An analysis of the pattern of genetic variation in Vitellaria paradoxa using RAPD markers

Vitellaria paradoxa C.F.Gaertn. is one of the most economically and socially important tree species in the Sudano-Sahelian region. Little is known of the pattern of variation within its natural range. Eight populations covering most of the natural range from Senegal to Uganda were sampled and leaves of 118 individual trees were collected. An analysis of molecular diversity was carried out using random amplified polymorphic DNA (RAPD) markers. Fifteen random primers generated 67 polymorphic and 15 monomorphic RAPD loci ranging from size 1670 bp to 280 bp. Shannon's diversity index varied from Central Africa/Ndele (0.374) to Uganda/Amoya (0.350) but the differences between populations were smaller than the population standard errors. Correspondence analysis of unrooted neighbour-joining trees suggested that genetic distances between populations were correlated with geographic distances. This trend was confirmed by a Mantel test giving a coefficient of correlation between genetic and geographic distances of R = 0.88 (P = 0.0001). Result of AMOVA (analyses of molecular variance) showed that 14.8% (P = 0.002) of the RAPD variation was distributed among populations. Nested analysis of variance indicated that variance between the western and eastern groups of population represented 8.7% (P = 0.001) of the total variation and the variation amongst populations within group was 9.5% (P = 0.001). Eighty two percent of the variation was explained by variation amongst individuals within populations. The origin of genetic structure and level of diversity may be explained by the glacial refugia, the biological traits of Vitellaria paradoxa and by the impact of semi-domestication. Based on these results, sampling options of the natural populations are suggested for in or ex situ conservation. For the development of Vitellaria paradoxa breeding population, the sampling should consist of many individual trees selected within a few populations to capture a large proportion of variation.This revised version was published online in November 2005 with corrections to the Cover Date.