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转录组测序分析天冬氨酸和谷氨酸对广叶绣球菌生长的影响

刘晓瑜 肖冬来 马璐 杨驰 林辉 江晓凌

刘晓瑜,肖冬来,马璐,等. 转录组测序分析天冬氨酸和谷氨酸对广叶绣球菌生长的影响 [J]. 福建农业学报,2023,38(7):833−841 doi: 10.19303/j.issn.1008-0384.2023.07.009
引用本文: 刘晓瑜,肖冬来,马璐,等. 转录组测序分析天冬氨酸和谷氨酸对广叶绣球菌生长的影响 [J]. 福建农业学报,2023,38(7):833−841 doi: 10.19303/j.issn.1008-0384.2023.07.009
LIU X Y, XIAO D L, MA L, et al. Transcriptome Analysis on Effect of Glutamic and Aspartic Acids on Growth of Sparassis latifolia [J]. Fujian Journal of Agricultural Sciences,2023,38(7):833−841 doi: 10.19303/j.issn.1008-0384.2023.07.009
Citation: LIU X Y, XIAO D L, MA L, et al. Transcriptome Analysis on Effect of Glutamic and Aspartic Acids on Growth of Sparassis latifolia [J]. Fujian Journal of Agricultural Sciences,2023,38(7):833−841 doi: 10.19303/j.issn.1008-0384.2023.07.009

转录组测序分析天冬氨酸和谷氨酸对广叶绣球菌生长的影响

doi: 10.19303/j.issn.1008-0384.2023.07.009
基金项目: 福建省科技计划公益类专项(2020R1035005);福建省自然科学基金(2021J01505);福建省农业高质量发展超越“5511”协同创新工程项目(XTCXGC2021007)
详细信息
    作者简介:

    刘晓瑜(1991 —),女,硕士,研究实习员,主要从事食用菌栽培生理研究,E-mail:liu.xiaoyu1991@163.com

    通讯作者:

    肖冬来(1981 —),男,博士,副研究员,主要从事食用菌栽培生理研究,E-mail:xdljiangsu@163.com

  • 中图分类号: S646

Transcriptome Analysis on Effect of Glutamic and Aspartic Acids on Growth of Sparassis latifolia

  • 摘要:   目的  通过转录组测序分析添加不同氮源培养后广叶绣球菌基因差异表达情况,旨在探究氨基酸调节基质降解的分子机理,为其高效生产提供理论依据。  方法  以硫酸铵、鱼粉蛋白胨、天冬氨酸和谷氨酸为氮源,测定菌丝生长速度并利用转录组测序技术对不同氮源诱导下广叶绣球菌进行基因差异表达分析。  结果  天冬氨酸和谷氨酸相对于硫酸铵、鱼粉蛋白胨可显著促进菌丝生长(P<0.01);GO功能富集分析显示差异基因主要富集在氧化还原酶活性、铁离子跨膜转运蛋白活性和铁离子的还原和转运同化等;KEGG通路富集分析显示,富集度较高的通路主要有色氨酸代谢、花生四烯酸代谢和氮代谢等。差异基因中溶血素蛋白ostreolysin A6、GroES类似蛋白和6-甲基水杨酸脱羧酶等基因在天冬氨酸或谷氨酸诱导下表达量变化倍数较大(P<0.01)。  结论  天冬氨酸和谷氨酸可能通过促进绣球菌氧化还原酶活性及铁离子代谢过程,提高其基质利用能力。研究结果为进一步研究广叶绣球菌木质纤维素降解机制及栽培生理提供理论依据。
  • 图  1  不同氮源对广叶绣球菌生长的影响

    Figure  1.  Effects of different nitrogen sources on growth of S. latifolia

    图  2  差异表达基因统计图(A)和韦恩图(B)

    Figure  2.  Statistical histogram (A) and Venn diagram (B) of DEGs

    图  3  差异基因GO(A)和KEGG(B)富集分析

    Figure  3.  GO (A) and KEGG (B) enrichment analyses on DEGs

    图  4  差异显著基因热图聚类分析

    热图上数字为基因表达量FPKM值,下同。

    Figure  4.  Heat map clustering on significantly differentiated genes

    Datas are FPKM values. Same for below.

    图  5  氧化还原酶基因热图聚类分析

    Figure  5.  Heat map clustering on oxidoreductase genes

    图  6  纤维素和半纤维素降解相关基因热图聚类分析

    Figure  6.  Heat map clustering on cellulose- and hemicellulose-degrading genes

    图  7  铁离子转运和还原相关基因热图聚类分析

    Figure  7.  Heat map clustering on iron transport and reduction genes

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出版历程
  • 收稿日期:  2023-04-23
  • 修回日期:  2023-05-11
  • 网络出版日期:  2023-07-06
  • 刊出日期:  2023-07-28

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