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Design optimization methods for genomic DNA tiling arrays.

Bertone, Paul (författare)
Yale University
Trifonov, Valery (författare)
Yale University
Rozowsky, Joel S (författare)
Yale University
visa fler...
Schubert, Falk (författare)
Yale University
Emanuelsson, Olof (författare)
Yale University
Karro, John (författare)
Yale University
Kao, Ming-Yang (författare)
Northwestern University
Snyder, Michael (författare)
Yale University
Gerstein, Mark (författare)
Yale University
visa färre...
 (creator_code:org_t)
2005-12-19
2006
Engelska.
Ingår i: Genome Research. - : Cold Spring Harbor Laboratory. - 1088-9051 .- 1549-5469. ; 16:2, s. 271-281
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • A recent development in microarray research entails the unbiased coverage, or tiling, of genomic DNA for the large-scale identification of transcribed sequences and regulatory elements. A central issue in designing tiling arrays is that of arriving at a single-copy tile path, as significant sequence cross-hybridization can result from the presence of non-unique probes on the array. Due to the fragmentation of genomic DNA caused by the widespread distribution of repetitive elements, the problem of obtaining adequate sequence coverage increases with the sizes of subsequence tiles that are to be included in the design. This becomes increasingly problematic when considering complex eukaryotic genomes that contain many thousands of interspersed repeats. The general problem of sequence tiling can be framed as finding an optimal partitioning of non-repetitive subsequences over a prescribed range of tile sizes, on a DNA sequence comprising repetitive and non-repetitive regions. Exact solutions to the tiling problem become computationally infeasible when applied to large genomes, but successive optimizations are developed that allow their practical implementation. These include an efficient method for determining the degree of similarity of many oligonucleotide sequences over large genomes, and two algorithms for finding an optimal tile path composed of longer sequence tiles. The first algorithm, a dynamic programming approach, finds an optimal tiling in linear time and space; the second applies a heuristic search to reduce the space complexity to a constant requirement. A Web resource has also been developed, accessible at http://tiling.gersteinlab.org, to generate optimal tile paths from user-provided DNA sequences.

Ämnesord

NATURVETENSKAP  -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)

Nyckelord

TRANSCRIPTION FACTOR-BINDING
GENE-EXPRESSION
SACCHAROMYCES-CEREVISIAE
OLIGONUCLEOTIDE ARRAYS
REPETITIVE ELEMENTS
CHIP-CHIP
SEQUENCES
SITES
IDENTIFICATION
HUMAN-CHROMOSOME-22

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