Originally published as Genetics Published Articles Ahead of Print on September 19, 2005.

Genetics, Vol. 172, 639-646, January 2006, Copyright © 2006
doi:10.1534/genetics.105.044974

Modeling Population Genetic Data in Autotetraploid Species

Z. W. Luo*,{dagger},1, Ze Zhang*, R. M. Zhang{dagger}, Madhav Pandey{ddagger}, Oliver Gailing{ddagger}, Hans H. Hattemer{ddagger} and Reiner Finkeldey{ddagger}

* School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom, {dagger} Laboratory of Population and Quantitative Genetics, State Key Laboratory of Genetic Engineering, Fudan University, Shanghai 200433, China and {ddagger} Institute of Forest Genetics and Forest Tree Breeding, Faculty of Forest Science and Forest Ecology, University of Göttingen, Büsgenweg 2, D-37077 Göttingen, Germany

1 Corresponding author: School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom.
E-mail: z.w.luo{at}bham.ac.uk

Allozyme and PCR-based molecular markers have been widely used to investigate genetic diversity and population genetic structure in autotetraploid species. However, an empirical but inaccurate approach was often used to infer marker genotype from the pattern and intensity of gel bands. Obviously, this introduces serious errors in prediction of the marker genotypes and severely biases the data analysis. This article developed a theoretical model to characterize genetic segregation of alleles at genetic marker loci in autotetraploid populations and a novel likelihood-based method to estimate the model parameters. The model properly accounts for segregation complexities due to multiple alleles and double reduction at autotetrasomic loci in natural populations, and the method takes appropriate account of incomplete marker phenotype information with respect to genotype due to multiple-dosage allele segregation at marker loci in tetraploids. The theoretical analyses were validated by making use of a computer simulation study and their utility is demonstrated by analyzing microsatellite marker data collected from two populations of sycamore maple (Acer pseudoplatanus L.), an economically important autotetraploid tree species. Numerical analyses based on simulation data indicate that the model parameters can be adequately estimated and double reduction is detected with good power using reasonable sample size.




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