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1.
To evaluate the possible genetic interrelationships between flour components and the sedimentation volume（SD）,a doubled haploid（DH） population comprising 168 lines were used to identify the conditional quantitative trait loci（QTLs） for SD in three environments.Ten additive QTLs and 15 pairs of epistatic QTLs were detected for SD through unconditional and conditional QTL mapping.Three major additive QTLs were detected for SD conditioned on the seven quality traits.Two additive QTLs were found to be independent of these traits.Three additive QTLs were suppressed by three of the seven traits because of non-detection in unconditional mapping.Three pairs of epistatic QTLs were completely affected by the seven traits because of detection in unconditional mapping but no-detection in conditional mapping.Twelve pairs of epistatic QTLs were detected in conditional mapping.Our results indicated that conditional mapping could contribute to a better understanding of the interdependence of different and closely correlated traits at the QTL molecular level,especially some minor QTLs were found.The conditional mapping approach provides new insights that will make it possible to avoid the disadvantages of different traits by breeding through molecular design.  相似文献   

2.
This study was undertaken to dissect quantitative trait loci （QTLs） controlling yield traits on the short arm of rice chromosome 6. A residual heterozygous line that carries a heterozygous segment extending from RM587 to RM19784 on the short arm of rice chromosome 6 was selected from an F7 population of the indica rice cross Zhenshan 97B/Milyang 46. An F2：3 population consisting of 221 lines was derived and grown in two trial sites. Six yield traits including number of panicles per plant, number of filled grains per panicle, total number of spikelets per panicle, spikelet fertility, 1 000-grain weight, and grain yield per plant were measured. An SSR marker linkage map was constructed and employed to determine QTLs for yield traits with Windows QTL Cartographer 2.5. QTLs were detected in the target interval for all the traits analyzed except NP, with phenotypic variance explained by a single QTL ranging between 6.3% and 35.2%. Most of the QTLs for yield components acted as additive QTLs, while the three QTLs for grain yield had dominance degrees of 1.65, 0.84, and -0.42, respectively. It was indicated that three or more QTLs for yield traits were located in the target region. The genetic action mode, the direction of the QTL effect, and the magnitude of the QTL effect varied among different QTLs for a given trait, and among QTLs for different traits that were located in the same interval.  相似文献   

3.
Heading date of rice is a key agronomic trait determining cultivated areas and seasons and affecting yield. In the present study, ifve primary single segment substitution lines with the same genetic background were used to detect quantitative trait loci （QTLs） for heading date in rice. Two QTLs, qHD3 and qHD6 on the short arm of chromosome 3 and the short arm of chromosome 6, respectively, were identiifed under natural long-day （NLD）. Nineteen secondary single segment substitution lines （SSSLs） and seven double segments pyramiding lines were designed to map the two QTLs and to evaluate their epistatic interaction between them. By overlapping mapping, qHD3 was mapped in a 791-kb interval between SSR markers RM3894 and RM569 and qHD6 in a 1 125-kb interval between RM587 and RM225. Results revealed the existence of epistatic interaction between qHD3 and qHD6 under natural long-day （NLD）. It was also found that qHD3 and qHD6 had signiifcant effects on plant height and yield traits, indicating that both of the QTLs have pleiotropic effects.  相似文献   

4.
Plant height(PH) is one of the most important agronomic traits of rice, as it directly affects the lodging resistance and the high yield potent ial. Meanwhile, PH is often constrained by water supply over the entire growth period. In this study, a recombinant inbred line(RIL) derived from Xiaobaijingzi and Kongyu 131 strains grown under drought stress and with normal irrigation over 2 yr(2013 and 2014), respectively(regarded as four environments), was used to dissect the genetic basis of PH by developmental dynamics QTL analysis combined with QTL×environment interactions. QTLs with net effects excluding the accumulated effects were detected to explore the relationship between gene×gene interactions and gene×environment interactions in specific growth period. A total of 26 addi tive QTLs(A-QTLs) and 37 epistatic QTLs(E-QTLs) associated with PH were detected by un conditional and conditional mapping over seven growth periods. q PH-2-3, q PH-4-3, q PH-6-1, q PH-7-1, and q PH-12-5 could be detected by both unconditional and conditional analyses. q PH-4-3 and q PH-7-5 were detected in four stages(periods) to be sequentially expressed QTLs controlling PH continuous variation. QTLs with additive effects(A-QTLs) were mostly expressed in the period S3|S2(the time interval from stages 2 to 3), and QTL×environment interactions performed actively in the first three stages(periods) which could be an important developmental period for rice to undergo external morphogenesis during drought stress. Several QTLs showed high adaptability for drought stress and many QTLs were closely related to the environments such as q PH-3-5, q PH-2-2 and q PH-6-1. 72.5% of the QTLs with a and aa effects detected by conditional analysis were under drought stress, and the PVE of QTLs detected by conditional analysis under drought stress were also much higher than that under normal irrigation. We infer that environments would influence the detection results an d sequential expressio n of genes was highly influenced by environments as well. Many QTLs(q PH-1-2, q PH-3-5, q PH-4-1, q PH-2-3) coincident with previously identified drought resistance genes. The result of this study is helpful to elucidating the gene tic mechanis m and regulatory network underlying the devel opment of PH in rice and providing references to marker assisted selection.  相似文献   

5.
Dissecting the genetic relationships among gluten-related traits is important for high quality wheat breeding. Quantitative trait loci(QTLs) analysis for gluten strength,as measured by sedimentation volume(SV) and gluten index(GI),was performed using the QTLNetwork 2.0 software. Recombinant inbred lines(RILs) derived from the winter wheat varieties Shannong 01-35×Gaocheng 9411 were used for the study. A total of seven additive QTLs for gluten strength were identified using an unconditional analysis. QGi1 D-13 and QSv1 D-14 were detected through unconditional and conditional QTLs mapping,which explained 9.15–45.08% of the phenotypic variation. QTLs only identified under conditional QTL mapping were located in three marker intervals:WPT-3743–GLU-D1(1 D),WPT-7001–WMC258(1 B),and WPT-8682–WPT-5562(1 B). Six pairs of epistatic QTLs distributed nine chromosomes were identified. Of these,two main effect QTLs(QGi1 D-13 and QSv1 D-14) and 12 pairs of epistatic QTLs were involved in interactions with the environment. The results indicated that chromosomes 1 B and 1 D are important for the improvement of gluten strength in common wheat. The combination of conditional and unconditional QTLs mapping could be useful for a better understanding of the interdependence of different traits at the QTL molecular level.  相似文献   

6.
Single segment substitution lines （SSSLs） each with a single chromosome segment from a donor under the same genetic background as the recipient were developed in rice by advanced backcrossing and molecular marker-assisted selection. Using the SSSLs, the QTLs for the important agronomic traits in rice would be detected under different environmental conditions. Detection of the QTLs controlling 22 important traits in rice was done with 32 SSSLs by the randomized block design in 2-4 cropping seasons. 59 QTLs were detected and distributed on chromosomes 1, 2, 3, 4, 6, 7, 8, 10, and 11, of which 18 QTLs were detected more than twice. Only 30.5% of the QTLs were detected repeatedly in different cropping seasons. Most of the QTLs of important agronomic traits were of little additive effects and instability. The QTLs controlling the traits, such as grain weight, grain length, ratio of grain length to width, and heading date were relatively stable. The stable QTLs usually had larger additive effects and were less affected by environment. The QTLs for the important agronomic traits were detected using the SSSLs in rice with high resolution under different environmental conditions. The instability of the QTLs may be the basis of the variation of rice plants during growth and development. It would be the genetic basis for improving yield and quality in rice cultivars by farming methods.  相似文献   

7.
The objectives of this study were to investigate the genetic factors controlling the chlorophyll content of rice leaf using QTL analysis. A linkage map consisting of 207 DNA markers was constructed by using 247 recombinant inbred lines (RILs) derived from an indica-indica rice cross of Zhenshan97B×Milyang 46. In 2002 and 2003, the contents of chlorophyll a and b of the parents and the 247 RILs were measured on the top first leaf, top second leaf, and top third leaf, respectively. The software QTLMapper 1.6 was used to detect quantitative trait loci (QTLs), additive by environment (AE) interactions, and epistatic by environment (AAE) interactions. A total of eight QTLs in four intervals were detected to have significant additive effects on chlorophyll a and b contents at different leaf positions, with 1.96-9.77% of phenotypic variation explained by a single QTL, and two QTLs with significant AE interactions were detected. Epistasis analysis detected nine significant additive-by-additive interactions on chlorophyll a and b contents, and one pair of QTLs with significant AAE interactions was detected. On comparison with QTLs for yield traits detected in the same population, it was found in many cases that the QTLs for chlorophyll a and b contents and those for yield traits were located in the same chromosome intervals.  相似文献   

8.
A rice residual heterozygous line （RHL） carrying a heterozygous segment extending from RM111 to RM19784 on the short arm of rice chromosome 6 was selected from a RHL-derived population used previously. The resultant F2：3 population was used to detect quantitative trait loci （QTLs） for three yield traits, the number of spikelets per panicle （NSP）, the number of grains per panicle （NGP） and grain yield per plant （GY）. Two QTLs for NSP, one QTL for NGP and one QTL for GY were detected, all of which were partially dominant and had the enhancing alleles from the maternal line Zhenshan 97B. Analysis based on the genotypic groups of the markers closely linked to the two QTLs for NSP indicated that they did not interact with each other. Two F2 populations and two near isogenic line （NIL） sets segregating in two sub-regions of interval RM111-RM19784 were developed. The two QTLs for NSP were validated, of which one had major effect and was co-segregated with heading date gene Hdl, and the other had smaller effect and was located in an upper region linked to Hdl. The two regions also showed significant effects on the number of filled grain and grain yield, although the effect on the number of filled grain was less consistent.  相似文献   

9.
Flowering time and branching type are important agronomic traits related to the adaptability and yield of soybean. Molecular bases for major flowering time or maturity loci, E1 to E4, have been identified. However, more flowering time genes in cultivars with different genetic backgrounds are needed to be mapped and cloned for a better understanding of flowering time regulation in soybean. In this study, we developed a population of Japanese cultivar(Toyomusume)×Chinese cultivar(Suinong 10) to map novel quantitative trait locus(QTL) for flowering time and branch number. A genetic linkage map of a F_2 population was constructed using 1 306 polymorphic single nucleotide polymorphism(SNP) markers using Illumina Soy SNP8 ki Select Bead Chip containing 7 189(SNPs). Two major QTLs at E1 and E9, and two minor QTLs at a novel locus, qFT2_1 and at E3 region were mapped. Using other sets of F_2 populations and their derived progenies, the existence of a novel QTL of qFT2_1 was verified. qBR6_1, the major QTL for branch number was mapped to the proximate to the E1 gene, inferring that E1 gene or neighboring genetic factor is significantly contributing to the branch number.  相似文献   

10.
Understanding the genetic mechanism underlying folate biosynthesis and accumulation in rice would be beneficial for breeding high folate content varieties as a cost-effective approach to addressing widespread folate deficiency in developing countries. In this study, the inheritance of rice grain folate content was investigated in the Lemont/Teqing recombinant inbred lines and the Koshihikari/Kasalath//Koshihikari backcross inbred lines. 264 F12 recombinant inbred lines（RILs） and 182 BC1F10 backcross inbred lines（BILs） with their parents planted in randomized complete blocks with two replicates in 2010, and RILs harvested in 2008 were used for QTL detection using inclusive composite interval mapping（ICIM） method. In the RIL population, two QTLs, denoted by qQTF-3-1 and qQTF-3-2（QTF, quantitative total folate）, explaining 7.8% and 11.1-15.8% of the folate content variation were detected in one or two years, respectively. In the BIL population, a QTL, denoted by qQTF-3-3, was detected, explaining 25.3% of the variation in folate content. All the positive alleles for higher folate content were from the high-folate parents, i.e., Teqing and Kasalath. The known putative folate biosynthesis genes do not underlie the QTLs detected in this study and therefore may be novel loci affecting folate content in milled rice. QTLs identified in this study have potential value for marker assisted breeding for high-folate rice variety.  相似文献   

11.
【目的】了解各个发育时期控制水稻分蘖数QTL的“静态”和“动态”信息。【方法】利用单片段代换系对不同时期的水稻分蘖数QTL同时进行非条件和条件定位分析。【结果】（1）水稻分蘖数至少受14个QTL影响,它们分布在第1、2、3、4、6、7和8号共7条染色体的相应代换片段上;（2）各个时期影响水稻分蘖数的QTL数量（变动在6～9之间）和效应（变动在1.49～3.49之间）均不相同;（3）水稻分蘖数QTL的表达具有很强的时序性,主要集中在移栽后0～7 d（有6个正表达）,14～21 d（有9个随机表达）和35～42 d（有6个负表达）3个时间段内,正、负表达分别决定了最高分蘖和有效分蘖的数量;（4）每个QTL在整个生育期至少表达1次,有些可多次表达;（5）某个时期的分蘖数量取决于所有QTL的累积效应,而某个时间段内分蘖数的增减量则取决于所有QTL的净效应。【结论】用单片段代换系和条件QTL定位方法对发育性状进行QTL定位分析非常有效和准确。  相似文献   

12.
 【目的】阐明影响小麦籽粒淀粉基因/QTL的时空表达和动态变化情况,为运用条件QTL更好地揭示小麦籽粒淀粉动态积累的基因表达提供参考。【方法】本研究以小麦品种花培3号和豫麦57构建的168个双单倍体（doubled haploid, DH）群体为材料,在6个不同的环境下种植,分别在花后12 d、17 d、22 d、27 d和32 d取样,对小麦籽粒淀粉含量（GSC）积累的条件和非条件QTL进行分析。【结果】在籽粒灌浆的5个时期,一共检测到7个非条件QTL和4个条件QTL,没有一个条件QTL能在测定的5个时期都有效应。7个非条件QTL分别分布在2A、3A、3B、4A、5D染色体上,其中QGsc4A在整个灌浆过程都能表达,5个时期的表型变异贡献率分别为13.57%、16.57%、21.96%、22.53%、22.90%。4个条件QTL中,QGsc4A在花后12 d、17 d、32 d均能检测到,总贡献率为21.80%,对籽粒淀粉积累的净增长量起主要作用。其它非条件QTL和条件QTL只在一个或几个阶段出现且效应值较小,花后27 d没有检测到条件QTL。【结论】控制GSC积累的数量性状基因以一定的时空方式表达,小麦籽粒淀粉积累的QTL动态分析,可以了解小麦籽粒淀粉积累的遗传规律及其对小麦籽粒发育的影响,为小麦产量和品质形成的分子基础的深入研究提供参考。  相似文献   

13.
小麦籽粒蛋白质含量的动态QTL定位   总被引：2，自引：1，他引：1  
 【目的】检测灌浆过程中控制小麦籽粒蛋白质含量（GPC）的条件及非条件QTL,阐明不同时期及不同时段内QTL的表达方式,揭示籽粒蛋白质积累的分子遗传机理。【方法】以花培3号×豫麦57的168个双单倍体（doubled haploid,DH）群体为材料,于6个不同的环境下种植,在籽粒灌浆的5个时期取样,对小麦GPC进行动态QTL分析。【结果】共检测到影响GPC的9个非条件QTL和10个条件QTL。QGpc3A为整个灌浆过程都能表达的非条件QTL,其余条件和非条件QTL只在几个或单独一个时期表达。花后12 d,控制GPC的基因表达活跃,非条件QTL和条件QTL总共能解释表型变异贡献率的42.62%;花后22 d,条件QTL和非条件QTL总共可解释表型变异的贡献率较低,仅为17.43%,GPC降到“低谷”。 QGpc4A-1对GPC前期积累有重要意义,QGpc1D和QGpc4A-2对GPC灌浆中后期积累有重要意义。【结论】GPC呈现出“高-低-高”的变化规律,控制GPC的基因在灌浆过程中以一定的时空方式表达。  相似文献   

14.
水稻(Oryza sativa L.)分蘖数和株高的遗传分析   总被引：6，自引：0，他引：6       下载免费PDF全文
水稻分蘖数和株高是两个重要的农艺性状.为剖解它们的遗传结构,本研究用一套来源于籼粳组合IR64×Azucena的DH群体对这两个性状进行了QTL定位分析.表型数据来源于两个生长季节,采用基于混合线性模型的方法分析.结果表明,分蘖数主要由普通遗传因素和互作遗传因素控制(呈现61.7%的普通遗传率和17.2%的互作遗传率),共有19个QTLs与分蘖数有关,其中9个和6对QTLs分别具有单位点的遗传效应和2位点的互作效应,QTL1-8和QTL 1-12的上位性效应由于在春季的贡献率达21.6%,因而认为是一对主效.株高主要由普通遗传因素控制,普通遗传率为92.6%,共受到15个QTLs的影响,其中8个QTLs具有加性效应,1个QTL具有加性与环境的互作效应,4对上位性QTLs具有加性与加性互作效应.QTL 1-15被认为是主效QTL,而其余的是微效QTLs.两个性状表型之间存在显著的负向部分相关,然而,性状相关的遗传基础仍需做进一步的探讨.  相似文献   

15.
小麦株高发育动态QTL定位   总被引：8，自引：2，他引：6  
【目的】检测小麦生长发育过程中控制株高的条件QTL和非条件QTL,揭示株高发育的分子遗传机理,获得更多调控株高的遗传信息。【方法】以两个主栽小麦品种花培3号和豫麦57的F1获得的含有168个株系的DH(双单倍体)群体为材料,自拔节至开花期,每隔7d取样测定株高(分蘖节至穗顶端)。根据3个环境下株高的表型数据和含有323个位点的分子遗传图谱,采用条件复合区间作图法进行小麦株高的发育动态QTL分析。【结果】共检测到18个非条件QTL和10个条件QTL。在18个非条件QTL中,Qph5D-1在前4个取样期(3月9日—4月23日)均能检测到,Qph4D-1在后3个取样期均能检测到,分别是挑旗前、后阶段影响株高的主效QTL,其它非条件QTL在少数几个取样期发现或效应很小。10个条件QTL中,Qph5D-1在两个阶段均能检测到,总贡献率为30.1%。Qph4B在5月1日—5月8日检测到,贡献率为20.3%,对后期株高的净增长量起主要作用。其它条件QTL只在一个阶段出现或效应较小。【结论】影响株高的QTL数目及其QTL表达效应在株高形成的过程中有很大的变化,说明控制株高生长的数量性状基因以一定的时空方式表达。在小麦育种中,本研究结果可为株高的分子标记辅助选择提供理论依据。  相似文献   

16.
水稻穗干物质重发育动态的QTL定位   总被引：18，自引：1，他引：17  
 以籼稻品种IR64和粳稻品种Azucena及其DH群体(123个DH系)为遗传研究材料,在穗干物质积累的不同时期测定穗重。利用包括RFLP、同工酶标记和RAPD等175个分子标记的水稻连锁图谱,采用条件复合区间作图法对水稻穗部干物质积累进行QTL的动态定位。在各时期能检测到14个非条件QTL,而最终穗重只能检测到3个非条件QTL。条件QTL分析表明,基因在水稻发育过程中以一定的时空方式表达。亲本和极端个体的QTL总效应分析表明,增效基因和减效基因在不同个体中的累积程度不同。控制穗干物质积累的发育过程存在两组基因,一组基因控制稻穗谷粒内外颖的发育,另一组基因可能控制谷粒内容物的充实。  相似文献   

17.
【背景】粮食安全是保障国家安全的重要基础,水稻是人民赖以生存的主要粮食作物,提高其产量是重要的育种目标。水稻产量由每株有效穗数、每穗实粒数和粒重等性状构成,其中,粒重与籽粒形状、充实程度等密切相关。但这些性状都是由多基因控制,遗传基础复杂。染色体片段代换系(CSSL)可将这些复杂性状的QTL较准确地分解为单个孟得尔因子研究,且与育种工作紧密衔接,因而是理想的遗传研究和育种材料。【目的】前期以4代换片段的水稻染色体片段代换系Z481精细定位了一个易落粒基因SH6,但Z481与受体日本晴间还存在多个显著差异的穗部性状。明晰控制这些差异性状的QTL在代换片段上如何分布,并分解为单片段代换系,对目标QTL的图位克隆及应用于水稻分子设计育种有重要应用价值。【方法】利用受体亲本日本晴与Z481杂交构建的次级F2分离群体以SAS9.3统计软件的混合线性模型(mixed linear model,MLM)法进行穗部性状QTL定位(P<0.05),然后,根据基因型和表型,从F2选择42个单株在F3株系利用MAS法培育单片段及双片段代...  相似文献   

18.
利用单片段代换系定位水稻抽穗期QTL   总被引：22，自引：4，他引：22  
 抽穗期是水稻品种的重要农艺性状之一，对抽穗期QTL进行定位并研究其遗传效应在水稻育种中是至关重要的。本研究利用以6个水稻品种为供体的52个单片段代换系为试验材料，通过t测验比较单片段代换系与受体亲本华粳籼74之间抽穗期的差异，对代换片段上的抽穗期QTL进行了鉴定。以P≤0.001为阈值共鉴定出20个抽穗期QTL，这些QTL分布于水稻的10条染色体。QTL加性效应值为-5.9～1.1，加性效应百分率为-7.4%～1.4%。有8个QTL被定位在小于10.0 cM的区段内。利用1个单片段代换系与华粳籼74杂交发展的F2群体对qHD-3-1进行了定位。在作图群体中，早抽穗和迟抽穗植株数符合3:1的分离比，早抽穗表现为显性。利用微卫星标记将qHD-3-1定位于3号染色体短臂，PSM304和RM569分别位于其两侧，遗传距离分别为2.4 cM和5.1 cM。  相似文献   

19.
本研究以元江普通野生稻与优良栽培稻亲本特青配制的野生稻染色体片段代换系为材料,在幼苗生长阶段,利用室内、室外株高、干重抑制率的表型数据检测与耐铝相关的QTL,分别检测到11、18、14和5个与耐铝相关的QTL,分布于不同的染色体上,室内、室外株高抑制率的表型数据检测结果表明,位于第8染色体RM38附近和第12染色体RM277附近贡献率较大,分别为12%和11%,分析是主效QTL。室内、室外干重抑制率的表型数据检测到的最大QTL的贡献率分别只有9%和8%,未检测到主效QTL。重复检测到的QTL分布于第7、8、9、11和12染色体上。第8染色体上有2个QTL,其中RM310附近的QTL被三次重复检测到,其余的被检测到二次,分析这些QTL是稳定的QTL。  相似文献   

20.
油菜开花期QTL定位及与粒重的遗传关联性   总被引：2，自引：1，他引：1  
【目的】明确中国和欧洲油菜开花期主控位点及其对粒重的影响,为早熟油菜品种选育提供科学依据。【方法】以欧洲冬油菜Sollux和中国品种高油605的选系(Gaoyou)杂交F1经小孢子培养产生的DH群体为材料,采用7年9种环境下的开花期表型数据和新版SG图谱定位开花期QTL,并采用条件遗传学和QTL分析相结合的条件QTL定位方法,解析开花期对千粒重QTL的影响,最后对各20个极端开花期株系的基因型和表现型进行性状-标记的符合度测定,为标记筛选用于辅助选育提供依据。【结果】应用WinQTLCart 2.5复合区间作图法,共检测到7个在3种以上环境中稳定表达的控制开花QTL,加性效应值在0.58—3.85 d,解释了表型总变异的84%。8对上位性QTL效应总和为加性总效应的41.8%。QTL与环境互作效应只在少数位点和个别环境中显著。在3个主效QTL峰值或相近位置上定位了4个在拟南芥中调控开花的关键基因FT、API、FLC和FY的6个同源拷贝,为发掘控制这些QTL的候选基因提供了有价值的参考信息。条件QTL分析表明,在4个增重效应均来自Gaoyou的千粒重QTL位点(qSWA2、qSWA3、qSWA4和qSWC2),大粒等位基因效应可能与开花早、籽粒灌浆期长有关。通过选择这些位点的早开花标记基因型有望同时提高种子千粒重,这也部分给出了开花期与千粒重之间极显著负相关的遗传解释,但2个粒重主效位点(qSWA7和qSWC8)的遗传效应不受开花期影响。根据SG群体极端开花期株系在3个效应值最大的QTL(qFTA2、qFTC2和qFTC6)区域标记基因型和开花期表现型的关联分析,筛选获得6个高质量、高吻合度的共显性标记推荐育种应用。qFTA2位点,标记辅助准确率为70%-80%;qFTC2和qFTC6位点的选择效率达到80%-100%。基因型组配分析显示,聚合qFTA2、qFTC2和qFTC6的早开花等位基因,可显著提早开花期,同步增加千粒重但不影响含油量和角果粒数。【结论】7个QTL均显示早开花等位基因来自中国亲本。拟南芥中调控开花关键基因FT、API、FLC和FY的6个同源拷贝定位到3个主效QTL峰值位置。开花迟、早显著影响4个千粒重QTL位点,但2个最重要的粒重位点(qSWA7和qSWC8)不受影响;3个主效QTL(qFTA2、qFTC2和qFTC6)的6个共显性标记可用于早熟基因的转育和早熟材料的筛选。  相似文献   

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