Development of SSR Molecular Markers Based on Transcriptome Data of Pinus kesiya var. langbianensis

doi:10.13560/j.cnki.biotech.bull.1985.2017.05.010

Abstract

Abstract: In Simao pine（Pinus kesiya var. langbianensis）breeding programs,lack of co-dominant genetic markers constrains the development of molecular marker assisted breeding. The aim of this study is to develop SSR molecular markers using transcriptome sequencing data. Searching the SSR loci from 59636 unigenes of P. kesiya var. langbianensis with MISA software,total 3745 SSRs were obtained,accounting for 6.28% of the total unigenes,averagely one SSR per 11.36 kb. Trinucleotide and dinucleotide repeats were dominant types among SSRs with the ratio of 49% and 24%,and others were only 27%. AGC/CTG was the most trinucleotide motif and AT/TA was the most dinucleotide motif. The primers were designed and synthetized based on randomly selected 224 SSR loci,verification by agarose gel electrophoresis revealed that 29 loci showed clear polymorphism. While only 12 of the 29 loci satisfied the multiple fragments of SSR repeat motifs in capillary electrophoresis and their amplification efficiencies were higher than 85%. Genetic diversity of 42 Simao pine samples from Jingdong and Puwen populations was investigated with these 12 fluorescently labeled primers. A total of 35 alleles were detected,the polymorphism information content（PIC）of all loci ranged from 0.0932-0.4809（the mean was 0.3069）. Among these,4 loci were classified as lowly polymorphic ones（0 < PIC <0.25）and 8 loci as moderately polymorphic ones（0.25 < PIC <0.5）. Conclusively,these 12 SSRs may be used in future studies on genetic diversity,linkage mapping,gene location and cloning,providing the technical support for molecular marker assisted breeding and mutation in P. kesiya var. langbianensis.

Key words: Pinus kesiya var. Langbianensis, transcriptome, SSR, primer development

ZHAO Neng, YUAN Xiao-long, MIAO Fu-jun, WANG Yi, CHEN Wei, LI Jiang, WU Tao, WANG Juan. Development of SSR Molecular Markers Based on Transcriptome Data of Pinus kesiya var. langbianensis[J]. Biotechnology Bulletin, 2017, 33(5): 71-77.

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