整合转录组和代谢组学分析揭示玉米对层出镰孢茎腐病的响应机制

doi:10.3864/j.issn.0578-1752.2025.01.006

Abstract

Abstract:

【Objective】Stalk rot is a prevalent disease of maize (Zea mays) that severely affects maize yield and quality worldwide. The diseases are caused by several types of fungi and bacteria that are part of the complex of microorganisms. Among which, the ascomycete fungus Fusarium proliferatum has become one of the most aggressive causal agents of maize diseases in China in recent years. The study aims to provide a comprehensive analysis of multi-omics of maize stalks following F. proliferatum inoculation and valuable insights into the molecular basis of the response, including functional annotation and enrichment analyses of the major pathways enriched for differentially expressed genes (DEGs) and differentially expressed metabolites (DEMs) of maize conditioning F. proliferatum infection, and to lay theoretical foundation for maize breeding and disease management.【Method】Maize inbred lines ZC17 (ZhengC17, resistant) and CH72 (Chang72, susceptible), with different levels of resistance to F. proliferatum were used for sample collection. Seedlings at the nine-leaf stage with uniform performance were selected for artificial inoculation. Maize plants were inoculated by punching a hole in the stem at the second or third internode above the soil line using a sterile micropipette tip, followed by injection of 50 μL of freshly prepared F. proliferatum inoculum. A similar number of plants were inoculated with PDB as a mock treatment. The wounds were sealed with vaseline after inoculation. The upper and lower stem segments immediately adjacent to the inoculation segments were sampled at 7 dpi (days post inoculation), all individual samples were used for further transcriptome and nontargeted-metabolomics analysis. The inoculated internodes of the individual plants were split and symptoms were observed for evaluating of SRS_A (stalk rot score on average) and DSI (disease severity index). Multiple bioinformatics tools were used to conduct in-depth analysis of the transcriptome sequencing data and metabolomics data, and the DEGs were verified by real-time fluorescence quantitative PCR (RT-qPCR).【Result】Phenotypic and physiological characteristics indicated that the inoculated group of samples from the resistant inbred line ZC17 showed significantly lower lesion areas and symptoms than those of the sensitive inbred line CH72 after inoculation with F. proliferatum. The SRS_A and DSI of the ZC17 and CH72 stalks were consistent with the symptom phenotypes: the susceptible inbred CH72 had approximately 2.48-fold more SRSAs than the resistant inbred ZC17 line, and its DSI increased by 35.36% compared to that of ZC17. The results of the principal component analysis (PCA) showed a high reproducibility of the samples within the group. In PC1, ZC17 and CH72 were separated from each other. In PC2, FP group and MK group were separated from each other. The DEGs in the two comparison pairs (ZC17_FP vs. ZC17_MK, CH72_FP vs. CH72_MK) were analyzed. More DEGs were found in CH72 than those of ZC17 post inoculation, whereas nearly 50% of the DEGs share the same trend of expression between the two comparison pairs. Functional annotation and enrichment analysis found that DEGs and DEMs were enriched in pathways such as biosynthesis of plant secondary metabolites, phenylalanine metabolism, biosynthesis of plant hormones, and plant-pathogen interactions. Integrated analysis of transcriptomics and metabolomics data revealed that phenylalanine, tyrosine, and tryptophan biosynthesis and phenylalanine metabolism were significantly enriched in both the transcriptomic and metabolomic data for CH72 and ZC17. This result suggested that these pathways play a key role in the maize response to F. proliferatum. In addition, transcriptional factors of bHLH, MYB, NAC, and WRKY families were significantly activated after fungal inoculation, demonstrating the important role of transcription factors in the maize response to F. proliferatum infestation. To further confirm the reliability of the sequencing data, 11 genes were randomly selected for qPCR validation, which showed that the trends of the RNA-Seq and qPCR results were consistent in both CH72 and ZC17, Spearman rank correlation analysis also showed high concordance between the RNA-Seq and qPCR results (r=0.75, P=7.5e-05).【Conclusion】Phenylalanine metabolism-related pathways are crucial in maize response to F. proliferatum stalk rot. Key enzymes such as C4H, PAL, ADT, GOT and significantly up-regulated metabolites such as 2-coumaric acid, 3-hydroxycinnamic acid, indole, phenylalanine, tryptophan and tyrosine play an important role in plant disease resistance. The potential disease resistance-related transcription factors, genes and metabolites excavated in this study can provide an important basis for further analysis of the molecular response mechanism of maize to F. proliferatum stalk rot.

Key words: transcriptome, metabolome, maize stalk rot, Fusarium proliferatum, phenylalanine metabolism

CAO YanYong, CHENG ZeQiang, MA Juan, YANG WenBo, ZHU WeiHong, SUN XinYan, LI HuiMin, XIA LaiKun, DUAN CanXing. Integrating Transcriptomic and Metabolomic Analyses Reveals Maize Responses to Stalk Rot Caused by Fusarium proliferatum[J].Scientia Agricultura Sinica, 2025, 58(1): 75-90.

Figures/Tables 11

Table 1

Fig. 1

Table 2

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Table 3

The 10 metabolites with the largest differences in up- and down-regulation in different comparison groups"

比较组 Comparison	代谢物 Metabolite	Log₂FC
CH72 (FP/MK)	蜀葵苷Scorzoside	9.201
	N-(p-羟苯基)乙基对羟基肉桂酰胺N-(p-Hydroxyphenyl)ethyl p-hydroxycinnamide	7.304
	伏马菌素B1 Fumonisin B1	6.862
	对香豆酸乙酯Ethyl p-coumarate	6.373
	L-苯丙氨酸L-Phenylalanine	5.878
	肉桂酸Cinnamic acid	5.759
	苯丙氨酸Phenylalanine	5.666
	N-(1-脱氧-1-果糖基)酪氨酸N-(1-Deoxy-1-fructosyl)tyrosine	5.439
	吲哚-3-乙酰胺Indole-3-acetamide	5.205
	溶血磷脂酰肌醇15:0 LysoPI 15:0	4.876
	1-硬脂酰-2-羟基-sn-甘油-3-磷酸胆碱1-Stearoyl-2-hydroxy-sn-glycero-3-phosphocholine	-4.631
	氧化型谷胱甘肽Glutathione, oxidized	-3.808
	L-谷胱甘肽（氧化型）L-Glutathione (oxidized form)	-3.355
	2-(2-噻吩基)呋喃2-(2-Thienyl)furan	-3.311
	翠雀素-3-O-(6''-O-α-鼠李吡喃糖基-β-葡萄糖苷) Delphinidin-3-O-(6''-O-alpha-rhamnopyranosyl-beta-glucopyranoside)	-2.606
	溶血磷脂酰甘油16:0 LysoPG 16:0	-2.547
	溶血磷脂酰胆碱18:1 LysoPC 18:1	-2.251
	谷氨酰胺-亮氨酸Gln-Leu	-2.060
	缬氨酸-苯丙氨酸Val-Phe	-2.011
	酪氨酸-亮氨酸Tyr-Leu	-1.965
ZC17 (FP/MK)	阿洛糖Allose	6.719
	乙酸Acetic acid	6.535
	广木香内酯Costunolide	5.894
	D-1,5-脱水果糖D-1,5-Anhydrofructose	5.306
	5-吡哆醇内酯5-Pyridoxolactone	5.276
	伏马菌素B1 Fumonisin B1	5.182
	甘油1-十六酸酯Glycerol 1-hexadecanoate	4.816
	溶血磷脂酰肌醇15:0 LysoPI 15:0	4.631
	棕矢车菊素Jaceidin	4.175
	松油酸乙酯Pinolenic acid ethyl ester	4.070
	溶血磷脂酰乙醇胺18:3 LysoPE 18:3	-2.731
	2,4-二羟基苯甲酸2,4-Dihydroxybenzoic acid	-2.772
	缬氨酸-亮氨酸Val-Leu	-2.899
	前列腺素A1 Prostaglandin A1	-3.159
	9-氢过氧基-10E,12Z,15Z-十八碳三烯酸9-Hydroperoxy-10E,12Z,15Z-octadecatrienoic acid	-3.160
	穆坪马兜铃酰胺Moupinamide	-3.722
	(9S,10E,12S,13S)- 9,12,13-三羟基-10-十八碳烯酸(9S,10E,12S,13S)-9,12,13-Trihydroxy-10-octadecenoic acid	-3.923
	溶血磷脂酰胆碱18:3 LysoPC 18:3	-3.984
	(9ξ,10ξ,12ξ)- 9,10-二羟基-12-十八碳烯酸(9xi,10xi,12xi)-9,10-Dihydroxy-12-octadecenoic acid	-4.171
	去甲异波尔定Norisoboldine	-4.280

Table 3

Fig. 6

Fig. 7

Fig. 8

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基因 Gene	引物Primer	序列 Sequence (5′ to 3′)
Zm00001d028815	8815-1F	GACGCCTACAACTAAACC
Zm00001d028815	8815-1R	ACAACACAAGGACAGCAC
Zm00001d028816	8816-1F	GATTTCTTCCTTGCCTTTT
Zm00001d028816	8816-1R	ACACACCCACACACATTTG
Zm00001d028313	8313-2F	AAAGGAGGAAGGAGACCA
Zm00001d028313	8313-2R	CCCGCCATAGAAGATTGT
Zm00001d014250	4250F	AAGTGTCGCTGCAGAGGTTC
Zm00001d014250	4250R	TCCTTTAAGGCCGTCGCTTG
Zm00001d022139	2139F	CCGACAAGGCAAAGGATCTG
Zm00001d022139	2139R	GGCTCTCAGGCTCCTTCTTG
Zm00001d043528	3528-1F	AGCTTGCCCCTTTCTCAAC
Zm00001d043528	3528-1R	ACCAGGAACACCGTCATTT
Zm00001d017121	7121F	CCAATGCTAGCTGCACAACC
Zm00001d017121	7121R	AACAGCCTTAGCAGCTCCAG
Zm00001d004366	4366F	ACTCATTCCGCGACATCGAA
Zm00001d004366	4366R	GCGGTCATCGTCAAGGTACA
Zm00001d043144	3144F	ACGACGAGTTCGTCAAGGTC
Zm00001d043144	3144R	TGCACCAGCATGTACTGGAC
Zm00001d021168	1168F	CCAGGTTTCCACCGTGCTTC
Zm00001d021168	1168R	AGGACACGTACAGGACGGAC
Zm00001d009028	9028F	TTGAACTGCGCCGCCTTG
Zm00001d009028	9028R	AGGAAACCCACAGACTTGGC
GAPDH	GAPDH1F	CCATCACTGCCACACAGAAAAC
GAPDH	GAPDH1R	AGGAACACGGAAGGACATACCAG

样品 Sample	原始序列数 Raw reads	原始碱基数 Raw bases	有效序列数 Valid reads	有效碱基数 Valid bases	有效比率 Valid ratio (%)	Q20 (%)	Q30 (%)	基因组比对序列数Mapped reads
ZC17_MK1	48487174	7.27G	46461886	6.97G	95.82	99.94	97.59	41846591 (90.07%)
ZC17_MK2	38471678	5.77G	37250738	5.59G	96.83	99.95	98.99	33782858 (90.69%)
ZC17_MK3	42311182	6.35G	40990978	6.15G	96.88	99.95	98.79	37004587 (90.27%)
ZC17_FP1	44341730	6.65G	43314250	6.50G	97.68	99.95	98.69	39449341 (91.08%)
ZC17_FP2	44878826	6.73G	43756214	6.56G	97.50	99.95	98.70	39796076 (90.95%)
ZC17_FP3	44490646	6.67G	43362776	6.50G	97.46	99.95	98.99	39559652 (91.23%)
CH72_MK1	48737466	7.31G	47558210	7.13G	97.58	99.95	98.37	42325490 (89.00%)
CH72_MK2	39150064	5.87G	38093258	5.71G	97.30	99.96	99.02	34198799 (89.78%)
CH72_MK3	45219372	6.78G	44260068	6.64G	97.88	99.95	98.68	39511099 (89.27%)
CH72_FP1	47658538	7.15G	46484104	6.97G	97.54	99.96	98.56	41481231 (89.24%)
CH72_FP2	43802340	6.57G	42961890	6.44G	98.08	99.96	99.17	38760342 (90.22%)
CH72_FP3	41930108	6.29G	40712488	6.11G	97.10	99.96	99.13	34565595 (84.90%)

Integrating Transcriptomic and Metabolomic Analyses Reveals Maize Responses to Stalk Rot Caused by Fusarium proliferatum

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