Triplex-Inspector: an analysis tool for triplex-mediated targeting of genomic loci

TTSBBC: triplex target site biomarkers and barcodes in cancer

The technology of triplex-forming oligonucleotides (TFOs) provides an approach to manipulate genes at the DNA level. TFOs bind to specific sites on genomic DNA, creating a unique intermolecular triple-helix DNA structure through Hoogsteen hydrogen bonding. This targeting by TFOs is site-specific and the locations TFOs bind are referred to as TFO target sites (TTS). Triplexes have been observed to selectively influence gene expression, homologous recombination, mutations, protein binding, and DNA damage. These sites typically feature a poly-purine sequence in duplex DNA, and the characteristics of these TTS sequences greatly influence the formation of the triplex. We introduce TTSBBC, a novel analysis and visualization platform designed to explore features of TTS sequences to enable users to design and validate TTSs. The web server can be freely accessed at https://kowalski-labapps.dellmed.utexas.edu/TTSBBC/.

Long noncoding RNA study: Genome-wide approaches

Long noncoding RNAs (lncRNAs) have been confirmed to play a crucial role in various biological processes across several species. Though many efforts have been devoted to the expansion of the lncRNAs landscape, much about lncRNAs is still unknown due to their great complexity. The development of high-throughput technologies and the constantly improved bioinformatic methods have resulted in a rapid expansion of lncRNA research and relevant databases. In this review, we introduced genome-wide research of lncRNAs in three parts: (i) novel lncRNA identification by high-throughput sequencing and computational pipelines; (ii) functional characterization of lncRNAs by expression atlas profiling, genome-scale screening, and the research of cancer-related lncRNAs; (iii) mechanism research by large-scale experimental technologies and computational analysis. Besides, primary experimental methods and bioinformatic pipelines related to these three parts are summarized. This review aimed to provide a comprehensive and systemic overview of lncRNA genome-wide research strategies and indicate a genome-wide lncRNA research system.

Aid or Antagonize: Nuclear Long Noncoding RNAs Regulate Host Responses and Outcomes of Viral Infections

Long noncoding RNAs (lncRNAs) are transcripts measuring >200 bp in length and devoid of protein-coding potential. LncRNAs exceed the number of protein-coding mRNAs and regulate cellular, developmental, and immune pathways through diverse molecular mechanisms. In recent years, lncRNAs have emerged as epigenetic regulators with prominent roles in health and disease. Many lncRNAs, either host or virus-encoded, have been implicated in critical cellular defense processes, such as cytokine and antiviral gene expression, the regulation of cell signaling pathways, and the activation of transcription factors. In addition, cellular and viral lncRNAs regulate virus gene expression. Viral infections and associated immune responses alter the expression of host lncRNAs regulating immune responses, host metabolism, and viral replication. The influence of lncRNAs on the pathogenesis and outcomes of viral infections is being widely explored because virus-induced lncRNAs can serve as diagnostic and therapeutic targets. Future studies should focus on thoroughly characterizing lncRNA expressions in virus-infected primary cells, investigating their role in disease prognosis, and developing biologically relevant animal or organoid models to determine their suitability for specific therapeutic targeting. Many cellular and viral lncRNAs localize in the nucleus and epigenetically modulate viral transcription, latency, and host responses to infection. In this review, we provide an overview of the role of nuclear lncRNAs in the pathogenesis and outcomes of viral infections, such as the Influenza A virus, Sendai Virus, Respiratory Syncytial Virus, Hepatitis C virus, Human Immunodeficiency Virus, and Herpes Simplex Virus. We also address significant advances and barriers in characterizing lncRNA function and explore the potential of lncRNAs as therapeutic targets.

Recent Development in Biomedical Applications of Oligonucleotides with Triplex-Forming Ability

A DNA structure, known as triple-stranded DNA, is made up of three oligonucleotide chains that wind around one another to form a triple helix (TFO). Hoogsteen base pairing describes how triple-stranded DNA may be built at certain conditions by the attachment of the third strand to an RNA, PNA, or DNA, which might all be employed as oligonucleotide chains. In each of these situations, the oligonucleotides can be employed as an anchor, in conjunction with a specific bioactive chemical, or as a messenger that enables switching between transcription and replication through the triplex-forming zone. These data are also considered since various illnesses have been linked to the expansion of triplex-prone sequences. In light of metabolic acidosis and associated symptoms, some consideration is given to the impact of several low-molecular-weight compounds, including pH on triplex production in vivo. The review is focused on the development of biomedical oligonucleotides with triplexes.

TripDesign: A DNA Triplex Design Approach Based on Interaction Forces

A DNA triplex has the advantages of improved nanostructure stability and pH environment responsiveness compared with single-stranded and double-stranded nucleic acids. However, sequence stability and low design efficiency hinder the application of DNA triplexes. Therefore, a DNA triplex design approach (TripDesign) based on interaction forces is proposed. First, we present the stacking force constraint, torsional stress constraint, and G-quadruplex motif constraint and then use an improved memetic algorithm to design triplex sequences under combinatorial constraints. Finally, to quantify the process of triplex formation, we also explore the minimum length of the triplex-forming oligos (TFOs) required to form the triplex and the factors that produce depletion in cyclic pH-jump experiments. The experimental results show that the sequences produced by TripDesign have high stability and reversibility, and the proposed approach achieves efficient and automatic sequence design. In addition, this study characterizes multiple basic parameters of DNA triplex formation and promotes the wider application of DNA triplexes in nanotechnology.

Illuminating lncRNA Function Through Target Prediction

Most of the transcribed human genome codes for noncoding RNAs (ncRNAs), and long noncoding RNAs (lncRNAs) make for the lion's share of the human ncRNA space. Despite growing interest in lncRNAs, because there are so many of them, and because of their tissue specialization and, often, lower abundance, their catalog remains incomplete and there are multiple ongoing efforts to improve it. Consequently, the number of human lncRNA genes may be lower than 10,000 or higher than 200,000. A key open challenge for lncRNA research, now that so many lncRNA species have been identified, is the characterization of lncRNA function and the interpretation of the roles of genetic and epigenetic alterations at their loci. After all, the most important human genes to catalog and study are those that contribute to important cellular functions-that affect development or cell differentiation and whose dysregulation may play a role in the genesis and progression of human diseases. Multiple efforts have used screens based on RNA-mediated interference (RNAi), antisense oligonucleotide (ASO), and CRISPR screens to identify the consequences of lncRNA dysregulation and predict lncRNA function in select contexts, but these approaches have unresolved scalability and accuracy challenges. Instead-as was the case for better-studied ncRNAs in the past-researchers often focus on characterizing lncRNA interactions and investigating their effects on genes and pathways with known functions. Here, we focus most of our review on computational methods to identify lncRNA interactions and to predict the effects of their alterations and dysregulation on human disease pathways.

Emerging Roles of LncRNAs in the EZH2-regulated Oncogenic Network

Cancer is a life-threatening disease, but cancer therapies based on epigenetic mechanisms have made great progress. Enhancer of zeste homolog 2 (EZH2) is the key catalytic component of Polycomb repressive complex 2 (PRC2) that mediates the tri-methylation of lysine 27 on histone 3 (H3K27me3), a well-recognized marker of transcriptional repression. Mounting evidence indicates that EZH2 is elevated in various cancers and associates with poor prognosis. In addition, many studies revealed that EZH2 is also involved in transcriptional repression dependent or independent of PRC2. Meanwhile, long non-coding RNAs (lncRNAs) have been reported to regulate numerous and diverse signaling pathways in oncogenesis. In this review, we firstly discuss functional interactions between EZH2 and lncRNAs that determine PRC2-dependent and -independent roles of EZH2. Secondly, we summarize the lncRNAs regulating EZH2 expression at transcription, post-transcription and post-translation levels. Thirdly, we review several oncogenic pathways cooperatively regulated by lncRNAs and EZH2, including the Wnt/β-catenin and p53 pathways. In conclusion, lncRNAs play a key role in the EZH2-regulated oncogenic network with many fertile directions to be explored.

RNA:DNA triple helices: from peculiar structures to pervasive chromatin regulators

The genomes of complex eukaryotes largely contain non-protein-coding DNA, which is pervasively transcribed into a plethora of non-coding RNAs (ncRNAs). The functional importance of many of these ncRNAs has been investigated in the last two decades, revealing their crucial and multifaceted roles in chromatin regulation. A common mode of action of ncRNAs is the recruitment of chromatin modifiers to specific regions in the genome. Whereas many ncRNA-protein interactions have been characterised in detail, binding of ncRNAs to their DNA target sites is much less understood. Recently developed RNA-centric methods have mapped the genome-wide distribution of ncRNAs, however, how ncRNAs achieve locus-specificity remains mainly unresolved. In terms of direct RNA-DNA interactions, two kinds of triple-stranded structures can be formed: R-loops consisting of an RNA:DNA hybrid and a looped out DNA strand, and RNA:DNA triple helices (triplexes), in which the RNA binds to the major groove of the DNA double helix by sequence-specific Hoogsteen base pairing. In this essay, we will review the current knowledge about RNA:DNA triplexes, summarising triplex formation rules, detection methods, and ncRNAs reported to engage in triplexes. While the functional characterisation of RNA:DNA triplexes is still anecdotal, recent advances in high-throughput and computational analyses indicate their widespread distribution in the genome. Thus, we are witnessing a paradigm shift in the appreciation of RNA:DNA triplexes, away from exotic structures towards a prominent mode of ncRNA-chromatin interactions.

Triplex and other DNA motifs show motif-specific associations with mitochondrial DNA deletions and species lifespan

The "theory of resistant biomolecules" posits that long-lived species show resistance to molecular damage at the level of their biomolecules. Here, we test this hypothesis in the context of mitochondrial DNA (mtDNA) as it implies that predicted mutagenic DNA motifs should be inversely correlated with species maximum lifespan (MLS). First, we confirmed that guanine-quadruplex and direct repeat (DR) motifs are mutagenic, as they associate with mtDNA deletions in the human major arc of mtDNA, while also adding mirror repeat (MR) and intramolecular triplex motifs to a growing list of potentially mutagenic features. What is more, triplex motifs showed disease-specific associations with deletions and an apparent interaction with guanine-quadruplex motifs. Surprisingly, even though DR, MR and guanine-quadruplex motifs were associated with mtDNA deletions, their correlation with MLS was explained by the biased base composition of mtDNA. Only triplex motifs negatively correlated with MLS even after adjusting for body mass, phylogeny, mtDNA base composition and effective number of codons. Taken together, our work highlights the importance of base composition for the comparative biogerontology of mtDNA and suggests that future research on mitochondrial triplex motifs is warranted.

Genome-Wide Computational Analysis and Validation of Potential Long Noncoding RNA-Mediated DNA-DNA-RNA Triplexes in the Human Genome

Long noncoding RNAs are well studied for their regulatory actions through interaction with DNA regulating biological roles of DNA, RNA, or protein. However, direct binding of lncRNA with DNA is rarely demonstrated in experiments. The present protocol explains genome wide computational strategies to choose lncRNAs that can bind directly to the chromatin by forming highly stable DNA-DNA-RNA triplexes. The chapter also focuses on biophysical methods that can be used to validate the computationally derived lncRNA-gene targets in vitro.

Deep Learning in LncRNAome: Contribution, Challenges, and Perspectives

Long non-coding RNAs (lncRNA), the pervasively transcribed part of the mammalian genome, have played a significant role in changing our protein-centric view of genomes. The abundance of lncRNAs and their diverse roles across cell types have opened numerous avenues for the research community regarding lncRNAome. To discover and understand lncRNAome, many sophisticated computational techniques have been leveraged. Recently, deep learning (DL)-based modeling techniques have been successfully used in genomics due to their capacity to handle large amounts of data and produce relatively better results than traditional machine learning (ML) models. DL-based modeling techniques have now become a choice for many modeling tasks in the field of lncRNAome as well. In this review article, we summarized the contribution of DL-based methods in nine different lncRNAome research areas. We also outlined DL-based techniques leveraged in lncRNAome, highlighting the challenges computational scientists face while developing DL-based models for lncRNAome. To the best of our knowledge, this is the first review article that summarizes the role of DL-based techniques in multiple areas of lncRNAome.

Deep learning based DNA:RNA triplex forming potential prediction

BACKGROUND

Long non-coding RNAs (lncRNAs) can exert functions via forming triplex with DNA. The current methods in predicting the triplex formation mainly rely on mathematic statistic according to the base paring rules. However, these methods have two main limitations: (1) they identify a large number of triplex-forming lncRNAs, but the limited number of experimentally verified triplex-forming lncRNA indicates that maybe not all of them can form triplex in practice, and (2) their predictions only consider the theoretical relationship while lacking the features from the experimentally verified data.

RESULTS

In this work, we develop an integrated program named TriplexFPP (Triplex Forming Potential Prediction), which is the first machine learning model in DNA:RNA triplex prediction. TriplexFPP predicts the most likely triplex-forming lncRNAs and DNA sites based on the experimentally verified data, where the high-level features are learned by the convolutional neural networks. In the fivefold cross validation, the average values of Area Under the ROC curves and PRC curves for removed redundancy triplex-forming lncRNA dataset with threshold 0.8 are 0.9649 and 0.9996, and these two values for triplex DNA sites prediction are 0.8705 and 0.9671, respectively. Besides, we also briefly summarize the cis and trans targeting of triplexes lncRNAs.

CONCLUSIONS

The TriplexFPP is able to predict the most likely triplex-forming lncRNAs from all the lncRNAs with computationally defined triplex forming capacities and the potential of a DNA site to become a triplex. It may provide insights to the exploration of lncRNA functions.

Towards a comprehensive pipeline to identify and functionally annotate long noncoding RNA (lncRNA)

Long noncoding RNAs (lncRNAs) are implicated in various genetic diseases and cancer, attributed to their critical role in gene regulation. They are a divergent group of RNAs and are easily differentiated from other types with unique characteristics, functions, and mechanisms of action. In this review, we provide a list of some of the prominent data repositories containing lncRNAs, their interactome, and predicted and validated disease associations. Next, we discuss various wet-lab experiments formulated to obtain the data for these repositories. We also provide a critical review of in silico methods available for the identification purpose and suggest techniques to further improve their performance. The bulk of the methods currently focus on distinguishing lncRNA transcripts from the coding ones. Functional annotation of these transcripts still remains a grey area and more efforts are needed in that space. Finally, we provide details of current progress, discuss impediments, and illustrate a roadmap for developing a generalized computational pipeline for comprehensive annotation of lncRNAs, which is essential to accelerate research in this area.

Human Long Noncoding RNA Interactome: Detection, Characterization and Function

The application of a new generation of sequencing techniques has revealed that most of the genome has already been transcribed. However, only a small part of the genome codes proteins. The rest of the genome "dark matter" belongs to divergent groups of non-coding RNA (ncRNA), that is not translated into proteins. There are two groups of ncRNAs, which include small and long non-coding RNAs (sncRNA and lncRNA respectively). Over the last decade, there has been an increased interest in lncRNAs and their interaction with cellular components. In this review, we presented the newest information about the human lncRNA interactome. The term lncRNA interactome refers to cellular biomolecules, such as nucleic acids, proteins, and peptides that interact with lncRNA. The lncRNA interactome was characterized in the last decade, however, understanding what role the biomolecules associated with lncRNA play and the nature of these interactions will allow us to better understand lncRNA's biological functions in the cell. We also describe a set of methods currently used for the detection of lncRNA interactome components and the analysis of their interactions. We think that such a holistic and integrated analysis of the lncRNA interactome will help to better understand its potential role in the development of organisms and cancers.

Prediction of lncRNAs and their interactions with nucleic acids: benchmarking bioinformatics tools

The genomes of mammalian species are pervasively transcribed producing as many noncoding as protein-coding RNAs. There is a growing body of evidence supporting their functional role. Long noncoding RNA (lncRNA) can bind both nucleic acids and proteins through several mechanisms. A reliable computational prediction of the most probable mechanism of lncRNA interaction can facilitate experimental validation of its function. In this study, we benchmarked computational tools capable to discriminate lncRNA from mRNA and predict lncRNA interactions with other nucleic acids. We assessed the performance of 9 tools for distinguishing protein-coding from noncoding RNAs, as well as 19 tools for prediction of RNA-RNA and RNA-DNA interactions. Our conclusions about the considered tools were based on their performances on the entire genome/transcriptome level, as it is the most common task nowadays. We found that FEELnc and CPAT distinguish between coding and noncoding mammalian transcripts in the most accurate manner. ASSA, RIBlast and LASTAL, as well as Triplexator, turned out to be the best predictors of RNA-RNA and RNA-DNA interactions, respectively. We showed that the normalization of the predicted interaction strength to the transcript length and GC content may improve the accuracy of inferring RNA interactions. Yet, all the current tools have difficulties to make accurate predictions of short-trans RNA-RNA interactions-stretches of sparse contacts. All over, there is still room for improvement in each category, especially for predictions of RNA interactions.

Towards a complete map of the human long non-coding RNA transcriptome

Gene maps, or annotations, enable us to navigate the functional landscape of our genome. They are a resource upon which virtually all studies depend, from single-gene to genome-wide scales and from basic molecular biology to medical genetics. Yet present-day annotations suffer from trade-offs between quality and size, with serious but often unappreciated consequences for downstream studies. This is particularly true for long non-coding RNAs (lncRNAs), which are poorly characterized compared to protein-coding genes. Long-read sequencing technologies promise to improve current annotations, paving the way towards a complete annotation of lncRNAs expressed throughout a human lifetime.

Long Noncoding RNA MEG3 Is an Epigenetic Determinant of Oncogenic Signaling in Functional Pancreatic Neuroendocrine Tumor Cells

The long noncoding RNA (lncRNA) MEG3 is significantly downregulated in pancreatic neuroendocrine tumors (PNETs). MEG3 loss corresponds with aberrant upregulation of the oncogenic hepatocyte growth factor (HGF) receptor c-MET in PNETs. Meg3 overexpression in a mouse insulin-secreting PNET cell line, MIN6, downregulates c-Met expression. However, the molecular mechanism by which MEG3 regulates c-MET is not known. Using chromatin isolation by RNA purification and sequencing (ChIRP-Seq), we identified Meg3 binding to unique genomic regions in and around the c-Met gene. In the absence of Meg3, these c-Met regions displayed distinctive enhancer-signature histone modifications. Furthermore, Meg3 relied on functional enhancer of zeste homolog 2 (EZH2), a component of polycomb repressive complex 2 (PRC2), to inhibit c-Met expression. Another mechanism of lncRNA-mediated regulation of gene expression utilized triplex-forming GA-GT rich sequences. Transfection of such motifs from Meg3 RNA, termed triplex-forming oligonucleotides (TFOs), in MIN6 cells suppressed c-Met expression and enhanced cell proliferation, perhaps by modulating other targets. This study comprehensively establishes epigenetic mechanisms underlying Meg3 control of c-Met and the oncogenic consequences of Meg3 loss or c-Met gain. These findings have clinical relevance for targeting c-MET in PNETs. There is also the potential for pancreatic islet β-cell expansion through c-MET regulation to ameliorate β-cell loss in diabetes.

Genome-wide computational analysis of potential long noncoding RNA mediated DNA:DNA:RNA triplexes in the human genome

BACKGROUND

Only a handful of long noncoding RNAs have been functionally characterized. They are known to modulate regulation through interacting with other biomolecules in the cell: DNA, RNA and protein. Though there have been detailed investigations on lncRNA-miRNA and lncRNA-protein interactions, the interaction of lncRNAs with DNA have not been studied extensively. In the present study, we explore whether lncRNAs could modulate genomic regulation by interacting with DNA through the formation of highly stable DNA:DNA:RNA triplexes.

METHODS

We computationally screened 23,898 lncRNA transcripts as annotated by GENCODE, across the human genome for potential triplex forming sequence stretches (PTS). The PTS frequencies were compared across 5'UTR, CDS, 3'UTR, introns, promoter and 1000 bases downstream of the transcription termination sites. These regions were annotated by mapping to experimental regulatory regions, classes of repeat regions and transcription factors. We validated few putative triplex mediated interactions where lncRNA-gene pair interaction is via pyrimidine triplex motif using biophysical methods.

RESULTS

We identified 20,04,034 PTS sites to be enriched in promoter and intronic regions across human genome. Additional analysis of the association of PTS with core promoter elements revealed a systematic paucity of PTS in all regulatory regions, except TF binding sites. A total of 25 transcription factors were found to be associated with PTS. Using an interaction network, we showed that a subset of the triplex forming lncRNAs, have a positive association with gene promoters. We also demonstrated an in vitro interaction of one lncRNA candidate with its predicted gene target promoter regions.

CONCLUSIONS

Our analysis shows that PTS are enriched in gene promoter and largely associated with simple repeats. The current study suggests a major role of a subset of lncRNAs in mediating chromatin organization modulation through CTCF and NSRF proteins.

p53 Specifically Binds Triplex DNA In Vitro and in Cells

Triplex DNA is implicated in a wide range of biological activities, including regulation of gene expression and genomic instability leading to cancer. The tumor suppressor p53 is a central regulator of cell fate in response to different type of insults. Sequence and structure specific modes of DNA recognition are core attributes of the p53 protein. The focus of this work is the structure-specific binding of p53 to DNA containing triplex-forming sequences in vitro and in cells and the effect on p53-driven transcription. This is the first DNA binding study of full-length p53 and its deletion variants to both intermolecular and intramolecular T.A.T triplexes. We demonstrate that the interaction of p53 with intermolecular T.A.T triplex is comparable to the recognition of CTG-hairpin non-B DNA structure. Using deletion mutants we determined the C-terminal DNA binding domain of p53 to be crucial for triplex recognition. Furthermore, strong p53 recognition of intramolecular T.A.T triplexes (H-DNA), stabilized by negative superhelicity in plasmid DNA, was detected by competition and immunoprecipitation experiments, and visualized by AFM. Moreover, chromatin immunoprecipitation revealed p53 binding T.A.T forming sequence in vivo. Enhanced reporter transactivation by p53 on insertion of triplex forming sequence into plasmid with p53 consensus sequence was observed by luciferase reporter assays. In-silico scan of human regulatory regions for the simultaneous presence of both consensus sequence and T.A.T motifs identified a set of candidate p53 target genes and p53-dependent activation of several of them (ABCG5, ENOX1, INSR, MCC, NFAT5) was confirmed by RT-qPCR. Our results show that T.A.T triplex comprises a new class of p53 binding sites targeted by p53 in a DNA structure-dependent mode in vitro and in cells. The contribution of p53 DNA structure-dependent binding to the regulation of transcription is discussed.

Computational Approaches for Functional Prediction and Characterisation of Long Noncoding RNAs

Although a considerable portion of eukaryotic genomes is transcribed as long noncoding RNAs (lncRNAs), the vast majority are functionally uncharacterised. The rapidly expanding catalogue of mechanistically investigated lncRNAs has provided evidence for distinct functional subclasses, which are now ripe for exploitation as a general model to predict functions for uncharacterised lncRNAs. By utilising publicly-available genome-wide datasets and computational methods, we present several developed and emerging in silico approaches to characterise and predict the functions of lncRNAs. We propose that the application of these techniques provides valuable functional and mechanistic insight into lncRNAs, and is a crucial step for informing subsequent functional studies.

Selective Preference of Parallel DNA Triplexes Is Due to the Disruption of Hoogsteen Hydrogen Bonds Caused by the Severe Nonisostericity between the G*GC and T*AT Triplets

Implications of DNA, RNA and RNA.DNA hybrid triplexes in diverse biological functions, diseases and therapeutic applications call for a thorough understanding of their structure-function relationships. Despite exhaustive studies mechanistic rationale for the discriminatory preference of parallel DNA triplexes with G*GC & T*AT triplets still remains elusive. Here, we show that the highest nonisostericity between the G*GC & T*AT triplets imposes extensive stereochemical rearrangements contributing to context dependent triplex destabilisation through selective disruption of Hoogsteen scheme of hydrogen bonds. MD simulations of nineteen DNA triplexes with an assortment of sequence milieu reveal for the first time fresh insights into the nature and extent of destabilization from a single (non-overlapping), double (overlapping) and multiple pairs of nonisosteric base triplets (NIBTs). It is found that a solitary pair of NIBTs, feasible either at a G*GC/T*AT or T*AT/G*GC triplex junction, does not impinge significantly on triplex stability. But two overlapping pairs of NIBTs resulting from either a T*AT or a G*GC interruption disrupt Hoogsteen pair to a noncanonical mismatch destabilizing the triplex by ~10 to 14 kcal/mol, implying that their frequent incidence in multiples, especially, in short sequences could even hinder triplex formation. The results provide (i) an unambiguous and generalised mechanistic rationale for the discriminatory trait of parallel triplexes, including those studied experimentally (ii) clarity for the prevalence of antiparallel triplexes and (iii) comprehensive perspectives on the sequence dependent influence of nonisosteric base triplets useful in the rational design of TFO's against potential triplex target sites.

Biochemical Methods To Investigate lncRNA and the Influence of lncRNA:Protein Complexes on Chromatin

Long noncoding RNAs (lncRNAs), defined as nontranslated transcripts greater than 200 nucleotides in length, are often differentially expressed throughout developmental stages, tissue types, and disease states. The identification, visualization, and suppression/overexpression of these sequences have revealed impacts on a wide range of biological processes, including epigenetic regulation. Biochemical investigations on select systems have revealed striking insight into the biological roles of lncRNAs and lncRNA:protein complexes, which in turn prompt even more unanswered questions. To begin, multiple protein- and RNA-centric technologies have been employed to isolate lncRNA:protein and lncRNA:chromatin complexes. LncRNA interactions with the multi-subunit protein complex PRC2, which acts as a transcriptional silencer, represent some of the few cases where the binding affinity, selectivity, and activity of a lncRNA:protein complex have been investigated. At the same time, recent reports of full-length lncRNA secondary structures suggest the formation of complex structures with multiple independent folding domains and pave the way for more detailed structural investigations and predictions of lncRNA three-dimensional structure. This review will provide an overview of the methods and progress made to date as well as highlight new methods that promise to further inform the molecular recognition, specificity, and function of lncRNAs.

The TTSMI database: a catalog of triplex target DNA sites associated with genes and regulatory elements in the human genome

A triplex target DNA site (TTS), a stretch of DNA that is composed of polypurines, is able to form a triple-helix (triplex) structure with triplex-forming oligonucleotides (TFOs) and is able to influence the site-specific modulation of gene expression and/or the modification of genomic DNA. The co-localization of a genomic TTS with gene regulatory signals and functional genome structures suggests that TFOs could potentially be exploited in antigene strategies for the therapy of cancers and other genetic diseases. Here, we present the TTS Mapping and Integration (TTSMI; http://ttsmi.bii.a-star.edu.sg) database, which provides a catalog of unique TTS locations in the human genome and tools for analyzing the co-localization of TTSs with genomic regulatory sequences and signals that were identified using next-generation sequencing techniques and/or predicted by computational models. TTSMI was designed as a user-friendly tool that facilitates (i) fast searching/filtering of TTSs using several search terms and criteria associated with sequence stability and specificity, (ii) interactive filtering of TTSs that co-localize with gene regulatory signals and non-B DNA structures, (iii) exploration of dynamic combinations of the biological signals of specific TTSs and (iv) visualization of a TTS simultaneously with diverse annotation tracks via the UCSC genome browser.

GT-Scan: identifying unique genomic targets

A number of technologies, including CRISPR/Cas, transcription activator-like effector nucleases and zinc-finger nucleases, allow the user to target a chosen locus for genome editing or regulatory interference. Specificity, however, is a major problem, and the targeted locus must be chosen with care to avoid inadvertently affecting other loci ('off-targets') in the genome. To address this we have created 'Genome Target Scan' (GT-Scan), a flexible web-based tool that ranks all potential targets in a user-selected region of a genome in terms of how many off-targets they have. GT-Scan gives the user flexibility to define the desired characteristics of targets and off-targets via a simple 'target rule', and its interactive output allows detailed inspection of each of the most promising candidate targets. GT-Scan can be used to identify optimal targets for CRISPR/Cas systems, but its flexibility gives it potential to be adapted to other genome-targeting technologies as well.

AVAILABILITY AND IMPLEMENTATION

GT-Scan can be run via the web at: http://gt-scan.braembl.org.au.