NONCODEv4: exploring the world of long non-coding RNA genes

Whole-genome bisulfite sequencing maps from multiple human tissues reveal novel CpG islands associated with tissue-specific regulation

CpG islands (CGIs) are one of the most widely studied regulatory features of the human genome, with critical roles in development and disease. Despite such significance and the original epigenetic definition, currently used CGI sets are typically predicted from DNA sequence characteristics. Although CGIs are deeply implicated in practical analyses of DNA methylation, recent studies have shown that such computational annotations suffer from inaccuracies. Here we used whole-genome bisulfite sequencing from 10 diverse human tissues to identify a comprehensive, experimentally obtained, single-base resolution CGI catalog. In addition to the unparalleled annotation precision, our method is free from potential bias due to arbitrary sequence features or probe affinity differences. In addition to clarifying substantial false positives in the widely used University of California Santa Cruz (UCSC) annotations, our study identifies numerous novel epigenetic loci. In particular, we reveal significant impact of transposable elements on the epigenetic regulatory landscape of the human genome and demonstrate ubiquitous presence of transcription initiation at CGIs, including alternative promoters in gene bodies and non-coding RNAs in intergenic regions. Moreover, coordinated DNA methylation and chromatin modifications mark tissue-specific enhancers at novel CGIs. Enrichment of specific transcription factor binding from ChIP-seq supports mechanistic roles of CGIs on the regulation of tissue-specific transcription. The new CGI catalog provides a comprehensive and integrated list of genomic hotspots of epigenetic regulation.

A catalogue of novel bovine long noncoding RNA across 18 tissues

Long non-coding RNA (lncRNA) have been implicated in diverse biological roles including gene regulation and genomic imprinting. Identifying lncRNA in bovine across many differing tissue would contribute to the current repertoire of bovine lncRNA, and help further improve our understanding of the evolutionary importance and constraints of these transcripts. Additionally, it could aid in identifying sites in the genome outside of protein coding genes where mutations could contribute to variation in complex traits. This is particularly important in bovine as genomic predictions are increasingly used in genetic improvement for milk and meat production. Our aim was to identify and annotate novel long non coding RNA transcripts in the bovine genome captured from RNA Sequencing (RNA-Seq) data across 18 tissues, sampled in triplicate from a single cow. To address the main challenge in identifying lncRNA, namely distinguishing lncRNA transcripts from unannotated genes and protein coding genes, a lncRNA identification pipeline with a number of filtering steps was developed. A total of 9,778 transcripts passed the filtering pipeline. The bovine lncRNA catalogue includes MALAT1 and HOTAIR, both of which have been well described in human and mouse genomes. We attempted to validate the lncRNA in libraries from three additional cows. 726 (87.47%) liver and 1,668 (55.27%) blood class 3 lncRNA were validated with stranded liver and blood libraries respectively. Additionally, this study identified a large number of novel unknown transcripts in the bovine genome with high protein coding potential, illustrating a clear need for better annotations of protein coding genes.

Lnc2Cancer: a manually curated database of experimentally supported lncRNAs associated with various human cancers

Lnc2Cancer (http://www.bio-bigdata.net/lnc2cancer) is a manually curated database of cancer-associated long non-coding RNAs (lncRNAs) with experimental support that aims to provide a high-quality and integrated resource for exploring lncRNA deregulation in various human cancers. LncRNAs represent a large category of functional RNA molecules that play a significant role in human cancers. A curated collection and summary of deregulated lncRNAs in cancer is essential to thoroughly understand the mechanisms and functions of lncRNAs. Here, we developed the Lnc2Cancer database, which contains 1057 manually curated associations between 531 lncRNAs and 86 human cancers. Each association includes lncRNA and cancer name, the lncRNA expression pattern, experimental techniques, a brief functional description, the original reference and additional annotation information. Lnc2Cancer provides a user-friendly interface to conveniently browse, retrieve and download data. Lnc2Cancer also offers a submission page for researchers to submit newly validated lncRNA-cancer associations. With the rapidly increasing interest in lncRNAs, Lnc2Cancer will significantly improve our understanding of lncRNA deregulation in cancer and has the potential to be a timely and valuable resource.

An integrative transcriptomic analysis reveals p53 regulated miRNA, mRNA, and lncRNA networks in nasopharyngeal carcinoma

It has been reported that p53 dysfunction is closely related to the carcinogenesis of nasopharyngeal carcinoma (NPC). Recently, an increasing body of evidence has indicated that microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) participate in p53-associated signaling pathways and, in addition to mRNAs, form a complex regulation network to promote tumor occurrence and progression. The aim of this study was to elucidate the p53-regulated miRNAs, mRNAs, and lncRNAs and their regulating networks in NPC. Firstly, we overexpressed p53 in the NPC cell line HNE2 and performed transcriptomic gene expression profiling (GEP) analysis, which included miRNAs, mRNAs, and lncRNAs, using microarray technology at 0, 12, 24, and 48 h after transfection. There were 38 miRNAs (33 upregulated and 5 downregulated), 2107 mRNAs (296 upregulated and 1811 downregulated), and 1190 lncRNAs (133 upregulated and 1057 downregulated) that were significantly dysregulated by p53. Some of the dysregulated molecules were confirmed by quantitative real-time polymerase chain reaction (qRT-PCR). Then, we integrated previously published miRNAs, mRNAs, and lncRNAs GEP datasets from NPC biopsies to investigate the expression of these p53 regulated molecules and found that 7 miRNAs, 218 mRNAs, and 101 lncRNAs regulated by p53 were also differentially expressed in NPC tissues. Finally, p53-regulated miRNA, mRNA, and lncRNA networks were constructed using bioinformatics methods. These miRNAs, mRNAs, and lncRNAs may participate in p53 downstream signaling pathways and play important roles in the carcinogenesis of NPC. Thorough investigations of their biological functions and regulating relationships will provide a novel view of the p53 signaling pathway, and the restoration of p53 functioning or its downstream gene regulating network is potentially of great value in treating NPC patients.

Hepatic Long Intergenic Noncoding RNAs: High Promoter Conservation and Dynamic, Sex-Dependent Transcriptional Regulation by Growth Hormone

Long intergenic noncoding RNAs (lincRNAs) are increasingly recognized as key chromatin regulators, yet few studies have characterized lincRNAs in a single tissue under diverse conditions. Here, we analyzed 45 mouse liver RNA sequencing (RNA-Seq) data sets collected under diverse conditions to systematically characterize 4,961 liver lincRNAs, 59% of them novel, with regard to gene structures, species conservation, chromatin accessibility, transcription factor binding, and epigenetic states. To investigate the potential for functionality, we focused on the responses of the liver lincRNAs to growth hormone stimulation, which imparts clinically relevant sex differences to hepatic metabolism and liver disease susceptibility. Sex-biased expression characterized 247 liver lincRNAs, with many being nuclear RNA enriched and regulated by growth hormone. The sex-biased lincRNA genes are enriched for nearby and correspondingly sex-biased accessible chromatin regions, as well as sex-biased binding sites for growth hormone-regulated transcriptional activators (STAT5, hepatocyte nuclear factor 6 [HNF6], FOXA1, and FOXA2) and transcriptional repressors (CUX2 and BCL6). Repression of female-specific lincRNAs in male liver, but not that of male-specific lincRNAs in female liver, was associated with enrichment of H3K27me3-associated inactive states and poised (bivalent) enhancer states. Strikingly, we found that liver-specific lincRNA gene promoters are more highly species conserved and have a significantly higher frequency of proximal binding by liver transcription factors than liver-specific protein-coding gene promoters. Orthologs for many liver lincRNAs were identified in one or more supraprimates, including two rat lincRNAs showing the same growth hormone-regulated, sex-biased expression as their mouse counterparts. This integrative analysis of liver lincRNA chromatin states, transcription factor occupancy, and growth hormone regulation provides novel insights into the expression of sex-specific lincRNAs and their potential for regulation of sex differences in liver physiology and disease.

Potential Gene Interactions in the Cell Cycles of Gametes, Zygotes, Embryonic Stem Cells and the Development of Cancer

OBJECTIVES

This review is to explore whether potential gene interactions in the cell cycles of gametes, zygotes, and embryonic stem (ES) cells are associated with the development of cancer.

METHODS

MEDPILOT at the Central Library of the University of Cologne, Germany (Zentralbibliothek Köln) that covers 5,800 international medical journals and 4,300 E-journals was used to collect data. The initial searches were done in December 2012 and additional searches in October 2013-May 2015. The search terms included "cancer development," "gene interaction," and "ES cells," and the time period was between 1998 and 2015. A total of 147 articles in English language only were included in this review.

RESULTS

Transgenerational gene translation is implemented in the zygote through interactions of epigenetic isoforms of transcription factors (TFs) from parental gametes, predominantly during the first two zygote cleavages. Pluripotent transcription factors may provide interacting links with mutated genes during zygote-to-ES cell switches. Translation of post-transcriptional carcinogenic genes is implemented by abnormally spliced, tumor-specific isoforms of gene-encoded mRNA/non-coding RNA variants of TFs employing de novo gene synthesis and neofunctionalization. Post-translationally, mutated genes are preserved in pre-neoplastic ES cell subpopulations that can give rise to overt cancer stem cells. Thus, TFs operate as cell/disease-specific epigenetic messengers triggering clinical expression of neoplasms.

CONCLUSION

Potential gene interactions in the cell cycle of gametes, zygotes, and ES cells may play some roles in the development of cancer.

Genome-wide identification of long noncoding RNA genes and their potential association with fecundity and virulence in rice brown planthopper, Nilaparvata lugens

Background

The functional repertoire of long noncoding RNA (lncRNA) has been characterized in several model organisms, demonstrating that lncRNA plays important roles in fundamental biological processes. However, they remain largely unidentified in most species. Understanding the characteristics and functions of lncRNA in insects would be useful for insect resources utilization and sustainable pest control.

Methods

A computational pipeline was developed to identify lncRNA genes in the rice brown planthopper, Nilaparvata lugens, a destructive rice pest causing huge yield losses. Strand specific RT-PCR were used to determine the transcription orientation of lncRNAs.

Results

In total, 2,439 lncRNA transcripts corresponding to 1,882 loci were detected from 12 whole transcriptomes (RNA-seq) datasets, including samples from high fecundity (HFP), low fecundity (LFP), I87i and C89i populations, in addition Mudgo and TN1 virulence strains. The identified N. lugens lncRNAs had low sequence similarities with other known lncRNAs. However, their structural features were similar with mammalian counterparts. N. lugens lncRNAs had shorter transcripts than protein-coding genes due to the lower exon number though their exons and introns were longer. Only 19.9% of N. lugens lncRNAs had multiple alternatively spliced isoforms. We observed biases in the genome location of N. lugens lncRNAs. More than 30% of the lncRNAs overlapped with known protein-coding genes. These lncRNAs tend to be co-expressed with their neighboring genes (Pearson correlation, p < 0.01, T-test) and might interact with adjacent protein-coding genes. In total, 19-148 lncRNAs were specifically-expressed in the samples of HFP, LFP, Mudgo, TN1, I87i and C89i populations. Three lncRNAs specifically expressed in HFP and LFP populations overlapped with reproductive-associated genes.

Discussion

The structural features of N. lugens lncRNAs are similar to mammalian counterparts. Coexpression and function analysis suggeste that N. lugens lncRNAs might have important functions in high fecundity and virulence adaptability.

Conclusions

This study provided the first catalog of lncRNA genes in rice brown planthopper. Gene expression and genome location analysis indicated that lncRNAs might play important roles in high fecundity and virulence adaptation in N. lugens.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1953-y) contains supplementary material, which is available to authorized users.

lncRScan-SVM: A Tool for Predicting Long Non-Coding RNAs Using Support Vector Machine

Functional long non-coding RNAs (lncRNAs) have been bringing novel insight into biological study, however it is still not trivial to accurately distinguish the lncRNA transcripts (LNCTs) from the protein coding ones (PCTs). As various information and data about lncRNAs are preserved by previous studies, it is appealing to develop novel methods to identify the lncRNAs more accurately. Our method lncRScan-SVM aims at classifying PCTs and LNCTs using support vector machine (SVM). The gold-standard datasets for lncRScan-SVM model training, lncRNA prediction and method comparison were constructed according to the GENCODE gene annotations of human and mouse respectively. By integrating features derived from gene structure, transcript sequence, potential codon sequence and conservation, lncRScan-SVM outperforms other approaches, which is evaluated by several criteria such as sensitivity, specificity, accuracy, Matthews correlation coefficient (MCC) and area under curve (AUC). In addition, several known human lncRNA datasets were assessed using lncRScan-SVM. LncRScan-SVM is an efficient tool for predicting the lncRNAs, and it is quite useful for current lncRNA study.

Deep sequencing and de novo assembly of the mouse oocyte transcriptome define the contribution of transcription to the DNA methylation landscape

Background

Previously, a role was demonstrated for transcription in the acquisition of DNA methylation at imprinted control regions in oocytes. Definition of the oocyte DNA methylome by whole genome approaches revealed that the majority of methylated CpG islands are intragenic and gene bodies are hypermethylated. Yet, the mechanisms by which transcription regulates DNA methylation in oocytes remain unclear. Here, we systematically test the link between transcription and the methylome.

Results

We perform deep RNA-Seq and de novo transcriptome assembly at different stages of mouse oogenesis. This reveals thousands of novel non-annotated genes, as well as alternative promoters, for approximately 10 % of reference genes expressed in oocytes. In addition, a large fraction of novel promoters coincide with MaLR and ERVK transposable elements. Integration with our transcriptome assembly reveals that transcription correlates accurately with DNA methylation and accounts for approximately 85–90 % of the methylome. We generate a mouse model in which transcription across the Zac1/Plagl1 locus is abrogated in oocytes, resulting in failure of DNA methylation establishment at all CpGs of this locus. ChIP analysis in oocytes reveals H3K4me2 enrichment at the Zac1 imprinted control region when transcription is ablated, establishing a connection between transcription and chromatin remodeling at CpG islands by histone demethylases.

Conclusions

By precisely defining the mouse oocyte transcriptome, this work not only highlights transcription as a cornerstone of DNA methylation establishment in female germ cells, but also provides an important resource for developmental biology research.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0769-z) contains supplementary material, which is available to authorized users.

Storage time does not modify the gene expression profile of cryopreserved human metaphase II oocytes

STUDY QUESTION

Does storage time have any impact on the transcriptome of slowly frozen cryopreserved human metaphase II (MII) oocytes?

SUMMARY ANSWER

The length of cryostorage has no effect on the gene expression profile of human MII oocytes.

WHAT IS KNOWN ALREADY

Oocyte cryopreservation is a widely used technique in IVF for storage of surplus oocytes, as well as for fertility preservation (i.e. women undergoing gonadotoxic therapies) and oocyte donation programs. Although cryopreservation has negative impacts on oocyte physiology and it is associated with decrease of transcripts, no experimental data about the effect of storage time on the oocyte molecular profile are available to date.

STUDY DESIGN, SIZE, DURATION

This study included 27 women, ≤38 years aged, without any ovarian pathology, undergoing IVF treatment. Surplus MII oocytes were donated after written informed consent. A total of 31 non-cryopreserved oocytes and 68 surviving slow-frozen/rapid-thawed oocytes (32 oocytes cryostored for 3 years and 36 cryostored for 6 years) were analyzed.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Pools of ≈10 oocytes for each group were prepared. Total RNA was extracted from each pool, amplified, labeled and hybridized on oligonucleotide microarrays. Analyses were performed by R software using the limma package.

MAIN RESULTS AND THE ROLE OF CHANCE

Comparison of gene expression profiles between surviving thawed oocytes after 3 and 6 years of storage in liquid nitrogen found no differently expressed genes. The expression profiles of cryopreserved MII oocytes significantly differed from those of non-cryopreserved oocytes in 107 probe sets corresponding to 73 down-regulated and 29 up-regulated unique transcripts. Gene Ontology analysis by DAVID bioinformatics resource disclosed that cryopreservation deregulates genes involved in oocyte function and early embryo development, such as chromosome organization, RNA splicing and processing, cell cycle, cellular response to DNA damage and to stress, DNA repair, calcium ion binding, malate dehydrogenase activity and mitochondrial activity. Among the probes significantly up-regulated in cryopreserved oocytes, two corresponded to ovary-specific expressed large intergenic noncoding (linc)RNAs.

LIMITATIONS, REASONS FOR CAUTION

Data validation in a larger cohort of samples would be beneficial, although we applied stringent criteria for gene selection (fold-change >3 or <1/3 and FDR < 0.1). Further research should be undertaken to verify experimentally that the length of cryostorage has no effect on gene expression profile of vitrified/warmed MII oocytes, as well as to include in analyses 'older' frozen oocytes.

WIDER IMPLICATIONS OF THE FINDINGS

Confirmation that the length of storage does not alter the gene expression profile of frozen oocytes is noteworthy for the safety issue of long-term oocyte banking, i.e. fertility preservation, gamete donation.

STUDY FUNDING/COMPETING INTEREST

This study was supported by a grant of the Italian Ministry of Health (CCM 2012) and by Ferring Pharmaceutical company. The authors have no conflicts of interest to declare.

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/.

Gene Expression Variations of Red-White Skin Coloration in Common Carp (Cyprinus carpio)

Teleosts have more types of chromatophores than other vertebrates and the genetic basis for pigmentation is highly conserved among vertebrates. Therefore, teleosts are important models to study the mechanism of pigmentation. Although functional genes and genetic variations of pigmentation have been studied, the mechanisms of different skin coloration remains poorly understood. The koi strain of common carp has various colors and patterns, making it a good model for studying the genetic basis of pigmentation. We performed RNA-sequencing for red skin and white skin and identified 62 differentially expressed genes (DEGs). Most of them were validated with RT-qPCR. The up-regulated DEGs in red skin were enriched in Kupffer's vesicle development while the up-regulated DEGs in white skin were involved in cytoskeletal protein binding, sarcomere organization and glycogen phosphorylase activity. The distinct enriched activity might be associated with different structures and functions in erythrophores and iridophores. The DNA methylation levels of two selected DEGs inversely correlated with gene expression, indicating the participation of DNA methylation in the coloration. This expression characterization of red-white skin along with the accompanying transcriptome-wide expression data will be a useful resource for further studies of pigment cell biology.

The RNA world in the 21st century-a systems approach to finding non-coding keys to clinical questions

There was evidence that RNAs are a functionally rich class of molecules not only since the arrival of the next-generation sequencing technology. Non-coding RNAs (ncRNA) could be the key to accelerated diagnosis and enhanced prediction of disease and therapy outcomes as well as the design of advanced therapeutic strategies to overcome yet unsatisfactory approaches.In this review, we discuss the state of the art in RNA systems biology with focus on the application in the systems biomedicine field. We propose guidelines for analysing the role of microRNAs and long non-coding RNAs in human pathologies. We introduce RNA expression profiling and network approaches for the identification of stable and effective RNomics-based biomarkers, providing insights into the role of ncRNAs in disease regulation. Towards this, we discuss ways to model the dynamics of gene regulatory networks and signalling pathways that involve ncRNAs. We also describe data resources and computational methods for finding putative mechanisms of action of ncRNAs. Finally, we discuss avenues for the computer-aided design of novel RNA-based therapeutics.

Long non-coding RNA: A new paradigm for lung cancer

Lung cancer is the leading cause of cancer-related deaths worldwide. Recent advances in whole genome transcriptome analysis have enabled the identification of numerous members of a novel class of non-coding RNAs, i.e., long non-coding RNAs (lncRNAs), which play important roles in a wide range of biological processes and whose deregulation causes human disease, including cancer. Herein we provide a comprehensive survey of lncRNAs associated with lung cancer, with particular focus on the functions that either facilitate or inhibit the progression of lung cancer and the pathways involved. Emerging data on the use of lncRNAs as biomarkers for the diagnosis and prognosis of cancer are also discussed. We cast this information within the wider perspective of lncRNA biogenesis and molecular functions in the cell. Relationships that exist between lncRNAs, genome-wide transcription, and lung cancer are discussed. Deepening our understanding on these processes is critical not only from a mechanistic standpoint, but also for the development of novel biomarkers and effective therapeutic targets for cancer patients.

The identification and characterization of novel transcripts from RNA-seq data

Owing greatly to the advancement of next-generation sequencing (NGS), the amount of NGS data is increasing rapidly. Although there are many NGS applications, one of the most commonly used techniques 'RNA sequencing (RNA-seq)' is rapidly replacing microarray-based techniques in laboratories around the world. As more and more of such techniques are standardized, allowing technicians to perform these experiments with minimal hands-on time and reduced experimental/operator-dependent biases, the bottleneck of such techniques is clearly visible; that is, data analysis. Further complicating the matter, increasing evidence suggests most of the genome is transcribed into RNA; however, the majority of these RNAs are not translated into proteins. These RNAs that do not become proteins are called 'noncoding RNAs (ncRNAs)'. Although some time has passed since the discovery of ncRNAs, their annotations remain poor, making analysis of RNA-seq data challenging. Here, we examine the current limitations of RNA-seq analysis using case studies focused on the detection of novel transcripts and examination of their characteristics. Finally, we validate the presence of novel transcripts using biological experiments, showing novel transcripts can be accurately identified when a series of filters is applied. In conclusion, novel transcripts that are identified from RNA-seq must be examined carefully before proceeding to biological experiments.

TANRIC: An Interactive Open Platform to Explore the Function of lncRNAs in Cancer

Long noncoding RNAs (lncRNA) have emerged as essential players in cancer biology. Using recent large-scale RNA-seq datasets, especially those from The Cancer Genome Atlas (TCGA), we have developed "The Atlas of Noncoding RNAs in Cancer" (TANRIC; http://bioinformatics.mdanderson.org/main/TANRIC:Overview), a user-friendly, open-access web resource for interactive exploration of lncRNAs in cancer. It characterizes the expression profiles of lncRNAs in large patient cohorts of 20 cancer types, including TCGA and independent datasets (>8,000 samples overall). TANRIC enables researchers to rapidly and intuitively analyze lncRNAs of interest (annotated lncRNAs or any user-defined ones) in the context of clinical and other molecular data, both within and across tumor types. Using TANRIC, we have identified a large number of lncRNAs with potential biomedical significance, many of which show strong correlations with established therapeutic targets and biomarkers across tumor types or with drug sensitivity across cell lines. TANRIC represents a valuable tool for investigating the function and clinical relevance of lncRNAs in cancer, greatly facilitating lncRNA-related biologic discoveries and clinical applications.

Long noncoding RNA linc00617 exhibits oncogenic activity in breast cancer

Protein-coding genes account for only 2% of the human genome, whereas the vast majority of transcripts are noncoding RNAs including long noncoding RNAs. LncRNAs are involved in the regulation of a diverse array of biological processes, including cancer progression. An evolutionarily conserved lncRNA TUNA, was found to be required for pluripotency of mouse embryonic stem cells. In this study, we found the human ortholog of TUNA, linc00617, was upregulated in breast cancer samples. Linc00617 promoted motility and invasion of breast cancer cells and induced epithelial-mesenchymal-transition (EMT), which was accompanied by generation of stem cell properties. Moreover, knockdown of linc00617 repressed lung metastasis in vivo. We demonstrated that linc00617 upregulated the expression of stemness factor Sox2 in breast cancer cells, which was shown to promote the oncogenic activity of breast cancer cells by stimulating epithelial-to-mesenchymal transition and enhancing the tumor-initiating capacity. Thus, our data indicate that linc00617 functions as an important regulator of EMT and promotes breast cancer progression and metastasis via activating the transcription of Sox2. Together, it suggests that linc00617 may be a potential therapeutic target for aggressive breast cancer. © 2015 Wiley Periodicals, Inc.

Short stories on zebrafish long noncoding RNAs

The recent re-annotation of the transcriptome of human and other model organisms, using next-generation sequencing approaches, has unravelled a hitherto unknown repertoire of transcripts that do not have a potential to code for proteins. These transcripts have been largely classified into an amorphous class popularly known as long noncoding RNAs (lncRNA). This discovery of lncRNAs in human and other model systems have added a new layer to the understanding of gene regulation at the transcriptional and post-transcriptional levels. In recent years, three independent studies have discovered a number of lncRNAs expressed in different stages of zebrafish development and adult tissues using a high-throughput RNA sequencing approach, significantly adding to the repertoire of genes known in zebrafish. A subset of these transcripts also shows distinct and specific spatiotemporal patterns of gene expression, pointing to a tight regulatory control and potential functional roles in development, organogenesis, and/ or homeostasis. This review provides an overview of the lncRNAs in zebrafish and discusses how their discovery could provide new insights into understanding biology, explaining mutant phenotypes, and helping in potentially modeling disease processes.

C-It-Loci: a knowledge database for tissue-enriched loci

MOTIVATION

Increasing evidences suggest that most of the genome is transcribed into RNAs, but many of them are not translated into proteins. All those RNAs that do not become proteins are called 'non-coding RNAs (ncRNAs)', which outnumbers protein-coding genes. Interestingly, these ncRNAs are shown to be more tissue specifically expressed than protein-coding genes. Given that tissue-specific expressions of transcripts suggest their importance in the expressed tissue, researchers are conducting biological experiments to elucidate the function of such ncRNAs. Owing greatly to the advancement of next-generation techniques, especially RNA-seq, the amount of high-throughput data are increasing rapidly. However, due to the complexity of the data as well as its high volume, it is not easy to re-analyze such data to extract tissue-specific expressions of ncRNAs from published datasets.

RESULTS

Here, we introduce a new knowledge database called 'C-It-Loci', which allows a user to screen for tissue-specific transcripts across three organisms: human, mouse and zebrafish. C-It-Loci is intuitive and easy to use to identify not only protein-coding genes but also ncRNAs from various tissues. C-It-Loci defines homology through sequence and positional conservation to allow for the extraction of species-conserved loci. C-It-Loci can be used as a starting point for further biological experiments.

AVAILABILITY AND IMPLEMENTATION

C-It-Loci is freely available online without registration at http://c-it-loci.uni-frankfurt.de.

CONTACT

uchida@med.uni-frankfurt.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The circulating transcriptome as a source of non-invasive cancer biomarkers: concepts and controversies of non-coding and coding RNA in body fluids

The gold standard for cancer diagnosis remains the histological examination of affected tissue, obtained either by surgical excision, or radiologically guided biopsy. Such procedures however are expensive, not without risk to the patient, and require consistent evaluation by expert pathologists. Consequently, the search for non-invasive tools for the diagnosis and management of cancer has led to great interest in the field of circulating nucleic acids in plasma and serum. An additional benefit of blood-based testing is the ability to carry out screening and repeat sampling on patients undergoing therapy, or monitoring disease progression allowing for the development of a personalized approach to cancer patient management. Despite having been discovered over 60 years ago, the clear clinical potential of circulating nucleic acids, with the notable exception of prenatal diagnostic testing, has yet to translate into the clinic. The recent discovery of non-coding (nc) RNA (in particular micro(mi)RNAs) in the blood has provided fresh impetuous for the field. In this review, we discuss the potential of the circulating transcriptome (coding and ncRNA), as novel cancer biomarkers, the controversy surrounding their origin and biology, and most importantly the hurdles that remain to be overcome if they are really to become part of future clinical practice.

YeATS - a tool suite for analyzing RNA-seq derived transcriptome identifies a highly transcribed putative extensin in heartwood/sapwood transition zone in black walnut

The transcriptome provides a functional footprint of the genome by enumerating the molecular components of cells and tissues. The field of transcript discovery has been revolutionized through high-throughput mRNA sequencing (RNA-seq). Here, we present a methodology that replicates and improves existing methodologies, and implements a workflow for error estimation and correction followed by genome annotation and transcript abundance estimation for RNA-seq derived transcriptome sequences (YeATS - Yet Another Tool Suite for analyzing RNA-seq derived transcriptome). A unique feature of YeATS is the upfront determination of the errors in the sequencing or transcript assembly process by analyzing open reading frames of transcripts. YeATS identifies transcripts that have not been merged, result in broken open reading frames or contain long repeats as erroneous transcripts. We present the YeATS workflow using a representative sample of the transcriptome from the tissue at the heartwood/sapwood transition zone in black walnut. A novel feature of the transcriptome that emerged from our analysis was the identification of a highly abundant transcript that had no known homologous genes (GenBank accession: KT023102). The amino acid composition of the longest open reading frame of this gene classifies this as a putative extensin. Also, we corroborated the transcriptional abundance of proline-rich proteins, dehydrins, senescence-associated proteins, and the DNAJ family of chaperone proteins. Thus, YeATS presents a workflow for analyzing RNA-seq data with several innovative features that differentiate it from existing software.

YeATS - a tool suite for analyzing RNA-seq derived transcriptome identifies a highly transcribed putative extensin in heartwood/sapwood transition zone in black walnut

The transcriptome provides a functional footprint of the genome by enumerating the molecular components of cells and tissues. The field of transcript discovery has been revolutionized through high-throughput mRNA sequencing (RNA-seq). Here, we present a methodology that replicates and improves existing methodologies, and implements a workflow for error estimation and correction followed by genome annotation and transcript abundance estimation for RNA-seq derived transcriptome sequences (YeATS - Yet Another Tool Suite for analyzing RNA-seq derived transcriptome). A unique feature of YeATS is the upfront determination of the errors in the sequencing or transcript assembly process by analyzing open reading frames of transcripts. YeATS identifies transcripts that have not been merged, result in broken open reading frames or contain long repeats as erroneous transcripts. We present the YeATS workflow using a representative sample of the transcriptome from the tissue at the heartwood/sapwood transition zone in black walnut. A novel feature of the transcriptome that emerged from our analysis was the identification of a highly abundant transcript that had no known homologous genes (GenBank accession: KT023102). The amino acid composition of the longest open reading frame of this gene classifies this as a putative extensin. Also, we corroborated the transcriptional abundance of proline-rich proteins, dehydrins, senescence-associated proteins, and the DNAJ family of chaperone proteins. Thus, YeATS presents a workflow for analyzing RNA-seq data with several innovative features that differentiate it from existing software.

MBRidge: an accurate and cost-effective method for profiling DNA methylome at single-base resolution

Organisms and cells, in response to environmental influences or during development, undergo considerable changes in DNA methylation on a genome-wide scale, which are linked to a variety of biological processes. Using MethylC-seq to decipher DNA methylome at single-base resolution is prohibitively costly. In this study, we develop a novel approach, named MBRidge, to detect the methylation levels of repertoire CpGs, by innovatively introducing C-hydroxylmethylated adapters and bisulfate treatment into the MeDIP-seq protocol and employing ridge regression in data analysis. A systematic evaluation of DNA methylome in a human ovarian cell line T29 showed that MBRidge achieved high correlation (R > 0.90) with much less cost (∼10%) in comparison with MethylC-seq. We further applied MBRidge to profiling DNA methylome in T29H, an oncogenic counterpart of T29's. By comparing methylomes of T29H and T29, we identified 131790 differential methylation regions (DMRs), which are mainly enriched in carcinogenesis-related pathways. These are substantially different from 7567 DMRs that were obtained by RRBS and related with cell development or differentiation. The integrated analysis of DMRs in the promoter and expression of DMR-corresponding genes revealed that DNA methylation enforced reverse regulation of gene expression, depending on the distance from the proximal DMR to transcription starting sites in both mRNA and lncRNA. Taken together, our results demonstrate that MBRidge is an efficient and cost-effective method that can be widely applied to profiling DNA methylomes.

Advances in long noncoding RNAs: identification, structure prediction and function annotation

Long noncoding RNAs (lncRNAs), generally longer than 200 nucleotides and with poor protein coding potential, are usually considered collectively as a heterogeneous class of RNAs. Recently, an increasing number of studies have shown that lncRNAs can involve in various critical biological processes and a number of complex human diseases. Not only the primary sequences of many lncRNAs are directly interrelated to a specific functional role, strong evidence suggests that their secondary structures are even more interrelated to their known functions. As functional molecules, lncRNAs have become more and more relevant to many researchers. Here, we review recent, state-of-the-art advances in the three levels (the primary sequence, the secondary structure and the function annotation) of the lncRNA research, as well as computational methods for lncRNA data analysis.

Identification and characterization of long non-coding RNAs involved in osmotic and salt stress in Medicago truncatula using genome-wide high-throughput sequencing

BACKGROUND

Long non-coding RNAs (lncRNAs) have been shown to play crucially regulatory roles in diverse biological processes involving complex mechanisms. However, information regarding the number, sequences, characteristics and potential functions of lncRNAs in plants is so far overly limited.

RESULTS

Using high-throughput sequencing and bioinformatics analysis, we identified a total of 23,324 putative lncRNAs from control, osmotic stress- and salt stress-treated leaf and root samples of Medicago truncatula, a model legume species. Out of these lncRNAs, 7,863 and 5,561 lncRNAs were identified from osmotic stress-treated leaf and root samples, respectively. While, 7,361 and 7,874 lncRNAs were identified from salt stress-treated leaf and root samples, respectively. To reveal their potential functions, we analyzed Gene Ontology (GO) terms of genes that overlap with or are neighbors of the stress-responsive lncRNAs. Enrichments in GO terms in biological processes such as signal transduction, energy synthesis, molecule metabolism, detoxification, transcription and translation were found.

CONCLUSIONS

LncRNAs are likely involved in regulating plant's responses and adaptation to osmotic and salt stresses in complex regulatory networks with protein-coding genes. These findings are of importance for our understanding of the potential roles of lncRNAs in responses of plants in general and M. truncatula in particular to abiotic stresses.

Revealing protein-lncRNA interaction

Long non-coding RNAs (lncRNAs) are associated to a plethora of cellular functions, most of which require the interaction with one or more RNA-binding proteins (RBPs); similarly, RBPs are often able to bind a large number of different RNAs. The currently available knowledge is already drawing an intricate network of interactions, whose deregulation is frequently associated to pathological states. Several different techniques were developed in the past years to obtain protein–RNA binding data in a high-throughput fashion. In parallel, in silico inference methods were developed for the accurate computational prediction of the interaction of RBP–lncRNA pairs. The field is growing rapidly, and it is foreseeable that in the near future, the protein–lncRNA interaction network will rise, offering essential clues for a better understanding of lncRNA cellular mechanisms and their disease-associated perturbations.

GermlncRNA: a unique catalogue of long non-coding RNAs and associated regulations in male germ cell development

Spermatogenic failure is a major cause of male infertility, which affects millions of couples worldwide. Recent discovery of long non-coding RNAs (lncRNAs) as critical regulators in normal and disease development provides new clues for delineating the molecular regulation in male germ cell development. However, few functional lncRNAs have been characterized to date. A major limitation in studying lncRNA in male germ cell development is the absence of germ cell-specific lncRNA annotation. Current lncRNA annotations are assembled by transcriptome data from heterogeneous tissue sources; specific germ cell transcript information of various developmental stages is therefore under-represented, which may lead to biased prediction or fail to identity important germ cell-specific lncRNAs. GermlncRNA provides the first comprehensive web-based and open-access lncRNA catalogue for three key male germ cell stages, including type A spermatogonia, pachytene spermatocytes and round spermatids. This information has been developed by integrating male germ transcriptome resources derived from RNA-Seq, tiling microarray and GermSAGE. Characterizations on lncRNA-associated regulatory features, potential coding gene and microRNA targets are also provided. Search results from GermlncRNA can be exported to Galaxy for downstream analysis or downloaded locally. Taken together, GermlncRNA offers a new avenue to better understand the role of lncRNAs and associated targets during spermatogenesis.

Database URL: http://germlncrna.cbiit.cuhk.edu.hk/

An evolving view of epigenetic complexity in the brain

Recent scientific advances have revolutionized our understanding of classical epigenetic mechanisms and the broader landscape of molecular interactions and cellular functions that are inextricably linked to these processes. Our current view of epigenetics includes an increasing appreciation for the dynamic nature of DNA methylation, active mechanisms for DNA demethylation, differential functions of 5-methylcytosine and its oxidized derivatives, the intricate regulatory logic of histone post-translational modifications, the incorporation of histone variants into chromatin, nucleosome occupancy and dynamics, and direct links between cellular signalling pathways and the actions of chromatin 'reader', 'writer' and 'eraser' molecules. We also have an increasing awareness of the seemingly ubiquitous roles played by diverse classes of selectively expressed non-coding RNAs in transcriptional, post-transcriptional, post-translational and local and higher order chromatin modulatory processes. These perspectives are still evolving with novel insights continuing to emerge rapidly (e.g. those related to epigenetic regulation of mobile genetic elements, epigenetic mechanisms in mitochondria, roles in nuclear architecture and 'RNA epigenetics'). The precise functions of these epigenetic factors/phenomena are largely unknown. However, it is unequivocal that they serve as key mediators of brain complexity and flexibility, including neural development and aging, cellular differentiation, homeostasis, stress responses, and synaptic and neural network connectivity and plasticity.

SRD: a Staphylococcus regulatory RNA database

An overflow of regulatory RNAs (sRNAs) was identified in a wide range of bacteria. We designed and implemented a new resource for the hundreds of sRNAs identified in Staphylococci, with primary focus on the human pathogen Staphylococcus aureus. The "Staphylococcal Regulatory RNA Database" (SRD, http://srd.genouest.org/) compiled all published data in a single interface including genetic locations, sequences and other features. SRD proposes novel and simplified identifiers for Staphylococcal regulatory RNAs (srn) based on the sRNA's genetic location in S. aureus strain N315 which served as a reference. From a set of 894 sequences and after an in-depth cleaning, SRD provides a list of 575 srn exempt of redundant sequences. For each sRNA, their experimental support(s) is provided, allowing the user to individually assess their validity and significance. RNA-seq analysis performed on strains N315, NCTC8325, and Newman allowed us to provide further details, upgrade the initial annotation, and identified 159 RNA-seq independent transcribed sRNAs. The lists of 575 and 159 sRNAs sequences were used to predict the number and location of srns in 18 S. aureus strains and 10 other Staphylococci. A comparison of the srn contents within 32 Staphylococcal genomes revealed a poor conservation between species. In addition, sRNA structure predictions obtained with MFold are accessible. A BLAST server and the intaRNA program, which is dedicated to target prediction, were implemented. SRD is the first sRNA database centered on a genus; it is a user-friendly and scalable device with the possibility to submit new sequences that should spread in the literature.

Long non-coding RNAs and their biological roles in plants

With the development of genomics and bioinformatics, especially the extensive applications of high-throughput sequencing technology, more transcriptional units with little or no protein-coding potential have been discovered. Such RNA molecules are called non-protein-coding RNAs (npcRNAs or ncRNAs). Among them, long npcRNAs or ncRNAs (lnpcRNAs or lncRNAs) represent diverse classes of transcripts longer than 200 nucleotides. In recent years, the lncRNAs have been considered as important regulators in many essential biological processes. In plants, although a large number of lncRNA transcripts have been predicted and identified in few species, our current knowledge of their biological functions is still limited. Here, we have summarized recent studies on their identification, characteristics, classification, bioinformatics, resources, and current exploration of their biological functions in plants.

Long Noncoding RNAs in Digestive System Malignancies: A Novel Class of Cancer Biomarkers and Therapeutic Targets?

High throughput methodologies have revealed the existence of an unexpectedly large number of long noncoding RNAs (lncRNAs). The unconventional role of lncRNAs in gene expression regulation and their broad implication in oncogenic and tumor suppressive pathways have introduced lncRNAs as novel biological tumor markers. The most prominent example of lncRNAs application in routine clinical practice is PCA3, a FDA-approved biomarker for prostate cancer. Regarding digestive system malignancies, the oncogenic HOTAIR is one of the most widely studied lncRNAs in the preclinical level and has already been identified as a potent prognostic marker for major malignancies of the gastrointestinal tract. Here, we provide an overview of recent findings regarding the emerging role of lncRNAs not only as key regulators of cancer initiation and progression in colon, stomach, pancreatic, liver, and esophageal cancers, but also as reliable tumor markers and therapeutic tools. lncRNAs can be easily, rapidly, and cost-effectively determined in tissues, serum, and gastric juice, making them highly versatile analytes. Taking also into consideration the largely unmet clinical need for early diagnosis and more accurate prognostic/predictive markers for gastrointestinal cancer patients, we comment upon the perspectives of lncRNAs as efficient molecular tools that could aid in the clinical management.

Genetics of RA susceptibility, what comes next?

Genome-wide association studies (GWASs) have been used to great effect to identify genetic susceptibility loci for complex disease. A series of GWAS and meta-analyses have informed the discovery of over 100 loci for rheumatoid arthritis (RA). In common with findings in other autoimmune diseases the lead signals for the majority of these loci do not map to known gene sequences. In order to realise the benefit of investment in GWAS studies it is vital we determine how disease associated alleles function to influence disease processes. This is leading to rapid development in our knowledge as to the function of non-coding regions of the genome. Here we consider possible functional mechanisms for intergenic RA-associated variants which lie within lncRNA sequences.

Long noncoding RNAs in cardiovascular diseases

In recent year, increasing evidence suggests that noncoding RNAs play important roles in the regulation of tissue homeostasis and pathophysiological conditions. Besides small noncoding RNAs (eg, microRNAs), >200-nucleotide long transcripts, namely long noncoding RNAs (lncRNAs), can interfere with gene expressions and signaling pathways at various stages. In the cardiovascular system, studies have detected and characterized the expression of lncRNAs under normal physiological condition and in disease states. Several lncRNAs are regulated during acute myocardial infarction (eg, Novlnc6) and heart failure (eg, Mhrt), whereas others control hypertrophy, mitochondrial function and apoptosis of cardiomyocytes. In the vascular system, the endothelial-expressed lncRNAs (eg, MALAT1 and Tie-1-AS) can regulate vessel growth and function, whereas the smooth-muscle-expressed lncRNA smooth muscle and endothelial cell-enriched migration/differentiation-associated long noncoding RNA was recently shown to control the contractile phenotype of smooth muscle cells. This review article summarizes the data on lncRNA expressions in mouse and human and highlights identified cardiovascular lncRNAs that might play a role in cardiovascular diseases. Although our understanding of lncRNAs is still in its infancy, these examples may provide helpful insights how lncRNAs interfere with cardiovascular diseases.

ALDB: a domestic-animal long noncoding RNA database

Background

Long noncoding RNAs (lncRNAs) have attracted significant attention in recent years due to their important roles in many biological processes. Domestic animals constitute a unique resource for understanding the genetic basis of phenotypic variation and are ideal models relevant to diverse areas of biomedical research. With improving sequencing technologies, numerous domestic-animal lncRNAs are now available. Thus, there is an immediate need for a database resource that can assist researchers to store, organize, analyze and visualize domestic-animal lncRNAs.

Results

The domestic-animal lncRNA database, named ALDB, is the first comprehensive database with a focus on the domestic-animal lncRNAs. It currently archives 12,103 pig intergenic lncRNAs (lincRNAs), 8,923 chicken lincRNAs and 8,250 cow lincRNAs. In addition to the annotations of lincRNAs, it offers related data that is not available yet in existing lncRNA databases (lncRNAdb and NONCODE), such as genome-wide expression profiles and animal quantitative trait loci (QTLs) of domestic animals. Moreover, a collection of interfaces and applications, such as the Basic Local Alignment Search Tool (BLAST), the Generic Genome Browser (GBrowse) and flexible search functionalities, are available to help users effectively explore, analyze and download data related to domestic-animal lncRNAs.

Conclusions

ALDB enables the exploration and comparative analysis of lncRNAs in domestic animals. A user-friendly web interface, integrated information and tools make it valuable to researchers in their studies. ALDB is freely available from http://res.xaut.edu.cn/aldb/index.jsp.

Long noncoding RNAs in cardiac development and ageing

A large part of the mammalian genome is transcribed into noncoding RNAs. Long noncoding RNAs (lncRNAs) have emerged as critical epigenetic regulators of gene expression. Distinct molecular mechanisms allow lncRNAs either to activate or to repress gene expression, thereby participating in the regulation of cellular and tissue function. LncRNAs, therefore, have important roles in healthy and diseased hearts, and might be targets for therapeutic intervention. In this Review, we summarize the current knowledge of the roles of lncRNAs in cardiac development and ageing. After describing the definition and classification of lncRNAs, we present an overview of the mechanisms by which lncRNAs regulate gene expression. We discuss the multiple roles of lncRNAs in the heart, and focus on the regulation of embryonic stem cell differentiation, cardiac cell fate and development, and cardiac ageing. We emphasize the importance of chromatin remodelling in this regulation. Finally, we discuss the therapeutic and biomarker potential of lncRNAs.

Expression analysis of the long non-coding RNA antisense to Uchl1 (AS Uchl1) during dopaminergic cells' differentiation in vitro and in neurochemical models of Parkinson's disease

Antisense (AS) transcripts are RNA molecules that are transcribed from the opposite strand to sense (S) genes forming S/AS pairs. The most prominent configuration is when a lncRNA is antisense to a protein coding gene. Increasing evidences prove that antisense transcription may control sense gene expression acting at distinct regulatory levels. However, its contribution to brain function and neurodegenerative diseases remains unclear. We have recently identified AS Uchl1 as an antisense to the mouse Ubiquitin carboxy-terminal hydrolase L1 (Uchl1) gene (AS Uchl1), the synthenic locus of UCHL1/PARK5. This is mutated in rare cases of early-onset familial Parkinson's Disease (PD) and loss of UCHL1 activity has been reported in many neurodegenerative diseases. Importantly, manipulation of UchL1 expression has been proposed as tool for therapeutic intervention. AS Uchl1 induces UchL1 expression by increasing its translation. It is the representative member of SINEUPs (SINEB2 sequence to UP-regulate translation), a new functional class of natural antisense lncRNAs that activate translation of their sense genes. Here we take advantage of FANTOM5 dataset to identify the transcription start sites associated to S/AS pair at Uchl1 locus. We show that AS Uchl1 expression is under the regulation of Nurr1, a major transcription factor involved in dopaminergic cells' differentiation and maintenance. Furthermore, AS Uch1 RNA levels are strongly down-regulated in neurochemical models of PD in vitro and in vivo. This work positions AS Uchl1 RNA as a component of Nurr1-dependent gene network and target of cellular stress extending our understanding on the role of antisense transcription in the brain.

De novo origin of VCY2 from autosome to Y-transposed amplicon

The formation of new genes is a primary driving force of evolution in all organisms. The de novo evolution of new genes from non-protein-coding genomic regions is emerging as an important additional mechanism for novel gene creation. Y chromosomes underlie sex determination in mammals and contain genes that are required for male-specific functions. In this study, a search was undertaken for Y chromosome de novo genes derived from non-protein-coding sequences. The Y chromosome orphan gene variable charge, Y-linked (VCY)2, is an autosome-derived gene that has sequence similarity to large autosomal fragments but lacks an autosomal protein-coding homolog. VCY2 locates in the amplicon containing long DNA fragments that were transposed from autosomes to the Y chromosome before the ape-monkey split. We confirmed that VCY2cannot be encoded by autosomes due to the presence of multiple disablers that disrupt the open reading frame, such as the absence of start or stop codons and the presence of premature stop codons. Similar observations have been made for homologs in the autosomes of the chimpanzee, gorilla, rhesus macaque, baboon and out-group marmoset, which suggests that there was a non-protein-coding ancestral VCY2 that was common to apes and monkeys that predated the transposition event. Furthermore, while protein-coding orthologs are absent, a putative non-protein-coding VCY2 with conserved disablers was identified in the rhesus macaque Y chromosome male-specific region. This finding implies that VCY2 might have not acquired its protein-coding ability before the ape-monkey split. VCY2 encodes a testis-specific expressed protein and is involved in the pathologic process of male infertility, and the acquisition of this gene might improve male fertility. This is the first evidence that de novo genes can be generated from transposed autosomal non-protein-coding segments, and this evidence provides novel insights into the evolutionary history of the Y chromosome.

Systematic identification and characterization of long intergenic non-coding RNAs in fetal porcine skeletal muscle development

Long intergenic non-coding RNAs (lincRNAs) play important roles in many cellular processes. Here, we present the first systematic identification and characterization of lincRNAs in fetal porcine skeletal muscle. We obtained a total of 55.02 million 90-bp paired-end reads and assembled 54,550 transcripts using cufflinks. We developed a pipeline to identify 570 multi-exon lincRNAs by integrating a set of previous approaches. These putative porcine lincRNAs share many characteristics with mammalian lincRNAs, such as a relatively short length, small number of exons and low level of sequence conservation. We found that the porcine lincRNAs were preferentially located near genes mediating transcriptional regulation rather than those with developmental functions. We further experimentally analyzed the features of a conserved mouse lincRNA gene and found that isoforms 1 and 4 of this lincRNA were enriched in the cell nucleus and were associated with polycomb repressive complex 2 (PRC2). Our results provide a catalog of fetal porcine lincRNAs for further experimental investigation of the functions of these genes in the skeletal muscle developmental process.

Long Non-Coding RNA Expression during Aging in the Human Subependymal Zone

The human subependymal zone (SEZ) is debatably a source of newly born neurons throughout life and neurogenesis is a multi-step process requiring distinct transcripts during cell proliferation and early neuronal maturation, along with orchestrated changes in gene expression during cell state/fate transitions. Furthermore, it is becoming increasingly clear that the majority of our genome that results in production of non-protein-coding RNAs plays vital roles in the evolution, development, adaptation, and region-specific function of the human brain. We predicted that some transcripts expressed in the SEZ may be unique to this specialized brain region, and that a comprehensive transcriptomic analysis of this region would aid in defining expression changes during neuronal birth and growth in adult humans. Here, we used deep RNA sequencing of human SEZ tissue during adulthood and aging to characterize the transcriptional landscape with a particular emphasis on long non-coding RNAs (lncRNAs). The data show predicted age-related changes in mRNAs encoding proliferation, progenitor, and inflammatory proteins as well as a unique subset of lncRNAs that are highly expressed in the human SEZ, many of which have unknown functions. Our results suggest the existence of robust proliferative and neuronal differentiation potential in the adult human SEZ and lay the foundation for understanding the involvement of lncRNAs in postnatal neurogenesis and potentially associated neurodevelopmental diseases that emerge after birth.

LncRNAs and neoplasia

Long noncoding RNAs are emerging as new mediators of tumorigenesis by virtue of their various functions and their capacity to induce different mechanisms as a result of their wide spectrum of interactions. They play critical roles in a broad range of cellular processes including regulation of gene expression, imprinting, chromatin modification, transcription and posttranslational processing. Expression and activity of lncRNAs are deregulated in several types of human cancer. Impairment of lncRNA activity may affect key components of the cellular gene regulatory networks and is associated with deregulation of a large number of cellular oncogenic pathways. LncRNAs are also being evaluated as diagnostic and prognostic biomarkers and may provide targets for potential therapeutic applications. An improved understanding of the roles played by lncRNAs in cancer will lead to more effective therapeutic strategies. In this review we summarize the current knowledge on lncRNAs and their function as mediators of tumor development.

A liver-enriched long non-coding RNA, lncLSTR, regulates systemic lipid metabolism in mice

Long non-coding RNAs (lncRNAs) constitute a significant portion of mammalian genome, yet the physiological importance of lncRNAs is largely unknown. Here, we identify a liver-enriched lncRNA in mouse that we term liver-specific triglyceride regulator (lncLSTR). Mice with a liver-specific depletion of lncLSTR exhibit a marked reduction in plasma triglyceride levels. We show that lncLSTR depletion enhances apoC2 expression, leading to robust lipoprotein lipase activation and increased plasma triglyceride clearance. We further demonstrate that the regulation of apoC2 expression occurs through an FXR-mediated pathway. LncLSTR forms a molecular complex with TDP-43 to regulate expression of Cyp8b1, a key enzyme in the bile acid synthesis pathway, and engenders an in vivo bile pool that induces apoC2 expression through FXR. Finally, we demonstrate that lncLSTR depletion can reduce triglyceride levels in a hyperlipidemia mouse model. Taken together, these data support a model in which lncLSTR regulates a TDP-43/FXR/apoC2-dependent pathway to maintain systemic lipid homeostasis.

Decoding the complex genetic causes of heart diseases using systems biology

The pace of disease gene discovery is still much slower than expected, even with the use of cost-effective DNA sequencing and genotyping technologies. It is increasingly clear that many inherited heart diseases have a more complex polygenic aetiology than previously thought. Understanding the role of gene-gene interactions, epigenetics, and non-coding regulatory regions is becoming increasingly critical in predicting the functional consequences of genetic mutations identified by genome-wide association studies and whole-genome or exome sequencing. A systems biology approach is now being widely employed to systematically discover genes that are involved in heart diseases in humans or relevant animal models through bioinformatics. The overarching premise is that the integration of high-quality causal gene regulatory networks (GRNs), genomics, epigenomics, transcriptomics and other genome-wide data will greatly accelerate the discovery of the complex genetic causes of congenital and complex heart diseases. This review summarises state-of-the-art genomic and bioinformatics techniques that are used in accelerating the pace of disease gene discovery in heart diseases. Accompanying this review, we provide an interactive web-resource for systems biology analysis of mammalian heart development and diseases, CardiacCode ( http://CardiacCode.victorchang.edu.au/ ). CardiacCode features a dataset of over 700 pieces of manually curated genetic or molecular perturbation data, which enables the inference of a cardiac-specific GRN of 280 regulatory relationships between 33 regulator genes and 129 target genes. We believe this growing resource will fill an urgent unmet need to fully realise the true potential of predictive and personalised genomic medicine in tackling human heart disease.

Proteogenomics: concepts, applications and computational strategies

Proteogenomics is an area of research at the interface of proteomics and genomics. In this approach, customized protein sequence databases generated using genomic and transcriptomic information are used to help identify novel peptides (not present in reference protein sequence databases) from mass spectrometry-based proteomic data; in turn, the proteomic data can be used to provide protein-level evidence of gene expression and to help refine gene models. In recent years, owing to the emergence of new sequencing technologies such as RNA-seq and dramatic improvements in the depth and throughput of mass spectrometry-based proteomics, the pace of proteogenomic research has greatly accelerated. Here I review the current state of proteogenomic methods and applications, including computational strategies for building and using customized protein sequence databases. I also draw attention to the challenge of false positive identifications in proteogenomics and provide guidelines for analyzing the data and reporting the results of proteogenomic studies.

A semi-supervised learning approach for RNA secondary structure prediction

RNA secondary structure prediction is a key technology in RNA bioinformatics. Most algorithms for RNA secondary structure prediction use probabilistic models, in which the model parameters are trained with reliable RNA secondary structures. Because of the difficulty of determining RNA secondary structures by experimental procedures, such as NMR or X-ray crystal structural analyses, there are still many RNA sequences that could be useful for training whose secondary structures have not been experimentally determined. In this paper, we introduce a novel semi-supervised learning approach for training parameters in a probabilistic model of RNA secondary structures in which we employ not only RNA sequences with annotated secondary structures but also ones with unknown secondary structures. Our model is based on a hybrid of generative (stochastic context-free grammars) and discriminative models (conditional random fields) that has been successfully applied to natural language processing. Computational experiments indicate that the accuracy of secondary structure prediction is improved by incorporating RNA sequences with unknown secondary structures into training. To our knowledge, this is the first study of a semi-supervised learning approach for RNA secondary structure prediction. This technique will be useful when the number of reliable structures is limited.

Identification of long non-coding RNAs in insects genomes

The development of high throughput sequencing technologies (HTS) has allowed researchers to better assess the complexity and diversity of the transcriptome. Among the many classes of non-coding RNAs (ncRNAs) identified the last decade, long non-coding RNAs (lncRNAs) represent a diverse and numerous repertoire of important ncRNAs, reinforcing the view that they are of central importance to the cell machinery in all branches of life. Although lncRNAs have been involved in essential biological processes such as imprinting, gene regulation or dosage compensation especially in mammals, the repertoire of lncRNAs is poorly characterized for many non-model organisms. In this review, we first focus on what is known about experimentally validated lncRNAs in insects and then review bioinformatic methods to annotate lncRNAs in the genomes of hexapods.

From discovery to function: the expanding roles of long noncoding RNAs in physiology and disease

Long noncoding RNAs (lncRNAs) are a relatively poorly understood class of RNAs with little or no coding capacity transcribed from a set of incompletely annotated genes. They have received considerable attention in the past few years and are emerging as potentially important players in biological regulation. Here we discuss the evolving understanding of this new class of molecular regulators that has emerged from ongoing research, which continues to expand our databases of annotated lncRNAs and provide new insights into their physical properties, molecular mechanisms of action, and biological functions. We outline the current strategies and approaches that have been employed to identify and characterize lncRNAs, which have been instrumental in revealing their multifaceted roles ranging from cis- to trans-regulation of gene expression and from epigenetic modulation in the nucleus to posttranscriptional control in the cytoplasm. In addition, we highlight the molecular and biological functions of some of the best characterized lncRNAs in physiology and disease, especially those relevant to endocrinology, reproduction, metabolism, immunology, neurobiology, muscle biology, and cancer. Finally, we discuss the tremendous diagnostic and therapeutic potential of lncRNAs in cancer and other diseases.

Analysis of long non-coding RNAs highlights tissue-specific expression patterns and epigenetic profiles in normal and psoriatic skin

BACKGROUND

Although analysis pipelines have been developed to use RNA-seq to identify long non-coding RNAs (lncRNAs), inference of their biological and pathological relevance remains a challenge. As a result, most transcriptome studies of autoimmune disease have only assessed protein-coding transcripts.

RESULTS

We used RNA-seq data from 99 lesional psoriatic, 27 uninvolved psoriatic, and 90 normal skin biopsies, and applied computational approaches to identify and characterize expressed lncRNAs. We detect 2,942 previously annotated and 1,080 novel lncRNAs which are expected to be skin specific. Notably, over 40% of the novel lncRNAs are differentially expressed and the proportions of differentially expressed transcripts among protein-coding mRNAs and previously-annotated lncRNAs are lower in psoriasis lesions versus uninvolved or normal skin. We find that many lncRNAs, in particular those that are differentially expressed, are co-expressed with genes involved in immune related functions, and that novel lncRNAs are enriched for localization in the epidermal differentiation complex. We also identify distinct tissue-specific expression patterns and epigenetic profiles for novel lncRNAs, some of which are shown to be regulated by cytokine treatment in cultured human keratinocytes.

CONCLUSIONS

Together, our results implicate many lncRNAs in the immunopathogenesis of psoriasis, and our results provide a resource for lncRNA studies in other autoimmune diseases.

Functional genomic screening approaches in mechanistic toxicology and potential future applications of CRISPR-Cas9

Characterizing variability in the extent and nature of responses to environmental exposures is a critical aspect of human health risk assessment. Chemical toxicants act by many different mechanisms, however, and the genes involved in adverse outcome pathways (AOPs) and AOP networks are not yet characterized. Functional genomic approaches can reveal both toxicity pathways and susceptibility genes, through knockdown or knockout of all non-essential genes in a cell of interest, and identification of genes associated with a toxicity phenotype following toxicant exposure. Screening approaches in yeast and human near-haploid leukemic KBM7 cells have identified roles for genes and pathways involved in response to many toxicants but are limited by partial homology among yeast and human genes and limited relevance to normal diploid cells. RNA interference (RNAi) suppresses mRNA expression level but is limited by off-target effects (OTEs) and incomplete knockdown. The recently developed gene editing approach called clustered regularly interspaced short palindrome repeats-associated nuclease (CRISPR)-Cas9, can precisely knock-out most regions of the genome at the DNA level with fewer OTEs than RNAi, in multiple human cell types, thus overcoming the limitations of the other approaches. It has been used to identify genes involved in the response to chemical and microbial toxicants in several human cell types and could readily be extended to the systematic screening of large numbers of environmental chemicals. CRISPR-Cas9 can also repress and activate gene expression, including that of non-coding RNA, with near-saturation, thus offering the potential to more fully characterize AOPs and AOP networks. Finally, CRISPR-Cas9 can generate complex animal models in which to conduct preclinical toxicity testing at the level of individual genotypes or haplotypes. Therefore, CRISPR-Cas9 is a powerful and flexible functional genomic screening approach that can be harnessed to provide unprecedented mechanistic insight in the field of modern toxicology.