Modelling and estimating pollen movement in oilseed rape (Brassica napus) at the landscape scale using genetic markers

被引:59
作者
Devaux, C.
Lavigne, C.
Austerlitz, F.
Klein, E. . K.
机构
[1] Univ Paris 11, CNRS, UMR 8079, Lab Ecol Systemat & Evolut,ENGREF, F-91405 Orsay, France
[2] INRA, Unite Rech Plantes & Syst Hort, F-84914 Avignon 9, France
[3] INRA, Unite Rech Biometrie, F-84914 Avignon 9, France
关键词
Brassica napus; dispersal kernels; long-distance pollination; mating models; microsatellite markers; TORMINALIS L. CRANTZ; PATERNITY ANALYSIS; HERBICIDE-RESISTANCE; WILDSERVICE TREE; LONG-DISTANCE; DISPERSAL; FLOW; POPULATION; TRANSGENE; FIELD;
D O I
10.1111/j.1365-294X.2006.03155.x
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Understanding patterns of pollen movement at the landscape scale is important for establishing management rules following the release of genetically modified (GM) crops. We use here a mating model adapted to cultivated species to estimate dispersal kernels from the genotypes of the progenies of male-sterile plants positioned at different sampling sites within a 10 x 10-km oilseed rape production area. Half of the pollen clouds sampled by the male-sterile plants originated from uncharacterized pollen sources that could consist of both large volunteer and feral populations, and fields within and outside the study area. The geometric dispersal kernel was the most appropriate to predict pollen movement in the study area. It predicted a much larger proportion of long-distance pollination than previously fitted dispersal kernels. This best-fitting mating model underestimated the level of differentiation among pollen clouds but could predict its spatial structure. The estimation method was validated on simulated genotypic data, and proved to provide good estimates of both the shape of the dispersal kernel and the rate and composition of pollen issued from uncharacterized pollen sources. The best dispersal kernel fitted here, the geometric kernel, should now be integrated into models that aim at predicting gene flow at the landscape level, in particular between GM and non-GM crops.
引用
收藏
页码:487 / 499
页数:13
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