Decoding randomly ordered DNA arrays

We have developed a simple and efficient algorithm to identify each member of a large collection of DNA-linked objects through the use of hybridization, and have applied it to the manufacture of randomly assembled arrays of beads in wells. Once the algorithm has been used to determine the identity o...

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Bibliographic Details
Published in:	Genome research Vol. 14; no. 5; pp. 870 - 877
Main Authors:	Gunderson, Kevin L, Kruglyak, Semyon, Graige, Michael S, Garcia, Francisco, Kermani, Bahram G, Zhao, Chanfeng, Che, Diping, Dickinson, Todd, Wickham, Eliza, Bierle, Jim, Doucet, Dennis, Milewski, Monika, Yang, Robert, Siegmund, Chris, Haas, Juergen, Zhou, Lixin, Oliphant, Arnold, Fan, Jian-Bing, Barnard, Steven, Chee, Mark S
Format:	Journal Article
Language:	English
Published:	United States Cold Spring Harbor Laboratory Press 01-05-2004
Subjects:	Algorithms Computational Biology - methods Methods Oligonucleotide Array Sequence Analysis - methods Oligonucleotide Array Sequence Analysis - trends Random Allocation Research Design Sequence Analysis, DNA - methods Silicon Dioxide - chemistry
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Summary:	We have developed a simple and efficient algorithm to identify each member of a large collection of DNA-linked objects through the use of hybridization, and have applied it to the manufacture of randomly assembled arrays of beads in wells. Once the algorithm has been used to determine the identity of each bead, the microarray can be used in a wide variety of applications, including single nucleotide polymorphism genotyping and gene expression profiling. The algorithm requires only a few labels and several sequential hybridizations to identify thousands of different DNA sequences with great accuracy. We have decoded tens of thousands of arrays, each with 1520 sequences represented at approximately 30-fold redundancy by up to approximately 50,000 beads, with a median error rate of <1 x 10(-4) per bead. The approach makes use of error checking codes and provides, for the first time, a direct functional quality control of every element of each array that is manufactured. The algorithm can be applied to any spatially fixed collection of objects or molecules that are associated with specific DNA sequences.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 These authors contributed equally to this work. Corresponding author. E-MAIL mchee@illumina.com ; FAX (858) 202-4680. Article and publication are at http://www.genome.org/cgi/doi/10.1101/gr.2255804. Article published online before print in April 2004.
ISSN:	1088-9051
DOI:	10.1101/gr.2255804