Microarray oligonucleotide probes

Blood-derived lncRNAs as biomarkers for cancer diagnosis: the Good, the Bad and the Beauty

Cancer ranks as one of the deadliest diseases worldwide. The high mortality rate associated with cancer is partially due to the lack of reliable early detection methods and/or inaccurate diagnostic tools such as certain protein biomarkers. Cell-free nucleic acids (cfNA) such as circulating long noncoding RNAs (lncRNAs) have been proposed as a new class of potential biomarkers for cancer diagnosis. The reported correlation between the presence of tumors and abnormal levels of lncRNAs in the blood of cancer patients has notably triggered a worldwide interest among clinicians and oncologists who have been actively investigating their potentials as reliable cancer biomarkers. In this report, we review the progress achieved (“the Good”) and challenges encountered (“the Bad”) in the development of circulating lncRNAs as potential biomarkers for early cancer diagnosis. We report and discuss the diagnostic performance of more than 50 different circulating lncRNAs and emphasize their numerous potential clinical applications (“the Beauty”) including therapeutic targets and agents, on top of diagnostic and prognostic capabilities. This review also summarizes the best methods of investigation and provides useful guidelines for clinicians and scientists who desire conducting their own clinical studies on circulating lncRNAs in cancer patients via RT-qPCR or Next Generation Sequencing (NGS).

DNA nanotechnology for nucleic acid analysis: multifunctional molecular DNA machine for RNA detection

The Nobel prize in chemistry in 2016 was awarded for 'the design and synthesis of molecular machines'. Here we designed and assembled a molecular machine for the detection of specific RNA molecules. An association of several DNA strands, named multifunctional DNA machine for RNA analysis (MDMR1), was designed to (i) unwind RNA with the help of RNA-binding arms, (ii) selectively recognize a targeted RNA fragment, (iii) attract a signal-producing substrate and (iv) amplify the fluorescent signal by catalysis. MDMR1 enabled detection of 16S rRNA at concentrations ∼24 times lower than that by a traditional deoxyribozyme probe.

miRNA detection methods and clinical implications in lung cancer

Lung cancer is the leading cause of cancer death worldwide. Therefore, advances in the diagnosis and treatment of the disease are urgently needed. miRNAs are a family of small, noncoding RNAs that regulate gene expression at the transcriptional level. miRNAs have been reported to be deregulated and to play a critical role in different types of cancer, including lung cancer. Thus, miRNA profiling in lung cancer patients has become the core of several investigations. To this end, the development of a multitude of platforms for miRNA profiling analysis has been essential. This article focuses on the different technologies available for assessing miRNAs and the most important results obtained to date in lung cancer.

Recent advances of microRNA-based molecular diagnostics to reduce false-positive lung cancer imaging

Lung cancer is the leading cause of cancer deaths in the world. Advances in early detection crucial to enable timely curative surgery have been made in recent years. Cost-benefit profiles of lung cancer screening in smokers by low-dose computed tomography are still under evaluation. In particular, the high false-positive rates of low-dose computed tomography, together with the issue of overdiagnosis and the overall costs of screening, prompted a focus on the development of noninvasive complementary biomarkers to implement lung cancer screening. MicroRNA are a new class of blood-based biomarkers useful for early lung cancer detection and prognosis definition. Here, we discuss the seminal publications that reported circulating microRNA signatures with the greatest potential to impact clinical activity and patient care.

The Peri-Implant and Periodontal Microbiota in Patients with and without Clinical Signs of Inflammation

Late implant failures, caused by the inflammation of surrounding tissues are a problem in implant dentistry. The path of bacterial transmission from teeth to implants is not completely understood. Therefore, the purpose of this study was to analyze intraindividual bacterial transmission characterizing subgingival microbiomes in teeth and implants, both in healthy subjects and in those with signs of periodontitis or peri-implantitis. Samples of peri-implant and dental sulcus fluid were collected. To identify the predominant microbiota, amplified fragments of bacterial 16S rRNA gene were separated by single strand conformation polymorphism analysis, sequenced and taxonomically classified. A total of 25 different predominant genera were found in the diseased group and 14 genera in the healthy group. Species richness did not differ significantly between implants, neighboring teeth and teeth with largest probing depth in the diseased group. Additionally, no differences between teeth and implants in the healthy group were detected. In contrast, microbial diversity varied between the different sampling points. Species richness is similar in healthy and diseased sites, but the composition of the bacterial community differed within the individual subjects. The underlying analyses strongly suggest that complete transmission from neighboring teeth to implants is unlikely.

Anomalous electrophoretic migration of short oligodeoxynucleotides labelled with 5'-terminal Cy5 dyes

By using a fluorescent exonuclease assay, we reported unusual electrophoretic mobility of 5'-indocarbo-cyanine 5 (5'-Cy5) labelled DNA fragments in denaturing polyacrylamide gels. Incubation time and enzyme concentration were two parameters involved in the formation of 5'-Cy5-labelled degradation products, while the structure of the substrate was slightly interfering. Replacement of positively charged 5'-Cy5-labelled DNA oligonucleotides (DNA oligos) by electrically neutral 5'-carboxyfluorescein (5'-FAM) labelled DNA oligos abolished the anomalous migration pattern of degradation products. MS analysis demonstrated that anomalously migrating products were in fact 5'-labelled DNA fragments ranging from 1 to 8 nucleotides. Longer 5'-Cy5-labelled DNA fragments migrated at the expected position. Altogether, these data highlighted, for the first time, the influence of the mass/charge ratio of 5'-Cy5-labelled DNA oligos on their electrophoretic mobility. Although obtained by performing 3' to 5' exonuclease assays with the family B DNA polymerase from Pyrococcus abyssi, these observations represent a major concern in DNA technology involving most DNA degrading enzymes.

Targeted sequencing for gene discovery and quantification using RNA CaptureSeq

RNA sequencing (RNAseq) samples the majority of expressed genes infrequently, owing to the large size, complex splicing and wide dynamic range of eukaryotic transcriptomes. This results in sparse sequencing coverage that can hinder robust isoform assembly and quantification. RNA capture sequencing (CaptureSeq) addresses this challenge by using oligonucleotide probes to capture selected genes or regions of interest for targeted sequencing. Targeted RNAseq provides enhanced coverage for sensitive gene discovery, robust transcript assembly and accurate gene quantification. Here we describe a detailed protocol for all stages of RNA CaptureSeq, from initial probe design considerations and capture of targeted genes to final assembly and quantification of captured transcripts. Initial probe design and final analysis can take less than 1 d, whereas the central experimental capture stage requires ∼7 d.

Effect of Target Length on Specificity and Sensitivity of Oligonucleotide Microarrays: A Comparison between Dendrimer and Modified PCR based Labelling Methods

DNA microarrays are widely used as end point detectors for gene expression analysis. Several methods have been developed for target labelling to enable quantification but without taking target length into consideration. Here we highlight the importance of choosing the optimum target length that would ensure specificity without compromising sensitivity of the assay. For this, eight plasmids that are identical to each other except for a closely related 23 bp unique reporter (UR) sequence were used to examine the hybridization efficiency for these URs. Targets of various lengths were generated and labelled as follows: full length and 330 bases transcripts using a dendrimer labelling method, 120 bp amplicons by the modified PCR end labelling method and synthetic labelled targets of 33 bases. This report also shows the advantages of using the modified PCR method over other labelling methods in generating labelled amplicons of the desired lengths to maximize hybridization efficiency.

Selective nucleic acid capture with shielded covalent probes

Nucleic acid probes are used for diverse applications in vitro, in situ, and in vivo. In any setting, their power is limited by imperfect selectivity (binding of undesired targets) and incomplete affinity (binding is reversible, and not all desired targets bound). These difficulties are fundamental, stemming from reliance on base pairing to provide both selectivity and affinity. Shielded covalent (SC) probes eliminate the longstanding trade-off between selectivity and durable target capture, achieving selectivity via programmable base pairing and molecular conformation change, and durable target capture via activatable covalent cross-linking. In pure and mixed samples, SC probes covalently capture complementary DNA or RNA oligo targets and reject two-nucleotide mismatched targets with near-quantitative yields at room temperature, achieving discrimination ratios of 2-3 orders of magnitude. Semiquantitative studies with full-length mRNA targets demonstrate selective covalent capture comparable to that for RNA oligo targets. Single-nucleotide DNA or RNA mismatches, including nearly isoenergetic RNA wobble pairs, can be efficiently rejected with discrimination ratios of 1-2 orders of magnitude. Covalent capture yields appear consistent with the thermodynamics of probe/target hybridization, facilitating rational probe design. If desired, cross-links can be reversed to release the target after capture. In contrast to existing probe chemistries, SC probes achieve the high sequence selectivity of a structured probe, yet durably retain their targets even under denaturing conditions. This previously incompatible combination of properties suggests diverse applications based on selective and stable binding of nucleic acid targets under conditions where base-pairing is disrupted (e.g., by stringent washes in vitro or in situ, or by enzymes in vivo).

Meeting the methodological challenges in molecular mapping of the embryonic epigenome

The past decade of life sciences research has been driven by progress in genomics. Many voices are already proclaiming the post-genomics era, in which phenomena other than sequence polymorphism influence gene expression and also explain complex phenotypes. One of these burgeoning fields is the study of the epigenome. Although the mechanisms by which chromatin structure and reorganization as well as cytosine methylation influence gene expression are not fully understood, they are being invoked to explain the now-accepted long-term impact of the environment on gene expression, which appears to be a factor in the development of numerous diseases. Such studies are particularly relevant in early embryonic development, during which waves of epigenetic reprogramming are known to have profound impacts. Since gametes and zygotes are in the process of resetting the genome in order to create embryonic stem cells that will each differentiate to create one of many specific tissue types, this phase of life is now viewed as a window of susceptibility to epigenetic reprogramming errors. Epigenetics could explain the influence of factors such as the nutritional/metabolic status of the mother or the artificial environment of assisted reproductive technologies. However, the peculiar nature of early embryos in addition to their scarcity poses numerous technological challenges that are slowly being overcome. The principal subject of this article is to review the suitability of various current and emerging technological platforms to study oocytes and early embryonic epigenome with more emphasis on studying DNA methylation. Furthermore, the constraint of samples size, inherent to the study of preimplantation embryo development, was put in perspective with the various molecular platforms described.

A methodical microarray design enables surveying of expression of a broader range of genes in Ciona intestinalis

We provide a new oligo-microarray for Ciona intestinalis, based on the NimbleGen 12-plex×135k format. The array represents 106,285 probes, which is more than double the probe number of the currently available 44k microarray. These probes cover 99.2% of the transcripts in the KyotoHoya (KH) models, published in 2008, and they contain 81.1% of the entries in the UniGene database that are not included in the KH models. In this paper, we show that gene expression levels measured by this new 135k microarray are highly correlated with those obtained by the existing 44k microarray for genes common to both arrays. We also investigated gene expression using samples obtained from the ovary and the neural complex of adult C. intestinalis, showing that the expression of tissue-specific genes is consistent with previous reports. Approximately half of the highly expressed genes identified in the 135k microarray are not included in the previous microarray. The high coverage of gene models by this microarray made it possible to identify splicing variants for a given transcript. The 135k microarray is useful in investigating the functions of genes that are not yet well characterized. Detailed information about this 135k microarray is accessible at no charge from supplemental materials, NCBI Gene Expression Omnibus (GEO), and http://marinegenomics.oist.jp.

Computational Sequence Design Techniques for DNA Microarray Technologies

In systems biology and biomedical research, microarray technology is a method of choice that enables the complete quantitative and qualitative ascertainment of gene expression patterns for whole genomes. The selection of high quality oligonucleotide sequences that behave consistently across multiple experiments is a key step in the design, fabrication and experimental performance of DNA microarrays. The aim of this chapter is to outline recent algorithmic developments in microarray probe design, evaluate existing probe sequences used in commercial arrays, and suggest methodologies that have the potential to improve on existing design techniques.

Detection of bacterial 16S rRNA using a molecular beacon-based X sensor

We demonstrate how a long structurally constrained RNA can be analyzed in homogeneous solution at ambient temperatures with high specificity using a sophisticated biosensor. The sensor consists of a molecular beacon probe as a signal reporter and two DNA adaptor strands, which have fragments complementary to the reporter and to the analyzed RNA. One adaptor strand uses its long RNA-binding arm to unwind the RNA secondary structure. Second adaptor strand with a short RNA-binding arm hybridizes only to a completely complementary site, thus providing high recognition specificity. Overall the three-component sensor and the target RNA form a four-stranded DNA crossover (X) structure. Using this sensor, Escherichia coli16S rRNA was detected in real time with the detection limit of ~0.17 nM. The high specificity of the analysis was proven by differentiating Bacillus subtilis from E. coli 16S rRNA sequences. The sensor responds to the presence of the analyte within seconds.

Functional Studies of microRNAs in Neural Stem Cells: Problems and Perspectives

In adult mammals, neural stem cells (NSCs) are found in two niches of the brain; the subventricular zone by the lateral ventricles and the subgranular zone of the dentate gyrus in the hippocampus. Neurogenesis is a complex process that is tightly controlled on a molecular level. Recently, microRNAs (miRNAs) have been implicated to play a central role in the regulation of NCSs. miRNAs are small, endogenously expressed RNAs that regulate gene expression at the post-transcriptional level. However, functional studies of miRNAs are complicated due to current technical limitations. In this review we describe recent findings about miRNAs in NSCs looking closely at miR-124, miR-9, and let-7. In addition, we highlight technical strategies used to investigate miRNA function, accentuating limitations, and potentials.

Computational Sequence Design Techniques for DNA Microarray Technologies

In systems biology and biomedical research, microarray technology is a method of choice that enables the complete quantitative and qualitative ascertainment of gene expression patterns for whole genomes. The selection of high quality oligonucleotide sequences that behave consistently across multiple experiments is a key step in the design, fabrication and experimental performance of DNA microarrays. The aim of this chapter is to outline recent algorithmic developments in microarray probe design, evaluate existing probe sequences used in commercial arrays, and suggest methodologies that have the potential to improve on existing design techniques.

Application of microarray-based comparative genomic hybridization in prenatal and postnatal settings: three case reports

Microarray-based comparative genomic hybridization (array CGH) is a newly emerged molecular cytogenetic technique for rapid evaluation of the entire genome with sub-megabase resolution. It allows for the comprehensive investigation of thousands and millions of genomic loci at once and therefore enables the efficient detection of DNA copy number variations (a.k.a, cryptic genomic imbalances). The development and the clinical application of array CGH have revolutionized the diagnostic process in patients and has provided a clue to many unidentified or unexplained diseases which are suspected to have a genetic cause. In this paper, we present three clinical cases in both prenatal and postnatal settings. Among all, array CGH played a major discovery role to reveal the cryptic and/or complex nature of chromosome arrangements. By identifying the genetic causes responsible for the clinical observation in patients, array CGH has provided accurate diagnosis and appropriate clinical management in a timely and efficient manner.

Strategies for DNA methylation analysis in developmental studies

Developmental processes in eukaryotes are highly dependent on DNA methylation. 5-methylcytosine (m(5) C) is the most prevalent and best understood DNA modification implicated in maintenance of genomic integrity and function across species. Although m(5) C occurs almost exclusively in symmetrical CpG context in vertebrates, additional asymmetrical distribution in CpHpG and CpHpH sites has been observed in plants and embryonic stem cells. To this end, accurate and reproducible methodology for full analysis of the DNA methylome is highly demanded. Fortunately, a variety of methods enable quantitative DNA methylation mapping at a single-base resolution and in a large scale. Here, we provide a critical overview of methods applied primarily to m(5) C detection with particular emphasis on technical improvements of the classical bisulfite-conversion protocol. We further describe strategies in combination with emerging technologies that allow acquisition of highly reliable data for developmental studies.

The impact of quantitative optimization of hybridization conditions on gene expression analysis

Background

With the growing availability of entire genome sequences, an increasing number of scientists can exploit oligonucleotide microarrays for genome-scale expression studies. While probe-design is a major research area, relatively little work has been reported on the optimization of microarray protocols.

Results

As shown in this study, suboptimal conditions can have considerable impact on biologically relevant observations. For example, deviation from the optimal temperature by one degree Celsius lead to a loss of up to 44% of differentially expressed genes identified. While genes from thousands of Gene Ontology categories were affected, transcription factors and other low-copy-number regulators were disproportionately lost. Calibrated protocols are thus required in order to take full advantage of the large dynamic range of microarrays.

For an objective optimization of protocols we introduce an approach that maximizes the amount of information obtained per experiment. A comparison of two typical samples is sufficient for this calibration. We can ensure, however, that optimization results are independent of the samples and the specific measures used for calibration. Both simulations and spike-in experiments confirmed an unbiased determination of generally optimal experimental conditions.

Conclusions

Well calibrated hybridization conditions are thus easily achieved and necessary for the efficient detection of differential expression. They are essential for the sensitive pro filing of low-copy-number molecules. This is particularly critical for studies of transcription factor expression, or the inference and study of regulatory networks.

Accurate estimates of microarray target concentration from a simple sequence-independent Langmuir model

Background

Microarray technology is a commonly used tool for assessing global gene expression. Many models for estimation of target concentration based on observed microarray signal have been proposed, but, in general, these models have been complex and platform-dependent.

Principal Findings

We introduce a universal Langmuir model for estimation of absolute target concentration from microarray experiments. We find that this sequence-independent model, characterized by only three free parameters, yields excellent predictions for four microarray platforms, including Affymetrix, Agilent, Illumina and a custom-printed microarray. The model also accurately predicts concentration for the MAQC data sets. This approach significantly reduces the computational complexity of quantitative target concentration estimates.

Conclusions

Using a simple form of the Langmuir isotherm model, with a minimum of parameters and assumptions, and without explicit modeling of individual probe properties, we were able to recover absolute transcript concentrations with high R² on four different array platforms. The results obtained here suggest that with a “spiked-in” concentration series targeting as few as 5–10 genes, reliable estimation of target concentration can be achieved for the entire microarray.

Development of a DNA microarray to detect antimicrobial resistance genes identified in the National Center for Biotechnology Information database

To understand the mechanisms and epidemiology of antimicrobial resistance (AR), the genetic elements responsible must be identified. Due to the myriad of possible genes, a high-density genotyping technique is needed for initial screening. To achieve this, AR genes in the National Center for Biotechnology Information GenBank database were identified by their annotations and compiled into a nonredundant list of 775 genes. A DNA microarray was constructed of 70mer oligonucelotide probes designed to detect these genes encoding resistances to aminoglycosides, beta-lactams, chloramphenicols, glycopeptides, heavy metals, lincosamides, macrolides, metronidazoles, polyketides, quaternary ammonium compounds, streptogramins, sulfonamides, tetracyclines, and trimethoprims as well as resistance transfer genes. The microarray was validated with two fully sequenced control strains of Salmonella enterica: Typhimurium LT2 (sensitive) and Typhi CT18 (multidrug resistance [MDR]). All resistance genes encoded on the MDR plasmid, pHCM1, harbored by CT18 were detected in that strain, whereas no resistance genes were detected in LT2. The microarray was also tested with a variety of bacteria, including MDR Salmonella enterica serovars, Escherichia coli, Campylobacter spp., Enterococcus spp., methicillin-resistant Staphylococcus aureus, Listeria spp., and Clostridium difficile. The results presented here demonstrate that a microarray can be designed to detect virtually all AR genes found in the National Center for Biotechnology Information database, thus reducing the subsequent assays necessary to identify specific resistance gene alleles.

Profiling DNA methylomes from microarray to genome-scale sequencing

DNA cytosine methylation is a central epigenetic modification which plays critical roles in cellular processes including genome regulation, development and disease. Here, we review current and emerging microarray and next-generation sequencing based technologies that enhance our knowledge of DNA methylation profiling. Each methodology has limitations and their unique applications, and combinations of several modalities may help build the entire methylome. With advances on next-generation sequencing technologies, it is now possible to globally map the DNA cytosine methylation at single-base resolution, providing new insights into the regulation and dynamics of DNA methylation in genomes.

Application of equilibrium models of solution hybridization to microarray design and analysis

Background

The probe percent bound value, calculated using multi-state equilibrium models of solution hybridization, is shown to be useful in understanding the hybridization behavior of microarray probes having 50 nucleotides, with and without mismatches. These longer oligonucleotides are in widespread use on microarrays, but there are few controlled studies of their interactions with mismatched targets compared to 25-mer based platforms.

Principal Findings

50-mer oligonucleotides with centrally placed single, double and triple mismatches were spotted on an array. Over a range of target concentrations it was possible to discriminate binding to perfect matches and mismatches, and the type of mismatch could be predicted accurately in the concentration midrange (100 pM to 200 pM) using solution hybridization modeling methods. These results have implications for microarray design, optimization and analysis methods.

Conclusions

Our results highlight the importance of incorporating biophysical factors in both the design and the analysis of microarrays. Use of the probe “percent bound” value predicted by equilibrium models of hybridization is confirmed to be important for predicting and interpreting the behavior of long oligonucleotide arrays, as has been shown for short oligonucleotide arrays.

Basic concepts of microarrays and potential applications in clinical microbiology

The introduction of in vitro nucleic acid amplification techniques, led by real-time PCR, into the clinical microbiology laboratory has transformed the laboratory detection of viruses and select bacterial pathogens. However, the progression of the molecular diagnostic revolution currently relies on the ability to efficiently and accurately offer multiplex detection and characterization for a variety of infectious disease pathogens. Microarray analysis has the capability to offer robust multiplex detection but has just started to enter the diagnostic microbiology laboratory. Multiple microarray platforms exist, including printed double-stranded DNA and oligonucleotide arrays, in situ-synthesized arrays, high-density bead arrays, electronic microarrays, and suspension bead arrays. One aim of this paper is to review microarray technology, highlighting technical differences between them and each platform's advantages and disadvantages. Although the use of microarrays to generate gene expression data has become routine, applications pertinent to clinical microbiology continue to rapidly expand. This review highlights uses of microarray technology that impact diagnostic microbiology, including the detection and identification of pathogens, determination of antimicrobial resistance, epidemiological strain typing, and analysis of microbial infections using host genomic expression and polymorphism profiles.

Hybridization thermodynamics of NimbleGen microarrays

Background

While microarrays are the predominant method for gene expression profiling, probe signal variation is still an area of active research. Probe signal is sequence dependent and affected by probe-target binding strength and the competing formation of probe-probe dimers and secondary structures in probes and targets.

Results

We demonstrate the benefits of an improved model for microarray hybridization and assess the relative contributions of the probe-target binding strength and the different competing structures. Remarkably, specific and unspecific hybridization were apparently driven by different energetic contributions: For unspecific hybridization, the melting temperature T_m was the best predictor of signal variation. For specific hybridization, however, the effective interaction energy that fully considered competing structures was twice as powerful a predictor of probe signal variation. We show that this was largely due to the effects of secondary structures in the probe and target molecules. The predictive power of the strength of these intramolecular structures was already comparable to that of the melting temperature or the free energy of the probe-target duplex.

Conclusions

This analysis illustrates the importance of considering both the effects of probe-target binding strength and the different competing structures. For specific hybridization, the secondary structures of probe and target molecules turn out to be at least as important as the probe-target binding strength for an understanding of the observed microarray signal intensities. Besides their relevance for the design of new arrays, our results demonstrate the value of improving thermodynamic models for the read-out and interpretation of microarray signals.

Application of ESTs in microarray analysis

Microarray analyses provide information on the relative expression levels of large numbers of gene products (transcripts). As such they have been widely used to examine differences in gene expression across a variety of samples such as tissues and life-cycle stages. Due to a previous lack of sequence data, microarray analyses have typically centred on the study of well-characterised model organisms. However, the recent availability of large sets of expressed sequence tags (ESTs) generated for the purpose of gene discovery offers the opportunity to consider designing and applying microarray technology to a larger and more diverse set of species. Here we outline the array-design process involving the generation of an optimised set of oligoprobes from a minimally redundant but maximally representative list of sequences from raw EST data. We illustrate these principles by showing how we designed and fabricated a high-density oligoarray for the rainbow trout, a non-model species for which large numbers of ESTs, and a non-redundant assembly is available. This approach brings array technology within the reach of all investigators, even those with limited budgets.

Model-based probe set optimization for high-performance microarrays

A major challenge in microarray design is the selection of highly specific oligonucleotide probes for all targeted genes of interest, while maintaining thermodynamic uniformity at the hybridization temperature. We introduce a novel microarray design framework (Thermodynamic Model-based Oligo Design Optimizer, TherMODO) that for the first time incorporates a number of advanced modelling features: (i) A model of position-dependent labelling effects that is quantitatively derived from experiment. (ii) Multi-state thermodynamic hybridization models of probe binding behaviour, including potential cross-hybridization reactions. (iii) A fast calibrated sequence-similarity-based heuristic for cross-hybridization prediction supporting large-scale designs. (iv) A novel compound score formulation for the integrated assessment of multiple probe design objectives. In contrast to a greedy search for probes meeting parameter thresholds, this approach permits an optimization at the probe set level and facilitates the selection of highly specific probe candidates while maintaining probe set uniformity. (v) Lastly, a flexible target grouping structure allows easy adaptation of the pipeline to a variety of microarray application scenarios. The algorithm and features are discussed and demonstrated on actual design runs. Source code is available on request.

Novel insights into the unfolded protein response using Pichia pastoris specific DNA microarrays

Background

DNA Microarrays are regarded as a valuable tool for basic and applied research in microbiology. However, for many industrially important microorganisms the lack of commercially available microarrays still hampers physiological research. Exemplarily, our understanding of protein folding and secretion in the yeast Pichia pastoris is presently widely dependent on conclusions drawn from analogies to Saccharomyces cerevisiae. To close this gap for a yeast species employed for its high capacity to produce heterologous proteins, we developed full genome DNA microarrays for P. pastoris and analyzed the unfolded protein response (UPR) in this yeast species, as compared to S. cerevisiae.

Results

By combining the partially annotated gene list of P. pastoris with de novo gene finding a list of putative open reading frames was generated for which an oligonucleotide probe set was designed using the probe design tool TherMODO (a thermodynamic model-based oligoset design optimizer). To evaluate the performance of the novel array design, microarrays carrying the oligo set were hybridized with samples from treatments with dithiothreitol (DTT) or a strain overexpressing the UPR transcription factor HAC1, both compared with a wild type strain in normal medium as untreated control. DTT treatment was compared with literature data for S. cerevisiae, and revealed similarities, but also important differences between the two yeast species. Overexpression of HAC1, the most direct control for UPR genes, resulted in significant new understanding of this important regulatory pathway in P. pastoris, and generally in yeasts.

Conclusion

The differences observed between P. pastoris and S. cerevisiae underline the importance of DNA microarrays for industrial production strains. P. pastoris reacts to DTT treatment mainly by the regulation of genes related to chemical stimulus, electron transport and respiration, while the overexpression of HAC1 induced many genes involved in translation, ribosome biogenesis, and organelle biosynthesis, indicating that the regulatory events triggered by DTT treatment only partially overlap with the reactions to overexpression of HAC1. The high reproducibility of the results achieved with two different oligo sets is a good indication for their robustness, and underlines the importance of less stringent selection of regulated features, in order to avoid a large number of false negative results.

Strong position-dependent effects of sequence mismatches on signal ratios measured using long oligonucleotide microarrays

Background

Microarrays are an important and widely used tool. Applications include capturing genomic DNA for high-throughput sequencing in addition to the traditional monitoring of gene expression and identifying DNA copy number variations. Sequence mismatches between probe and target strands are known to affect the stability of the probe-target duplex, and hence the strength of the observed signals from microarrays.

Results

We describe a large-scale investigation of microarray hybridisations to murine probes with known sequence mismatches, demonstrating that the effect of mismatches is strongly position-dependent and for small numbers of sequence mismatches is correlated with the maximum length of perfectly matched probe-target duplex. Length of perfect match explained 43% of the variance in log₂ signal ratios between probes with one and two mismatches. The correlation with maximum length of perfect match does not conform to expectations based on considering the effect of mismatches purely in terms of reducing the binding energy. However, it can be explained qualitatively by considering the entropic contribution to duplex stability from configurations of differing perfect match length.

Conclusion

The results of this study have implications in terms of array design and analysis. They highlight the significant effect that short sequence mismatches can have upon microarray hybridisation intensities even for long oligonucleotide probes.

All microarray data presented in this study are available from the GEO database [1], under accession number [GEO: GSE9669]

A study of the relationships between oligonucleotide properties and hybridization signal intensities from NimbleGen microarray datasets

Well-defined relationships between oligonucleotide properties and hybridization signal intensities (HSI) can aid chip design, data normalization and true biological knowledge discovery. We clarify these relationships using the data from two microarray experiments containing over three million probes from 48 high-density chips. We find that melting temperature (T_m) has the most significant effect on HSI while length for the long oligonucleotides studied has very little effect. Analysis of positional effect using a linear model provides evidence that the protruding ends of probes contribute more than tethered ends to HSI, which is further validated by specifically designed match fragment sliding and extension experiments. The impact of sequence similarity (SeqS) on HSI is not significant in comparison with other oligonucleotide properties. Using regression and regression tree analysis, we prioritize these oligonucleotide properties based on their effects on HSI. The implications of our discoveries for the design of unbiased oligonucleotides are discussed. We propose that isothermal probes designed by varying the length is a viable strategy to reduce sequence bias, though imposing selection constraints on other oligonucleotide properties is also essential.

Expression profiling of microRNA using oligo DNA arrays

After 12 years from its first application, microarray technology has become the reference technique to monitor gene expression of thousands of genes in the same experiment. In the past few years an increasing amount of evidence showed the importance of non-coding RNA (ncRNA) in different human diseases. The microRNAs (miRNAs) are one of the groups of ncRNA. They are small RNA fragments, 19-25 nucleotides long, with a main regulatory function on both protein coding genes and non-coding RNAs. The application of microarray platforms applied to miRNA profiling determined their deregulation in virtually all human diseases that have been studied. We previously developed a custom miRNA microarray platform, and here we describe the protocol we used to work with it including the oligo design strategy, the microarray printing protocol, the target-probe hybridization and the signal detection.

Genome-wide analysis of DNA methylation patterns

Cytosine methylation is the most common covalent modification of DNA in eukaryotes. DNA methylation has an important role in many aspects of biology, including development and disease. Methylation can be detected using bisulfite conversion, methylation-sensitive restriction enzymes, methyl-binding proteins and anti-methylcytosine antibodies. Combining these techniques with DNA microarrays and high-throughput sequencing has made the mapping of DNA methylation feasible on a genome-wide scale. Here we discuss recent developments and future directions for identifying and mapping methylation, in an effort to help colleagues to identify the approaches that best serve their research interests.

[4] Use of External Controls in Microarray Experiments

DNA microarray analysis has become the most widely used technique for the study of gene expression patterns on a genomic scale. Microarray analysis is a complex technique involving many steps, and a number of commercial and in-house developed arrays and protocols for data collection and analysis are used in different laboratories. Inclusion of external or spike-in RNA controls allows one to evaluate the variability in gene expression measurements and to facilitate the comparison of data collected using different platforms and protocols. This chapter describes what external controls are, which collections of spike-in controls are available to researchers, and how they are implemented in the laboratory. Applications of external controls in the assessment of microarray performance, normalization strategies, the evaluation of algorithms for gene expression analysis, and the potential to quantify absolute mRNA levels are discussed.

[8] Printing Your Own Inkjet Microarrays

DNA arrays are now the tools of choice for high-throughput DNA/RNA analysis. While many technologies exist for mass-producing arrays, there are just a few ways to economically produce small batches of custom oligonucleotide arrays for prototyping experiments and specialized applications. Inkjet printing, adapted from the world of office electronics to the world of molecular biology, is one such method. With programmable oligonucleotide synthesizers, scientists can prototype DNA array assays quickly and inexpensively. A benchtop inkjet arrayer-nicknamed POSAM-can be built by most skilled molecular biology laboratories. Inkjet arrays can fulfill the changing needs of those studying the complex network of relationships in systems biology.