超级杂交稻两优培九产量杂种优势标记与QTL分析

doi:10.3864/j.issn.0578-1752.2014.14.001

摘要/Abstract

摘要： 【目的】对超级杂交稻两优培九影响产量及其构成因素性状的杂种优势位点进行定位，在此基础上探讨亲本培矮64S和9311的遗传差异与水稻产量性状的杂种优势间的关系，以探明水稻产量杂种优势的分子预测途径。【方法】应用经单粒传法获得后续世代的219个培矮64S×9311 F8重组自交系（RILs）株系材料与亲本培矮64S回交，并选用151个分布于水稻基因组12条染色体上的SSR多态性标记，构建回交群体RILs BCF1；构建基因组总长为1 617.7 cM、标记间平均距离10.93 cM和含151个分子标记的遗传图谱；采用分子标记技术和自由度不等的单向分组方差两组法、三组法分析，用SAS软件ANOVA分析、混合线性模型复合区间作图等方法，对回交RILs BCF1群体的产量性状及其构成因素的F1表型值进行相关分析、优势预测与QTL定位。【结果】本回交杂种群体RILs BCF1具备多种基因型，遗传变异丰富，性状平均值均显著高于亲本群体重组自交系RILs F8，共筛选到影响RILs BCF1群体产量及其构成因素性状杂种优势的阳性、增效位点74个；其中，三组法所筛选的阳性、增效位点数高于两组法，用这些阳性、增效位点所预测的遗传距离与产量F1性状值的相关性也显著提高；三组法所筛选产量性状的增效位点与两组法所筛选的增效位点完全一致；连锁紧密的位点有成簇分布的现象，每穗空粒数、每穗实粒数、结实率有6个杂种优势位点相同，并与3个产量杂种优势位点重叠，且均处在第7染色体上；通过逐步回归建立了对4个产量性状进行预测的回归方程模型；筛选到28个杂合型的特异性标记，它们与产量性状的表型值显著相关，使用特异性标记可使遗传距离与产量F1性状值的相关系数由全部标记的0.335提高到0.617；定位到3个与产量杂种优势相关的QTL和3个影响每穗实粒数杂种优势的QTL。其中，在第7染色体上影响每穗实粒数和产量杂种优势的QTL QGpp7和QHy7与影响每穗实粒数和产量杂种优势的增效位点的结果相符。【结论】通过增加筛选产量杂种优势阳性位点或增效位点数量、筛选影响杂种优势特异性分子标记的方法，可显著提高分子标记遗传距离与产量F1性状值的相关性，有效提高用分子标记遗传距离对杂种优势预测效率。定位了3个影响产量杂种优势的QTL及3个影响每穗总粒数杂种优势的QTL，分别在第2、3、7、11和12染色体上，其中，影响产量杂种优势的数量性状位点QHy7，贡献率为7.48%，可用于杂种优势的预测和杂交组合的选配。定位于第3染色体RM293—RM468的表型贡献率为14.9%的抽穗期QTL可用于早熟高产水稻的选育。

关键词: 超级杂交稻 , 产量性状杂种优势 , 杂种优势预测 , QTL定位

Abstract: 【Objective】 The heterosis loci and QTLs of yield and yield components were detected by using a RILsBCF1 population derived from a cross between Pei’ai 64S and 9311. The relationship was explored between the genetic variance of these two parental lines and yield heterosis in the resulted hybrid for predicting hybrid heterosis.【Method】Based on a population of 219 recombinant inbred lines (RILs) of F8 generation produced by single seed descendant method from the Pei’ai 64S×9311 cross, a RILsBCF1 population was generated by backcrossing of RILs to Pei’ai 64S. With a total of 151 polymorphic SSR markers, a linkage map was constructed spanning 1 617.7 cM across the whole genome with an average marker interval of 10.93 cM. The correlation between genetic distances and F1 trait performance of RILsBCF1 and their prediction in yield and yield component traits were conducted respectively by using molecular marker analysis, one-way ANOVA with different freedoms, and composite interval mapping using mix linear model in SAS, together with heterosis prediction and QTL mapping. 【Result】The RILsBCF1 used in the study showed significant diversity with high segregation in multiple traits, and their average performance was significantly higher than that of RILs F8. In this RILsBCF1 population, 74 heterosis positive loci and effect-increasing loci were identified by two-group method and three-group method in yield and yield component traits, respectively. Compared with two-group method, three-group method could get more positive loci or effect-increasing loci to a certain degree and raise efficiency of predicting correlationship between genetic distances of both positive loci and effect-increasing loci and F1 traits’ performances. The result of the effect-increasing loci detecting was the same in both two-group and three-group methods. Six heterosis loci were detected at the same regions for three traits (Sterile lemma per panicle, Grains per panicle and Pencentage seed setting), overlapped with three yield effect-increasing loci clustered on chromosome 7. Based on the relationship between marker-effect values of yield effect-increasing loci using the three-group method and F1 trait performance, four multiple regression prediction models were constructed using a stepwise procedure. A total of 28 markers with heterozygous genotypes were identified to significantly increase the correlation coefficient between the genetic distances and the F1 trait performance from 0.335 to 0.617. Three QTLs for yield heterosis and three QTLs for grain per panicle heterosis were mapped using this RILsBCF1 population. The mapped loci of QTL QGpp7 for grain per panicle heterosis and QHy7 for yield heterosis matched the effect-increasing loci identified by the methods of two-group and three group analyses. 【Conclusion】The approaches of screening more positive loci or effect-increasing loci and specific markers which influent heterosis can increase the correlation coefficient between the genetic distances and the F1 traits performances, and thus can be applied more efficiently in predicting the yield heterosis of rice hybrids with genetic distance of molecular markers. The yield QTL QHy7 located on chromosome 7 with a yield increase contribution of 7.48% can be used for yield heterosis prediction and in hybrid rice breeding. A heading stage QTL located between RM293-RM468 on chromosome 3 with the contribution of 14.9% can be used for rareripe high yield rice breeding.

Key words: super-yielding hybrid rice , yield component trait heterosis , heterosis prediction , QTL mapping

辛业芸1, 2, 袁隆平1, 2. 超级杂交稻两优培九产量杂种优势标记与QTL分析[J]. 中国农业科学, 2014, 47(14): 2699-2714.

XIN Ye-Yun-1, 2 , YUAN Long-Ping-1, 2 . Heterosis loci and QTL of Super Hybrid Rice Liangyoupeijiu Yield by Using Molecular Marker[J]. Scientia Agricultura Sinica, 2014, 47(14): 2699-2714.

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参考文献

[1]Smith O S, Smith J S, Bowen S L, Tenborg R A, Wall S J. Similarities among a group of elite maize inbreds as measured by pedigree, F1 grain yield, grain yield, heterosis, and RFLPs. Theoretical and Applied Genetics, 1990, 80: 833-840.

[2]Stuber C W, Lincoln S E, Wolff D W, Helentjaris T, Lander E S. Identification of genetic factors contributing to heterosis in a hybrid from two elite maize inbred lines using molecular markers. Genetics, 1992, 132: 823-839.

[3]Zhang Q, Gao Y J, Yang S H, Ragab R A, Saghai Maroof M A, Li Z B. Diallel analysis of heterosis in elite hybrid rice based on RFLPs and microsatellites. Theoretical and Applied Genetics, 1994, 89: 185-192.

[4]Zhang Q F, Gao Y J, Saghai Maroof M A, Yang S H, Li J X. Molecular divergence and hybrid performance in rice. Molecular Breeding, 1995, 1(2): 133-142.

[5]Zhang Q, Zhou Z Q, Yang G P, Xu C G, Liu K D, Saghai Maroof M A. Molecular marker heterozygosity and hybrid performance in indica and japonica rice. Theoretical and Applied Genetics, 1996, 93: 1218-1224.

[6]Xiao J, Li J, Yuan L, McCouch S R, Tanksley S D. Genetic diversity and its relationship to hybrid performance and heterosis in rice as revealed by PCR-based markers. Theoretical and Applied Genetics, 1996, 92(6): 637-643.

[7]Martin J M, Talbert L E , Lanning S P, Blake N K. Hybrid performance in wheat s related to parental diversity. Crop Science, 995, 35: 104-108.

[8]Diers B W, Mcvetty P B, Osborn T C. Relationship between heterosis and genentic distance based on restiriction fragment length polymer phism markers in oilseed rape (Brassica napus L.). Crop Science, 1996, 36: 79-83.

[9]Lee M, Godshalk E B, Lamkey K R, Woodman W W. Association of restriction fragment length polymorphisms among maize inbreds with agronomic performance of their crosses. Crop Science, 1989, 29(4): 1067-1071.

[10]蔡健, 兰伟. AFLP标记与水稻杂种产量及产量杂种优势的预测. 中国农学通报, 2005, 21(4): 39-43.

Cai J, Lan W. Using of AFLP marker to predict the hybrid yield and yield heterosis in rice. Chinese Agricultural Science Bulletin, 2005, 21(4): 39-43. (in Chinese)

[11]吴敏生, 王守才, 戴景瑞. RAPD分子标记与玉米杂种产量预测的研究. 遗传学报, 1999, 26(5): 578-584.

Wu M S, Wang S C, Dai J R. RAPD marker studies in predicting the heterosis of F1 yield in maize (Zea mays L.). Acta Genetica Sinica, 1999, 26(5): 578-584. (in Chinese)

[12]袁力行, 傅骏骅, 刘新芝, 彭泽斌, 张世煌, 李新海, 李连城. 利用分子标记预测玉米杂种优势的研究. 中国农业科学, 2000, 33(6): 6-12.

Yuan L X, Fu J H, Liu X Z, Peng Z B, Zhang S H, Li X H, Li L C. Study on prediction of heterosis in maize(Zea mays L.) using the molecular marker. Scientia Agricultura Sinica, 2000, 33(6): 6-12. (in Chinese)

[13]Saghai Maroof M A, Yang G P, Zhang Q, Gravois K A. Correlation between molecular marker distance and hybrid performance in US southern long grain rice. Crop Science, 1997, 37: 145-150.

[14]韦新宇, 许旭明, 张受刚, 卓伟, 马彬林, 杨腾帮, 杨旺兴, 邹文广, 范祖军. 籼粳交恢复系产量相关性状的遗传方差与杂种优势分析. 三明农业科技, 2010, 118(3): 2-5.

Wei X Y, Xu X M. Zhang S G, Zhuo W, Ma B L, Yang T B, Yang W X, Zou W G, Fan Z J. Genetic variance and heterosis in yield related traits of restorer lines of indica-japonica rice crosses. Sanming Agricultural Science and Technology, 2010, 118(3): 2-5. (in Chinese)

[15]Melchinger A E, Lee M, Lamkey K R, Hallauer A R, Woodman W L. Genetic diversity for RFLP: Relation to estimated genetic effect in maize inbreds. Theoretical and Applied Genetics, 1990, 80: 488-496.

[16]何光华, 侯磊, 李德谋, 罗小英, 牛国清, 唐梅, 裴炎. 利用分子标记预测杂交水稻产量及其构成因素. 遗传学报, 2002, 29(5): 438-444.

He G H, Hou L, Li D M, Luo X Y, Niu G Q, Tang M, Pei Y. Prediction of yield and yield components in hybrid rice by using molecular markers. Acta Genetica Sinica, 2002, 29(5): 438-444. (in Chinese)

[17]卢瑶, 凌英华, 杨正林, 陈春燕, 钟秉强, 何光华. 用二组法和三组法预测杂交稻米直链淀粉和蛋白质含量. 农业生物技术学报, 2008, 16(2): 309-314.

Lu Y, Ling Y H, Yang Z L, Chen C Y, Zhong B Q, He G H. Prediction of amylose and protein contents of indica rice by two-group method and three-group method. Journal of Agricultural Biotechnology, 2008, 16(2): 309-314. (in Chinese)

[18]查仁明, 桑贤春, 赵芳明, 凌英华, 罗洪发, 李云峰. AFLP增效和减效位点预测杂交水稻产量性状模型构建. 中国农学通报, 2010, 26(11): 18-22.

Zha R M, Sang X C, Zhao F M, Ling Y H, Luo H F, Li Y F. Foundation of predictive model of hybrid yield traits in rice (Oryza sativa L.) with effect-increasing and effect-decreasing loci of AFLP. Chinese Agricultural Science Bulletin, 2010, 26(11): 18-22. (in Chinese)

[19]查仁明, 杨正林, 赵芳明, 桑贤春, 凌英华, 谢戎, 何光华. 分子标记遗传效应预测杂交水稻产量性状. 植物遗传资源学报, 2010, 11(1): 72-77.

Zha R M, Yang Z L, Zhao F M, Sang X C, Ling Y H, Xie R, He G H. Prediction of F1 yield using genetic effects of molecular marker in indica rice(Oryza sativa L.). Journal of Plant Genetic Resources, 2010, 11(1): 72-77. (in Chinese)

[20]Bernardo R. Relationship between single-cross performance and molecular marker heterozygosity. Theoretical and Applied Genetics, 1992, 83: 628-634.

[21]吴敏生, 戴景瑞. AFLP标记与玉米杂种产量、产量杂种优势的预测. 植物学报, 2000, 42(6): 600-604.

Wu M S, Dai J R. Using of AFLP marker to predict the hybrid yield and yield heterosis in maize (Zea mays L.). Acta Botanica Sinica, 2000, 42(6): 600-604. (in Chinese)

[22]孙其信, 倪中福, 陈希勇, 刘志勇, 黄铁城. 冬小麦部分基因杂合性与杂种优势表达. 中国农业大学学报, 1997, 2(1): 64-116.

Sun Q X, Ni Z F, Chen X Y, Liu Z Y, Huang T C. Partial genome heterozygosity and heterosis in winter wheat. Journal of China Agricultural University, 1997, 2(1): 64-116. (in Chinese)

[23]Lin H X, Qian H R, Zhuang J Y, Lu J, Min S K, Xiong Z M, Huang N, Zheng K L. RFLP mapping of QTLs for yield and related characters in rice (Oryza sariva L.). Theoretical and Applied Genetics, 1996, 92: 920-927.

[24]Yano M, Sasaki T. Genetic and molecular dissection of quantitative traits in rice. Plant Molecular Biology, 1997, 35: 145-153.

[25]包劲松, 何平, 夏英武, 陈英, 朱立煌. 不同发育阶段水稻苗高的QTL分析. 遗传, 1999, 21(5): 38-40.

Bao J S, He P, Xia Y W, Chen Y, Zhu L H. Mapping QTLs for rice seedling height at different developmental stages. Hereditas, 1999, 21(5): 38-40. (in Chinese)

[26]廖春燕, 吴平, 易可可, 胡彬, 倪俊健. 不同遗传背景及环境中水稻穗长的QTLs和上位性分析. 遗传学报, 2000, 27(7): 599-607.

Liao C Y, Wu P, Yi K K, Hu B, Ni J J. QTLs and epistasis underlying rice (Oryza sariva L.) panicle length in different genetic background and environments. Acta Genetica Sinica, 2000, 27(7): 599-607. (in Chinese)

[27]陈深广, 沈希宏, 曹立勇, 占小登, 冯跃, 吴伟明, 程式华. 水稻产量性状杂种优势的QTL定位. 中国农业科学, 2010, 43(24): 4983-4990.

Chen S G, Shen X H, Cao L Y, Zhan X D, Feng Y, Wu W M, Cheng S H. QTL mapping for heterosis of yield traits in rice. Scientia Agricultura Sinica, 2010, 43(24): 4983-4990. (in Chinese)

[28]Tanksley S D. Mapping polygenes. Annual Review of Genetics, 1993, 27: 205-233.

[29]Xiao J H, Li J M, Yuan L P, Tanksley S D. Dominance is the major genetic basis in rice as revealed by QTL analysis using molecular markers. Genetics, 1995, 140(2): 745-754.

[30]吴晓林. 用分子标记预测植物和动物杂种优势的研究[D]. 长沙: 湖南农业大学, 2000.

Wu X L. Predicting heterosis using DNA markers in plant and animal species [D]. Changsha: Hunan Agriculture University, 2000. (in Chinese)

[31]徐建龙, 薛庆中, 罗利军, 黎志康. 水稻单株有效穗和每穗粒数的QTL剖析. 遗传学报, 2001, 28(8): 752-759.

Xu J L, Xue Q Z, Luo L J, Li Z K. QTL dissection of panicle number per plant and spikelet number per panicle in rice (Oryza sariva L.). Acta Genetica Sinica, 2001, 28(8): 752-759. (in Chinese)

[32]郑景生, 江良荣, 曾健敏, 林文雄, 李义珍. 应用明恢86和佳辐占的F2群体定位水稻部分重要农业性状和产量构成的QTL. 分子植物育种, 2003, 1(5/6): 633-639.

Zheng J S, Jiang L R, Zeng J M, Lin W X, Li Y Z. QTL analysis of heading date, plant height and yield components in F2 population derived from Minghui 86xJiafuzhan. Molecular Plant Breeding, 2003, 1(5/6): 633-639. (in Chinese)

[33]Zhou Y, Li W, Wu W, Chen Q, Mao D, Worland A J. Genetic dissection of heading time and its components in rice. Theoretical and Applied Genetics, 2001, 102: 1236-1242.