Piroon Jenjaroenpun

Characterization of RNA in exosomes secreted by human breast cancer cell lines using next-generation sequencing

Exosomes are nanosized (30–100 nm) membrane vesicles secreted by most cell types. Exosomes have been found to contain various RNA species including miRNA, mRNA and long non-protein coding RNAs. A number of cancer cells produce elevated levels of exosomes. Because exosomes have been isolated from most body fluids they may provide a source for non-invasive cancer diagnostics. Transcriptome profiling that uses deep-sequencing technologies (RNA-Seq) offers enormous amount of data that can be used for biomarkers discovery, however, in case of exosomes this approach was applied only for the analysis of small RNAs. In this study, we utilized RNA-Seq technology to analyze RNAs present in microvesicles secreted by human breast cancer cell lines. Exosomes were isolated from the media conditioned by two human breast cancer cell lines, MDA-MB-231 and MDA-MB-436. Exosomal RNA was profiled using the Ion Torrent semiconductor chip-based technology. Exosomes were found to contain various classes of RNA with the major class represented by fragmented ribosomal RNA (rRNA), in particular 28S and 18S rRNA subunits. Analysis of exosomal RNA content revealed that it reflects RNA content of the donor cells. Although exosomes produced by the two cancer cell lines shared most of the RNA species, there was a number of non-coding transcripts unique to MDA-MB-231 and MDA-MB-436 cells. This suggests that RNA analysis might distinguish exosomes produced by low metastatic breast cancer cell line (MDA-MB-436) from that produced by highly metastatic breast cancer cell line (MDA-MB-231). The analysis of gene ontologies (GOs) associated with the most abundant transcripts present in exosomes revealed significant enrichment in genes encoding proteins involved in translation and rRNA and ncRNA processing. These GO terms indicate most expressed genes for both, cellular and exosomal RNA. For the first time, using RNA-seq, we examined the transcriptomes of exosomes secreted by human breast cancer cells. We found that most abundant exosomal RNA species are the fragments of 28S and 18S rRNA subunits. This limits the number of reads from other RNAs. To increase the number of detectable transcripts and improve the accuracy of their expression level the protocols allowing depletion of fragmented rRNA should be utilized in the future RNA-seq analyses on exosomes. Present data revealed that exosomal transcripts are representative of their cells of origin and thus could form basis for detection of tumor specific markers.

Ecotopic viral integration site 1 (EVI1) regulates multiple cellular processes important for cancer and is a synergistic partner for FOS protein in invasive tumors

Ecotropic viral integration site 1 (EVI1) is an oncogenic dual domain zinc finger transcription factor that plays an essential role in the regulation of hematopoietic stem cell renewal, and its overexpression in myeloid leukemia and epithelial cancers is associated with poor patient survival. Despite the discovery of EVI1 in 1988 and its emerging role as a dominant oncogene in various types of cancer, few EVI1 target genes are known. This lack of knowledge has precluded a clear understanding of exactly how EVI1 contributes to cancer. Using a combination of ChIP-Seq and microarray studies in human ovarian carcinoma cells, we show that the two zinc finger domains of EVI1 bind to DNA independently and regulate different sets of target genes. Strikingly, an enriched fraction of EVI1 target genes are cancer genes or genes associated with cancer. We also show that more than 25% of EVI1-occupied genes contain linked EVI1 and activator protein (AP)1 DNA binding sites, and this finding provides evidence for a synergistic cooperative interaction between EVI1 and the AP1 family member FOS in the regulation of cell adhesion, proliferation, and colony formation. An increased number of dual EVI1/AP1 target genes are also differentially regulated in late-stage ovarian carcinomas, further confirming the importance of the functional cooperation between EVI1 and FOS. Collectively, our data indicate that EVI1 is a multipurpose transcription factor that synergizes with FOS in invasive tumors.

Quantitative model of R-loop forming structures reveals a novel level of RNA–DNA interactome complexity

R-loop is the structure co-transcriptionally formed between nascent RNA transcript and DNA template, leaving the non-transcribed DNA strand unpaired. This structure can be involved in the hyper-mutation and dsDNA breaks in mammalian immunoglobulin (Ig) genes, oncogenes and neurodegenerative disease related genes. R-loops have not been studied at the genome scale yet. To identify the R-loops, we developed a computational algorithm and mapped R-loop forming sequences (RLFS) onto 66 803 sequences defined by UCSC as ‘known’ genes. We found that ∼59% of these transcribed sequences contain at least one RLFS. We created R-loopDB (http://rloop.bii.a-star.edu.sg/), the database that collects all RLFS identified within over half of the human genes and links to the UCSC Genome Browser for information integration and visualisation across a variety of bioinformatics sources. We found that many oncogenes and tumour suppressors (e.g. Tp53, BRCA1, BRCA2, Kras and Ptprd) and neurodegenerative diseases related genes (e.g. ATM, Park2, Ptprd and GLDC) could be prone to significant R-loop formation. Our findings suggest that R-loops provide a novel level of RNA–DNA interactome complexity, playing key roles in gene expression controls, mutagenesis, recombination process, chromosomal rearrangement, alternative splicing, DNA-editing and epigenetic modifications. RLFSs could be used as a novel source of prospective therapeutic targets.

Integrative analysis of the human cis-antisense gene pairs, miRNAs and their transcription regulation patterns

Cis-antisense gene pairs (CASGPs) can transcribe mRNAs from an opposite strand of a given locus. To classify and understand diverse CASGP phenomena in the human we compiled a genome-wide catalog of CASGPs and integrated these sequences with microarray, SAGE and miRNA data. Using the concept of overlapping regions and clustering of SA transcripts by chromosome coordinates, we identified up to 9000 overlapping antisense loci. Four thousand three hundred and seventy-four of these CASGPs form 1759 complex gene architectures. We found that ∼35% (6347/18160) of RefSeq genes are overlapped with the antisense transcripts. About 30% of Affymetrix U133 microarray initial sequences map transcripts of ∼35% CASGPs and reveal mostly concordant expression in CASGPs. We found strong significant overrepresentation of human miRNA genes in loci of CASGPs. We developed a data-driven model of cross-talk between co-expressed CASGPs and DICER1-mediated miRNA pathway in normal spermatogenesis and in severe teratozoospermia. Specifically, we revealed complex SA structural–functional gene module composing the protein-coding genes, WDR6, DALRD3, NDUFAF3 and ncRNA precursors, mir-425 and mir-191, which could provide downregulation of ncRNA pathway via direct targeting DICER1 and basonuclin 2 transcripts by mir-425 and mir-191 in normal spermatogenesis, but this mechanism is switched off in severe teratozoospermia. The database is available from http://globalisland.bii.a-star.edu.sg/∼jiangtao/sas/index3.php?link =about

Contrasting expression patterns of coding and noncoding parts of the human genome upon oxidative stress

Oxidative stress (OS) is caused by an imbalance between pro- and anti-oxidant reactions leading to accumulation of reactive oxygen species within cells. We here investigate the effect of OS on the transcriptome of human fibroblasts. OS causes a rapid and transient global induction of transcription characterized by pausing of RNA polymerase II (PolII) in both directions, at specific promoters, within 30 minutes of the OS response. In contrast to protein-coding genes, which are commonly down-regulated, this novel divergent, PolII pausing-phenomenon leads to the generation of thousands of long noncoding RNAs (lncRNAs) with promoter-associated antisense lncRNAs transcripts (si-paancRNAs) representing the major group of stress-induced transcripts. OS causes transient dynamics of si-lncRNAs in nucleus and cytosol, leading to their accumulation at polysomes, in contrast to mRNAs, which get depleted from polysomes. We propose that si-lncRNAs represent a novel component of the transcriptional stress that is known to determine the outcome of immediate-early and later cellular stress responses and we provide insights on the fate of those novel mature lncRNA transcripts by showing that their association with polysomal complexes is significantly increased in OS.

Role of genomic architecture in the expression dynamics of long noncoding RNAs during differentiation of human neuroblastoma cells

BackgroundMammalian genomes are extensively transcribed producing thousands of long non-protein-coding RNAs (lncRNAs). The biological significance and function of the vast majority of lncRNAs remain unclear. Recent studies have implicated several lncRNAs as playing important roles in embryonic development and cancer progression. LncRNAs are characterized with different genomic architectures in relationship with their associated protein-coding genes. Our study aimed at bridging lncRNA architecture with dynamical patterns of their expression using differentiating human neuroblastoma cells model.ResultsLncRNA expression was studied in a 120-hours timecourse of differentiation of human neuroblastoma SH-SY5Y cells into neurons upon treatment with retinoic acid (RA), the compound used for the treatment of neuroblastoma. A custom microarray chip was utilized to interrogate expression levels of 9,267 lncRNAs in the course of differentiation. We categorized lncRNAs into 19 architecture classes according to their position relatively to protein-coding genes. For each architecture class, dynamics of expression of lncRNAs was studied in association with their protein-coding partners. It allowed us to demonstrate positive correlation of lncRNAs with their associated protein-coding genes at bidirectional promoters and for sense-antisense transcript pairs. In contrast, lncRNAs located in the introns and downstream of the protein-coding genes were characterized with negative correlation modes. We further classified the lncRNAs by the temporal patterns of their expression dynamics. We found that intronic and bidirectional promoter architectures are associated with rapid RA-dependent induction or repression of the corresponding lncRNAs, followed by their constant expression. At the same time, lncRNAs expressed downstream of protein-coding genes are characterized by rapid induction, followed by transcriptional repression. Quantitative RT-PCR analysis confirmed the discovered functional modes for several selected lncRNAs associated with proteins involved in cancer and embryonic development.ConclusionsThis is the first report detailing dynamical changes of multiple lncRNAs during RA-induced neuroblastoma differentiation. Integration of genomic and transcriptomic levels of information allowed us to demonstrate specific behavior of lncRNAs organized in different genomic architectures. This study also provides a list of lncRNAs with possible roles in neuroblastoma.

QmRLFS-finder: a model, web server and stand-alone tool for prediction and analysis of R-loop forming sequences

The possible formation of three-stranded RNA and DNA hybrid structures (R-loops) in thousands of functionally important guanine-rich genic and inter-genic regions could suggest their involvement in transcriptional regulation and even development of diseases. Here, we introduce the first freely available R-loop prediction program called Quantitative Model of R-loop Forming Sequence (RLFS) finder (QmRLFS-finder), which predicts RLFSs in nucleic acid sequences based on experimentally supported structural models of RLFSs. QmRLFS-finder operates via a web server or a stand-alone command line tool. This tool identifies and visualizes RLFS coordinates from any natural or artificial DNA or RNA input sequences and creates standards-compliant output files for further annotation and analysis. QmRLFS-finder demonstrates highly accurate predictions of the detected RLFSs, proposing new perspective to further discoveries in R-loop biology, biotechnology and molecular therapy. QmRLFS-finder is freely available at http://rloop.bii.a-star.edu.sg/?pg=qmrlfs-finder.

Duplex stem-loop-containing quadruplex motifs in the human genome: a combined genomic and structural study

Duplex stem-loops and four-stranded G-quadruplexes have been implicated in (patho)biological processes. Overlap of stem-loop- and quadruplex-forming sequences could give rise to quadruplex–duplex hybrids (QDH), which combine features of both structural forms and could exhibit unique properties. Here, we present a combined genomic and structural study of stem-loop-containing quadruplex sequences (SLQS) in the human genome. Based on a maximum loop length of 20 nt, our survey identified 80 307 SLQS, embedded within 60 172 unique clusters. Our analysis suggested that these should cover close to half of total SLQS in the entire genome. Among these, 48 508 SLQS were strand-specifically located in genic/promoter regions, with the majority of genes displaying a low number of SLQS. Notably, genes containing abundant SLQS clusters were strongly associated with brain tissues. Enrichment analysis of SLQS-positive genes and mapping of SLQS onto transcriptional/mutagenesis hotspots and cancer-associated genes, provided a statistical framework supporting the biological involvements of SLQS. In vitro formation of diverse QDH by selective SLQS hits were successfully verified by nuclear magnetic resonance spectroscopy. Folding topologies of two SLQS were elucidated in detail. We also demonstrated that sequence changes at mutation/single-nucleotide polymorphism loci could affect the structural conformations adopted by SLQS. Thus, our predicted SLQS offer novel insights into the potential involvement of QDH in diverse (patho)biological processes and could represent novel regulatory signals.

Statistics of protein-DNA binding and the total number of binding sites for a transcription factor in the mammalian genome

BackgroundTranscription factor (TF)-DNA binding loci are explored by analyzing massive datasets generated with application of Chromatin Immuno-Precipitation (ChIP)-based high-throughput sequencing technologies. These datasets suffer from a bias in the information about binding loci availability, sample incompleteness and diverse sources of technical and biological noises. Therefore adequate mathematical models of ChIP-based high-throughput assay(s) and statistical tools are required for a robust identification of specific and reliable TF binding sites (TFBS), a precise characterization of TFBS avidity distribution and a plausible estimation the total number of specific TFBS for a given TF in the genome for a given cell type.ResultsWe developed an exploratory mixture probabilistic model for a specific and non-specific transcription factor-DNA (TF-DNA) binding. Within ChiP-seq data sets, the statistics of specific and non-specific DNA-protein binding is defined by a mixture of sample size-dependent skewed functions described by Kolmogorov-Waring (K-W) function (Kuznetsov, 2003) and exponential function, respectively. Using available Chip-seq data for eleven TFs, essential for self-maintenance and differentiation of mouse embryonic stem cells (SC) (Nanog, Oct4, sox2, KLf4, STAT3, E2F1, Tcfcp211, ZFX, n-Myc, c-Myc and Essrb) reported in Chen et al (2008), we estimated (i) the specificity and the sensitivity of the ChiP-seq binding assays and (ii) the number of specific but not identified in the current experiments binding sites (BSs) in the genome of mouse embryonic stem cells. Motif finding analysis applied to the identified c-Myc TFBSs supports our results and allowed us to predict many novel c-Myc target genes.ConclusionWe provide a novel methodology of estimating the specificity and the sensitivity of TF-DNA binding in massively paralleled ChIP sequencing (ChIP-seq) binding assay. Goodness-of fit analysis of K-W functions suggests that a large fraction of low- and moderate- avidity TFBSs cannot be identified by the ChIP-based methods. Thus the task to identify the binding sensitivity of a TF cannot be technically resolved yet by current ChIP-seq, compared to former experimental techniques. Considering our improvement in measuring the sensitivity and the specificity of the TFs obtained from the ChIP-seq data, the models of transcriptional regulatory networks in embryonic cells and other cell types derived from the given ChIp-seq data should be carefully revised.

Sense-antisense gene-pairs in breast cancer and associated pathological pathways

More than 30% of human protein-coding genes form hereditary complex genome architectures composed of sense-antisense (SA) gene pairs (SAGPs) transcribing their RNAs from both strands of a given locus. Such architectures represent important novel components of genome complexity contributing to gene expression deregulation in cancer cells. Therefore, the architectures might be involved in cancer pathways and, in turn, be used for novel drug targets discovery. However, the global roles of SAGPs in cancer pathways has not been studied. Here we investigated SAGPs associated with breast cancer (BC)-related pathways using systems biology, prognostic survival and experimental methods. Gene expression analysis identified 73 BC-relevant SAGPs that are highly correlated in BC. Survival modelling and metadata analysis of the 1161 BC patients allowed us to develop a novel patient prognostic grouping method selecting the 12 survival-significant SAGPs. The qRT-PCR-validated 12-SAGP prognostic signature reproducibly stratified BC patients into low- and high-risk prognostic subgroups. The 1381 SAGP-defined differentially expressed genes common across three studied cohorts were identified. The functional enrichment analysis of these genes revealed the GABPA gene network, including BC-relevant SAGPs, specific gene sets involved in cell cycle, spliceosomal and proteasomal pathways. The co-regulatory function of GABPA in BC cells was supported using siRNA knockdown studies. Thus, we demonstrated SAGPs as the synergistically functional genome architectures interconnected with cancer-related pathways and associated with BC patient clinical outcomes. Taken together, SAGPs represent an important component of genome complexity which can be used to identify novel aspects of coordinated pathological gene networks in cancers.