Volume 15, Issue 3 (12-2020)                   MGj 2020, 15(3): 191-202 | Back to browse issues page

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Asharioun A, Adavoudi R, Rezaei H, Khosravi R, Dibaj P, Ardani P et al . Evaluation of genetic diversity and estimation of probability of identity indices in brown bear in Parvar protected area. MGj. 2020; 15 (3) :191-202
URL: http://mg.genetics.ir/article-1-1602-en.html
University of Tehran
Abstract:   (468 Views)
In recent years, increase in human-induced habitat disturbances and illegal hunting have led to reduction and isolation of the remaining populations of the brown bear. Despite its ecological importance on the health of natural ecosystems, there is a data scarcity on the genetic diversity and kinship relationships between individuals in the remaining populations. Advances in the DNA extraction from non-invasive samples has facilitated genetic studies on vulnerable species. In the present study, we used non-invasive sampling methods to assess genetic diversity indices, the probability of genetic identity among individuals, and the number of unique genotypes in the samples in order to estimate the minimum number of brown bears in the Parvar protected area. A total of 10 microsatellites were amplified using the extracted DNA from non-invasive samples. The overall observed heterozygosity, expected heterozygosity, and polymorphic information content were estimated 0.51, 0.57, and 0.5 respectively. The probability of identity indices (i.e. PID sib and PID unbiased) were 0.078 and 0.0032 respectively. Also, a total of 19 unique genotypes were identified. Our results showed that despite the low quality of non-invasive extracted DNAs, the amplified microsatellites had statistically effectiveness in identifying samples, assessing probability of genetic identity, and estimating minimum population size. The adopted approach in the present study can be used as a guideline for estimating population size and evaluating kinship relationships between individuals, especially for threatened carnivores, using non-invasive sampling approach.
 
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Type of Study: Applicable | Subject: Subject 02
Received: 2019/11/7 | Accepted: 2020/09/22 | Published: 2020/12/27

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