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超级杂交稻协优9308重组自交系籽粒充实相关性状遗传分析与基因定位
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摘要
灌浆充实是水稻的一个重要特性,直接影响产量的高低。目前对灌浆速率等灌浆特性的研究主要集中在生理生化上,由于该性状测定繁琐,利用遗传群体在基因水平上的研究甚少。为探索水稻灌浆过程中的相关基因表达,以期获得在多环境下稳定表达的相关性状QTL,本研究利用超级稻协优9308重组自交系群体为研究材料,结合构建的遗传连锁图谱,多环境条件下对强势籽粒和弱势籽粒的灌浆速率、籽粒动态发育以及灌浆持续期、充实度、穗总粒数、穗实粒数、有效穗、结实率、Q酶活性、粒长、粒宽、粒厚、籽粒体积、籽粒长宽比、百粒重等相关性状进行了QTL定位分析,主要研究结果如下:
     1.采用winQTLCart2.5软件对强势籽粒在4个环境下(贵阳2010、贵阳2011、富阳2010、富阳2011)与弱势籽粒在两个环境下(富阳2010、富阳2011)的最大灌浆速率和平均灌浆速率进行QTL定位分析,共检测到13个主效应QTLs,分布于第1、2、3、4、5、6、8染色体上。其中,检测到强势籽粒最大灌浆速率5个QTLs,平均灌浆速率6个QTLs,单个QTL可解释其表型贡献率的5.12%-9.56%,这些QTLs能在两个环境中稳定检测到的有:qSGFRmax-4、qSGFRmax-8、qSGFRmean-4、qSGFRmean-8;检测到弱势籽粒最大灌浆速率4个QTLs,平均灌浆速率3个QTLs。单个QTL可解释其表型贡献率的7.46%-14.28%。
     2.对4个环境下强势籽粒灌浆的5个时期灌浆速率(花后第6d、12d、18d、24d、30d)和平均灌浆速率(1-6d、7-12d、13-18d、19-24d、25-30d)进行QTL定位分析,共检测到21个主效应QTLs,分布在第1、2、3、4、6、7、8、9、11染色体上,单个QTL可解释的各自性状表型贡献率介于5.05%-18.09%。其中,检测到5个时期灌浆速率14个主效应QTLs,平均灌浆速率13个主效应QTLs,二者共同QTLs有6个,上述QTLs中,qSGFR-3-1在3个环境下的多个时期稳定检测到,表型贡献率介于7.16%-18.09%,最大LOD值为5.64,增效等位基因来自高值亲本协青早B。2个环境条件下检测到影响弱势籽粒5个灌浆时期的灌浆速率和平均灌浆速率主效应QTLs分别为14个和11个,其中共同QTLs有7个,这些QTLs中,位于第6染色体上RM136-RM6302区间的qIGFR-6-1能在两组试验的同一时期检测到,同时在富阳2011的4个时期检测到,表型贡献率介于6.91%-14.69%。在第3染色体上RM282-RM6283区间和RM7370-RM16区间、第6染色体上RM136-RM6302区间和RM3724-RM3330区间、第7染色体上RM5436-RM3670区间均检测到控制强、弱势籽粒灌浆速率QTL。
     3.采用条件分析方法结合复合区间作图法,对籽粒发育动态进行QTL定位。4个环境下检测到强势籽粒5个灌浆时期籽粒重的非条件与条件QTLs共21个,分布在第1、2、3、4、6、7、8、9染色体上,单个QTL可解释各自性状的表型贡献率介于5.25%-18.86%,其中非条件QTLs为16个,条件QTLs11个,非条件与对应的条件QTLs有6个。2个环境下检测到弱势籽粒5个灌浆时期粒重的非条件与条件QTLs共16个,分布在第1、2、3、5、6、7、8和第10染色体上,单个QTL可解释各自性状的表型变异介于5.73%-18.05%,其中非条件QTLs为12个,条件QTLs为10个,非条件与对应的条件QTLs有6个。位于第6染色体上RM136-RM6302区间的qIWG-6-1在弱势粒灌浆4个时期都能检测到并存在对应的条件QTL,说明该QTL对弱势粒灌浆起着重要的作用。检测到位于第3染色体上RM282-RM6283区间和RM7370-RM16区间、第6染色体上RM136-RM6302区间和第7染色体上RM5436-RM3670区间存在控制强、弱势籽粒灌浆速率和阶段粒重QTL,这与灌浆速率同粒重高度正相关吻合,今后可将这4个SSR标记区间作为深入研究籽粒灌浆特性的重点区域。
     4.4个环境下检测到控制籽粒充实度A(GPA)、充实度B (GPB)、充实度C (GPC)、灌浆持续期(GPD)、穗实粒数(NFGP)、穗总粒数(GNPP)、结实率(SF)、有效穗(PP)和百粒重(100-GW)(3个环境)等9个性状主效应QTLs共59个,分布于第1、2、3、5、6、7、8、9、10、11染色体上,单个QTL对各自性状表型变异的贡献率为4.69%-23.74%。其中,充实度A检测到2个QTLs,充实度B检测到5个QTLs,充实度C检测到5个QTLs,检测到灌浆持续期、穗实粒数、穗总粒数、结实率、有效穗和百粒重的主效应QTLs分别为6、12、11、6、8和4个。上述QTLs中,能在2个以上环境检测到有:qGPC-1、qGFD-6-1、qGFD-7-1、qGFD-7-2、qNFGP-6-1、qGNPP-2、qGNPP-3-1、qGNPP-7-2、qPP-2、qPP-3-1、qWG-3-1、qWG-6-2。
     5.对富阳试验点2010年的2个灌浆时期(花后第10d、15d)和2011年的3个灌浆时期(花后第10d、15d、20d)的籽粒Q酶活性进行QTL定位,共检测到9个影响Q酶活性的主效应QTLs,分布在第2、3、5、6、7染色体上,单个QTL可解释其表型变异介于5.68%-11.59%。其中影响花后第10d籽粒Q酶活性的QTL为7个,花后第15d籽粒Q酶活性的QTL为2个,花后第20d籽粒Q酶活性的QTL为1个。影响花后第10d籽粒Q酶活性的qQ10-3与花后第15d籽粒Q酶活性的qQ15-3-2同处于第3染色体RM282-RM6283区间,该区间同时检测到控制灌浆速率的QTL,揭示了Q酶活性与灌浆速率呈正相关的内在联系。
     6.在3个环境下(富阳2010、富阳2011、贵阳2011)共检测到控制籽粒长、粒宽、粒厚、籽粒体积和籽粒长宽比5个性状的26个主效应QTLs。其中,粒长共检测到4个QTLs,分布于第3、7、10、11染色体上,单个QTL可解释的表型贡献率在3.98%-54.58%之间,位于第3染色体RM6283-RM7370区间的qGl3-1在3个环境下均被检测到;粒宽检测到4个QTLs,位于第3和第6染色体上,单个QTL可解释6.98%-9.77%的表型变异,位于第3染色体RM7370-RM16区间的qGw3-2在3个环境均能检测到;粒厚检测到8个QTLs,分布于第1、2、3、6、8、11、12染色体上,单个QTL可解释表型变异的4.91%-11.92%, qGt3-1在2011年贵阳和2010年富阳环境下被检测到;籽粒体积共检测到5个QTLs,位于第3、4、6、7、11染色体上,单个QTL可解释表型变异的5.07%-22.35%,位于第3染色体RM6283-RM7370标记区间的qGv3-1能在3个环境都被检测到,表达稳定;检测到籽粒长宽比QTL5个,分布于第3、10、11染色体上,单个QTL可解释表型变异的5.17%-47.81%,位于第3染色体SSR标记RM6283-RM7370区间qGlwr3-1在3个环境均被检测到,贡献率都超过30%。第3染色体上RM6283-RM7370区间均检测到控制粒长、粒厚、籽粒体积和籽粒长宽比的QTL,且表型贡献率较大。
     7.应用基于MCIM的分析方法,采用QTLNetwork2.0软件对多环境下籽粒灌浆速率等相关性状表型值进行联合检测,共检测到8个性状(强势粒最大灌浆率、强势粒阶段粒重、弱势粒阶段粒重、弱势粒阶段灌浆速率、灌浆持续期、粒宽、粒厚和粒长宽比)的24对加性×加性上位互作效应的QTL,贡献率介于0.26%-4.16%;检测到的主效应QTLs与环境互作效应远小于自身的加性效应。
     8.本研究发现多个重要的QTL聚集区,可同时影响籽粒灌浆速率、籽粒重、粒形、Q酶活性等性状,阐释了灌浆速率与产量相关性状的密切相关关系。例如在第3染色体上RM282-RM16区间检测到强弱势籽粒的最大灌浆速率、平均灌浆速率、阶段灌浆速率、阶段籽粒重以及粒形、Q酶活性等QTLs,第6染色体上RM136-RM6302区间检测到强弱势籽粒的阶段灌浆速率和阶段籽粒重、Q酶活性、籽粒充实度和穗实粒数等QTLs,第7染色体上RM5436-RM3670区间检测到强弱势籽粒的阶段灌浆速率和阶段籽粒重、Q酶活性、穗实粒数、穗总粒数和有效穗等QTLs。
Grain filling, as an important feature in rice, directly affects the production. At present, the studiesof grain filling characters such as grain filling rate mainly focused on physiology and biochemistry.However, because the measurement of this trait is complicated, the research using genetic population atthe level of genes is very little. In order to explore the related gene expression during rice grain fillingand obtain stable QTLs with expression in multiple environments, recombinant inbred lines (RIL)population derived from Xieyou9308, which was combined with the molecular genetic linkage map,was used as materials to identify and analyze the QTLs for grain filling rate of superior and inferiorgrains, developmental behaviour of grains, grain filling duration, grain plumpness, grain number perpanicle, number of filled grain per panicle, productive panicles, spikelet fertility, Q enzyme activity,grain length, grain width, grain thickness, grain volume, grain length to width ratio and100-grainweight under different conditions. The main results were as follows:
     1. The QTLs for the maximum and average grain filling rate of superior grains across fourenvironments (Guiyang2010,2011; Fuyang2010,2011) and inferior grains across two environments(Fuyang2010,2011) were determined using winQTLCart2.5, and13major QTLs were detected onchromosomes1,2,3,4,5,6, and8. A total of5and6QTLs for the maximum and average grain fillingrate of superior grains were detected respectively, and the detected QTL individually accounted for5.12%-9.56%of the phenotypic variation. Among the QTLs, qSGFRmax-4, qSGFRmax-8,qSGFRmean-4and qSGFRmean-8could be detected under two environments. In addition, a total of4and3QTLs for the maximum and average grain filling rate of inferior grains were detected respectively,and the detected QTL individually accounted for7.46%-14.28%.
     2. Grain filling rate of superior grains at five stages (6d,12d,18d,24d, and30d after anthesis) andaverage grain filling rate of superior grains (1-6d,7-12d,13-18d,19-24d and25-30d) across fourenvironments were used for QTL analysis. A total of21major QTLs were detected on chromosomes1,2,3,4,5,6,7,8,9and11. The detected QTL individually accounted for5.05%-18.09%of thephenotypic variation. Among the QTLs,14and13QTLs for grain filling rate at five stages and averagegrain filling rate at five stages were detected respectively, and6common QTLs were found. qSGFR-3-1could be detected at multiple stages under three environments, and phenotypic variance explained byindividual QTL ranged from7.16%to18.09%. The maximum LOD value was5.64and positive allelecame from Xieqingzao B. A total of major14and11QTLs for grain filling rate of inferior grains at fivestages and average grain filling rate of inferior grains across two environments were detectedrespectively, and7common QTLs were found. Among these QTLs, qSGFR-3-1in the intervalRM136-RM6302on chromosome6could be detected at the same stages in the two trials. Furthermore,it could be detected at four stages in Fuyang at2011, and phenotypic variance explained by individualQTL ranged from6.91%to14.69%. QTLs for grain filling rate of superior and inferior grains weredetected in intervals including RM282-RM6283and RM7370-RM16on chromosome3, RM136-RM6302and RM3724-RM3330on chromosome6, and RM5436-RM3670on chromosome7.
     3. Developmental behaviour of grains at five stages across four environments was used for QTLanalysis by using conditional composite interval mapping method. A total of21unconditional andconditional QTLs for superior grain weight were detected on chromosomes1,2,3,4,6,7,8and9,explaining5.25%-18.86%of phenotypic variation. Among these QTLs, there were16unconditionalQTLs,11conditional QTLs, and6corresponding QTLs. A total of16unconditional and conditionalQTLs for inferior grain weight at five stages across two environments were detected on chromosomes1,2,3,5,6,7,8and10, explaining5.73%-18.05%of phenotypic variation. Among these QTLs, therewere12unconditional QTLs,10conditional QTLs, and6corresponding QTLs. qIWG-6-1in theinterval RM136-RM6302on chromosome6was detected at four inferior grain filling stages, and therewas corresponding conditional QTL, suggesting that this QTL may play an important role in inferiorgrain filling. QTLs for grain filling rate of superior and inferior grains and grain weight were detected inintervals including RM282-RM6283and RM7370-RM16on chromosome3, RM136-RM6302andRM5436-RM3670on chromosome7, which was consistent with the fact that grain filling rate shows asignificantly positive correlation with grain weight. The results may provide four important intervals forfurther study on grain filling.
     4. A total of59major QTLs for nine traits including GPA, GPB, GPC, GPD, NFGP, SF, PP, and100-GW across four environments were detected on chromosomes1,2,3,5,6,7,8,9,10and11. TheQTL individually accounted for4.69%-23.74%of the phenotypic variation. A total of2,5,5,6,12,11,6,8and4QTLs for GPA, GPB, GPC, GPD, NFGP, SF, PP, and100-GW were detected respectively.Among these QTLs, qGPC-1, qGFD-6-1, qGFD-7-1, qGFD-7-2, qNFGP-6-1, qGNPP-2, qGNPP-3-1,qGNPP-7-2, qPP-2, qPP-3-1, qWG-3-1, and qWG-6-2were detected across two or more environments.
     5. Q enzyme activities at two grain filling stages (10d and15d after anthesis) in2010and at threegrain filling stages (10d,15d, and20d after anthesis) in2011in Fuyang were used for QTL analysis. Atotal of9major QTLs were detected on chromosomes2,3,5,6, and7, explaining5.68%-11.59%ofphenotypic variation. There were7,2, and1QTLs for Q enzyme activity at10d,15d and20d afteranthesis, respectively. Both qQ10-3for Q enzyme activity at10d after anthesis and qQ15-3-2for Qenzyme activity at15d after anthesis were located in the interval RM282-RM6283on chromosome3.The QTL for grain filling rate was also detected in this interval, suggesting that Q enzyme activityshows positive correlation with grain filling rate.
     6. A total of26major QTLs for five traits including grain length, grain width, grain thickness, grainvolume and grain length to width ratio across three environments (Fuyang2010,2011; Guiyang2011)were detected. Among these QTLs,4QTLs for grain length were detected on chromosome3,7,10, and11, explaining3.98%-54.58%of phenotypic variation. qGl3-1in the interval RM6283-RM7370onchromosome3could be detected in the three trials.4QTLs for grain width were detected onchromosome3and6, explaining6.98%-9.77%of phenotypic variation. qGw3-2in the intervalRM7370-RM16on chromosome3could be detected in the three trials.8QTLs for grain thickness weredetected on chromosome1,2,3,6,8,11, and12, explaining4.91%-11.92%of phenotypic variation. qGt3-1could be detected in the trials in Guiyang at2011and in Fuyang at2010.5QTLs for grainvolume were detected on chromosome3,4,6,7, and11, explaining5.07%-22.35%of phenotypicvariation. qGv3-1in the interval RM6283-RM7370on chromosome3could be detected in the threetrials.5QTLs for grain length to width ratio were detected on chromosome3,10, and11, explaining5.17%-47.81%of phenotypic variation. qGlwr3-1in the interval RM6283-RM7370on chromosome3could be detected in the three trials. The maximum phenotypic variance explained by this QTL wasmore than30%. QTLs for grain length, grain thickness, grain volume and grain length to width ratiocould be detected in the interval RM6283-RM7370on chromosome3, and the phenotypic varianceexplained by individual QTL was large.
     7. QTLs for traits related to grain filling rate under different conditions were analyzed by MCIMusing QTL-Network2.0. A total of24QTL pairs with additive×additive epistatic effects for8traits(the maximum grain filling rate and grain weight of superior grains, grain weight and grain filling rateof inferior grains, grain filling duration, grain width, grain thickness and grain length to width ratio)were detected, explaining0.26%-4.16%of phenotypic variation. QTL×environment interaction effectsof the major QTLs were less than their additive effect.
     8. Many QTL aggregation intervals were determined in this study, which affected grain filling rate,grain weight, grain type and Q enzyme activity. The results illustrated the close relationship between thefilling rate and yield related traits. For example, QTLs for the maximum grain filling rate of superiorand inferior grains, average grain filling rate, grain filling rate and grain weight at each stage of superiorand inferior grains, grain type, and Q enzyme activity were detected in the interval RM282-RM16onchromosome3; QTLs for grain filling rate and grain weight at each stage of superior and inferior grains,Q enzyme activity, grain plumpness, and number of filled grain per panicle were detected in the intervalRM136-RM6302on chromosome6; QTLs for grain filling rate and grain weight at each stage ofsuperior and inferior grains, Q enzyme activity, number of filled grain per panicle, grain number perpanicle, productive panicles were detected in the interval RM5436-RM3670on chromosome7.
引文
1.柏新付,蔡永萍,聂凡.脱落酸与稻麦籽粒灌浆的关系.植物生理学通讯,1989,(3):40-41
    2.白石.水稻灌浆速率和持续时间对产量的影响.福建稻麦科学,1981,2:55-57
    3.曹显祖,朱庆森.关于杂交水稻结实率的研究.江苏农业科学,1981,1:1-7
    4.曹立勇,占小登,庄杰云,等.水稻产量性状的QTL定位于上位性分析.中国农业科学,2003,36(11):1241-1247
    5.陈光辉,官春云,陈立云等.两系亚种间杂交稻籽粒充实度的遗传研.作物学报,2001,27(6):811-816.
    6.程式华,廖西元,闵绍楷.中国超级稻研究:背景、目标和有关问题的思考.中国稻米,1998,1:3-5
    7.程式华,庄杰云,曹立勇,等.超级稻分子育种研究.中国水稻科学.2004,18(5):377-383
    8.程式华.中国超级稻育种研究的创新与发展.沈阳农业大学学报,2007,38(5):647-651
    9.程方民,蒋德安,吴平,等.早籼稻籽粒灌浆过程中淀粉合成酶的变化及温度效应特征.作物学报,2001,27(2):201-206
    10.戴高兴,杨占烈,邓国富,等.超级杂交稻协优9308重组自交系主茎叶片数的动态QTL分析.中国水稻科学,2012,26(3):291-296
    11.丁安明,李君,催法,等.利用小麦关联RIL群体定位产量相关性状QTL.作物学报,2011,27(9):1511-1524
    12.董明辉,赵步洪,吴翔宙,等.水稻解释期不同籽粒相关内院激素含量和关键酶活性的差异及其与品质关系.中国农业科学,2008,41(2):370-380
    13.段俊,梁承邺,黄毓文,等.不同类型水稻品种(组合)籽粒灌浆特性及库源关系的比较研究.中国农业科学,1996,29(3):66-73
    14.付景,徐云姖,陈露,等.超级稻花后强、弱势粒淀粉合成相关酶活性和激素含量变化及其与籽粒灌浆的关系.中国水稻科学,2012,26(3):302-310
    15.符冠富,李华,陶龙兴,等.灌浆期遮光对水稻籽粒生长和Q酶活性的影响.生态学杂志,2009,28(3):438-444
    16.高用明.复杂上位性及其与环境互作的QTL定位方法和杂种优势预测研究.博士学位论文,浙江:2001
    17.顾世梁,朱庆森,杨建昌.不同水稻材料籽粒灌浆特性的分析.作物学报,2001,27(1):7-14
    18.顾世粱,王增春,惠大丰,等.遗传与栽培因素对水稻籽粒充实度等穗部性状影响的研究.北京:农业出版社,1994,266-270
    19.顾自奋,朱庆森,曹显祖.水稻结实率的研究-稻穗上强弱势粒的干重积累过程与空秕粒的分布.中国农业科学,1981,(6):38-44
    20.郭龙彪,罗利军,邢永忠等.水稻汕优63重组自交系重要农艺性状的QTLs和互作分析.农艺生物技术学报,2002,10(4):327-333
    21.何慈信,朱军,严建强,等.水稻穗干物质重发育动态的QTL定位.中国农业科学,2000,33(1):24-32
    22.何道根,潘晓飚,屈为栋.杂交早稻穗充实度的遗传分析.中国农学通报,1998,14(5):30-32
    23.何小红,徐辰武,蒯建敏,等.数量性状基因作图精度的主要影响因子.作物学报,2001,27(4):469-476
    24.何予卿,徐才国.上位性对光敏核不育水稻不育性不稳定性的影响.植物学报,2000,42(10):1062-1068.
    25.何祯祥,施季森,邱进清,等.林木遗传图谱构建的技术与策略.浙江林学院学报,1998,15(2):151-157
    26.黄华松,孙宗修,胡培松,等.食用稻米品种形成研究的现状与展望.中国水稻科学,1998,12(3):172-176
    27.贾继增.分子标记种质资源鉴定和分了标记育种.中国农业科学,1996,29(4):1-10
    28.贾小丽,叶江华,苗利国,等.水稻重组自交系群体灌浆速率的遗传分析.中国农学通报,2012,28(21):22-26
    29.贾小丽,叶江华,苗利国,等.水稻籽粒灌浆速率的发育遗传机制研究.热带作物学报,2012,33(4):622-626
    30.江建华,张晚霞,刘晓丽,等.多环境下粳稻株高动态QTL分析.中国水稻科学,2012,26(1):55-64
    31.江良荣,王伟,黄建勋,等.水稻粒形性状的上位性和QE互作效应分析.分子植物育种,2009,7(4):690-698
    32.金正勋,杨静,钱春荣,等.灌浆成熟期温度对水稻籽粒淀粉合成关键酶活性及品质的影响.中国水稻科学,2005,19(4):377-380
    33.库丽霞,孙朝辉,王翠玲,等.玉米光周期敏感相关性状发育动态QTL定位.作物学报,2010,36(4):602-611
    34.黎毛毛,徐磊,任军芳,等.粳稻粒形性状的数量性状基因座检测.中国农业科学,2009,42(7):2255-2261
    35.李广军,李河南,程利国,等.大豆叶绿素含量动态表达的QTL分析.作物学报,2010,36(2):242248
    36.李伟,左清凡,张建中.水稻籼粳型品系杂种籽粒充实度的遗传分析.华中农业大学学报,2002,4(21):321-324
    37.雷东阳,陈立云.水稻抽穗期QTLs的检测及上位性和环境互作效应.湖南农业大学学报(自然科学版),2010,36(3):245-249
    38.梁建生,曹显祖,徐生,等.水稻籽粒库强与其淀粉积累之间关系的研究.作物学报,1994,20(6):685-691.
    39.林鸿宣,闵绍楷,熊振民,等.应用RFLP图谱定位分析籼稻粒形数量性状基因座位.中国农业科学,1995,28(4):1-7
    40.林荔辉,吴为人.水稻粒形和粒重的QTL定位分析.分子植物育种,2003,1(3):337-342
    41.林建荣,石春海,吴明国.不同环境条件下粳型杂交稻稻米外观品质性状的遗传效应.中国水稻科学,2003,17(1):16-20.
    42.刘宾,赵亮,张坤普,等.小麦株高发育动态QTL定位.中国农业科学,2010,43(22):4562-4570
    43.吕冰,吕冰,郭志刚,梁建生.水稻胚乳中淀粉合成相关酶活性的变化对支链淀粉精细结构的影响.中国科学,2008,38(8):766-773
    44.马钧,明东风,马文波,等.不同施氮时期对水稻淀粉积累及淀粉合成相关酶类活性变化研究.中国农业科学,2005,38(2):290-296.
    45.马莲菊,崔鑫福,吕文彦.淀粉合成相关酶活性变化及其与籽粒灌浆和稻米品质的关系.山东农业大学学报,2006,37(3):354-358。
    46.牛傲雷,卢训莉,宋驰.水稻DH群体籽粒充实度的QTL定位.武汉植物学研究,2004,22(6):477-481
    47.沈波,陈能,李太贵,等.温度对早籼稻米垩白发生与胚乳物质形成的影响.中国水稻科学,1997,11(3):183-186
    48.沈波,蒋德安,吴平,等.早籼稻籽粒灌浆过程中淀粉合成酶的变化及温度效应特征.作物学报,2001,27(2):201-206
    49.沈波,庄杰云,樊叶杨,等.水稻籽粒淀粉分支酶活性的遗传分析.植物生理与分子生物学学报,2005,31(6):631-636
    50.沈希宏,陈深广,曹立勇,等.超级杂交稻协优9308重组自交系的分子遗传图谱构建.分子植物育种,2008,6(5):861-866
    51.石春海,申宗坦.早籼粒形的遗传和改良.中国水稻科学,1995,9(1):27-32.
    52.苏泽胜,李泽福.安徽省超级稻研究与应用现状及展望.沈阳农业大学学报,2007,38(5):739-743
    53.孙德生,李文滨,张忠臣,等.大豆株高QTL发育动态分析.作物学报,2006,32(4):509-514
    54.唐瑭,谢红,吕冰,等.植物激素对杂交稻籽粒灌浆及蔗糖合酶活性的影响.中国水稻科学,2011,25(2):182-188
    55.王建林.中国粮食总产量结构分析与丰歉评估.气象,1998,24(12):7-12.
    56.王军,朱金燕,周勇,等.基于染色体单片段代换系的水稻粒形QTL定位.作物学报,2013,39(4):617-625
    57.王天铎.水稻籽粒灌浆过程中粒重分布的动态研究.植物学报,1962,10(2):113-119
    58.王维,蔡一霞,蔡昆争,等.水分胁迫对贪青水稻籽粒充实及其淀粉合成关键酶活性的影响.作物学报,2006,32(7):927-929.
    59.王熹,施一平.乙烯利对水稻催熟效应的生理分析.作物学报,1976,18(2):150-155
    60.王志琴,叶玉秀,杨建昌,等.水稻灌浆期籽粒中蔗糖合成酶活性和变化调节.作物学报,2004,30(7):634-643
    61.王文文,兰进好,田纪春.小麦籽粒灌浆速率及粒重QTL初步研究.中国农学通报,2012,28(36):63-70
    62.王瑞霞,张秀英,肖世和,等.不同生态环境下小麦籽粒灌浆速率及千粒重QTL分析.作物学报,2008,34(10):1750-1756
    63.吴为人,李维明,卢浩然.基于最小二乘估计的数量性状基因座的复合区间定位法.福建农业大学学报,1996,25(4):393-399
    64.吴为人,李维明,卢浩然.数量性状基因座的动态定位策略.生物数学学报,1997,12(5):490-498
    65.武翠,绍国军,吕文彦,等.不同发育时期水稻强、弱势粒灌浆速率的遗传分析.中国农业科学,2007,40(6):1135-1141
    66.夏斌,郭涛,王慧,等.水稻淀粉合成关键酶的研究进展.中国农学通报,2009,25(22):47-51
    67.夏淑芳,张振清.稻穗上各部位籽粒干物质积累的规律和呼吸强度的变化.植物生理学报,1964, S1:251-263
    68.谢华安.华南型超级稻育种及其技术研究进展.沈阳农业大学学报,2007,38(5):714-718
    69.谢华安.中国特别是福建的超级稻研究进展.中国稻米,2004,2:7-9
    70.邢永忠,谈移芳,徐才国,等.利用水稻重组自交系群体定位谷粒外观性状的数量性状基因.植物学报,2001,43(8):840-845
    71.严建兵,汤华,黄益勤,等.不同发育时期玉米株高QTL的动态分析.科学通报,2003,48(18):1959-1964
    72.杨建昌,彭少兵,顾世梁,等.水稻灌浆期籽粒中3个与淀粉合成有关的酶活性变化.作物学报,2001,27(2):157-164.
    73.杨建昌,王国忠,王志琴,等.旱种水稻灌浆特性与灌浆期籽粒中激素含量的变化.作物学报,2002,28(5):615-621
    74.杨建昌,袁莉民,唐成,等.结实期干湿交替灌溉对稻米品质及籽粒中一些酶活性的影响.作物学报,2005,31(8):1052-1057.
    75.杨建昌.水稻弱势粒灌浆机理与调控途径.作物学报,2010,36(12):2011-2019
    76.杨运清,李仁杰,李淑玲.动态性状遗传参数估计方法.畜牧兽医学报,1996,27(5):4l2-416
    77.杨亚春,倪大虎,宋丰顺,等.不同生态地点下稻米外观品质性状的QTL定位分析.中国水稻科学,2011,25(1):43-51
    78.余四斌,李建雄,徐才国,等.上位性效应是水稻杂种优势的重要遗传基础.中国科学C辑,1998,41(3):293-302
    79.袁爱平,曹立勇,庄杰云,等.水稻株高、抽穗期和有效穗数的QTL与环境的互作分析.遗传学报,2003,30(10):899-906
    80.袁隆平.两系法杂交水稻研究进展.中国农业科学,1990,(3):1-6
    81.袁隆平.两系杂交稻育种进展.杂交水稻,1993(3):1-6
    82.张光恒,张国平,钱前,等.不同环境条件下稻谷粒形数量性状的QTL分析.中国水稻科学,2004,18(1):16-22
    83.张俊国,曹丙晨,张步龙,等.不同粳稻品种灌浆速率的研究.辽宁农业科学,1991,1:21-26
    84.张祖建,朱庆森,曹显祖,等.亚种间杂交稻籽粒充实度表现及其配合力.江苏农学院学报,1995,16(2):5-9
    85.章志宏,宋文贞,刘少佳,等.水稻籼粳交DH群体籽粒充实度的遗传分析.武汉植物学研究,2002,20(1):1-4
    86.赵步洪,张洪熙,朱庆森,等.两系杂交稻籽粒充实不良的成因及其与激素含量关系.中国农业科学,2006,39(3):477-486
    87.赵步洪,张文杰,常二华,等.水稻灌浆期籽粒中淀粉合成关键酶的活性变化及其与灌浆速率和蒸煮品质的关系.中国农业科学,2004,37(8):1123-1129
    88.翟荣荣,冯跃,王会民,等.不同水分条件下水稻苗期根系性状的QTL分析.核农学报,2012,26(7):0975-0982
    89.周元昌,陈启锋,吴为人,等.作物QTL定位研究进展.福建大学学报,2000,29(2):138-144
    90.朱军.复杂数量性状基因定位的混合线性模型方法.中国农业科技出版社,1998,11-20
    91.朱军.运用混合线性模型定位复杂数量性状基因的方法.浙江大学学报(自然科学版),1999,33(3):327-335
    92.朱庆森,曹显祖,顾自奋.杂交水稻南优3号籽粒发育动态研究.中国农业科学,1980,14(1):43-49
    93.朱庆森,曹显祖,骆亦其.水稻籽粒的灌浆生长分析.作物学报,1988,14:182-192.
    94.朱庆森,王志琴,张祖建,等.水稻籽粒充实程度的指标研究.江苏农学院学报,1995,16(2):1-4
    95.朱庆森.水稻品种库源特征及其类型划分的研究.作物学报,1987,13(4):265-272.
    96.朱运昌,廖伏明.水稻两系亚种间杂种优势的研究.杂交水稻,1990(3):32-34
    97.邹应斌.杂交水稻籽粒充实过程研究初报.湖南农业科学,1986,(4):20-24
    98.左清凡,宋宇,张冬玲,等.水稻稻穗灌浆生长的基因效应全程分析.作物学报,2005,31(7):821-826
    99.左清凡,谢平,宋宇,等.水稻籽粒不同发育时期灌浆速率的遗传及其与环境互作的分析.中国农业科学,2002,35(5):465-470
    100. Ahn S N, Bolich C N, McClung A M, et al. RFLP analysis of genomic regions associated withcooked kernel elongation in rice. Theor Appl Genet,1993,87(1):27-32
    101. Akagi H, Nakamura A, Yokozeki-Misono Y, et al. Positional cloning of the rice Rf-1gene, arestorer of BT-type cytoplasmic male sterility that encodes a mitochondria-targeting PPR protein.Theor Appl Genet,2004,108:1449-1457
    102. Akkareddy S, Lakshminarayana R.V, Sakile S, et al. Molecular mapping of QTLs for yield and itscomponents under two water supply conditions in rice (Oryza sativa L.). Crop Sci. Biotech.2011(March)14(1):45-56.
    103. Aoki N, Hirose T, Scofield G N, Whitfeld P R, et al. The sucrose transporter gene family in rice.2003. Plant Cell Physiol,44(33):223-232。
    104. Ashikari M, Sakakibara H, Lin S, et al. Cytokinin oxidase regulates rice grain roduction. Science,2005,309(5735):741-745
    105. Atchley W R,Xu S Z, Vogl C. Developmental quantitative genetic models of evolutionary change.Dev Genet,1994,15(1):92-103.
    106. Botstein D, White R L, Skolnick M, et al. Construction of a genetic linkage map in man usingrestriction fragment length polymorphisms. Am J Hum Genet,1980,32(3):314-331
    107. Cao G Q, Zhu J. Conditional genetic analysis on quantitative trait loci for yield and its componentsin rice. J Life Sci,2007,4,(1):71-76
    108. Causse M A, Fulton T M, Cho Y G, et al. Saturated molecular map of the rice genome based on aninterspecific backcross population. Genetics,1994,138(4):1251-1274
    109. Cho J I, Lee SK, Ko S, et al. Molecular cloning and expression analysis of the cell-wall invertasegene family in rice (Oryza sativa.L). Plant Cell Rep,2005,24(4):225-236
    110. Coulson A, Sulston J, Brenner S, et al. Toward a physical map of the genome of the nematodeCaenorhabditis elegans. Proc Natl Acad Sci USA,1986,83(20):7821-7825
    111. Cui K H, Peng S B, Xing Y Z, et al. Molecular dissection of the genetic relationships of source,sink and transport tissue with yield traits in rice. Theor Appl Genet,2003,106(4):649–658
    112. Doi K, Izawa T, Fuse T, et al. Ehd1, a B-type response regulator in rice, confers short-daypromotion of flowering and controls FT-like gene expression. Genes Dev,2004,18(8):926-936
    113. Falconer D S, Mackay T F. Introduction to quantitative genetics. New York: Longman Scientific&Technical,1996,4thed
    114. Fan C C, Xing Y Z, Mao H L, et al. GS3, major QTL for grain length and weight and minor QTLfor grain width and hickness in rice, encode a putative transmembrane protein. Theor Appl Genet,2006,112(6):1164-1171
    115. Guo L B, Zhu L H, Xu Y B, et al. QTL analysis of seed dormancy in rice (Oryza sativa L.).Euphytica,2004,140(3):155-162.
    116. Han L Z, Qiao Y L, Zang S Y, et al. QTL analysis of some agronomic traits in rice under differentgrowing environments. Ag Sci China,2006,5(1):15-22
    117. Harushima Y, Yano M, Shomura A, et al. A high-density rice genetic linkage map with2275markers using a single F2population. Genetics,1998,148(1):479-494
    118. Hirose T, Scofield G N, Terao T. An expression analysis profile for the entire sucrose synthase genefamily in rice. Plant Sci,2008,174(5):534-543
    119. Hirose T, Takano M, Terao M. Cell wall invertase in developing rice caryopsis: molecular cloningof oscin1and analysis of its expression in relation to its role in grain filling. Plant Cell Physiol,2002,43(4):452-459
    120. Hirose T, Terao T. A comprehensive expression analysis of the starch synthase gene family in rice(Oryza sativa L.). Planta,2004,220(1):9-16
    121. Huang N, Parco A, Mew T, et al. RFLP mapping of isozymes, RAPD and QTLs for grain shape,brown planthopper resistance in a doubled haploid rice population. Mol Breeding,1997,3(2):105-113
    122. Hyne v, Kearsey M J, Pike D J, et al. QTL analysis: unreliability and bias in estimation procedures.Mol Breeding,1995, l(3):273-282
    123. James M G, Denyer K, Myers A M. Starch synthesis in the cereal endosperm. Curr Opin Plant Biol,2003,6(3):215-222
    124. Jansen R C, Ooijen J W, Stam P, et al. Genotype-by-environment interaction in genetic mapping ofmultiple quantitative trait loci. Theor Appl Genet,1995,91(1):33-37
    125. Jiang D, Cao W X, Dai T B. Activities of key enzymes for starch synthesis in relation to growth ofsuperior and inferior grains on winter wheat(Triticum aestivum L.)spike. Plant Growth Regul,2003,41(3):247-257
    126. Jiang G H, Xu C G, Tu J M, et al. Pyramiding of insect and disease resistance genes into an eliteindica, cytoplasm male sterile restorer line of rice, Minghui63. Plant Breeding,2004,123(2):112-116
    127. Jiang H W, Dian W M, Liu F Y, et al. Molecular cloning and expression analysis of three genesencoding starch synthase II in rice. Planta,2004,218(6):1062-1070
    128. Kao C H, Zeng Z B, Teasdale R D. Multiple interval mapping for quantitative trait loci. Genetics,1999,152(3):1203-1216
    129. Kato T, Sakural N, Kuraishi S. The changes of endogenous abscisic acid in developing grains oftwo rice cuhivars with different grain size. Jap J Crop Sci,1993,62(5):456-461
    130. Kato T, Takeda K. Associations among characters related to yield sink capacity in space-plantedrice. Crop Sci,1996,36(5):1135–1139
    131. Kato T. Change of sucrose synthase activity in developing endosperm of rice cultivars. Crop Sci,1995,35(3):827-831
    132. Kato T. Effect of spikelet removal on the grain filling of Akenohoshi, a rice cultivar with numerousspikelets in a panicle. Jap Agri Sci,2004,142(4):177-181
    133. Kearsey M J, Farquhar A G. QTL analysis in plants: where are we now? Heredity,1998,80(2):137-142
    134. Kearsey M J. The principles of QTL analysis (a minimal mathematics approach). J Exp Bot,1998,327(49):1619-1623
    135. King R W. Abscisic acid in developing wheat grains and its relationship to grain growth andmaturation. Planta,1976,132(1):43-51
    136. Kirkpatrick M, Lofsvold D, Bulmer M. Analysis of the inheritance, selection and evolution ofgrowth trajectories. Genetics,1990,124(4):979-993
    137. Kojima S, Takahashi Y, Kobayashi Y, et al. Hd3a, a rice ortholog of the Arabidopsis FT gene,promotes transition to flowering downstream of Hd1under short-day conditions. Plant CellPhysiol,2002,43(10),1096-1105
    138. Kurata N, NagamuraY, Yamamoto K. A300kilo base interval gentic map of rice including883expressed sequences. Nat Genet,1994,8(4):365-372
    139. Lander E S, Botstein D. Mapping mendelian factors underlying quantitative traits using RFLPlinkage maps. Genetics,1989,121(1):85-199
    140. Li J, Xiao J, Grandllo S, et al. QTL detection for rice grain quality traits using an interspecificbackcross population derived from cultivated Asian (O. sativa L.) and African (O. glaberrima S.)rice. Genome(National research council Canada),2004,47:697-704
    141. Li xiao-guang, Liu Hai-ying, Jin Zheng-xun1, et al. Changes in Activities of Key Enzymes forStarch Synthesis and Glutamine Synthetase in Grains of Progenies from a Rice Cross During GrainFilling. Rice science,2010,17(3):243-246
    142. Li Z F, Wan J M, Xia J F, et al. Mapping quantitative trait loci underlying appearance quality ofrice grains (Oryza sativa L.). Acta Genetica Sinica,2003,30(3):251-259
    143. Liang J, Zhang J, Cao X. Grain sink strength may be related to the poor grain filling ofIndica-japonica rice (Oryza sativa) hybrids. Physiol Plantarum,2001,112(4):470-477
    144. Liang Y S, Zhan X D, Gao Z Q, et al. Mapping of QTLs associated with important agronomic traitsusing three populations derived from a super hybrid rice Xieyou9308. Euphytica,2012,184(1):1-13
    145. Liu Z H, Ji H Q, Cui Z T, et al. QTL detected for grain-filling rate in maize using a RIL population.Mol Breeding,2011,27(1):25–36.
    146. Ma Y Z, Mackown C T, Vansanford D A V. Sink manipulation in wheat: compensatory changes inkernel size. Crop Sci,1990,30(5):1099–1105.
    147. Matsubara K, Kono I, Hori K, et al. Novel QTLs for photoperiodic flowering revealed by usingreciprocal backcross inbred lines from crosses between japonica rice cultivars. Theor Appl Genet,2008,117(6):935-945
    148. McCouch S R, Cho Y G, Yano M, et al. Report on QTL Nomenclature. Rice Genet Newslett,1997,14:11–13
    149. McCouch S, Kochert G, Yu Z, et al. Molecular mapping of rice chromosomes. Theor Appl Genet,1988,76(6):815-829
    150. Miura K, Lin S Y, Yano M, et al. Mapping quantitative trait loci controlling seed longevity inrice(Oryza sativa L.). Theor Appl Genet,2002,104(6):981-986.
    151. Nagaraju J, Kathirvel M, Ramesh K R,et al. Genetic analysis of traditional and evolved Basmatiand non-Basmati rice varieties by using fluorescence-based ISSR-PCR and SSR markers. Proc NatAcad Sci USA,2002,99(9):5836-5841
    152. Nagata K, Shimizu H, Terao T. Quantitative trait loci for nonstructural carbohydrate accumulationin leaf sheaths and culms of rice and their effects on grain filling. Breeding Sci,2002,52(4):275-283
    153. Nakamura Y. Towards a better understanding of the metabolic system for amylopectin biosynthesisin plants: rice endosperm as a model tissue. Plant Cell physiol,2002,43(7):718-725
    154. Nakamura Y. Towards a better understanding of the metabolic system for amylopectin biosynthesisin plants: rice endosperm as a model tissue. Plant Cell physiol,2002,43(7):718-725.
    155. Nakamura,Y. Yuki K, Park S Y. Carbohydrate metabolism in the developing endosperm of ricegrains. Plant Cell Physiol,1989,30(6):833-839;
    156. Naoko F, Mayumi Y, Noriko Asakura, et al. Function and characterization of starch synthase iusing mutants in rice. Plant Physiology,2006,140(3):1070-1084
    157. Naoko F, Mayumi Y, Tomonori K et al. Characterization of ssiiia-deficient mutants of rice: thefunction of ssiiia and pleiotropic effects by ssiiia deficiency in the rice endosperm.. PlantPhysiology,2007,144(4):2009-2023
    158. Nass H G, Reisser B. Grain filling period and grain yield relationships in spring wheat. Can J PlantSci,1975,55:673-678
    159. Nelson O E, Rines H W. The enzymatic deficiency in the waxy mutant of maize. Biochem BiophysRes Commun,1962,31(9):297-300
    160. Normile D. Yangtze seen as earliest rice site. Science,1997,275(5298):309
    161. Parnell F R, Rangaswamy G N, Yangar A Y, et al. The inheritance of characters in rice. Mem DeptAgr India Bot Ser,1917,9(1):75-105
    162. Preiss J, Ball K, Smith-White B, et al. Starch biosynthesis and its regulation. Biochem SocTrans,1991,19:539-547
    163. Qu Y Y, Mu P, Zhang H L, et al. Mapping QTLs of root morphological traits at different growthstages in rice. Genetica,2008,133(2):187–200
    164. Redona E D, Mackil D J. Quantitative trait locus analysis for rice panicle and grain characteristics.Theor App1Genet,1998,96(6):957-963
    165. Roitsch T, Balibrea M E, Hofmann M, et al. Extracellular invertase: key metabolic enzyme and PRprotein. J Exp Bot,2003,54(382):513-524
    166. Shomura A, Izawa T, Ebana K., et al. Deletion in a gene associated with grain size increased yieldsduring rice domestication. Nat Genet,2008,40(8):1023-1028
    167. Shure M, Wessler S, Federoff N. Molecular identification and isolation of the Waxylocus in maize.Cell,1983,35(1):225-233
    168. Smith A M, Denyer K, Martin C. The synthesis of the starch granule. Annu Rev Plant Physiol PlantMol Biol.1997,48(1):67-87
    169. Song X J, Huang W, Shi M, et al. A QTL for rice grain width and weight encodes a previouslyunknown RING-type E3ubiquitin ligase. Nat Genet,2007,39(5):623-630
    170. Stuber C W, Moll R H, Goodman M.M.: Allozyme frequency changes associated with selection forincreased grain yield in maize (Zea mays L). Genetics,1980,95:225-236
    171. Sturm A, Tang G Q. The sucrose-cleaving enzymes of plants are crucial for development, growthand carbon partitioning. Trends Plant Sci,1999,4(10):401–407
    172. Sun D S, Li W B, Zhang Z C, et al. Quantitative trait loci analysis for the developmental behaviorof Soybean (Glycine max L. Merr.). Theor Appl Genet,2006,112(4):665-673
    173. Tan Y F, Xing Y Z, Li J X, et al,. Genetic bases of appearance quality of rice grains in Shanyou63,an elite rice hybrid. Theoretical and applied genetics,2000,101:823-829
    174. Takahashi Y, Shomura A, Sasaki T, et al. Hd6, a rice quantitative trait locus involved inphotoperiod sensitivity, encodes the α subunit of protein kinase CK2. Proc Natl Acad Sci USA,2001,98(14):7922-7927
    175. Takai T, Fukuta Y, Shiraiwa T, et al. Time-related mapping of quantitative trait loci controllinggrain-filling in rice (Oryza sativa L.). J Exp Bot,2005,56(418):2107-2118
    176. Takashi,A. Kouichi,M. Tatsuhito,F., Gene expression of ADP-glucose pyrophosphorylase andstarch contents in rice cultured cells are cooperatively regulated by sucrose and ABA. Plant CellPhysiol,2005,46(6):937-946
    177. Tang T, Xie H, Wang Y X, et al. The effect of sucrose and abscisic acid interaction on sucrosesynthase and its relationship to grain filling of rice (Oryza sativa L.). J Exp Bot,2009,60(9):2641-2652
    178. Tanksley S D. Mapping polygenes. Annu Rev Genet,1993,27(10):205-233
    179. Temnykh S, Declerck G, Luashova A, et al. Computational and experimental analysis ofmicrosatellites in rice (Oryza sativa L.): frequency, length variation, transposon associations, andgenetic marker potential. Genome Res,2001,11(8):1441-1452
    180. Teng W, Han Y, Du Y, et al. QTL analyses of seed weight during the development of soybean(Glycine max L. Merr.). Heredity,2009,102(4):372-380
    181. Thevenot C, Simond-Cote E, Reyss A, et al. QTLs for enzyme activities and soluble carbohydratesinvolved in starch accumulation during grain filling in maize. J Exp Bot,2005,56(413):945-958
    182. Tsai C Y. The function of the waxy locus in starch synthesis in maize endosperm. Biochem Genet,1974,11(2):83-96
    183. Tymowska-Lalanne Z, Kreis M. Expression of the Arabidopsis thaliana invertase gene family.Planta,1998,207(2):259-265
    184. Umemoto T, Yano M, Satoh H, et al. Mapping of a gene responsible for the difference inamylopectin structure between japonica-type and indica-type rice varieties. Theor Appl Genet,2002,104(1):1-8
    185. Vergara B S, Chang T T. The flowering response of the rice plant to photoperiod, a review of theliterature,4th ed. Manila: International Rice Research Institute,1985
    186. Wan X Y, Wan J M, Jiang L, et al. QTL analysis for rice grain length and fine mapping of anidentified QTL with stable and major effects. Theor Appl Genet,2006,112(7):1258-1270
    187. Wang A Y, Kao M H, Yang W H, et al. Differentialy and developmentally regulated expression ofthree ricesucrose synthase genes. Plant Cell Physiol,1999,40(8):800–807
    188. Wang D L, Zhu J, Li Z K, et al. Mapping QTLs with epistatic effects and QTL (environmentinteractions. Theor Appl Genet,1999,99(7):1255-1264
    189. Wang E T, Wang J J, Zhu X D et al. Control of rice grain-filling and yield by a gene with apotential signature of domestication. Nat Genet,2008,40(11):1370-1374
    190. Wang G L, Mackilld J, Bonmanj M, et a1. RFLP mapping of genes conferring complete a durablyresistant rice cultivar. Genetics,1994,136:1421-1434
    191. Wang J K, Wan X Y, Crossa J, et al. QTL mapping of grain length in rice (Oryza sativa L.) usingchromosome segment substitution lines. Genet Res,2006,88(2):93-104
    192. Wang R X, Hai L, Zhang X Y et al. QTL mapping for grain filling rate and yield-related traits inRILs of the Chinese winter wheat population Heshangmai3Yu8679. Theor Appl Genet,2009,118(2):313–325
    193. Wang X Y, Wan J M, Weng J F, et al. Stability of QTLs for rice grain dimension and endospermchalkiness characteristics across eight environments. Theor Appl Genet,2005,110:1334-1346
    194. Wang S, Basten C J, Zeng Z B. Windows QTL Cartographer2.5department of statistics. NorthCarolina State University, Raleigh, USA,2006
    195. Wang Y H and Li J Y. Molecular mechanism of plant architecture. Annual Review Plant Biology,2008.59:253-279
    196. Wang Z H, Wu X S, Ren Q, et al. QTL mapping for developmental behavior of plant height inwheat (Triticum aestivum L.). Euphytica,2010,174(3):447-458
    197. Weller J I, Soller M, Brody T. Linkage analysis of quantitative traits in an interspecific cross oftomato (Lycopersicon esculentum×Lycopersicon pimpinellifolium) by means of genetic markers.Genetics,1988,118(2):329-339
    198. Weng J, Gu S H, Wan X Y, et al. Isolation and initial characterization of GW5, a major QTLassociated with rice grain width and weight. Cell Res,2008,18:1199–1209
    199. Wiegand C L, Cuellar J A. Duration of grain filling and kernel weight of wheat as by temperature.Crop Sci,1981,21:95-101
    200. Xie X, Song M H, Jin F, et al. Fine mapping of a grain weight quantitative trait locus on ricechromosome8using near-isogenic lines derived from a cross between Oryza sativa and Oryzarufipogon. Theor Appl Genet,2006,115(5):885-894
    201. Xing Y Z, Zhang Q F. Genetic and molecular bases of rice yield. Annu Rev Plant Biol,2010,61,421-442
    202. Xue W Y, Xing Y Z, Weng X Y, et al. Natural variation in Ghd7is an important regulator ofheading date and yield potential in rice. Nat Genet,2008,40(6):761-767
    203. Yamamoto T, Lin H X, Sasaki T, et al. Identification of heading date quantitative trait locus Hd6and characterization of its epistatic interactions with Hd2in rice using advanced backcross progeny.Genetics,2000,154(2):885-891
    204. Yan J Q, Zhu J, He C X,et al. Quantitative trait loci analysis for the developmental behavior oftiller number in rice (Oryza sativa L.). Theor Appl Genet,1998,97(1):267-274
    205. Yan W H, Wang P, Chen H X, et al. A major QTL, Ghd8, plays pleiotropic roles in regulating grainproductivity, plant height, and heading date in rice. Mol Plant,2011,4(2):319-330
    206. Yang J C, Cao Y Y, Zhang H, et al. Involvement of polyamines in the post-anthesis development ofinferior and superior spikelets in rice. Planta,2008,228(1):137-149
    207. Yang J C, Peng S B, Visperas R M, et al. Grain filling pattern and cytokinin content in the grainsand roots of rice plants. Plant Growth Regul,2000,30(3):261-270
    208. Yang J C, Zhang J H, Liu K, et al. Abscisic acid and ethylene interact in wheat grains in responseto soil drying during grain filling. New Phytol,2006,171(2):293-303
    209. Yang J C, Zhang J H, Wang Z Q, et al. Hormonal changes in the grains of rice subjected to waterstress during grain filling. Plant Physiol,2001,127(1):315-323;
    210. Yang J C, Zhang J S, Wang Z Q, et al. Post-anthesis development of inferior and superior spikeletsin rice in relation to abscisic acid and ethylene. J Exp Bot,2006,57(1):149-160
    211. Yang J C, Zhang J.H, Wang Z.Q, et al. Activities of enzymes involved in sucrose-to-starchmetabolism in rice grains subjected to water stress during filling. File Crop Rse,2003,81(1):69-81
    212. Yang J, Zhang J, Wang Z, et al. Post-anthesis development of inferior and superior spikelets in ricein relation to abscisic acid and ethylene. J Exp Bot,2006,57(1):149-160
    213. Yang J, Zhang J. Grain filling problem in super rice. J Exp Bot,2010,61(1):1-5
    214. Yano M, Katayose Y, Ashikari M, et al. Hd1, a Major photoperiod sensitivity quantitative traitlocus in rice, is closely related to the Arabidopsis flowering time gene CONSTANS. Plant Cell,2000,12(12):2473-2484
    215. Yu B, Lin Z, Li H, et al. TAC1, a major quantitative trait locus controlling tiller angle in rice. PlantJ,2007,52(5):891-898.
    216. Yu J, Hu S, Wang J, et al. A draft sequence of the rice genome (Oryza sativa L ssp japonica).Science,2002,296(5565):79-92
    217. Zeng Z B. Precision mapping of quantitative trait loci. Genetics,1994,136(4):1457-468
    218. Zeng Z B. Theoretical basis for separation of multiple linked gene effects in mapping quantitativetrait loci. Proc Nall Acad Sci USA,1993,90(23):10972-10976
    219. Zhang G Y, Cheng Z J, Zhang X, et al. Double repression of soluble starch synthase genes SSIIaand SSIIIa in rice (Oryza sativa L.) uncovers interactive effects on the physicochemical propertiesof starch. Genome,2011,54(6):448-459
    220. Zhang H, Chen T T. Wang Z Q, et al. Involvement of cytokinins in the grain filling of rice underalternate wetting and drying irrigation. J Exp Botany,2010,61(13):3719-3733
    221. Zhang Y S, Luo L J, Xu C G, et al. Quantitative trait loci for panicle size, heading date and plantheight co-segregating in trait-performance derived near-isogenic lines of rice (Oryza sativa L.).Theor Appl Genet,2006,113(2):361-368
    222. Zhang Z H, Yu S B, Yu T, et al. Mapping quantitative trait loci (QTLs) for seedling-vigor usingrecombinant inbred lines of rice (Oryza sativa L.). Field Crops Res,2005,91(2):161-170
    223. Zhou L J, Jing L, Liu X, et al. Mapping and interaction of QTLs for thousand-grain weight andpercentage of grains with chalkiness in rice. Acta Agron Sin,2009,35(2):255-261
    224. Zhu J, Weir B S. Mixed model approaches for genetic analysis of quantitative traits. In AdvancedTopics in Biomathematics: Proceedings of International Conference on Mathematical Biology.1998,1:321-330
    225. Zhu J. Analysis of conditional genetic effects and variance components in developmental genetics.Genetics,1995,141(4):1633-1639

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