Development of genomic microsatellite markers for Aconitum gymnandrum (Ranunculaceae) by next generation sequencing (NGS)

  • Meng Hou
  • Guo-zhen Du
  • Zhi-gang ZhaoEmail author
Short Communication


Mating plays key roles in the demographic and genetic dynamics of populations. Estimates of mating portfolios and system based on progeny array (PA) method required highly polymorphic genetic markers, of which microsatellite is a good choice. In this study, we reported 19 polymorphic microsatellite loci for Aconitum gymnandrum. The number of alleles per locus ranged from 2 to 12. Observed and expected heterozygosity ranged from 0.000 to 1.000 and from 0.219 to 0.842, respectively. Seven loci showed significant deviation from Hardy–Weinberg equilibrium. These markers will provide a useful tool for pollination ecology and population genetic studies of A. gymnandrum in Qinghai-Tibet plateau.


Microsatellite Aconitum gymnandrum Mating system Parentage analysis Genetic diversity 



This work is funded by National Key Research and Development Program of China (2017YFC0504801), Key Research Program of Gansu (18ZD2FA009) and the Natural Science Foundation of China (Grant Nos. 31370402, 31570229, 31870411) to Z.G. Zhao.

Compliance with ethical standards

Conflict of interest

The authors declare that they do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.


  1. 1.
    Goodwillie C, Kalisz S, Eckert CG (2005) The evolutionary enigma of mixed mating systems in plants: occurrence, theoretical explanations, and empirical evidence. Annu Rev Ecol Evol Syst 36:47–79CrossRefGoogle Scholar
  2. 2.
    Karron JD, Holmquist KG, Flanagan RJ, Mitchell RJ (2009) Pollinator visitation patterns strongly influence among-flower variation in selfing rate. Ann Bot 103:1379–1383CrossRefGoogle Scholar
  3. 3.
    Kalisz S, Randle A, Chaiffetz D, Faigeles M, Butera A, Beight C (2012) Dichogamy correlates with outcrossing rate and defines the selfing syndrome in the mixed-mating genus Collinsia. Ann Bot 109:571–582CrossRefGoogle Scholar
  4. 4.
    Xiao-Min Shang (1985) Chromosome studies of subgenus Gymnaconitum endemic to china and Beesia (Ranunculaceae). J Syst Evol 23(4):270–274Google Scholar
  5. 5.
    Wang LY, Abbott RJ, Zheng W, Chen P, Wang YJ, Liu JQ (2009) History and evolution of alpine plants endemic to the Qinghai-Tibetan Plateau: Aconitum gymnandrum (Ranunculaceae). Mol Ecol 18:709–721CrossRefGoogle Scholar
  6. 6.
    Zhao ZG, Meng JL, Fan BL, Du GZ (2008) Size-dependent sex allocation in Aconitum gymnandrum (Ranunculaceae): physiological basis and effects of maternal family and environment. Plant Biol (Stuttg) 10:694–703CrossRefGoogle Scholar
  7. 7.
    Zhao ZG, Meng JL, Fan BL, Du GZ (2008) Reproductive patterns within racemes in protandrous Aconitum gymnandrum (Ranunculaceae): potential mechanism and among-family variation. Plant Syst Evol 273:247–256CrossRefGoogle Scholar
  8. 8.
    Zhao ZG, Liu ZJ, Conner JK (2015) Plasticity of floral sex allocation within inflorescences of hermaphrodite Aconitum gymnandrum. J Plant Ecol 8:130–135CrossRefGoogle Scholar
  9. 9.
    Doyle JJ, Doyle JL (1987) A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem bull 19:11–15Google Scholar
  10. 10.
    Cox MP, Peterson DA, Biggs PJ (2010) SolexaQA: at-a-glance quality assessment of illumina second-generation sequencing data. BMC Bioinform 11(1):485CrossRefGoogle Scholar
  11. 11.
    Magoc T, Salzberg SL (2011) FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27(21):2957–2963CrossRefGoogle Scholar
  12. 12.
    Thiel T, Michalek WR, Varshneyk K, Graner A (2003) Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.). Theor Appl Genet 10:411–422CrossRefGoogle Scholar
  13. 13.
    Rozen S, Skaletsky H (2000) Primer3 on the WWW for general users and for biologist programmers. Methods Mol Biol (Clifton, NJ) 132:365–386Google Scholar
  14. 14.
    Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 28:2537–2539CrossRefGoogle Scholar

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© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.State Key Laboratory of Grassland and Agro-Ecosystems, School of Life SciencesLanzhou UniversityLanzhouChina

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