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The electronic form of this document may be cited in the following style:
Human Genome Program, U.S. Department of Energy, DOE Human Genome Program Contractor-Grantee Workshop IV, 1994.

Abstracts scanned from text submitted for November 1994 DOE Human Genome Program Contractor-Grantee Workshop. Inaccuracies have not been corrected.

Efficient Pooling of YAC Libraries

David J. Balding[1], David C. Bruce, William J. Bruno, Norman A. Doggett, Emanuel Knill, David C. Torney, and Clive C. Whittaker
Center for Human Genome Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, USA; [1]Queen Mary and Westfield College, University of London, London, UK.

We have developed general methods for designing and implementing pooling experiments for YAC libraries of all sizes and coverages, primarily for repeated STS screening. Conventional pooling uses variations of multi-tiered row-and-column pools. Although implementation and interpretation of row-and-column pools is straightforward, we propose more efficient designs.

We have implemented combinatorial algorithms which can optimize pooling experiments, even the costs of constructing pools, testing pools and confirming candidate-positive clones. Random k-sets designs are particularly effective in minimizing the total number of pools. In random k-sets designs, every clone occurs in k of the pools, and the pool assays are performed in one pass. We show how to evaluate the expected number of definite-positive clones--clones which must be positive based upon the pool assays--given the number of positive clones is binomially distributed. The parameter k can be chosen to maximize this expectation. For example, if a 33,000 clone library with tenfold coverage were pooled using a random ten-sets design with 170 pools, then approximately half of the positive clones would be definite-positive. If one used a random ten-sets design on 253 pools, then approximately 95 percent of the positive clones would be definite-positive. Random k-sets designs have no a priori constraints on the number of pools or clones; they are easily generated on a computer. Furthermore, they can be designed to correct for false-negative and other pool-assay errors.

In addition, we can often get improved performance if there is an upper bound on the number of pools in which any two clones coincide. When each clone occurs in k pools, such designs are referred to as k-sets packings. We compare the performance of our designs and other implemented designs.

The implementation of efficient pooling strategies requires the use of robots. We are using commercially available system (Packard multiPROBE 204) to pool two ~1300 clone YAC libraries using optimized random four-sets designs. Using one robot, one of these libraries can be pooled into 47 pools in about 11 hours, with every clone occurring in four pools. Our first STS assay yielded the correct PCR product in eight of ten pools known to contain a positive clone. We have developed effective techniques for ranking the candidate-positive clones when the rates of false-negative and false-positive pool assays are appreciable; this work is described in detail in a separate abstract. Here we note that random k-set designs can be efficient even with typical error rates.