影响水稻穗部性状及籽粒碾磨品质的QTL及其环境互作分析

doi:10.3724/SP.J.1006.2011.01175

摘要/Abstract

摘要： 利用优质恢复系测258为轮回亲本与粳型糯稻新品系IR75862杂交创制的BC₁F₇回交导入系群体，在广西南宁和海南三亚定位了产量相关性状(二次枝梗数、穗总粒数、穗实粒数、粒重和穗重)、粒型(粒长、宽、厚)和碾磨品质(糙米率、精米率和整精米率)的主效QTL并剖析其环境互作效应。双亲在穗实粒数、千粒重、粒长和粒宽及整精米率等性状上存在显著差异。各产量相关性状间呈极显著正相关，而与千粒重和粒长呈极显著负相关。多数产量及粒型相关性状与3种碾磨品质相关不显著。在南宁和三亚环境下检测到影响产量相关性状、粒型及碾磨品质的主效QTL共计57个，包括二次枝梗数的6个，穗实粒数4个，穗总粒数、粒重和穗重各5个，粒长9个，粒宽7个，粒厚1个，糙米率4个，精米率5个和整精米率6个，分布在除第11染色体外的所有染色体上。多数影响枝梗数、穗粒数和粒重的QTL成簇分布，而且与影响BR、MR和HR的QTL分布在不同染色体区域。在第2、第3、第4、第5和第6染色体上鉴定出影响穗粒数、粒重、粒型及碾磨品质的重要QTL，这些QTL在以往不同遗传背景和环境下被多次检测到。在第8染色体RM152~RM310区间鉴定到1个影响粒长和粒宽的新的QTL，能同步增加粒宽和粒长。鉴定出的这些稳定表达的QTL具有标记辅助选择育种的应用价值。整精米率是受环境影响最大的性状，其QTL的环境互作效应明显。对QTL的环境互作效应特点及其在品种标记辅助改良中的作用进行了深入探讨。

关键词: 数量性状基因座, 基因与环境互作, 导入系, 碾磨品质, 产量相关性状

Abstract: QTLs and their interactions with environments for yield-related traits—second branch number (SBN), spikelet number per panicle (SNP), filled grains number per panicle (FGN), 1000-grain weight (TGW) and panicle weight (PW); grain type traits—grain length (GL), width (GW) and thinkness (GT); and milling quality traits—brown rice percentage (BR), milled rice percentage (MR) and head rice percentage (HR) were identified and analyzed in the two environments, Nanning of Guangxi and Sanya of Hainan, using an introgression line population derived from the cross of recurrent parent Ce258 and a donor IR75862. There were significant differences in FGN, TGW, GL, GW and HR between the two parents. Significant correlations were found among the yield-related traits, and they were strikingly negatively correlated with TGW and GL. Most yield-related traits and grain type had no significant correlations with the three milling quality traits. A total of 57 QTLs were identified for yield-related traits, grain type and milling quality, including six for SBN, four for FGN, five for each of SNP, PW and TGW, nine for GL, seven for W, one for GT, four for BR, five for MR and six for HR, which distributed on all chromosomes except chromosome 11. Most QTLs affecting SBN, SNP and TGW clustered and distributed in the chromosomes independent of the QTLs for BR, MR and HR. Some important QTLs for the above traits were identified on chromosomes 2, 3, 4, 5, and 6 which had been previously detected many times in various genetic backgrounds and environments. One QTL affecting GL and GW in the region of RM152-RM310 on chromosome 8 was newly identified, which simultaneously increased GL and GW. The stable QTLs identified in this study are of importance for marker-assisted selection (MAS) in rice breeding programs. In addition, HR was largely affected by environment and the QTLs for HR had a significant interaction with environment. The interaction characteristics of QTL with environment and its application in MAS were deeply discussed in the paper.

Key words: Quantitative trait locus, QTL ×, environment interaction, introgression lines, milling quality, yield-related traits

胡霞, 石瑜敏, 贾倩, 徐琴, 王韵, 陈凯, 孙勇, 朱苓华, 徐建龙, 黎志康. 影响水稻穗部性状及籽粒碾磨品质的QTL及其环境互作分析[J]. 作物学报, 2011, 37(07): 1175-1185.

HU Xia, SHI Yu-Min, JIA Qian, XU Qin, WANG Yun, CHEN Kai, SUN Yong, ZHU Lian-Hua, XU Jian-Long, LI Zhi-Kang. Analyses of QTLs for Rice Panicle and Milling Quality Traits and Their Interaction with Environment[J]. Acta Agron Sin, 2011, 37(07): 1175-1185.

参考文献

[1]Peng S B, Cassman K G, Virmani S S, Sheehy J, Khush G S. Yield potential trends of tropical rice since the release of IR8 and the challenge of increasing rice yield potential. Crop Sci, 1999, 39: 1552–1559
[2]Juliano B O, Villareal C P. Grain Quality Evaluation of World Rice. Manila, Philippines: International Rice Research Institute, 1993. pp 35–60
[3]Jennings P R, Kauffman W R. Rice Improvement. Los Banos, Laguna, Philippines: International Rice Research Institute, 1979. pp 101–120
[4]Khush G S. Prospects of and approaches to increasing the genetic yield potential of rice. In: Evenson R E, Herdt R W, Hossain M, eds. Rice Research in Asia: Progress and Priorities. CAB International, Wallingford: UK at the University Press, Cambridge, 1996. pp 59–71
[5]Takita T. Inheritance of grain size and the relationship between grain size and other characters in rice. Bull Nat Agric Res Cent, 1985, 3: 55–71
[6]Chauhan J S. Inheritance of grain weight, size and shape in rainfed rice (Oryza sativa L.). Indian J Agric Sci, 1998, 68: 9–12
[7]Zhu J, Weir B S. Analysis of cytoplasmic and maternal effects: II. Genetic models for triploid endosperms. Theor Appl Genet, 1994, 89: 160–166
[8]Shi C H, Zhu J, Zang R C, Chen G L. Genetic and heterosis analysis for cooking quality traits of indica rice in different environments. Theor Appl Genet, 1997, 95: 294–300
[9]Zhuang J Y, Lin H X, Qian G R, Hittalmani S, Huang N, Zheng K L. Analysis of QTL × environment interaction for yield components and plant height in rice. Thero Appl Genet, 1997, 95: 799–808
[10]Li Z K, Pinson S R M, Park W D, Paterson A H, Stansel J W. Epistasis for three grain yield components in rice (Oryza sativa L.). Genetics, 1997, 145: 453–465
[11]Xu J L, Yu S B, Luo L J, Zhong D B, Sanchez A, Mei H W, Khush G S, Li Z K. Molecular dissection of the primary sink size in rice (Oryza sativa L.). Plant Breed, 2004, 123: 43–50
[12]Fan C, Xing Y, Mao H, Lu T, Han B, Xu C, Li X, Zhang Q. GS3, a major QTL for grain length and weight and minor QTL for grain width and thickness in rice, encodes a putative transmembrane protein. Theor Appl Genet, 2006, 112: 1164–1171
[13]Zheng T Q, Xu J L, Li Z K, Zhai H Q, Wan J M. Genomic regions associated with milling quality and grain shape identified in a set of random introgression lines of rice (Oryza sativa L.). Plant Breed, 2007, 126: 158–163
[14]Ando T, Yamamoto T, Shimizu T, Ma X, Shomura A, Takeuchi Y, Lin S Y, Yano M. Genetic dissection and pyramiding of quantitative traits for panicle architecture by using chromosomal segment substitution lines in rice. Theor Appl Genet, 2008, 116: 881–890
[15]Xing Y-Z(邢永忠), Xu C-G(徐才国), Hua J-P(华金平), Tan Y-F(谈移芳). Analysis of QTL × Environment interaction for rice oanicle characteristics. Acta Genet Sin (遗传学报), 2001, 28(5): 439–446 (in Chinese with English abstract)
[16]Temnykh S, DeClerck G, Lukashova A, Lipovich L, Cartinhour S, McCouch S. 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
[17]SAS Institute. SAS/STAT User’s Guide. SAS Institute, Cary, 1996
[18]Wang D L, Zhu J, Li Z K, Paterson A H. Mapping QTLs with epistatic effects and QTL × environment interactions by mixed linear model approaches. Theor Appl Genet, 1999, 99: 1255–1264
[19]Wang Y, Kuroda E, Hirano M. Analysis of high yielding mechanism on rice varieties belonging to different plant types. Jpn J Crop Sci, 1997, 66: 293–299
[20]Xu Z-J(徐正进), Chen W-F(陈温福), Ma-D-R(马殿荣), Lü Y-N(吕英娜), Zhou S-Q(周淑清), Liu L-X(刘丽霞). Correlations between rice grain shapes and main qualitative characteristics. Acta Agron Sin (作物学报), 2004, 30(9): 894–900 (in Chinese with English abstract)
[21]Liu J-F(刘家富), Kui L-M(奎丽梅), Zhu Z-F(朱作峰), Tan L-B(谭禄宾), Wang G-J(王桂娟), Li Q-W(黎其万), Shu J-H(束继红), Sun C-Q(孙传清). Identification of QTLs associated with processing quality and appearance quality of common wild rice (Oryza rufipogon Griff.). J Agric Biotechnol (农业生物技术学报), 2007, 15(1): 90–96 (in Chinese with English abstract)
[22]Yao G-X(姚国新), Li J-J(李金杰), Zhang Q(张强), Hu G-L(胡广隆), Chen C(陈超), Tang B(汤波), Zhang H-L(张洪亮), Li Z-C(李自超). Mapping QTLs for grain weight and shape using four sister near isogenic lines in rice (Oryza sativa L.). Acta Agron Sin (作物学报), 2010, 36(8): 1310–1317 (in Chinese with English abstract)
[23]Lu C, Shen L,Tan Z, Xu Y, He P, Chen Y, Zhu L. Comparative mapping of QTLs for agronomy traits of rice across environments using a doubled haploid population. Theor Appl Genet, 1996, 93: 1211–1217
[24]Li Z K, Pinson S R M, Stansel J W, Paterson A H. Genetic dissection of the source-sink relationship affecting fecundity and yield in rice (Oryza sativa L.). Mol Breed, 1998, 4: 419–426
[25]Mei H W, Xu J L, Li Z K, Yu X Q, Guo L B, Wang Y P, Ying C S, Luo L J. QTLs influencing panicle size detected in two reciprocal introgressive line (IL) populations in rice (Oryza sativa L.). Theor Appl Genet, 2006, 112: 648–656
[26]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
[27]Shomura A, Izawa T, Ebana K, Ebitani T, Kanegae H, Konishi S, Yano M. Deletion in a gene associated with grain size increased yields during rice domestication. Nat Genet, 2008, 40: 1023–1028
[28]Wang E, Wang J, Zhu X, Hao W, Wang L, Li Q, Zhang L, He W, Lu B, Lin H, Ma H, Zhang G, He Z. Control of rice grain-filling and yield by a gene with a potential signature of domestication. Nat Genet, 2008, 40: 1370–1374
[29]Paterson A H, Damon S, Hewitt J D, Zamir D, Rabinowitch H D, Lincoln S E, Lander E S, Tanksley S D. Mendelian factors underlying quantitative traits in tomato: comparison across species, generations and environments. Genetics, 1991, 127: 181–197
[30]Li Z K, Yu S B, Lafitte H R, Huang N, Courtois B, Hittalmani S, Vijayakumar C H M, Liu G F, Wang G C, Shashidhar H E, Zhuang J Y, Zheng K L, Singh V P, Sidhu J S, Srivantaneeyakul S, Khush G S. QTL × environment interactions in rice. I. Heading date and plant height. Theor Appl Genet, 2003, 108: 141–153
[31]Jansen R C, Stam P. High resolution of quantitative traits into multiple loci via interval mapping. Genetics, 1994, 136: 1447–1485
[32]Wang S C. Simulation Study on the Methods for Mapping Quantitative Trait Loci in Inbred Line Crosses. PhD Dissertation of Zhejiang University, 2000
[33]Wang Y(王韵), Cheng L-R(程立锐), Sun Y(孙勇), Zhou Z(周政), Zhu L-H(朱苓华), Xu Z-J(徐正进), Xu J-L(徐建龙), Li Z-K(黎志康). Genetic background effect on QTL expression of heading date and plant height and their interaction with environment in reciprocal introgression lines of rice. Acta Agron Sin (作物学报), 2009, 35(8): 1386–1394 (in Chinese with English abstract)

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