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Originally published as Genetics Published Articles Ahead of Print on June 11, 2007.

Genetics, Vol. 176, 2035-2054, August 2007, Copyright © 2007
doi:10.1534/genetics.107.074377

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Predicting the Size of the Progeny Mapping Population Required to Positionally Clone a Gene

Stephen J. Dinka*, Matthew A. Campbell{dagger}, Tyler Demers* and Manish N. Raizada*,1

* Department of Plant Agriculture, University of Guelph, Guelph, Ontario, Canada N1G 2W1 and {dagger} The Institute for Genomic Research, Rockville, MD, 20850

1 Corresponding author: Department of Plant Agriculture, University of Guelph, 50 Stone Rd., Guelph, Ontario, Canada N1G 2W1.
E-mail: Raizada{at}uoguelph.ca

A key frustration during positional gene cloning (map-based cloning) is that the size of the progeny mapping population is difficult to predict, because the meiotic recombination frequency varies along chromosomes. We describe a detailed methodology to improve this prediction using rice (Oryza sativa L.) as a model system. We derived and/or validated, then fine-tuned, equations that estimate the mapping population size by comparing these theoretical estimates to 41 successful positional cloning attempts. We then used each validated equation to test whether neighborhood meiotic recombination frequencies extracted from a reference RFLP map can help researchers predict the mapping population size. We developed a meiotic recombination frequency map (MRFM) for ~1400 marker intervals in rice and anchored each published allele onto an interval on this map. We show that neighborhood recombination frequencies (R-map, >280-kb segments) extracted from the MRFM, in conjunction with the validated formulas, better predicted the mapping population size than the genome-wide average recombination frequency (R-avg), with improved results whether the recombination frequency was calculated as genes/cM or kb/cM. Our results offer a detailed road map for better predicting mapping population size in diverse eukaryotes, but useful predictions will require robust recombination frequency maps based on sampling more progeny.






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Copyright © 2007 by the Genetics Society of America.