Please use this identifier to cite or link to this item:
Type of publication: Straipsnis Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or / and Scopus (S1)
Field of Science: Miškotyra / Forestry (A004)
Author(s): Danusevičius, Darius;Kavaliauskas, Darius;Fussi, Barbara
Title: Optimum Sample Size for SSR-based Estimation of Representative Allele Frequencies and Genetic Diversity in Scots Pine Populations
Is part of: Baltic Forestry. Girionys : Lithuanian Forest Research Institute et all, 2016, Vol. 22, N 2
Extent: p. 194-202
Date: 2016
Keywords: Differentiation;Sampling;SSR;Genetic diversity;Pinus sylvestris
Abstract: We used the random subsampling approach based on the empirical data to identify the representative sample size for accurate estimates of allele frequencies within a population. The empirical data consisted of 12 nuclear microsatellite marker scores for 400 individuals sampled within 1 ha area in a representative natural stand of Scots pine. For each sample size, 100 resampled subsets were randomly drawn (without replacement). The sample size, at which 95 % of the resampled subsets contained all the alleles at a given frequency present in the empirical data set, was considered as a 95 % probability of sampling these alleles. The resampled subsets were also used to calculate main genetic diversity parameters and their variances to be used as a measure of accuracy of sampling. The results showed that at the 95 % probability level, the sample sizes of 20-25 and 65-80 individuals were large enough to capture all the alleles at frequency above 0.05 and 0.01-0.05, respectively. 300-350 individuals were required to sample the alleles at frequencies below 0.01 at the 95 % probability. The upper bound of the sample sizes was required for the loci exhibiting high He values (>0.80)
Affiliation(s): Lietuvos agrarinių ir miškų mokslų centras Miškų institutas
Vytauto Didžiojo universitetas
Žemės ūkio akademija
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

Files in This Item:
marc.xml8.12 kBXMLView/Open

MARC21 XML metadata

Show full item record
Export via OAI-PMH Interface in XML Formats
Export to Other Non-XML Formats

CORE Recommender

Citations 5

checked on Feb 27, 2021

Page view(s)

checked on Aug 17, 2019

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.