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Genetic structure of ural populations of Larix sibirica Ledeb. on the base of analysis of nucleotide polymorphism Cover

Genetic structure of ural populations of Larix sibirica Ledeb. on the base of analysis of nucleotide polymorphism

Open Access
|Apr 2020

Abstract

Research on the state and dynamics of the gene pool (an important natural resource that determines the potential fitness of living organisms and, ultimately, their long-term survival) becomes an important problem in the context of increased anthropogenic environmental impact. They are especially important for key species of ecosystems of a global scale importance. Larix sibirica Ledeb., which spreads from the Western Siberia to the Russian North-West, is one of such forest tree species. We identified patterns of genetic structure of populations on the example of the species’ Western race on the Middle and Northern Urals. The analysis of nucleotide polymorphism of genes of ABA-inducible protein, MADS-box-transcription factor and of 4-kumarat: CoA ligase (a part of the gene) was used as a method. Evidences were obtained that a part of the populations previously formed a single large population. At the same time, populations with different gene pools were found. As a result, differences between populations within the region were more pronounced (fixation index FST = -0.021 – 0.260, total haplotype diversity Hd = 0.636 – 0.911; nucleotide diversity π = 0.005 – 0.009; number of mutations θW = 0.005 – 0.012) than in other parts of the race. Causes of this phenomenon are discussed. It was concluded that the larch forests with a unique gene pool and/or high genetic diversity should be objects of population-oriented forestry and conservation.

DOI: https://doi.org/10.2478/sg-2020-0004 | Journal eISSN: 2509-8934 | Journal ISSN: 0037-5349
Language: English
Page range: 20 - 28
Published on: Apr 6, 2020
Published by: Johann Heinrich von Thünen Institute
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2020 Yu. S. Vasilyeva, A. A. Zhulanov, S. V. Boronnikova, Yu. A. Yanbaev, published by Johann Heinrich von Thünen Institute
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.