摘要
利用高密度花生基因表达谱芯片比较遗传背景相似而在产量上存在显著差异的2个南方花生品种粤油7号和汕油523荚果与叶片的基因表达谱。结果表明,汕油523与粤油7号荚果差异表达基因高达1383个,其中上调表达基因662个,下调表达基因721个。叶片中差异表达基因有647个,其中上调表达基因234个,下调表达基因413个。基因表达差异在10倍以上的上调和下调基因在荚果中分别有52个和105个,而在叶片中只有2个和5个。功能注释结果表明,差异表达基因集中在细胞内和膜上,而其分子功能主要为结合和催化活性,主要参与代谢、细胞和生物调控等生物过程。在花生荚果和叶片中,还有近一半的差异表达基因的功能未知,表明这2个器官中还有大量的基因尚待发掘。为验证基因芯片数据的可靠性和重复性,选择4个差异表达基因进行实时定量PCR分析,其结果与芯片检测结果吻合。
Great improvements have been achieved in peanut yield, quality and resistance through traditional breeding methods. However, variations in gene expression profiles in major cultivars are yet unclear. Here, we used a high-density peanut oligonu-cleotide microarray to analyze gene expression profiles in pod and leaf of Shanyou 523 and Yueyou 7, which are widely grown in southern China. The results indicated that 1 383 differentially expressed genes were detected in pod, including 662 and 721 of genes were up-and down-regulated, respectively. Besides 647 differentially expressed genes were detected in leaf, including 234 and 413 of genes were up-and down-regulated, respectively. Among the pod differentially expressed genes, 52 and 105 genes were, up-and down-regulated at least 10-fold in pod, whereas only two and five were found in leaf. To further characterize these differentially expressed genes, we used Gene Ontology (GO) for their annotation. The results showed that a large proportion of differentially expressed genes from both pod and leaf were distributed in cell and membrane, possessed binding and catalytic activities and were involved in metabolic and cellular processes. Additionally, the expression of four differentially expressed genes was validated by real time qRT-PCR, further confirming the microarray results.
出处
《作物学报》
CAS
CSCD
北大核心
2011年第8期1378-1388,共11页
Acta Agronomica Sinica
基金
现代农业产业技术体系建设专项资金(nycyta-19)
国家自然科学基金项目(30971819
30900907)
广东省自然科学基金项目(10151064001000002)
粤港关键领域重点突破项目(2008A024200009)资助
关键词
花生栽培种
基因芯片
基因表达谱
差异表达基因
实时定量RT-PCR
Cultivated peanut (Arachis hypogaea L.); Microarray; Gene expression profiles; Differentially expressed genes; Real-time quantitative RT-PCR