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Research | Open Access

Characterization of novel microsatellite markers of the Emei Shan Liocichla using restriction site-associated DNA sequencing

Ailin Yang1De Chen1Pengcheng Wang1Yiqiang Fu2( )Zhengwang Zhang ( )
Ministry of Education Key Laboratory for Biodiversity and Ecological Engineering, College of Life Sciences, Beijing Normal University, Beijing 100875, China
College of Life Sciences, Leshan Normal University, Leshan, Sichuan 614000, China
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Abstract

Background

The Emei Shan Liocichla (Liocichla omeiensis) is an endemic bird species to southwestern China with a small geographic range. However, little was known about the genetic status of this threatened species.

Methods

We applied restriction-site-associated DNA sequencing (RAD-Seq) for rapid mass identification of microsatellite markers of the Emei Shan Liocichla.

Results

A total of 11, 564 microsatellite sequences were obtained, 600 random loci were designed for screening and 24 polymorphic microsatellite loci were selected for further validation. The average allele number, average observed heterozygosity and average expected heterozygosity were relatively low in our samples, which were 6.08, 0.6618 and 0.7048, respectively, indicating that the Emei Shan Liocichla might have lost some genetic diversity. Further analyses suggested that the populations distributed on two mountains (Daxiangling and Xiaoliangshan) showed a modest degree of genetic differentiation.

Conclusions

These novel microsatellite markers provided valuable preliminary knowledge regarding the genetic status of the Emei Shan Liocichla and can be useful in further studies, as well as in the management and conservation of this species.

References

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Avian Research
Article number: 13

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Cite this article:
Yang A, Chen D, Wang P, et al. Characterization of novel microsatellite markers of the Emei Shan Liocichla using restriction site-associated DNA sequencing. Avian Research, 2017, 8(1): 13. https://doi.org/10.1186/s40657-017-0071-8

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Received: 26 February 2017
Accepted: 18 May 2017
Published: 26 May 2017
© The Author(s) 2017.

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.