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Title: Development of novel genic microsatellite markers from transcriptome sequencing in sugar maple (Acer saccharum Marsh.)
Authors: Harmon, Monica
Lane, Thomas
Staton, Margaret
Coggeshall, Mark V.
Best, Teodora
Chen, Chien-Chih
Liang, Haiying
Zembower, Nicole
Drautz-Moses, Daniela I.
Hwee, Yap Zhei
Schuster, Stephan C.
Schlarbaum, Scott E.
Carlson, John E.
Gailing, Oliver
Keywords: Acer Saccharum
Issue Date: 2017
Source: Harmon, M., Lane, T., Staton, M., Coggeshall, M. V., Best, T., Chen, C.-C., et al. (2017). Development of novel genic microsatellite markers from transcriptome sequencing in sugar maple (Acer saccharum Marsh.). BMC Research Notes, 10(1), 369-.
Series/Report no.: BMC Research Notes
Abstract: Background: Sugar maple (Acer saccharum Marsh.) is a hardwood tree species native to northeastern North America and economically valued for its wood and sap. Yet, few molecular genetic resources have been developed for this species to date. Microsatellite markers have been a useful tool in population genetics, e.g., to monitor genetic variation and to analyze gene flow patterns. The objective of this study is to develop a reference transcriptome and microsatellite markers in sugar maple. Findings: A set of 117,861 putative unique transcripts were assembled using 29.2 Gb of RNA sequencing data derived from different tissues and stress treatments. From this set of sequences a total of 1068 microsatellite motifs were identified. Out of 58 genic microsatellite markers tested on a population of 47 sugar maple trees in upper Michigan, 22 amplified well, of which 16 were polymorphic and 6 were monomorphic. Values for expected heterozygosity varied from 0.224 to 0.726 for individual loci. Of the 16 polymorphic markers, 15 exhibited transferability to other Acer L. species. Conclusions: Genic microsatellite markers can be applied to analyze genetic variation in potentially adaptive genes relative to genomic reference markers as a basis for the management of sugar maple genetic resources in the face of climate change.
DOI: 10.1186/s13104-017-2653-2
Rights: © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, 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 ( applies to the data made available in this article, unless otherwise stated.
Fulltext Permission: open
Fulltext Availability: With Fulltext
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