Scientific Reports (Jan 2021)

De novo transcriptomic analysis and identification of EST-SSR markers in Stephanandra incisa

  • Cuiping Zhang,
  • Zhonglan Wu,
  • Xinqiang Jiang,
  • Wei Li,
  • Yizeng Lu,
  • Kuiling Wang

DOI
https://doi.org/10.1038/s41598-020-80329-7
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 10

Abstract

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Abstract Stephanandra incisa is a wild-type shrub with beautiful leaves and white flowers and is commonly used as a garden decoration accessory. However, the limited availability of genomic data of S. incisa has restricted its breeding process. Here, we identified EST-SSR markers using de novo transcriptome sequencing. In this study, a transcriptome database containing 35,251 unigenes, having an average length of 985 bp, was obtained from S. incisa. From these unigene sequences, we identified 5,555 EST-SSRs, with a distribution density of one SSR per 1.60 kb. Dinucleotides (52.96%) were the most detected SSRs, followed by trinucleotides (34.64%). From the EST-SSR loci, we randomly selected 100 sites for designing primer and used the DNA of 60 samples to verify the polymorphism. The average value of the effective number of alleles (Ne), Shannon’s information index (I), and expective heterozygosity (He) was 1.969, 0.728, and 0.434, respectively. The polymorphism information content (PIC) value was in the range of 0.108 to 0.669, averaging 0.406, which represented a middle polymorphism level. Cluster analysis of S. incisa were also performed based on the obtained EST-SSR data in our work. As shown by structure analysis, 60 individuals could be classified into two groups. Thus, the identification of these novel EST-SSR markers provided valuable sequence information for analyzing the population structure, genetic diversity, and genetic resource assessment of S. incisa and other related species.