Genetics, Vol. 167, 1915-1928, August 2004, Copyright © 2004
doi:10.1534/genetics.103.015693

Significance Tests and Weighted Values for AFLP Similarities, Based on Arabidopsis in Silico AFLP Fragment Length Distributions

Wim J. M. Koopman*,1 and Gerrit Gort{dagger}

* Nationaal Herbarium Nederland—Wageningen Branch, Biosystematics Group, Wageningen University, 6703 BL Wageningen, The Netherlands
{dagger} Biometris, Wageningen University and Research Centre, 6700 AA, Wageningen, The Netherlands

1 Corresponding author: Plant Research International B.V., 6700 AA, Wageningen, The Netherlands.
E-mail: wim.koopman{at}wur.nl

Many AFLP studies include relatively unrelated genotypes that contribute noise to data sets instead of signal. We developed: (1) estimates of expected AFLP similarities between unrelated genotypes, (2) significance tests for AFLP similarities, enabling the detection of unrelated genotypes, and (3) weighted similarity coefficients, including band position information. Detection of unrelated genotypes and use of weighted similarity coefficients will make the analysis of AFLP data sets more informative and more reliable. Test statistics and weighted coefficients were developed for total numbers of shared bands and for Dice, Jaccard, Nei and Li, and simple matching (dis)similarity coefficients. Theoretical and in silico AFLP fragment length distributions (FLDs) were examined as a basis for the tests. The in silico AFLP FLD based on the Arabidopsis thaliana genome sequence was the most appropriate for angiosperms. The G + C content of the selective nucleotides in the in silico AFLP procedure significantly influenced the FLD. Therefore, separate test statistics were calculated for AFLP procedures with high, average, and low G + C contents in the selective nucleotides. The test statistics are generally applicable for angiosperms with a G + C content of ~35–40%, but represent conservative estimates for genotypes with higher G + C contents. For the latter, test statistics based on a rice genome sequence are more appropriate.




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