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Open Access Methodology article

Amplified fragment length homoplasy: in silico analysis for model and non-model species

Margot Paris*, Benjamin Bonnes, Gentile Francesco Ficetola, Bénédicte N Poncet and Laurence Després

Author Affiliations

Laboratoire d'Ecologie Alpine, CNRS-UMR 5553, Université Joseph Fourier, BP 53, 38041 Grenoble Cedex 09, France

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BMC Genomics 2010, 11:287  doi:10.1186/1471-2164-11-287

Published: 7 May 2010

Abstract

Background

AFLP markers are widely used in evolutionary genetics and ecology. However the frequent occurrence of non-homologous co-migrating fragments (homoplasy) both at the intra- and inter-individual levels in AFLP data sets is known to skew key parameters in population genetics. Geneticists can take advantage of the growing number of full genome sequences available for model species to study AFLP homoplasy and to predict it in non-model species.

Results

In this study we performed in silico AFLPs on the complete genome of three model species to predict intra-individual homoplasy in a prokaryote (Bacillus thuringiensis ser. konkukian), a plant (Arabidopsis thaliana) and an animal (Aedes aegypti). In addition, we compared in silico AFLPs to empirical data obtained from three related non-model species (Bacillus thuringiensis ser. israelensis, Arabis alpina and Aedes rusticus). Our results show that homoplasy rate sharply increases with the number of peaks per profile. However, for a given number of peaks per profile, genome size or taxonomical range had no effect on homoplasy. Furthermore, the number of co-migrating fragments in a single peak was dependent on the genome richness in repetitive sequences: we found up to 582 co-migrating fragments in Ae. aegypti. Finally, we show that in silico AFLPs can help to accurately predict AFLP profiles in related non-model species.

Conclusions

These predictions can be used to tackle current issues in the planning of AFLP studies by limiting homoplasy rate and population genetic estimation bias. ISIF (In SIlico Fingerprinting) program is freely available at http://www-leca.ujf-grenoble.fr/logiciels.htm webcite.