Accessing genetic information with high-density DNA arrays

Periodic emission of droplets from an oscillating electrified meniscus of a low-viscosity, highly conductive liquid

The generation of identical droplets of controllable size in the micrometer range is a problem of much interest owing to the numerous technological applications of such droplets. This work reports an investigation of the regime of periodic emission of droplets from an electrified oscillating meniscus of a liquid of low viscosity and high electrical conductivity attached to the end of a capillary tube, which may be used to produce droplets more than ten times smaller than the diameter of the tube. To attain this periodic microdripping regime, termed axial spray mode II by Juraschek and Röllgen [R. Juraschek and F. W. Röllgen, Int. J. Mass Spectrom. 177, 1 (1998)], liquid is continuously supplied through the tube at a given constant flow rate, while a dc voltage is applied between the tube and a nearby counter electrode. The resulting electric field induces a stress at the surface of the liquid that stretches the meniscus until, in certain ranges of voltage and flow rate, it develops a ligament that eventually detaches, forming a single droplet, in a process that repeats itself periodically. While it is being stretched, the ligament develops a conical tip that emits ultrafine droplets, but the total mass emitted is practically contained in the main droplet. In the parametrical domain studied, we find that the process depends on two main dimensionless parameters, the flow rate nondimensionalized with the diameter of the tube and the capillary time, q, and the electric Bond number B(E), which is a nondimensional measure of the square of the applied voltage. The meniscus oscillation frequency made nondimensional with the capillary time, f, is of order unity for very small flow rates and tends to decrease as the inverse of the square root of q for larger values of this parameter. The product of the meniscus mean volume times the oscillation frequency is nearly constant. The characteristic length and width of the liquid ligament immediately before its detachment approximately scale as powers of the flow rate and depend only weakly on the applied voltage. The diameter of the main droplets nondimensionalized with the diameter of the tube satisfies d(d)≈(6/π)(1/3)(q/f)(1/3), from mass conservation, while the electric charge of these droplets is about 1/4 of the Rayleigh charge. At the minimum flow rate compatible with the periodic regimen, the dimensionless diameter of the droplets is smaller than one-tenth, which presents a way to use electrohydrodynamic atomization to generate droplets of highly conducting liquids in the micron-size range, in marked contrast with the cone-jet electrospray whose typical droplet size is in the nanometric regime for these liquids. In contrast with other microdripping regimes where the mass is emitted upon the periodic formation of a narrow capillary jet, the present regime gives one single droplet per oscillation, except for the almost massless fine aerosol emitted in the form of an electrospray.

Terahertz spectroscopy of oligonucleotides in aqueous solutions

A terahertz (THz) spectroscopic study is carried out to analyze DNA mutations in a label-free manner. Three newly designed liquid sample cells are considered and the best is selected as the sample carrier for THz transmission spectroscopic analyses. Discrimination based on spectral signatures of single-base mutations on single-stranded 20 nt oligonucleotides has been shown possible experimentally. The results clearly attest the ability of this promising approach for label-free analyses of single-base mutations of DNA molecules. This study has demonstrated that the THz spectroscopic technology can be considered as a potential diagnostic tool for investigating molecular reactions, such as DNA mutations.

A controlled microfluidic electrochemical lab-on-a-chip for label-free diffusion-restricted DNA hybridization analysis

Lab-on-a-chip (LOC) devices for electrochemical analysis of DNA hybridization events offer a technology for real-time and label-free assessment of biomarkers at the point-of-care. Here, we present a microfluidic LOC, with 3 × 3 arrayed electrochemical sensors for the analysis of DNA hybridization events. A new dual layer microfluidic valved manipulation system is integrated providing controlled and automated capabilities for high throughput analysis. This feature improves the repeatability, accuracy, and overall sensing performance (Fig. 1). The electrochemical activity of the fabricated microfluidic device is validated and demonstrated repeatable and reversible Nernstian characteristics. System design required detailed analysis of energy storage and dissipation as our sensing modeling involves diffusion-related electrochemical impedance spectroscopy. The effect of DNA hybridization on the calculated charge transfer resistance and the diffusional resistance components is evaluated. We demonstrate a specific device with an average cross-reactivity value of 27.5%. The device yields semilogarithmic dose response and enables a theoretical detection limit of 1 nM of complementary ssDNA target. This limit is lower than our previously reported non-valved device by 74% due to on-chip valve integration providing controlled and accurate assay capabilities.

A microfluidic-based electrochemical biochip for label-free DNA hybridization analysis

Miniaturization of analytical benchtop procedures into the micro-scale provides significant advantages in regards to reaction time, cost, and integration of pre-processing steps. Utilizing these devices towards the analysis of DNA hybridization events is important because it offers a technology for real time assessment of biomarkers at the point-of-care for various diseases. However, when the device footprint decreases the dominance of various physical phenomena increases. These phenomena influence the fabrication precision and operation reliability of the device. Therefore, there is a great need to accurately fabricate and operate these devices in a reproducible manner in order to improve the overall performance. Here, we describe the protocols and the methods used for the fabrication and the operation of a microfluidic-based electrochemical biochip for accurate analysis of DNA hybridization events. The biochip is composed of two parts: a microfluidic chip with three parallel micro-channels made of polydimethylsiloxane (PDMS), and a 3 x 3 arrayed electrochemical micro-chip. The DNA hybridization events are detected using electrochemical impedance spectroscopy (EIS) analysis. The EIS analysis enables monitoring variations of the properties of the electrochemical system that are dominant at these length scales. With the ability to monitor changes of both charge transfer and diffusional resistance with the biosensor, we demonstrate the selectivity to complementary ssDNA targets, a calculated detection limit of 3.8 nM, and a 13% cross-reactivity with other non-complementary ssDNA following 20 min of incubation. This methodology can improve the performance of miniaturized devices by elucidating on the behavior of diffusion at the micro-scale regime and by enabling the study of DNA hybridization events.

Multicolor and erasable DNA photolithography

The immobilization of DNA molecules onto a solid support is a crucial step in biochip research and related applications. In this work, we report a DNA photolithography method based on photocleavage of 2-nitrobenzyl linker-modified DNA strands. These strands were subjected to ultraviolet light irradiation to generate multiple short DNA strands in a programmable manner. Coupling the toehold-mediated DNA strand-displacement reaction with DNA photolithography enabled the fabrication of a DNA chip surface with multifunctional DNA patterns having complex geometrical structures at the microscale level. The erasable DNA photolithography strategy was developed to allow different paintings on the same chip. Furthermore, the asymmetrical modification of colloidal particles was carried out by using this photolithography strategy. This strategy has broad applications in biosensors, nanodevices, and DNA-nanostructure fabrication.

The accuracy of prediction of genomic selection in elite hybrid rye populations surpasses the accuracy of marker-assisted selection and is equally augmented by multiple field evaluation locations and test years

Background

Marker-assisted selection (MAS) and genomic selection (GS) based on genome-wide marker data provide powerful tools to predict the genotypic value of selection material in plant breeding. However, case-to-case optimization of these approaches is required to achieve maximum accuracy of prediction with reasonable input.

Results

Based on extended field evaluation data for grain yield, plant height, starch content and total pentosan content of elite hybrid rye derived from testcrosses involving two bi-parental populations that were genotyped with 1048 molecular markers, we compared the accuracy of prediction of MAS and GS in a cross-validation approach. MAS delivered generally lower and in addition potentially over-estimated accuracies of prediction than GS by ridge regression best linear unbiased prediction (RR-BLUP). The grade of relatedness of the plant material included in the estimation and test sets clearly affected the accuracy of prediction of GS. Within each of the two bi-parental populations, accuracies differed depending on the relatedness of the respective parental lines. Across populations, accuracy increased when both populations contributed to estimation and test set. In contrast, accuracy of prediction based on an estimation set from one population to a test set from the other population was low despite that the two bi-parental segregating populations under scrutiny shared one parental line. Limiting the number of locations or years in field testing reduced the accuracy of prediction of GS equally, supporting the view that to establish robust GS calibration models a sufficient number of test locations is of similar importance as extended testing for more than one year.

Conclusions

In hybrid rye, genomic selection is superior to marker-assisted selection. However, it achieves high accuracies of prediction only for selection candidates closely related to the plant material evaluated in field trials, resulting in a rather pessimistic prognosis for distantly related material. Both, the numbers of evaluation locations and testing years in trials contribute equally to prediction accuracy.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-556) contains supplementary material, which is available to authorized users.

Mechanisms of surface-mediated DNA hybridization

Single-molecule total internal reflection fluorescence microscopy was employed in conjunction with resonance energy transfer (RET) to observe the dynamic behavior of donor-labeled ssDNA at the interface between aqueous solution and a solid surface decorated with complementary acceptor-labeled ssDNA. At least 100,000 molecular trajectories were determined for both complementary strands and negative control ssDNA. RET was used to identify trajectory segments corresponding to the hybridized state. The vast majority of molecules from solution adsorbed nonspecifically to the surface, where a brief two-dimensional search was performed with a 7% chance of hybridization. Successful hybridization events occurred with a characteristic search time of ∼0.1 s, and unsuccessful searches resulted in desorption from the surface, ultimately repeating the adsorption and search process. Hybridization was reversible, and two distinct modes of melting (i.e., dehybridization) were observed, corresponding to long-lived (∼15 s) and short-lived (∼1.4 s) hybridized time intervals. A strand that melted back onto the surface could rehybridize after a brief search or desorb from the interface. These mechanistic observations provide guidance for technologies that involve DNA interactions in the near-surface region, suggesting a need to design surfaces that both enhance the complex multidimensional search process and stabilize the hybridized state.

Prediction of gene-based drug indications using compendia of public gene expression data and PubMed abstracts

The tremendous research effort on diseases and drug discovery has produced a huge amount of important biomedical information which is mostly hidden in the web. In addition, many databases have been created for the purpose of storing enormous amounts of information and high-throughput experiments related to drugs and diseases' effects on genes. Thus, developing an algorithm to integrate biological data from different sources forms one of the greatest challenges in the field of computational biology. Based on our belief that data integration would result in better understanding for the drug mode of action or the disease pathophysiology, we have developed a novel paradigm to integrate data from three major sources in order to predict novel therapeutic drug indications. Microarray data, biomedical text mining data, and gene interaction data have been all integrated to predict ranked lists of genes based on their relevance to a particular drug or disease molecular action. These ranked lists of genes have finally been used as a raw material for building a disease-drug connectivity map based on the enrichment between the up/down tags of a particular disease signature and the ranked lists of drugs. Using this paradigm, we have reported 13% sensitivity improvement in comparison with using microarray or text mining data independently. In addition, our paradigm is able to predict many clinically validated disease-drug associations that could not be captured using microarray or text mining data independently.

Arrayed identification of DNA signatures

Over the last few years, several initiatives have described efforts to combine previously invented techniques in molecular biology with parallel detection principles to sequence or genotype DNA signatures. The Infinium system from Illumina and the Affymetrix GeneChips are two systems suitable for whole-genome scoring of variable positions. However, directed candidate-gene approaches are more cost effective and several academic groups and the private sector provide techniques with moderate typing throughput combined with large sample capacity suiting these needs. Recently, whole-genome sequencing platforms based on the sequencing-by-synthesis principle were presented by 454 Life Sciences and Solexa, showing great potential as alternatives to conventional genotyping approaches. In addition to these sequencing initiatives, many efforts are pursuing novel ideas to facilitate fast and cost-effective whole genome sequencing, such as ligation-based sequencing. Reliable methods for routine re-sequencing of human genomes as a tool for personalized medicine, however, remain to be developed.

Molecular applications for identifying microbial pathogens in the post-9/11 era

Rapid advances in molecular and optical technologies over the past 10 years have dramatically impacted the way biologic research is conducted today. Examples include microarrays, capillary sequencing, optical mapping and real-time sequencing (Pyrosequencing). These technologies are capable of rapidly delivering massive amounts of genetic information and are becoming routine mainstays of many laboratories. Fortunately, advances in scientific computing have provided the enormous computing power necessary to analyze these enormous data sets. The application of molecular technologies should prove useful to the burgeoning field of microbial forensics. In the post-9/11 era, when securing America's food supply is a major endeavor, the need for rapid identification of microbes that accidentally or intentionally find their way into foods is apparent. The principle that distinguishes a microbial forensic investigation from a molecular epidemiology study is that a biocrime has been committed. If proper attribution is to be attained, a link must be made between a particular microbe in the food and the perpetrator who placed it there. Therefore, the techniques used must be able to discriminate individual isolates of a particular microbe. A battery of techniques in development for distinguishing individual isolates of particular foodborne pathogens is discussed.

Electrochemical patterning and detection of DNA arrays on a two-electrode platform

We report a novel method of DNA array formation that is electrochemically formed and addressed with a two-electrode platform. Electrochemical activation of a copper catalyst, patterned with one electrode, enables precise placement of multiple sequences of DNA onto a second electrode surface. The two-electrode patterning and detection platform allows for both spatial resolution of the patterned DNA array and optimization of detection through DNA-mediated charge transport with electrocatalysis. This two-electrode platform has been used to form arrays that enable differentiation between well-matched and mismatched sequences, the detection of TATA-binding protein, and sequence-selective DNA hybridization.

Counting the number of magnesium ions bound to the surface-immobilized thymine oligonucleotides that comprise spherical nucleic acids

Label-free studies carried out under aqueous phase conditions quantify the number of Mg(2+) ions binding to surface-immobilized T40 sequences, the subsequent reordering of DNA on the surface, and the consequences of Mg(2+) binding for DNA-DNA interactions. Second harmonic generation measurements indicate that, within error, 18-20 Mg(2+) ions are bound to the T40 strand at saturation and that the metal-DNA interaction is associated with a near 30% length contraction of the strand. Structural reordering, evaluated using vibrational sum frequency generation, atomic force microscopy, and dynamic light scattering, is attributed to increased charge screening as the Mg(2+) ions bind to the negatively charged DNA, reducing repulsive Coulomb forces between nucleotides and allowing the DNA single strands to collapse or coil upon themselves. The impact of Mg(2+) binding on DNA hybridization and duplex stability is assessed with spherical nucleic acid (SNA) gold nanoparticle conjugates in order to determine an optimal working range of Mg(2+) concentrations for DNA-DNA interactions in the absence of NaCl. The findings are consistent with a charge titration effect in which, in the absence of NaCl, (1) hybridization does not occur at room temperature if an average of 17.5 or less Mg(2+) ions are bound per T40 strand, which is not reached until the bulk Mg(2+) concentration approaches 0.5 mM; (2) hybridization proceeds, albeit with low duplex stability having an average Tm of 31(3)°C, if an average of 17.5-18.0 Mg(2+) ions are bound; and (3) highly stable duplexes having a Tm of 64(2)°C form if 18.5-19.0 Mg(2+) ions are bound, corresponding to saturation of the T40 strand.

Multiplexed VeraCode bead-based serological immunoassay for colorectal cancer

Colorectal cancer (CRC) is the second leading cause of cancer deaths in the US and Western world. Despite increased screening and advances in treatment, the mortality rate (ca. 50,000/year) and high national health-care burden for CRC are likely to remain high unless an effective non-invasive screening test for CRC is instituted for a large segment of the population. Blood-based protein biomarkers hold great promise for early disease diagnosis and personalized medicine; yet robust and reproducible multiplexing platforms and methodologies have lagged behind their genomic counterparts. Here, we report the development of a novel, multiplexed, hybrid immunoassay for CRC that is formatted on barcoded VeraCode™ micro-beads, which have until now only been used for genomic assays. The method combines a sandwich immunoassay format for detection of serum protein biomarkers with an antigen assay for autoantibody detection. The serum protein biomarkers CEA and GDF15 as well as autoantibodies to the p53 tumor associated antigen (TAA) were used to exemplify the method. This multiplex biomarker panel was configured to run on Illumina's holographically barcoded VeraCode™ micro-bead platform, which is capable of measuring hundreds of analytes simultaneously in a single well from small volumes of blood (<50 μL) using a 96-well industry standard microtiter plate. This novel use of the VeraCode™ micro-bead platform translates into a potentially low volume, high throughput, multiplexed assay for CRC, for the purposes of biomarker validation, as well as patient screening, diagnostics and prognostics. In an evaluation of a 186 patient sera training set (CRC and normal), we obtained a diagnostic sensitivity of 54% and a specificity of 98%. We anticipate that by expanding and refining the biomarkers in this initial panel, and performing more extensive clinical validations, such an assay could ultimately provide a basis for CRC population screening to complement the more invasive, expensive and low throughput (but highly sensitive and specific) colonoscopy.

Cinnamate-based DNA photolithography

As demonstrated by means of DNA nanoconstructs, as well as DNA functionalization of nanoparticles and micrometre-scale colloids, complex self-assembly processes require components to associate with particular partners in a programmable fashion. In many cases the reversibility of the interactions between complementary DNA sequences is an advantage. However, permanently bonding some or all of the complementary pairs may allow for flexibility in design and construction. Here, we show that the substitution of a cinnamate group for a pair of complementary bases provides an efficient, addressable, ultraviolet light-based method to bond complementary DNA covalently. To show the potential of this approach, we wrote micrometre-scale patterns on a surface using ultraviolet light and demonstrated the reversible attachment of conjugated DNA and DNA-coated colloids. Our strategy enables both functional DNA photolithography and multistep, specific binding in self-assembly processes.

Overview of DNA microarrays: types, applications, and their future

This unit provides an overview of DNA microarrays. Microarrays are a technology in which thousands of nucleic acids are bound to a surface and are used to measure the relative concentration of nucleic acid sequences in a mixture via hybridization and subsequent detection of the hybridization events. This overview first discusses the history of microarrays and the antecedent technologies that led to their development. This is followed by discussion of the methods of manufacture of microarrays and the most common biological applications. The unit ends with a brief description of the limitations of microarrays and discusses how microarrays are being rapidly replaced by DNA sequencing technologies.

Gene expression profiling and molecular pathway analysis for the identification of early-stage lung adenocarcinoma patients at risk for early recurrence

Clinicohistopathological staging is insufficient to predict disease progression and clinical outcome in lung carcinoma. Based on the results of the principal component analysis of 24 samples of early-stage lung adenocarcinoma, two subgroups were identified within the early-relapse group. The histological classification of all samples of group A was poorly differentiated, whereas one out of three in group B was poorly differentiated. DAVID functional annotation analysis revealed that the molecular pathways enriched in group A included those associated with cell adhesion molecules (CAMs), cell cycle and antigen processing and presentation, whereas those in group B included CAMs, T cell receptor signaling, cytokine-cytokine receptor interaction, toll-like receptor signaling, chemokine signaling, primary immunodeficiency and natural killer cell-mediated cytotoxicity. The CAM pathway was enriched in both groups. This comprehensive gene expression and functional pathway analysis identified a distinct molecular pathway, CAMs, that correlated with the early relapse of patients with early-stage lung adenocarcinoma.

Comparison of Gene Expression Profiles between Keratinocytes, Melanocytes and Fibroblasts

BACKGROUND

The skin has many important functions such as protection, preservation, temperature regulation, and vitamin D synthesis. It is composed of a variety of cell types including keratinocytes, melanocytes and fibroblasts.

OBJECTIVE

We attempted to compare the gene expression profiles between keratinocytes, melanocytes and fibroblast, using cDNA microarray.

METHODS

Keratinocytes, melanocytes and fibroblasts were primary cultured from five foreskin specimens. Total RNAs were extracted and pooled to reduce the individual variations, and then used for cDNA microarray.

RESULTS

Total 12,028 genes were selected as the reliable genes whose expression was detected in at least one of the three cell types. By comparing the relative expression levels with cutoff limitation as a fourfold change, we obtained 126 fibroblast-specific, 179 keratinocyte-specific and 173 melanocyte-specific genes, many of which are known to be characteristically expressed in each cell type. In addition, we identified many genes whose skin-specific functions have not yet been determined.

CONCLUSION

Our data provide important information on which to base further investigation into the specification of skin cell types.

A model of binding on DNA microarrays: understanding the combined effect of probe synthesis failure, cross-hybridization, DNA fragmentation and other experimental details of affymetrix arrays

BACKGROUND

DNA microarrays are used both for research and for diagnostics. In research, Affymetrix arrays are commonly used for genome wide association studies, resequencing, and for gene expression analysis. These arrays provide large amounts of data. This data is analyzed using statistical methods that quite often discard a large portion of the information. Most of the information that is lost comes from probes that systematically fail across chips and from batch effects. The aim of this study was to develop a comprehensive model for hybridization that predicts probe intensities for Affymetrix arrays and that could provide a basis for improved microarray analysis and probe development. The first part of the model calculates probe binding affinities to all the possible targets in the hybridization solution using the Langmuir isotherm. In the second part of the model we integrate details that are specific to each experiment and contribute to the differences between hybridization in solution and on the microarray. These details include fragmentation, wash stringency, temperature, salt concentration, and scanner settings. Furthermore, the model fits probe synthesis efficiency and target concentration parameters directly to the data. All the parameters used in the model have a well-established physical origin.

RESULTS

For the 302 chips that were analyzed the mean correlation between expected and observed probe intensities was 0.701 with a range of 0.88 to 0.55. All available chips were included in the analysis regardless of the data quality. Our results show that batch effects arise from differences in probe synthesis, scanner settings, wash strength, and target fragmentation. We also show that probe synthesis efficiencies for different nucleotides are not uniform.

CONCLUSIONS

To date this is the most complete model for binding on microarrays. This is the first model that includes both probe synthesis efficiency and hybridization kinetics/cross-hybridization. These two factors are sequence dependent and have a large impact on probe intensity. The results presented here provide novel insight into the effect of probe synthesis errors on Affymetrix microarrays; furthermore, the algorithms developed in this work provide useful tools for the analysis of cross-hybridization, probe synthesis efficiency, fragmentation, wash stringency, temperature, and salt concentration on microarray intensities.

Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L.) gene expression oligonucleotide microarray

Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01) allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.

Sequence-specific nucleic acid detection from binary pore conductance measurement

We describe a platform for sequence-specific nucleic acid (NA) detection utilizing a micropipet tapered to a 2 μm diameter pore and 3 μm diameter polystyrene beads to which uncharged peptide nucleic acid (PNA) probe molecules have been conjugated. As the target NAs hybridize to the complementary PNA-beads, the beads acquire negative charge and become electrophoretically mobile. An applied electric field guides these NA-PNA-beads toward the pipet tip, which they obstruct, leading to an indefinite, electrically detectable, partial blockade of the pore. In the presence of noncomplementary NA, even to the level of single base mismatch, permanent pore blockade is not seen. We show application of this platform to detection of the anthrax lethal factor sequence.

Application of resequencing microarrays in microbial detection and characterization

Microarrays are powerful, highly parallel assays that are transforming microbiological diagnostics and research. The adaptation of microarray-based resequencing technology for microbial detection and characterization resulted in the development of a number assays that have unique advantages over other existing technologies. This technological platform seems to be especially useful for sensitive and high-resolution multiplexed diagnostics for clinical syndromes with similar symptoms, screening environmental samples for biothreat agents, as well as genotyping and whole-genome analysis of single pathogens.

Acquired uniparental disomy in myeloproliferative neoplasms

The finding of somatically acquired uniparental disomy, where both copies of a chromosome pair or parts of chromosomes have originated from one parent, has led to the discovery of several novel mutated genes in myeloproliferative neoplasms and related disorders. This article examines how the development of single nucleotide polymorphism array technology has facilitated the identification of regions of acquired uniparental disomy and has led to a much greater understanding of the molecular pathology of these heterogeneous diseases.

Microfluidic chemical analysis systems

The field of microfluidics has exploded in the past decade, particularly in the area of chemical and biochemical analysis systems. Borrowing technology from the solid-state electronics industry and the production of microprocessor chips, researchers working with glass, silicon, and polymer substrates have fabricated macroscale laboratory components in miniaturized formats. These devices pump nanoliter volumes of liquid through micrometer-scale channels and perform complex chemical reactions and separations. The detection of reaction products is typically done fluorescently with off-chip optical components, and the analysis time from start to finish can be significantly shorter than that of conventional techniques. In this review we describe these microfluidic analysis systems, from the original continuous flow systems relying on electroosmotic pumping for liquid motion to the large diversity of microarray chips currently in use to the newer droplet-based devices and segmented flow systems. Although not currently widespread, microfluidic systems have the potential to become ubiquitous.

Advances in plant genome sequencing

The study of plant biology in the 21st century is, and will continue to be, vastly different from that in the 20th century. One driver for this has been the use of genomics methods to reveal the genetic blueprints for not one but dozens of plant species, as well as resolving genome differences in thousands of individuals at the population level. Genomics technology has advanced substantially since publication of the first plant genome sequence, that of Arabidopsis thaliana, in 2000. Plant genomics researchers have readily embraced new algorithms, technologies and approaches to generate genome, transcriptome and epigenome datasets for model and crop species that have permitted deep inferences into plant biology. Challenges in sequencing any genome include ploidy, heterozygosity and paralogy, all which are amplified in plant genomes compared to animal genomes due to the large genome sizes, high repetitive sequence content, and rampant whole- or segmental genome duplication. The ability to generate de novo transcriptome assemblies provides an alternative approach to bypass these complex genomes and access the gene space of these recalcitrant species. The field of genomics is driven by technological improvements in sequencing platforms; however, software and algorithm development has lagged behind reductions in sequencing costs, improved throughput, and quality improvements. It is anticipated that sequencing platforms will continue to improve the length and quality of output, and that the complementary algorithms and bioinformatic software needed to handle large, repetitive genomes will improve. The future is bright for an exponential improvement in our understanding of plant biology.

Single-molecule studies using magnetic traps

In recent years, techniques have been developed to study and manipulate single molecules of DNA and other biopolymers. In one such technique, the magnetic trap, a single DNA molecule is bound at one end to a glass surface and at the other to a magnetic microbead. Small magnets, whose position and rotation can be controlled, pull on and rotate the microbead. This provides a simple method to stretch and twist the molecule. The system allows one to apply and measure forces ranging from 10(-3) to >100 pN. In contrast to other techniques, the force measurement is absolute and does not require calibration of the sensor. In this article, we describe the principle of the magnetic trap, as well as its use in the measurement of the elastic properties of DNA and the study of DNA-protein interactions.

Using genome-wide expression profiling to define gene networks relevant to the study of complex traits: from RNA integrity to network topology

Postgenomic studies of the function of genes and their role in disease have now become an area of intense study since efforts to define the raw sequence material of the genome have largely been completed. The use of whole-genome approaches such as microarray expression profiling and, more recently, RNA-sequence analysis of transcript abundance has allowed an unprecedented look at the workings of the genome. However, the accurate derivation of such high-throughput data and their analysis in terms of biological function has been critical to truly leveraging the postgenomic revolution. This chapter will describe an approach that focuses on the use of gene networks to both organize and interpret genomic expression data. Such networks, derived from statistical analysis of large genomic datasets and the application of multiple bioinformatics data resources, potentially allow the identification of key control elements for networks associated with human disease, and thus may lead to derivation of novel therapeutic approaches. However, as discussed in this chapter, the leveraging of such networks cannot occur without a thorough understanding of the technical and statistical factors influencing the derivation of genomic expression data. Thus, while the catch phrase may be "it's the network … stupid," the understanding of factors extending from RNA isolation to genomic profiling technique, multivariate statistics, and bioinformatics are all critical to defining fully useful gene networks for study of complex biology.

FRET-based real-time DNA microarrays

We present a quantification method for affinity-based DNA microarrays which is based on the real-time measurements of hybridization kinetics. This method, i.e., real-time DNA microarrays, enhances the detection dynamic range of conventional systems by being impervious to probe saturation, washing artifacts, microarray spot-to-spot variations, and other intensity-affecting impediments. We demonstrate in both theory and practice that the time-constant of target capturing is inversely proportional to the concentration of the target analyte, which we take advantage of as the fundamental parameter to estimate the concentration of the analytes. Furthermore, to experimentally validate the capabilities of this method in practical applications, we present a FRET-based assay which enables the real-time detection in gene expression DNA microarrays.

Photochemical conversion of the o-nitrobenzyl-C-glucoside to a sugar lactone

A new family of activated glycosidic compounds has been designed and synthesized: (2,3,4,6-tetra-O-acetyl-β-D-glucopyranosyl)-2-nitrophenylmethane (1). It is stable in conditions commonly used for synthesis, and it can be converted to a sugar lactone derivative merely by photoirradiation (λ=365 nm): 2,3,4,6-tetra-O-acetyl-D-glucono-1,5-lactone (2). A mechanism for the reaction is proposed. The photochemical conversion of 1 in the presence of methanol has also been demonstrated, giving rise to methyl 2,3,4,6-tetra-O-acetyl-D-gluconate (3).

Diversity array technology markers: genetic diversity analyses and linkage map construction in rapeseed (Brassica napus L.)

We developed Diversity Array Technology (DArT) markers for application in genetic studies of Brassica napus and other Brassica species with A or C genomes. Genomic representation from 107 diverse genotypes of B. napus L. var. oleifera (rapeseed, AACC genomes) and B. rapa (AA genome) was used to develop a DArT array comprising 11 520 clones generated using PstI/BanII and PstI/BstN1 complexity reduction methods. In total, 1547 polymorphic DArT markers of high technical quality were identified and used to assess molecular diversity among 89 accessions of B. napus, B. rapa, B. juncea, and B. carinata collected from different parts of the world. Hierarchical cluster and principal component analyses based on genetic distance matrices identified distinct populations clustering mainly according to their origin/pedigrees. DArT markers were also mapped in a new doubled haploid population comprising 131 lines from a cross between spring rapeseed lines ‘Lynx-037DH’ and ‘Monty-028DH’. Linkage groups were assigned on the basis of previously mapped simple sequence repeat (SSRs), intron polymorphism (IP), and gene-based markers. The map consisted of 437 DArT, 135 SSR, 6 IP, and 6 gene-based markers and spanned 2288 cM. Our results demonstrate that DArT markers are suitable for genetic diversity analysis and linkage map construction in rapeseed.

Drug targets: single-cell transcriptomics hastens unbiased discovery

Drug discovery in neuro- and psychopharmacology is lagging, and the most commonly mentioned cause is the scarcity of drug targets. Using NextGen 'sequencing based single-cell transcriptomics' (SBSCT), several hundred different receptors and channels can be identified in individual neurons, and the functional gene product can subsequently be validated. The use of single-cell transcriptome data to reveal the entire receptor repertoire is crucial, as the copy numbers of mRNAs encoding receptors are low, and when cells are pooled dilution of rare mRNAs leads to loss of signal. These overlooked receptors on key neurons often mediate robust effects that may be therapeutically useful. SBSCT also enables the identification of orphan receptors and can provide strong evidence for receptor heterodimers. Here, we compare SBSCT to other single-cell profiling methods. We argue that the unbiased nature of SBSCT makes it a powerful tool for the identification of new drug targets.

Multiparametric determination of genes and their point mutations for identification of beta-lactamases

More than half of all currently used antibiotics belong to the beta-lactam group, but their clinical effectiveness is severely limited by antibiotic resistance of microorganisms that are the causative agents of infectious diseases. Several mechanisms for the resistance of Enterobacteriaceae have been established, but the main one is the enzymatic hydrolysis of the antibiotic by specific enzymes called beta-lactamases. Beta-lactamases represent a large group of genetically and functionally different enzymes of which extended-spectrum beta-lactamases (ESBLs) pose the greatest threat. Due to the plasmid localization of the encoded genes, the distribution of these enzymes among the pathogens increases every year. Among ESBLs the most widespread and clinically relevant are class A ESBLs of TEM, SHV, and CTX-M types. TEM and SHV type ESBLs are derived from penicillinases TEM-1, TEM-2, and SHV-1 and are characterized by several single amino acid substitutions. The extended spectrum of substrate specificity for CTX-M beta-lactamases is also associated with the emergence of single mutations in the coding genes. The present review describes various molecular-biological methods used to identify determinants of antibiotic resistance. Particular attention is given to the method of hybridization analysis on microarrays, which allows simultaneous multiparametric determination of many genes and point mutations in them. A separate chapter deals with the use of hybridization analysis on microarrays for genotyping of the major clinically significant ESBLs. Specificity of mutation detection by means of hybridization analysis with different detection techniques is compared.

Development of multisample detection system using a tag insertion primer and an electrochemical DNA chip

We have developed a novel multisample detection system by employing a technology combining a tag insertion primer and an electrochemical DNA chip. In the first application, Helicobacter species-infected mouse samples were detected. The primers that insert a different tag sequence in each sample were prepared, and loop-mediated isothermal amplification (LAMP) reaction was carried out. Then amplification products in which a part of the sequence was different in each sample could be obtained. The target sample in which these amplification products were mixed was injected into a cassette that included the DNA chip with immobilized probes. After the cassette was set in the DNA detection system, Genelyzer, the processes of hybridization, washing, and detection were performed by the system automatically. The positive and negative concordance rates of the existing nested polymerase chain reaction (PCR) method and this method were 100% (40/40 samples) and 97.3% (117/120 samples), respectively. This is a simple high-throughput method. Moreover, the cost per sample can be drastically lowered. Therefore, it is expected to contribute to the diagnosis of infectious agents in humans and animals.

PCR amplification-independent methods for detection of microbial communities by the high-density microarray PhyloChip

Environmental microbial community analysis typically involves amplification by PCR, despite well-documented biases. We have developed two methods of PCR-independent microbial community analysis using the high-density microarray PhyloChip: direct hybridization of 16S rRNA (dirRNA) or rRNA converted to double-stranded cDNA (dscDNA). We compared dirRNA and dscDNA communities to PCR-amplified DNA communities using a mock community of eight taxa, as well as experiments derived from three environmental sample types: chromium-contaminated aquifer groundwater, tropical forest soil, and secondary sewage in seawater. Community profiles by both direct hybridization methods showed differences that were expected based on accompanying data but that were missing in PCR-amplified communities. Taxon richness decreased in RNA compared to that in DNA communities, suggesting a subset of 20% in soil and 60% in groundwater that is active; secondary sewage showed no difference between active and inactive populations. Direct hybridization of dscDNA and RNA is thus a viable alternative to PCR-amplified microbial community analysis, providing identification of the active populations within microbial communities that attenuate pollutants, drive global biogeochemical cycles, or proliferate disease states.

Development of a molecular linkage map of pearl millet integrating DArT and SSR markers

Pearl millet is an important component of food security in the semi-arid tropics and is assuming greater importance in the context of changing climate and increasing demand for highly nutritious food and feed. Molecular tools have been developed and applied for pearl millet on a limited scale. However, the existing tool kit needs to be strengthened further for its routine use in applied breeding programs. Here, we report enrichment of the pearl millet molecular linkage map by exploiting low-cost and high-throughput Diversity Arrays Technology (DArT) markers. Genomic representation from 95 diverse genotypes was used to develop a DArT array with circa 7,000 clones following PstI/BanII complexity reduction. This array was used to genotype a set of 24 diverse pearl millet inbreds and 574 polymorphic DArT markers were identified. The genetic relationships among the inbred lines as revealed by DArT genotyping were in complete agreement with the available pedigree data. Further, a mapping population of 140 F(7) Recombinant Inbred Lines (RILs) from cross H 77/833-2 × PRLT 2/89-33 was genotyped and an improved linkage map was constructed by integrating DArT and SSR marker data. This map contains 321 loci (258 DArTs and 63 SSRs) and spans 1148 cM with an average adjacent-marker interval length of 3.7 cM. The length of individual linkage groups (LGs) ranged from 78 cM (LG 3) to 370 cM (LG 2). This better-saturated map provides improved genome coverage and will be useful for genetic analyses of important quantitative traits. This DArT platform will also permit cost-effective background selection in marker-assisted backcrossing programs as well as facilitate comparative genomics and genome organization studies once DNA sequences of polymorphic DArT clones are available.

Metabolic capabilities and systems fluctuations in Haloarcula marismortui revealed by integrative genomics and proteomics analyses

The 1310 Haloarcula marismortui proteins identified from mid-log and late-log phase soluble and membrane proteomes were analyzed in metabolic and cellular process networks to predict the available systems and systems fluctuations upon environmental stresses. When the connected metabolic reactions with identified proteins were examined, the availability of a number of metabolic pathways and a highly connected amino acid metabolic network were revealed. Quantitative spectral count analyses suggested 300 or more proteins might have expression changes in late-log phase. Among these, integrative network analyses indicated approximately 106 were metabolic proteins that might have growth-phase dependent changes. Interestingly, a large proportion of proteins in affected biomodules had the same trend of changes in spectral counts. Disregard the magnitude of changes, we had successfully predicted and validated the expression changes of nine genes including the rimK, gltCP, rrnAC0132, and argC in lysine biosynthesis pathway which were downregulated in late-log phase. This study had not only revealed the expressed proteins but also the availability of biological systems in two growth phases, systems level changes in response to the stresses in late-log phase, cellular locations of identified proteins, and the likely regulated genes to facilitate further analyses in the postgenomic era.

A study of performance on microarray data sets for a classifier based on information theoretic learning

Gene-expression microarray is a novel technology that allows the examination of tens of thousands of genes at a time. For this reason, manual observation is not feasible and machine learning methods are progressing to face these new data. Specifically, since the number of genes is very high, feature selection methods have proven valuable to deal with these unbalanced-high dimensionality and low cardinality-data sets. In this work, the FVQIT (Frontier Vector Quantization using Information Theory) classifier is employed to classify twelve DNA gene-expression microarray data sets of different kinds of cancer. A comparative study with other well-known classifiers is performed. The proposed approach shows competitive results outperforming all other classifiers.

Fabrication of DNA polymer brush arrays by destructive micropatterning and rolling-circle amplification

A method for fabricating DNA polymer brush arrays using photolithography and plasma etching followed by solid-phase enzymatic DNA amplification is reported. After attaching oligonucleotide primers to the surface of a glass coverslip, a thin layer of photoresist is spin-coated on the glass and patterned via photolithography to generate an array of posts in the resist. An oxygen-based plasma is then used to destroy the exposed oligonucleotide primers. The glass coverslip with the primer array is assembled into a microfluidic chip and DNA polymer brushes are synthesized on the oligonucleotide array by rolling-circle DNA amplification. We have demonstrated that the linear polymers can be rapidly synthesized in situ with a high degree of control over their density and length.

Global array-based transcriptomics from minimal input RNA utilising an optimal RNA isolation process combined with SPIA cDNA probes

BACKGROUND

Technical advances in the collection of clinical material, such as laser capture microdissection and cell sorting, provide the advantage of yielding more refined and homogenous populations of cells. However, these attractive advantages are counter balanced by the significant difficulty in obtaining adequate nucleic acid yields to allow transcriptomic analyses. Established technologies are available to carry out global transcriptomics using nanograms of input RNA, however, many clinical samples of low cell content would be expected to yield RNA within the picogram range. To fully exploit these clinical samples the challenge of isolating adequate RNA yield directly and generating sufficient microarray probes for global transcriptional profiling from this low level RNA input has been addressed in the current report. We have established an optimised RNA isolation workflow specifically designed to yield maximal RNA from minimal cell numbers. This procedure obtained RNA yield sufficient for carrying out global transcriptional profiling from vascular endothelial cell biopsies, clinical material not previously amenable to global transcriptomic approaches. In addition, by assessing the performance of two linear isothermal probe generation methods at decreasing input levels of good quality RNA we demonstrated robust detection of a class of low abundance transcripts (GPCRs) at input levels within the picogram range, a lower level of RNA input (50 pg) than previously reported for global transcriptional profiling and report the ability to interrogate the transcriptome from only 10 pg of input RNA. By exploiting an optimal RNA isolation workflow specifically for samples of low cell content, and linear isothermal RNA amplification methods for low level RNA input we were able to perform global transcriptomics on valuable and potentially informative clinically derived vascular endothelial biopsies here for the first time. These workflows provide the ability to robustly exploit ever more common clinical samples yielding extremely low cell numbers and RNA yields for global transcriptomics.

Human transcriptome array for high-throughput clinical studies

A 6.9 million-feature oligonucleotide array of the human transcriptome [Glue Grant human transcriptome (GG-H array)] has been developed for high-throughput and cost-effective analyses in clinical studies. This array allows comprehensive examination of gene expression and genome-wide identification of alternative splicing as well as detection of coding SNPs and noncoding transcripts. The performance of the array was examined and compared with mRNA sequencing (RNA-Seq) results over multiple independent replicates of liver and muscle samples. Compared with RNA-Seq of 46 million uniquely mappable reads per replicate, the GG-H array is highly reproducible in estimating gene and exon abundance. Although both platforms detect similar expression changes at the gene level, the GG-H array is more sensitive at the exon level. Deeper sequencing is required to adequately cover low-abundance transcripts. The array has been implemented in a multicenter clinical program and has generated high-quality, reproducible data. Considering the clinical trial requirements of cost, sample availability, and throughput, the GG-H array has a wide range of applications. An emerging approach for large-scale clinical genomic studies is to first use RNA-Seq to the sufficient depth for the discovery of transcriptome elements relevant to the disease process followed by high-throughput and reliable screening of these elements on thousands of patient samples using custom-designed arrays.

Suppression subtractive hybridization

Comparing two RNA populations that differ from the effects of a single independent variable, such as a drug treatment or a specific genetic defect, can establish differences in the abundance of specific transcripts that vary in a population dependent manner. There are different methods for identifying differentially expressed genes. These methods include microarray, Serial Analysis of Gene Expression (SAGE), and quantitative Reverse-Transcriptase Polymerase Chain Reaction (qRT-PCR). Herein, the protocol describes an easy and cost-effective alternative that does not require prior knowledge of the transcriptomes under examination. It is specifically relevant when low levels of RNA starting material are available. This protocol describes the use of Switching Mechanism At RNA Termini Polymerase Chain Reaction (SMART-PCR) to amplify cDNA from small amounts of RNA. The amplified cDNA populations under comparison are then subjected to Suppression Subtractive Hybridization (SSH-PCR). SSH-PCR is a technique that couples subtractive hybridization with suppression PCR to selectively amplify fragments of differentially expressed genes. The resulting products are cDNA populations enriched for significantly overrepresented transcripts in either of the two input RNAs. These cDNA populations can then be cloned to generate subtracted cDNA library. Microarrays made with clones from the subtracted forward and reverse cDNA libraries are then screened for differentially expressed genes using targets generated from tester and driver total RNAs.

Microarray evidences the role of pathologic adipose tissue in insulin resistance and their clinical implications

Clustering of insulin resistance and dysmetabolism with obesity is attributed to pathologic adipose tissue. The morphologic hallmarks of this pathology are adipocye hypertrophy and heightened inflammation. However, it's underlying molecular mechanisms remains unknown. Study of gene function in metabolically active tissues like adipose tissue, skeletal muscle and liver is a promising strategy. Microarray is a powerful technique of assessment of gene function by measuring transcription of large number of genes in an array. This technique has several potential applications in understanding pathologic adipose tissue. They are: (1) transcriptomic differences between various depots of adipose tissue, adipose tissue from obese versus lean individuals, high insulin resistant versus low insulin resistance, brown versus white adipose tissue, (2) transcriptomic profiles of various stages of adipogenesis, (3) effect of diet, cytokines, adipokines, hormones, environmental toxins and drugs on transcriptomic profiles, (4) influence of adipokines on transcriptomic profiles in skeletal muscle, hepatocyte, adipose tissue etc., and (5) genetics of gene expression. The microarray evidences of molecular basis of obesity and insulin resistance are presented here. Despite the limitations, microarray has potential clinical applications in finding new molecular targets for treatment of insulin resistance and classification of adipose tissue based on future risk of insulin resistance syndrome.