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Genome-wide identification and characterization of long intergenic non-coding RNAs in Ganoderma lucidum.
PUBLISHED: 01-01-2014
Ganoderma lucidum is a white-rot fungus best-known for its medicinal activities. We have previously sequenced its genome and annotated the protein coding genes. However, long non-coding RNAs in G. lucidum genome have not been analyzed. In this study, we have identified and characterized long intergenic non-coding RNAs (lincRNA) in G. lucidum systematically. We developed a computational pipeline, which was used to analyze RNA-Seq data derived from G. lucidum samples collected from three developmental stages. A total of 402 lincRNA candidates were identified, with an average length of 609 bp. Analysis of their adjacent protein-coding genes (apcGenes) revealed that 46 apcGenes belong to the pathways of triterpenoid biosynthesis and lignin degradation, or families of cytochrome P450, mating type B genes, and carbohydrate-active enzymes. To determine if lincRNAs and these apcGenes have any interactions, the corresponding pairs of lincRNAs and apcGenes were analyzed in detail. We developed a modified 3' RACE method to analyze the transcriptional direction of a transcript. Among the 46 lincRNAs, 37 were found unidirectionally transcribed, and 9 were found bidirectionally transcribed. The expression profiles of 16 of these 37 lincRNAs were found to be highly correlated with those of the apcGenes across the three developmental stages. Among them, 11 are positively correlated (r>0.8) and 5 are negatively correlated (r<-0.8). The co-localization and co-expression of lincRNAs and those apcGenes playing important functions is consistent with the notion that lincRNAs might be important regulators for cellular processes. In summary, this represents the very first study to identify and characterize lincRNAs in the genomes of basidiomycetes. The results obtained here have laid the foundation for study of potential lincRNA-mediated expression regulation of genes in G. lucidum.
Hematopoietic stem cells (HSCs) are used clinically for transplantation treatment to rebuild a patient's hematopoietic system in many diseases such as leukemia and lymphoma. Elucidating the mechanisms controlling HSCs self-renewal and differentiation is important for application of HSCs for research and clinical uses. However, it is not possible to obtain large quantity of HSCs due to their inability to proliferate in vitro. To overcome this hurdle, we used a mouse bone marrow derived cell line, the EML (Erythroid, Myeloid, and Lymphocytic) cell line, as a model system for this study. RNA-sequencing (RNA-Seq) has been increasingly used to replace microarray for gene expression studies. We report here a detailed method of using RNA-Seq technology to investigate the potential key factors in regulation of EML cell self-renewal and differentiation. The protocol provided in this paper is divided into three parts. The first part explains how to culture EML cells and separate Lin-CD34+ and Lin-CD34- cells. The second part of the protocol offers detailed procedures for total RNA preparation and the subsequent library construction for high-throughput sequencing. The last part describes the method for RNA-Seq data analysis and explains how to use the data to identify differentially expressed transcription factors between Lin-CD34+ and Lin-CD34- cells. The most significantly differentially expressed transcription factors were identified to be the potential key regulators controlling EML cell self-renewal and differentiation. In the discussion section of this paper, we highlight the key steps for successful performance of this experiment. In summary, this paper offers a method of using RNA-Seq technology to identify potential regulators of self-renewal and differentiation in EML cells. The key factors identified are subjected to downstream functional analysis in vitro and in vivo.
22 Related JoVE Articles!
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Production of Xenopus tropicalis Egg Extracts to Identify Microtubule-associated RNAs
Authors: Judith A. Sharp, Mike D. Blower.
Institutions: Massachusetts General Hospital, Harvard Medical School.
Many organisms localize mRNAs to specific subcellular destinations to spatially and temporally control gene expression. Recent studies have demonstrated that the majority of the transcriptome is localized to a nonrandom position in cells and embryos. One approach to identify localized mRNAs is to biochemically purify a cellular structure of interest and to identify all associated transcripts. Using recently developed high-throughput sequencing technologies it is now straightforward to identify all RNAs associated with a subcellular structure. To facilitate transcript identification it is necessary to work with an organism with a fully sequenced genome. One attractive system for the biochemical purification of subcellular structures are egg extracts produced from the frog Xenopus laevis. However, X. laevis currently does not have a fully sequenced genome, which hampers transcript identification. In this article we describe a method to produce egg extracts from a related frog, X. tropicalis, that has a fully sequenced genome. We provide details for microtubule polymerization, purification and transcript isolation. While this article describes a specific method for identification of microtubule-associated transcripts, we believe that it will be easily applied to other subcellular structures and will provide a powerful method for identification of localized RNAs.
Molecular Biology, Issue 76, Genetics, Developmental Biology, Biochemistry, Bioengineering, Cellular Biology, RNA, Messenger, Stored, RNA Processing, Post-Transcriptional, Xenopus, microtubules, egg extract, purification, RNA localization, mRNA, Xenopus tropicalis, eggs, animal model
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Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Authors: Philippe Pérot, Valérie Cheynet, Myriam Decaussin-Petrucci, Guy Oriol, Nathalie Mugnier, Claire Rodriguez-Lafrasse, Alain Ruffion, François Mallet.
Institutions: Joint Unit Hospices de Lyon-bioMérieux, BioMérieux, Hospices Civils de Lyon, Lyon 1 University, BioMérieux, Hospices Civils de Lyon, Hospices Civils de Lyon.
The prostate-specific antigen (PSA) is the main diagnostic biomarker for prostate cancer in clinical use, but it lacks specificity and sensitivity, particularly in low dosage values1​​. ‘How to use PSA' remains a current issue, either for diagnosis as a gray zone corresponding to a concentration in serum of 2.5-10 ng/ml which does not allow a clear differentiation to be made between cancer and noncancer2 or for patient follow-up as analysis of post-operative PSA kinetic parameters can pose considerable challenges for their practical application3,4. Alternatively, noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease, e.g. PCA3 in prostate cancer5,6 and to reveal uncharacterized aspects of tumor biology. Moreover, data from the ENCODE project published in 2012 showed that different RNA types cover about 62% of the genome. It also appears that the amount of transcriptional regulatory motifs is at least 4.5x higher than the one corresponding to protein-coding exons. Thus, long terminal repeats (LTRs) of human endogenous retroviruses (HERVs) constitute a wide range of putative/candidate transcriptional regulatory sequences, as it is their primary function in infectious retroviruses. HERVs, which are spread throughout the human genome, originate from ancestral and independent infections within the germ line, followed by copy-paste propagation processes and leading to multicopy families occupying 8% of the human genome (note that exons span 2% of our genome). Some HERV loci still express proteins that have been associated with several pathologies including cancer7-10. We have designed a high-density microarray, in Affymetrix format, aiming to optimally characterize individual HERV loci expression, in order to better understand whether they can be active, if they drive ncRNA transcription or modulate coding gene expression. This tool has been applied in the prostate cancer field (Figure 1).
Medicine, Issue 81, Cancer Biology, Genetics, Molecular Biology, Prostate, Retroviridae, Biomarkers, Pharmacological, Tumor Markers, Biological, Prostatectomy, Microarray Analysis, Gene Expression, Diagnosis, Human Endogenous Retroviruses, HERV, microarray, Transcriptome, prostate cancer, Affymetrix
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Detection of the Genome and Transcripts of a Persistent DNA Virus in Neuronal Tissues by Fluorescent In situ Hybridization Combined with Immunostaining
Authors: Frédéric Catez, Antoine Rousseau, Marc Labetoulle, Patrick Lomonte.
Institutions: CNRS UMR 5534, Université de Lyon 1, LabEX DEVweCAN, CNRS UPR 3296, CNRS UMR 5286.
Single cell codetection of a gene, its RNA product and cellular regulatory proteins is critical to study gene expression regulation. This is a challenge in the field of virology; in particular for nuclear-replicating persistent DNA viruses that involve animal models for their study. Herpes simplex virus type 1 (HSV-1) establishes a life-long latent infection in peripheral neurons. Latent virus serves as reservoir, from which it reactivates and induces a new herpetic episode. The cell biology of HSV-1 latency remains poorly understood, in part due to the lack of methods to detect HSV-1 genomes in situ in animal models. We describe a DNA-fluorescent in situ hybridization (FISH) approach efficiently detecting low-copy viral genomes within sections of neuronal tissues from infected animal models. The method relies on heat-based antigen unmasking, and directly labeled home-made DNA probes, or commercially available probes. We developed a triple staining approach, combining DNA-FISH with RNA-FISH and immunofluorescence, using peroxidase based signal amplification to accommodate each staining requirement. A major improvement is the ability to obtain, within 10 µm tissue sections, low-background signals that can be imaged at high resolution by confocal microscopy and wide-field conventional epifluorescence. Additionally, the triple staining worked with a wide range of antibodies directed against cellular and viral proteins. The complete protocol takes 2.5 days to accommodate antibody and probe penetration within the tissue.
Neuroscience, Issue 83, Life Sciences (General), Virology, Herpes Simplex Virus (HSV), Latency, In situ hybridization, Nuclear organization, Gene expression, Microscopy
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Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells
Authors: Anne Katchy, Cecilia Williams.
Institutions: University of Houston.
Estrogen plays vital roles in mammary gland development and breast cancer progression. It mediates its function by binding to and activating the estrogen receptors (ERs), ERα, and ERβ. ERα is frequently upregulated in breast cancer and drives the proliferation of breast cancer cells. The ERs function as transcription factors and regulate gene expression. Whereas ERα's regulation of protein-coding genes is well established, its regulation of noncoding microRNA (miRNA) is less explored. miRNAs play a major role in the post-transcriptional regulation of genes, inhibiting their translation or degrading their mRNA. miRNAs can function as oncogenes or tumor suppressors and are also promising biomarkers. Among the miRNA assays available, microarray and quantitative real-time polymerase chain reaction (qPCR) have been extensively used to detect and quantify miRNA levels. To identify miRNAs regulated by estrogen signaling in breast cancer, their expression in ERα-positive breast cancer cell lines were compared before and after estrogen-activation using both the µParaflo-microfluidic microarrays and Dual Labeled Probes-low density arrays. Results were validated using specific qPCR assays, applying both Cyanine dye-based and Dual Labeled Probes-based chemistry. Furthermore, a time-point assay was used to identify regulations over time. Advantages of the miRNA assay approach used in this study is that it enables a fast screening of mature miRNA regulations in numerous samples, even with limited sample amounts. The layout, including the specific conditions for cell culture and estrogen treatment, biological and technical replicates, and large-scale screening followed by in-depth confirmations using separate techniques, ensures a robust detection of miRNA regulations, and eliminates false positives and other artifacts. However, mutated or unknown miRNAs, or regulations at the primary and precursor transcript level, will not be detected. The method presented here represents a thorough investigation of estrogen-mediated miRNA regulation.
Medicine, Issue 84, breast cancer, microRNA, estrogen, estrogen receptor, microarray, qPCR
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Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale
Authors: Valentina Gandin, Kristina Sikström, Tommy Alain, Masahiro Morita, Shannon McLaughlan, Ola Larsson, Ivan Topisirovic.
Institutions: McGill University, Karolinska Institutet, McGill University.
mRNA translation plays a central role in the regulation of gene expression and represents the most energy consuming process in mammalian cells. Accordingly, dysregulation of mRNA translation is considered to play a major role in a variety of pathological states including cancer. Ribosomes also host chaperones, which facilitate folding of nascent polypeptides, thereby modulating function and stability of newly synthesized polypeptides. In addition, emerging data indicate that ribosomes serve as a platform for a repertoire of signaling molecules, which are implicated in a variety of post-translational modifications of newly synthesized polypeptides as they emerge from the ribosome, and/or components of translational machinery. Herein, a well-established method of ribosome fractionation using sucrose density gradient centrifugation is described. In conjunction with the in-house developed “anota” algorithm this method allows direct determination of differential translation of individual mRNAs on a genome-wide scale. Moreover, this versatile protocol can be used for a variety of biochemical studies aiming to dissect the function of ribosome-associated protein complexes, including those that play a central role in folding and degradation of newly synthesized polypeptides.
Biochemistry, Issue 87, Cells, Eukaryota, Nutritional and Metabolic Diseases, Neoplasms, Metabolic Phenomena, Cell Physiological Phenomena, mRNA translation, ribosomes, protein synthesis, genome-wide analysis, translatome, mTOR, eIF4E, 4E-BP1
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A Restriction Enzyme Based Cloning Method to Assess the In vitro Replication Capacity of HIV-1 Subtype C Gag-MJ4 Chimeric Viruses
Authors: Daniel T. Claiborne, Jessica L. Prince, Eric Hunter.
Institutions: Emory University, Emory University.
The protective effect of many HLA class I alleles on HIV-1 pathogenesis and disease progression is, in part, attributed to their ability to target conserved portions of the HIV-1 genome that escape with difficulty. Sequence changes attributed to cellular immune pressure arise across the genome during infection, and if found within conserved regions of the genome such as Gag, can affect the ability of the virus to replicate in vitro. Transmission of HLA-linked polymorphisms in Gag to HLA-mismatched recipients has been associated with reduced set point viral loads. We hypothesized this may be due to a reduced replication capacity of the virus. Here we present a novel method for assessing the in vitro replication of HIV-1 as influenced by the gag gene isolated from acute time points from subtype C infected Zambians. This method uses restriction enzyme based cloning to insert the gag gene into a common subtype C HIV-1 proviral backbone, MJ4. This makes it more appropriate to the study of subtype C sequences than previous recombination based methods that have assessed the in vitro replication of chronically derived gag-pro sequences. Nevertheless, the protocol could be readily modified for studies of viruses from other subtypes. Moreover, this protocol details a robust and reproducible method for assessing the replication capacity of the Gag-MJ4 chimeric viruses on a CEM-based T cell line. This method was utilized for the study of Gag-MJ4 chimeric viruses derived from 149 subtype C acutely infected Zambians, and has allowed for the identification of residues in Gag that affect replication. More importantly, the implementation of this technique has facilitated a deeper understanding of how viral replication defines parameters of early HIV-1 pathogenesis such as set point viral load and longitudinal CD4+ T cell decline.
Infectious Diseases, Issue 90, HIV-1, Gag, viral replication, replication capacity, viral fitness, MJ4, CEM, GXR25
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DNA-affinity-purified Chip (DAP-chip) Method to Determine Gene Targets for Bacterial Two component Regulatory Systems
Authors: Lara Rajeev, Eric G. Luning, Aindrila Mukhopadhyay.
Institutions: Lawrence Berkeley National Laboratory.
In vivo methods such as ChIP-chip are well-established techniques used to determine global gene targets for transcription factors. However, they are of limited use in exploring bacterial two component regulatory systems with uncharacterized activation conditions. Such systems regulate transcription only when activated in the presence of unique signals. Since these signals are often unknown, the in vitro microarray based method described in this video article can be used to determine gene targets and binding sites for response regulators. This DNA-affinity-purified-chip method may be used for any purified regulator in any organism with a sequenced genome. The protocol involves allowing the purified tagged protein to bind to sheared genomic DNA and then affinity purifying the protein-bound DNA, followed by fluorescent labeling of the DNA and hybridization to a custom tiling array. Preceding steps that may be used to optimize the assay for specific regulators are also described. The peaks generated by the array data analysis are used to predict binding site motifs, which are then experimentally validated. The motif predictions can be further used to determine gene targets of orthologous response regulators in closely related species. We demonstrate the applicability of this method by determining the gene targets and binding site motifs and thus predicting the function for a sigma54-dependent response regulator DVU3023 in the environmental bacterium Desulfovibrio vulgaris Hildenborough.
Genetics, Issue 89, DNA-Affinity-Purified-chip, response regulator, transcription factor binding site, two component system, signal transduction, Desulfovibrio, lactate utilization regulator, ChIP-chip
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Enhanced Northern Blot Detection of Small RNA Species in Drosophila Melanogaster
Authors: Pietro Laneve, Angela Giangrande.
Institutions: Institut de Génétique et de Biologie Moléculaire et Cellulaire, Istituto Italiano di Tecnologia.
The last decades have witnessed the explosion of scientific interest around gene expression control mechanisms at the RNA level. This branch of molecular biology has been greatly fueled by the discovery of noncoding RNAs as major players in post-transcriptional regulation. Such a revolutionary perspective has been accompanied and triggered by the development of powerful technologies for profiling short RNAs expression, both at the high-throughput level (genome-wide identification) or as single-candidate analysis (steady state accumulation of specific species). Although several state-of-art strategies are currently available for dosing or visualizing such fleeing molecules, Northern Blot assay remains the eligible approach in molecular biology for immediate and accurate evaluation of RNA expression. It represents a first step toward the application of more sophisticated, costly technologies and, in many cases, remains a preferential method to easily gain insights into RNA biology. Here we overview an efficient protocol (Enhanced Northern Blot) for detecting weakly expressed microRNAs (or other small regulatory RNA species) from Drosophila melanogaster whole embryos, manually dissected larval/adult tissues or in vitro cultured cells. A very limited amount of RNA is required and the use of material from flow cytometry-isolated cells can be also envisaged.
Molecular Biology, Issue 90, Northern blotting, Noncoding RNAs, microRNAs, rasiRNA, Gene expression, Gcm/Glide, Drosophila melanogaster
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Quick Fluorescent In Situ Hybridization Protocol for Xist RNA Combined with Immunofluorescence of Histone Modification in X-chromosome Inactivation
Authors: Minghui Yue, John Lalith Charles Richard, Norishige Yamada, Akiyo Ogawa, Yuya Ogawa.
Institutions: Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine.
Combining RNA fluorescent in situ hybridization (FISH) with immunofluorescence (immuno-FISH) creates a technique that can be employed at the single cell level to detect the spatial dynamics of RNA localization with simultaneous insight into the localization of proteins, epigenetic modifications and other details which can be highlighted by immunofluorescence. X-chromosome inactivation is a paradigm for long non-coding RNA (lncRNA)-mediated gene silencing. X-inactive specific transcript (Xist) lncRNA accumulation (called an Xist cloud) on one of the two X-chromosomes in mammalian females is a critical step to initiate X-chromosome inactivation. Xist RNA directly or indirectly interacts with various chromatin-modifying enzymes and introduces distinct epigenetic landscapes to the inactive X-chromosome (Xi). One known epigenetic hallmark of the Xi is the Histone H3 trimethyl-lysine 27 (H3K27me3) modification. Here, we describe a simple and quick immuno-FISH protocol for detecting Xist RNA using RNA FISH with multiple oligonucleotide probes coupled with immunofluorescence of H3K27me3 to examine the localization of Xist RNA and associated epigenetic modifications. Using oligonucleotide probes results in a shorter incubation time and more sensitive detection of Xist RNA compared to in vitro transcribed RNA probes (riboprobes). This protocol provides a powerful tool for understanding the dynamics of lncRNAs and its associated epigenetic modification, chromatin structure, nuclear organization and transcriptional regulation.
Genetics, Issue 93, Xist, X-chromosome inactivation, FISH, histone methylation, epigenetics, long non-coding RNA
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RNA Secondary Structure Prediction Using High-throughput SHAPE
Authors: Sabrina Lusvarghi, Joanna Sztuba-Solinska, Katarzyna J. Purzycka, Jason W. Rausch, Stuart F.J. Le Grice.
Institutions: Frederick National Laboratory for Cancer Research.
Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed "high-throughput selective 2' hydroxyl acylation analyzed by primer extension", or SHAPE, allows prediction of RNA secondary structure with single nucleotide resolution. This approach utilizes chemical probing agents that preferentially acylate single stranded or flexible regions of RNA in aqueous solution. Sites of chemical modification are detected by reverse transcription of the modified RNA, and the products of this reaction are fractionated by automated capillary electrophoresis (CE). Since reverse transcriptase pauses at those RNA nucleotides modified by the SHAPE reagents, the resulting cDNA library indirectly maps those ribonucleotides that are single stranded in the context of the folded RNA. Using ShapeFinder software, the electropherograms produced by automated CE are processed and converted into nucleotide reactivity tables that are themselves converted into pseudo-energy constraints used in the RNAStructure (v5.3) prediction algorithm. The two-dimensional RNA structures obtained by combining SHAPE probing with in silico RNA secondary structure prediction have been found to be far more accurate than structures obtained using either method alone.
Genetics, Issue 75, Molecular Biology, Biochemistry, Virology, Cancer Biology, Medicine, Genomics, Nucleic Acid Probes, RNA Probes, RNA, High-throughput SHAPE, Capillary electrophoresis, RNA structure, RNA probing, RNA folding, secondary structure, DNA, nucleic acids, electropherogram, synthesis, transcription, high throughput, sequencing
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Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture
Authors: Bernd Rädle, Andrzej J. Rutkowski, Zsolt Ruzsics, Caroline C. Friedel, Ulrich H. Koszinowski, Lars Dölken.
Institutions: Max von Pettenkofer Institute, University of Cambridge, Ludwig-Maximilians-University Munich.
The development of whole-transcriptome microarrays and next-generation sequencing has revolutionized our understanding of the complexity of cellular gene expression. Along with a better understanding of the involved molecular mechanisms, precise measurements of the underlying kinetics have become increasingly important. Here, these powerful methodologies face major limitations due to intrinsic properties of the template samples they study, i.e. total cellular RNA. In many cases changes in total cellular RNA occur either too slowly or too quickly to represent the underlying molecular events and their kinetics with sufficient resolution. In addition, the contribution of alterations in RNA synthesis, processing, and decay are not readily differentiated. We recently developed high-resolution gene expression profiling to overcome these limitations. Our approach is based on metabolic labeling of newly transcribed RNA with 4-thiouridine (thus also referred to as 4sU-tagging) followed by rigorous purification of newly transcribed RNA using thiol-specific biotinylation and streptavidin-coated magnetic beads. It is applicable to a broad range of organisms including vertebrates, Drosophila, and yeast. We successfully applied 4sU-tagging to study real-time kinetics of transcription factor activities, provide precise measurements of RNA half-lives, and obtain novel insights into the kinetics of RNA processing. Finally, computational modeling can be employed to generate an integrated, comprehensive analysis of the underlying molecular mechanisms.
Genetics, Issue 78, Cellular Biology, Molecular Biology, Microbiology, Biochemistry, Eukaryota, Investigative Techniques, Biological Phenomena, Gene expression profiling, RNA synthesis, RNA processing, RNA decay, 4-thiouridine, 4sU-tagging, microarray analysis, RNA-seq, RNA, DNA, PCR, sequencing
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RNA-seq Analysis of Transcriptomes in Thrombin-treated and Control Human Pulmonary Microvascular Endothelial Cells
Authors: Dilyara Cheranova, Margaret Gibson, Suman Chaudhary, Li Qin Zhang, Daniel P. Heruth, Dmitry N. Grigoryev, Shui Qing Ye.
Institutions: Children's Mercy Hospital and Clinics, School of Medicine, University of Missouri-Kansas City.
The characterization of gene expression in cells via measurement of mRNA levels is a useful tool in determining how the transcriptional machinery of the cell is affected by external signals (e.g. drug treatment), or how cells differ between a healthy state and a diseased state. With the advent and continuous refinement of next-generation DNA sequencing technology, RNA-sequencing (RNA-seq) has become an increasingly popular method of transcriptome analysis to catalog all species of transcripts, to determine the transcriptional structure of all expressed genes and to quantify the changing expression levels of the total set of transcripts in a given cell, tissue or organism1,2 . RNA-seq is gradually replacing DNA microarrays as a preferred method for transcriptome analysis because it has the advantages of profiling a complete transcriptome, providing a digital type datum (copy number of any transcript) and not relying on any known genomic sequence3. Here, we present a complete and detailed protocol to apply RNA-seq to profile transcriptomes in human pulmonary microvascular endothelial cells with or without thrombin treatment. This protocol is based on our recent published study entitled "RNA-seq Reveals Novel Transcriptome of Genes and Their Isoforms in Human Pulmonary Microvascular Endothelial Cells Treated with Thrombin,"4 in which we successfully performed the first complete transcriptome analysis of human pulmonary microvascular endothelial cells treated with thrombin using RNA-seq. It yielded unprecedented resources for further experimentation to gain insights into molecular mechanisms underlying thrombin-mediated endothelial dysfunction in the pathogenesis of inflammatory conditions, cancer, diabetes, and coronary heart disease, and provides potential new leads for therapeutic targets to those diseases. The descriptive text of this protocol is divided into four parts. The first part describes the treatment of human pulmonary microvascular endothelial cells with thrombin and RNA isolation, quality analysis and quantification. The second part describes library construction and sequencing. The third part describes the data analysis. The fourth part describes an RT-PCR validation assay. Representative results of several key steps are displayed. Useful tips or precautions to boost success in key steps are provided in the Discussion section. Although this protocol uses human pulmonary microvascular endothelial cells treated with thrombin, it can be generalized to profile transcriptomes in both mammalian and non-mammalian cells and in tissues treated with different stimuli or inhibitors, or to compare transcriptomes in cells or tissues between a healthy state and a disease state.
Genetics, Issue 72, Molecular Biology, Immunology, Medicine, Genomics, Proteins, RNA-seq, Next Generation DNA Sequencing, Transcriptome, Transcription, Thrombin, Endothelial cells, high-throughput, DNA, genomic DNA, RT-PCR, PCR
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Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR (qPCR) Arrays
Authors: Pauline Chugh, Kristen Tamburro, Dirk P Dittmer.
Institutions: University of North Carolina at Chapel Hill.
Quantitative real-time PCR (QPCR) has emerged as an accurate and valuable tool in profiling gene expression levels. One of its many advantages is a lower detection limit compared to other methods of gene expression profiling while using smaller amounts of input for each assay. Automated qPCR setup has improved this field by allowing for greater reproducibility. Its convenient and rapid setup allows for high-throughput experiments, enabling the profiling of many different genes simultaneously in each experiment. This method along with internal plate controls also reduces experimental variables common to other techniques. We recently developed a qPCR assay for profiling of pre-microRNAs (pre-miRNAs) using a set of 186 primer pairs. MicroRNAs have emerged as a novel class of small, non-coding RNAs with the ability to regulate many mRNA targets at the post-transcriptional level. These small RNAs are first transcribed by RNA polymerase II as a primary miRNA (pri-miRNA) transcript, which is then cleaved into the precursor miRNA (pre-miRNA). Pre-miRNAs are exported to the cytoplasm where Dicer cleaves the hairpin loop to yield mature miRNAs. Increases in miRNA levels can be observed at both the precursor and mature miRNA levels and profiling of both of these forms can be useful. There are several commercially available assays for mature miRNAs; however, their high cost may deter researchers from this profiling technique. Here, we discuss a cost-effective, reliable, SYBR-based qPCR method of profiling pre-miRNAs. Changes in pre-miRNA levels often reflect mature miRNA changes and can be a useful indicator of mature miRNA expression. However, simultaneous profiling of both pre-miRNAs and mature miRNAs may be optimal as they can contribute nonredundant information and provide insight into microRNA processing. Furthermore, the technique described here can be expanded to encompass the profiling of other library sets for specific pathways or pathogens.
Biochemistry, Issue 46, pre-microRNAs, qPCR, profiling, Tecan Freedom Evo, robot
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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
Authors: Silvia Paracchini, Anthony P. Monaco, Julian C. Knight.
Institutions: University of Oxford.
The number of significant genetic associations with common complex traits is constantly increasing. However, most of these associations have not been understood at molecular level. One of the mechanisms mediating the effect of DNA variants on phenotypes is gene expression, which has been shown to be particularly relevant for complex traits1. This method tests in a cellular context the effect of specific DNA sequences on gene expression. The principle is to measure the relative abundance of transcripts arising from the two alleles of a gene, analysing cells which carry one copy of the DNA sequences associated with disease (the risk variants)2,3. Therefore, the cells used for this method should meet two fundamental genotypic requirements: they have to be heterozygous both for DNA risk variants and for DNA markers, typically coding polymorphisms, which can distinguish transcripts based on their chromosomal origin (Figure 1). DNA risk variants and DNA markers do not need to have the same allele frequency but the phase (haplotypic) relationship of the genetic markers needs to be understood. It is also important to choose cell types which express the gene of interest. This protocol refers specifically to the procedure adopted to extract nucleic acids from fibroblasts but the method is equally applicable to other cells types including primary cells. DNA and RNA are extracted from the selected cell lines and cDNA is generated. DNA and cDNA are analysed with a primer extension assay, designed to target the coding DNA markers4. The primer extension assay is carried out using the MassARRAY (Sequenom)5 platform according to the manufacturer's specifications. Primer extension products are then analysed by matrix-assisted laser desorption/ionization time of-flight mass spectrometry (MALDI-TOF/MS). Because the selected markers are heterozygous they will generate two peaks on the MS profiles. The area of each peak is proportional to the transcript abundance and can be measured with a function of the MassARRAY Typer software to generate an allelic ratio (allele 1: allele 2) calculation. The allelic ratio obtained for cDNA is normalized using that measured from genomic DNA, where the allelic ratio is expected to be 1:1 to correct for technical artifacts. Markers with a normalised allelic ratio significantly different to 1 indicate that the amount of transcript generated from the two chromosomes in the same cell is different, suggesting that the DNA variants associated with the phenotype have an effect on gene expression. Experimental controls should be used to confirm the results.
Cellular Biology, Issue 45, Gene expression, regulatory variant, haplotype, association study, primer extension, MALDI-TOF mass spectrometry, single nucleotide polymorphism, allele-specific
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Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA
Authors: Ashwin Prakash, Jason Bechtel, Alexei Fedorov.
Institutions: University of Toledo Health Science Campus.
Non-coding genomic regions in complex eukaryotes, including intergenic areas, introns, and untranslated segments of exons, are profoundly non-random in their nucleotide composition and consist of a complex mosaic of sequence patterns. These patterns include so-called Mid-Range Inhomogeneity (MRI) regions -- sequences 30-10000 nucleotides in length that are enriched by a particular base or combination of bases (e.g. (G+T)-rich, purine-rich, etc.). MRI regions are associated with unusual (non-B-form) DNA structures that are often involved in regulation of gene expression, recombination, and other genetic processes (Fedorova & Fedorov 2010). The existence of a strong fixation bias within MRI regions against mutations that tend to reduce their sequence inhomogeneity additionally supports the functionality and importance of these genomic sequences (Prakash et al. 2009). Here we demonstrate a freely available Internet resource -- the Genomic MRI program package -- designed for computational analysis of genomic sequences in order to find and characterize various MRI patterns within them (Bechtel et al. 2008). This package also allows generation of randomized sequences with various properties and level of correspondence to the natural input DNA sequences. The main goal of this resource is to facilitate examination of vast regions of non-coding DNA that are still scarcely investigated and await thorough exploration and recognition.
Genetics, Issue 51, bioinformatics, computational biology, genomics, non-randomness, signals, gene regulation, DNA conformation
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Mosaic Zebrafish Transgenesis for Evaluating Enhancer Sequences
Authors: Erika Kague, Christopher Weber, Shannon Fisher.
Institutions: University of Pennsylvania .
The completion of the human genome sequence, along with that of many other species, has highlighted the challenge of ascribing specific function to non coding sequences. One prominent function carried out by the non coding fraction of the genome is to regulate gene transcription; however, there are no effective methods to broadly predict cis-regulatory elements from primary DNA sequence. We have developed an efficient protocol to functionally evaluate potential cis-regulatory elements through zebrafish transgenesis. Our approach offers significant advantages over cell-culture based techniques for developmentally important genes, since it provides information on spatial and temporal gene regulation. Conversely, it is faster and less expensive than similar experiments in transgenic mice, and we routinely apply it to sequences isolated from the human genome. Here we demonstrate our approach to selecting elements for testing based on sequence conservation and our protocol for cloning sequences and microinjecting them into zebrafish embryos.
Cellular Biology, Issue 41, zebrafish, transgenesis, microinjection, GFP, enhancers, transposon
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Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency
Authors: Stéphanie Beaucourt, Antonio V. Bordería, Lark L. Coffey, Nina F. Gnädig, Marta Sanz-Ramos, Yasnee Beeharry, Marco Vignuzzi.
Institutions: Institut Pasteur .
RNA viruses use RNA dependent RNA polymerases to replicate their genomes. The intrinsically high error rate of these enzymes is a large contributor to the generation of extreme population diversity that facilitates virus adaptation and evolution. Increasing evidence shows that the intrinsic error rates, and the resulting mutation frequencies, of RNA viruses can be modulated by subtle amino acid changes to the viral polymerase. Although biochemical assays exist for some viral RNA polymerases that permit quantitative measure of incorporation fidelity, here we describe a simple method of measuring mutation frequencies of RNA viruses that has proven to be as accurate as biochemical approaches in identifying fidelity altering mutations. The approach uses conventional virological and sequencing techniques that can be performed in most biology laboratories. Based on our experience with a number of different viruses, we have identified the key steps that must be optimized to increase the likelihood of isolating fidelity variants and generating data of statistical significance. The isolation and characterization of fidelity altering mutations can provide new insights into polymerase structure and function1-3. Furthermore, these fidelity variants can be useful tools in characterizing mechanisms of virus adaptation and evolution4-7.
Immunology, Issue 52, Polymerase fidelity, RNA virus, mutation frequency, mutagen, RNA polymerase, viral evolution
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Chromatin Isolation by RNA Purification (ChIRP)
Authors: Ci Chu, Jeffrey Quinn, Howard Y. Chang.
Institutions: Stanford University School of Medicine.
Long noncoding RNAs are key regulators of chromatin states for important biological processes such as dosage compensation, imprinting, and developmental gene expression 1,2,3,4,5,6,7. The recent discovery of thousands of lncRNAs in association with specific chromatin modification complexes, such as Polycomb Repressive Complex 2 (PRC2) that mediates histone H3 lysine 27 trimethylation (H3K27me3), suggests broad roles for numerous lncRNAs in managing chromatin states in a gene-specific fashion 8,9. While some lncRNAs are thought to work in cis on neighboring genes, other lncRNAs work in trans to regulate distantly located genes. For instance, Drosophila lncRNAs roX1 and roX2 bind numerous regions on the X chromosome of male cells, and are critical for dosage compensation 10,11. However, the exact locations of their binding sites are not known at high resolution. Similarly, human lncRNA HOTAIR can affect PRC2 occupancy on hundreds of genes genome-wide 3,12,13, but how specificity is achieved is unclear. LncRNAs can also serve as modular scaffolds to recruit the assembly of multiple protein complexes. The classic trans-acting RNA scaffold is the TERC RNA that serves as the template and scaffold for the telomerase complex 14; HOTAIR can also serve as a scaffold for PRC2 and a H3K4 demethylase complex 13. Prior studies mapping RNA occupancy at chromatin have revealed substantial insights 15,16, but only at a single gene locus at a time. The occupancy sites of most lncRNAs are not known, and the roles of lncRNAs in chromatin regulation have been mostly inferred from the indirect effects of lncRNA perturbation. Just as chromatin immunoprecipitation followed by microarray or deep sequencing (ChIP-chip or ChIP-seq, respectively) has greatly improved our understanding of protein-DNA interactions on a genomic scale, here we illustrate a recently published strategy to map long RNA occupancy genome-wide at high resolution 17. This method, Chromatin Isolation by RNA Purification (ChIRP) (Figure 1), is based on affinity capture of target lncRNA:chromatin complex by tiling antisense-oligos, which then generates a map of genomic binding sites at a resolution of several hundred bases with high sensitivity and low background. ChIRP is applicable to many lncRNAs because the design of affinity-probes is straightforward given the RNA sequence and requires no knowledge of the RNA's structure or functional domains.
Genetics, Issue 61, long noncoding RNA (lncRNA), genomics, chromatin binding, high-throughput sequencing, ChIRP
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Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
Authors: Alla Gagarinova, Mohan Babu, Jack Greenblatt, Andrew Emili.
Institutions: University of Toronto, University of Toronto, University of Regina.
Phenotypes are determined by a complex series of physical (e.g. protein-protein) and functional (e.g. gene-gene or genetic) interactions (GI)1. While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships2. Large-scale GI maps have been reported for eukaryotic organisms like yeast3-7, but GI information remains sparse for prokaryotes8, which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods9, 10. Here, we present the key steps required to perform quantitative E. coli Synthetic Genetic Array (eSGA) screening procedure on a genome-scale9, using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format. Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g. the 'Keio' collection11) and essential gene hypomorphic mutations (i.e. alleles conferring reduced protein expression, stability, or activity9, 12, 13) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system14. GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected9. Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process2. Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e. slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex2 as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred9.
Genetics, Issue 69, Molecular Biology, Medicine, Biochemistry, Microbiology, Aggravating, alleviating, conjugation, double mutant, Escherichia coli, genetic interaction, Gram-negative bacteria, homologous recombination, network, synthetic lethality or sickness, suppression
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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Authors: Haipeng Xing, Willey Liao, Yifan Mo, Michael Q. Zhang.
Institutions: Stony Brook University, Cold Spring Harbor Laboratory, University of Texas at Dallas.
ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2. Reliably identifying these regions was the focus of our work. Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5 to more rigorous statistical models, e.g. Hidden Markov Models (HMMs)6-8. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized. Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types. To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11 and epigenetic data12 to illustrate its usefulness.
Genetics, Issue 70, Bioinformatics, Genomics, Molecular Biology, Cellular Biology, Immunology, Chromatin immunoprecipitation, ChIP-Seq, histone modifications, segmentation, Bayesian, Hidden Markov Models, epigenetics
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A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
Authors: Gauthier Julie, Fadi F. Hamdan, Guy A. Rouleau.
Institutions: Universite de Montreal, Universite de Montreal, Universite de Montreal.
There are several lines of evidence supporting the role of de novo mutations as a mechanism for common disorders, such as autism and schizophrenia. First, the de novo mutation rate in humans is relatively high, so new mutations are generated at a high frequency in the population. However, de novo mutations have not been reported in most common diseases. Mutations in genes leading to severe diseases where there is a strong negative selection against the phenotype, such as lethality in embryonic stages or reduced reproductive fitness, will not be transmitted to multiple family members, and therefore will not be detected by linkage gene mapping or association studies. The observation of very high concordance in monozygotic twins and very low concordance in dizygotic twins also strongly supports the hypothesis that a significant fraction of cases may result from new mutations. Such is the case for diseases such as autism and schizophrenia. Second, despite reduced reproductive fitness1 and extremely variable environmental factors, the incidence of some diseases is maintained worldwide at a relatively high and constant rate. This is the case for autism and schizophrenia, with an incidence of approximately 1% worldwide. Mutational load can be thought of as a balance between selection for or against a deleterious mutation and its production by de novo mutation. Lower rates of reproduction constitute a negative selection factor that should reduce the number of mutant alleles in the population, ultimately leading to decreased disease prevalence. These selective pressures tend to be of different intensity in different environments. Nonetheless, these severe mental disorders have been maintained at a constant relatively high prevalence in the worldwide population across a wide range of cultures and countries despite a strong negative selection against them2. This is not what one would predict in diseases with reduced reproductive fitness, unless there was a high new mutation rate. Finally, the effects of paternal age: there is a significantly increased risk of the disease with increasing paternal age, which could result from the age related increase in paternal de novo mutations. This is the case for autism and schizophrenia3. The male-to-female ratio of mutation rate is estimated at about 4–6:1, presumably due to a higher number of germ-cell divisions with age in males. Therefore, one would predict that de novo mutations would more frequently come from males, particularly older males4. A high rate of new mutations may in part explain why genetic studies have so far failed to identify many genes predisposing to complexes diseases genes, such as autism and schizophrenia, and why diseases have been identified for a mere 3% of genes in the human genome. Identification for de novo mutations as a cause of a disease requires a targeted molecular approach, which includes studying parents and affected subjects. The process for determining if the genetic basis of a disease may result in part from de novo mutations and the molecular approach to establish this link will be illustrated, using autism and schizophrenia as examples.
Medicine, Issue 52, de novo mutation, complex diseases, schizophrenia, autism, rare variations, DNA sequencing
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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
Authors: Viktor Martyanov, Robert H. Gross.
Institutions: Dartmouth College.
SCOPE is an ensemble motif finder that uses three component algorithms in parallel to identify potential regulatory motifs by over-representation and motif position preference1. Each component algorithm is optimized to find a different kind of motif. By taking the best of these three approaches, SCOPE performs better than any single algorithm, even in the presence of noisy data1. In this article, we utilize a web version of SCOPE2 to examine genes that are involved in telomere maintenance. SCOPE has been incorporated into at least two other motif finding programs3,4 and has been used in other studies5-8. The three algorithms that comprise SCOPE are BEAM9, which finds non-degenerate motifs (ACCGGT), PRISM10, which finds degenerate motifs (ASCGWT), and SPACER11, which finds longer bipartite motifs (ACCnnnnnnnnGGT). These three algorithms have been optimized to find their corresponding type of motif. Together, they allow SCOPE to perform extremely well. Once a gene set has been analyzed and candidate motifs identified, SCOPE can look for other genes that contain the motif which, when added to the original set, will improve the motif score. This can occur through over-representation or motif position preference. Working with partial gene sets that have biologically verified transcription factor binding sites, SCOPE was able to identify most of the rest of the genes also regulated by the given transcription factor. Output from SCOPE shows candidate motifs, their significance, and other information both as a table and as a graphical motif map. FAQs and video tutorials are available at the SCOPE web site which also includes a "Sample Search" button that allows the user to perform a trial run. Scope has a very friendly user interface that enables novice users to access the algorithm's full power without having to become an expert in the bioinformatics of motif finding. As input, SCOPE can take a list of genes, or FASTA sequences. These can be entered in browser text fields, or read from a file. The output from SCOPE contains a list of all identified motifs with their scores, number of occurrences, fraction of genes containing the motif, and the algorithm used to identify the motif. For each motif, result details include a consensus representation of the motif, a sequence logo, a position weight matrix, and a list of instances for every motif occurrence (with exact positions and "strand" indicated). Results are returned in a browser window and also optionally by email. Previous papers describe the SCOPE algorithms in detail1,2,9-11.
Genetics, Issue 51, gene regulation, computational biology, algorithm, promoter sequence motif
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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