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作物学报 ›› 2011, Vol. 37 ›› Issue (08): 1378-1388.doi: 10.3724/SP.J.1006.2011.01378

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

两个南方花生主栽品种荚果与叶片基因表达谱分析

陈小平,朱方何,洪彦彬,刘海燕,张二华,周桂元,李少雄,钟旎,温世杰,李杏瑜,梁炫强*   

  1. 广东省农业科学作物研究所, 广东广州 510640
  • 收稿日期:2011-01-15 修回日期:2011-04-27 出版日期:2011-08-12 网络出版日期:2011-06-13
  • 通讯作者: 梁炫强, E-mail: Liang804@yahoo.com; Tel: 020-87597315
  • 基金资助:

    本研究由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。

Analysis of Gene Expression Profiles in Pod and Leaf of Two Major Peanut Cultivars in Southern China

CHEN Xiao-Ping,ZHU Fang-He,HONG Yan-Bin,LIU Hai-Yan,ZHANG Er-Hua,ZHOU Gui-Yuan,LI Shao-Xiong,ZHONG Ni,WEN Shi-Jie,LI Xing-Yu,LIANG Xuan-Qiang*   

  1. Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China
  • Received:2011-01-15 Revised:2011-04-27 Published:2011-08-12 Published online:2011-06-13
  • Contact: 梁炫强, E-mail: Liang804@yahoo.com; Tel: 020-87597315

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1 383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。

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

Abstract: 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 utilized a high-density peanut oligonucleotide 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, 662 and 721 of which were up- and down-regulated, respectively, while 647 differentially expressed genes were detected in leaf, 234 and 413 of which were up- and down-regulated, respectively. Among the pod differentially expressed genes, 52 and 105 genes were, respectively, up- and down-regulated at least 10-fold, whereas only two and five were found in leaf. To further characterize these differentially expressed genes, we used Gene Ontology (GO) for annotation of them. 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.

Key words: Cultivated peanut (Arachis hypogaea L.), Microarray, Gene expression profiles, Differentially expressed genes, Real-time quantitative RT-PCR

[1]FAOSTAT. 2009.
[http://faostat.fao.org/site/567/DesktopDefault.aspx?PageID=567#ancor]
[2]Qiu L-J(邱丽娟), Wang C-L(王昌陵), Zhou G-A(周国安), Chen S-Y(陈受宜), Chang R-Z(常汝镇). Soybean molecular breeding. Sci Agric Sin (中国农业科学), 2007, 40(11): 2418–2436 (in Chinese with English abstract)
[3]Su Y(苏岩), Qian Q(钱前), Zeng D-L(曾大力). Current status and prospects of rice molecular design breeding. China Rice (中国稻米), 2010, 16(2): 5–9 (in Chinese)
[4]Schena M, Shalon D, Davis R W, Brown P O. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 1995, 270: 467–470
[5]Sreenivasulu N, Sunkar R, Wobus U, Strickert M. Array platforms and bioinformatics tools for the analysis of plant transcriptome in response to abiotic stress. Methods Mol Biol, 2010, 639: 71–93
[6]Aharoni A, Vorst O. DNA microarrays for functional plant genomics. Plant Mol Biol, 2002, 48: 99–118
[7]Luo M, Liang X Q, Dang P, Holbrook C C, Bausher M G, Lee R D, Guo B Z. Microarray-based screening of differentially expressed genes in peanut in response to Aspergillus parasiticus infection and drought stress. Plant Sci, 2005, 169: 695–703
[8]Payton P, Kottapalli K R, Rowland D, Faircloth W, Guo B, Burow M, Puppala N, Gallo M. Gene expression profiling in peanut using high density oligonucleotide microarrays. BMC Genomics, 2009, 10: 265
[9]Guo B, Chen X, Hong Y, Liang X, Dang P, Brenneman T, Holbrook C, Culbreath A. Analysis of gene expression profiles in leaf tissues of cultivated peanuts and development of EST-SSR markers and gene discovery. Int J Plant Genomics, 2009, (2009): Article ID 715605, DOI: 10.1155/2009/715605
[10]Guo B, Chen X, Dang P, Scully B T, Liang X, Holbrook C C, Yu J, Culbreath A K. Peanut gene expression profiling in developing seeds at different reproduction stages during Aspergillus parasiticus infection. BMC Dev Biol, 2008, 8: 12
[11]Kottapalli K R, Rakwal R, Shibato J, Burow G, Tissue D, Burke J, Puppala N, Burow M, Payton P. Physiology and proteomics of the water-deficit stress response in three contrasting peanut genotypes. Plant Cell Environ, 2009, 32: 380–407
[12]Yu S-L(禹山林). Peanut Variety in China and Its Pedigree( ). Shanghai: Shanghai Scientific and Technical Publishers, 2008. pp 401–445 (in Chinese)
[13]Boote K J. Growth stages of peanut (Arachis hypogaea L.). Peanut Sci, 1982, 9: 35–40
[14]Chang S, Puryear J, Cairney J. A simple and efficient method for isolating RNA from pine trees. Plant Mol Biol Rep, 1993, 11: 113–116
[15]Yang Y H, Dudoit S, Luu P, Lin D M, Peng V, Ngai J, Speed T P. Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucl Acids Res, 2002, 30: e15
[16]Tusher V G, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA, 2001, 98: 5116–5121
[17]Xiao J-H(肖景华), Wu C-Y(吴昌银), Han B(韩斌), Xue Y-B(薛勇彪), Deng X-W(邓兴旺), Zhang Q-F(张启发). Advances in rice functional genomics in China. Sci China (Ser C: Life Sci)(中国科学C辑: 生命科学), 2009, 39 (10): 909–924 (in Chinese with English abstract)
[18]Song X J, Huang W, Shi M, Zhu M Z, Lin H X. A QTL for rice grain width and weight encodes a previously unknown RING-type E3 ubiquitin ligase. Nat Genet, 2007, 39: 623–630
[19]Fan C, Yu S, Wang C, Xing Y. A causal C-A mutation in the second exon of GS3 highly associated with rice grain length and validated as a functional marker. Theor Appl Genet, 2009, 118: 465–472
[20]Lescallett J, Chicurel M E, Lipshutz R, Dalma-Weiszhausz D D. Monitoring eukaryotic gene expression using oligonucleotide microarrays. Methods Mol Biol, 2004, 258: 71–94
[21]Wang Y, Barbacioru C, Hyland F, Xiao W, Hunkapiller K L, Blake J, Chan F, Gonzalez C, Zhang L, Samaha R R. Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays. BMC Genomics, 2006, 7: 59
[22]Dallas P B, Gottardo N G, Firth M J, Beesley A H, Hoffmann K, Terry P A, Freitas J R, Boag J M, Cummings A J, Kees U R. Gene expression levels assessed by oligonucleotide microarray analysis and quantitative real-time RT-PCR—how well do they correlate? BMC Genomics, 2005, 6: 59
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