MProbe: computer aided probe design for oligonucleotide microarrays

The present work describes a complete probe design software system for oligonucleotide microarrays based on Kane's research on probe sensitivity and specificity (Kane's rule). Combining Kane's rule and traditional criteria for probe design we constructed MProbe, the software system for oligonucleotide microarrays using Java. The general criteria for probe design are: (1) probes may have different lengths that range from 20 to 100 bases; (2) they should have a similar melting temperature (Tm) or GC content; (3) they should not contain stable secondary structures; and (4) they abide by Kane's rule.     

Determinants of sensitivity and specificity in spotted DNA microarrays with unmodified oligonucleotides

DNA microarrays with unmodified oligonucleotides are a cost-effective alternative to cDNA microarrays. This study examined how purity, length, homology and GC content of the oligonucleotide probes influence the sensitivity and specificity of the method using cyanobacterial genes. Oligonucleotide purification by high pressure liquid chromatography was omitted without significant reduction in hybridization sensitivity. For two of three genes tested, a reduction in oligonucleotide length did not reduce hybridization sensitivity, and maximum sensitivity was achieved with probes that were 45 nt long. Oligonucleotide probes with 相似文献   

A Strategy to Optimize the Oligo-Probes for Microarray-based Detection of Viruses

DNA microarrays have been acknowledged to represent a promising approach for the detection of viral pathogens. However, the probes designed for current arrays could cover only part of the given viral variants, that could result in false-negative or ambiguous data. If all the variants are to be covered, the requirement for more probes would render much higher spot density and thus higher cost of the arrays. Here we have developed a new strategy for oligonucleotide probe design. Using type I human immunodeficiency virus (HIV-1) tat gene as an example, we designed the array probes and validated the optimized parameters in silico. Results show that the oligo number is significantly reduced comparing with the existing methods, while specificity and hybridization efficiency remain intact. The adoption of this method in reducing the oligo numbers could increase the detection capacity for DNA microarrays, and would significantly lower the manufacturing cost for making array chips.     

Detecting unknown sequences with DNA microarrays: explorative probe design strategies

Designing environmental DNA microarrays that can be used to survey the extreme diversity of microorganisms existing in nature, represents a stimulating challenge in the field of molecular ecology. Indeed, recent efforts in metagenomics have produced a substantial amount of sequence information from various ecosystems, and will continue to accumulate large amounts of sequence data given the qualitative and quantitative improvements in the next-generation sequencing methods. It is now possible to take advantage of these data to develop comprehensive microarrays by using explorative probe design strategies. Such strategies anticipate genetic variations and thus are able to detect known and unknown sequences in environmental samples. In this review, we provide a detailed overview of the probe design strategies currently available to construct both phylogenetic and functional DNA microarrays, with emphasis on those permitting the selection of such explorative probes. Furthermore, exploration of complex environments requires particular attention on probe sensitivity and specificity criteria. Finally, these innovative probe design approaches require exploiting newly available high-density microarray formats.     

A strategy to optimize the oligo-probes for microarray-based detection of viruses

DNA microarrays have been acknowledged to represent a promising approach for the detection of viral pathogens. However, the probes designed for current arrays could cover only part of the given viral variants, that could result in false-negative or ambiguous data. If all the variants are to be covered, the requirement for more probes would render much higher spot density and thus higher cost of the arrays. Here we have developed a new strategy for oligonucleotide probe design. Using type I human immunodeficiency virus (HIV-1) tat gene as an example, we designed the array probes and validated the optimized parameters in silico. Results show that the oligo number is significantly reduced comparing with the existing methods, while specificity and hybridization efficiency remain intact. The adoption of this method in reducing the oligo numbers could increase the detection capacity for DNA microarrays, and would significantly lower the manufacturing cost for making array chips. These authors contribute equally to the work.     

Empirical Evaluation of Oligonucleotide Probe Selection for DNA Microarrays

DNA-based microarrays are increasingly central to biomedical research. Selecting oligonucleotide sequences that will behave consistently across experiments is essential to the design, production and performance of DNA microarrays. Here our aim was to improve on probe design parameters by empirically and systematically evaluating probe performance in a multivariate context. We used experimental data from 19 array CGH hybridizations to assess the probe performance of 385,474 probes tiled in the Duchenne muscular dystrophy (DMD) region of the X chromosome. Our results demonstrate that probe melting temperature, single nucleotide polymorphisms (SNPs), and homocytosine motifs all have a strong effect on probe behavior. These findings, when incorporated into future microarray probe selection algorithms, may improve microarray performance for a wide variety of applications.     

Design of long oligonucleotide probes for functional gene detection in a microbial community

MOTIVATION: Analysis of the functions of microorganisms and their dynamics in the environment is essential for understanding microbial ecology. For analysis of highly similar sequences of a functional gene family using microarrays, the previous long oligonucleotide probe design strategies have not been useful in generating probes. RESULTS: We developed a Hierarchical Probe Design (HPD) program that designs both sequence-specific probes and hierarchical cluster-specific probes from sequences of a conserved functional gene based on the clustering tree of the genes, specifically for analyses of functional gene diversity in environmental samples. HPD was tested on datasets for the nirS and pmoA genes. Our results showed that HPD generated more sequence-specific probes than several popular oligonucleotide design programs. With a combination of sequence-specific and cluster-specific probes, HPD generated a probe set covering all the sequences of each test set. AVAILABILITY: http://brcapp.kribb.re.kr/HPD/     

A model of molecular interactions on short oligonucleotide microarrays

High-density short oligonucleotide microarrays have become a widely used tool for measuring gene expression on a large scale. However, details of the mechanism of binding on microarrays remain unclear. Short oligonucleotide probes currently synthesized on microarrays are often ineffective as a result of limited sequence specificity or low sensitivity. Here, we describe a model of binding interactions on microarrays that reveals how probe signals depend on probe sequences and why certain probes are ineffective. The model indicates that the amount of nonspecific binding can be estimated from a simple rule. Using this model, we have developed an improved measure of gene expression for use in data analysis.     

Selection of optimal oligonucleotide probes for microarrays using multiple criteria, global alignment and parameter estimation

The oligonucleotide specificity for microarray hybridization can be predicted by its sequence identity to non-targets, continuous stretch to non-targets, and/or binding free energy to non-targets. Most currently available programs only use one or two of these criteria, which may choose ‘false’ specific oligonucleotides or miss ‘true’ optimal probes in a considerable proportion. We have developed a software tool, called CommOligo using new algorithms and all three criteria for selection of optimal oligonucleotide probes. A series of filters, including sequence identity, free energy, continuous stretch, GC content, self-annealing, distance to the 3′-untranslated region (3′-UTR) and melting temperature (T_m), are used to check each possible oligonucleotide. A sequence identity is calculated based on gapped global alignments. A traversal algorithm is used to generate alignments for free energy calculation. The optimal T_m interval is determined based on probe candidates that have passed all other filters. Final probes are picked using a combination of user-configurable piece-wise linear functions and an iterative process. The thresholds for identity, stretch and free energy filters are automatically determined from experimental data by an accessory software tool, CommOligo_PE (CommOligo Parameter Estimator). The program was used to design probes for both whole-genome and highly homologous sequence data. CommOligo and CommOligo_PE are freely available to academic users upon request.     

Selection of oligonucleotide probes for protein coding sequences

MOTIVATION: Large arrays of oligonucleotide probes have become popular tools for analyzing RNA expression. However to date most oligo collections contain poorly validated sequences or are biased toward untranslated regions (UTRs). Here we present a strategy for picking oligos for microarrays that focus on a design universe consisting exclusively of protein coding regions. We describe the constraints in oligo design that are imposed by this strategy, as well as a software tool that allows the strategy to be applied broadly. RESULT: In this work we sequentially apply a variety of simple filters to candidate sequences for oligo probes. The primary filter is a rejection of probes that contain contiguous identity with any other sequence in the sample universe that exceeds a pre-established threshold length. We find that rejection of oligos that contain 15 bases of perfect match with other sequences in the design universe is a feasible strategy for oligo selection for probe arrays designed to interrogate mammalian RNA populations. Filters to remove sequences with low complexity and predicted poor probe accessibility narrow the candidate probe space only slightly. Rejection based on global sequence alignment is performed as a secondary, rather than primary, test, leading to an algorithm that is computationally efficient. Splice isoforms pose unique challenges and we find that isoform prevalence will for the most part have to be determined by analysis of the patterns of hybridization of partially redundant oligonucleotides. AVAILABILITY: The oligo design program OligoPicker and its source code are freely available at our website.     

Position of the fluorescent label is a crucial factor determining signal intensity in microarray hybridizations

A key issue in applications of short oligonucleotide-based microarrays is how to design specific probes with high sensitivity. Some details of the factors affecting microarray hybridization remain unclear, hampering a reliable quantification of target nucleic acids. We have evaluated the effect of the position of the fluorescent label [position of label (POL)] relative to the probe-target duplex on the signal output of oligonucleotide microarrays. End-labelled single-stranded DNA targets of different lengths were used for hybridization with perfect-match oligonucleotide probe sets targeting different positions of the same molecule. Hybridization results illustrated that probes targeting the labelled terminus of the target showed significantly higher signals than probes targeting other regions. This effect was independent of the target gene, the fluorophore and the slide surface chemistry. Comparison of microarray signal patterns of fluorescently end-labelled, fluorescently internally random-labelled and radioactively end-labelled target-DNAs with the same set of oligonucleotide probes identified POL as a critical factor affecting signal intensity rather than binding efficiency. Our observations define a novel determinant for large differences of signal intensities. Application of the POL effect may contribute to better probe design and data interpretation in microarray applications.     

Probe selection algorithms with applications in the analysis of microbial communities

We propose two efficient heuristics for minimizing the number of oligonucleotide probes needed for analyzing populations of ribosomal RNA gene (rDNA) clones by hybridization experiments on DNA microarrays. Such analyses have applications in the study of microbial communities. Unlike in the classical SBH (sequencing by hybridization) procedure, where multiple probes are on a DNA chip, in our applications we perform a series of experiments, each one consisting of applying a single probe to a DNA microarray containing a large sample of rDNA sequences from the studied population. The overall cost of the analysis is thus roughly proportional to the number of experiments, underscoring the need for minimizing the number of probes. Our algorithms are based on two well-known optimization techniques, i.e. simulated annealing and Lagrangian relaxation, and our preliminary tests demonstrate that both algorithms are able to find satisfactory probe sets for real rDNA data.     

用于寡核苷酸探针设计的ARB软件

探针设计是制备高质量基因芯片的重中之重。ARB软件是用于设计系统发育芯片(Phylo Chip)探针的主要软件,然而由于安装困难、相关中文文章较少等原因,阻碍了其在国内的广泛使用。本文详细介绍了ARB软件的安装方法、探针设计及其他功能。这将有助于用户快速使用ARB软件进行探针设计,促进系统发育芯片的发展及其在各领域的应用。     

A fast and flexible approach to oligonucleotide probe design for genomes and gene families

MOTIVATION: With hundreds of completely sequenced microbial genomes available, and advancements in DNA microarray technology, the detection of genes in microbial communities consisting of hundreds of thousands of sequences may be possible. The existing strategies developed for DNA probe design, geared toward identifying specific sequences, are not suitable due to the lack of coverage, flexibility and efficiency necessary for applications in metagenomics. METHODS: ProDesign is a tool developed for the selection of oligonucleotide probes to detect members of gene families present in environmental samples. Gene family-specific probe sequences are generated based on specific and shared words, which are found with the spaced seed hashing algorithm. To detect more sequences, those sharing some common words are re-clustered into new families, then probes specific for the new families are generated. RESULTS: The program is very flexible in that it can be used for designing probes for detecting many genes families simultaneously and specifically in one or more genomes. Neither the length nor the melting temperature of the probes needs to be predefined. We have found that ProDesign provides more flexibility, coverage and speed than other software programs used in the selection of probes for genomic and gene family arrays. AVAILABILITY: ProDesign is licensed free of charge to academic users. ProDesign and Supplementary Material can be obtained by contacting the authors. A web server for ProDesign is available at http://www.uhnresearch.ca/labs/tillier/ProDesign/ProDesign.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Oligonucleotide fingerprint identification for microarray-based pathogen diagnostic assays

MOTIVATION: Advances in DNA microarray technology and computational methods have unlocked new opportunities to identify 'DNA fingerprints', i.e. oligonucleotide sequences that uniquely identify a specific genome. We present an integrated approach for the computational identification of DNA fingerprints for design of microarray-based pathogen diagnostic assays. We provide a quantifiable definition of a DNA fingerprint stated both from a computational as well as an experimental point of view, and the analytical proof that all in silico fingerprints satisfying the stated definition are found using our approach. RESULTS: The presented computational approach is implemented in an integrated high-performance computing (HPC) software tool for oligonucleotide fingerprint identification termed TOFI. We employed TOFI to identify in silico DNA fingerprints for several bacteria and plasmid sequences, which were then experimentally evaluated as potential probes for microarray-based diagnostic assays. Results and analysis of approximately 150 in silico DNA fingerprints for Yersinia pestis and 250 fingerprints for Francisella tularensis are presented. AVAILABILITY: The implemented algorithm is available upon request.     

A Java-based tool for the design of classification microarrays

Background  

Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria.     

ROSO: optimizing oligonucleotide probes for microarrays

ROSO is software to design optimal oligonucleotide probe sets for microarrays. Selected probes show no significant cross-hybridization, no stable secondary structures and their Tm are chosen to minimize the Tm variability of the probe set. AVAILABILITY: The program is available on the internet. Sources are freely available, for non-profit use, on request to the authors. Supplementary information: http://pbil.univ-lyon1.fr/roso     

Oligo Design: a computer program for development of probes for oligonucleotide microarrays

Oligonucleotide microarrays have demonstrated potential for the analysis of gene expression, genotyping, and mutational analysis. Our work focuses primarily on the detection and identification of bacteria based on known short sequences of DNA. Oligo Design, the software described here, automates several design aspects that enable the improved selection of oligonucleotides for use with microarrays for these applications. Two major features of the program are: (i) a tiling algorithm for the design of short overlapping temperature-matched oligonucleotides of variable length, which are useful for the analysis of single nucleotide polymorphisms and (ii) a set of tools for the analysis of multiple alignments of gene families and related short DNA sequences, which allow for the identification of conserved DNA sequences for PCR primer selection and variable DNA sequences for the selection of unique probes for identification. Note that the program does not address the full genome perspective but, instead, is focused on the genetic analysis of short segments of DNA. The program is Internet-enabled and includes a built-in browser and the automated ability to download sequences from GenBank by specifying the GI number. The program also includes several utilities, including audio recital of a DNA sequence (useful for verifying sequences against a written document), a random sequence generator that provides insight into the relationship between melting temperature and GC content, and a PCR calculator.