Inheritance and QTL Mapping of Salt Tolerance in Rice

An F2 population derived from the cross between Jiucaiqing (japonica) and IR36 (indica) was used to analyze the inheritance of salt tolerance in rice by genetic model of major-genes plus polygenes, and to map the corresponding QTLs by SSR molecular markers. Rice plants of P1, P2, F1 and F2 at 5- to 6- leaf stage were treated under 140 mmol/L NaCI for 10 days. Three indices representing the ability of salt tolerance of rice seedlings were measured, including salt tolerance rating (STR), Na^ /K^ ratio in roots and dry matter weight of shoots (DWS). STR, Na^ /K^ and DWS were all controlled by two major genes with modification by polygenes. Heritability of these traits from major genes was 17.8, 53.3 and 52.3%, respectively. The linkage map constructed by 62 SSR molecular markers covered a total length of about 1 142 cM. There were three QTLs detected for STR located on chromosome 1, 5 and 9, two QTLs for DWS on chromosomes 8 and 9, and two QTLs for Na^ /K^ on chromosomes 2 and 6, one on each chromosome respectively. Single QTL accounted for 6.7 to 19.3% of phenotypic variation. Identification method of salt tolerance in rice and breeding of rice varieties with salt tolerance based on molecular markers assisted selection had been discussed.     

Quantitative Trait Loci and Epistatic Analysis of Seed Anoxia Germinability in Rice (Oryza sativa)

Anoxia germinability (AG) of 35 rice varieties was evaluated under different temperature and water submergence conditions. The shoot (including coleoptile) length of seedlings germinating under 30℃, 0.2 m water submergence for 5 days could be used as an optimal criterion for the AG evaluation of all the varieties. Differences were observed among the AGs of 359 varieties from different regions and subspecies with the optimized method. Moreover, 81 recombinant inbred lines derived from a cross of Kinmaze (japonica)/DV85 (indica) were used to detect quantitative trait loci (QTLs) conferring AG. A total of five QTLs for AG in the recombinant inbred population were detected on chromosomes 1, 2, 5 and 7, respectively. Phenotypic variations explained by each QTL ranged from 10.5% to 19.6%. Based on the directions of the additive effects, the alleles at three loci qAG-1, qAG-2 and qAG-7 from Kinmaze increased AG, while alleles at loci qAG-5a and qAG-5b from DV85 increased AG. Meanwhile, three pairs of epistatic loci were found to be located on chromosomes 2, 3, 5 and 11 with significant effects ranging from 16.7% to 48.8%, and the highest one 48.78%, was detected between C563–X182 on chromosome 3 and R830–X208 on chromosome 5.     

Quantitative Trait Locus Analysis for Rice Yield Traits under Two Nitrogen Levels

A recombinant inbred line population derived from a super hybrid rice Xieyou 9308(Xieqingzao B/Zhonghui 9308) and its genetic linkage map were used to detect quantitative trait loci(QTLs) for rice yield traits under the low and normal nitrogen(N) levels. A total of 52 QTLs for yield traits distributed in 27 regions on 9 chromosomes were detected, with each QTL explaining 4.93%–26.73% of the phenotypic variation. Eleven QTLs were simultaneously detected under the two levels, and 30 different QTLs were detected under the two N levels, thereby suggesting that the genetic bases controlling rice growth under the low and normal N levels were different. QTLs for number of panicles per plant, number of spikelets per panicle, number of filled grains per panicle, and grain density per panicle under the two N levels were detected in the RM135–RM168 interval on chromosome 3. QTLs for number of spikelets per panicle and number of filled grains per panicle under the two N levels, as well as number of panicles per plant and grain density per panicle, under the low N level, were detected in the RM5556–RM310 interval on chromosome 8. The above described QTLs shared similar regions with previously reported QTLs for rice N recycling.     

QTL Analysis for Seven Quality Traits of RIL Population in Japonica Rice Based on Three Genetic Statistical Models

QTL mapping for seven quality traits was conducted by using 254 recombinant inbred lines (RIL) derived from a japonica-japonica rice cross of Xiushui 79/C Bao. The seven traits investigated were grain length (GL), grain length to width ratio (LWR), chalk grain rate (CGR), chalkiness degree (CD), gelatinization temperature (GT), amylose content (AC) and gel consistency (GC) of head rice. Three mapping methods employed were composite interval mapping in QTLMapper 2.0 software based on mixed linear model (MCIM), inclusive composite interval mapping in QTL IciMapping 3.0 software based on stepwise regression linear model (ICIM) and multiple interval mapping with regression forward selection in Windows QTL Cartographer 2.5 based on multiple regression analysis (MIMR). Results showed that five QTLs with additive effect (A-QTLs) were detected by all the three methods simultaneously, two by two methods simultaneously, and 23 by only one method. Five A-QTLs were detected by MCIM, nine by ICIM and 28 by MIMR. The contribution rates of single A-QTL ranged from 0.89% to 38.07%. All the QTLs with epistatic effect (E-QTLs) detected by MIMR were not detected by the other two methods. Fourteen pairs of E-QTLs were detected by both MCIM and ICIM, and 142 pairs of E-QTLs were detected by only one method. Twenty-five pairs of E-QTLs were detected by MCIM, 141 pairs by ICIM and four pairs by MIMR. The contribution rates of single pair of E-QTL were from 2.60% to 23.78%. In the Xiu-Bao RIL population, epistatic effect played a major role in the variation of GL and CD, and additive effect was the dominant in the variation of LWR, while both epistatic effect and additive effect had equal importance in the variation of CGR, AC, GT and GC. QTLs detected by two or more methods simultaneously were highly reliable, and could be applied to improve the quality traits in japonica hybrid rice.     

Identification of QTLs for Cadmium Tolerance During Seedling Stage and Validation of qCDSL1 in Rice

Cadmium(Cd)is a non-essential toxic metal that is harmful to plants.To investigate the genetic mechanism of Cd tolerance in rice,quantitative trait loci(QTLs)associated with Cd tolerance at the seedling stage were analyzed using a recombinant inbred line(RIL)population derived from a cross between PA64s and 93-11.A total of 36 QTLs associated with shoot length,root length,shoot dry weight,root dry weight and total dry weight were detected in Hangzhou and Lingshui of China.Among them,15 QTLs were identified under the control condition and 15 QTLs were identified under the Cd stress condition,and 6 QTLs for Cd tolerant coefficient were detected on chromosomes 1,3,7 and 9.The qCDSL1.1 and qCDSL1.2 were identified in Hangzhou and Lingshui,respectively,and had overlapping intervals on chromosome 1.To further confirm the effects of qCDSL1.1 and qCDSL1.2,we developed a chromosome segment substitution line(CSSL),CSSLqCDSL1,in 93-11 background harboring qCDSL1.1/qCDSL1.2 from PA64s.Compared to 93-11,CSSLqCDSL1 had increased shoot length under the Cd stress condition.These results pave the way for further isolation of those genes controlling Cd tolerance in rice and marker-assistant selection of rice elite varieties with Cd tolerance.     

QTL Mapping for Grain Size Traits Based on Extra-Large Grain Rice Line TD70

Grain size traits, including grain length, grain width and grain thickness, are controlled by quantitative trait loci （QTLs）. Many QTLs relating to rice grain size traits had been reported, but their control mechanisms have not yet been elucidated. A recombinant inbred line （RIL） population of 240 lines, deriving from a cross between TD70, an extra-large grain size japonica line with 80 g of 1000-grain weight, and Kasalath, a small grain size indica variety, were constructed and used to map grain size QTLs to a linkage map by using 141 SSR markers in 2010 and 2011. Five QTLs for grain length, six for grain width and seven for grain thickness were detected distributing over chromosomes 2, 3, 5, 7, 9 and 12. Seven QTLs, namely qGL3.1, qGW2, qGW2.2, qGW5.1, qGW5.2, qGT2.3 and qGT3.1, were detected in either of the two years and explained for 56.19%, 4.42%, 29.41%, 10.37%, 7.61%, 21.19% and 17.06% of the observed phenotypic variances on average, respectively. The marker interval RM1347-RM5699 on chromosome 2 was found common for grain length, grain width and grain thickness; qGL3.1 and qGT3.1 were mapped to the same interval RM6080-RM6832 on chromosome 3. All 18 QTL alleles were derived from the large grain parent TD70. Most of the QTLs mapped in the present study were found the same as the genes previously cloned （GW2, GS3 or qGL3, GW5 and GS5）, and several were the same as the QTLs （GS7 and qGL-7） previously mapped. Three QTLs, qGL2.2 on chromosome 2, qGW9 and qGT9 on chromosome 9, were first detected. These results laid a foundation for further fine mapping or cloning of these QTLs.     

Mapping QTL for Heat-Tolerance at Grain Filling Stage in Rice

A mapping population of 98 lines (backcross inbred lines, BILs) derived from a backcross of Nipponbare/Kasalath// Nipponbare was planted at two experimental sites, Nanjing and Nanchang, and treated with high and optimal temperature during grain filling, respectively. The grain weight heat susceptibility index [GWHSI= (grain weight at optimum temperature-grain weight at high temperature) / grain weight at optimum temperature ×100] was employed to evaluate the tolerance of rice to heat stress. A genetic linkage map with 245 RFLP markers and a mixed linear-model approach was used to detect quantitative trait loci (QTLs) and their main effects, epistatic interactions and QTL×environment interactions (Q×E). The threshold of LOD score=2.0 was used to detect the significance of association between marker and trait. A total of 3 QTLs controlling heat tolerance during grain filling were detected, on chromosomes 1, 4 and 7, with LOD scores of 8.16, 11.08 and 12.86, respectively, and they explained the phenotypic variance of 8.94, 17.25 and 13.50 %, correspondingly. The QTL located in the C1100-R1783 region of chromosome 4 showed no QTL×environment interaction and epistatic effect, suggesting that it could be stably expressed in different environments and genetic backgrounds, and thus it would be valuable in rice breeding for heat tolerance improvement. This QTL allele, derived from Kasalath reduced 3.31% of the grain weight loss under heat stress. One located between R1613-C970 on chromosome 1 and the other between C1226-R1440 on chromosome 7, with additive effect 2.38 and 2.92%, respectively. The tolerance alleles of both these QTLs were derived from Nipponbare. Both of these QTLs had significant QTL×environment interactions, and the latter was involved in epistatic interaction also. Eight pairs of epistatic effect QTLs were detected, one pair each on chromosomes 1,2,3, 5, 7, 8, 10 and 12. The results could be useful for elucidating the genetic mechanism of heat-tolerance and the development of new rice varieties with heat tolerance during grain filling phase.     

QTLs Analysis of Cold Tolerance During Early Growth Period for Rice

The quantitative trait loci (QTLs) for cold tolerance during early growth period were identified using a F2:3 population (including 200 individuals and lines derived from a cross between indica rice and japonica rice ‘Milyang 23/Jileng 1’) with microsatellite markers. The cold tolerance at the seedling and tillering stages, and the growth ability of seedling under low temperature conditions were evaluated. All of the traits associated with cold tolerance at early growth stages appeared a continuous distribution near to normal in F3 lines, these were inherited as quantitative traits controlled by polygenes. Three QTLs on chromosomes 1, 5 and 9, which associated with cold tolerance at the seedling stage were detected. Among them, qCTS1 accounted for 15.5% of observed phenotypic variation; Five QTLs on chromosomes 2, 3, 7, 9 and 11, associated with cold tolerance at the tillering stage were found, which explained lower percentage of observed phenotypic variation; Four QTLs on chromosomes 1, 2, 11 and 12, which associated with the growth ability of seedling under low temperature conditions were found, among them, qGAS2 and qGAS12 explained 26.6 and 42.9% of observed phenotypic variation, respectively, which were major genes.     

Utilization of eui Gene from a Recessive Tall Rice Mutant 02428h in Breeding

In order to improve the panicle extrusion of photo-and thermo-sensitive sterile line'Pei'ai 64S'by using elongated uppermost internode(eui)gene of the wide compatibility rice mutant'02428h',a new photo-and thermo-sensitive sterile line'P8hS' characterized with elongated uppermost internode was developed by transferring the eui gene into Pei'ai 64S through three successive backcrossing.Compared with Pei'ai 64S,the plant height of P8hS was 35.6 cm higher resulted from the elongation of the uppermost and the second internodes from the top.The panicle extrusion of Pei'ai 64S was completely improved and positive effects were found on the main economic characters of P8hS and its hybrids by introducing eui gene into Pei'ai 64S.     

QTL Mapping for Rice RVA Properties Using High-Throughput Re-sequenced Chromosome Segment Substitution Lines

The rapid visco analyser （RVA） profile is an important factor for evaluation of the cooking and eating quality of rice. To improve rice quality, the identification of new quantitative trait loci （QTLs） for RVA profiling is of great significance. We used a japonica rice cultivar Nipponbare as the recipient and indica rice 9311 as the donor to develop a population containing 38 chromosome segment substitution lines （CSSLs） genotyped by a high-throughput re-sequencing strategy. In this study, the population and the parent lines, which contained similar apparent amylose contents, were used to map the QTLs of RVA properties including peak paste viscosity （PKV）, hot paste viscosity （HPV）, cool paste viscosity （CPV）, breakdown viscosity （BKV）, setback viscosity （SBV）, consistency viscosity （CSV）, peak time （PET） and pasting temperature （PAT）. QTL analysis was carried out using one-way analysis of variance and Dunnett＇s test, and stable QTLs were identified over two years and under two environments. We identified 10 stable QTLs： qPKV2-1, qSBV2-1; qPKV5-1, qHPV5-1, qCPV5-1; qPKV7-1, qHPV7-1, qCPV7-1, qSBV7-1; and qPKV8-1 on chromosomes 2, 5, 7 and 8, respectively, with contributions ranging from -95.6% to 47.1%. Besides, there was pleiotropy in the QTLs on chromosomes 2, 5 and 7.     

利用单片段代换系鉴定水稻株高及其构成因素的QTL

 通过t测验比较了单片段代换系与受体亲本华粳籼74之间的表型差异，对以6个水稻品种为供体的52个单片段代换系代换片段上株高及其构成因素的QTL进行了鉴定。以P≤0.001为阈值，在14个代换片段上共鉴定出24个QTL，包括10个株高QTL、2个穗长QTL、4个倒1节间长QTL、5个倒2节间长QTL、3个倒3节间长QTL，这些QTL分布于水稻的9条染色体上。QTL加性效应值为-4.08～3.98 cm，加性效应百分率为-19.35%～10.43%。     

小麦重组自交系群体9个重要农艺性状的遗传分析

为了初步判断小麦重要性状的遗传组成,并筛选适于QTL定位的性状,以小偃81和西农1376及其构建的重组自交系群体(RILs)F7代为材料,采用植物数量性状主基因+多基因混合遗传模型研究了株高、叶面积、穗下茎长、穗下节长、穗下节间直径、穗长、小穗数、穗粒数和抽穗期等9个重要农艺性状的遗传特点.结果表明,穗下节长性状符合多基因遗传,无主基因存在;株高、小穗数、穗粒数、叶面积、穗长和抽穗期6个性状符合2对主基因+多基因遗传;穗下节间直径性状符合3对主基因遗传,无多基因存在;穗下茎长性状则符合3对主基因+多基因遗传.株高、穗长、抽穗期和穗下节间直径等4个性状的主基因遗传率分别为82.32％、75.75％、81.98％和91.04％,可能含有较大的主效QTL.     

植物生长调节剂对再生稻头季抗倒伏能力和两季产量的影响

【目的】为了探明植物生长调节剂对再生稻头季抗倒伏能力及两季产量的影响,【方法】以佳辐占、天优华占和甬优2640为试验材料,于拔节初期叶面喷施多效唑、乙烯利和抗倒酯,研究不同植物生长调节剂对水稻头季茎秆特性、力学指标及两季产量形成的影响。【结果】甬优2640基部节间抗折力和植株抗推力最大,抗倒伏能力强;佳辐占基部节间最长,株高最高,倒伏指数高,抗倒伏能力最差;天优华占基部倒伏指数小,抗倒伏能力介于前二者中间。与喷施清水对照相比,多效唑处理植株节间长、株高、茎壁厚与对照差异较小,增加了倒3节间(N₃)茎粗和倒4节间(N₄)和N₃的抗折力,降低了N₄和N₃的倒伏指数;乙烯利处理则显著增加了N₄长度,N₃茎粗和株高,对茎壁厚没有明显影响, 增强了N₃抗折力,降低了N₃倒伏指数;抗倒酯处理缩短了N₄、倒2节间(N₂)长,降低株高,增加N₃茎粗和N₃、N₂的茎壁厚度,增强了N₄、N₃的抗折力,降低了各节间的倒伏指数。3种植物生长调节剂处理均降低了头季产量,多效唑和抗倒酯处理增加了再生季产量,乙烯利降低了再生季产量。分析产量构成因素,植物生长调节剂处理主要影响了总穗粒数,头季总穗粒数减少,再生季总穗粒数增加。天优华占和甬优2640两季总产量均较对照降低,佳辐占总产量多效唑和抗倒酯处理较对照增加,乙烯利处理较对照降低。【结论】抗倒酯处理增强了再生稻头季茎秆的抗倒伏能力,而对两季总产量无显著影响,对再生稻头季抗倒伏栽培具有现实意义。     

栽培稻与普通野生稻BC2F2群体产量相关性状的QTL分析

以广陆矮4号(Oryza sativa ssp. indica)为母本及轮回亲本,普通野生稻（Oryza rufipogon）为父本,分单株连续回交2次,构建BC2F2群体。首先用241对具有双亲多态性的SSR标记对BC2F1单株进行代换片段分析,在此基础上,根据BC2F1的表型选产量较优的单株自交获得BC2F2群体,用代换片段上具有双亲杂合型基因型的24对SSR标记进行QTL定位。在所选的BC2F1单株上,共检测到分布于7条染色体上的20个野生稻的代换片段,平均每条染色体上有2.86个;代换片段长度最小为0.55 cM,最大为33.00 cM,平均长度为12.36 cM,总覆盖长度为247.20 cM,覆盖率为16.21%。利用BC2F2群体对14个产量相关性状进行QTL定位,共检测到控制8个性状的20个QTL。对性状表型值起增效作用的有11个,占总检出数的55%。控制产量相关性状的QTL存在簇状分布现象,这与表型相关分析结果相符合。     

不同化控制剂对优质杂交稻泰优398抗倒伏特性的影响

设置5种化控制剂处理,研究了拔节期前喷施不同化控制剂对优质稻泰优398茎秆配置、抗倒伏特性及产量的影响。结果表明,5种化控制剂喷施后株高均显著降低但对产量没有显著影响,其中,4种制剂喷施后能够缩短基部倒4、倒5节间长度,喷施25%多效唑悬浮剂和5%烯效唑可湿性粉剂能显著增加植株推阻和倒3节抗折力,从而增强植株抗倒伏能力。在本试验条件下的5种化控制剂中,在拔节期前喷施25%多效唑悬浮剂和5%烯效唑可湿性粉剂对优质稻泰优398的抗倒伏能力提升效果较好。     

用培矮64S/日本晴F2群体对水稻6个农艺性状的QTL定位

 用水稻测序品种培矮64S和日本晴配组建立了由180个单株组成的F2群体，构建了含137个SSR标记的连锁遗传图谱，对水稻的分蘖数、有效分蘖数、分蘖率、株高、剑叶长和穗长等6个相关农艺性状进行了QTL定位分析。共检测到14个QTL，分布在第1、2、4、5、6、7染色体的11个区间。检测到1个控制株高的主效QTL(qPH1 2),位于第1染色体，其表型贡献率为24.0%；1个控制剑叶长的主效QTL(qFL4）,位于第4染色体，其表型贡献率为30.5%。对所定位QTL的价值、QTL在染色体上的区域分布等进行了探讨。     

稻米粒形和垩白度的QTL定位和上位性分析

 利用由181个家系组成的Lemont/特青籼粳交重组自交系群体,以及由161个RFLP、SSR标记和3个形态标记构建的全长为1916.5 cM、覆盖水稻基因组12 条染色体的连锁图,采用线性模型的复合区间作图方法（QTLMapper V10）,对粒长、粒宽、长宽比和垩白度等4个稻米品质性状的数量性状座位（QTL）进行了分析。在水稻的所有12 条染色体上共定位到7个加性主效QTL和19对上位性QTL,其中控制粒长、粒宽、长宽比的主效QTL各2个,控制垩白度的QTL 1个,分别解释12.8%、40.0%、26.0%和42.1%的表型变异;共检测到6对影响垩白度、6对影响粒长、7对影响长宽比的上位性QTL,分别解释52.2%、31.3%和38.2% 的表型变异。结果表明,上位性QTL和主效QTL一样在稻米粒形和垩白度的遗传中起着重要的作用。     

不同温光条件下水稻抽穗期QTL的定位与分析

以广陆矮4号为受体,日本晴为供体的85个染色体单片段代换系群体为试验材料,通过单因素方差分析和Dunnett多重比较,测验单片段代换系与广陆矮4号之间抽穗期的差异,对代换片段上抽穗期相关的QTL进行了定位。以P≤0.001为阈值,在南京和海南不同温光条件下共定位到40个抽穗期相关的QTL。其中,21个QTL在2个环境中均被检测到;15个QTL只在南京环境中被检测到;4个QTL只在海南环境中被检测到。南京环境中定位到的36个抽穗期相关QTL,其加性效应值变化范围为2.8d~15.7d,加性效应百分率变化范围为3.8%~21.1%;海南环境中定位到的25个抽穗期相关QTL,加性效应值变化范围为1.8d~12.1d,加性效应百分率变化范围为1.7%~11.3%。这些QTL的定位,为进一步精细定位并克隆相应主效QTL和优异品种特定环境下的生育期改良奠定了基础。     

利用染色体片段置换系群体检测水稻叶片形态QTL

 水稻叶片的形态改良是水稻株型育种和产量育种的重要目标之一。以9311/日本晴染色体片段置换系（CSSLs）群体为材料,定位了上3叶叶片长、宽、叶面积共9个性状QTL,分析了叶片性状与产量性状之间的相关性,同时定位了主穗重及产量构成因素（颖花数、千粒重、结实率）相关QTL。结果表明,CSSLs群体的叶片性状之间存在显著或极显著相关性;叶片性状与主穗重呈显著或极显著正相关,与主穗颖花数呈极显著正相关;叶片形态多数性状与结实率、千粒重没有显著相关性。两年共定位到20个叶片性状QTL,分布于第1、3、4、5、6、9、11共7条染色体的10个区间,贡献率为3.82%~14.61%,其中贡献率大于10%有6个,多个QTL成簇分布在相同区间,3个QTL在两年间重复检测到,8个QTL为前人未报道的新位点。两年共检测到16个与控制主穗产量相关的QTL,分布于第1、2、3、5、7、8、10共7条染色体13个区间,其中有7个主穗产量相关QTL所在5个区间与叶片形态14个QTL所在区间一致。     

利用永久F_2群体定位小麦穗部性状相关的QTL

为发掘与小麦穗部性状相关的QTL,利用普通小麦BS366与白玉149杂交组合培育的73个DH群体为材料,构建了一套包含232个杂交组合的小麦永久F_2群体,基于90K SNP芯片标记构建了高密度遗传图谱,并利用该图谱对2个环境下的穗长、小穗数、穗粒数和千粒重进行QTL定位。结果发现,所构建的图谱总长19 533 cM,含有8 726个SNP标记,平均标记距离为2.24cM。结合群体基因分型结果,8 726个SNP标记合并为3 078个BIN标记,其中A基因组有1 283个(41.7%),B基因组有1 188个(38.6%),D基因组仅有607个(19.7%);共检测到96个QTL,分布在除3B和6B以外的19条染色体上,其中,控制穗长、小穗数、穗粒数和千粒重的QTL分别有20、59、6和11个,单一QTL可解释0.15%～12.34%的表型变异。51个QTL加性效应为正值,表明其加性效应来自于母本BS366;45个QTL加性效应为负值,表明其加性效应来自于父本白玉149。23个QTL的表型变异解释率大于5%,为主效QTL。