摘要
为了发掘影响水稻产量及其相关性状的QTL和重要的染色体区间,本研究利用以大穗型品种川香29B(籼稻)为母本,Lemont(粳稻)为父本构建了包含184个株系的F8重组自交系群体。在2009年,对单株有效穗数、穗长、一次枝梗数、二次枝梗数、每穗实粒数、每穗总粒数、着粒密度、结实率、千粒重和单株产量10个性状进行了QTL分析。主要研究结果如下：
(1)构建了一张水稻全基因组的遗传连锁图,该图谱包含98个SSR标记,总长为1244.8 cM,平均标记距离是17.25 cM。
(2)相关分析表明,单株产量与单株有效穗数、一次枝梗数、二次枝梗数、每穗实粒数、每穗总粒数、着粒密度、结实率和千粒重的相关性都到达显著或极显著正相关,只与穗长无显著相关性；单株有效穗数与穗长、一次枝梗数、二次枝梗数、每穗实粒数、每穗总粒数和着粒密度呈极显著负相关；穗长与一次枝梗数、二次枝梗数、每穗实粒数和每穗总粒数呈极显著正相关；二次枝梗数与一次枝梗数、每穗实粒数、每穗总粒数和着粒密度呈正相关,与千粒重呈负相关,与结实率相关不显著；单株有效穗数、穗长和一次枝梗数与结实率和千粒重的相关性都不显著；每穗实粒数与着粒密度和结实率呈极显著正相关,而与千粒重无显著相关性；每穗总粒数与着粒密度呈极显著正相关,千粒重呈极显著负相关,与结实率的相关性不显著；着粒密度与千粒重呈极显著负相关,与结实率相关性不显著；结实率与千粒重无显著相关性。
(3)在水稻全基因组内,共检测到28个影响产量及其相关性状的QTL。控制单株有效穗数的QTL有2个,命名为qNP-1和qNP-3,贡献率分别是7.47%和8.12%。控制穗长的QTL有5个,它们的贡献率在6.59%-15.53%之间,其中qPLT-3-3的LOD值和贡献率分别是3.06和15.53%。影响一次枝梗数的QTL有3个,单个QTL的贡献率在5.20%-32.11%之间,其中,qNPB-3的LOD值和贡献率为5.10和32.11%。控制二次枝梗数的QTL有3个,单个QTL贡献率在6.04%-10.78%之间。影响每穗实粒数的QTL有2个,命名为qNFGP-2和qNFGP-3,后者贡献率较大,为18.08%。控制每穗总粒数的QTL有3个,单个QTL贡献率在13.64%-19.86%之间,其中qTNSP-3的贡献率是19.86%。影响着粒密度的QTL有3个,贡献率在6.85%-11.84%之间。控制结实率的QTL有3个,贡献率变幅较小,在6.26%-6.96%之间。影响千粒重的QTL只有1个,命名为qTGWT-5,LOD值和贡献率分别2.96和7.02%。与单株产量有关的QTL有3个,命名为qGYD-3-1、qGYD-3-2和qGYD-5,它们的贡献率分别是14.05%、17.41%和10.62%。
(4)本研究发现了5个QTL成簇分布区间。在第3染色体上,有2个QTL成簇分布区间,分别是区间RM514-RM1004和RM520-RM3513。在RM514-RM1004区间内,存在控制穗长、结实率和单株产量部分QTL。在区间RM514-RM3684之中,存在控制穗长、一次枝梗数、每穗实粒数和每穗总粒数的部分QTL。在第4染色体的RM5503-RM1113区间内,存在控制每穗总粒数的qTNSP-4和控制着粒密度的qSD-4。在第5染色体上,影响穗长和千粒重的部分QTL在RM164-RM3437区间内。在第6染色体的RM5371-RM7193区间之中,存在控制二次枝梗数、每穗总粒数和着粒密度的部分QTL。
To explore the major QTL and important chromosome regions of the rice yield and its related traits, a recombinant inbred line (F8) population with 184 lines, derived from a cross between Chuanxiang 29B (Oryza sativa L. subsp. indica) and Lemont (O. satva L. subsp. japonica), was developed. And in 2009 year, the QTL of ten traits including NP, PL, NPB, NSB, NFGP, TNSP, SD, SSR, TGWT and GYD were exploited. The major results were as follows:
(1) A genetic linkage map of rice, which contained 98 SSR markers, was constructed. The map covered a total of 1244.8 cM with an average interval of 17.25 cM.
(2) The analysis of correlation between ten yield and its related traits indicated that: GYD had a positive or significant positive correlation with NP, NPB, NSB, NFGP, SD, TNSP and SSR, TGWT, and had no significant correlation with PL. NP had a significant negative correlation with PL, NPB, NSB, NFGP, TNSP and SD. PL had a significant positive correlation with NPB, NSB, NFGP and TNSP. NSB had a significant positive correlation with NPB, NFGP, TNSP and SD, and a significant negative correlation with TGWT, and no significant correlation with SSR. NP, PL and NPB had no significant correlation with SSR and TGWT. NFGP had a significant positive correlation with SD and SSR, and no significant correlation with TGWT. TNSP had a significant positive correlation with SD, and a negative correlation with TGWT, and no significant correlation with SSR. SD had a significant negative correlation with TGWT, and no significant correlation with SSR. And SSR had no significant correlation with TGWT.
(3) A total of twenty eight QTL, distributed on 1st、2nd、3rd、4th、5th、6th、7th、8th and 10th chromosome of rice, were detected. The two QTL named qNP-1 and qNP-3 were found to control NP. And their contributions were 7.47% and 8.12%, respectively. There were five QTL for PL. And their contributions were a range from 6.59% to 15.53%, in which qPLT-3-3 explained 15.53% of the total phenotypic variance. The three QTL were detected to control NPB. Their contributions were a range from 5.20% to 32.11%, in which the LOD score and contribution of qNPB-3 was 5.10 and 32.11%, respectively. There were three QTL controlling NSB. Their contributions were a range from 6.04% to 10.78%. There were two QTL named qNFGP-2 and qNFGP-3. And the contribution of qNFGP-3 was 18.08%. There were three QTL controlling TNSP. Their contributions were a range from 13.64% to 19.86%, in which qTNSP-3 explained 19.86% of the total phenotypic variance. There were three QTL controlling SD. And their contributions were a range from 6.85% to 11.84%. There were three QTL influencing SSR. Their contributions were a range from 6.26% to 6.96%. The one QTL for TGWT, named qTGWT-5, were found. Its LOD score and contribution were 2.96 and 7.02%. And three QTL controlling GYD were detected, named qGYD-3-1, qGYD-3-2 and qGYD-5, with the contribution of 14.05%, 17.41% and 10.62%, respectively.
(4) And there were five QTL clusters. On the 3rd chromosome, there were two clusters. A QTL cluster for PL, SSR and GYD was located between RM514 and RM1004, and another QTL cluster for PL, NSB, NFGP and TNSP was located between RM520 and RM3513. On the 4th chromosome, there was a QTL cluster for TNSP and SD between RM5503 and RM1113. On the 5th chromosome, a QTL cluster for PL and TGWT was detected between RM164 and RM3437. On the 6th chromosome, there was a QTL cluster for NBP, TNSP and SD between RM5371 and RM7193.
引文
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