Chrome Extension
WeChat Mini Program
Use on ChatGLM

大蒜体细胞胚发生过程中内源激素含量及相关基因表达的变化特征

Acta Botanica Boreali-Occidentalia Sinica(2021)

Cited 4|Views3
Abstract
该研究以大蒜品种'二水早'为材料,采用高效液相色谱串联质谱法(LC-MS/MS),检测了大蒜体细胞胚发生过程中花序轴(EX)、愈伤组织(CA)、早期胚性愈伤组织(PC)、后期胚性愈伤组织(LC)和球形胚(GE)阶段的5种生长素及其类似物、4种细胞分裂素(CTK)和脱落酸(ABA)含量,结合激素合成和信号转导相关基因表达量的动态变化,探讨3类激素在大蒜体细胞胚发生中的调控作用,为大蒜体细胞胚发生的激素调控提供理论依据,也为进一步研究植物体细胞胚发生的分子机理奠定基础.结果 表明:(1)在大蒜体细胞胚发生过程中,生长素及其类似物含量均呈现先升高后降低的变化趋势,且在PC阶段最高而在GE阶段最低;异戊烯基腺嘌呤(IP)、反式玉米素(tZ)和ABA在EX阶段含量最高,其余4个阶段的含量均显著低于EX阶段,而顺式玉米素(cZ)在CA和PC阶段含量较高,在GE阶段含量最低.(2)在PC阶段,IAA合成基因AsYUCCA1和AsTA1以及生长素外运载体基因AsABCB1的表达量升高;在LC阶段,生长素内运载体基因AsAUX1表达量升高,生长素应答基因AsARF1和AsARF2表达量降低,cZ合成基因AsLOG1在CA阶段表达量最高,细胞分裂素运输相关基因AsENT2和信号转导相关基因AsORR-A1、AsORR-A2在PC阶段表达量最高.(3)ABA合成限速酶基因AsNCED1和AsNCED2的表达量在大蒜体细胞胚发生的后4个阶段显著低于EX阶段,ABA信号转导相关基因AsPP2C表达量在PC阶段升高,AsABI1表达量在LC阶段升高,AsPYL1表达量在GE阶段升高.研究认为,在大蒜体细胞胚发生过程中,吲哚-3-甲醛(ICAld)、吲哚-3-丁酸(IBA)和cZ的积累有助于促进大蒜愈伤组织的形成,高水平的生长素及其类似物和低水平的IP、tZ有利于大蒜早期胚性愈伤组织的形成,而低水平的生长素及其类似物、CTK和ABA更利于大蒜球形胚的形成,表明激素合成相关基因可调控内源激素含量的变化,激素信号转导相关基因参与了大蒜体细胞胚的发生.
More
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest