Background Successful microarray experimentation requires a complex interplay between the slide

Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the 140147-77-9 manufacture DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a) a measure of variability in the signal intensities, b) a measure of the signal dynamic range and c) a measure of 140147-77-9 manufacture variability of the spot morphologies. Background Microarray production efforts require manipulations such as probe desiccation and reconstitution in print buffers, which become increasingly cumbersome with extended library sets. Once a particular print buffer composition has been selected, and the probe library is reconstituted in this solution, switching to an alternate buffer may require further cDNA amplifications or oligonucleotide syntheses to generate additional probes. It is undesirable to waste probe material evaluating immobilization chemistries yet optimization experiments are almost always required [1-4]. As novel slide and print chemistries emerge, in addition 140147-77-9 manufacture to advances in robotic dispensing systems, a thorough evaluation of the best combination of reagents and hardware should be considered before committing the probe collection to the spotting process. This is best achieved through the use of a microarray control set. A robust microarray control set should a) be easy to implement, b) be applicable to a wide variety of spotting robots, capillary pins and slide chemistries and provide a quality metric for all aspects of a microarray study including array fabrication, c) provide strong signal intensity to every probe on the array thereby facilitating accurate spot-finding, d) be reproducible, facilitating comparison of datasets from different users and laboratories, and e) measure signal intensity over a dynamic range [5]. Researchers typically prepare their own control sets. One example is the AFGC Microarray Control Set [6]. Commercial control sets have Rabbit Polyclonal to GK2 also been developed including, The Lucidea Microarray Score Card (Amersham Biosciences) and the SpotReport (Stratagene Inc., La Jolla, CA). These control sets have limited utility for evaluating the parameters in array fabrication, where uniform signal intensity across a given probe concentration is required. In the present approach we describe a ‘microarray meter’ which addresses the issues (a-e) outlined above. The probes are engineered with a universal sequence and printed across a defined concentration range, which provides a measure of the amount of DNA required with specific slide chemistries. Two fluorescent labeled targets are hybridized concurrently, a homogenous universal reference labeled with Cy3 and a pool of Cy5 labeled B. subtilis mRNAs, which serve as a control to measure signal intensity across a dynamic range. The reference allows assessment of spot detection and feature quality control, whereas the bacterial sequences monitor experimental dynamic range. In this study we applied the microarray meter tool to monitor the efficiency of array fabrication for three commercial microarray spotting robots paired with different capillary pin combinations. The microarray meter tool also permitted an evaluation of different slide and hybridization chemistries, further optimizing experimental conditions prior to the fabrication of high density arrays. Development of the microarray meter targets and probes The microarray meter consists of nucleic acid targets (reference and dynamic range control) and probe components. 140147-77-9 manufacture The first target component is a homogenous Synthetic Universal Amplicon (SUA) reference target, created as outlined in Figure ?Figure1.1. The second component comprises a series of dynamic range controls whose sequences are derived from Bacillus subtilis. These bacterial sequences were transcribed in vitro and each individually labeled with Cy5 (Table ?(Table1).1). After labeling,.

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