Novel pleiotropic loci controlling panicle architecture across environments in japonica rice （Oryza sativa L.）

To identify quantitative trait loci (QTLs) controlling panicle architecture in japonica rice, a genetic map was constructed based on simple sequence repeat (SSR) markers and 254 recombinant inbred lines (RILs) derived from a cross between cultivars Xiushui 79 and C Bao. Seven panicle traits were investigated under three environments. Single marker analysis indicated that a total of 27 SSR markers were highly associated with panicle traits in all the three environments. Percentage of phenotypic variation explained by single locus varied from 2% to 35%. Based on the mixed linear model, a total of 40 additive QTLs for seven panicle traits were detected by composite interval mapping, explaining 1.2%-35% of phenotypic variation. Among the 9 QTLs with more than 10% of explained phenotypic variation, two QTLs were for the number of primary branches per panicle (NPB), two for panicle length (PL), two for spikelet density (SD), one for the number of secondary branches per panicle (NSB), one for secondary branch distribution density (SBD), and one for the number of spikelets per panicle (NS), respectively. qPLSD-9-1 and qPLSD-9-2 were novel pleiotropic loci, showing effects on PL and SD simultaneously. qPLSD-9-1 explained 34.7% of the phenotypic variation for PL and 25.4% of the phenotypic variation for SD, respec- tively. qPLSD-9-2 explained 34.9% and 24.4% of the phenotypic variation for PL and SD, respectively. The C Bao alleles at the both QTLs showed positive effects on PL, and the Xiushui 79 alleles at the both QTLs showed positive effects on SD. Genetic variation of panicle traits are mainly attributed to additive effects. QTL × environment interactions were not significant for additive QTLs and additive × additive QTL pairs.     

水稻糙米重金属Cd含量的QTL分析

镉(Cd²⁺)是一种分布较广泛、毒性较强的一种重金属, 文章利用韭菜青×IR26杂交衍生的一个重组自交系群体(Recombinant inbred lines, RIL)及构建的SSR分子遗传图谱, 对控制糙米中Cd²⁺含量的QTL进行分析, 为选育籽粒中Cd²⁺低吸收或低积累的水稻品种提供参考。结果表明, 在Cd²⁺胁迫(5 mg/kg)处理条件下, 共检测到2个与糙米Cd²⁺含量有关的QTLs, 分别位于水稻第11染色体上的标记RM6288-RM6544和RM167-RM5704之间, 其中qCCBR-11a对表型贡献率为11.17%, 加性效应0.089; qCCBR-11b对表型变异贡献率为7.66%, 加性效应0.075。相关分析显示, 糙米Cd²⁺含量与株高、每穗总粒数、每穗实粒数、结实率和千粒重等产量性状的相关性均不显著, 糙米中Cd²⁺含量是一个相对独立、由基因控制的遗传性状。     

Quantitative Trait Loci for Panicle Layer Uniformity Identified in Doubled Haploid Lines of Rice in Two Environments

Uniformity of stem height in rice directly affects crop yield potential and appearance, and has become a vital index for rice improvement. In the present study, a doubled haploid (DH) population, derived from a cross between japonica rice Chunjiang 06 and indica rice TN1 was used to analyze the quantitative trait locus (QTL) for three related traits of panicle-layer-uniformity; that is, the tallest panicle height, the lowest panicle height and panicle layer disuniformity in two locations: Hangzhou (HZ) and Hainan (HN). A total of 16 QTLs for three traits distributed on eight chromosomes were detected in two different environments. Two QTLs, qTPH -4 and qTPH -8 were co-located with the QTLs for qLPH -4 and qLPH -8, which were only significant in the HZ environment, whereas the qTPH -6 and qLPH -6 located at the same interval were only significant in the HN environment. Two QTLs, qPLD -10-1 and qPLD -10-2, were closely linked to qTPH-10 , and they might have been at the same locus. One QTL, qPLD -3, was detected in both environments, explaining more than 23% of the phenotypic variations. The CJ06 allele of qPLD -3 could increase the panicle layer disuniformity by 9.23 and 4.74 cm in the HZ and HN environments. Except for qPLD -3, almost all other QTLs for the same trait were detected only in one environment, indicating that these three traits were dramatically affected by environmental factors. The results may be useful for elucidation of the molecular mechanism of panicle-layer-uniformity and marker assisted breeding for super-rice.     

Identification of QTLs for Yield and Associated Traits in F₂ Population of Rice

Identification of quantitative trait loci (QTLs) controlling yield and yield-related traits in rice was performed in the F₂ mapping population derived from parental rice genotypes DHMAS and K343. A total of 30 QTLs governing nine different traits were identified using the composite interval mapping (CIM) method. Four QTLs were mapped for number of tillers per plant on chromosomes 1 (2 QTLs), 2 and 3; three QTLs for panicle number per plant on chromosomes 1 (2 QTLs) and 3; four QTLs for plant height on chromosomes 2, 4, 5 and 6; one QTL for spikelet density on chromosome 5; four QTLs for spikelet fertility percentage (SFP) on chromosomes 2, 3 and 5 (2 QTLs); two QTLs for grain length on chromosomes 1 and 8; three QTLs for grain width on chromosomes1, 3 and 8; three QTLs for 1000-grain weight (TGW) on chromosomes 1, 4 and 8 and six QTLs for yield per plant (YPP) on chromosomes 2 (3 QTLs), 4, 6 and 8. Most of the QTLs were detected on chromosome 2, so further studies on chromosome 2 could help unlock some new chapters of QTL for this cross of rice variety. Identified QTLs elucidating high phenotypic variance can be used for marker-assisted selection (MAS) breeding. Further, the exploitation of information regarding molecular markers tightly linked to QTLs governing these traits will facilitate future crop improvement strategies in rice.     

普通野生稻中增产相关QTL的发掘

普通野生稻(Oryza Rufipogon)是重要的遗传资源,发掘其优良等位基因将对水稻遗传改良产生重要影响。文章从以珍汕97为轮回亲本,普通野生稻为供体的BC2F1群体中选择一个与珍汕97表型明显不同的单株BC2F1-15,经过连续自交获得回交重组自交系BC2F5群体。均匀分布于12条染色体的126个多态性SSR(Simplesequence repeats)标记基因型分析,发现BC2F1-15单株在30%的标记位点为杂合基因型;利用该群体共检测到4个抽穗期、3个株高、4个每穗颖花数、2个千粒重和1个单株产量QTL。在第7染色体RM481-RM2区间,检测到抽穗期、每穗颖花数和产量QTL,野生稻等位基因表现增效作用;其他3个每穗颖花数QTL位点,野生稻等位基因也均具有增效作用。结果表明野生稻携带有增产相关的等位基因,这些有利等位基因无疑是水稻遗传改良可资利用的新资源。     

Additive and additive × additive interaction make important contributions to spikelets per panicle in rice near isogenic (Oryza sativa L.) lines

Epistasis plays an important role in the genetic basis of rice yield traits. Taking interactions into account in breeding programs will help the development of high-yielding rice varieties. In this study, three sets of near isogenic lines (NILs) targeting three QTLs for spikelets per panicle (SPP), namely qSPP1, qSPP2 and qSPP7, which share the same Zhenshan 97 genetic background, were used to produce an F 2 population in which the three QTLs segregated simultaneously. The genotypes of the individual F 2 plants at the three QTLs were replaced with three markers that are closely linked to the corresponding QTLs. These QTLs were validated in the F 2 and F 3 popula- tions at the single marker level. qSPP7 exhibited major pleiotropic effects on SPP, plant height and heading date. Multifactor analysis of variance was performed for the F 2 population and its progeny. Additive × additive interaction between qSPP2 and qSPP7 had significant effects on SPP in both the F 2 population and its progeny. Both additive and additive × additive interactions could explain about 73% of the total SPP phenotypic variance. The SPP performance of 27 three-locus combinations was ranked and favorable combinations were rec- ommended for rice breeding in different ecosystems.     

Additive and additive x additive interaction make important contributions to spikelets per panicle in rice near isogenic （Oryza sativa L.） lines

Epistasis plays an important role in the genetic basis of rice yield traits. Taking interactions into account in breeding programs will help the development of high-yielding rice varieties. In this study, three sets of near isogenic lines (NILs) targeting three QTLs for spikelets per panicle (SPP), namely qSPP1, qSPP2 and qSPP7, which share the same Zhenshan 97 genetic background, were used to produce an F₂ population in which the three QTLs segregated simultaneously. The genotypes of the individual F₂ plants at the three QTLs were replaced with three markers that are closely linked to the corresponding QTLs. These QTLs were validated in the F₂ and F₃ populations at the single marker level. qSPP7 exhibited major pleiotropic effects on SPP, plant height and heading date. Multifactor analysis of variance was performed for the F₂ population and its progeny. Additive (additive interaction between qSPP2 and qSPP7 had significant effects on SPP in both the F₂ population and its progeny. Both additive and additive (additive interactions could explain about 73% of the total SPP phenotypic variance. The SPP performance of 27 three-locus combinations was ranked and favorable combinations were recommended for rice breeding in different ecosystems.     

Mapping quantitative trait loci associated with arsenic accumulation in rice (Oryza sativa)

The quantitative trait loci (QTLs) associated with arsenic (As) accumulation in rice were mapped using a doubled haploid population established by anther culture of F1 plants from a cross between a Japonica cultivar CJ06 and an Indica cultivar TN1 (Oryza sativa). Four QTLs for arsenic (As) concentrations were detected in the map. At the seedling stage, one QTL was mapped on chromosome 2 for As concentrations in shoots with 24.4% phenotypic variance and one QTL for As concentrations in roots was detected on chromosome 3. At maturity, two QTLs for As concentrations in grains were found on chromosomes 6 and 8, with 26.3 and 35.2% phenotypic variance, respectively. No common loci were detected among these three traits. Interestingly, the QTL on chromosome 8 was found to be colocated for As concentrations in grain at maturity and shoot phosphorus (P) concentrations at seedling stage. These results provide an insight into the genetic basis of As uptake and accumulation in rice, and will be useful in identifying genes associated with As accumulation.     

云南元江普通野生稻穗颈维管束和穗部性状的QTL分析

以云南元江普通野生稻为供体亲本,籼稻品种特青为轮回亲本构建高代回交群体,用SSR标记构建连锁图谱,在第1、2、3、4、7和10染色体上定位到7个控制穗颈大维管束数的QTL,在第1、2、3、4和8染色体上定位到5个控制穗颈小维管束数的QTL,在第11和12以外的10条染色体上,共定位到15个控制穗一、二次枝梗数和穗颖花数QTL。来自野生稻的等位基因大多表现负效,能显著减少群体的穗颈维管束数、枝梗数和颖花数,说明从野生稻演化成栽培稻的过程中,可能淘汰了一些对产量不利的QTL,保留了有利的QTL。相当一部分控制穗颈维管束数、枝梗数及颖花数的QTL在染色体上成簇分布或紧密连锁,且加性效应的方向一致,从理论上解释了这些性状表型显著相关的遗传基础,同时也说明在人工选择或自然选择下,这些性状可能存在平行进化或协同进化的关系。     

Identification of quantitative trait loci associated with small brown planthopper (Laodelphax striatellus Fallén) resistance in rice (Oryza sativa L.)

F(2) and BC(1) populations derived from the cross between 02428 / Rathu Heenati were used to investigate small brown planthopper (SBPH) resistance. Using the F(2) population, three QTLs for antixenosis against SBPH were located on chromosomes 2, 5 and 6, and accounted for 30.75% of the phenotypic variance; three QTLs for antibiosis against SBPH were detected on chromosomes 8, 9 and 12. qSBPH5-c explaining 7.21% of phenotypic variance for antibiosis was identified on chromosome 5 using the BC(1) population. A major QTL, qSBPH12-a1, explained about 40% of the phenotypic variance, and a minor QTL, qSBPH4-a, was detected by the SSST method in both the F(2) and BC(1) populations. The QTLs indentified in the present study will be useful for marker assisted selection of SBPH resistance in rice.     

Grain yield responses to moisture regimes in a rice population: association among traits and genetic markers

Drought is a major constraint to rice (Oryza sativa L.) production in rainfed and poorly irrigated environments. Identifying genomic regions influencing the response of yield and its components to water deficits will aid our understanding of the genetic mechanism of drought tolerance (DT) of rice and the development of DT varieties. Grain yield (GY) and its components of a recombinant inbred population developed from a lowland rice and an upland rice were investigated under different water levels in 2003 and 2004 in a rainout DT screening facility. Correlation and path analysis indicated that spikelet fertility (SF) was particularly important for grain yield with direct effect (P=0.60) under drought stress, while spikelet number per panicle (SN) contributed the most to grain yield (P=0.41) under well-watered condition. A total of 32 quantitative trait loci (QTLs) for grain yield and its components were identified. The phenotypic variation explained by individual QTLs varied from 1.29% to 14.76%. Several main effect QTLs affecting SF, 1,000-grain weight (TGW), panicle number (PN), and SN were mapped to the same regions on chromosome 4 and 8. These QTLs were detected consistently across 2 years and under both water levels in this study. Several digenic interactions among yield components were also detected. The identification of genomic regions associated with GY and its components under stress will be useful to improve drought tolerance of rice by marker-aided approaches.G. H. Zou and H. W. Mei contribute equally to this work.     

粳稻穗部结构性状的QTL分析

利用温带粳稻‘沈农265’和‘丽江新团黑谷’构建的重组自交系群体,在沈阳和哈尔滨两地对15个穗部结构性状进行了QTL分析。共检测到61个相关QTL,其中沈阳检测到的38个QTL在第1、4、6、11和12号染色体上形成了sir-QTL簇;而在哈尔滨检测到的31个QTL也在第3、9和10号染色体上形成了QTL簇。仅有8个QTL是在两地同时被检测到的,分别是控制一次枝梗数#＇．jqPBN4、控制穗长的qPL6和qPL9、控制一次枝梗实粒数的qGNPB4、控制一次枝梗颖花数的qTSNPBJ、控制结实率的qPSSIO、以及控制着粒密度qSD3和qSD9。其中,qPBN4（最高表型贡献率43．2％）、qPL9（最高表型贡献率63．2％）、qGNPB4（最高表型贡献率30．9％）和qSD9（最高表型贡献率42．9％）是主效QTL。通过进一步的分析发现控制穗长qPL9和控制着粒密度qSD94于DEPl所在区间。同时控制一次枝梗数和一次枝梗实粒数的位于第4号染色体长臂端的穗部结构主效QTL,qPBN4qGNPB4极富研究与应用价值。     

Genetic Analysis and QTL Detection for Resistance to White Tip Disease in Rice

The inheritance of resistance to white tip disease (WTDR) in rice (Oryza sativa L.) was analyzed with an artificial inoculation test in a segregating population derived from the cross between Tetep, a highly resistant variety that was identified in a previous study, and a susceptible cultivar. Three resistance-associated traits, including the number of Aphelenchoides besseyi (A. besseyi) individuals in 100 grains (NA), the loss rate of panicle weight (LRPW) and the loss rate of the total grains per panicle (LRGPP) were analyzed for the detection of the quantitative trait locus (QTL) in the population after construction of a genetic map. Six QTLs distributed on chromosomes 3, 5 and 9 were mapped. qNA3 and qNA9, conferring reproduction number of A. besseyi in the panicle, accounted for 16.91% and 12.54% of the total phenotypic variance, respectively. qDRPW5a and qDRPW5b, associated with yield loss, were located at two adjacent marker intervals on chromosome 5 and explained 14.15% and 14.59% of the total phenotypic variation and possessed LOD values of 3.40 and 3.39, respectively. qDRPW9 was considered as a minor QTL and only explained 1.02% of the phenotypic variation. qLRGPP5 contributed to the loss in the number of grains and explained 10.91% of the phenotypic variation. This study provides useful information for the breeding of resistant cultivars against white tip disease in rice.     

测序水稻品种SSR遗传连锁图谱的构建及其农艺性状基因座分析

利用测序水稻品种"Nipponbare（粳）/广陆矮4号（籼）"杂交F2群体90个单株为作图群体,构建含148个SSR标记的水稻遗传连锁图谱,覆盖基因组全长1737.81cM,标记间平均距11.90cM。利用该图谱及Excel2000和Mapmaker/QTL1.1b软件对分蘖数、穗数、穗长、主穗长、株高、剑叶长等六个农艺性状间的相互关系和基因位点进行分析,结果在LOD>2.2和P<0.005的条件下共检测到28个QTLs,它们分布在水稻所有染色体上,单个QTL对性状的分子贡献率11.1%-42.9%,其中大于20%有10个,并对选用已测序材料为亲本构建图谱来探讨水稻农艺性状的分子基础及其育种意义进行了讨论。     

两个水稻骨干恢复系重要农艺性状的遗传基础研究

水稻骨干恢复系是指在杂交稻育种中广泛应用的一类恢复系。探明骨干恢复系的遗传基础,发掘其重要农艺性状基因/QTL,对分子标记辅助选择水稻恢复系育种具有重要应用价值。本研究以生产上广泛应用的三系骨干恢复系成恢727和两系骨干恢复系9311为亲本,培育了具有250个系的重组自交系群体。分别在2015年三亚和2016年合肥两个环境下进行了9个重要农艺性状表型和SSR分子标记基因型鉴定,用SAS9.2分析表型数据,用QTL Ici Mapping v4.1进行QTL定位分析。在三亚和合肥两个环境下共检测到39个QTL,三亚检测到16个,分布于第1、2、4、7、8、10、11和12染色体上;合肥检测24个,分布于第1、2、3、7、8、9、10和12染色体上。其中qPH1-1在三亚和合肥两个环境下都能检测到,加性效应分别为-1.75和-2.46。在检测到的39个QTL中,有24个QTL的增效等位基因来自恢复系成恢727,15个QTL的增效等位基因来自9311。共计有26个QTL曾被前人定位,13个属于尚未见文献报道的新QTL。另外,在RM279~RM521、RM336~RM3534、RM25~RM547、RM553~RM160、RM222~RM271区段内检测到5个多效性QTL位点。其中RM25~RM547位点与已经克隆的基因Ghd8位置相近。RM553~RM160位点是一个新的多效性位点,分别控制每穗实粒数、单株产量和结实率,而且效应和表型变异贡献率都较大。其余3个位点在前人的研究中分别有所报道,但其多效性则是在本研究中首次发现。在本研究新发掘到的QTL中,控制穗数的QTL qPN12-1,控制穗长的QTL qPL1-2和qPL10-1,控制总粒数的QTL qSNP2-1和qSNP10-1,控制结实率的QTL qSF3-1,控制千粒重QTL qTGW7-1和控制产量的QTL qGY1-1效应均比较大,解释的表型遗传变异比例也较高。本研究的结果将会为相关性状QTL的精细定位、克隆和育种应用奠定基础。     

RFLP mapping of QTLs for yield and related characters in rice (Oryza sativa L.)

Quantitative triat loci (QTLs) for yield and related traits in rice were mapped based on RFLP maps from two indica/indica F₂ populations, Tesanai 2/CB and Waiyin 2/CB. In Tesanai 2/CB, 14 intervals carrying QTLs for eight traits were detected, including 3 for grain weight per plant (GWT), 2 for number of panicles per plant (NP), 2 for number of grains per panicle (NG), 1 for total number of spikelets per panicle (TNS), 1 for spikelet fertility (SF), 3 for 1000-grain weight (TGWT), 1 for spikelet density (SD), and 1 for number of first branches per main panicle. The 3 QTLs for GWT were located on chromosomes 1, 2, and 4, with 1 in each chromosome. The additive effect of the single locus ranged from 2.0 g to 9.1 g. A major gene (np4) for NP was detected on chromosome 4 within the interval of RG143–RG214, about 4cM for RG143, and this locus explained 26.1% of the observed phenotypic variance for NP. The paternal allele of this locus was responsible for reduced panicles per plant (3 panicles per plant). In another population, Waiyin 2/CB, 12 intervals containing QTLs for six of the above-mentioned traits were detected, including 3 for GWT, 2 for each of NP, TNS, TGWT and SD, 1 for SF. Three QTLs for GWT were located on chromosome 1, 4, and 5, respectively. The additive effect of the single locus for GWT ranged from 6.7 g to 8.8 g, while the dominance effect was 1.7–11.5 g. QTL mapping in two populations with a common male parent is compared and discussed.     

水稻品种USSR5早熟性的遗传分析

USSR5为极早熟的前苏联品种,以抽穗期近等基因系和抽穗期QTL近等基因系为测验品种,对USSR5的抽穗期基因型进行分析,表明USSR5携带了非感光基因e1、无感光功能的Se-1e基因、感光抑制基因i-Se-1和显性早熟基因Ef-1,从而使它表现极早熟的特性。此外,本研究调查了USSR5和N22的BC1F1和F2群体的抽穗期,利用WindowsQTLCartographer1.13a软件,采用复合区间作图法,在全基因组范围内,分析了南京夏季正常日照条件下2个群体的抽穗期QTL,在USSR5/N22//USSR5BC1F1群体,共检测到2个位点,分别位于第7、8染色体上,其LOD值分别是6.11和2.91,对表型总变异的解释率分别为27.38%和11.15%,2个位点上来自USSR5的等位基因均提早抽穗。在USSR5/N22F2群体,共检测到5个位点,分别位于第1、2、7、9、10染色体上。5个位点LOD值介于3.02～8.4,对表型总变异的解释率分别为4.07%和15.41%。除qHd-9外,其余控制抽穗期的4个基因位点上提早抽穗的等位基因均来源于USSR5。比较分析发现效应较大的qHd-7即是Hd4(E1),USSR5在该位点上携带非感光基因hd4(e1)。尽管本研究定位的其它抽穗期QTL和已知抽穗期基因之间尚不能一一对应,但在早熟性水稻品种选育中,USSR5将可作为良好的基因源加以利用。     

Identification of QTLs associated with physiological nitrogen use efficiency in rice

Demand for low-input sustainable crop cultivation is increasing to meet the need for environment-friendly agriculture. Consequently, developing genotypes with high nutrient use efficiency is one of the major objectives of crop breeding programs. This study was conducted to identify QTLs for traits associated with physiological nitrogen use efficiency (PNUE). A recombinant inbred population (DT-RILs) between Dasanbyeo (a tongil type rice, derived from an indica x japonica cross and similar to indica in its genetic make-up) and TR22183 (a Chinese japonica variety) consisting of 166 F8 lines was developed and used for mapping. A frame map of 1,409 cM containing 113 SSR and 103 STS markers with an average interval of 6.5 cM between adjacent marker loci was constructed using the DT-RILs. The RILs were cultivated in ordinary-N (N-P2O5-K2O = 100-80-80 kg/ha) and low-N (N-P2O5-K2O= 50-80-80 kg/ha) (100 kg/ha) conditions. PNUE was positively correlated with the harvest index and grain yield in both conditions. Twenty single QTLs (S-QTLs) and 58 pairs of epistatic loci (E-QTLs) were identified for the nitrogen concentration of grain, nitrogen concentration of straw, nitrogen content of shoot, harvest index, grain yield, straw yield and PNUE in both conditions. The phenotypic variance explained by these S-QTLs and E-QTLs ranged from 11.1 to 44.3% and from 16.0% to 63.6% , respectively. The total phenotypic variance explained by all the QTLs for each trait ranged from 35.8% to 71.3%, showing that the expression of PNUE and related characters depends significantly upon genetic factors. Both S-QTLs and E-QTLs may be useful for marker-assisted selection (MAS) to develop higher PNUE genotypes.     

Identification of Quantitative Trait Loci for Bacterial Blight Resistance Derived from Oryza meyeriana and Agronomic Traits in Recombinant Inbred Lines of Oryza sativa

Bacterial blight (BB) is one of the major diseases that affect rice productivity. In previous studies, BB resistance was transferred to cultivated rice Oryza sativa from wild rice Oryza meyeriana using asymmetric somatic hybridization. One of the resistant hybrid progenies (Y73) has also been shown to possess novel resistance gene(s) different from any of those previously associated with BB resistance. We have mapped quantitative trait loci (QTLs) for BB resistance in a recombinant inbred line (RIL) population derived from a cross between Y73 and a BB‐susceptible cv. IR24. Five QTLs were detected where Y73 alleles contributed to increased BB resistance. Three minor QTLs were identified on chromosomes 3, 10 and 11, and two major QTLs on chromosomes 1 and 5, respectively. QTL on chromosome 5, designated qBBR5, had the strongest effect on BB resistance, explaining approximately 37% of the phenotypic variance. Using the same RIL population, we also mapped QTLs for agronomic traits including plant height (PH), heading date (HD), plant yield (PYD) and PYD component traits. A total of 21 QTLs were identified, of which four were detected for PH, six for HD, three for panicle number per plant (PNPP), one for spikelets per panicle (SPP), six for 1000‐grain weight (TGW) and one for PYD. qPH1 (a QTL for PH) was found in the same interval as qBBR1 for BB resistance, and qHD11 for HD and qBBR11 for BB resistance also shared a similar interval. Additionally, BB resistance was significantly correlated with PH or HD in the RIL population. This suggests that the resistance genes may have pleiotropic effects on, or close linkage to, genes controlling PH or HD. These results will help deduce the resistance mechanisms of the novel resistance gene(s) and provide the basis for cloning them and using them in marker‐assisted breeding.     

Quantitative trait loci mapping of resistance to Laodelphax striatellus (Homoptera: Delphacidae) in rice using recombinant inbred lines

Laodelphax striatellus Fallén (Homoptera: Delphacidae), is a serious pest in rice, Oryza sativa L., production. A mapping population consisting of 81 recombinant inbred lines (RILs), derived from a cross between japonica' Kinmaze' and indica' DV85' rice, was used to detect quantitative trait loci (QTLs) for the resistance to L. striatellus. Seedbox screening test (SST), antixenosis test, and antibiosis test were used to evaluate the resistance response of the two parents and 81 RILs to L. striatellus at the seedling stage, and composite interval mapping was used for QTL analysis. When the resistance was measured by SST method, two QTLs conferring resistance to L. striatellus were mapped on chromosome 11, namely, Qsbph11a and Qsbph11b, with log of odds scores 2.51 and 4.38, respectively. The two QTLs explained 16.62 and 27.78% of the phenotypic variance in this population, respectively. In total, three QTLs controlling antixenosis against L. striatellus were detected on chromosomes 3, 4, and 11, respectively, accounting for 37.5% of the total phenotypic variance. Two QTLs expressing antibiosis to L. striatellus were mapped on chromosomes 3 and 11, respectively, explaining 25.9% of the total phenotypic variance. The identified QTL located between markers XNpb202 and C1172 on chromosome 11 was detected repeatedly by three different screening methods; therefore, it may be important to confer the resistance to L. striatellus. Once confirmed in other mapping populations, these QTLs should be useful in breeding for resistance to L. striatellus by marker-assisted selection of different resistance genes in rice varieties.