图1 主成分分析
纸质出版日期:2024-10-25,
收稿日期:2024-07-30
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为探究紫花苜蓿在石油污染下的耐受机理,采用超声碎促溶的方法,将3种有机物(十二烷、十六烷和二十四烷)配置成质量分数均为1%的混合溶液,模拟饱和烷烃污染对紫花苜蓿幼苗进行处理,分别对污染0,6, 24 h的植株取样进行转录组学分析,共获得1 431个差异表达基因(DEGs)。GO富集分析表明,这些DEGs主要涉及蛋白结合、代谢途径和催化活性等;KEGG富集分析表明,DEGs主要富集到植物病原体相互作用、MAPK信号通路和光合生物碳固定途径等。qRT-PCR验证转录组结果可靠。研究结果为研究植物降解和耐受原油中饱和石油烃污染机制原理及后续筛选和培育耐石油污染植物提供理论依据。
To explore the tolerance mechanism of Medicago sativa under oil pollution, this study adopted the method of ultrasonic crushing and solubilization to prepare a mixed solution of three organic compounds (Dodecane, n-Hexadecane, and n-Tetracosane) at a concentration of 1% to simulate saturated alkanes and treat Medicago sativa seedlings. Samples were taken from plants exposed to pollution for 0h, 6h, and 24h for transcriptomic analysis. The results showed that a total of 1431 DEGs were obtained. GO enrichment analysis indicated that these DEGs were mainly involved in protein binding, metabolic pathways, and catalytic activity. KEGG enrichment analysis showed that DEGs were mainly enriched in plant pathogen interaction, MAPK signaling pathway and photosynthetic biological carbon fixation pathway. qRT-PCR was further used to verify the reliability of the results. This study provides theoretical basis for exploring the mechanism of plant degradation and tolerance of saturated petroleum hydrocarbon in crude oil pollution, as well as subsequent screening and cultivation of petroleum-tolerant plants through transcriptome analysis of Medicago sativa treated with saturated alkanes.
石油由气态、液态和固态的烃类组成的混合物,通常贮藏在地壳上层部分[
紫花苜蓿(Medicago sativa)属于豆科苜蓿属,为多年生草本植物,主要种植在中国北方干旱、半干旱地区[
紫花苜蓿作为一种重要的牧草,其研究已经越来越深入。王天楚等将紫花苜蓿的种子在不同浓度的镉溶液中处理后继续培养生长,并对其幼苗进行指标测定,发现紫花苜蓿对于镉具有一定的富集作用[
对饱和烷烃胁迫处理前(0 h)和处理后6 h和24 h的紫花苜蓿植株进行转录组的高通量测序。各个样品的GC质量分数均超过42%,且Q20>96%,Q30>94%(见
样本信息 | 有效数据 | Q20/% | Q30/% | GC质量分数/% |
---|---|---|---|---|
CK-1 | 51137498 | 97.03 | 94.88 | 43.14 |
CK-2 | 44552210 | 96.83 | 94.49 | 42.93 |
CK-3 | 43676428 | 96.93 | 94.64 | 43.22 |
WR-6 h-1 | 47270614 | 96.93 | 94.67 | 43.20 |
WR-6 h-2 | 42207482 | 96.86 | 94.52 | 43.09 |
WR-6 h-3 | 47222008 | 96.97 | 94.72 | 42.97 |
WR-24 h-1 | 48684712 | 96.87 | 94.54 | 42.90 |
WR-24 h-2 | 45004252 | 96.82 | 94.59 | 42.70 |
WR-24 h-3 | 45496924 | 96.75 | 94.47 | 42.72 |
为了降低数据的复杂性,评估各个样品间的重复性,对9个测序样品进行了主成分分析。结果显示,对照组和处理组之间存在差异,且对照组CK-1、CK-2和CK-3之间重复性较好,模拟石油污染胁迫6 h的WR-6h-1、WR-6h-2和WR-6h-3较为集中,模拟石油污染胁迫24 h的WR-24h-1、WR-24h-2和WR-24h-3的距离较近,样品间重复性合理(见
图1 主成分分析
Fig.1 Principal component analysis
注: PC1为主成分1对区分样本的贡献度,PC2为主成分2对区分样本的贡献度。
使用基于负二项分布的DESeq2软件对Raw Counts进行分析,并将Padjust<0.05和|log2FC|≥1作为差异基因的筛选标准。结果显示,与对照(CK)组相比,在模拟石油污染胁迫6 h后,共检测到783个差异表达基因,其中480个基因表达上调,而303个基因表达下调。当模拟石油污染胁迫时间达到24 h时,差异表达基因的数量变为582个,其中434个基因表达上调,148个基因表达下调(见
图2 基因差异分析火山图
Fig.2 Volcano plot of gene differential expression analysis
注: FC (Fold Change)为差异倍数。
Venn图展示了各个基因集中基因的个数及它们间的重叠关系。将3组CKvsWR-6h、CKvsWR-24h和WR-6hvsWR-24h的DEGs进行比较得到
图3 差异基因表达 Venn 图
Fig.3 Venn diagram of differential gene expression
GO数据库(Gene Ontology)是由基因本体联合会(Gene Ontology Consortium)所建立的,是一个国际标准化的基因功能分类体系,可以对基因和蛋白的功能进行限定和描述。分别将CKvsWR-6h、CKvsWR-24h和WR-6hvsWR-24h的DCGs进行GO功能富集分析。
结果显示,在CKvsWR-6h组〔见
图4 转录组差异表达基因的 GO富集分析
Fig.4 GO enrichment analysis of differentially expressed genes from transcriptome data
在CKvsWR-24h组〔见
在WR-6hvsWR-24h组〔见
以上结果表明,各类膜结构在响应烷烃胁迫时发挥重要的作用,水杨酸、谷胱甘肽代谢过程在模拟石油污染下紫花苜蓿的响应方面产生一定影响,通过调节氧化还原系统及抗性信号转导帮助其缓解烷烃污染胁迫给机体带来的损伤。
KEGG (Kyoto Encyclopedia of Genes and Genomes)数据库是一个整合了基因组、化学和系统功能信息的综合性数据库,包含了基因、蛋白质、代谢物和信号通路等生物分子的综合信息。将CKvsWR-6h、CKvsWR-24h和 WR-6hvsWR-24h的差异表达基因进行了KEGG富集分析。
结果显示,在CKvsWR-6h组〔见
图5 转录组差异表达基因的KEGG富集分析
Fig.5 KEGG enrichment analysis of differentially expressed genes in transcriptome profiling
转录组测序共获得了1 431个差异表达基因,选取在抗氧化相关信号通路、非生物胁迫相关的信号通路和生长发育相关的信号通路中共10个最显著差异表达的基因进行验证。qRT-PCR验证结果如
图6 qRT-PCR验证差异表达基因
Fig.6 Validation of differentially expressed genes by qRT-PCR
注: p值,也称显著性值。以0 h为对照,*p<0.05,**p<0.01和***p<0.001。
紫花苜蓿作为一种重要的牧草,其生长和发育过程中常会受到各种环境胁迫的影响,这些胁迫可能来自干旱[
本研究对模拟石油污染处理不同时间的紫花苜蓿植株的转录组进行测序,进而研究紫花苜蓿应对模拟石油污染胁迫的深层机制,对于土壤修复和生态环境保护具有重要意义。本研究从CK vsWR-6h和CK vsWR-24 h中分别获得783个和582个差异表达基因〔见
RT-qPCR具有高灵敏度、高特异性、高通量、实时监测且不受物种限制[
以紫花苜蓿作为研究材料,用dH2O浸泡过夜后播种到营养土和蛭石1∶1配比的混合土中,在人工气候室(光照强度为100 μmol·m-2;温度25 ℃;光周期为16 h光照/8 h黑暗;空气湿度 65%)内进行培养。
待播种一周之后,将紫花苜蓿幼苗从土壤里移出,用清水洗干净其根部并移栽到水培箱中进行水培,加入适量的Hoagland培养液[
1%的模拟饱和烷烃污染混合溶液的配置方法如下:分别称取1 g的十二烷、十六烷和二十四烷于97 mL的ddH2O中,使用超声仪频率为45 kHZ超声30 min直至形成乳浊液。
分别收集胁迫6 h和24 h后的紫花苜蓿植株,以胁迫前(0 h)的紫花苜蓿植株作为对照,采集的紫花苜蓿植株经液氮研磨成粉末后立即放入-80 ℃冰箱中保存。每个处理组重复3次,每个样品共收集1 g材料。
所有紫花苜蓿样本基于Illumina Novaseq 6000 测序平台完成转录组的测序,测序采用Illumina TruseqTM RNA sample prep Kit方法进行文库构建。
为保证后续生物信息分析的准确性,使用fastp软件对原始测序数据进行过滤,从而得到高质量的测序数据(clean data),以保证后续分析的顺利进行。使用HISAT2[
使用软件RSEM[
将选取的10个显著差异基因进行qRT-PCR分析以验证数据的可靠性。使用Trizol法提取对照组和处理组样品的总RNA,cDNA按照PrimeScript 1st Strand cDNA试剂盒说明书反转录合成。以GAPDH作为内参基因,各基因序列引物设计在附录中(见
基因编号 | 基因名称 | 正向引物 | 反向引物 |
---|---|---|---|
MsG0680034725.01 | protein REDOX2-Like | TTGGCAGCAAGGGAAACTGA | TCCAAGAGCTGACCAAGCAC |
MsG0580024680.01 | NAC family transcription factor | TGCAATGTCCCTCCTATGGC | AGGGGAGATCCAGAAGGTTGA |
MsG0880044306.01 | gibberellin 2-beta-dioxygenase 1 | TGCACCTTTGCCTTGTCTCA | TCTCTCAAAGTGACAAAGCCT |
MsG0380015231.01 | glutathione S-transferase,amino-terminal | ACACAAGGCATAGCATAGCATA | GTCCACCAAAACATAGTGGGG |
MsG0780039504.01 | cytochrome P450 76T24 | GAGCCGCAATGAAATGGTGC | ATAGCTCTGCCATGACCCAC |
MsG0480021753.01 | L-ascorbate oxidase homolog | GCACAAGTGAATGGCAAGCA | CTTCAGAGGAGTGTCGGCTG |
MsG0380016748.01 | peroxidase P7 | AGAAACTCTGCTCGTGGATTTG | CAGCACATGATACAACGCCAG |
MsG0280008006.01 | flowering-promoting factor 1-like proten 1 | CAATCACGGCATCAGCGAGGAG | CTTGCGTAGCCAACACTCTCACC |
MsG0580028960.01 | transcription factor MYB1 | AGGTGTTGGTTCATACCGCA | TGAGCGTTTGTGGAACTGGA |
MsG0180000525.01 | transcription factor WRKY7 | GACCAACATGTGTGAGAACTATGA | ACTTTCACTCTCAGCTTTTCTCTTT |
* | GAPDH | TCATTCCGTGTCCCAACCG | CCACATCATCTTCAGTGTAACCCA |
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