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。     

玉米子粒容重的遗传分析

采用包括基因型×环境互作效应的种子性状遗传模型,对玉米子粒容重的遗传进行了研究.结果表明:玉米子粒容重遗传表达主要受胚乳基因效应(VAe+VDe)、胚基因效应(VAo+VDo)所控制,其中三倍体胚乳基因效应占重要地位.基因型×环境互作表现为胚显性×环境(VDoE)、胚乳加性×环境(VAeE)和胚乳显性×环境(VDeE)互作.在普通遗传率中,以胚乳遗传率h2Ge为主,其余为零.在互作遗传率中,以胚乳互作遗传率h2GeE为主。     

小麦抽穗期QTL及其与环境的互作

为筛选稳定表达的小麦抽穗期QTL用于辅助选择,以旱选10号×鲁麦14的DH群体为试材,在四种环境下对抽穗期进行QTL。结果表明,该DH群体抽穗期呈连续性分布,表现为多基因控制的数量性状。四种环境下共检测到6个抽穗期加性QTLs,分别位于1B、1D、4D、6B、7B、7D染色体上,LOD值为3.13~10.88,贡献率在1.57%~6.72%之间,其中QHd-1D-1和QHd-7B与环境具有互作效应。共检测到10对上位性QTL位点,互作效应值为-0.39~0.423,表型贡献率在1.39%~4.86%之间,其中4对上位性位点与环境具有互作效应。     

小麦单株穗数的遗传分析及基于QTL定位的最优基因型预测

为给小麦育种提供参考,以种植于陕西杨凌、岐山、乾县三地的中国春(母本)×兰考大粒(父本)F2∶3家系为材料,对小麦单株穗数进行数量性状主基因+多基因混合模型遗传分析和QTL定位,并对最优株系基因型及遗传效应进行预测。结果表明:(1)单株穗数符合数量性状遗传特征,由一对加性和部分显性主基因(A-1模型)控制。(2)联合分析三个环境下的单株穗数得到9个控制单株穗数的QTL位点,其中QPn4B-2为主效位点,具有增穗的加性效应,与遗传分析结果相吻合,同时还得到自身无主效应但存在较强上位效应的5个位点;单独分析得到具有QTL与环境互作效应的7个位点,可见上位效应及环境互作效应对小麦单株穗数遗传有较大的影响。(3)在排除基因与环境互作效应以及分别考虑三地基因与环境互作效应4种情况下,单株穗数最优基因型预测效应值较中国春(P1)分别增加了1.45、1.45、1.9337和1.45,其中岐山地区预测效应值最高,达3.954 2,由此可推知此杂交组合后代在提高单株穗数这一性状上存在较大潜力;岐山地区最优株系QTL基因型在QPn2A、QPn6B位点上与杨凌和乾县两地不同,可见不同环境所对应的最优株系基因型存在差异。预测了普通最优株系的最佳基因型组合,同时讨论了在育种中获得最优株系的途径。     

大豆百粒重QTL的上位效应和基因型×环境互作效应分析

本研究中基于Charleston×东农594重组自交系群体,采用完备区间作图和混合线性模型对2006-2010年连续5年的百粒重QTL进行定位,并进行基因×环境互作及上位性分析。本研究定位了16个与大豆百粒重性状相关的QTL,其中有5个QTL分别与环境发生互作,互作贡献率在0.11%~0.52%之间;定位了8对上位互作位点,贡献率在1.15%~2.59%之间。     

大豆百粒重QTL的上位效应和基因型×环境互作效应

基于Charleston×东农594重组自交系群体,采用完备区间作图和混合线性模型对2006-2010年连续5年的百粒重QTL进行定位,并进行基因×环境互作及上位性分析。结果定位了16个与大豆百粒重性状相关的QTL,其中有5个QTL分别与环境发生互作,互作贡献率在0.11%～0.52%之间;定位了8对上位互作位点,贡献率在1.15%～2.59%之间。     

玉米穗位高遗传效应及其与环境互作效应分析

采用基因型×环境互作效应的加性-显性-母体遗传模型(ADM模型)分析方法,研究玉米穗位高性状遗传主效应及其与环境互作遗传效应。结果表明：玉米穗位高主要受显性效应控制,其次是受加性效应控制,同时还受显性×环境互作效应、母体×环境互作效应不同遗传控制体系基因型×环境互作效应显著影响。对穗位高性状的选择效果受环境影响较大,宜在较晚世代进行选择。育种中根据亲本穗位高在不同环境中遗传效应预测值组配杂交组合,提高玉米穗位高性状的选择效率。     

水稻重要农艺性状的两年QTL剖析

 利用水稻汕优63（珍汕97 × 明恢63）重组自交系群体241个株系，对株高、生育期、产量及其产量构成因子等9个重要农艺性状进行了年度间的QTL定位和比较。结果表明，9个性状的表现型在两年均为连续分布，且都存在一定数量的双向超亲遗传类型。两年共检测到64个QTL，分布于水稻除第4染色体外的其余11条染色体，其中1999年检测到45个，2000年检测到35个，两年相同的QTL共16个。2000年检测到的QTL贡献率介于283%~1499%，且大多低于1999年。不同环境可以影响QTL的表达，但表达差异并不全是QTL×环境(QE)互作结果，也可能是由于该性状的遗传力偏低、QTL本身效应偏低或QE互作等原因共同造成的。另外，检测到8个显著的QE互作，但其互作效应明显低于对应的QTL效应。     

4个环境下稳定表达的控制粳稻穗角性状的新位点

 在4个环境下种植直立穗粳稻品种秀水79与弯曲穗品种C堡及两者杂交后衍生得到的RIL群体254个株系并调查其穗角,运用主基因+多基因混合遗传模型对穗角性状进行遗传分离分析;运用基于混合线性模型的QTLNetwork 2.0软件和基于多元回归模型的WinQTLcart 2.5软件的复合区间作图法,对穗角性状进行QTL定位。结果发现,1）穗角性状受两对主基因+多基因共同控制,以主基因遗传为主;2）QTLNetwork 2.0检测到8个控制穗角性状的加性QTL,解释表型变异的0.01%~39.89%;WinQTLcart 2.5检测到12个控制穗角性状的加性QTL,可解释表型变异的2.83%~30.60%。检测到的所有QTL分布于第4、5、6、7、9、11染色体上,其中分布于RM3700-RM3600和RM5652-RM410区间的两个主效位点qPA9.2和qPA9.5,以及分布于RM257-OSR28区间的qPA9.7 在两种方法和4个环境下均检测到,减效等位基因来自秀水79;3）检测到8对加性×加性上位性互作位点,解释表型变异的0.36%~1.71%。检测到的各个加性和上位性位点均不存在显著的基因型与环境的互作。      

粳稻8个异交相关性状及其中亲优势的QTL定位与遗传分析

 为探明控制粳稻异交相关性状及其中亲优势的基因作用类型,利用秀堡RIL群体及其2个回交(BCF1)群体对穗抽出度、剑叶长、剑叶角度、穗剑高度差、倒2叶长、倒2叶角度、穗与倒2叶（穗二）高度差和倒1节间长8个异交相关性状及其中亲优势进行QTL定位。3个群体中共检测到45个显著的主效QTL（M QTL）,单个M QTL的贡献率变幅为1.5%～803%。73.3%的M QTL表现为加性效应,4.5%的M QTL表现为部分或完全显性效应,22.2%的M QTL表现为超显性效应。3个群体中共检测到82对显著的双基因上位性QTL（E QTL）。RIL群体中检测到43对E QTL,单对E QTL的贡献率变幅为1.0%～7.0%,平均2.7%。在以秀水79为父本、与秀堡RIL群体回交的后代（XSBCF1群体）中检测到16对E QTL,其中利用BCF1表型值检测到11对E QTL,单对E QTL的贡献率变幅为11.2%～36.8%,平均21.0%;利用中亲优势值检测到6对E QTL,单对E QTL的贡献率变幅为33.1%～76.8%,平均55.0%。在以C堡为父本、与秀堡RIL群体回交的后代（CBBCF1群体）中检测到23对E QTL,其中利用BCF1表型值检测到16对E QTL,单对E QTL的贡献率变幅为6.2%～60.0%,平均24.0%;利用中亲优势值检测到7对E QTL,单对E QTL的贡献率变幅为21.3%～44.4%,平均31.0%。上述结果表明,粳稻异交相关性状是由多位点控制的,基因对性状本身的作用类型以加性效应为主;粳稻异交相关性状中亲优势主要遗传基础为超显性效应和上位性效应。     

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.     

稻米出饭特性QTL分析及遗传研究

 米粒长、饭粒长和饭粒延伸系数等性状与米饭品质密切相关。以籼稻台中本地1号（TN1）与粳稻春江06为亲本构建的加倍单倍体群体为材料,利用全基因饱和分子标记连锁遗传图谱对多个稻米出饭特性相关的性状进行QTL定位, 共检测到14个QTL。其中,米粒长和米粒浸长QTL各1个,均位于第2染色体上,分别可以解释性状变异的15.20% 和1850%;1个米粒浸泡膨胀率QTL,位于第6染色体上,可解释性状变异的1339%;1个煮饭粒长QTL,位于第9染色体上,可解释性状变异的1360%; 3个蒸饭粒长QTL,分别位于第1、3和12染色体上,共解释性状变异4500%;4个煮饭延伸率QTL, 分别位于第3、6、9和10染色体上,共解释性状变异6130%; 3个蒸饭延伸率QTL分别位于第1、3和6染色体上,共解释性状变异4910%。在已知的Wx和ALK基因所在区域都检测到了米饭延伸性相关的QTL。相比较而言,覆盖ALK基因的QTL对出饭特性的影响更大,LOD值达到了635。该研究结果可为稻米出饭特性相关调控基因的克隆奠定基础,同时对稻米品质的改良及高产优质稻品种的分子标记辅助选育提供理论参考。     

Construction of SSR Linkage Map and Analysis of QTLs for Rolled Leaf in Japonica Rice

Genetic analysis of rolled leaf is important to rice ideotype breeding. To detect loci controlling rolled leaf of japonica restorer lines, SSR marker genotypes and phenotypes of flag leaf rolling index (LRI) were investigated in Xiushui 79 (P1, a japonica rice variety), C Bao (P2, a japonica restorer line) and 254 recombinant inbred lines derived from the cross between P1 and P2 , and in two environments. A genetic map of this cross was constructed, QTLs for LRI were detected and their interactions with environments were analyzed. Among 818 pairs of SSR primers, 90 primers showed polymorphism between P1 and P2, and 12 markers showed highly significant correlation with LRI in both environments based on single marker regression analysis. The genetic map containing 74 information loci has a total distance of 744.6 cM, with an average of 10.1 cM between two adjacent loci. Three QTLs (qRL-1, qRL-7 and qRL-8-1) were detected with two softwares: WinQTLCart 2.5 and QTLNetwork2.0. qRL-8-1 was a new locus, accounting for 15.5% and 12.8% of phenotypic variations in the two environments, respectively. The phenotypic variation explained by additive effect was 6.6%. No interaction was found between qRL-8-1 genotype and environments.     

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.[...     

New Stably Expressed Loci Responsible for Panicle Angle Trait in Japonica Rice in Four Environments

Panicle angle (PA) of 254 recombinant inbred lines derived from a cross between two japonica varieties Xiushui 79 and C Bao was investigated under four environments,and a genetic linkage map including 111 SSR markers was constructed.Genetic analysis was conducted by mixed major gene plus polygene inheritance models,and quantitative trait loci (QTLs) identification by the QTLNetwork 2.0 and the composite interval mapping approach of WinQTLCart 2.5 software.Results showed that the PA trait was controlled by two major genes plus polygenes,mainly by major genes.Eight QTLs for PA were detected by the QTLNetwork 2.0 software,and each locus explained 0.01% to 39.89% of the phenotypic variation.Twelve QTLs for PA were detected by the WinQTLCart 2.5 software,with each locus explaining 2.83% to 30.60% of the phenotypic variation.Two major QTLs (qPA9.2 and qPA9.5) distributed between RM3700 and RM3600 and between RM5652 and RM410,respectively,and a moderate QTL (qPA9.7) distributed between RM257 and OSR28,were both detected by the two methods in all of the four environments.The negative effect alleles of the three QTLs were from Xiushui 79.In addition,eight pairs of epistatic QTLs with minor effects were also detected.QTL × environment interactions were not significant for additive QTLs and epistatic QTL pairs.     

粳稻SSR连锁图谱的构建及恢复系卷叶性状QTL分析

  调查了粳稻品种秀水79 (P1)与粳稻恢复系C堡 (P2)及其衍生的254个重组自交系的SSR标记基因型和两个环境下主茎剑叶卷曲度,构建了该组合的SSR标记连锁图谱并分析了剑叶卷曲度QTL及其与环境的互作。在检测的818对SSR引物中,有90对引物在P1与P2之间扩增出多态性条带。单标记回归分析显示有12个标记在两个环境下均显示与剑叶卷曲度呈极显著相关。74个信息位点构成的连锁图谱全长744.6 cM,位点间平均图距10.1 cM。利用两种分析软件 WinQTLcart 2.5和QTLNetwork 2.0共同检测到3个QTL (qRL 1、qRL 7和qRL 8 1),其中qRL 8 1是新发现的,在两个环境下贡献率分别为15.5%和12.8%,加性贡献率为6.6%,且与环境不存在互作。     

利用贝叶斯法进行水稻籽粒植酸含量性状的QTL定位及互作分析

 利用水稻植酸含量差异较大的品种中花11(粳型)和LPA（籼型）为亲本杂交获得F2群体的172个单株,构建了含126个SSR和4个STS标记的遗传连锁图谱,利用贝叶斯（Bayesian）法对水稻籽粒植酸含量性状进行了主效应QTL定位和上位性互作分析。共检测到 3 个与水稻籽粒植酸含量性状有关的主效QTL,分布在第3、5和6 染色体的相应区间内,表型贡献率分别为538%、802%和462%,降低籽粒植酸含量的等位基因均来自亲本LPA。检测到10对上位性互作影响籽粒植酸含量, 分布于水稻第1、3、5、6、11染色体上,互作效应值为169～518,其表型变异的解释率为867%～2473%。     

盐胁迫下水稻苗期Na+含量的QTL定位

利用来自籼稻品种H359和Acc 8558的一个重组自交系群体（131个株系）及相应的遗传图谱（包含147个RFLP和79个SSR标记）,以150 mmol/L的NaCl处理后的幼苗地上部Na+含量为指标,采用复合区间定位方法,对水稻耐盐性QTL进行了定位。共检测到13个QTL,分别位于第1、2、5、6、7和12染色体上,对表型变异的总贡献率达到60.88%,其中,qSC1b的效应最大,可解释约45%的表型变异。通过比较表明,许多前人报道的与水稻盐胁迫有关的QTL/基因与本研究检测到的QTL的位置相同或相近。     

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.