利用贝叶斯法进行水稻籽粒植酸含量性状的QTL定位及互作分析

doi:10.3969/j.issn.10017216.2009.05.05

中国水稻科学

利用贝叶斯法进行水稻籽粒植酸含量性状的QTL定位及互作分析

李茂柏^1,#. 王慧^1，#.张建明¹.李丁鲁².杨润清³.周宇琼³.朴钟泽^1,*

¹上海市农业科学院作物育种栽培研究所, 上海 201106; ²韩国农村振兴厅农业生命工学研究院, 韩国水原 441-707; 3上海交通大学农业与生物学院, 上海 200240; ^#共同第一作者；*通讯联系人, E-mail: zzpiao@163.com

收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-09-10 发布日期:2009-09-10

QTL Mapping and Epistasis Analysis for Phytic Acid Concentration in Rice Grain by Using the Bayesian Model Selection

LI Mao-bai^1,#, WANG Hui^1，#, ZHANG Jian-ming¹, LEE Jung-ro², YANG Run-qing³, ZHOU Yu-qiong³, PIAO Zhong-ze^1,2,*

¹Crop Breeding and Cultivation Research Institute, Shanghai Academy of Agricultural Sciences， Shanghai 201106, China; ²National Institute of Agricultural Biotechnology, Rural Development Administration, Suwon 441707， Korea; ³School of Agriculture and Biology, Shanghai Jiaotong University, Shanghai 200240, China； ^# These authors contributed equally to this paper; *Corresponding author， E-mail： zzpiao@163.com

Received:1900-01-01 Revised:1900-01-01 Online:2009-09-10 Published:2009-09-10

摘要/Abstract

摘要： 利用水稻植酸含量差异较大的品种中花11(粳型)和LPA（籼型）为亲本杂交获得F2群体的172个单株，构建了含126个SSR和4个STS标记的遗传连锁图谱，利用贝叶斯（Bayesian）法对水稻籽粒植酸含量性状进行了主效应QTL定位和上位性互作分析。共检测到 3 个与水稻籽粒植酸含量性状有关的主效QTL，分布在第3、5和6 染色体的相应区间内，表型贡献率分别为538%、802%和462%，降低籽粒植酸含量的等位基因均来自亲本LPA。检测到10对上位性互作影响籽粒植酸含量, 分布于水稻第1、3、5、6、11染色体上，互作效应值为169～518，其表型变异的解释率为867%～2473%。

关键词: 水稻, 植酸, 数量性状基因座, 贝叶斯法

Abstract: Main QTL and epistasis interaction effects for phytic acid concentration in rice grain were investigated by using a F2 population consisted of 172 lines derived from the cross between an indica rice LPA(the grain phytic acid concentration was 7.11 mg/g) and a japonica rice Zhonghua 11(the phytic acid concentration was 11.92 mg/g) with the Bayesian model selection. A genetic linkage map including 126 SSR and 4 STS markers was constructed with the F2 population. Three main QTLs related to phytic acid concentration in rice grain were detected. They were located on chromosomes 3, 5, and 6, explaining 5.38%, 802%, and 462% of phenotypic variation, respectively. The three alleles for reducing the phytic aid concentration were from the parent LPA. Ten pairs of epistatic interaction were detected on chromosomes 1, 3, 5, 6, and 11, with the interaction effects from 169 to 518 and the percentages of phenotypic variance ranged from 867% to 2473%.

Key words: Key words: rice, phytic acid, quantitative trait locus, Bayesian model

李茂柏,. 王慧,.张建明.李丁鲁.杨润清.周宇琼.朴钟泽,. 利用贝叶斯法进行水稻籽粒植酸含量性状的QTL定位及互作分析[J]. 中国水稻科学 2009,23(5): 475-480 . , DOI: 10.3969/j.issn.10017216.2009.05.05 .

LI Mao-bai,#,WANG Hui，#,ZHANG Jian-ming,LEE Jung-ro,YANG Run-qing,ZHOU Yu-qiong,PIAO Zhong-ze. QTL Mapping and Epistasis Analysis for Phytic Acid Concentration in Rice Grain by Using the Bayesian Model Selection[J]. Chinese Journal of Rice Science 2009,23(5): 475-480 ., DOI: 10.3969/j.issn.10017216.2009.05.05 .

参考文献

[1]张玉良, 李文新. 作物种子中植酸及其研究概况. 种子, 1991(4): 33-34.

[2]Francis G, Makkar H P S, Becker K. Antinutritional factors present in plantderived alternate fish feed ingredients and their effects in fish. Aquaculture,2001, 199(3/4): 197-227.

[3]Stephens L, Radenberg T, Thiel U, et al. The detection, purification, structural characterization and metabolism of diphosphoinositol pentakis phosphate(s). J Biol Chem, 1993, 268(6): 4009-4015.

[4]任学良, 舒庆尧. 低植酸作物的研究进展及展望. 核农学报, 2004, 18(6): 438-442.

[5]Li Z K, Pinson S R M, Paterson A H, et al. Epistasis for three grain yield components in rice(Oryza sativa L.). Genetics, 1997, 145(2): 453-465.

[6]黄祖六, 谭学林, Tragoonrung S, 等. 稻米直链淀粉含量基因座位的分子标记定位. 作物学报, 2000, 26(6): 777-782.

[7]吴长明, 孙传清, 陈亮, 等. 稻米营养品质性状的QTL及其与食味品质的关系研究. 吉林农业科学, 2002, 27(4): 3-7.

[8]姜树坤, 徐正进, 陈温福. 水稻QTL图位克隆的特征分析. 遗传, 2008, 30(9): 1121-1126.

[9]Stangoulis J C R, Huynh B L, Welch R M, et al. Quantitative trait loci for phytate in rice grain and their relationship with grain micronutrient content. Euphytica, 2007, 154(3): 289-294.

[10]Carlin B P, Louis T A. Bayes and empirical Bayes Methods for Data Analysis. London, UK: Chapman & Hall, 2000.

[11]Gelman A, Carlin J B, Stern H S, et al. Bayesian Data Analysis. London, UK: Chapman & Hall, 1995.

[12]Yi N J, Yandell B S, Churchill G A, et al. Bayesian model selection for genomewide epistatic quantitative trait loci analysis. Genetics, 2005, 170(3): 1333-1344.

[13]Yandell B S, Mehta T, Banerjee S, et al. R/qtlbim: QTL with Bayesian interval mapping in experimental crosses. Bioinformatics, 2007, 23(5): 641-643.

[14]AnkraBadu G A, Pomp D, Shriner D, et al. Genetic influences on growth and body composition in mice: Multilocus interactions. Int J Obesity, 2009, 33(1): 89-95.

[15]Miller G A, Youngs V L, Oplinger E S. Environment and cultivar effects on oat phytic acid concentration. Cereal Chem, 1980, 57(3): 189-191.

[16]Dai F, Wang J M, Zhang S H, et al. Genotypic and environmental variation in phytic acid content and its relation to protein content and malt quality in barley. Food Chem, 2007, 105(2): 606-611.

[17]Wang Z, Fang X J. Plant DNA isolation. Mol Plant Breed, 2003, 1(2): 281-288.

[18]Zheng J S, Lu B. PCR technique and its practical methods. Mol Plant Breed, 2003, 1(3): 381-394.

[19]Temnykh S, DeClerck G, Lukashova A, et al. Computational and experimental analysis of microsatellites in rice (Oryza sativa L.): Frequency, length variation, transposon associations, and genetic marker potential. Genome Res, 2001, 11: 1441-1452.

[20]Kao C H, Zeng Z B, Modeling epistasis of quantitative trait loci using Cockerham′s Model. Genetics, 2002, 160: 1243-1261.

[21]Yang R Q, Xu S Z. Bayesian shrinkage analysis of quantitative trait loci for dynamic traits. Genetics, 2007, 176(2): 1169-1185.

[22]Kass R E, Raftery A E. Bayes factors. J Am Sta Assoc, 1995, 90: 773-795.

[23]Larson S R, Rutger J N, Young K A, et al. Isolation and genetic mapping of a nonlethal rice (Oryza sativa L.) low phytic acid 1 mutation. Crop Sci, 2000, 40(5): 1397-1405.

[24]Andaya C B, Tai T H. Fine mapping of the rice low phytic acid (lpa1) locus. Theor Appl Genet, 2005, 111(3): 489-495.

[25]Liu Q L, Xu X H, Ren X L, et al. Generation and characterization of low phytic acid germplasm in rice (Oryza sativa L.). Theor Appl Genet, 2007, 114(5): 803-814.

[26]Cao G Q, Zhu J, He C X, et al. QTL analysis for epistatic effects and QTL×environment interaction effects on final height of rice. Acta Genet Sin, 2001, 28(2): 135-143.

利用贝叶斯法进行水稻籽粒植酸含量性状的QTL定位及互作分析

QTL Mapping and Epistasis Analysis for Phytic Acid Concentration in Rice Grain by Using the Bayesian Model Selection

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