JoVE Visualize What is visualize?
Related JoVE Video
Pubmed Article
Lower-order effects adjustment in quantitative traits model-based multifactor dimensionality reduction.
Identifying gene-gene interactions or gene-environment interactions in studies of human complex diseases remains a big challenge in genetic epidemiology. An additional challenge, often forgotten, is to account for important lower-order genetic effects. These may hamper the identification of genuine epistasis. If lower-order genetic effects contribute to the genetic variance of a trait, identified statistical interactions may simply be due to a signal boost of these effects. In this study, we restrict attention to quantitative traits and bi-allelic SNPs as genetic markers. Moreover, our interaction study focuses on 2-way SNP-SNP interactions. Via simulations, we assess the performance of different corrective measures for lower-order genetic effects in Model-Based Multifactor Dimensionality Reduction epistasis detection, using additive and co-dominant coding schemes. Performance is evaluated in terms of power and familywise error rate. Our simulations indicate that empirical power estimates are reduced with correction of lower-order effects, likewise familywise error rates. Easy-to-use automatic SNP selection procedures, SNP selection based on "top" findings, or SNP selection based on p-value criterion for interesting main effects result in reduced power but also almost zero false positive rates. Always accounting for main effects in the SNP-SNP pair under investigation during Model-Based Multifactor Dimensionality Reduction analysis adequately controls false positive epistasis findings. This is particularly true when adopting a co-dominant corrective coding scheme. In conclusion, automatic search procedures to identify lower-order effects to correct for during epistasis screening should be avoided. The same is true for procedures that adjust for lower-order effects prior to Model-Based Multifactor Dimensionality Reduction and involve using residuals as the new trait. We advocate using "on-the-fly" lower-order effects adjusting when screening for SNP-SNP interactions using Model-Based Multifactor Dimensionality Reduction analysis.
Authors: Adam J. Adler, Graham B. Wiley, Patrick M. Gaffney.
Published: 11-19-2013
Genotyping variants in the human genome has proven to be an efficient method to identify genetic associations with phenotypes. The distribution of variants within families or populations can facilitate identification of the genetic factors of disease. Illumina's panel of genotyping BeadChips allows investigators to genotype thousands or millions of single nucleotide polymorphisms (SNPs) or to analyze other genomic variants, such as copy number, across a large number of DNA samples. These SNPs can be spread throughout the genome or targeted in specific regions in order to maximize potential discovery. The Infinium assay has been optimized to yield high-quality, accurate results quickly. With proper setup, a single technician can process from a few hundred to over a thousand DNA samples per week, depending on the type of array. This assay guides users through every step, starting with genomic DNA and ending with the scanning of the array. Using propriety reagents, samples are amplified, fragmented, precipitated, resuspended, hybridized to the chip, extended by a single base, stained, and scanned on either an iScan or Hi Scan high-resolution optical imaging system. One overnight step is required to amplify the DNA. The DNA is denatured and isothermally amplified by whole-genome amplification; therefore, no PCR is required. Samples are hybridized to the arrays during a second overnight step. By the third day, the samples are ready to be scanned and analyzed. Amplified DNA may be stockpiled in large quantities, allowing bead arrays to be processed every day of the week, thereby maximizing throughput.
25 Related JoVE Articles!
Play Button
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
Play Button
Collection and Extraction of Saliva DNA for Next Generation Sequencing
Authors: Michael R. Goode, Soo Yeon Cheong, Ning Li, William C. Ray, Christopher W. Bartlett.
Institutions: The Research Institute at Nationwide Children's Hospital, The Ohio State University, The Ohio State University.
The preferred source of DNA in human genetics research is blood, or cell lines derived from blood, as these sources yield large quantities of high quality DNA. However, DNA extraction from saliva can yield high quality DNA with little to no degradation/fragmentation that is suitable for a variety of DNA assays without the expense of a phlebotomist and can even be acquired through the mail. However, at present, no saliva DNA collection/extraction protocols for next generation sequencing have been presented in the literature. This protocol optimizes parameters of saliva collection/storage and DNA extraction to be of sufficient quality and quantity for DNA assays with the highest standards, including microarray genotyping and next generation sequencing.
Medicine, Issue 90, DNA collection, saliva, DNA extraction, Next generation sequencing, DNA purification, DNA
Play Button
From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Authors: Wen-Ting Tsai, Ahmed Hassan, Purbasha Sarkar, Joaquin Correa, Zoltan Metlagel, Danielle M. Jorgens, Manfred Auer.
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
Play Button
Lignin Down-regulation of Zea mays via dsRNAi and Klason Lignin Analysis
Authors: Sang-Hyuck Park, Rebecca Garlock Ong, Chuansheng Mei, Mariam Sticklen.
Institutions: University of Arizona, Michigan State University, The Institute for Advanced Learning and Research, Michigan State University.
To facilitate the use of lignocellulosic biomass as an alternative bioenergy resource, during biological conversion processes, a pretreatment step is needed to open up the structure of the plant cell wall, increasing the accessibility of the cell wall carbohydrates. Lignin, a polyphenolic material present in many cell wall types, is known to be a significant hindrance to enzyme access. Reduction in lignin content to a level that does not interfere with the structural integrity and defense system of the plant might be a valuable step to reduce the costs of bioethanol production. In this study, we have genetically down-regulated one of the lignin biosynthesis-related genes, cinnamoyl-CoA reductase (ZmCCR1) via a double stranded RNA interference technique. The ZmCCR1_RNAi construct was integrated into the maize genome using the particle bombardment method. Transgenic maize plants grew normally as compared to the wild-type control plants without interfering with biomass growth or defense mechanisms, with the exception of displaying of brown-coloration in transgenic plants leaf mid-ribs, husks, and stems. The microscopic analyses, in conjunction with the histological assay, revealed that the leaf sclerenchyma fibers were thinned but the structure and size of other major vascular system components was not altered. The lignin content in the transgenic maize was reduced by 7-8.7%, the crystalline cellulose content was increased in response to lignin reduction, and hemicelluloses remained unchanged. The analyses may indicate that carbon flow might have been shifted from lignin biosynthesis to cellulose biosynthesis. This article delineates the procedures used to down-regulate the lignin content in maize via RNAi technology, and the cell wall compositional analyses used to verify the effect of the modifications on the cell wall structure.
Bioengineering, Issue 89, Zea mays, cinnamoyl-CoA reductase (CCR), dsRNAi, Klason lignin measurement, cell wall carbohydrate analysis, gas chromatography (GC)
Play Button
Isolation and Quantification of Botulinum Neurotoxin From Complex Matrices Using the BoTest Matrix Assays
Authors: F. Mark Dunning, Timothy M. Piazza, Füsûn N. Zeytin, Ward C. Tucker.
Institutions: BioSentinel Inc., Madison, WI.
Accurate detection and quantification of botulinum neurotoxin (BoNT) in complex matrices is required for pharmaceutical, environmental, and food sample testing. Rapid BoNT testing of foodstuffs is needed during outbreak forensics, patient diagnosis, and food safety testing while accurate potency testing is required for BoNT-based drug product manufacturing and patient safety. The widely used mouse bioassay for BoNT testing is highly sensitive but lacks the precision and throughput needed for rapid and routine BoNT testing. Furthermore, the bioassay's use of animals has resulted in calls by drug product regulatory authorities and animal-rights proponents in the US and abroad to replace the mouse bioassay for BoNT testing. Several in vitro replacement assays have been developed that work well with purified BoNT in simple buffers, but most have not been shown to be applicable to testing in highly complex matrices. Here, a protocol for the detection of BoNT in complex matrices using the BoTest Matrix assays is presented. The assay consists of three parts: The first part involves preparation of the samples for testing, the second part is an immunoprecipitation step using anti-BoNT antibody-coated paramagnetic beads to purify BoNT from the matrix, and the third part quantifies the isolated BoNT's proteolytic activity using a fluorogenic reporter. The protocol is written for high throughput testing in 96-well plates using both liquid and solid matrices and requires about 2 hr of manual preparation with total assay times of 4-26 hr depending on the sample type, toxin load, and desired sensitivity. Data are presented for BoNT/A testing with phosphate-buffered saline, a drug product, culture supernatant, 2% milk, and fresh tomatoes and includes discussion of critical parameters for assay success.
Neuroscience, Issue 85, Botulinum, food testing, detection, quantification, complex matrices, BoTest Matrix, Clostridium, potency testing
Play Button
Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity
Authors: Angela J. Brandt, Gaston A. del Pino, Jean H. Burns.
Institutions: Case Western Reserve University.
Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as plant-soil feedbacks (PSF) have large effects on plant performance, and create environmental heterogeneity that depends on the community composition. Understanding the importance of PSF for plant community assembly necessitates understanding of the role of heterogeneity in PSF, in addition to mean PSF effects. Here, we describe a protocol for manipulating plant-induced soil heterogeneity. Two example experiments are presented: (1) a field experiment with a 6-patch grid of soils to measure plant population responses and (2) a greenhouse experiment with 2-patch soils to measure individual plant responses. Soils can be collected from the zone of root influence (soils from the rhizosphere and directly adjacent to the rhizosphere) of plants in the field from conspecific and heterospecific plant species. Replicate collections are used to avoid pseudoreplicating soil samples. These soils are then placed into separate patches for heterogeneous treatments or mixed for a homogenized treatment. Care should be taken to ensure that heterogeneous and homogenized treatments experience the same degree of soil disturbance. Plants can then be placed in these soil treatments to determine the effect of plant-induced soil heterogeneity on plant performance. We demonstrate that plant-induced heterogeneity results in different outcomes than predicted by traditional coexistence models, perhaps because of the dynamic nature of these feedbacks. Theory that incorporates environmental heterogeneity influenced by the assembling community and additional empirical work is needed to determine when heterogeneity intrinsic to the assembling community will result in different assembly outcomes compared with heterogeneity extrinsic to the community composition.
Environmental Sciences, Issue 85, Coexistence, community assembly, environmental drivers, plant-soil feedback, soil heterogeneity, soil microbial communities, soil patch
Play Button
Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat
Authors: Daniel E. Bradford, Katherine P. Magruder, Rachel A. Korhumel, John J. Curtin.
Institutions: University of Wisconsin-Madison.
Fear of certain threat and anxiety about uncertain threat are distinct emotions with unique behavioral, cognitive-attentional, and neuroanatomical components. Both anxiety and fear can be studied in the laboratory by measuring the potentiation of the startle reflex. The startle reflex is a defensive reflex that is potentiated when an organism is threatened and the need for defense is high. The startle reflex is assessed via electromyography (EMG) in the orbicularis oculi muscle elicited by brief, intense, bursts of acoustic white noise (i.e., “startle probes”). Startle potentiation is calculated as the increase in startle response magnitude during presentation of sets of visual threat cues that signal delivery of mild electric shock relative to sets of matched cues that signal the absence of shock (no-threat cues). In the Threat Probability Task, fear is measured via startle potentiation to high probability (100% cue-contingent shock; certain) threat cues whereas anxiety is measured via startle potentiation to low probability (20% cue-contingent shock; uncertain) threat cues. Measurement of startle potentiation during the Threat Probability Task provides an objective and easily implemented alternative to assessment of negative affect via self-report or other methods (e.g., neuroimaging) that may be inappropriate or impractical for some researchers. Startle potentiation has been studied rigorously in both animals (e.g., rodents, non-human primates) and humans which facilitates animal-to-human translational research. Startle potentiation during certain and uncertain threat provides an objective measure of negative affective and distinct emotional states (fear, anxiety) to use in research on psychopathology, substance use/abuse and broadly in affective science. As such, it has been used extensively by clinical scientists interested in psychopathology etiology and by affective scientists interested in individual differences in emotion.
Behavior, Issue 91, Startle; electromyography; shock; addiction; uncertainty; fear; anxiety; humans; psychophysiology; translational
Play Button
Metabolic Labeling and Membrane Fractionation for Comparative Proteomic Analysis of Arabidopsis thaliana Suspension Cell Cultures
Authors: Witold G. Szymanski, Sylwia Kierszniowska, Waltraud X. Schulze.
Institutions: Max Plank Institute of Molecular Plant Physiology, University of Hohenheim.
Plasma membrane microdomains are features based on the physical properties of the lipid and sterol environment and have particular roles in signaling processes. Extracting sterol-enriched membrane microdomains from plant cells for proteomic analysis is a difficult task mainly due to multiple preparation steps and sources for contaminations from other cellular compartments. The plasma membrane constitutes only about 5-20% of all the membranes in a plant cell, and therefore isolation of highly purified plasma membrane fraction is challenging. A frequently used method involves aqueous two-phase partitioning in polyethylene glycol and dextran, which yields plasma membrane vesicles with a purity of 95% 1. Sterol-rich membrane microdomains within the plasma membrane are insoluble upon treatment with cold nonionic detergents at alkaline pH. This detergent-resistant membrane fraction can be separated from the bulk plasma membrane by ultracentrifugation in a sucrose gradient 2. Subsequently, proteins can be extracted from the low density band of the sucrose gradient by methanol/chloroform precipitation. Extracted protein will then be trypsin digested, desalted and finally analyzed by LC-MS/MS. Our extraction protocol for sterol-rich microdomains is optimized for the preparation of clean detergent-resistant membrane fractions from Arabidopsis thaliana cell cultures. We use full metabolic labeling of Arabidopsis thaliana suspension cell cultures with K15NO3 as the only nitrogen source for quantitative comparative proteomic studies following biological treatment of interest 3. By mixing equal ratios of labeled and unlabeled cell cultures for joint protein extraction the influence of preparation steps on final quantitative result is kept at a minimum. Also loss of material during extraction will affect both control and treatment samples in the same way, and therefore the ratio of light and heave peptide will remain constant. In the proposed method either labeled or unlabeled cell culture undergoes a biological treatment, while the other serves as control 4.
Empty Value, Issue 79, Cellular Structures, Plants, Genetically Modified, Arabidopsis, Membrane Lipids, Intracellular Signaling Peptides and Proteins, Membrane Proteins, Isotope Labeling, Proteomics, plants, Arabidopsis thaliana, metabolic labeling, stable isotope labeling, suspension cell cultures, plasma membrane fractionation, two phase system, detergent resistant membranes (DRM), mass spectrometry, membrane microdomains, quantitative proteomics
Play Button
High Throughput Quantitative Expression Screening and Purification Applied to Recombinant Disulfide-rich Venom Proteins Produced in E. coli
Authors: Natalie J. Saez, Hervé Nozach, Marilyne Blemont, Renaud Vincentelli.
Institutions: Aix-Marseille Université, Commissariat à l'énergie atomique et aux énergies alternatives (CEA) Saclay, France.
Escherichia coli (E. coli) is the most widely used expression system for the production of recombinant proteins for structural and functional studies. However, purifying proteins is sometimes challenging since many proteins are expressed in an insoluble form. When working with difficult or multiple targets it is therefore recommended to use high throughput (HTP) protein expression screening on a small scale (1-4 ml cultures) to quickly identify conditions for soluble expression. To cope with the various structural genomics programs of the lab, a quantitative (within a range of 0.1-100 mg/L culture of recombinant protein) and HTP protein expression screening protocol was implemented and validated on thousands of proteins. The protocols were automated with the use of a liquid handling robot but can also be performed manually without specialized equipment. Disulfide-rich venom proteins are gaining increasing recognition for their potential as therapeutic drug leads. They can be highly potent and selective, but their complex disulfide bond networks make them challenging to produce. As a member of the FP7 European Venomics project (, our challenge is to develop successful production strategies with the aim of producing thousands of novel venom proteins for functional characterization. Aided by the redox properties of disulfide bond isomerase DsbC, we adapted our HTP production pipeline for the expression of oxidized, functional venom peptides in the E. coli cytoplasm. The protocols are also applicable to the production of diverse disulfide-rich proteins. Here we demonstrate our pipeline applied to the production of animal venom proteins. With the protocols described herein it is likely that soluble disulfide-rich proteins will be obtained in as little as a week. Even from a small scale, there is the potential to use the purified proteins for validating the oxidation state by mass spectrometry, for characterization in pilot studies, or for sensitive micro-assays.
Bioengineering, Issue 89, E. coli, expression, recombinant, high throughput (HTP), purification, auto-induction, immobilized metal affinity chromatography (IMAC), tobacco etch virus protease (TEV) cleavage, disulfide bond isomerase C (DsbC) fusion, disulfide bonds, animal venom proteins/peptides
Play Button
Genotyping of Plant and Animal Samples without Prior DNA Purification
Authors: Pak Y. Chum, Josh D. Haimes, Chas P. André, Pia K. Kuusisto, Melissa L. Kelley.
Institutions: Thermo Fisher Scientific.
The Direct PCR approach facilitates PCR amplification directly from small amounts of unpurified samples, and is demonstrated here for several plant and animal tissues (Figure 1). Direct PCR is based on specially engineered Thermo Scientific Phusion and Phire DNA Polymerases, which include a double-stranded DNA binding domain that gives them unique properties such as high tolerance of inhibitors. PCR-based target DNA detection has numerous applications in plant research, including plant genotype analysis and verification of transgenes. PCR from plant tissues traditionally involves an initial DNA isolation step, which may require expensive or toxic reagents. The process is time consuming and increases the risk of cross contamination1, 2. Conversely, by using Thermo Scientific Phire Plant Direct PCR Kit the target DNA can be easily detected, without prior DNA extraction. In the model demonstrated here, an example of derived cleaved amplified polymorphic sequence analysis (dCAPS)3,4 is performed directly from Arabidopsis plant leaves. dCAPS genotyping assays can be used to identify single nucleotide polymorphisms (SNPs) by SNP allele-specific restriction endonuclease digestion3. Some plant samples tend to be more challenging when using Direct PCR methods as they contain components that interfere with PCR, such as phenolic compounds. In these cases, an additional step to remove the compounds is traditionally required2,5. Here, this problem is overcome by using a quick and easy dilution protocol followed by Direct PCR amplification (Figure 1). Fifteen year-old oak leaves are used as a model for challenging plants as the specimen contains high amounts of phenolic compounds including tannins. Gene transfer into mice is broadly used to study the roles of genes in development, physiology and human disease. The use of these animals requires screening for the presence of the transgene, usually with PCR. Traditionally, this involves a time consuming DNA isolation step, during which DNA for PCR analysis is purified from ear, tail or toe tissues6,7. However, with the Thermo Scientific Phire Animal Tissue Direct PCR Kit transgenic mice can be genotyped without prior DNA purification. In this protocol transgenic mouse genotyping is achieved directly from mouse ear tissues, as demonstrated here for a challenging example where only one primer set is used for amplification of two fragments differing greatly in size.
Genetics, Issue 67, Molecular Biology, Plant Biology, Medicine, Direct PCR, DNA amplification, DNA purification, dCAPS, PCR-based target DNA detection, genotyping, Arabidopsis, oak, mouse tissues
Play Button
Technique and Considerations in the Use of 4x1 Ring High-definition Transcranial Direct Current Stimulation (HD-tDCS)
Authors: Mauricio F. Villamar, Magdalena Sarah Volz, Marom Bikson, Abhishek Datta, Alexandre F. DaSilva, Felipe Fregni.
Institutions: Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School, Pontifical Catholic University of Ecuador, Charité University Medicine Berlin, The City College of The City University of New York, University of Michigan.
High-definition transcranial direct current stimulation (HD-tDCS) has recently been developed as a noninvasive brain stimulation approach that increases the accuracy of current delivery to the brain by using arrays of smaller "high-definition" electrodes, instead of the larger pad-electrodes of conventional tDCS. Targeting is achieved by energizing electrodes placed in predetermined configurations. One of these is the 4x1-ring configuration. In this approach, a center ring electrode (anode or cathode) overlying the target cortical region is surrounded by four return electrodes, which help circumscribe the area of stimulation. Delivery of 4x1-ring HD-tDCS is capable of inducing significant neurophysiological and clinical effects in both healthy subjects and patients. Furthermore, its tolerability is supported by studies using intensities as high as 2.0 milliamperes for up to twenty minutes. Even though 4x1 HD-tDCS is simple to perform, correct electrode positioning is important in order to accurately stimulate target cortical regions and exert its neuromodulatory effects. The use of electrodes and hardware that have specifically been tested for HD-tDCS is critical for safety and tolerability. Given that most published studies on 4x1 HD-tDCS have targeted the primary motor cortex (M1), particularly for pain-related outcomes, the purpose of this article is to systematically describe its use for M1 stimulation, as well as the considerations to be taken for safe and effective stimulation. However, the methods outlined here can be adapted for other HD-tDCS configurations and cortical targets.
Medicine, Issue 77, Neurobiology, Neuroscience, Physiology, Anatomy, Biomedical Engineering, Biophysics, Neurophysiology, Nervous System Diseases, Diagnosis, Therapeutics, Anesthesia and Analgesia, Investigative Techniques, Equipment and Supplies, Mental Disorders, Transcranial direct current stimulation, tDCS, High-definition transcranial direct current stimulation, HD-tDCS, Electrical brain stimulation, Transcranial electrical stimulation (tES), Noninvasive Brain Stimulation, Neuromodulation, non-invasive, brain, stimulation, clinical techniques
Play Button
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
Play Button
Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles
Authors: Eva Wagner, Sören Brandenburg, Tobias Kohl, Stephan E. Lehnart.
Institutions: Heart Research Center Goettingen, University Medical Center Goettingen, German Center for Cardiovascular Research (DZHK) partner site Goettingen, University of Maryland School of Medicine.
In cardiac myocytes a complex network of membrane tubules - the transverse-axial tubule system (TATS) - controls deep intracellular signaling functions. While the outer surface membrane and associated TATS membrane components appear to be continuous, there are substantial differences in lipid and protein content. In ventricular myocytes (VMs), certain TATS components are highly abundant contributing to rectilinear tubule networks and regular branching 3D architectures. It is thought that peripheral TATS components propagate action potentials from the cell surface to thousands of remote intracellular sarcoendoplasmic reticulum (SER) membrane contact domains, thereby activating intracellular Ca2+ release units (CRUs). In contrast to VMs, the organization and functional role of TATS membranes in atrial myocytes (AMs) is significantly different and much less understood. Taken together, quantitative structural characterization of TATS membrane networks in healthy and diseased myocytes is an essential prerequisite towards better understanding of functional plasticity and pathophysiological reorganization. Here, we present a strategic combination of protocols for direct quantitative analysis of TATS membrane networks in living VMs and AMs. For this, we accompany primary cell isolations of mouse VMs and/or AMs with critical quality control steps and direct membrane staining protocols for fluorescence imaging of TATS membranes. Using an optimized workflow for confocal or superresolution TATS image processing, binarized and skeletonized data are generated for quantitative analysis of the TATS network and its components. Unlike previously published indirect regional aggregate image analysis strategies, our protocols enable direct characterization of specific components and derive complex physiological properties of TATS membrane networks in living myocytes with high throughput and open access software tools. In summary, the combined protocol strategy can be readily applied for quantitative TATS network studies during physiological myocyte adaptation or disease changes, comparison of different cardiac or skeletal muscle cell types, phenotyping of transgenic models, and pharmacological or therapeutic interventions.
Bioengineering, Issue 92, cardiac myocyte, atria, ventricle, heart, primary cell isolation, fluorescence microscopy, membrane tubule, transverse-axial tubule system, image analysis, image processing, T-tubule, collagenase
Play Button
Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Authors: C. R. Gallistel, Fuat Balci, David Freestone, Aaron Kheifets, Adam King.
Institutions: Rutgers University, Koç University, New York University, Fairfield University.
We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.
Behavior, Issue 84, genetics, cognitive mechanisms, behavioral screening, learning, memory, timing
Play Button
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
Play Button
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
Play Button
Investigating Protein-protein Interactions in Live Cells Using Bioluminescence Resonance Energy Transfer
Authors: Pelagia Deriziotis, Sarah A. Graham, Sara B. Estruch, Simon E. Fisher.
Institutions: Max Planck Institute for Psycholinguistics, Donders Institute for Brain, Cognition and Behaviour.
Assays based on Bioluminescence Resonance Energy Transfer (BRET) provide a sensitive and reliable means to monitor protein-protein interactions in live cells. BRET is the non-radiative transfer of energy from a 'donor' luciferase enzyme to an 'acceptor' fluorescent protein. In the most common configuration of this assay, the donor is Renilla reniformis luciferase and the acceptor is Yellow Fluorescent Protein (YFP). Because the efficiency of energy transfer is strongly distance-dependent, observation of the BRET phenomenon requires that the donor and acceptor be in close proximity. To test for an interaction between two proteins of interest in cultured mammalian cells, one protein is expressed as a fusion with luciferase and the second as a fusion with YFP. An interaction between the two proteins of interest may bring the donor and acceptor sufficiently close for energy transfer to occur. Compared to other techniques for investigating protein-protein interactions, the BRET assay is sensitive, requires little hands-on time and few reagents, and is able to detect interactions which are weak, transient, or dependent on the biochemical environment found within a live cell. It is therefore an ideal approach for confirming putative interactions suggested by yeast two-hybrid or mass spectrometry proteomics studies, and in addition it is well-suited for mapping interacting regions, assessing the effect of post-translational modifications on protein-protein interactions, and evaluating the impact of mutations identified in patient DNA.
Cellular Biology, Issue 87, Protein-protein interactions, Bioluminescence Resonance Energy Transfer, Live cell, Transfection, Luciferase, Yellow Fluorescent Protein, Mutations
Play Button
Training Synesthetic Letter-color Associations by Reading in Color
Authors: Olympia Colizoli, Jaap M. J. Murre, Romke Rouw.
Institutions: University of Amsterdam.
Synesthesia is a rare condition in which a stimulus from one modality automatically and consistently triggers unusual sensations in the same and/or other modalities. A relatively common and well-studied type is grapheme-color synesthesia, defined as the consistent experience of color when viewing, hearing and thinking about letters, words and numbers. We describe our method for investigating to what extent synesthetic associations between letters and colors can be learned by reading in color in nonsynesthetes. Reading in color is a special method for training associations in the sense that the associations are learned implicitly while the reader reads text as he or she normally would and it does not require explicit computer-directed training methods. In this protocol, participants are given specially prepared books to read in which four high-frequency letters are paired with four high-frequency colors. Participants receive unique sets of letter-color pairs based on their pre-existing preferences for colored letters. A modified Stroop task is administered before and after reading in order to test for learned letter-color associations and changes in brain activation. In addition to objective testing, a reading experience questionnaire is administered that is designed to probe for differences in subjective experience. A subset of questions may predict how well an individual learned the associations from reading in color. Importantly, we are not claiming that this method will cause each individual to develop grapheme-color synesthesia, only that it is possible for certain individuals to form letter-color associations by reading in color and these associations are similar in some aspects to those seen in developmental grapheme-color synesthetes. The method is quite flexible and can be used to investigate different aspects and outcomes of training synesthetic associations, including learning-induced changes in brain function and structure.
Behavior, Issue 84, synesthesia, training, learning, reading, vision, memory, cognition
Play Button
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Authors: Marcus Cheetham, Lutz Jancke.
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2 proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness (DHL) (Figure 1). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
Play Button
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Authors: Rangaraj M. Rangayyan, Shantanu Banik, J.E. Leo Desautels.
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion. Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
Play Button
Combining Behavioral Endocrinology and Experimental Economics: Testosterone and Social Decision Making
Authors: Christoph Eisenegger, Michael Naef.
Institutions: University of Zurich, Royal Holloway, University of London.
Behavioral endocrinological research in humans as well as in animals suggests that testosterone plays a key role in social interactions. Studies in rodents have shown a direct link between testosterone and aggressive behavior1 and folk wisdom adapts these findings to humans, suggesting that testosterone induces antisocial, egoistic or even aggressive behavior2. However, many researchers doubt a direct testosterone-aggression link in humans, arguing instead that testosterone is primarily involved in status-related behavior3,4. As a high status can also be achieved by aggressive and antisocial means it can be difficult to distinguish between anti-social and status seeking behavior. We therefore set up an experimental environment, in which status can only be achieved by prosocial means. In a double-blind and placebo-controlled experiment, we administered a single sublingual dose of 0.5 mg of testosterone (with a hydroxypropyl-β-cyclodextrin carrier) to 121 women and investigated their social interaction behavior in an economic bargaining paradigm. Real monetary incentives are at stake in this paradigm; every player A receives a certain amount of money and has to make an offer to another player B on how to share the money. If B accepts, she gets what was offered and player A keeps the rest. If B refuses the offer, nobody gets anything. A status seeking player A is expected to avoid being rejected by behaving in a prosocial way, i.e. by making higher offers. The results show that if expectations about the hormone are controlled for, testosterone administration leads to a significant increase in fair bargaining offers compared to placebo. The role of expectations is reflected in the fact that subjects who report that they believe to have received testosterone make lower offers than those who say they believe that they were treated with a placebo. These findings suggest that the experimental economics approach is sensitive for detecting neurobiological effects as subtle as those achieved by administration of hormones. Moreover, the findings point towards the importance of both psychosocial as well as neuroendocrine factors in determining the influence of testosterone on human social behavior.
Neuroscience, Issue 49, behavioral endocrinology, testosterone, social status, decision making
Play Button
Brain Imaging Investigation of the Neural Correlates of Emotion Regulation
Authors: Sanda Dolcos, Keen Sung, Ekaterina Denkova, Roger A. Dixon, Florin Dolcos.
Institutions: University of Illinois, Urbana-Champaign, University of Alberta, Edmonton, University of Alberta, Edmonton, University of Alberta, Edmonton, University of Alberta, Edmonton, University of Illinois, Urbana-Champaign, University of Illinois, Urbana-Champaign.
The ability to control/regulate emotions is an important coping mechanism in the face of emotionally stressful situations. Although significant progress has been made in understanding conscious/deliberate emotion regulation (ER), less is known about non-conscious/automatic ER and the associated neural correlates. This is in part due to the problems inherent in the unitary concepts of automatic and conscious processing1. Here, we present a protocol that allows investigation of the neural correlates of both deliberate and automatic ER using functional magnetic resonance imaging (fMRI). This protocol allows new avenues of inquiry into various aspects of ER. For instance, the experimental design allows manipulation of the goal to regulate emotion (conscious vs. non-conscious), as well as the intensity of the emotional challenge (high vs. low). Moreover, it allows investigation of both immediate (emotion perception) and long-term effects (emotional memory) of ER strategies on emotion processing. Therefore, this protocol may contribute to better understanding of the neural mechanisms of emotion regulation in healthy behaviour, and to gaining insight into possible causes of deficits in depression and anxiety disorders in which emotion dysregulation is often among the core debilitating features.
Neuroscience, Issue 54, Emotion Suppression, Automatic Emotion Control, Deliberate Emotion Control, Goal Induction, Neuroimaging
Play Button
Basics of Multivariate Analysis in Neuroimaging Data
Authors: Christian Georg Habeck.
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience
Play Button
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
Play Button
Pyrosequencing: A Simple Method for Accurate Genotyping
Authors: Cristi King, Tiffany Scott-Horton.
Institutions: Washington University in St. Louis.
Pharmacogenetic research benefits first-hand from the abundance of information provided by the completion of the Human Genome Project. With such a tremendous amount of data available comes an explosion of genotyping methods. Pyrosequencing(R) is one of the most thorough yet simple methods to date used to analyze polymorphisms. It also has the ability to identify tri-allelic, indels, short-repeat polymorphisms, along with determining allele percentages for methylation or pooled sample assessment. In addition, there is a standardized control sequence that provides internal quality control. This method has led to rapid and efficient single-nucleotide polymorphism evaluation including many clinically relevant polymorphisms. The technique and methodology of Pyrosequencing is explained.
Cellular Biology, Issue 11, Springer Protocols, Pyrosequencing, genotype, polymorphism, SNP, pharmacogenetics, pharmacogenomics, PCR
Copyright © JoVE 2006-2015. All Rights Reserved.
Policies | License Agreement | ISSN 1940-087X
simple hit counter

What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.