Volume 11, Issue 2 (2020)                   JMBS 2020, 11(2): 185-191 | Back to browse issues page

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1- Tarbiat Modares University , mojtabakhayam@gmail.comm
2- Shahid Beheshti Medical University
3- Seed and Plant Certification and Registration Institute
4- Isfahan University of Technology
Abstract:   (2988 Views)
In stevia (Stevia rebaudiana), breeding programs are mainly aimed at developing plants with high Rebaudioside-A (RA) content. To this end, in order to screen stevia plants and selection of varieties with the highest amount of desired sweeteners (RA) using molecular markers, the present study was conducted on RNA-seq data of varieties having different amounts of RA. We took advantage of CLC to make de novo transcriptome assembly for each variety with k-mer and contig length values of 20 and 200bp, respectively. The assembly was annotated using the latest Arabidopsis proteome release. To identify signatures of candidate polymorphic SSRs among the stevia varieties, the assembled sequences were used as an input for CandiSSR, followed by designing primer pairs for identified polymorphic SSRs. We identified 368 potential polymorphic SSRs based on the stevia transcriptome analysis, among which 360 were qualified for primer design. Almost 89% of the contig sequences possessing polymorphic SSRs had the best blast hit against Arabidopsis proteome. We found contigs similar to the UDP-Glycosyltransferase protein family and Deoxyxylulose-5-phosphate synthase which are involved in biosynthesis pathway of steviol glycosides. Also, gene set enrichment analysis using PlantGSE through Hypergeometric test (FDR<0.05) identified enriched metabolic pathways in the sequences contained polymorphic SSRs; It is therefore most likely that such connections exist between the SSRs and biosynthesis of steviol glycosides. Hence, it could conceivably be hypothesized that the SSR markers developed in this study would be reliable in molecular breeding of stevia toward selection of varieties with high RA content.
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Article Type: Original Research | Subject: Bioinformatics
Received: 2019/08/31 | Accepted: 2019/10/30 | Published: 2020/06/6

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