IgA 肾病患者与膜性肾病患者外周血单核细胞mRNA分析

为了寻找诊断、鉴别IgA肾病(IgAN)和膜性肾病(MN)的血液特异性标记物,利用公共数据库中的IgAN和MN患者的外周血单核细胞(PBMCs)的转录组表达谱数据集识别特异性生物标记物,为诊断和鉴别提供简便、可靠的依据补充。从公共基因表达数据库(GEO)下载IgAN患者组(n=15)和MN患者组(n=8)芯片数据集,筛选前250个差异表达基因(DEGs)。通过分析筛选关键基因和途径,进行基因本体(GO)富集分析、京都基因与基因组百科全书(KEGG)通路分析和蛋白质与蛋白质相互作用关系(PPI)分析等进一步了解DEGs。通过分析共发现75个显著DEGs,其中73个上调基因,2个下调基因。GO富集分析的生物学过程(BP)主要包括蛋白质转运、内溶酶体到溶酶体转运、趋化因子介导的信号通路作用等。显著富集差异表达基因KEGG通路分析包括Endocytosis和Hepatitis B的相关信号通路。PPI筛选出EPS15、STAT4、CCL2、SUN2、SEC24C、SEC31A、GOLGB1、F2R,RAB12和PTK2B等关键基因。成功筛选出核心差异表达基因,为IgAN和MN的诊断和鉴别提供简便、可靠的依据补充,甚至提供治疗的新靶点。     

Uncovering the pathogenesis and identifying novel targets of pancreatic cancer using bioinformatics approach

Pancreatic cancer is a uniformly lethal disease that can be difficult to diagnose at its early stage. Thus, our present study aimed to explore the underlying mechanism and identify new targets for this disease. The data GSE16515, including 36 tumor and 16 normal samples were available from Gene Expression Omnibus. Differentially expressed genes (DEGs) were screened out using Robust Multichip Averaging and LIMMA package. Moreover, gene ontology and pathway enrichment analyses were performed to DEGs. Followed with protein–protein interaction (PPI) network construction by STRING and Cytoscape, module analysis was conducted using ClusterONE. Finally, based on PubMed, text mining about these DEGs was carried out. Total 274 up-regulated and 93 down-regulated genes were identified as the common DEGs and these genes were discovered significantly enriched in cell adhesion and extracellular region terms, as well as ECM-receptor interaction pathway. In addition, five modules were screened out from the up-regulated PPI network with none in down-regulated network. Finally, the up-regulated genes, including MIA, MET and CEACAMS, and down-regulated genes, such as FGF, INS and LAPP, had the most references in text mining analysis. Our findings demonstrate that the up- and down-regulated genes play important roles in pancreatic cancer development and might be new targets for the therapy.     

基于转录组的肝豆状核变性调控网络的构建和分析

本研究旨在利用生物信息学方法构建经铜诱导的ATP7B基因敲除HepG2细胞系的转录调控网络。探讨关键转录因子在肝豆状核变性发生、发展中的潜在作用机制。收集公共基因表达数据库（gene expression omnibus,GEO）中包含野生型、ATP7B基因敲除型、铜诱导的野生型和铜诱导的ATP7B基因敲除型HepG2细胞系数据。筛选由铜诱导产生的差异表达基因（differentially expressed genes,DEGs）后进行基因本体论（gene ontology,GO）、京都基因和基因组百科全书（Kyoto encyclopedia of genes and genomes,KEGG）富集分析。基于蛋白相互作用网络,识别疾病关键基因和功能模块,并对关键功能模块中的基因进行富集分析。最后,构建转录调控网络,筛选核心转录因子。共筛选出1 034个差异表达基因,其中上调525个,下调509个。上、下调关键功能模块分别包括了3 785个和3 931个基因。关键功能模块中的基因主要定位于细胞-基质连接、染色体、剪接复合体、核糖体等区域,共同参与了mRNA加工、组蛋白修饰、RNA剪切、DNA代谢调节、蛋白磷酸化等生物学过程,且与转录共调控活性、DNA转录因子结合、泛素样蛋白连接酶结合等分子功能相关。KEGG分析表明功能模块中的基因显著富集的通路包括乙型肝炎、有丝分裂原活化蛋白激酶（mitogen-activated protein kinase,MAPK）信号通路、细胞衰老和凋亡、神经营养信号通路和神经变性途径等。肝豆状核变性转录调控网络包括11个差异表达转录因子和96个差异表达基因,其中U2AF1、NFRKB、FUS、MAX、SRSF1、CEBPA和RXRA为核心差异表达转录因子。该研究为肝豆状核变性转录调控相关分子的生物学功能研究提供了重要的参考依据。     

RNA sequence analysis identified bone morphogenetic protein-2 (BMP2) as a biomarker underlying form deprivation myopia

PurposeForm deprivation myopia (FDM) is an urgent public issue characterized by pathological changes, but the underlying mechanism remained unclear. The aim was to investigate bone morphogenetic proteins (BMPs) utilizing the pathogenesis of FDM.Material and methodsGene expression omnibus (GEO) database was used to analyze one mRNA profile (GSE89325) of FDM. Sixteen retina samples (8 FDM and 8 controls) were randomly divided into seven groups for differential gene expression analysis in R. software. The gene pathway and protein-protein interaction (PPI) analysis were performed by the DAVID and STRING databases. Cytoscape was used to draw the PPI network. The gene ontology (GO) enrichment and Kyoto encyclopedia of genes and Genomes (KEGG) analysis were determined to achieve gene annotation and visualization.ResultsA total of 18420 differentially expressed genes (DEGs) were identified associated with FDM. The only non-significant gene (BEND6) was separately analyzed between two groups. Thirteen hub genes were discovered, ACVR1, ACVR2A, ACVR2B, RGMB, BMPR2, BMPR1A, BMP2, BMPR1B, CHRD, PTH, PTH1R, PTHLH, and WNT9A. The expression alteration in FDM were mainly enriched in cytokine-cytokine, and neuroactive ligand receptor interaction pathways. BMP2 was the key gene in myopia progression.ConclusionsOf clinical perspective, our findings reveal that expression of BMP2 as an underlying mechanism of FDM, providing an insight for therapeutic interventions.     

家兔前体脂肪细胞分化不同时期基因表达谱分析

脂肪的过度积累严重危害人类健康。前体脂肪细胞分化是脂肪发育的关键过程,研究前体脂肪细胞分化相关基因的表达有助于认识脂肪沉积的机理。尽管家兔是一种理想的研究脂肪发育的动物模型,但是针对其前体脂肪细胞分化不同时期基因表达谱的研究鲜见报道。本研究通过诱导家兔前体脂肪细胞分化,在分化第0 d、3 d和9 d收集脂肪细胞,利用转录组测序(RNA-seq),在分化第3 d样本与第0 d样本的比较中筛选出1352个差异表达基因(differentially expressed genes, DEGs),在分化第9 d样本与第3 d样本的比较中筛选出888个DEGs。GO (gene ontology)功能富集和KEGG (kyoto encyclopedia of genes and genomes)通路分析发现,0~3 d分化期上调的DEGs显著富集在PPAR信号通路和PI3K-Akt信号通路上,3~9d分化期上调的DEGs显著富集到与细胞周期调控有关的GO条目和KEGG信号通路,0~3d和3~9d阶段特异上调的DEGs可能分别作用于细胞质和细胞核。通过DEGs的蛋白-蛋白互作(protein-protein interaction, PPI)网络分析发现,筛选出的核心节点(hub node)基因可能通过调控细胞周期而影响家兔前体脂肪细胞分化。     

Bioinformatics Analysis of Microarray Data to Reveal Novel Genes Related to Cold-Resistance of Maize

Low temperature has become a major abiotic stress factor that can reduce maize yield and cause a number of economic loss. This study was designed to identify key genes and pathways associated with coldresistance of maize. The gene expression profile GSE46704, including 4 control temperature treated plants and 4 low temperature treated plants, was downloaded from the Gene Expression Omnibus database. Differentially-expressed genes (DEGs) were identified by limma package. Then, protein-protein interaction (PPI) network and module selection were constructed using Cytoscape. Moreover, the DEGs were re-matched based on the Zea mays L. gene ID and symbol data from PlantRegMap. Finally, the re-matched DEGs were performed functional and pathway enrichment analyses by the DAVID online tool. A total of 750 DEGs were screened (including 387 up-regulated and 363 down-regulated genes) In the PPI network, GRMZM2G070837_P01 and GRMZM2G114578_P01 had higher degrees. Besides, carbohydrate metabolic process, starch and sucrose metabolism and biosynthesis of secondary metabolites were significantly enriched in functional and pathway enrichment analysis. GRMZM2G070837_P01 and GRMZM2G114578_P01 might play a critical role in cold-resistance of maize. Meanwhile, carbohydrate metabolic process, starch and sucrose metabolism and biosynthesis of secondary metabolites might function in cold-resistance of maize.     

Identification of hub genes and pathways in adrenocortical carcinoma by integrated bioinformatic analysis

Adrenocortical carcinoma (ACC), a rare malignant neoplasm originating from adrenal cortical cells, has high malignancy and few treatments. Therefore, it is necessary to explore the molecular mechanism of tumorigenesis, screen and verify potential biomarkers, which will provide new clues for the treatment and diagnosis of ACC. In this paper, three gene expression profiles (GSE10927, GSE12368 and GSE90713) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were obtained using the Limma package. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were enriched by DAVID. Protein‐protein interaction (PPI) network was evaluated by STRING database, and PPI network was constructed by Cytoscape. Finally, GEPIA was used to validate hub genes’ expression. Compared with normal adrenal tissues, 74 up‐regulated DEGs and 126 down‐regulated DEGs were found in ACC samples; GO analysis showed that up‐regulated DEGs were enriched in organelle fission, nuclear division, spindle, et al, while down‐regulated DEGs were enriched in angiogenesis, proteinaceous extracellular matrix and growth factor activity; KEGG pathway analysis showed that up‐regulated DEGs were significantly enriched in cell cycle, cellular senescence and progesterone‐mediated oocyte maturation; Nine hub genes (CCNB1, CDK1, TOP2A, CCNA2, CDKN3, MAD2L1, RACGAP1, BUB1 and CCNB2) were identified by PPI network; ACC patients with high expression of 9 hub genes were all associated with worse overall survival (OS). These hub genes and pathways might be involved in the tumorigenesis, which will offer the opportunities to develop the new therapeutic targets of ACC.     

Analysis of the potential pathways and target genes in spinal cord injury using bioinformatics methods

Spinal cord injury (SCI) remains to be the most devastating type of trauma for patients because of long lasting disability and limited response to the acute drug administration and efforts at rehabilitation. With the purpose to identify potential targets for SCI treatment and to gain more insights into the mechanisms of SCI, the microarray data of GSE2270, including 119 raphe magnus (RM) samples and 125 sensorimotor cortex (SMTC) samples, was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened in RM group and SMTC group compared with their corresponding controls, respectively. A protein–protein interaction (PPI) network was constructed based on the common DEGs identified in both RM group and SMTC group. Gene ontology (GO) and pathway enrichment analyses of the overlapping DEGs were performed. Furthermore, the common DEGs enriched in each pathway were analyzed to identify significant regulatory elements. Totally, 173 overlapping DEGs (130 up-regulated and 43 down-regulated) were identified in both RM and SMTC samples. These overlapping DEGs were enriched in different GO terms. Pathway enrichment analysis revealed that DEGs were mainly related to inflammation and immunity. CD68 molecule (CD68) was a hub protein in the PPI network. Moreover, the regulatory network showed that ras-related C3 botulinum toxin substrate 2 (RAC2), CD44 molecule (CD44), and actin related protein 2/3 complex (ARPC1B) were hub genes. RAC2, CD44, and ARPC1B may be significantly involved in the pathogenesis of SCI by participating significant pathways such as extracellular matrix-receptor signaling pathway and Toll-like receptor signaling pathway.     

Ossification of the posterior longitudinal ligament related genes identification using microarray gene expression profiling and bioinformatics analysis

Ossification of the posterior longitudinal ligament (OPLL) is a kind of disease with physical barriers and neurological disorders. The objective of this study was to explore the differentially expressed genes (DEGs) in OPLL patient ligament cells and identify the target sites for the prevention and treatment of OPLL in clinic. Gene expression data GSE5464 was downloaded from Gene Expression Omnibus; then DEGs were screened by limma package in R language, and changed functions and pathways of OPLL cells compared to normal cells were identified by DAVID (The Database for Annotation, Visualization and Integrated Discovery); finally, an interaction network of DEGs was constructed by string. A total of 1536 DEGs were screened, with 31 down-regulated and 1505 up-regulated genes. Response to wounding function and Toll-like receptor signaling pathway may involve in the development of OPLL. Genes, such as PDGFB, PRDX2 may involve in OPLL through response to wounding function. Toll-like receptor signaling pathway enriched genes such as TLR1, TLR5, and TLR7 may involve in spine cord injury in OPLL. PIK3R1 was the hub gene in the network of DEGs with the highest degree; INSR was one of the most closely related genes of it. OPLL related genes screened by microarray gene expression profiling and bioinformatics analysis may be helpful for elucidating the mechanism of OPLL.     

转录组分析揭示东方蜜蜂微孢子虫侵染意大利蜜蜂的分子机制

【目的】本研究旨在通过差异表达基因(differentially expressed gene, DEG)分析以及毒力因子和其他侵染相关因子分析,在转录组水平揭示东方蜜蜂微孢子虫Nosema ceranae侵染意大利蜜蜂Apis mellifera ligustica的分子机制。【方法】基于前期已获得高质量的东方蜜蜂微孢子虫纯化孢子(NcCK)及侵染意大利蜜蜂工蜂7和10 d的东方蜜蜂微孢子虫(分别为NcT1和NcT2)转录组数据,根据P≤0.05且|log_2(Fold change)|≥1的标准,通过比较分析筛选出NcCK vs NcT1, NcCK vs NcT2和NcT1 vs NcT2比较组的DEG。通过相关生物信息学软件对上述DEG进行Venn分析、GO分类和KEGG代谢通路富集分析。根据Nr和KEGG数据库注释信息和相关文献进行对东方蜜蜂微孢子虫的毒力因子和侵染相关因子的统计和分析。通过RT-qPCR验证转录组数据及DEG表达趋势。【结果】从NcCK vs NcT1, NcCK vs NcT2和NcT1 vs NcT2比较组分别鉴定出1 397, 1 497和52个DEG。Venn分析结果显示各比较组共有的上调和下调基因分别为10和1个。GO分类结果显示,NcCK vs NcT1和NcCK vs NcT2中DEG富集数最多的功能条目为代谢进程、细胞进程、单组织进程、细胞、细胞组件、细胞器、催化活性和结合,而NcT1 vs NcT2中DEG富集数最多的是代谢进程、细胞进程、单组织进程、催化活性和结合。KEGG代谢通路富集分析结果显示,NcCK vs NcT1和NcCK vs NcT2中DEG分别富集到80和79条通路;富集在糖酵解/糖异生和MAPK信号通路的上调基因数量多于下调基因。毒力因子分析结果显示,孢壁蛋白9基因和孢壁蛋白12基因在NcCK vs NcT1和NcCK vs NcT2中均下调表达,孢壁蛋白8基因仅在NcCK vs NcT1中表达量下调;此外孢壁蛋白前体基因、孢壁和锚定盘复合蛋白基因、几丁质合酶基因、极管蛋白基因、蓖麻毒素B凝集素基因的表达水平在NcCK vs NcT1和NcCK vs NcT2中表现为上调。侵染相关因子分析结果表明,糖酵解途径的3个关键酶基因在NcCK vs NcT1和NcCK vs NcT2中上调表达;3个涉及ATP/ADP移位酶的基因在NcCK vs NcT1和NcCK vs NcT2中上调表达,但有1个表达量下调;2个涉及ABC转运蛋白的基因在NcCK vs NcT1和NcCK vs NcT2中上调表达,另有4个下调表达。RT-qPCR结果证实了本研究中转录组数据及DEG表达趋势的真实可靠性。【结论】本研究通过比较分析解析东方蜜蜂微孢子虫侵染意大利蜜蜂工蜂过程的转录组动态,揭示了孢壁蛋白、孢壁和锚定盘复合蛋白、几丁质酶、极管蛋白和蓖麻毒素B凝集素等毒力因子编码基因,以及己糖激酶、丙酮酸激酶、6-磷酸果糖激酶、ATP/ADP移位酶和ABC转运蛋白等侵染相关因子编码基因在病原增殖中扮演重要角色,为阐明东方蜜蜂微孢子虫的侵染机制提供了基础。     

COPD 差异表达基因的生物信息学分析及在LUSC样本中的表达

为确定慢性阻塞性肺病(COPD)的分子标记物及COPD与肺鳞状细胞癌(LUSC)共存的差异表达基因,探寻COPD合并肺癌的预测因子,发现新的治疗靶点。本研究采用生物信息学方法,从GEO数据库中筛选3套基因芯片数据集,挖掘COPD患者小气道上皮细胞(SAEC)的差异表达基因(DEG)以及潜在的生物标记物,并通过基因本体(GO)、京都基因与基因组百科全书(KEGG)富集分析预测DEGs的功能及参与的代谢途径。继而对DEGs构建PPI网络,使用Cytoscape软件筛选子模块和Hub基因,并将Hub基因通过TCGA数据库分析其在LUSC中的差异表达情况及差异基因间的相关性。结果共获得52个上调基因和24个下调基因,代谢通路主要集中在细胞色素P450对外源物质的代谢、化学致癌、花生四烯酸代谢及甲状腺激素合成四条途径上,通过Cytoscape软件从PPI网络中筛选得到2个功能模块和10个Hub基因,进一步验证发现其中5个基因在TCGA数据库中的LUSC样本中同样差异表达。由此推测SPP1、ALDH3A1、SPRR3、KRT6A和SPRR1B 可能为COPD 分子标记物及COPD与LUSC共存的DEGs,从而为研究COPD和LUSC的发病机制及二者潜在关系奠定良好的基础。     

小儿脓毒症休克相关基因的筛选及网络构建

为探究脓毒症休克与SIRS的差异表达基因及网络的构建,筛选潜在的核心基因,从GEO数据库下载相关基因表达谱GSE26378,数据分为脓毒症休克与SIRS各29个样本,通过在线软件GCBI对其进行标准化及差异基因筛选;对差异基因进行GO分析;基于KEGG进行功能通路分析以及基因信号网络分析;差异基因共表达网络分析。结果表明:两组中总共有1 456个基因被识别为差异基因(P0.05),与SIRS组相比,脓毒症休克组中有条859条下调基因,597条上调基因。GO功能富集分析显示差异基因主要参与了细胞周期、细胞免疫、细胞代谢。KEGG功能通路分析显示差异基因主要参与了MAPK信号通路、P53信号通路、wnt信号通路、细胞凋亡信号通路,细胞周期受体信号通路等。共表达分析发现基因CCNB1、NUSAP1、OIP5、SHCBP1、ZWINT、TOP2A、DLGAP5等位于网络中央部位,而基因信号网络分析发现基因PLCB1、PIK3CA、STAT3、CAMK2D、PRKCB、CREB1位于网络核心。基因芯片分析有助于发现脓毒症休克与SIRS患儿外周血单核细胞在转录组学上的改变,而生物信息学网络分析有助于发现潜在的靶点。     

The microRNA expression profiles of mouse mesenchymal stem cell during chondrogenic differentiation

MicroRNAs are potential key regulators in mesenchymal stem cells chondrogenic differentiation. However, there were few reports about the accurate effects of miRNAs on chondrogenic differentiation. To investigate the mechanisms of miRNAs-mediated regulation during the process, we performed miRNAs microarray in MSCs at four different stages of TGF-β3-induced chondrogenic differentiation. We observed that eight miRNAs were significantly up-regulated and five miRNAs were downregulated. Interestingly, we found two miRNAs clusters, miR-143/145 and miR-132/212, kept on down-regulation in the process. Using bioinformatics approaches, we analyzed the target genes of these differentially expressed miRNAs and found a series of them correlated with the process of chondrogenesis. Furthermore, the qPCR results showed that the up-regulated (or down-regulated) expression of miRNAs were inversely associated with the expression of predicted target genes. Our results first revealed the expression profiles of miRNAs in chondrogenic differentiation of MSCs and provided a new insight on complicated regulation mechanisms of chondrogenesis.     

基于高通量转录组测序技术的无精子症患者睾丸组织比较转录组分析

本研究探讨不同程度无精子症患者睾丸组织的转录组差异,了解差异表达基因(DEG)在功能、分类和代谢通路的不同,揭示无精子症患者精子发生分子机制,为促进男性不育研究的发展提供理论基础.选取1份非梗阻性无精子症和4份梗阻性无精子症患者睾丸组织样品(从无精子到有精子),进行RNA提取和文库构建,利用Illumina HiSeqTM2500高通量测序,构建无精子症患者睾丸组织转录组文库,并用生物信息学方法进行分析.结果发现,样品比对基因组数据库的平均比对率为94.38%,共检测2 242个属于预测新的蛋白质编码基因的转录本.得到差异表达基因统计结果为:NOA vs. OA1基因上调8 045,下调1 150;OA1 vs. OA2基因上调1 538,下调420;OA2 vs. OA3基因上调1 275,下调1 690;OA3 vs. OA4基因上调1 834,下调1 853.比较5例无精子症睾丸组织的差异基因KEGG,主要富集在RNA降解通路、基底细胞瘤通路、癌通路、黑色素生成通路和调节干细胞多能性等信号通路. PRM1、PRM2、TNP1、UBXN6、CXCL16、NUPR2、CCDC136和CRISP2等基因的表达呈递增趋势,并具有时序特异性.此外,5例无精子症睾丸组织的表达基因有不同程度的基因融合.综上,基因融合可能和无精子症相关,并且不同程度无精子症患者睾丸组织的差异表达基因数量、功能、分类和代谢通路不同.本研究筛选出精子发生、精子运动等差异表达基因,丰富了无精子症患者睾丸组织转录组信息,为开展无精子症患者睾丸组织相关基因及分子调控机制的研究奠定基础.     

侧孢短芽孢杆菌S2-31拮抗下细辛叶枯病菌转录组差异表达分析

通过分析侧孢短芽孢杆菌拮抗作用下叶枯病菌的转录组学特征,研究差异表达基因(DEGs)和代谢通路的富集情况,初步探索侧孢短芽孢杆菌拮抗叶枯病菌的分子机制。首先利用S2-31与叶枯病菌的对峙培养观察其拮抗作用,然后利用转录组测序探究侧孢短芽孢杆菌拮抗下和正常生长下的叶枯病菌的基因表达水平差异,并进行RT-qPCR验证,最后,利用相关数据库对DEGs进行注释和富集分析。对峙培养后,叶枯病菌菌丝出现皱缩、扭曲等现象。测序后共得到3681个DEGs,其中2224个相对上调,1457个相对下调。GO功能注释分析表明,上调和下调表达的DEGs均注释到生物过程8个亚群、细胞组分8个亚群和分子功能4个亚群。KEGG富集分析中,共有732个unigenes定位到115条生物学通路中,其中富集程度相对较高的通路有氨基糖和核苷糖代谢、糖基磷脂酰肌醇(GPI)锚定生物合成和过氧化物酶体;涉及差异基因较多的通路有淀粉和蔗糖代谢、剪接体和胞吞作用;上调表达的DEGs主要富集在代谢途径,下调表达的DEGs主要富集在遗传信息处理和细胞过程途径。从显著富集的通路中筛选出与菌丝生长发育相关的差异表达基因,结果表明侧孢短芽孢杆菌主要抑制病原菌菌丝过氧化物酶体的形成、胞吞过程和GPI锚定的合成等过程。差异表达基因的RT-qPCR验证结果与转录组测序的结果一致。在侧孢短芽孢杆菌S2-31的拮抗下抑制了叶枯病菌的生长,其转录组特征也发生显著变化,差异基因主要涉及代谢、细胞过程以及遗传信息处理等途径的相关通路。     

Bioinformatics identification of the methylerythritol phosphate pathway associated genes in <Emphasis Type="Italic">Arabidopsis thaliana</Emphasis> with <Emphasis Type="Italic">ceh1</Emphasis> mutant

The methylerythritol phosphate (MEP) pathway for the production of isoprenoids is recently discovered. The current study aimed to identify MEP pathway disorder-related molecular mechanisms and potential genes in Arabidopsis thaliana. Microarray data (GSE61675) obtained from ceh1 mutant plants and corresponding parental lines were retrieved from Gene Expression Omnibus (GEO) database and were applied for differentially expressed genes (DEGs) screening. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed. Protein-protein interaction (PPI) network was then constructed and displayed by Cytoscape software. Total 762 DEGs including 620 up-regulated and 142 down-regulated genes were screened. In addition, a great many of DEGs were mainly involved in biosynthesis and metabolism-related pathways, such as stilbenoid, diarylheptanoid, and gingerol biosynthesis, and biosynthesis of terpenoids and steroids. Moreover, a PPI network contained 90 down-regulated genes and 497 up-regulated genes were obtained. Up-regulated DEGs including glutaredoxin (GRX480, cytochrome BC1 synthase (BCS1, syntaxin of plants 121 (SYP121) and A. thaliana MAP kinase 11 (ATMPK11) with higher degree in this network were hub nodes. Pathways including stilbenoid, diarylheptanoid, and gingerol biosynthesis obtained in our study were consistent with previous studies. Importantly, GRX480, BCS1 and ATMPK11 could have close interactions with the MEP pathway and may play important roles in the biosynthesis of isoprenoids.