Suppr超能文献

用于三种甜叶菊基因型基因鉴定和转录本分析的RNA测序

RNA-Seq for gene identification and transcript profiling of three Stevia rebaudiana genotypes.

作者信息

Chen Junwen, Hou Kai, Qin Peng, Liu Hongchang, Yi Bin, Yang Wenting, Wu Wei

机构信息

Agronomy College of Sichuan Agricultural University, Wenjiang, Chengdu, Sichuan 611130, China.

出版信息

BMC Genomics. 2014 Jul 7;15(1):571. doi: 10.1186/1471-2164-15-571.

Abstract

BACKGROUND

Stevia (Stevia rebaudiana) is an important medicinal plant that yields diterpenoid steviol glycosides (SGs). SGs are currently used in the preparation of medicines, food products and neutraceuticals because of its sweetening property (zero calories and about 300 times sweeter than sugar). Recently, some progress has been made in understanding the biosynthesis of SGs in Stevia, but little is known about the molecular mechanisms underlying this process. Additionally, the genomics of Stevia, a non-model species, remains uncharacterized. The recent advent of RNA-Seq, a next generation sequencing technology, provides an opportunity to expand the identification of Stevia genes through in-depth transcript profiling.

RESULTS

We present a comprehensive landscape of the transcriptome profiles of three genotypes of Stevia with divergent SG compositions characterized using RNA-seq. 191,590,282 high-quality reads were generated and then assembled into 171,837 transcripts with an average sequence length of 969 base pairs. A total of 80,160 unigenes were annotated, and 14,211 of the unique sequences were assigned to specific metabolic pathways by the Kyoto Encyclopedia of Genes and Genomes. Gene sequences of all enzymes known to be involved in SG synthesis were examined. A total of 143 UDP-glucosyltransferase (UGT) unigenes were identified, some of which might be involved in SG biosynthesis. The expression patterns of eight of these genes were further confirmed by RT-QPCR.

CONCLUSION

RNA-seq analysis identified candidate genes encoding enzymes responsible for the biosynthesis of SGs in Stevia, a non-model plant without a reference genome. The transcriptome data from this study yielded new insights into the process of SG accumulation in Stevia. Our results demonstrate that RNA-Seq can be successfully used for gene identification and transcript profiling in a non-model species.

摘要

背景

甜叶菊(Stevia rebaudiana)是一种重要的药用植物,可产生二萜类甜菊糖苷(SGs)。由于其甜味特性(零卡路里,甜度约为蔗糖的300倍),SGs目前被用于制备药品、食品和营养保健品。最近,在了解甜叶菊中SGs的生物合成方面取得了一些进展,但对这一过程的分子机制了解甚少。此外,甜叶菊作为一种非模式物种,其基因组学仍未得到表征。新一代测序技术RNA-Seq的出现,为通过深入的转录本分析扩大甜叶菊基因的鉴定提供了机会。

结果

我们展示了利用RNA-seq对三种具有不同SG组成的甜叶菊基因型转录组图谱的全面描绘。生成了191,590,282条高质量读数,然后组装成171,837条转录本,平均序列长度为969个碱基对。总共注释了80,160个单基因,其中14,211个独特序列被京都基因与基因组百科全书分配到特定的代谢途径。检查了所有已知参与SG合成的酶的基因序列。共鉴定出143个尿苷二磷酸葡萄糖基转移酶(UGT)单基因,其中一些可能参与SG的生物合成。通过RT-QPCR进一步证实了其中8个基因的表达模式。

结论

RNA-seq分析鉴定了编码负责甜叶菊中SG生物合成的酶的候选基因,甜叶菊是一种没有参考基因组的非模式植物。本研究的转录组数据为甜叶菊中SG积累过程提供了新的见解。我们的结果表明,RNA-Seq可以成功用于非模式物种的基因鉴定和转录本分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c60/4108789/731b183f4333/12864_2013_6267_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验