GoArrays: highly dynamic and efficient microarray probe design

MOTIVATION: The use of oligonucleotide microarray technology requires a very detailed attention to the design of specific probes spotted on the solid phase. These problems are far from being commonplace since they refer to complex physicochemical constraints. Whereas there are more and more publicly available programs for microarray oligonucleotide design, most of them use the same algorithm or criteria to design oligos, with only little variation. RESULTS: We show that classical approaches used in oligo design software may be inefficient under certain experimental conditions, especially when dealing with complex target mixtures. Indeed, our biological model is a human obligate parasite, the microsporidia Encephalitozoon cuniculi. Targets that are extracted from biological samples are composed of a mixture of pathogen transcripts and host cell transcripts. We propose a new approach to design oligonucleotides which combines good specificity with a potentially high sensitivity. This approach is original in the biological point of view as well as in the algorithmic point of view. We also present an experimental validation of this new strategy by comparing results obtained with standard oligos and with our composite oligos. A specific E.cuniculi microarray will overcome the difficulty to discriminate the parasite mRNAs from the host cell mRNAs demonstrating the power of the microarray approach to elucidate the lifestyle of an intracellular pathogen using mix mRNAs

Seeds for effective oligonucleotide design

Background: DNA oligonucleotides are a very useful tool in biology. The best algorithms for designing good DNA oligonucleotides are filtering out unsuitable regions using a seeding approach. Determining the quality of the seeds is crucial for the performance of these algorithms.\ud Results: We present a sound framework for evaluating the quality of seeds for oligonucleotide design. The F-score is used to measure the accuracy of each seed. A number of natural candidates are tested: contiguous (BLAST-like), spaced, transitions-constrained, and multiple spaced seeds. Multiple spaced seeds are the best, with more seeds providing better accuracy. Single spaced and transition seeds are very close whereas, as expected, contiguous seeds come last. Increased accuracy comes at the price of reduced efficiency. An exception is that single spaced and transitions-constrained seeds are both more accurate and more efficient than contiguous ones.\ud Conclusions: Our work confirms another application where multiple spaced seeds perform the best. It will be useful in improving the algorithms for oligonucleotide desig

Dynamic probe selection for studying microbial transcriptome with high-density genomic tiling microarrays

<p>Abstract</p> <p>Background</p> <p>Current commercial high-density oligonucleotide microarrays can hold millions of probe spots on a single microscopic glass slide and are ideal for studying the transcriptome of microbial genomes using a tiling probe design. This paper describes a comprehensive computational pipeline implemented specifically for designing tiling probe sets to study microbial transcriptome profiles.</p> <p>Results</p> <p>The pipeline identifies every possible probe sequence from both forward and reverse-complement strands of all DNA sequences in the target genome including circular or linear chromosomes and plasmids. Final probe sequence lengths are adjusted based on the maximal oligonucleotide synthesis cycles and best isothermality allowed. Optimal probes are then selected in two stages - sequential and gap-filling. In the sequential stage, probes are selected from sequence windows tiled alongside the genome. In the gap-filling stage, additional probes are selected from the largest gaps between adjacent probes that have already been selected, until a predefined number of probes is reached. Selection of the highest quality probe within each window and gap is based on five criteria: sequence uniqueness, probe self-annealing, melting temperature, oligonucleotide length, and probe position.</p> <p>Conclusions</p> <p>The probe selection pipeline evaluates global and local probe sequence properties and selects a set of probes dynamically and evenly distributed along the target genome. Unique to other similar methods, an exact number of non-redundant probes can be designed to utilize all the available probe spots on any chosen microarray platform. The pipeline can be applied to microbial genomes when designing high-density tiling arrays for comparative genomics, ChIP chip, gene expression and comprehensive transcriptome studies.</p

Numerical ecology validates a biogeographical distribution and gender-based effect on mucosa-associated bacteria along the human colon

We applied constrained ordination numerical ecology methods to data produced with a human intestinal tract-specific phylogenetic microarray (the Aus-HIT Chip) to examine the microbial diversity associated with matched biopsy tissue samples taken from the caecum, transverse colon, sigmoid colon and rectum of 10 healthy patients. Consistent with previous studies, the profiles revealed a marked intersubject variability; however, the numerical ecology methods of analysis allowed the subtraction of the subject effect from the data and revealed, for the first time, evidence of a longitudinal gradient for specific microbes along the colorectum. In particular, probes targeting Streptococcus and Enterococcus spp. produced strongest signals with caecal and transverse colon samples, with a gradual decline through to the rectum. Conversely, the analyses suggest that several members of the Enterobacteriaceae increase in relative abundance towards the rectum. These collective differences were substantiated by the multivariate analysis of quantitative PCR data. We were also able to identify differences in the microarray profiles, especially for the streptococci and Faecalibacterium prausnitzii, on the basis of gender. The results derived by these multivariate analyses are biologically intuitive and suggest that the biogeography of the colonic mucosa can be monitored for changes through cross-sectional and/or inception cohort studies