摘要
以抗旱性强的花生品种丰花5号为材料,利用Solexa高通量测序技术对15%PEG处理后的花生叶片cDNA文库进行差异基因表达谱分析。结果表明,转录组基因表达表现出高度的不均一性和冗余性,低于10个拷贝的标签占总标签种类的73.1%,但其表达量只占总标签表达量的9.0%。根据已知序列信息鉴定出935个差异表达基因,其中64.5%下调表达。基因功能分析表明,差异表达基因广泛涉及糖、蛋白、核酸和脂类等生物大分子代谢、能量代谢以及次生代谢过程。在花生干旱响应基因表达谱分析中,发现9个类黄酮代谢相关基因在干旱胁迫下显著上调表达,其中4个编码类黄酮合成酶类,3个编码甲基转移酶,2个编码MYB转录因子。通过半定量RT-PCR对花生苯丙氨酸解氨酶基因(AhPAL)表达分析表明,15%PEG干旱胁迫6h诱导该基因显著表达。推测类黄酮代谢在花生干旱胁迫响应中起重要作用。
Drought, one of the most important abiotic stresses, usually causes adverse effects on the productivity and quality of crops. In this study, a drought-resistant variety Fenghua 5 was used to analyse leaf cDNA library of peanut treated with 15% PEG by Solexa high-throughput technology, and detect the differentially expressed genes under drought stress. The results of Solexa sequencing indicated the gene expression in peanut transcriptome presented strong nonhomogeneity and redundancy. The se- quenced tags less than 10 copies accounted for 73.1% of the total tag types, however its expression level only accounted for 9.0% of the total. A total of 935 differentially expressed genes were screened out based on the reference tags, of which 64.5% were down-regulated. These differentially expressed genes were involved in metabolisms of carbohydrate, protein, nucleic acid, lipid and energy, and secondary metabolism. Gene expression analysis of peanut also showed that nine transcripts related to flavonoid metabolism significantly up-regulated under drought stress, including four encoding flavonoid biosynthesis enzymes, three en- coding methyltransferase and two encoding MYB transcription factor. The gene expression analysis using semi-quantitative RT-PCR assays indicated that AhPAL was induced significantly by 15% PEG treatment for 6 h. The result showed that flavonoid metabolism might play an important role in peanut responding to drought stress.
出处
《作物学报》
CAS
CSCD
北大核心
2013年第6期1045-1053,共9页
Acta Agronomica Sinica
基金
国家现代农业产业技术体系建设专项(CARS-14-07B)
国家自然科学基金项目(31101177)
山东省自然科学基金项目(ZR2011CQ027)资助
关键词
花生
干旱
高通量测序
基因表达谱
Peanut
Drought
High-throughput sequencing
Gene expression profile