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Molecular Breeding

, Volume 34, Issue 4, pp 2205–2217 | Cite as

Development of SNP and InDel markers via de novo transcriptome assembly in Sesamum indicum L.

  • Libin Wei
  • Hongmei Miao
  • Chun Li
  • Yinghui Duan
  • Jiaojiao Niu
  • Tide Zhang
  • Qiongyi Zhao
  • Haiyang Zhang
Article

Abstract

Cultivated sesame (Sesamum indicum L.) is an important oil crop because of its high oil content and quality. In order to discover the single nucleotide polymorphisms (SNPs) and insertion/deletions (InDels) in RNA-Seq, we collected a total of 33.47 Gbp of data from three sesame transcriptome datasets. A reference transcriptome covering 267,508 unigenes was constructed. Among the 37,646 transcripts with complete open reading frames, a total of 7,450 SNPs and 362 InDels were found with frequencies of one SNP per 6.66 kb and one InDel per 137 kb, respectively. Most of the SNPs were transition-type with the nucleotide transitions C–T or A–G. A total of 21 InDel types with lengths ranging from 1 to 38 bp were identified, and the short InDels (1–2 bp) were most abundant at a ratio of over 80 %. Furthermore, 4,959 (66.56 %) SNPs were detected in protein-coding regions: 2,899 (58.46 %) were synonymous and 2,060 (41.54 %) were nonsynonymous. All SNPs and InDels detected in this study were bi-allelic. Of the randomly selected 40 SNPs and 40 InDels, 92.5 % of the SNPs and 95.0 % of the InDels exhibited polymorphism according to the PCR-based and Sanger-sequenced results. Furthermore, the efficiencies of the newly developed polymorphic SNP and InDel markers were evaluated among 36 commercial sesame cultivars. More than 90.0 % of the markers displayed the expected polymorphic amplifications. The polymorphism information content values ranged from 0.05 to 0.58 with an average of 0.38. Moreover, all genotypes of the 36 commercial cultivars tested were definitively distinguished by 21 SNPs and 16 InDels. These newly identified molecular markers may provide a foundation for cultivar identification, genetic diversity analysis, qualitative and quantitative trait mapping and marker-assisted selection breeding in sesame.

Keywords

Sesame Single-nucleotide polymorphisms (SNPs) Insertions/deletions (InDels) Cultivar identification 

Notes

Acknowledgments

This work was supported by the National ‘973’ Project (Grant No. 2011C B109304), the earmarked fund for China Agriculture Research System (Grant No. CARS-15) and the National Natural Science Foundation of China (U1204318).

Supplementary material

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Supplementary material 1 (DOC 56 kb)
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Additional file 4 Comparisons of three groups of sesame transcriptomes. Contigs from each of the three cultivars were screened against the A. thaliana proteome. The non-redundant sequences of three accessions to the A. thaliana proteome are shown. (JPEG 62 kb)
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Additional file 5 Characteristics of the reference transcriptome. There are 229,862 non-ORF sequences and 37,646 ORF sequences in the reference transcriptome. Among the 37,646 ORF sequences, the total lengths of coding regions and non-coding regions reach 34.67 Mbp and 14.94 Mbp, respectively. (TIFF 522 kb)
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Additional file 6 Information on all SNPs among the three RNA-Seq materials. SNP position and types are shown. (XLS 2,504 kb)
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Additional file 7 Information on all InDels among the three RNA-Seq materials. InDels position and types are shown. (XLS 106 kb)
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Additional file 17 DNA fingerprint profiles of the 36 sesame cultivars using 16 SNP markers. Sesame cultivars M1–M36 were differentiated using a panel of 16 SNP markers. (DOC 78 kb)
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Supplementary material 18 (DOC 77 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Libin Wei
    • 1
  • Hongmei Miao
    • 1
  • Chun Li
    • 1
  • Yinghui Duan
    • 1
  • Jiaojiao Niu
    • 1
  • Tide Zhang
    • 1
  • Qiongyi Zhao
    • 2
  • Haiyang Zhang
    • 1
  1. 1.Henan Sesame Research CenterHenan Academy of Agricultural SciencesZhengzhouChina
  2. 2.Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological SciencesChinese Academy of SciencesShanghaiChina

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