陈仕淼, 郑剑, 陆覃昱, 张继, 石兰蓉, 马松琼, 范兢升, 甘卫堂. 2023: 番木瓜抗倒伏优势微生物及候选基因筛选. 南方农业学报, 54(2): 336-346. DOI: 10.3969/j.issn.2095-1191.2023.02.002
引用本文: 陈仕淼, 郑剑, 陆覃昱, 张继, 石兰蓉, 马松琼, 范兢升, 甘卫堂. 2023: 番木瓜抗倒伏优势微生物及候选基因筛选. 南方农业学报, 54(2): 336-346. DOI: 10.3969/j.issn.2095-1191.2023.02.002
CHEN Shi-miao, ZHENG Jian, LU Qin-yu, ZHANG Ji, SHI Lan-rong, MA Song-qiong, FAN Jing-sheng, GAN Wei-tang. 2023: Screening of dominant microorganisms and candidate genes of papaya lodging resistance. Journal of Southern Agriculture, 54(2): 336-346. DOI: 10.3969/j.issn.2095-1191.2023.02.002
Citation: CHEN Shi-miao, ZHENG Jian, LU Qin-yu, ZHANG Ji, SHI Lan-rong, MA Song-qiong, FAN Jing-sheng, GAN Wei-tang. 2023: Screening of dominant microorganisms and candidate genes of papaya lodging resistance. Journal of Southern Agriculture, 54(2): 336-346. DOI: 10.3969/j.issn.2095-1191.2023.02.002

番木瓜抗倒伏优势微生物及候选基因筛选

Screening of dominant microorganisms and candidate genes of papaya lodging resistance

  • 摘要: 【目的】筛选抗倒伏性强的番木瓜根际优势微生物,挖掘番木瓜抗倒伏差异表达的关键基因,为揭示番木瓜抗倒伏机制及相关品种选育提供参考。【方法】试验设常规施肥量处理(每株施用2.5 kg有机肥,CK)、缺肥处理(不施有机肥,WLR)和高有机肥处理(每株施用10 kg有机肥,SLR) 3个处理,根据其转录组数据和根际微生物数据,利用加权基因共表达网络(WGCNA)关联分析番木瓜抗倒伏相关的关键基因,并分析根际微生物变化情况。【结果】 SLR处理的植株抗倒伏性最强,其次是CK,WLR处理植株的抗倒伏性最差。WLR处理植株的株高、节间长度和茎粗均显著低于CK和SLR处理的植株(P<0.05)。通过微生物组数据分析得到影响抗倒伏性状优势微生物为链丝菌属(Streptomyces)、慢生根瘤菌属(Bradyrhizobium)、RB41菌属及噬几丁质菌属(Chitinophaga)。通过WGCNA分析得到2个与番木瓜抗倒伏性能相关的品蓝模块和淡黄模块,进而对这2个模块构建基因共表达网络,筛选出可能与番木瓜抗倒伏性能密切相关的乙酰辅酶A乙酰转移酶基因(AACT)、聚腺苷酸结合蛋白基因(RBP47)、线粒体输入内膜转位酶亚基基因(TIM9)、钙依赖通道7TM区域基因(HYP1)、韧皮部蛋白质丝网络蛋白基因(SEO)和半胱氨酸蛋白酶抑制剂a基因(CPI)等6个核心基因。核心基因功能分析结果显示,品蓝模块涉及番木瓜萜类代谢调控,而淡黄色模块涉及番木瓜韧皮部生长代谢调控。【结论】根际优势微生物与番木瓜抗倒伏性密切相关,其可通过调控番木瓜茎的生长从而提高抗倒伏性,可作为抗倒伏性强番木瓜品种选育的微生物筛选标记之一。

     

    Abstract: 【Objective】To screen dominant microorganisms in root of papaya with strong lodging resistance,and to mine key genes of differential expression of papaya lodging resistance,so as to provide reference for revealing mechanism of papaya lodging resistance and related variety breeding selection.【Method】In the experiment,three treatments were set up,conventional fertilizer application(2.5 kg organic fertilizer per plant,CK),fertilizer deficiency treatment (no organic fertilizer, WLR)and high organic fertilizer treatment(10 kg organic fertilizer per plant,SLR). Based on transcriptome and rhizosphere microorganism data,association analyses of weighted gene co-expression network analysis (WGCNA)were conducted to analyze key genes related to papaya lodging resistance and changes of rhizosphere microorganisms.【Result】 The plants treated with SLR had the strongest lodging resistance,followed by CK,and the plants treated with WLR had the worst lodging resistance. The plant height,internode length,and stem diameter of WLR treated plants were significantly lower than those of CK and SLR treated plants(P<0.05). Through microbiome data analysis,dominant microorganisms that affected the trait of lodging resistance were identified:Streptomyces,Bradyrhizobium,RB41 and Chitinophaga. Two modules related to papaya lodging resistance(royal blue module and light yellow module)were obtained through WGCNA analysis. Weighted gene co-expression networks based on these two modules were established and then 6 core genes possibly related to papaya lodging resistance were screened: acetyl-CoA acetyltransferase(AACT), polyadenylate-binding protein RBP47-like gene(RBP47),mitochondrial import inner membrane translocase subunit gene(TIM9),Calcium dependent channel 7TM region gene(HYP1),phloem protein filament network protein gene (SEO),and cysteine proteinase inhibitor a-like gene(CPI). Functional analysis of the core genes showed that the royal blue module was involved in papaya terpenoid metabolism regulation,while the light yellow module was involved in papaya phloem growth regulation.【Conclusion】 Dominant rhizosphere microorganisms are closely related to papaya lodging resistance,and as they can strengthen lodging resistance through regulating papaya stem growth,they can be taken as one of the microorganism screening markers for highly lodging-resistant papaya breeding.

     

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