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。     

水稻顶部三叶与穗重的关系及其QTL分析

 摘要: 对水稻汕优63重组自交系群体顶部3张叶片的长、宽、重和单穗重等10个性状进行了相关分析和QTL定位。穗重与9个叶片性状存在极显著的正相关，其中与倒2叶重的相关系数最大，剑叶重次之。所有性状在重组自交系群体中均存在双向超亲分离，接近正态分布。共检测到44个主效QTL和43对双位点互作影响上述10个性状。主效QTL分布于水稻的除第8染色体外的其余11条染色体上，贡献率介于3.19%~26.23%；互作分布于水稻的12条染色体上，贡献率变幅为2.03%~8.93%。第2染色体的R2510-RM211标记区间同时检测到控制单穗重和倒2叶重的QTL，该QTL对超级稻株型育种具有应用价值。     

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.     

不同环境下稻米品质性状QTL的检测及稳定性分析

【目的】挖掘新的稻米品质性状QTL并利用分子育种技术改良稻米品质。【方法】利用构建的一套以籼稻香型恢复系昌恢121为背景亲本,以优质粳稻越光为供体亲本的染色体片段代换系（CSSLs）为材料,在4个环境下对稻米品质性状进行QTL检测及稳定性分析。【结果】在4个环境下共检测到44个QTL,其中6个QTL能在多个环境下被检测到;第2、3、5、6和10染色体上存在多效QTL簇,对稻米品质性状具有明显的调控作用;第1、6和12染色体上7个QTL能在不同环境下稳定表达。【结论】第1染色体RM3143-RM1117区间qPGWC1和第12染色体RM3331-RM5479区间qPaT12是两个新的稳定表达QTL。     

不同生态环境下水稻穗部性状QTL鉴定

【目的】发掘与产量相关的穗粒性状QTL对进一步克隆和利用高产基因具有重要意义。【方法】以超级粳稻龙稻5号和典型高产籼稻中优早8号杂交衍生的重组自交系群体为试材,在4种环境下对穗部性状进行比较和QTL分析。【结果】共检测到63个穗部性状QTL,分布于除第9染色体外的11条染色体上。在4个环境下分别检测到27、27、18和35个QTL。其中,16个QTL能在2个环境下被检测到,12个在3个以上环境下稳定表达,分别占QTL总数的25.40%和19.05%;第1、3、4和5染色体的多效QTL簇能在不同环境下稳定表达,对穗部性状具有明显的调控作用。【结论】第3染色体STS3.3-STS3.6区间的qSNP3、第4染色体RM5688-RM1359区间的qSNP4.1是2个新的稳定表达的多效性QTL簇。此外,上位性效应是调控穗部性状的重要组分。     

不同环境下稻米品质性状QTL的检测及稳定性分析

【目的】挖掘新的稻米品质性状QTL并利用分子育种技术改良稻米品质。【方法】利用构建的一套以籼稻香型恢复系昌恢121为背景亲本，以优质粳稻越光为供体亲本的染色体片段代换系（CSSLs）为材料，在4个环境下对稻米品质性状进行QTL检测及稳定性分析。【结果】在4个环境下共检测到44个QTL，其中6个QTL能在多个环境下被检测到；第2、3、5、6和10染色体上存在多效QTL簇，对稻米品质性状具有明显的调控作用；第1、6和12染色体上7个QTL能在不同环境下稳定表达。【结论】第1染色体RM3143−RM1117区间qPGWC1和第12染色体RM3331−RM5479区间qPaT12是两个新的稳定表达QTL。     

水稻灌浆期耐热害的数量性状基因位点分析

 利用由98个家系组成的Nipponbare / Kasalath // Nipponbare回交重组自交系群体及其分子连锁图谱，以粒重感热指数\[（适温粒重-高温粒重）/适温粒重×100\]为评价指标，采用混合线性模型的QTL定位方法，对水稻灌浆期耐热性的主效、上位性数量性状基因位点及其与环境的互作进行分析。共检测到3个灌浆期耐热性主效QTL，分别位于第1、4和7染色体上，LOD值为8.16、11.08和12.86，贡献率8.94%、17.25%和13.50%。其中位于第4染色体标记C1100-R1783之间的QTL，没有显著的上位性和环境互作效应，表明在不同环境和遗传背景中的表达较为稳定，在水稻耐热性育种中可能具有较大的利用价值，其耐热性等位基因来自亲本Kasalath，高温热害时可减少粒重损失3.31%。位于第1染色体标记R1613-C970之间的QTL和第7染色体标记C1226-R1440之间的QTL，耐热性等位基因来自亲本Nipponbare，分别可减少粒重损失2.38%和2.92%。这两个QTL均具有与环境的互作效应，其中第7染色体上的QTL还和其他基因位点有互作。检测到8对加性×加性上位性互作QTL，分布于第1、2、3、5、7、8、10和12染色体上。没有检测到上位性QTL与环境的互作效应。     

不同年份水稻产量性状的QTL分析

分别于2005年和2006年利用热研2号（粳稻）和密阳23（籼稻）为亲本构建的含111个家系的F6和F7重组自交系群体,对单株穗数、每穗颖花数、每穗实粒数、结实率、千粒重和单株产量6个性状进行了QTL分析。两年共检测到分布于7条染色体上的19个QTL,其中2005年检测到10个,2006年检测到14个,两年相同的QTL 5个。大多数性状之间具有显著的表型相关性,相关性较强的性状之间具有较多共同或紧密连锁的QTL。检测到3个控制产量性状的QTL区域存在一因多效或紧密连锁,其中第8染色体上RM5556-RM331区域两年同时检测到控制每穗颖花数、每穗实粒数以及单株产量的QTL。这些QTL为通过分子标记辅助选择提高水稻产量提供了有用信息。     

籼稻C84和粳稻春江16B重组自交系遗传图谱构建及籽粒性状QTL定位与验证

【目的】本研究旨在挖掘水稻粒型新基因、探索其分子机理,解析籽粒发育调控遗传网络奠定基础,并为通过分子标记聚合有利基因开展超级稻分子设计育种提供理论依据。【方法】以植株和籽粒形态差异较大的晚粳稻品种春江16B(CJ16B）和广亲和中籼稻背景恢复系C84为亲本构建含有188个家系的重组自交系为作图群体,利用158对在双亲中存在多态性差异的分子标记,构建了遗传连锁图谱,总遗传距离为1428.40cM,平均标记间距为9.04cM。在构建遗传图谱的基础上,完成RIL188个株系籽粒的粒长、粒宽、粒厚、长宽比和千粒重等5个性状考查并进行QTL定位。【结果】在海南陵水和浙江杭州两地共检测到籽粒相关主效QTL30个,包括籽粒QTL新座位18个,解释遗传变异3.51%~17.25%。其中粒长、粒宽、粒厚和长宽比QTL位点分别为9个、5个、5个和6个,千粒重QTL位点5个。经基因座位比对,发现有5个QTL区间与已克隆的调控籽粒形态相关基因座位相近,我们通过对双亲目标基因的测序并根据差异位点设计dCAPs分子标记进行验证。【结论】该RIL群体及其遗传图谱可用于水稻重要农艺性状主效QTL基因的定位和克隆,新定位的18个粒型QTL可以为水稻籽粒发育调控网络提供补充和资料积累。     

基于3种遗传统计模型对粳稻米质性状的QTL分析

 以粳粳交组合秀水79/C堡衍生的254个重组自交系为材料,利用基于混合线性模型的QTLMapper 2.0软件的复合区间作图法(MCIM)、基于逐步回归线性模型的QTL IciMapping 3.0软件的完备复合区间作图法(ICIM)和基于多元回归分析的Windows QTL Cartographer 2.5软件的多区间作图回归前进选择法(MIMR)等3种定位方法,对整精米的粒长、长宽比、垩白粒率、垩白度、直链淀粉含量、糊化温度和胶稠度等7个米质性状进行了QTL分析。结果表明,3种方法同时检测到的具有加性效应的QTL (A QTL)有5个,2种方法同时检测到的A QTL有2个,仅能在1种方法中检测到的A QTL有23个。MCIM、ICIM和MIMR检测到的A QTL个数分别为5、9和28,单个A QTL贡献率为0.89%~38.07%。MIMR检测到的具有上位性效应的QTL (E QTL)在另2种方法中都未被检测到。MCIM 和ICIM同时检测到的E QTL有14对,仅能在1种方法中检测到的E QTL有142对。MCIM、ICIM和MIMR检测到的E QTL对数分别为25、141和4,单对E QTL贡献率为2.60%~23.78%。在秀堡RIL群体中,粒长和垩白度的变异以上位性效应为主,长宽比则以加性效应为主,而垩白粒率、直链淀粉含量、糊化温度和胶稠度为加性效应和上位性效应同等重要。两种及以上方法同时检测到的QTL可靠性高,可用于改良杂交粳稻米质。     

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.     

Genetic relationship between grain yield and the contents of protein and fat in a recombinant inbred population of rice

To study the genetic relationship between grain yield and the nutrient contents in rice, 209 recombinant inbred lines derived from a cross between indica rice Xieqingzao B and Milyang 46 were used to determine quantitative trait loci (QTLs) affecting the yields and contents of the two major nutritional components in brown rice. Seven traits were analyzed, including brown rice recovery (BRR), protein content (PC), fat content (FC), grain yield (GYD), brown rice yield (BRYD), protein yield (PYD) and fat yield (FYD). The nutrient contents were significantly negatively correlated with BRR, GYD and BRYD, and the variations on nutrient yield were mainly ascribed to GYD. A total of 22 QTLs distributed on 10 regions of eight chromosomes were detected. Two QTL clusters were found on the short arm of chromosome 6 and the long arm of chromosome 10, respectively. The former was responsible for all the seven traits, and the latter for all the traits except BRR and FC. In both regions, the maternal alleles decreased nutrient contents, but they increased the yields of grain, brown rice, protein and fat. Implication of these results for the breeding of rice varieties with enhancing nutritional capacity is discussed.     

Mapping of qTGW1.1,a Quantitative Trait Locus for 1000-Grain Weight in Rice (Oryza sativa L.)

1000-grain weight(TGW) is one of the three component traits of the grain yield in rice(Oryza sativa L). This study was conducted to validate and fine-map qT GW1.1, a minor QTL for TGW which was previously located in a 3.7-Mb region on the long arm of rice chromosome 1. Five sets of near isogenic lines(NILs) were developed from two BC2F4 populations of the indica rice cross Zhenshan 973/Milyang 46.The NIL sets consisted of two homozygous genotypic groups differing in the regions RM11448-RM11522,RM11448- RM11549, RM1232- RM11615, RM11543-RM11554 and RM11569-RM11621, respectively. Four traits, including TGW, grain length, grain width and heading date, were measured. Phenotypic difference between the two genotypic groups in each NIL population was analyzed using SAS procedure GLM.Significant QTL effects were detected on TGW with the Zhenshan 97 allele increasing grain weight by0.12 g to 0.14 g and explaining 8.30% to 15.19% of the phenotypic variance. Significant effects were also observed for grain length and width, whereas no significant effect was found for heading date. Based on comparison among the five NILs on the segregating regions and the results of QTL analysis, qT GW1.1was delimited to a 376.9-kb region flanked by DNA markers Wn28382 and RM11554. Our results indicate that the effects of minor QTLs could be steadily detected in a highly isogenic background and suggest that such QTLs could be utilized in the breeding of high-yielding rice varieties.     

粳稻垩白性状的QTL检测

 利用大粒粳稻DL115与小粒粳稻XL005杂交获得的F2群体200个单株为作图群体,采用复合区间作图方法,利用SSR标记对稻米垩白性状进行了数量性状基因座(QTL)检测。研究结果表明,稻米垩白粒率、垩白大小和垩白度在F3株系均呈连续分布,表现为由多基因控制的数量性状。检测到与稻米垩白性状相关的QTL 8个,分别位于第3（5个）、第5（2个）和第6（1个）染色体上,包括与垩白粒率有关的QTL 3个,与垩白大小相关的QTL 2个,与垩白度有关的QTL 3个。其中位于第3染色体RM6832-RM411、RM15456-RM6832和RM6266-RM15456区间的qPGWC3、qACE3b和qDEC3b,分别解释垩白粒率、垩白大小和垩白度表型变异的43.89%、18.83%和19.57%,为主效QTL。上述3个主效QTL所在染色体上的位置与前人研究结果均不一致,认为是新的QTL。所检测到的8个QTL中,除qPGWC6的增效等位基因来自无垩白亲本XL005外,其他7个QTL的增效等位基因均来自垩白性状值较大的亲本DL115。垩白粒率和垩白大小基因作用表现为部分显性,垩白度基因作用表现为加性。     

特大粒水稻材料粒型性状的QTL检测

 利用特大粒粳稻TD70（2011年千粒重达80 g）和籼稻品种Kasalath杂交,经单粒传法获得的240个重组自交系（RIL）为作图群体,分别于2010年和2011年对粒长、粒宽、粒厚性状进行鉴定,用完备区间作图法,以均匀分布于12条染色体的141个SSR标记对粒型性状进行QTL检测。共检测到粒型性状的 QTL 18 个,分布于第2、3、5、7、9和12染色体上。其中,控制粒长的QTL 5个,控制粒宽的QTL 6个,控制粒厚的QTL 7个。两年间均能检测到的QTL有7个,分别为粒长QTL qGL3.1,粒宽QTL qGW2.1、qGW2.2、qGW5.1、qGW5.2,粒厚QTL qGT2.3、qGT3.1;其平均贡献率分别为56.19%、4.42%、29.41%、10.37%、7.61%、21.19%和17.06%。第2染色体RM1347-RM5699区间是粒长、粒宽、粒厚的共同标记区间。第3染色体RM6080-RM6832区间为粒长qGL3.1、粒厚qGT3.1共同标记区间。18 个QTL的增效等位基因均来源于大粒亲本TD70,且增效作用显著。定位的大部分位点包含已报道的精细定位和克隆的主要粒型基因;除第2染色体的qGW2.1（qGT2.1）、qGW2.3、qGL2.2和第12染色体的qGT12等位点已有粒型性状相关报道外,定位的qGT22,qGW9 和qGT9可能是新的QTL。     

水稻第6染色体短臂株高及产量性状QTL的分解

针对第6染色体短臂上一个对产量性状遗传具有重要作用的区间RM587-RM19715,从珍汕97B/密阳46重组自交系群体中筛选到1个剩余杂合体,自交衍生获得一个由195个个体组成的F2群体,检测控制株高和产量性状的QTL。经分析,在目标区间的上部和下部分别检测到1个QTL簇,分别对除单株穗数以外的产量性状因子具显著作用,单个QTL对群体性状表型变异的贡献率为5.0%~55.5%。将第6染色体上的产量性状QTL分解到更小的区间中,为产量性状QTL的精细定位和克隆打下了基础。     

利用染色体片段置换系群体定位和分析水稻粒重和粒型QTL

[目的]挖掘水稻粒重和粒型相关性状QTL,对于解析水稻籽粒遗传机理具有重要作用.[方法]本研究以籼稻9311为受体、粳稻日本晴为供体构建的染色体片段置换系(Chromosome Segment Substitution Lines,CSSLs)群体为材料,在4个环境下对控制稻谷与糙米的粒重和粒型QTL进行了定位分析.[...     

Genome-Wide Association Analysis and Allelic Mining of Grain Shape-Related Traits in Rice

Excavating single nucleotide polymorphisms(SNPs) significantly associated with rice grain shape and predicting candidate genes through genome-wide association study(GWAS) can provide a theoretical basis for discovery and utilization of excellent genetic resources in rice. Based on 16 352 SNPs, 161 natural indica rice varieties with various grain sizes in southern China were used for GWAS of grain shape-related traits, referring to grain length(GL), grain width(GW), 1000-grain weight(TGW), and grain length/width(GLW). Phenotypic statistics showed that coefficient of variation values for these four traits GL, GW, TGW and GLW were 9.92%, 9.09%, 20.20% and 16.38%, respectively. Each trait showed a normal distribution, and there was a certain correlation between these traits. Through general linear model correlation analysis, a total of 38 significant loci were identified, and a range of 100 kb upstream and downstream of the significant loci was identified as the candidate interval. On chromosome 3, GS3 and q GL3 were found to regulate GL. On chromosome 6, TGW6 and GW6 a were found to regulate TGW. Also, some QTLs related to grain shape were found on chromosomes 5 and 9. Besides that, using sequenced 3 K-germplasm resources, we found that there are 22 overlapped varieties between these two natural populations. Twenty-six SNPs and fourteen haplotypes were identified in five regions of GS3 genes. The detection of multiple candidate genes/QTLs within the candidate interval is beneficial for further excavation of superior rice genetic resources.     

多环境下粳稻产量及其相关性状的条件和非条件QTL定位

 为了剖析粳稻产量及其相关性状的遗传基础,利用粳稻品种秀水79×Ｃ堡衍生的重组自交系群体,在3个环境下对全生育期、株高、单株穗数、每穗粒数、百粒重、籽粒产量和生物产量进行了非条件和条件QTL定位。共检测到43个主效QTL和29对上位性QTL。利用非条件QTL定位方法检测到37个主效QTL和26对上位性QTL。其中,籽粒产量定位到3个主效QTL qGY1.2、qGY7.1和qGY9,未检测到上位性QTL。利用条件QTL方法分别将全生育期、株高、穗数、每穗粒数、百粒重和生物产量各自调整到同一水平后,籽粒产量共检测到9个主效条件QTL和3对上位性QTL,其中3个主效QTL与非条件下定位到的相同。位于第9染色体长臂区间RM6570-RM5652的qGY9在非条件及全生育期、株高、穗数、粒数和百粒重调整到同一水平后均可检测到,但加性效应、贡献率并不相同,显示该区间来自C堡的片段能够增加株高、穗数和百粒重从而增加产量。通过条件方法在第3染色体长臂区间RM7097-RM448及第6染色体长臂区间RM162-RM5753上定位到的产量QTL增加籽粒产量的等位基因可以降低株高,缩短生育期。     

Mapping quantitative trait loci (QTLs) for seedling-vigor using recombinant inbred lines of rice (Oryza sativa L.)

Seedling-vigor is important for optimum stand establishment and increasing weed competitive ability in rice cropping systems. In the current study, three seedling-vigor-related traits, seed germination rate, seedling shoot length and dry matter weight, were investigated by the paper-roll tests with rice recombinant inbred lines derived from a cross between Lemont (japonica) and Teqing (indica). The phenotype data, together with a linkage map consisting of 198 marker loci, was used to conduct composite interval mapping by QTLMapper 1.0 to simultaneously map both main-effect and epistatic QTLs for seedling-vigor in rice. Totally, 13 putative main-effect QTLs and 19 pairs of epistatic loci with R² ≥ 5% were identified. Almost all of these QTLs or interactions individually explained only around 5–10% of the phenotypic variation. The majority (68%) of these main-effect and epistatic loci were clustered in seven chromosome regions, each spanning 12–28 cM (centi-Morgan) and containing three or more detectable loci. When detectable for the multiple seedling-vigor-related traits, either the main-effect QTLs or the epistatic interactions sharing the same map location had their additive or epistatic effects in the same direction, which agreed well with the positive correlations among the traits. The results demonstrated that seedling-vigor in rice could be controlled by many loci, most of which had small effects, but, relatively, epistasis as a genetic factor was much more important than main-effects of QTLs. Along with the results reported previously, this study revealed the extensive genetic diversity for seedling-vigor in rice. In addition, the QTL q^SV-7 on chromosome 7 was found to have the largest main-effects on multiple seedling-vigor-related traits and therefore could be used as a potential target to be genetically manipulated by marker-assisted selection in rice seedling-vigor breeding programs.