Nucleic Acids Research, 1994, Vol. 22, No. 22 4828-4836
© 1994
COMPUTATIONAL BIOLOGY |
A method for fast database search for all k-nucleotide repeats
Department of Mathematics DRB 155, 1024 W. 36th Pl., Los Angeles, CA 90089–1113, USA 1Department of Mathematics and Department of Molecular Biology, University of Southern California DRB 155, 1024 W. 36th Pl., Los Angeles, CA 90089–1113, USA
*To whom correpsondence should be addressed at: Department of Biomathematical Sciences, Box 1023, The Mount Sinai Medical Center, One Gustave L. Levy Place, New York, NY 10029-6574, USA
Received April 14, 1994. Revised June 24, 1994. Accepted August 15, 1994.
A significant portion of DNA consists of repeating patterns of various sizes, from very small (one, two and three nucleotides) to very large (over 300 nucleotides). Although the functions of these repeating regions are not well understood, they appear important for understanding the expression, regulation and evolution of DNA. For example, increases in the number of trinucleotide repeats have been associated with human genetic disease, including Fragile-X mental retardation and Huntington's disease. Repeats are also useful as a tool in mapping and identifying DNA; the number of copies of a particular pattern at a site is often variable among individuals (polymorphic) and is therefore helpful in locating genes via linkage studies and also in providing DNA fingerprints of individuals. The number of repeating regions is unknown as is the distribution of pattern sizes. It would be useful to search for such regions in the DNA database in order that they may be studied more fully. The DNA database currently consists of approximately 150 million basepairs and is growing exponentially. Therefore, any program to look for repeats must be efficient and fast. In this paper, we present some new techniques that are useful in recognizing repeating patterns and describe a new program for rapidly detecting repeat regions in the DNA database where the basic unit of the repeat has size up to 32 nucleotides. It is our hope that the examples in this paper will illustrate the unrealized diversity of repeats in DNA and that the program we have developed will be a useful tool for locating new and interesting repeats.
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