Transcriptome analysis of Saposhnikovia divaricata and mining of bolting and flowering genes

IF 4.7 4区 医学 Q1 CHEMISTRY, MEDICINAL Chinese Herbal Medicines Pub Date : 2023-10-01 DOI:10.1016/j.chmed.2022.08.008
Min Zhang , Wenle Wang , Qian Liu , Erhuan Zang , Lijun Wu , Guofa Hu , Minhui Li
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引用次数: 0

Abstract

Objective

Early bolting of Saposhnikovia divaricata has seriously hindered its medicinal value and sustainable development of resources. The molecular mechanism of bolting and flowering of S. divaricata is still unclear and worth of research. In our study, we explored the transcriptome of the genes related to the bolting and flowering of S. divaricata.

Methods

The transcriptome library was constructed, sequenced, assembled and annotated from the bolting and unbolting leaves of S. divaricata by high-throughput sequencing at the bud and flowering stage. Focus on the pathways related to bolting and flowering in plants, and exploring genes. The expression of seven candidate genes was verified by real-time fluorescence quantitative PCR (qRT-PCR).

Results

Transcriptome results showed that 249 889 422 high-quality clean reads were obtained. A total of 67 866 unigenes were assembled with an average length of 948.1 bp. Trinity de Novo assembly produced 67 866 unigenes with an average length of 948.1 bp. Among 993 differentially expressed genes, 484 genes were significantly up-regulated and 509 genes were down-regulated in the SdM group. A total of 79 GO terms were significantly enriched for differentially expressed genes. KEGG results showed that 11 154 unigenes were enriched in 89 pathways. And 21 candidate genes related to bolting and flowering of S. divaricata were excavated. The qRT-PCR results showed that expression trends of HDA9, PHYB, AP2, TIR1, Hsp90, CaM, and IAA7 were consistent with transcriptomic sequencing results. In addition, RNA-seq had identified 10 740 transcription factors and classified them into 58 families by their conserved domains. Further studies showed that the transcription factors regulating the flowering of S. divaricata were mainly distributed in the NAC, MYB_related, HB-other, ARF, and AP2 families.

Conclusion

Based on the results of this study, it was found that the plant hormone signal transduction pathway was one of the decisive factors to control bolting and flowering. Among them, auxin related genes IAA and TIR1 are the key genes in the bolting and flowering process of S. divaricata.

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三叶草转录组分析及抽苔和开花基因的挖掘
目的过早抽苔严重影响了牡丹的药用价值和资源的可持续开发。花莲抽苔和开花的分子机制尚不清楚,值得进一步研究。在我们的研究中,我们探索了与S. divaricata抽苔和开花相关的基因的转录组。方法采用高通量测序的方法,在花蕾期和开花期分别对三叶抽苔和未抽苔叶片进行转录组文库构建、测序、组装和注释。重点研究植物抽苔和开花的相关途径,探索相关基因。通过实时荧光定量PCR (qRT-PCR)验证7个候选基因的表达。结果转录组结果显示,共获得249 889 422条高质量的干净reads。共组装了67 866个单基因,平均长度为948.1 bp。Trinity de Novo组合共产生67 866个单基因,平均长度为948.1 bp。在993个差异表达基因中,SdM组484个基因显著上调,509个基因显著下调。共有79个GO项被差异表达基因显著富集。KEGG结果显示,89条通路中富集了11 154个单基因。挖掘出21个与开花和抽苔相关的候选基因。qRT-PCR结果显示,HDA9、PHYB、AP2、TIR1、Hsp90、CaM、IAA7的表达趋势与转录组测序结果一致。此外,RNA-seq鉴定了10 740个转录因子,并根据其保守结构域将其分为58个家族。进一步研究表明,调控花楸开花的转录因子主要分布在NAC、MYB_related、HB-other、ARF和AP2家族中。结论本研究发现,植物激素信号转导途径是控制抽苔和开花的决定性因素之一。其中,生长素相关基因IAA和TIR1是金盏花抽苔和开花过程的关键基因。
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来源期刊
Chinese Herbal Medicines
Chinese Herbal Medicines CHEMISTRY, MEDICINAL-
CiteScore
4.40
自引率
5.30%
发文量
629
审稿时长
10 weeks
期刊介绍: Chinese Herbal Medicines is intended to disseminate the latest developments and research progress in traditional and herbal medical sciences to researchers, practitioners, academics and administrators worldwide in the field of traditional and herbal medicines. The journal's international coverage ensures that research and progress from all regions of the world are widely included. CHM is a core journal of Chinese science and technology. The journal entered into the ESCI database in 2017, and then was included in PMC, Scopus and other important international search systems. In 2019, CHM was successfully selected for the “China Science and Technology Journal Excellence Action Plan” project, which has markedly improved its international influence and industry popularity. CHM obtained the first impact factor of 3.8 in Journal Citation Reports (JCR) in 2023.
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