Primique: automatic design of specific PCR primers for each sequence in a family

<p>Abstract</p> <p>Background</p> <p>In many contexts, researchers need specific primers for all sequences in a family such that each primer set amplifies only its target sequence and none of the others, e.g. to detect which transcription factor out of a family of very similar proteins that is present in a sample, or to design diagnostic assays for the identification of pathogen strains.</p> <p>Results</p> <p>This paper presents primique, a new graphical, user-friendly, fast, web-based tool which solves the problem: It designs specific primers for each sequence in an uploaded set. Further, a secondary set of sequences <it>not </it>to be amplified by any primer pair may be uploaded. Primers with high sequence similarity to non-target sequences are selected against. Lastly, the suggested primers may be checked against the National Center for Biotechnology Information databases for possible mis-priming.</p> <p>Conclusion</p> <p>Results are presented in interactive tables, and various primer properties are listed and displayed graphically. Any close match alignments can be displayed. Given 30 sequences, the running time of primique is about 20 seconds.</p> <p>primique can be reached via this web address: <url>http://cgi-www.daimi.au.dk/cgi-chili/primique/front.py</url></p

An efficient algorithm for the stochastic simulation of the hybridization of DNA to microarrays

<p>Abstract</p> <p>Background</p> <p>Although oligonucleotide microarray technology is ubiquitous in genomic research, reproducibility and standardization of expression measurements still concern many researchers. Cross-hybridization between microarray probes and non-target ssDNA has been implicated as a primary factor in sensitivity and selectivity loss. Since hybridization is a chemical process, it may be modeled at a population-level using a combination of material balance equations and thermodynamics. However, the hybridization reaction network may be exceptionally large for commercial arrays, which often possess at least one reporter per transcript. Quantification of the kinetics and equilibrium of exceptionally large chemical systems of this type is numerically infeasible with customary approaches.</p> <p>Results</p> <p>In this paper, we present a robust and computationally efficient algorithm for the simulation of hybridization processes underlying microarray assays. Our method may be utilized to identify the extent to which nucleic acid targets (e.g. cDNA) will cross-hybridize with probes, and by extension, characterize probe robustnessusing the information specified by MAGE-TAB. Using this algorithm, we characterize cross-hybridization in a modified commercial microarray assay.</p> <p>Conclusions</p> <p>By integrating stochastic simulation with thermodynamic prediction tools for DNA hybridization, one may robustly and rapidly characterize of the selectivity of a proposed microarray design at the probe and "system" levels. Our code is available at <url>http://www.laurenzi.net</url>.</p