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草业学报 ›› 2023, Vol. 32 ›› Issue (4): 112-128.DOI: 10.11686/cyxb2022139

• 研究论文 • 上一篇    

红三叶响应淹水胁迫的相关通路及差异表达基因分析

尚盼盼, 曾兵, 屈明好, 李明阳, 杨兴云, 郑玉倩, 沈秉娜, 毕磊, 杨成, 曾兵()   

  1. 西南大学动物科学技术学院,重庆 402460
    2.草食动物科学重庆市重点实验室,重庆 400715
  • 收稿日期:2022-03-30 修回日期:2022-05-13 出版日期:2023-04-20 发布日期:2023-01-29
  • 通讯作者: 曾兵
  • 作者简介:E-mail:zbin78@163.com
    尚盼盼(1996-),女,甘肃定西人,在读硕士。E-mail: 1916001864 @qq.com
  • 基金资助:
    中央高校基本科研业务费项目荣昌专项(XDJK2020RC001);重庆市现代山地特色高效农业产业技术体系(草食牲畜)2023和西南大学大学生创新训练项目(X202210635042)

Analysis of metabolic pathways and differentially expressed genes of Trifolium pratense responding to waterlogging stress

Pan-pan SHANG, Bing ZENG, Ming-hao QU, Ming-yang LI, Xing-yun YANG, Yu-qian ZHENG, Bing-na SHEN, Lei BI, Cheng YANG, Bing ZENG()   

  1. College of Animal Science and Technology,Southwest University,Chongqing 402460,China
    2.Chongqing Key Laboratory of Herbivore Science,Chongqing 400715,China
  • Received:2022-03-30 Revised:2022-05-13 Online:2023-04-20 Published:2023-01-29
  • Contact: Bing ZENG

摘要:

淹水胁迫是影响植物生长发育和分布的重要非生物胁迫,对植物淹水胁迫的研究是解决近年来极端强降水天气下植物生产管理的关键。红三叶作为优质豆科牧草,耐淹性较差,长期水淹会导致烂根死亡。为研究红三叶淹水胁迫下的分子响应机理,本研究通过Illumina高通量测序平台,以耐涝型品种“红龙”淹水胁迫下0、8 和24 h 三个时间点的幼苗叶片为材料进行转录组测序,将测序数据与参考基因组比对后进行差异表达基因(DEGs)分析和功能注释。结果显示,与对照0 h相比,“红龙”在淹水胁迫8 h后,有5065个DEGs,其中,上调表达基因2442个,下调表达基因2623个;在淹水胁迫24 h后,有9022个DEGs,其中,上调表达基因4279个,下调表达基因4743个。基因本体数据库富集结果显示,DEGs 主要富集于代谢过程、细胞过程、生物调节、细胞、催化活性等条目;东京基因与基因组数据库富集结果显示, DEGs显著富集于植物激素信号调节、植物-病原互作、碳代谢和乙醛酸及二羧酸代谢等通路中,其中乙醛酸及二羧酸代谢通路中过氧化氢酶和甲酸脱氢酶等抗氧化酶相关基因高表达;并且发现差异表达的AP2/ERF、WRKY、bHLH、NAC、bZIP等重要转录因子在红三叶响应淹水胁迫中也发挥重要作用。最后利用qRT-PCR对DEGs进行表达模式的分析验证,发现其与RNA-Seq结果一致,证实了测序结果的准确性。本研究根据转录组信息对DEGs展开功能注释、代谢通路、转录因子等方面的分析研究,初步了解红三叶对淹水胁迫的分子响应机理,为后续候选基因功能挖掘提供了基础数据和理论支撑。

关键词: 红三叶, 淹水胁迫, 转录组测序, 代谢通路, 差异表达基因

Abstract:

Waterlogging stress is an important abiotic stress that affects plant growth, development and distribution, and research on plant waterlogging stress is key to addressing plant production management under extreme heavy rainfall in recent years. Trifolium pratense is a high-quality legume forage, but is poorly tolerant to waterlogging, and long-term waterlogging can lead to root rot and death. In order to investigate the molecular response mechanism of T. pratense under waterlogging stress, the transcriptome was sequenced from seedling leaves of the waterlogging-tolerant variety “Hong Long” at 0, 8 and 24 h using an Illumina high-throughput sequencing platform, and the sequenced data were compared with the reference genome for differentially expressed genes (DEGs) and functional annotation. The results showed that, compared with the control 0 h, “Hong Long” had 5065 DEGs after 8 h of waterlogging stress, among which 2442 genes were up-regulated and 2623 genes were down-regulated; After 24 h of waterlogging stress, there were 9022 DEGs, among which 4279 genes were up-regulated and 4743 genes were down-regulated. The gene ontology (GO) enrichment results showed that DEGs were mainly enriched in terms of metabolic process, cellular process, biological regulation, cell and catalytic activity; The kyoto encyclopedia of genes and genomes (KEGG) enrichment results showed that DEGs were significantly enriched in pathways such as plant hormone signal transduction, plant-pathogen interaction, carbon metabolism and glyoxylate and dicarboxylate metabolism, in which antioxidant enzymes such as peroxidase and formic dehydrogenase were highly expressed in the glyoxylate and dicarboxylate metabolism pathways. This study also found that the differentially expressed AP2/ERF, WRKY, bHLH, NAC, bZIP and other important transcription factors also played important roles in the response of T. pratense to waterlogging stress. Finally, the expression pattern of DEGs was verified by qRT-PCR and found to be consistent with the RNA-Seq results, confirming the accuracy of the sequencing results. In this study, functional annotation, metabolic pathways and transcription factors of DEGs were analyzed based on the transcriptome information, which provided a preliminary understanding of the molecular response mechanisms of T. pratense to waterlogging stress and provided basic data and theoretical direction for the subsequent functional mining of candidate genes.

Key words: Trifolium pratense, waterlogging stress, transcriptomic sequencing, metabolic pathways, differentially expressed genes