Data from amplified fragment length polymorphism (AFLP) markers show indication of size homoplasy and of a relationship between degree of homoplasy and fragment size

Abstract

We investigate the distribution of sizes of fragments obtained from the amplified fragment length polymorphism (AFLP) marker technique. We find that empirical distributions obtained in two plant species, Phaseolus lunatus and Lolium perenne, are consistent with the expected distributions obtained from analytical theory and from numerical simulations. Our results indicate that the size distribution is strongly asymmetrical, with a much higher proportion of small than large fragments, that it is not influenced by the number of selective nucleotides nor by genome size but that it may vary with genome-wide GC-content, with a higher proportion of small fragments in cases of lower GC-content when considering the standard AFLP protocol with the enzyme MseI. Results from population samples of the two plant species show that there is a negative relationship between AFLP fragment size and fragment population frequency. Monte Carlo simulations reveal that size homoplasy, arising from pulling together nonhomologous fragments of the same size, generates patterns similar to those observed in P. lunatus and L. perenne because of the asymmetry of the size distribution. We discuss the implications of these results in the context of estimating genetic diversity with AFLP markers.

Genetic and epigenetic divergence between disturbed and undisturbed subpopulations of a Mediterranean shrub: a 20‐year field experiment

“…Only fragments ≥150 base pairs in size were considered to reduce possible biases arising from size homoplasy (Vekemans et al. 2002). AFLP genotyping error rates were determined for each primer combination by running repeated, independent analyses for 35 plants (23.5% of total), and estimated as the ratio of the number of discordant scores in the two analyses (all plants and markers combined) to the product of the number of plants by the number of scored markers.…”

Distinction between cultivated and wild chicory gene pools using AFLP markers

“…The table was then converted into a matrix where fragments were scored as either present (1) or absent (0). Using the software AFLP-SURV v1.0 (Vekemans et al 2002, available at http://www.ulb.ac.be/sciences/ lagev), estimates of pairwise relatedness coefficients (r) were calculated between individuals according to Lynch and Milligan (1994). A principal co-ordinate (PCO) analysis was performed based on this matrix using NTSys (Rohlf 2000) and the first two axes were plotted graphically.…”

Genetic structure of Aedes aegypti in the city of Córdoba (Argentina), a recently reinfested area

“…Ninety-five percent confidence intervals were calculated for H e values. These calculations were performed using the program AFLPsurv (Vekemans et al 2002).…”

“…These data were used to estimate allele frequencies, assuming that each RAPD band of a given molecular size was the product of a dominant allele at a given locus and that genotype frequencies at RAPD loci were in HardyWeinberg equilibrium, as demonstrated by de Sousa et al (2000). These calculations were performed with AFLPsurv (Vekemans et al 2002) using the Bayesian method with non-uniform prior distribution of allele frequencies. Zhivotovsky (1999) demonstrated that this method gives the most accurate estimation of allele frequencies for dominant markers.…”