水稻产量性状竞争优势QTL定位

【目的】检测与水稻产量性状竞争优势相关的数量性状座位（QTL），探讨水稻竞争优势的遗传基础。【方法】以特青为母本、以基于IR24遗传背景的6个IRBB近等基因系为父本，配组衍生了由204个水稻恢复系株系组成的重组自交系（RIL）群体，并用各个RIL与不育系中9A杂交获得测交F₁群体。两年同地种植两套群体，相邻两列并列种植相应的RIL和F₁，设2次重复。成熟时每份材料每个重复混收中间4株，考查单株穗数、每穗实粒数、每穗总粒数、结实率、千粒重和单株产量，计算得出2次重复的平均值。在各个性状上，以同一年的数据为基础，将F₁表现型减除对应RIL表现型，获得1套衍生数据。以（F₁-RIL）数据为基础，应用QTLNetwork 2.0检测QTL；经1 000次Permutation计算，选用全基因组显著性水平P＜0.05为阈值。【结果】6个产量性状在RIL和F₁群体之间均呈极显著正相关，相关系数以千粒重最高，为0.903；以单株穗数和单株产量最低，分别为0.333和0.357；结实率、每穗实粒数和每穗总粒数居中，分别为0.406、0.448和0.680。结果还表明，随着RIL表型值的增加，F₁杂种优势强度逐步降低、杂种劣势强度逐步升高。未检测到控制单株穗数的QTL，但在其他5个性状上共检测到16个QTL，分布于水稻第2、3、5、6、8和10染色体，其中，3个控制每穗实粒数，4个控制每穗总粒数，3个控制结实率，4个控制千粒重，2个控制单株产量，单个QTL的贡献率为1.7 %-22.1 %。控制每穗实粒数的所有3个QTL全部表现为中9A/IR24的竞争优势优于中9A/特青，而在每穗总粒数、结实率和千粒重上，分别有3、2和2个QTL表现为中9A/IR24的竞争优势优于中9A/特青，有1、1和2个QTL表现为中9A/特青的竞争优势优于中9A/IR24。在控制单株产量的2个QTL中，qGY2与控制每穗实粒数和每穗总粒数的qNGP2和qNSP2位于同一区间，qGY10与控制每穗实粒数和结实率的qNGP10和qSF10位于同一区间，它们均表现为中9A/IR24的竞争优势高于中9A/特青。【结论】亲本性状表现和杂种优势均对F₁的产量表现具有重要作用，与竞争优势有关的QTL对杂交稻产量性状遗传控制具有重要作用。

QTL Mapping for Standard Heterosis of Yield Traits in Rice

【Objective】 This study was conducted to determine quantitative trait loci (QTLs) associated with the standard heterosis of yield traits and to analyze the genetic basis of standard heterosis in rice. 【Method】 A recombinant inbred line (RIL) population was derived from crosses between rice restorer lines Teqing and six IRBB lines that are near isogenic lines in the genetic background of IR24. A testcross population was also constructed by crossing the 204 RILs to male sterile line Zhong 9A. The 204 sets of RILs and corresponding F₁ were grown side by side for two years in the same trial site. They were planted in two replications. At maturity, the middle four plants of each replication for each line were harvested together. The number of panicles per plant (NP), number of grains per panicle (NGP), number of spikelets per panicle (NSP), spikelet fertility (SF), 1000-grain weight (TGW) and grain yield per plant (GY) were measured. Mean values over the two replications were used for data analysis. A data set derived by subtracting the trait value of a RIL from that of its corresponding F₁ was used for QTL analysis using QTLNetwork 2.0. A putative QTL was claimed using a genome-wise type I error of P<0.05 determined by 1000 permutations. 【Result】 Significant positive correlations between the RILs and F₁s were observed for all the six traits. The correlation coefficients were highest for TGW (0.903), lowest for NP (0.333) and GY (0.357), and intermediate for SF (0.406), NGP (0.448) and NSP (0.680). A total of 16 QTLs distributed on chromosomes 2, 3, 5, 6, 8 and 10 were detected, including three (3) for NGP, four (4) for NSP, three (3) for SF, four (4) for TGW, and two (2) for GY. The phenotypic variance explained by a single QTL ranged from 1.7 % to 22.1 %. All three QTLs affecting NGP showed higher standard heterosis for Zhong 9A/IR24 than Zhong 9A/Teqing. For NSP, SF and TGW, three, two and two QTLs had higher standard heterosis for Zhong 9A/IR24 than Zhong 9A/Teqing, and one, one and two QTLs were higher in standard heterosis for Zhong 9A/Teqing than Zhong 9A/IR24. Of the two QTLs associated with GY, qGY2 overlapped with qNGP2 for NGP and qNSP2 for NSP, and qGY10 overlapped with qNGP10 for NGP and qSF10 for SF. All six QTLs showed higher standard heterosis for Zhong 9A/IR24 than Zhong 9A/Teqing. 【Conclusion】 F₁ performance was correlated with both parental performance and F₁ heterosis. QTLs for standard heterosis play an important role in the genetic control of F₁ performance of yield traits in rice.