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Pubmed Article
Optimal scaling of digital transcriptomes.
PUBLISHED: 01-01-2013
Deep sequencing of transcriptomes has become an indispensable tool for biology, enabling expression levels for thousands of genes to be compared across multiple samples. Since transcript counts scale with sequencing depth, counts from different samples must be normalized to a common scale prior to comparison. We analyzed fifteen existing and novel algorithms for normalizing transcript counts, and evaluated the effectiveness of the resulting normalizations. For this purpose we defined two novel and mutually independent metrics: (1) the number of "uniform" genes (genes whose normalized expression levels have a sufficiently low coefficient of variation), and (2) low Spearman correlation between normalized expression profiles of gene pairs. We also define four novel algorithms, one of which explicitly maximizes the number of uniform genes, and compared the performance of all fifteen algorithms. The two most commonly used methods (scaling to a fixed total value, or equalizing the expression of certain housekeeping genes) yielded particularly poor results, surpassed even by normalization based on randomly selected gene sets. Conversely, seven of the algorithms approached what appears to be optimal normalization. Three of these algorithms rely on the identification of "ubiquitous" genes: genes expressed in all the samples studied, but never at very high or very low levels. We demonstrate that these include a "core" of genes expressed in many tissues in a mutually consistent pattern, which is suitable for use as an internal normalization guide. The new methods yield robustly normalized expression values, which is a prerequisite for the identification of differentially expressed and tissue-specific genes as potential biomarkers.
Authors: Dilyara Cheranova, Margaret Gibson, Suman Chaudhary, Li Qin Zhang, Daniel P. Heruth, Dmitry N. Grigoryev, Shui Qing Ye.
Published: 02-13-2013
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.
28 Related JoVE Articles!
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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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Expression Analysis of Mammalian Linker-histone Subtypes
Authors: Magdalena Medrzycki, Yunzhe Zhang, Kaixiang Cao, Yuhong Fan.
Institutions: Georgia Institute of Technology .
Linker histone H1 binds to the nucleosome core particle and linker DNA, facilitating folding of chromatin into higher order structure. H1 is essential for mammalian development1 and regulates specific gene expression in vivo2-4. Among the highly conserved histone proteins, the family of H1 linker histones is the most heterogeneous group. There are 11 H1 subtypes in mammals that are differentially regulated during development and in different cell types. These H1 subtypes include 5 somatic H1s (H1a-e), the replacement H10, 4 germ cell specific H1 subtypes, and H1x5. The presence of multiple H1 subtypes that differ in DNA binding affinity and chromatin compaction ability6-9 provides an additional level of modulation of chromatin function. Thus, quantitative expression analysis of individual H1 subtypes, both of mRNA and proteins, is necessary for better understanding of the regulation of higher order chromatin structure and function. Here we describe a set of assays designed for analyzing the expression levels of individual H1 subtypes (Figure 1). mRNA expression of various H1 variant genes is measured by a set of highly sensitive and quantitative reverse transcription-PCR (qRT-PCR) assays, which are faster, more accurate and require much less samples compared with the alternative approach of Northern blot analysis. Unlike most other cellular mRNA messages, mRNAs for most histone genes, including the majority of H1 genes, lack a long polyA tail, but contain a stem-loop structure at the 3' untranslated region (UTR)10. Therefore, cDNAs are prepared from total RNA by reverse transcription using random primers instead of oligo-dT primers. Realtime PCR assays with primers specific to each H1 subtypes (Table 1) are performed to obtain highly quantitative measurement of mRNA levels of individual H1 subtypes. Expression of housekeeping genes are analyzed as controls for normalization. The relative abundance of proteins of each H1 subtype and core histones is obtained through reverse phase high-performance liquid chromatography (RP-HPLC) analysis of total histones extracted from mammalian cells11-13. The HPLC method and elution conditions described here give optimum separations of mouse H1 subtypes. By quantifying the HPLC profile, we calculate the relative proportion of individual H1 subtypes within H1 family, as well as determine the H1 to nucleosome ratio in the cells.
Genetics, Issue 61, H1 linker histones, histone H1 subtypes, chromatin, RT-PCR, HPLC, gene expression
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Environmentally Induced Heritable Changes in Flax
Authors: Cory Johnson, Tiffanie Moss, Christopher Cullis.
Institutions: Case Western Reserve University.
Some flax varieties respond to nutrient stress by modifying their genome and these modifications can be inherited through many generations. Also associated with these genomic changes are heritable phenotypic variations 1,2. The flax variety Stormont Cirrus (Pl) when grown under three different nutrient conditions can either remain inducible (under the control conditions), or become stably modified to either the large or small genotroph by growth under high or low nutrient conditions respectively. The lines resulting from the initial growth under each of these conditions appear to grow better when grown under the same conditions in subsequent generations, notably the Pl line grows best under the control treatment indicating that the plants growing under both the high and low nutrients are under stress. One of the genomic changes that are associated with the induction of heritable changes is the appearance of an insertion element (LIS-1) 3, 4 while the plants are growing under the nutrient stress. With respect to this insertion event, the flax variety Stormont Cirrus (Pl) when grown under three different nutrient conditions can either remain unchanged (under the control conditions), have the insertion appear in all the plants (under low nutrients) and have this transmitted to the next generation, or have the insertion (or parts of it) appear but not be transmitted through generations (under high nutrients) 4. The frequency of the appearance of this insertion indicates that it is under positive selection, which is also consistent with the growth response in subsequent generations. Leaves or meristems harvested at various stages of growth are used for DNA and RNA isolation. The RNA is used to identify variation in expression associated with the various growth environments and/or t he presence/absence of LIS-1. The isolated DNA is used to identify those plants in which the insertion has occurred.
Plant Biology, Issue 47, Flax, genome variation, environmental stress, small RNAs, altered gene expression
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Inducing Plasticity of Astrocytic Receptors by Manipulation of Neuronal Firing Rates
Authors: Alison X. Xie, Kelli Lauderdale, Thomas Murphy, Timothy L. Myers, Todd A. Fiacco.
Institutions: University of California Riverside, University of California Riverside, University of California Riverside.
Close to two decades of research has established that astrocytes in situ and in vivo express numerous G protein-coupled receptors (GPCRs) that can be stimulated by neuronally-released transmitter. However, the ability of astrocytic receptors to exhibit plasticity in response to changes in neuronal activity has received little attention. Here we describe a model system that can be used to globally scale up or down astrocytic group I metabotropic glutamate receptors (mGluRs) in acute brain slices. Included are methods on how to prepare parasagittal hippocampal slices, construct chambers suitable for long-term slice incubation, bidirectionally manipulate neuronal action potential frequency, load astrocytes and astrocyte processes with fluorescent Ca2+ indicator, and measure changes in astrocytic Gq GPCR activity by recording spontaneous and evoked astrocyte Ca2+ events using confocal microscopy. In essence, a “calcium roadmap” is provided for how to measure plasticity of astrocytic Gq GPCRs. Applications of the technique for study of astrocytes are discussed. Having an understanding of how astrocytic receptor signaling is affected by changes in neuronal activity has important implications for both normal synaptic function as well as processes underlying neurological disorders and neurodegenerative disease.
Neuroscience, Issue 85, astrocyte, plasticity, mGluRs, neuronal Firing, electrophysiology, Gq GPCRs, Bolus-loading, calcium, microdomains, acute slices, Hippocampus, mouse
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RNA-Seq Analysis of Differential Gene Expression in Electroporated Chick Embryonic Spinal Cord
Authors: Felipe M. Vieceli, C.Y. Irene Yan.
Institutions: Universidade de São Paulo.
In ovo electroporation of the chick neural tube is a fast and inexpensive method for identification of gene function during neural development. Genome wide analysis of differentially expressed transcripts after such an experimental manipulation has the potential to uncover an almost complete picture of the downstream effects caused by the transfected construct. This work describes a simple method for comparing transcriptomes from samples of transfected embryonic spinal cords comprising all steps between electroporation and identification of differentially expressed transcripts. The first stage consists of guidelines for electroporation and instructions for dissection of transfected spinal cord halves from HH23 embryos in ribonuclease-free environment and extraction of high-quality RNA samples suitable for transcriptome sequencing. The next stage is that of bioinformatic analysis with general guidelines for filtering and comparison of RNA-Seq datasets in the Galaxy public server, which eliminates the need of a local computational structure for small to medium scale experiments. The representative results show that the dissection methods generate high quality RNA samples and that the transcriptomes obtained from two control samples are essentially the same, an important requirement for detection of differential expression genes in experimental samples. Furthermore, one example is provided where experimental overexpression of a DNA construct can be visually verified after comparison with control samples. The application of this method may be a powerful tool to facilitate new discoveries on the function of neural factors involved in spinal cord early development.
Developmental Biology, Issue 93, chicken embryo, in ovo electroporation, spinal cord, RNA-Seq, transcriptome profiling, Galaxy workflow
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Experimental Manipulation of Body Size to Estimate Morphological Scaling Relationships in Drosophila
Authors: R. Craig Stillwell, Ian Dworkin, Alexander W. Shingleton, W. Anthony Frankino.
Institutions: University of Houston, Michigan State University.
The scaling of body parts is a central feature of animal morphology1-7. Within species, morphological traits need to be correctly proportioned to the body for the organism to function; larger individuals typically have larger body parts and smaller individuals generally have smaller body parts, such that overall body shape is maintained across a range of adult body sizes. The requirement for correct proportions means that individuals within species usually exhibit low variation in relative trait size. In contrast, relative trait size can vary dramatically among species and is a primary mechanism by which morphological diversity is produced. Over a century of comparative work has established these intra- and interspecific patterns3,4. Perhaps the most widely used approach to describe this variation is to calculate the scaling relationship between the size of two morphological traits using the allometric equation y=bxα, where x and y are the size of the two traits, such as organ and body size8,9. This equation describes the within-group (e.g., species, population) scaling relationship between two traits as both vary in size. Log-transformation of this equation produces a simple linear equation, log(y) = log(b) + αlog(x) and log-log plots of the size of different traits among individuals of the same species typically reveal linear scaling with an intercept of log(b) and a slope of α, called the 'allometric coefficient'9,10. Morphological variation among groups is described by differences in scaling relationship intercepts or slopes for a given trait pair. Consequently, variation in the parameters of the allometric equation (b and α) elegantly describes the shape variation captured in the relationship between organ and body size within and among biological groups (see 11,12). Not all traits scale linearly with each other or with body size (e.g., 13,14) Hence, morphological scaling relationships are most informative when the data are taken from the full range of trait sizes. Here we describe how simple experimental manipulation of diet can be used to produce the full range of body size in insects. This permits an estimation of the full scaling relationship for any given pair of traits, allowing a complete description of how shape covaries with size and a robust comparison of scaling relationship parameters among biological groups. Although we focus on Drosophila, our methodology should be applicable to nearly any fully metamorphic insect.
Developmental Biology, Issue 56, Drosophila, allometry, morphology, body size, scaling, insect
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A Parasite Rescue and Transformation Assay for Antileishmanial Screening Against Intracellular Leishmania donovani Amastigotes in THP1 Human Acute Monocytic Leukemia Cell Line
Authors: Surendra K. Jain, Rajnish Sahu, Larry A. Walker, Babu L. Tekwani.
Institutions: University of Mississippi, University of Mississippi.
Leishmaniasis is one of the world's most neglected diseases, largely affecting the poorest of the poor, mainly in developing countries. Over 350 million people are considered at risk of contracting leishmaniasis, and approximately 2 million new cases occur yearly1. Leishmania donovani is the causative agent for visceral leishmaniasis (VL), the most fatal form of the disease. The choice of drugs available to treat leishmaniasis is limited 2;current treatments provide limited efficacy and many are toxic at therapeutic doses. In addition, most of the first line treatment drugs have already lost their utility due to increasing multiple drug resistance 3. The current pipeline of anti-leishmanial drugs is also severely depleted. Sustained efforts are needed to enrich a new anti-leishmanial drug discovery pipeline, and this endeavor relies on the availability of suitable in vitro screening models. In vitro promastigotes 4 and axenic amastigotes assays5 are primarily used for anti-leishmanial drug screening however, may not be appropriate due to significant cellular, physiological, biochemical and molecular differences in comparison to intracellular amastigotes. Assays with macrophage-amastigotes models are considered closest to the pathophysiological conditions of leishmaniasis, and are therefore the most appropriate for in vitro screening. Differentiated, non-dividing human acute monocytic leukemia cells (THP1) (make an attractive) alternative to isolated primary macrophages and can be used for assaying anti-leishmanial activity of different compounds against intracellular amastigotes. Here, we present a parasite-rescue and transformation assay with differentiated THP1 cells infected in vitro with Leishmania donovani for screening pure compounds and natural products extracts and determining the efficacy against the intracellular Leishmania amastigotes. The assay involves the following steps: (1) differentiation of THP1 cells to non-dividing macrophages, (2) infection of macrophages with L. donovani metacyclic promastigotes, (3) treatment of infected cells with test drugs, (4) controlled lysis of infected macrophages, (5) release/rescue of amastigotes and (6) transformation of live amastigotes to promastigotes. The assay was optimized using detergent treatment for controlled lysis of Leishmania-infected THP1 cells to achieve almost complete rescue of viable intracellular amastigotes with minimal effect on their ability to transform to promastigotes. Different macrophage:promastigotes ratios were tested to achieve maximum infection. Quantification of the infection was performed through transformation of live, rescued Leishmania amastigotes to promastigotes and evaluation of their growth by an alamarBlue fluorometric assay in 96-well microplates. This assay is comparable to the currently-used microscopic, transgenic reporter gene and digital-image analysis assays. This assay is robust and measures only the live intracellular amastigotes compared to reporter gene and image analysis assays, which may not differentiate between live and dead amastigotes. Also, the assay has been validated with a current panel of anti-leishmanial drugs and has been successfully applied to large-scale screening of pure compounds and a library of natural products fractions (Tekwani et al. unpublished).
Infection, Issue 70, Immunology, Infectious Diseases, Molecular Biology, Cellular Biology, Pharmacology, Leishmania donovani, Visceral Leishmaniasis, THP1 cells, Drug Screening, Amastigotes, Antileishmanial drug assay
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Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy
Authors: Víctor A. Lórenz-Fonfría, Joachim Heberle.
Institutions: Freie Universität Berlin.
Monitoring the dynamics of protonation and protein backbone conformation changes during the function of a protein is an essential step towards understanding its mechanism. Protonation and conformational changes affect the vibration pattern of amino acid side chains and of the peptide bond, respectively, both of which can be probed by infrared (IR) difference spectroscopy. For proteins whose function can be repetitively and reproducibly triggered by light, it is possible to obtain infrared difference spectra with (sub)microsecond resolution over a broad spectral range using the step-scan Fourier transform infrared technique. With ~102-103 repetitions of the photoreaction, the minimum number to complete a scan at reasonable spectral resolution and bandwidth, the noise level in the absorption difference spectra can be as low as ~10-4, sufficient to follow the kinetics of protonation changes from a single amino acid. Lower noise levels can be accomplished by more data averaging and/or mathematical processing. The amount of protein required for optimal results is between 5-100 µg, depending on the sampling technique used. Regarding additional requirements, the protein needs to be first concentrated in a low ionic strength buffer and then dried to form a film. The protein film is hydrated prior to the experiment, either with little droplets of water or under controlled atmospheric humidity. The attained hydration level (g of water / g of protein) is gauged from an IR absorption spectrum. To showcase the technique, we studied the photocycle of the light-driven proton-pump bacteriorhodopsin in its native purple membrane environment, and of the light-gated ion channel channelrhodopsin-2 solubilized in detergent.
Biophysics, Issue 88, bacteriorhodopsin, channelrhodopsin, attenuated total reflection, proton transfer, protein dynamics, infrared spectroscopy, time-resolved spectroscopy, step-scan, membrane proteins, singular value decomposition
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High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
Authors: Laura Ekstrand, Nikolaus Karpinsky, Yajun Wang, Song Zhang.
Institutions: Iowa State University.
Digital fringe projection (DFP) techniques provide dense 3D measurements of dynamically changing surfaces. Like the human eyes and brain, DFP uses triangulation between matching points in two views of the same scene at different angles to compute depth. However, unlike a stereo-based method, DFP uses a digital video projector to replace one of the cameras1. The projector rapidly projects a known sinusoidal pattern onto the subject, and the surface of the subject distorts these patterns in the camera’s field of view. Three distorted patterns (fringe images) from the camera can be used to compute the depth using triangulation. Unlike other 3D measurement methods, DFP techniques lead to systems that tend to be faster, lower in equipment cost, more flexible, and easier to develop. DFP systems can also achieve the same measurement resolution as the camera. For this reason, DFP and other digital structured light techniques have recently been the focus of intense research (as summarized in1-5). Taking advantage of DFP, the graphics processing unit, and optimized algorithms, we have developed a system capable of 30 Hz 3D video data acquisition, reconstruction, and display for over 300,000 measurement points per frame6,7. Binary defocusing DFP methods can achieve even greater speeds8. Diverse applications can benefit from DFP techniques. Our collaborators have used our systems for facial function analysis9, facial animation10, cardiac mechanics studies11, and fluid surface measurements, but many other potential applications exist. This video will teach the fundamentals of DFP techniques and illustrate the design and operation of a binary defocusing DFP system.
Physics, Issue 82, Structured light, Fringe projection, 3D imaging, 3D scanning, 3D video, binary defocusing, phase-shifting
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Longitudinal Measurement of Extracellular Matrix Rigidity in 3D Tumor Models Using Particle-tracking Microrheology
Authors: Dustin P. Jones, William Hanna, Hamid El-Hamidi, Jonathan P. Celli.
Institutions: University of Massachusetts Boston.
The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and modified as part of a set of complex, two-way mechanosensitive interactions. While the development of biologically-relevant 3D tumor models have facilitated mechanistic studies on the impact of matrix rheology on tumor growth, the inverse problem of mapping changes in the mechanical environment induced by tumors remains challenging. Here, we describe the implementation of particle-tracking microrheology (PTM) in conjunction with 3D models of pancreatic cancer as part of a robust and viable approach for longitudinally monitoring physical changes in the tumor microenvironment, in situ. The methodology described here integrates a system of preparing in vitro 3D models embedded in a model extracellular matrix (ECM) scaffold of Type I collagen with fluorescently labeled probes uniformly distributed for position- and time-dependent microrheology measurements throughout the specimen. In vitro tumors are plated and probed in parallel conditions using multiwell imaging plates. Drawing on established methods, videos of tracer probe movements are transformed via the Generalized Stokes Einstein Relation (GSER) to report the complex frequency-dependent viscoelastic shear modulus, G*(ω). Because this approach is imaging-based, mechanical characterization is also mapped onto large transmitted-light spatial fields to simultaneously report qualitative changes in 3D tumor size and phenotype. Representative results showing contrasting mechanical response in sub-regions associated with localized invasion-induced matrix degradation as well as system calibration, validation data are presented. Undesirable outcomes from common experimental errors and troubleshooting of these issues are also presented. The 96-well 3D culture plating format implemented in this protocol is conducive to correlation of microrheology measurements with therapeutic screening assays or molecular imaging to gain new insights into impact of treatments or biochemical stimuli on the mechanical microenvironment.
Bioengineering, Issue 88, viscoelasticity, mechanobiology, extracellular matrix (ECM), matrix remodeling, 3D tumor models, tumor microenvironment, stroma, matrix metalloprotease (MMP), epithelial-mesenchymal transition (EMT)
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One-channel Cell-attached Patch-clamp Recording
Authors: Bruce A. Maki, Kirstie A. Cummings, Meaghan A. Paganelli, Swetha E. Murthy, Gabriela K. Popescu.
Institutions: University at Buffalo, SUNY, University at Buffalo, SUNY, The Scripps Research Institute, University at Buffalo, SUNY.
Ion channel proteins are universal devices for fast communication across biological membranes. The temporal signature of the ionic flux they generate depends on properties intrinsic to each channel protein as well as the mechanism by which it is generated and controlled and represents an important area of current research. Information about the operational dynamics of ion channel proteins can be obtained by observing long stretches of current produced by a single molecule. Described here is a protocol for obtaining one-channel cell-attached patch-clamp current recordings for a ligand gated ion channel, the NMDA receptor, expressed heterologously in HEK293 cells or natively in cortical neurons. Also provided are instructions on how to adapt the method to other ion channels of interest by presenting the example of the mechano-sensitive channel PIEZO1. This method can provide data regarding the channel’s conductance properties and the temporal sequence of open-closed conformations that make up the channel’s activation mechanism, thus helping to understand their functions in health and disease.
Neuroscience, Issue 88, biophysics, ion channels, single-channel recording, NMDA receptors, gating, electrophysiology, patch-clamp, kinetic analysis
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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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Optimization and Utilization of Agrobacterium-mediated Transient Protein Production in Nicotiana
Authors: Moneim Shamloul, Jason Trusa, Vadim Mett, Vidadi Yusibov.
Institutions: Fraunhofer USA Center for Molecular Biotechnology.
Agrobacterium-mediated transient protein production in plants is a promising approach to produce vaccine antigens and therapeutic proteins within a short period of time. However, this technology is only just beginning to be applied to large-scale production as many technological obstacles to scale up are now being overcome. Here, we demonstrate a simple and reproducible method for industrial-scale transient protein production based on vacuum infiltration of Nicotiana plants with Agrobacteria carrying launch vectors. Optimization of Agrobacterium cultivation in AB medium allows direct dilution of the bacterial culture in Milli-Q water, simplifying the infiltration process. Among three tested species of Nicotiana, N. excelsiana (N. benthamiana × N. excelsior) was selected as the most promising host due to the ease of infiltration, high level of reporter protein production, and about two-fold higher biomass production under controlled environmental conditions. Induction of Agrobacterium harboring pBID4-GFP (Tobacco mosaic virus-based) using chemicals such as acetosyringone and monosaccharide had no effect on the protein production level. Infiltrating plant under 50 to 100 mbar for 30 or 60 sec resulted in about 95% infiltration of plant leaf tissues. Infiltration with Agrobacterium laboratory strain GV3101 showed the highest protein production compared to Agrobacteria laboratory strains LBA4404 and C58C1 and wild-type Agrobacteria strains at6, at10, at77 and A4. Co-expression of a viral RNA silencing suppressor, p23 or p19, in N. benthamiana resulted in earlier accumulation and increased production (15-25%) of target protein (influenza virus hemagglutinin).
Plant Biology, Issue 86, Agroinfiltration, Nicotiana benthamiana, transient protein production, plant-based expression, viral vector, Agrobacteria
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Authors: Hans-Peter Müller, Jan Kassubek.
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
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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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Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
Authors: Shan Zong, Shuyun Deng, Kenian Chen, Jia Qian Wu.
Institutions: The University of Texas Graduate School of Biomedical Sciences at Houston.
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.
Genetics, Issue 93, EML Cells, Self-renewal, Differentiation, Hematopoietic precursor cell, RNA-Sequencing, Data analysis
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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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Affinity-based Isolation of Tagged Nuclei from Drosophila Tissues for Gene Expression Analysis
Authors: Jingqun Ma, Vikki Marie Weake.
Institutions: Purdue University.
Drosophila melanogaster embryonic and larval tissues often contain a highly heterogeneous mixture of cell types, which can complicate the analysis of gene expression in these tissues. Thus, to analyze cell-specific gene expression profiles from Drosophila tissues, it may be necessary to isolate specific cell types with high purity and at sufficient yields for downstream applications such as transcriptional profiling and chromatin immunoprecipitation. However, the irregular cellular morphology in tissues such as the central nervous system, coupled with the rare population of specific cell types in these tissues, can pose challenges for traditional methods of cell isolation such as laser microdissection and fluorescence-activated cell sorting (FACS). Here, an alternative approach to characterizing cell-specific gene expression profiles using affinity-based isolation of tagged nuclei, rather than whole cells, is described. Nuclei in the specific cell type of interest are genetically labeled with a nuclear envelope-localized EGFP tag using the Gal4/UAS binary expression system. These EGFP-tagged nuclei can be isolated using antibodies against GFP that are coupled to magnetic beads. The approach described in this protocol enables consistent isolation of nuclei from specific cell types in the Drosophila larval central nervous system at high purity and at sufficient levels for expression analysis, even when these cell types comprise less than 2% of the total cell population in the tissue. This approach can be used to isolate nuclei from a wide variety of Drosophila embryonic and larval cell types using specific Gal4 drivers, and may be useful for isolating nuclei from cell types that are not suitable for FACS or laser microdissection.
Biochemistry, Issue 85, Gene Expression, nuclei isolation, Drosophila, KASH, GFP, cell-type specific
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Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
Authors: Johannes Felix Buyel, Rainer Fischer.
Institutions: RWTH Aachen University, Fraunhofer Gesellschaft.
Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the additional advantage of short development and production times, but expression levels can vary significantly between batches thus giving rise to regulatory concerns in the context of good manufacturing practice. We used a design of experiments (DoE) approach to determine the impact of major factors such as regulatory elements in the expression construct, plant growth and development parameters, and the incubation conditions during expression, on the variability of expression between batches. We tested plants expressing a model anti-HIV monoclonal antibody (2G12) and a fluorescent marker protein (DsRed). We discuss the rationale for selecting certain properties of the model and identify its potential limitations. The general approach can easily be transferred to other problems because the principles of the model are broadly applicable: knowledge-based parameter selection, complexity reduction by splitting the initial problem into smaller modules, software-guided setup of optimal experiment combinations and step-wise design augmentation. Therefore, the methodology is not only useful for characterizing protein expression in plants but also for the investigation of other complex systems lacking a mechanistic description. The predictive equations describing the interconnectivity between parameters can be used to establish mechanistic models for other complex systems.
Bioengineering, Issue 83, design of experiments (DoE), transient protein expression, plant-derived biopharmaceuticals, promoter, 5'UTR, fluorescent reporter protein, model building, incubation conditions, monoclonal antibody
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Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Authors: Helen H Won, Sasinya N Scott, A. Rose Brannon, Ronak H Shah, Michael F Berger.
Institutions: Memorial Sloan-Kettering Cancer Center, Memorial Sloan-Kettering Cancer Center.
Efforts to detect and investigate key oncogenic mutations have proven valuable to facilitate the appropriate treatment for cancer patients. The establishment of high-throughput, massively parallel "next-generation" sequencing has aided the discovery of many such mutations. To enhance the clinical and translational utility of this technology, platforms must be high-throughput, cost-effective, and compatible with formalin-fixed paraffin embedded (FFPE) tissue samples that may yield small amounts of degraded or damaged DNA. Here, we describe the preparation of barcoded and multiplexed DNA libraries followed by hybridization-based capture of targeted exons for the detection of cancer-associated mutations in fresh frozen and FFPE tumors by massively parallel sequencing. This method enables the identification of sequence mutations, copy number alterations, and select structural rearrangements involving all targeted genes. Targeted exon sequencing offers the benefits of high throughput, low cost, and deep sequence coverage, thus conferring high sensitivity for detecting low frequency mutations.
Molecular Biology, Issue 80, Molecular Diagnostic Techniques, High-Throughput Nucleotide Sequencing, Genetics, Neoplasms, Diagnosis, Massively parallel sequencing, targeted exon sequencing, hybridization capture, cancer, FFPE, DNA mutations
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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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Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae
Authors: Melissa N. Patterson, Patrick H. Maxwell.
Institutions: Rensselaer Polytechnic Institute.
Saccharomyces cerevisiae has been an excellent model system for examining mechanisms and consequences of genome instability. Information gained from this yeast model is relevant to many organisms, including humans, since DNA repair and DNA damage response factors are well conserved across diverse species. However, S. cerevisiae has not yet been used to fully address whether the rate of accumulating mutations changes with increasing replicative (mitotic) age due to technical constraints. For instance, measurements of yeast replicative lifespan through micromanipulation involve very small populations of cells, which prohibit detection of rare mutations. Genetic methods to enrich for mother cells in populations by inducing death of daughter cells have been developed, but population sizes are still limited by the frequency with which random mutations that compromise the selection systems occur. The current protocol takes advantage of magnetic sorting of surface-labeled yeast mother cells to obtain large enough populations of aging mother cells to quantify rare mutations through phenotypic selections. Mutation rates, measured through fluctuation tests, and mutation frequencies are first established for young cells and used to predict the frequency of mutations in mother cells of various replicative ages. Mutation frequencies are then determined for sorted mother cells, and the age of the mother cells is determined using flow cytometry by staining with a fluorescent reagent that detects bud scars formed on their cell surfaces during cell division. Comparison of predicted mutation frequencies based on the number of cell divisions to the frequencies experimentally observed for mother cells of a given replicative age can then identify whether there are age-related changes in the rate of accumulating mutations. Variations of this basic protocol provide the means to investigate the influence of alterations in specific gene functions or specific environmental conditions on mutation accumulation to address mechanisms underlying genome instability during replicative aging.
Microbiology, Issue 92, Aging, mutations, genome instability, Saccharomyces cerevisiae, fluctuation test, magnetic sorting, mother cell, replicative aging
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Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform
Authors: Samuel M. Peterson, Jennifer L. Freeman.
Institutions: Purdue University.
Gene microarray technology permits quantitative measurement and gene expression profiling of transcript levels on a genome-wide basis. Gene microarray technology is used in numerous biological disciplines in a variety of applications including global gene expression analysis in relation to developmental stage, to a disease state, and in toxic responses. Herein, we include a demonstration of global gene expression analysis using a comprehensive zebrafish-specific oligonucleotide microarray platform. The zebrafish expression microarray platform contains 385,000 probes, 60 base pairs in length, interrogating 37,157 targets with up to 12 probes per target. For this platform, all cDNA and genomic information available for the zebrafish was collected from various genomic databases including Ensembl (, VEGA (, UCSC (, and ZFIN ( As a result this expression array provides complete coverage of the current zebrafish transcriptome. The zebrafish expression microarray was printed by Roche NimbleGen (Madison, WI). This technical demonstration includes the fluorescent labeling of a cDNA product, hybridization of the labeled cDNA product to the microarray platform, and array scanning for signal acquisition using the one color analysis strategy.
Developmental Biology, Issue 30, zebrafish, microarray, genomics, gene expression, RNA, oligonucleotide
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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 an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells
Authors: Adam M. McCoy, Claudia Litterst, Michelle L. Collins, Luis A. Ugozzoli.
Institutions: Bio-Rad Laboratories.
The use of siRNA mediated gene knockdown is continuing to be an important tool in studies of gene expression. siRNA studies are being conducted not only to study the effects of downregulating single genes, but also to interrogate signaling pathways and other complex interaction networks. These pathway analyses require both the use of relevant cellular models and methods that cause less perturbation to the cellular physiology. Electroporation is increasingly being used as an effective way to introduce siRNA and other nucleic acids into difficult to transfect cell lines and primary cells without altering the signaling pathway under investigation. There are multiple critical steps to a successful siRNA experiment, and there are ways to simplify the work while improving the data quality at several experimental stages. To help you get started with your siRNA mediated gene knockdown project, we will demonstrate how to perform a pathway study complete from collecting and counting the cells prior to electroporation through post transfection real-time PCR gene expression analysis. The following study investigates the role of the transcriptional activator STAT6 in IL-4 dependent gene expression of CCL17 in a Burkitt lymphoma cell line (Namalwa). The techniques demonstrated are useful for a wide range of siRNA-based experiments on both adherent and suspension cells. We will also show how to streamline cell counting with the TC10 automated cell counter, how to electroporate multiple samples simultaneously using the MXcell electroporation system, and how to simultaneously assess RNA quality and quantity with the Experion automated electrophoresis system.
Cellular Biology, Issue 38, Cell Counting, Gene Silencing, siRNA, Namalwa Cells, IL4, Gene Expression, Electroporation, Real Time PCR
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Targeted Expression of GFP in the Hair Follicle Using Ex Vivo Viral Transduction
Authors: Robert M. Hoffman, Lingna Li.
Institutions: AntiCancer, Inc..
There are many cell types in the hair follicle, including hair matrix cells which form the hair shaft and stem cells which can initiate the hair shaft during early anagen, the growth phase of the hair cycle, as well as pluripotent stem cells that play a role in hair follicle growth but have the potential to differentiate to non-follicle cells such as neurons. These properties of the hair follicle are discussed. The various cell types of the hair follicle are potential targets for gene therapy. Gene delivery system for the hair follicle using viral vectors or liposomes for gene targeting to the various cell types in the hair follicle and the results obtained are also discussed.
Cellular Biology, Issue 13, Springer Protocols, hair follicles, liposomes, adenovirus, genes, stem cells
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Building a Better Mosquito: Identifying the Genes Enabling Malaria and Dengue Fever Resistance in A. gambiae and A. aegypti Mosquitoes
Authors: George Dimopoulos.
Institutions: Johns Hopkins University.
In this interview, George Dimopoulos focuses on the physiological mechanisms used by mosquitoes to combat Plasmodium falciparum and dengue virus infections. Explanation is given for how key refractory genes, those genes conferring resistance to vector pathogens, are identified in the mosquito and how this knowledge can be used to generate transgenic mosquitoes that are unable to carry the malaria parasite or dengue virus.
Cellular Biology, Issue 5, Translational Research, mosquito, malaria, virus, dengue, genetics, injection, RNAi, transgenesis, transgenic
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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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