Genetic diversity and differentiation of Siberian spruce populations at nuclear microsatellite loci

Genetic diversity and differentiation of Siberian spruce populations at nuclear microsatellite loci The results of the study of 21 populations of Siberian spruce (Picea obovata Ledeb.) from different parts of the species natural range by microsatellite (SSR) analysis of nuclear DNA are presented. Using nine loci developed for Picea abies (L.) Karst. and Picea glauca (Moench) Voss and detecting variation in Picea obovata, the parameters of intra- and interpopulation genetic diversity, as well as the degree of population differentiation, were determined. It was demonstrated that the population of Siberian spruce in the study was characterized by a relatively high average level of intrapopulation variability (H o = 0.408; H e = 0.423) and low interpopulation differentiation (F st = 0.048, P = 0.001) at this class of DNA markers. The genetic distance between populations ranged from 0.009 to 0.167, averaging 0.039. The isolated Magadan population, located in the extreme Northeast of Russia at a considerable distance from the main species range and characterized by the lowest genetic diversity among the studied populations, was maximally differentiated from the rest of the spruce populations. In addition, the steppe Ubukun population from Buryatia and the population from the Bogd Khan Uul Biosphere Reserve, Mongolia, were considerably different in the genetic structure from most populations of Siberian spruce, although to a lesser extent than the Magadan population. These findings are consistent with the results of previous studies of this species carried out using allozyme and microsatellite loci of chloroplast DNA and point to the prospects of using nuclear microsatellites as DNA markers to analyze the population genetic structure of Siberian spruce. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Russian Journal of Genetics Springer Journals

Genetic diversity and differentiation of Siberian spruce populations at nuclear microsatellite loci

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Publisher
Springer Journals
Copyright
Copyright © 2016 by Pleiades Publishing, Inc.
Subject
Biomedicine; Human Genetics; Animal Genetics and Genomics; Microbial Genetics and Genomics
ISSN
1022-7954
eISSN
1608-3369
D.O.I.
10.1134/S1022795416090088
Publisher site
See Article on Publisher Site

Abstract

The results of the study of 21 populations of Siberian spruce (Picea obovata Ledeb.) from different parts of the species natural range by microsatellite (SSR) analysis of nuclear DNA are presented. Using nine loci developed for Picea abies (L.) Karst. and Picea glauca (Moench) Voss and detecting variation in Picea obovata, the parameters of intra- and interpopulation genetic diversity, as well as the degree of population differentiation, were determined. It was demonstrated that the population of Siberian spruce in the study was characterized by a relatively high average level of intrapopulation variability (H o = 0.408; H e = 0.423) and low interpopulation differentiation (F st = 0.048, P = 0.001) at this class of DNA markers. The genetic distance between populations ranged from 0.009 to 0.167, averaging 0.039. The isolated Magadan population, located in the extreme Northeast of Russia at a considerable distance from the main species range and characterized by the lowest genetic diversity among the studied populations, was maximally differentiated from the rest of the spruce populations. In addition, the steppe Ubukun population from Buryatia and the population from the Bogd Khan Uul Biosphere Reserve, Mongolia, were considerably different in the genetic structure from most populations of Siberian spruce, although to a lesser extent than the Magadan population. These findings are consistent with the results of previous studies of this species carried out using allozyme and microsatellite loci of chloroplast DNA and point to the prospects of using nuclear microsatellites as DNA markers to analyze the population genetic structure of Siberian spruce.

Journal

Russian Journal of GeneticsSpringer Journals

Published: Nov 24, 2016

References

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