Genetic diversity of the African poplar (Populus ilicifolia) populations in Kenya View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2016-08

AUTHORS

Sammy Muraguri Mutegi, Alice Muchugi, Sammy Carsan, Robert Kariba, Ramni Jamnadass, Phanuel Oballa, Amy M. Brunner, Steven Runo

ABSTRACT

We evaluated the genetic diversity of the African poplar (Populus ilicifolia) populations found in Kenya compared with reference samples of five poplar species from North America and one species introduced in Kenya from India (KEFRI-Kenya). Amplified fragment length polymorphism (AFLP) was used with the objective of providing important information for breeding and in situ/ex situ conservation of this species. Samples collected from three locations along the species’ natural range (Athi, Ewaso Nyiro, and Tana rivers) were compared with four samples of locally planted Populus deltoides stand introduced from India and ten reference samples from North America. Six AFLP primer combinations produced 521 clear bands for analysis. The percentage polymorphic loci were lowest in Tana (20.4 %) and highest in Athi (40.6 %). The average heterozygosity across the studied populations was between 0.07 and 0.3. AMOVA revealed more genetic variation partitioning within population (87 %; P < 0.01) than among populations (13 %; P < 0.01) suggesting significant genetic variation between populations. Further, UPGMA delineation showed two clusters of the Tana, Athi, and Ewaso Nyiro populations clustered together compared to the North America and India/KEFRI reference samples. Moreover, the study showed that the Athi population is more diverse than those of Tana and Ewaso Nyiro and may be important for conservation, domestication, and improvement studies. The genetic differentiation (FST = 0.134) among Kenyan P. ilicifolia populations suggests limited possibility of gene flow between these populations. More... »

PAGES

66

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11295-016-1013-z

DOI

http://dx.doi.org/10.1007/s11295-016-1013-z

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https://app.dimensions.ai/details/publication/pub.1040227398


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