Parallel Syntenic Alignments

  • Natsuhiko Futamura
  • Srinivas Aluru
  • Xiaoqiu Huang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2552)


Given two genomic DNA sequences, the syntenic alignment problem is to compute an ordered list of subsequences for each sequence such that the corresponding subsequence pairs exhibit a high degree of similarity. Syntenic alignments are useful in comparing genomic DNA from related species andin identifying conservedgen es. In this paper, we present a parallel algorithm for computing syntenic alignments that runs in O(mn/p) time and O(m + n/p) memory per processor, where m and n are the respective lengths of the two genomic sequences. Our algorithm is time optimal with respect to the corresponding sequential algorithm and can use O(n/log n) processors, where n is the length of the larger sequence. Using an implementation of this parallel algorithm, we report the alignment of human chromosome 12p13 andit s syntenic region in mouse chromosome 6 (both over 220, 000 base pairs in length) in under 24 minutes on a 64-processor IBM xSeries cluster.


Parallel Algorithm Optimal Alignment Syntenic Region Human Chromosome 12p13 Special Column 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. [1]
    S. Aluru, N. Futamura and K. Mehrotra, Biological sequence comparison using prefix computations, Proc. International Parallel Processing Symposium (1999) 653–659. 420Google Scholar
  2. [2]
    M.A. Ansari-Lari, J.C. Oeltjen, S. Schwartz, Z. Zhang, D.M. Muzny, J. Lu, J.H. Gorrell, A. C. Chinault, J.W. Belmont, W. Miller and R. A. Gibbs, Comparative sequence analysis of a gene-rich cluster at human chromosome 12p13 and its syntenic region in mouse chromosome 6, Genome Research, 8 (1998) 29–40. 429Google Scholar
  3. [3]
    S. Batzoglou, L. Pachter, J. P. Mesirov, B. Berger and E. S. Lander, Human and mouse gene structure: comparative analysis andap plication to exon prediction, Genome Research, 10 (2000) 950–958. 421CrossRefGoogle Scholar
  4. [4]
    A.L. Delcher, S. Kasif, R.D. Fleischmann, J. Peterson, O. While and S.L. Salzberg, Alignment of whole genomes. Nucleic Acids Research, 27 (1999) 2369–2376. 421CrossRefGoogle Scholar
  5. [5]
    E.W. Edmiston and R.A. Wagner, Parallelization of the dynamic programming algorithm for comparison of sequences, Proc. International Conference on Parallel Processing (1987) 78–80. 420Google Scholar
  6. [6]
    E.W. Edmiston, N.G. Core, J. H. Saltz and R.M. Smith, Parallel processing of biological sequence comparison algorithms, International Journal of Parallel Programming, 17(3) (1988) 259–275. 420zbMATHCrossRefMathSciNetGoogle Scholar
  7. [7]
    O. Gotoh, An improvedalgorit hm for matching biological sequences. Journal of Molecular Biology, 162 (1982) 705–708. 420CrossRefGoogle Scholar
  8. [8]
    D. S. Hirschberg, A linear space algorithm for computing maximal common subsequences, Communications of the ACM, 18(6) (1975) 341–343. 423zbMATHCrossRefMathSciNetGoogle Scholar
  9. [9]
    X. Huang, A space-efficient parallel sequence comparison algorithm for a messagepassing multiprocessor, International Journal of Parallel Programming, 18(3) (1989) 223–239. 420CrossRefGoogle Scholar
  10. [10]
    X. Huang, A space-efficient algorithm for local similarities, Computer Applications in the Biosciences, 6(4) (1990) 373–381. 420Google Scholar
  11. [11]
    X. Huang and K. Chao, A generalized global alignement algorithm, manuscript in preparation. 421Google Scholar
  12. [12]
    N. Jareborg, E. Birney, and R. Durbin, Comparative analysis of noncoding regions of 77 orthologous mouse andh uman gene pairs, Genome Research, 9, (1999) 815–824. 421CrossRefGoogle Scholar
  13. [13]
    E. Lander, J.P. Mesirov and W. Taylor, Protein sequence comparison on a data parallel computer, Proc. International Conference on Parallel Processing (1988) 257–263. 420Google Scholar
  14. [14]
    E.W. Mayers and W. Miller, Optimal alignments in linear space, Computer Applications in the Biosciences, 4(1) (1988) 11–17. 420Google Scholar
  15. [15]
    S.B. Needleman and C. D. Wunsch, A general method applicable to the search for similarities in the amino acidseq uence of two proteins, Journal of Molecular Biology, 48 (1970) 443–453. 420CrossRefGoogle Scholar
  16. [16]
    S. Schwartz, Z. Zhang, K. Frazer, A. Smit, C. Riemer, J. Bouck, R. Gibbs, R. Hardison, and W. Miller, PipMaker-A web server for aligning two genomic DNA sequences, Genome Research, 10 (2000) 577–586. 421CrossRefGoogle Scholar
  17. [18]
    T. F. Smith and M. S. Waterman, Identification of common molecular subsequences, Journal of Molecular Biology, 147 (1981) 195–197. 420CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Natsuhiko Futamura
    • 1
  • Srinivas Aluru
    • 1
  • Xiaoqiu Huang
    • 1
  1. 1.Iowa State UniversityAmesUSA

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