Abstract
We describe the theoretical basis of an approach using microarrays of probes and libraries of BACs to construct maps of the probes, by assigning relative locations to the probes along the genome. The method depends on several hybridization experiments: in each experiment, we sample (with replacement) a large library of BACs to select a small collection of BACs for hybridization with the probe arrays. The resulting data can be used to assign a local distance metric relating the arrayed probes, and then to position the probes with respect to each other. The method is shown to be capable of achieving surprisingly high accuracy within individual contigs and with less than 100 microarray hybridization experiments even when the probes and clones number about 105, thus involving potentially around 1010 individual hybridizations.
This approach is not dependent upon existing BAC contig information, and so should be particularly useful in the application to previously uncharacterized genomes. Nevertheless, the method may be used to independently validate a BAC contig map or a minimal tiling path obtained by intensive genomic sequence determination.
We provide a detailed probabilistic analysis to characterize the outcome of a single hybridization experiment and what information can be garnered about the physical distance between any pair of probes. This analysis then leads to a formulation of a likelihood optimization problem whose solution leads to the relative probe locations. After reformulating the optimization problem in a graphtheoretic setting and by exploiting the underlying probabilistic structure, we develop an efficient approximation algorithm for our original problem. We have implemented the algorithm and conducted several experiments for varied sets of parameters. Our empirical results are highly promising and are reported here as well. We also explore how the probabilistic analysis and algorithmic efficiency issues affect the design of the underlying biochemical experiments.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
F. Alizadeh, R.M. Karp, D.K. Weisser, and G. Zweig. “Physical Mapping of Chromosomes Using Unique Probes,” Journal of Computational Biology, 2(2):159–185, 1995.
E. Barillot, J. Dausset, and D. Cohen. “Theoretical Analysis of a Physical Mapping Strategy Using Random Single-Copy Landmarks,” Journal of Computational Biology, 2(2): 159–185, 1995.
A. Ben-Dor and B. Chor. “On constructing radiation hybrid maps,” Proceedings of the First International Conference on Computational Molecular Biology, 17–26, 1997
H. Chernoff. “A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations,” Annals of Mathematical Statistics, 23:483–509, 1952.
R. Drmanac et al., “DNA sequence determination by hybridization: a strategy for efficient large-scale sequencing,” Science, 163(5147):596, Feb 4, 1994.
P.W. Goldberg, M.C. Golumbic, H. Kaplan, and R. Shamir. “Four Strikes Against Physical Mapping of DNA,” Journal of Computational Biology, 2(1): 139–152, 1995.
D. Greenberg and S. Istrail. “Physical mapping by STS hybridization: Algorithmic strategies and the challenge of software evaluation,” Journal of Computational Biology, 2(2):219–273, 1995.
J. Hℴastad, L. Ivansson, J. Lagergren, “Fitting Points on the Real Line and its Application to RH Mapping,” Lecture Notes in Computer Science, 1461:465–467, 1998.
N. Lisitsyn and M. Wigler, “Cloning the differences between two complex genomes”, Science, 258:946–951, 1993.
R. Lucito, J. West, A. Reiner, J. Alexander, D. Esposito, B. Mishra, S. Powers, L. Norton, and M. Wigler, “Detecting Gene Copy Number Fluctuations in Tumor Cells by Microarray Analysis of Genomic Representations,” Genome Research, 10(11): 1726–1736, 2000.
M.J. Palazzolo, S.A. Sawyer, C.H. Martin, D.A. Smoller, and D.L. Hartl “Optimized Strategies for Sequence-Tagged-Site Selection in Genome Mapping,” Proc. Natl. Acad. Sci. USA, 88(18):8034–8038, 1991.
D. Slonim, L. Kruglyak, L. Stein, and E. Lander, “Building human genome maps with radiation hybrids,” Journal of Computational Biology, 4(4):487–504, 1997.
R. E. Tarjan. Data Structures and Network Algorithms, CBMS 44 SIAM, Philadelphia, 1983.
D.C. Torney, “Mapping Using Unique Sequences,” J Mol Biol, 217(2):259–264, 1991.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Casey, W., Mishra, B., Wigler, M. (2001). Placing Probes along the Genome Using Pairwise Distance Data. In: Gascuel, O., Moret, B.M.E. (eds) Algorithms in Bioinformatics. WABI 2001. Lecture Notes in Computer Science, vol 2149. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44696-6_5
Download citation
DOI: https://doi.org/10.1007/3-540-44696-6_5
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42516-8
Online ISBN: 978-3-540-44696-5
eBook Packages: Springer Book Archive