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Genetic Diversity and Population Structure of Acacia senegal (L) Willd. in Kenya
Authors:Stephen F Omondi  Eliud Kireger  Otto G Dangasuk  Ben Chikamai  David W Odee  Stephen Cavers  Damase P Khasa
Institution:1. Department of Forestry and Wood Science Technology, Moi University, P.O Box?1125, Eldoret, Kenya
3. Kenya Forestry Research Institute, P.O Box?20412-00200, Nairobi, Kenya
2. Department of Biological sciences, Moi University, P.O Box?1125, Eldoret, Kenya
4. NERC Centre for Ecology and Hydrology, Bush Estate, Penicuik, Midlothian, EH26 0QB, UK
5. Centre for Forest Research (CEF), Canada Research Chair in Forest and Environmental Genomics, Faculty of Forestry and Geomatics, Pavillon Eugene Marchand, Université Laval, Sainte-Foy, Québec, Canada, G1K 7P4
Abstract:The level of genetic diversity and population structure of Acacia senegal variety kerensis in Kenya was examined using seven polymorphic nuclear microsatellite loci and two chloroplast microsatellite loci. In both chloroplast and nuclear datasets, high levels of genetic diversity were found within all populations and genetic differentiation among populations was low, indicating extensive gene flow. Analysis of population structure provided support for the presence of two groups of populations, although all individuals had mixed ancestry. Groups reflected the influence of geography on gene flow, with one representing Rift Valley populations whilst the other represented populations from Eastern Kenya. The similarities between estimates derived from nuclear and chloroplast data suggest highly effective gene dispersal by both pollen and seed in this species, although population structure appears to have been influenced by distributional changes in the past. The few contrasts between the spatial patterns for nuclear and chloroplast data provided additional support for the idea that, having fragmented in the past, groups are now thoroughly mixed as a result of extensive gene flow. For the purposes of conservation and in situ management of genetic resources, sampling could target a few, large populations ideally distributed among the spatial groups identified. This should ensure the majority of extant variation is preserved, and facilitate the investigation of variation in important phenotypic traits and development of breeding populations.
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