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De novo and comparative transcriptome analysis of cultivated and wild spinach

文献类型： 外文期刊

作者： Xu, Chenxi 1 ; Jiao, Chen 2 ; Zheng, Yi 2 ; Sun, Honghe 2 ; Liu, Wenli 2 ; Cai, Xiaofeng 1 ; Wang, Xiaoli 1 ; Liu, Shuang 1 ;

作者机构： 1.Shanghai Normal Univ, Dev & Collaborat Innovat Ctr Plant Germplasm Reso, Coll Life & Environm Sci, Shanghai 200234, Peoples R China

2.Cornell Univ, Boyce Thompson Inst Plant Res, Ithaca, NY 14853 USA

3.Northwest A&F Univ, Coll Hort, State Key Lab Crop Stress Biol Arid Areas, Yangling 712100, Shaanxi, Peoples R China

4.Natl Engn Res Ctr Vegetables, Key Lab Biol & Genet Improvement Hort Crops North, Beijing 100097, Peoples R China

5.USDA, Agr Res Stn, Salinas, CA 93905 USA

6.USDA ARS, Robert W Holley Ctr Agr & Hlth, Ithaca, NY 14853 USA

期刊名称：SCIENTIFIC REPORTS （ 影响因子：4.379； 五年影响因子：5.133 ）

ISSN： 2045-2322

年卷期： 2015 年 5 卷

页码：

收录情况： SCI

摘要： Spinach (Spinacia oleracea L.) is an economically important green leafy vegetable crop. In this study, we performed deep transcriptome sequencing for nine spinach accessions: three from cultivated S. oleracea, three from wild S. turkestanica and three from wild S. tetrandra. A total of approximately 100 million high-quality reads were generated, which were de novo assembled into 72,151 unigenes with a total length of 46.5 Mb. By comparing sequences of these unigenes against different protein databases, nearly 60% of them were annotated and 50% could be assigned with Gene Ontology terms. A total of 387 metabolic pathways were predicted from the assembled spinach unigenes. From the transcriptome sequencing data, we were able to identify a total of similar to 320,000 high-quality single nucleotide polymorphisms (SNPs). Phylogenetic analyses using SNPs as well as gene expression profiles indicated that S. turkestanica was more closely related to the cultivated S. oleracea than S. tetrandra. A large number of genes involved in responses to biotic and abiotic stresses were found to be differentially expressed between the cultivated and wild spinach. Finally, an interactive online database (http://www.spinachbase.org) was developed to allow the research community to efficiently retrieve, query, mine and analyze our transcriptome dataset.

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