAs. Moreover, we constructed lncRNA expression phylogenetic trees across nine mammals and demonstrated that lncRNA expression profiles can reliably determine phylogenic placement in a manner similar to their coding counterparts. Our data also reveal that the evolutionary rate of lncRNA expression varies among tissues and is significantly higher than those for protein-coding genes. To streamline the processes of browsing lncRNAs and detecting their evolutionary statuses, we integrate all the data produced in this study into a database named PhyloNONCODE (http://www.bioinfo.org/phyloNoncode). Our work starts to place mammalian lncRNAs in an evolutionary context and represent a rich resource for comparative and functional analyses of this critical layer of genome.

RNA regulatory networks in animals and plants: a long noncoding RNA perspective

A recent highlight of genomics research has been the discovery of many families of transcripts which have function but do not code for proteins. An important group is long noncoding RNAs (lncRNAs), which are typically longer than 200 nt, and whose members originate from thousands of loci across genomes. We review progress in understanding the biogenesis and regulatory mechanisms of lncRNAs. We describe diverse computational and high throughput technologies for identifying and studying lncRNAs. We discuss the current knowledge of functional elements embedded in lncRNAs as well as insights into the lncRNA-based regulatory network in animals. We also describe genome-wide studies of large amount of lncRNAs in plants, as well as knowledge of selected plant lncRNAs with a focus on biotic/abiotic stress-responsive lncRNAs.

Genome-wide identification of long noncoding natural antisense transcripts and their responses to light in Arabidopsis

Recent research on long noncoding RNAs (lncRNAs) has expanded our understanding of gene transcription regulation and the generation of cellular complexity. Depending on their genomic origins, lncRNAs can be transcribed from intergenic or intragenic regions or from introns of protein-coding genes. We have recently reported more than 6000 intergenic lncRNAs in Arabidopsis. Here, we systematically identified long noncoding natural antisense transcripts (lncNATs), defined as lncRNAs transcribed from the opposite DNA strand of coding or noncoding genes. We found a total of 37,238 sense–antisense transcript pairs and 70% of annotated mRNAs to be associated with antisense transcripts in Arabidopsis. These lncNATs could be reproducibly detected by different technical platforms, including strand-specific tiling arrays, Agilent custom expression arrays, strand-specific RNA-seq, and qRT-PCR experiments. Moreover, we investigated the expression profiles of sense–antisense pairs in response to light and observed spatial and developmental-specific light effects on 626 concordant and 766 discordant NAT pairs. Genes for a large number of the light-responsive NAT pairs are associated with histone modification peaks, and histone acetylation is dynamically correlated with light-responsive expression changes of NATs.

Long non-coding RNAs and complex human diseases

Long non-coding RNAs (lncRNAs) are a heterogeneous class of RNAs that are generally defined as non-protein-coding transcripts longer than 200 nucleotides. Recently, an increasing number of studies have shown that lncRNAs can be involved in various critical biological processes, such as chromatin remodeling, gene transcription, and protein transport and trafficking. Moreover, lncRNAs are dysregulated in a number of complex human diseases, including coronary artery diseases, autoimmune diseases, neurological disorders, and various cancers, which indicates their important roles in these diseases. Here, we reviewed the current understanding of lncRNAs, including their definition and subclassification, regulatory functions, and potential roles in different types of complex human diseases.

Multiple-omic data analysis of Klebsiella pneumoniae MGH 78578 reveals its transcriptional architecture and regulatory features

Background

The increasing number of infections caused by strains of Klebsiella pneumoniae that are resistant to multiple antibiotics has developed into a major medical problem worldwide. The development of next-generation sequencing technologies now permits rapid sequencing of many K. pneumoniae isolates, but sequence information alone does not provide important structural and operational information for its genome.

Results

Here we take a systems biology approach to annotate the K. pneumoniae MGH 78578 genome at the structural and operational levels. Through the acquisition and simultaneous analysis of multiple sample-matched –omics data sets from two growth conditions, we detected 2677, 1227, and 1066 binding sites for RNA polymerase, RpoD, and RpoS, respectively, 3660 RNA polymerase-guided transcript segments, and 3585 transcription start sites throughout the genome. Moreover, analysis of the transcription start site data identified 83 probable leaderless mRNAs, while analysis of unannotated transcripts suggested the presence of 119 putative open reading frames, 15 small RNAs, and 185 antisense transcripts that are not currently annotated.

Conclusions

These findings highlight the strengths of systems biology approaches to the refinement of sequence-based annotations, and to provide new insight into fundamental genome-level biology for this important human pathogen.

The role and clinical implications of microRNAs in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is common and one of the most aggressive of all human cancers. Recent studies have indicated that miRNAs, a class of small noncoding RNAs that regulate gene expression post-transcriptionally, directly contribute to HCC by targeting many critical regulatory genes. Several miRNAs are involved in hepatitis B or hepatitis C virus replication and virus-induced changes, whereas others participate in multiple intracellular signaling pathways that modulate apoptosis, cell cycle checkpoints, and growth-factor-stimulated responses. When disturbed, these pathways appear to result in malignant transformation and ultimately HCC development. Recently, miRNAs circulating in the blood have acted as possible early diagnostic markers for HCC. These miRNA also could serve as indicators with respect to drug efficacy and be prognostic in HCC patients. Such biomarkers would assist stratification of HCC patients and help direct personalized therapy. Here, we summarize recent advances regarding the role of miRNAs in HCC development and progression. Our expectation is that these and ongoing studies will contribute to the understanding of the multiple roles of these small noncoding RNAs in liver tumorigenesis.

Transcriptional regulation of translocator protein (Tspo) via a SINE B2-mediated natural antisense transcript in MA-10 Leydig cells

Translocator protein (18 kDa; TSPO) is a mitochondrial cholesterol- and drug-binding protein involved in cholesterol import into mitochondria, the rate-limiting step in steroidogenesis. TSPO is expressed at high levels in Leydig cells of the testis, and its expression levels dictate the ability of the cells to form androgen. In search of mechanisms that regulate Tspo expression, a number of transcription factors acting on its promoter region have been identified. We report herein the presence of a mechanism of regulation of Tspo expression via complementation with a natural antisense transcript (NAT). At the Tspo locus, a short interspersed repetitive element (SINE) of the SINE B2 family has the potential for high transcriptional activity. The extension of the SINE B2 element-mediated transcript overlapped with exon 3 of the Tspo gene and formed a NAT specific for Tspo (Tspo-NAT) in MA-10 mouse tumor Leydig cells. The identified Tspo-NAT was also found in testis and kidney tissues. Overexpression of the Tspo-NAT regulated Tspo gene expression and its function in steroid formation in MA-10 cells. Time-course studies have indicated that Tspo-NAT expression is regulated by cAMP and could regulate TSPO levels to maintain optimal steroid production by MA-10 Leydig cells. Taken together, these results suggest a new micro-transcriptional mechanism that regulates Tspo expression and thus steroidogenesis via an intron-based SINE B2-driven NAT specific for the Tspo gene.

Arabidopsis Argonaute10 specifically sequesters miR166/165 to regulate shoot apical meristem development

The shoot apical meristem (SAM) comprises a group of undifferentiated cells that divide to maintain the plant meristem and also give rise to all shoot organs. SAM fate is specified by class III HOMEODOMAIN-LEUCINE ZIPPER (HD-ZIP III) transcription factors, which are targets of miR166/165. In Arabidopsis, AGO10 is a critical regulator of SAM maintenance, and here we demonstrate that AGO10 specifically interacts with miR166/165. The association is determined by a distinct structure of the miR166/165 duplex. Deficient loading of miR166 into AGO10 results in a defective SAM. Notably, the miRNA-binding ability of AGO10, but not its catalytic activity, is required for SAM development, and AGO10 has a higher binding affinity for miR166 than does AGO1, a principal contributor to miRNA-mediated silencing. We propose that AGO10 functions as a decoy for miR166/165 to maintain the SAM, preventing their incorporation into AGO1 complexes and the subsequent repression of HD-ZIP III gene expression.

RNAi screen indicates widespread biological function for human natural antisense transcripts

Natural antisense transcripts represent a class of regulatory RNA molecules, which are characterized by their complementary sequence to another RNA transcript. Extensive sequencing efforts suggest that natural antisense transcripts are prevalent throughout the mammalian genome; however, their biological significance has not been well defined. We performed a loss-of-function RNA interference (RNAi) screen, which targeted 797 evolutionary conserved antisense transcripts, and found evidence for a regulatory role for a number of natural antisense transcripts. Specifically, we found that natural antisense transcripts for CCPG1 and RAPGEF3 may functionally disrupt signaling pathways and corresponding biological phenotypes, such as cell viability, either independently or in parallel with the corresponding sense transcript. Our results show that the large-scale siRNA screen can be applied to evaluate natural antisense transcript modulation of fundamental cellular events.

Natural antisense transcripts regulate gene expression in an epigenetic manner

Cytosine DNA methylation, covalent histone modifications, and RNA-mediated gene regulation are the major aspects of epigenetic regulation. Natural antisense transcripts (NATs), as a new member of regulatory RNAs, occur ubiquitously in prokaryote and eukaryote, and play significant roles in physiological or pathological processes. NATs, mostly non-coding RNAs, are involved in transcriptional interference, genomic imprinting, X inactivation, RNA editing, translational regulation, RNA export, DNA methylation, histone modifications, and so on. NATs regulate gene expression through direct interaction with the sense transcripts or indirect interaction with other targets, such as DNA methyltransferases, histone acetylases and histone deacetylases. There may be a direct link among NATs, DNA methylaton and histone modifications. Through formation of sense-antisense duplex structures, NATs exert a widespread impact on conventional gene expression at the mRNA and/or protein level and regulate sense transcripts in a concordant or discordant manner. As one of the important components in epigenetics, NATs could be a potentially rich source for scientists to exploit in the therapy of cancers and other diseases.

Identification of differentially expressed sense and antisense transcript pairs in breast epithelial tissues

BACKGROUND

More than 20% of human transcripts have naturally occurring antisense products (or natural antisense transcripts--NATs), some of which may play a key role in a range of human diseases. To date, several databases of in silico defined human sense-antisense (SAS) pairs have appeared, however no study has focused on differential expression of SAS pairs in breast tissue. We therefore investigated the expression levels of sense and antisense transcripts in normal and malignant human breast epithelia using the Affymetrix HG-U133 Plus 2.0 and Almac Diagnostics Breast Cancer DSA microarray technologies as well as massively parallel signature sequencing (MPSS) data.

RESULTS

The expression of more than 2500 antisense transcripts were detected in normal breast duct luminal cells and in primary breast tumors substantially enriched for their epithelial cell content by DSA microarray. Expression of 431 NATs were confirmed by either of the other two technologies. A corresponding sense transcript could be identified on DSA for 257 antisense transcripts. Of these SAS pairs, 163 have not been previously reported. A positive correlation of differential expression between normal and malignant breast samples was observed for most SAS pairs. Orientation specific RT-QPCR of selected SAS pairs validated their expression in several breast cancer cell lines and solid breast tumours.

CONCLUSION

Disease-focused and antisense enriched microarray platforms (such as Breast Cancer DSA) confirm the assumption that antisense transcription in the human breast is more prevalent than previously anticipated. Expression of a proportion of these NATs has already been confirmed by other technologies while the true existence of the remaining ones has to be validated. Nevertheless, future studies will reveal whether the relative abundances of antisense and sense transcripts have regulatory influences on the translation of these mRNAs.

An Ariadne's thread to the identification and annotation of noncoding RNAs in eukaryotes

Non-protein coding RNAs (ncRNAs) have emerged as a vast and heterogeneous portion of eukaryotic transcriptomes. Several ncRNA families, either short (<200 nucleotides, nt) or long (>200 nt), have been described and implicated in a variety of biological processes, from translation to gene expression regulation and nuclear trafficking. Most probably, other families are still to be discovered. Computational methods for ncRNA research require different approaches from the ones normally used in the prediction of protein-coding genes. Indeed, primary sequence alone is often insufficient to infer ncRNA functionality, whereas secondary structure and local conservation of portions of the transcript could provide useful information for both the prediction and the functional annotation of ncRNAs. Here we present an overview of computational methods and bioinformatics resources currently available for studying ncRNA genes, introducing the common themes as well as the different approaches required for long and short ncRNA identification and annotation.

Mapping of small RNAs in the human ENCODE regions

The elucidation of the largely unknown transcriptome of small RNAs is crucial for the understanding of genome and cellular function. We report here the results of the analysis of small RNAs (< 50 nt) in the ENCODE regions of the human genome. Size-fractionated RNAs from four different cell lines (HepG2, HelaS3, GM06990, SK-N-SH) were mapped with the forward and reverse ENCODE high-density resolution tiling arrays. The top 1% of hybridization signals are termed SmRfrags (Small RNA fragments). Eight percent of SmRfrags overlap the GENCODE genes (CDS), given that the majority map to intergenic regions (34%), intronic regions (53%), and untranslated regions (UTRs) (5%). In addition, 9.6% and 16.8% of SmRfrags in the 5' UTR regions overlap significantly with His/Pol II/TAF250 binding sites and DNase I Hypersensitive sites, respectively (compared to the 5.3% and 9% expected). Interestingly, 17%-24% (depending on the cell line) of SmRfrags are sense-antisense strand pairs that show evidence of overlapping transcription. Only 3.4% and 7.2% of SmRfrags in intergenic regions overlap transcribed fragments (Txfrags) in HeLa and GM06990 cell lines, respectively. We hypothesized that a fraction of the identified SmRfrags corresponded to microRNAs. We tested by Northern blot a set of 15 high-likelihood predictions of microRNA candidates that overlap with smRfrags and validated three potential microRNAs ( approximately 20 nt length). Notably, most of the remaining candidates showed a larger hybridizing band ( approximately 100 nt) that could be a microRNA precursor. The small RNA transcriptome is emerging as an important and abundant component of the genome function.