普通×爆裂玉米RILs构建及主要性状QTL分析
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摘要
爆裂玉米是一种专门用来制作玉米花系列休闲食品的专用型玉米,在休闲食品工业具有独特的应用价值。膨爆特性和产量等主要育种目标性状都是由多基因控制的复杂数量性状,虽然国内外遗传育种学家在爆裂玉米种质创新和主要性状传统数量遗传方面进行了比较全面的系统研究,但利用爆裂玉米种质对主要性状开展有关分子数量遗传研究较少。本研究以普通玉米自交系丹232与优良爆裂玉米自交系N04杂交构建的含有258个家系的F9代重组近交系(RILs)为材料,利用SSR分子标记构建高密度遗传连锁图谱,采用复合区间作图法,以排列测验1 000次所得LOD值作为阈值,对RIL群体的3个膨爆特性指标、8个穗粒性状、4个籽粒营养品质性状和9个植株性状进行3种环境条件下及合并分析的QTL定位和效应分析,采用多区间作图法分析定位QTL间的上位效应,采用多性状联合分析的复合区间作图法对膨爆特性指标间、主要穗粒性状间、主要籽粒营养品质性状间以及主要植株性状间进行了多性状联合QTL分析,探讨各性状的分子遗传机制及其间的遗传关系,同时与以往利用相同亲本构建的F2:3和BC2F2群体的定位结果进行比较,筛选具有环境和世代稳定性的关键QTL,为进一步开展分子标记辅助选择、QTL精细定位和克隆以及其他相关研究提供更为可靠的理论依据和材料平台。
     本研究主要实验和研究结果如下:
     1、选用覆盖玉米基因组的723对SSR引物对两个亲本N04和丹232进行多态性检测,获得212个共显性标记位点,占29.32%。利用Mapmaker3.0作图软件构建的分子标记连锁图包括207个共显性标记,图谱总长度为2 408.80 cM,相邻两标记间的平均距离为11.64 cM。
     2、RIL群体3个膨爆特性指标、8个穗粒性状、4个籽粒营养品质性状和9个植株性状中除膨化倍数和穗上位叶片数外,其余各性状均表现出超双亲分离;各性状均呈连续正态分布;大多数性状家系、环境及家系与环境互作均存在显著或极显著差异;各膨爆特性、穗粒性状、籽粒营养品质性状、植株性状的遗传力均较大,分别为0.90~0.92、0.83~0.94、0.67~0.93、0.80~0.96。
     3、3种环境条件下及合并分析共检测到27个与3个膨爆特性指标相关的QTL,单个QTL的贡献率为4.43%~20.95%,其中qPF-1-1、qPV-7-1和qPR-1-1 3个QTL在3种环境条件下及合并分析均被检测到,具有环境稳定性,7个QTL的贡献率大于10%;12对QTL或标记区间存在上位性互作效应;qPF-1-1、qPF-2-1、qPF-6-2、qPV-1-1、qPV-6-1、qPR-1-1、qPR-6-1和qPR-6-2 8个QTL利用F2:3群体也定位到,qPF-2-1和qPV-6-1 QTL利用BC2F2群体也定位到,具有世代稳定性。
     4、3种环境条件下及合并分析共检测到87个与8个穗粒性状相关的QTL,单个QTL的贡献率为3.93%~24.59%,其中qGW-10-1、qGWP-4-1、qGWP-4-2、qGWP-10-1、q100GW-1-1、q100GW-5-1、q100GW-7-1、qEL-1-1、qEL-1-2、qED-1-1、qERN-4-1、qERN-9-1和qKR-4-1 13个QTL在3种环境或两种环境条件下及合并分析均被检测到,具有环境稳定性,39个QTL的贡献率大于10%;35对QTL或标记区间存在上位性互作效应;q100GW-5-1、q100GW-7-1、qEL-3-1、qED-10-2、qERN-4-1和qERN-10-1 6个QTL利用F2:3群体也定位到,q100GW-5-1、qEL-3-1和qED-10-1 3个QTL利用BC2F2群体也定位到,q100GW-5-1和qEL-3-1 QTL利用F2:3和BC2F2群体均定位到,具有世代稳定性,q100GW-5-1同时具有环境和世代稳定性。
     5、3种环境条件下及合并分析共检测到52个与4个籽粒营养品质相关的QTL,单个QTL的贡献率为4.10%~16.80%,其中qCP-3-1、qCP-4-1、qCT-3-1、qCT-4-1、qCT-5-2、qCT-9-1、qCF-1-1和qLS-3-1和8个QTL在3种环境或两种环境条件下及合并分析均被检测到,具有环境稳定性,16个QTL的贡献率大于10%;18对QTL或标记区间存在上位性互作效应; qCP-4-1、qCP-6-1、qCT-3-1和qCT-4-1 4个QTL利用F2:3群体也定位到,qCP-6-1、qCT-3-1和qCF-7-2 3个QTL利用BC2F2群体也定位到,qCP-6-1和qCT-3-1 2个QTL利用F2:3和BC2F2群体均定位到,具有世代稳定性,qCT-3-1同时具有环境和世代稳定性。
     6、3种环境条件下及合并分析共检测到180个与9个植株性状有关的QTL,单个QTL的贡献率为3.86%~28.40%,其中qSD-5-2、qPH-1-2、qPH-4-1、qPH-5-1、qPH-7-1、qPH-8-3、qEH-1-1、qEH-3-2、qEH-5-1、qEH-10-1、qTH-5-2、qTH-7-1、qTH-8-1、qTHPH-1-1、qTHPH-10-1、qLNE-5-3、qLNE-6-1、qLA-2-1、qLA-2-2、qLA-4-1、qLA-7-1、qLA-7-3、qLA-8-2、qTL-7-1、、qTL-8-2、qTB-4-1和qTB-8-1 27个QTL在3种环境或两种环境条件下及合并分析均被检测到,具有环境稳定性,66个QTL的贡献率大于10%;54对QTL或标记区间存在上位性互作效应;qPH-7-1、qPH-7-2、qPH-8-3、qPH-9-1、qEH-3-2、qTH-8-1、qTHPH-3-1、qTHPH-3-2、qLNE-3-4、qLNE-5-2、qLA-4-1、qLA-7-2、qLA-8-2、qTL-6-1和qTB-10-1 15个QTL利用F2:3群体也定位到,qPH-1-2、qPH-8-3、qTH-1-1、qTH-7-1、qTH-8-1、qTHPH-3-1、qTHPH-10-1、qTL-4-3、qTL-8-2和qTB-10-1 10个QTL利用BC2F2群体也定位到,qPH-8-3、qTH-8-1、qTHPH-3-1和qTB-10-1 4个QTL利用F2:3和BC2F2群体均定位到,具有世代稳定性,qPH-8-3、qTH-8-1和qTHPH-3-1 3个QTL同时具有环境和世代稳定性。
     7、RIL群体的各类性状间不同环境条件下呈比较一致的相关关系;3个膨爆特性指标间、百粒重与穗行数和行粒数间、株高与穗位高和顶高间以及脂肪含量与蛋白含量间均呈极显著正相关,淀粉含量与蛋白含量呈极显著负相关;对呈显著的性状进行多性状联合QTL分析,共检测到256个多性状QTL,其中新检测到131个QTL。位于多条染色体上控制相关性状的QTL存在紧密连锁或一因多效。
Popcorn is a special kind of corn type used to make popcorn flake for a series pastime foodstuff, it has unique values in the snack-food industry. Popping characteristics and grain yield are important traits in maize breeding. They are all quantitative trait controlled by multiple genes. Domestic and foreign breeders have conducted lots of researches in germplasm improvement and traditional quantitative genetics. But few researches have been done in the molecular quantitative genetics for most characters in popcorn. In this research, two hundred and fifty-eight RILs were developed from a cross between a dent corn indred, Dan232, and an elite popcorn indred, N04. A high-density genetic map was constructed using SSR markers. Three popping characteristics, 8 ear-kernel traits, 9 plant traits and 4 kernel nutritive characters were evaluated. High-density genetic maps were constructed using SSR markers. QTL analyses were conducted by composite interval mapping (CIM) method and the LOD threshold values were determined by 1000 times permutation test. The interactions of detected QTL were identified using multiple interval mapping (MIM) method according to the result obtained using CIM method. The joint QTL analysis for two or three different traits were done using composite interval mapping (CIM) of multiple traits analysis, including popping characteristics, ear-kernel characters, kernel nutritive characters, and plant characters. This research was to analyze their molecular genetic mechanism and genetic correlations among different characters. Also, stable QTL across different environments and generations could be selected by comparing with its F2:3 and BC2F2 population derived form the same parents. These results provide more reliable theoretical basis and materials for marker-assisted selection, fine mapping, map-based cloning, and other related researches in future.
     The main results in this study were as follows:
     1. Totally, 723 SSR primers were selected to screen polymorphism between two parents, N04 and Dan232, 212 markers (29.32%) were in co-dominant segregation. Two hundred and seven pairs SSR markers were selected to construct a genetic linkage map using Mapmaker 3.0 with a total genetic length of 2 408.8 cM and the average interval of 11.64 cM.
     2. Transgressive segregation were observed for three popping characters, eight ear-kernel characters, nine plant characters and four kernel nutritive characters in the RIL population except for popping fold (PF) and leaves above ear (LNE). Normal distribution was observed for all traits. The heritability of 3 popping characters, 8 ear-kernel characters, 9 plant characters and 4 kernel nutritive characters were all high, ranging from 0.90 to 0.92, 0.83 to 0.94, 0.67 to 0.93 and 0.80 to 0.96, respectively.
     3. Twenty-seven QTL were detected for 3 popping characters under three environments and in combined analysis. Phenotypic variation explained by a single QTL varied from 4.43% to 20.95%. Of these, 3 QTL (qPF-1-1、qPV-7-1 and qPR-1-1) were common under three different environments and in combined analysis, and 7 QTL explained up to 10% phenotypic variation. Digenic interactions were detected for 12 pairs of QTL or marker intervals. Eight QTL (qPF-1-1, qPF-2-1, qPF-6-2, qPV-1-1, qPV-6-1, qPR-1-1, qPR-6-1, and qPR-6-2) were also detected in the F2:3 population, two QTL (qPF-2-1 and qPV-6-1) were also detected in the BC2F2 population, which were stable between generations.
     4. Eighty-seven QTL were detected for 8 ear-kernel traits under three environments and in combined analysis, phenotypic variation explained by a single QTL varied from 3.93% to 24.59%. Of these, thirteen QTL (qGW-10-1, qGWP-4-1, qGWP-4-2, qGWP-10-1, q100GW-1-1, q100GW-5-1, q100GW-7-1, qEL-1-1, qEL-1-2, qED-1-1, qERN-4-1, qERN-9-1, and qKR-4-1) were common under three different environments and in combined analysis, and 39 QTL explained up to 10% phenotypic variation. Digenic interactions were detected for 35 pairs of QTL or marker intervals. Six QTL (q100GW-5-1, q100GW-7-1, qEL-3-1, qED-10-2, qERN-4-1, and qERN-10-1) were also detected in the F2:3 population, three QTL (q100GW-5-1, qEL-3-1, and qED-10-1) were also detected in the BC2F2 population. q100GW-5-1 was detected under 3 environments and in all populations, and qEL-3-1 was detected in 3 populations, which showed stability across environments and generations.
     5. Fifty-two QTL were detected for 4 kernel nutritive characters under three environments and in combined analysis, phenotypic variation explained by a single QTL varied from 4.10% to 16.80%. Of these, eight QTL (qCP-3-1, qCP-4-1, qCT-3-1, qCT-4-1, qCT-5-2, qCT-9-1, qCF-1-1, and qLS-3-1) were common under three or two different environments and in combined analysis, and 6 QTL explained up to 10% phenotypic variation. Digenic interactions were detected for 18 pairs of QTLs or marker intervals. Four QTL (qCP-4-1, qCP-6-1, qCT-3-1, and qCT-4-1) were also detected in the F2:3 population, three QTL (qCP-6-1、qCT-3-1, and qCF-7-2) were also detected in the BC2F2 population. qCT-3-1 was detected under 3 environments and in all populations, and qCP-6-1 was detected in 3 populations, which showed stability across environments and generations.
     6. One hundred and eighty QTL were detected for 9 plant traits under three environments and in combined analysis, phenotypic variation explained by a single QTL varied from 3.86% to 28.40%. Of these, twenty-seven QTL (qSD-5-2, qPH-1-2, qPH-4-1, qPH-5-1, qPH-7-1, qPH-8-3, qEH-1-1, qEH-3-2, qEH-5-1, qEH-10-1, qTH-5-2, qTH-7-1, qTH-8-1, qTHPH-1-1, qTHPH-10-1, qLNE-5-3, qLNE-6-1, qLA-2-1, qLA-2-2, qLA-4-1, qLA-7-1, qLA-7-3, qLA-8-2, qTL-7-1, qTL-8-2, qTB-4-1, and qTB-8-1) were common detected under three or two different environments and in combined analysis, sixty QTL explained up to 10%; Digenic interactions were detected for 54 pairs of QTL or marker intervals. Fifteen QTL (qPH-7-1, qPH-7-2, qPH-8-3, qPH-9-1, qEH-3-2, qTH-8-1, qTHPH-3-1, qTHPH-3-2, qLNE-3-4, qLNE-5-2, qLA-4-1, qLA-7-2, qLA-8-2, qTL-6-1, and qTB-10-1) were also detected in F2:3 population, ten QTL(qPH-1-2, qPH-8-3, qTH-1-1, qTH-7-1, qTH-8-1, qTHPH-3-1, qTHPH-10-1, qTL-4-3, qTL-8-2 and qTB-10-1) were also detected in BC2F2 population. qPH-8-3, qTH-8-1, qTHPH-3-1 and qTB-10-1 were detected under 3 environments and in all populations, and qPH-8-3, qTH-8-1, and qTHPH-3-1 were detected in 3 populations, which showed stability across environments and generations.
     7. Relationships between 4 kind of traits were consistent under 3 environments. Significant positive correlations were observed among 3 popping characters. 100GW was positively correlated with ERN and RKN, PH was positively correlated with EH and TH, and CF was positively correlated with CP, but CT was negatively correlated with CP. Two hundred and fifty-six QTL for correlated traits were detected by multiple traits analysis and 131 new QTL were detected. QTL for several related traits, showing pleiotroy or tight linkage, have been found on more than one chromosome.
引文
1.陈亮,楼巧君,孙宗修,邢永忠,余新桥,罗利军.水稻低温发芽力的QTL定位.中国水稻科学,2006,20(2):159-164.
    2.丁效华.作物数量性状基因图位克隆研究进展.植物遗传资源学报,2005,6(4):464-468.
    3.付家峰.玉米植株性状QTL的遗传背景和环境稳定性及其遗传相关研究.河南农业大学硕士论文,2008.
    4.方宣钧,吴为人,唐纪良.作物DNA标记辅助育种.科学出版社,2001.
    5.顾红雅,等.植物基因与分子操作[M].北京大学出版社,1995:142-150.
    6.兰进好,李新海,高树仁,张宝石,张世煌.不同生态环境下玉米产量性状QTL分析.作物学报, 2005, 31(10): 1253-1259.
    7.李玉玲,江洪勋.爆裂玉米胚乳数量性状的遗传研究.生物数学学报, 2002,17(4):435-439.
    8.李玉玲,靳永胜,薛喜梅等.爆裂玉米穗粒性状与爆裂性的关系研究.河南农业科学,l999,(5):ll-l2.
    9.李玉玲,鹿智江..爆裂玉米与普通玉米杂交后代选系的膨爆特性研究.河南农业大学学报,2000,34(3):210-212.
    10.李玉玲,吴锁伟,牛素贞,李志强,薛淑丽.爆裂玉米自交系与不同优势类群普通玉米自交系的配合力及聚类分析.河南农业大学学报,2004,38(1):5-8.
    11.李玉玲.爆裂玉米膨爆特性的遗传及杂交种研究进展.中国农学通报,2001,17(1):43-45.
    12.李玉玲.爆裂玉米种质遗传及其数量性状的分子遗传研究.河南农业大学博士论文,2005.
    13.李玉玲,牛素贞,董永彬.利用高代回交方法定位爆裂玉米膨化倍数QTL.作物学报,2007a, 33(5):831~836.
    14.李学慧,利用两个相关F2:3群体研究玉米穗粒性状QTL及粒重与籽粒品质性状遗传关系.河南农业大学硕士论文,2008.
    15.柳李旺,朱协飞,郭旺珍,张天真.分子标记辅助选择聚合棉花Rf1育性恢复基因和抗虫Bt基因.分子植物育种, 2003,1:48-52.
    16.刘宗华,汤继华,王春丽,田国伟,卫晓轶,胡彦民,崔党群.氮胁迫与非胁迫条件下玉米不同时期株高的动态QTL定位.作物学报,2007,33(5):782~789.
    17.马晓萍,王玉兰,等.爆裂玉米膨胀倍数的遗传研究.吉林农业科学,2001,26(4):9-13.
    18.梅德圣,李云昌,王汉中.作物产量性状QTL定位的研究现状及应用前景.中国农学通报,2003,19(5):83-88.
    19.莫惠栋.数量性状遗传基础研究的回顾与思考-后基因组时代数量遗传领域的挑战.扬州大学学报(农业与生命科学版),2003,24(2):24-31.
    20.沈新莲,袁有禄,郭旺珍,朱协飞,张天真.棉花高强纤维主效QTL的遗传稳定性及它的分子标记辅助选择效果.高技术通讯,2001,10:13-17.
    21.宋宪亮,孙学振,张天真.偏分离及对植物遗传作图的影响.农业生物技术学报,2006,(02):286-292.
    22.宋秀芳.玉米籽粒油分含量基因的SSR分子标记、定位及相关分析.中国农业大学博士论文,2003.
    23.汤华,严建兵,黄益勤,郑用琏,李建生.玉米5个农艺性状的QTL定位.遗传学报,2005,32(2):203-209.
    24.王连铮,戴景瑞(主编).全国作物育种学术讨论会论文集.北京:中国农业科技出版社1998:11-20.
    25.王延召.玉米籽粒品质性状QTL定位及其遗传相关研究.河南农业大学博士论文,2008.
    26.王阳,刘成,王天宇,石云素,宋燕春,黎裕.干旱胁迫和正常灌溉条件下玉米产量性状QTL分析.植物遗传资源学报,2007,8(2):179-183.
    27.王阳,刘成,王天宇,石云素,宋燕春,黎裕.干旱胁迫和正常灌溉条件下玉米产量性状QTL分析.2007,植物遗传资源学报,2007,8(2):179-183.
    28.向道权,曹海河,曹永国,等.玉米SSR遗传图谱的构建及产量性状基因定位.遗传学报, 2001,28(8):778-784.
    29.向道权.玉米遗传图谱的构建及产量性状基因定位.中国农业大学博士研究生论文,2001.
    30.邢永忠,徐才国,华金平,谈移芳,孙新立.水稻株高和抽穗期基因的定位和分离.植物学报,2001,43(7):721-726.
    31.邢永忠,徐才国.作物数量性状基因研究进展.遗传,2001,23(5):498-502.
    32.徐云碧.分子数量遗传学.北京:中国农业大学出版社,1994.
    33.严建兵,汤华,黄益勤,郑用琏,李建生.玉米F2群体分子标记偏分离的遗传分析.遗传学报,2003, 30: 913-918.
    34.杨俊品,荣廷昭,向道权,唐海涛,黄烈健,戴景瑞.玉米数量性状定位.作物学报,2005,31(2):188-196.
    35.杨晓军,路明,张世煌,周芳,曲延英,谢传晓.玉米株高和穗位高的QTL定位.遗传,2008,(11):1477-1486.
    36.于永涛,张吉民,石云素,宋燕春,王天宇,黎裕.利用不同群体对玉米株高和叶片夹角的QTL分析.玉米科学,2006,14(2):88~92.
    37.张晓国,刘玉乐,康良仪,朱英国,田波.水稻花药特异表达基因启动子的扩增及克隆.武汉大学学报(自然科学版) ,1997, 43(4),480-484.
    38.张志明,赵茂俊,荣廷昭,潘光堂.玉米SSR连锁图谱构建与株高及穗位高QTL定位.作物学报,2007,33(2):341-344.
    39.章元明.作物QTL定位方法研究进展.科学通报,2006,51(19):2223-2231.
    40.赵洪波,李明丽,鲁绍雄,连林生,李国治.群体规模和性状遗传力对F2设计下QTL定位效果的影响.云南农业大学学报(自然科学版),2007,22(2):159-163
    41.赵永锋.玉米单片段导入系群体的构建及QTL鉴定初探.河北农业大学博士论文,2006.
    42.郑祖平,黄玉碧,田孟良,谭振波.不同供氮水平下玉米株型相关性状的QTLs定位和上位性效应分析.玉米科学,2007,15(2):14-18.
    43.周晓果,张正斌.作物数量性状基因座定位及分析研究进展.西北植物学报,2005,25(3):625-630.
    44.朱军.复杂数量性状基因定位的混合线性模型方法.王连铮,戴景瑞(主编):全国作物育种学术讨论会论文集.北京:中国农业科技出版社,1998.
    45.朱成松,王付华,王建飞,李广军,张红生,章元明.回交、DH和RIL偏分离群体遗传图谱的重新构建.科学通报,2007,52(8):918-922
    46. Alpert K B, Tanksley S D. High~resolution mapping and isolation of a yeast artificial chromosome contig containing fw2.2: A major fruit weight quantitative trait locus in tomato.Proc Natl Acad Sci USA, 1996, 93: 15503-15507.
    47. Ashman R B. Popcorn, Purdue University, Cooperative Extension Service, Plant Disease Control, Bulletin. 1983, BP-4.
    48. Austin D F, Lee M, Veldboom L R, Hallauer A R. Genetic mapping in maize with hybrid progeny across testers and generations: grain yield and grain moisture. Crop Sci, 2000, 40: 30-39.
    49. Austin D F, Lee M, Veldboom L R. Genetic mapping in maize with hybrid progeny across testers and generations: plant height and flowering. Theor Appl Genet, 2001, 102: 163-176.
    50. Austin D F, Lee M. Detection of quantitative trait loci for grain yield and yield components in maize across generations in stress and nonstress environments. Crop Sci, 1998, 38: 1296-1308.
    51. Austin D F, Lee M. Genetic resolution and verification of quantitative trait loci for flowering and plant height with recombinant inbred lines of maize. Genome, 1996, 39 (6):957-968.
    52. Babu.R., Nair S.K.,Kumar A.,Rao H.S. et al. Mapping QTLs for popping ability in a popcorn×flint corn cross. Theor Appl Genet, 2006: 1392-1399
    53. Beavis W D, Smith O S, Grant D, Fincher R. Identification of quantitative trait loci using a small sample of topcrossed and F4 progeny from maize. Crop Sci, 1994, 34: 882-892.
    54. Bernacchi D, T Beck-Bunn, Y Eshed, J Lopez, V Petiard, J Uhlig, D Zamir & S Tanksley, 1. Advanced backcross QTL analysis of tomato.I. Identification of QTLs for traits of agronomic importance from Lycopersicon hirsutum. Theor. Appl. Genet. 1998, 97: 381-397.
    55. Brondani C, Rangel P,Brondani R,Ferreira M.QTL mapping and introgression of yield-related traits from Oryza glumaepatulato to cultivated rice (Oryza sativa) using microsatellite markers. Theor Appl Genet, 2002.104: 1192-1203
    56. Chee P W, Elias E M, Anderson J A, Kianian S F. Evaluation of a High Grain Protein QTL from Triticum turgidum L. var. dicoccoides in an Adapted Durum Wheat Background. Crop Sci, 2001, 41: 295 - 301.
    57. Chuck G, RobbinsT,Nijjar C,et al. Tagging and cloning of a petunia flower color gene with the maize transposable element activator. Plant Cell, 1993, 5:371-378.
    58. Churchill GA, and Doerge RW. Empirical threshold values for quantitative trait mapping. Genetics, 1994, 138: 963-971.
    59. Clark D, Dudley J W, Rocheford T R, LeDeauxb J R. Genetic analysis of corn kernel Chemical composition in the random mated 10 generation of the cross of generations 70 of IHO×ILO. Crop Sci, 2006, 46: 807-819.
    60. Clary G.A. study of the inheritance of expansion in popcorn [Disertation], Purdue West Lafayette, IN, 1954
    61. Coe E H, Polacco M. Gene list and working maps. Maize Genet Coop Newslet, 1995, 694: 157-191
    62. DeVicente M.C and Tanksley S.D.QTL Analysis of Transgressive Segregation in an Interspecific Tomato Cross. Genetics 1993 134: 585-596.
    63. Dholakia BB, Ammiraju SS, Lagu MD , R?der MS , Rao VS, Dhaliwal HS, Ranjekar PK, Gupta VS.Molecular marker analysis of kernel size and shape in bread wheat. Plant Breeding, 2003,122: 392-397.
    64. Doebley J, Bacigalupo A, Stec A . Inheritance of kernel weight in two maize-teosinte hybridpopulations: implications for crop evolution. Journal of Heredity, 1994, 85:191-195.
    65. Doebley J, Stec A, Gustus C. Teosinte branched1 and the origin of maize: Evidence for epistasis and the evolution of dominance. Genetics, 1995, 141: 333-346.
    66. Doebley J, Stec A, Hubbard L. The evolution of apical dominance in maize. Nature, 1997, 386: 485-488.
    67. Doffing S M,NoraD, Croz-Mason,Thomas-compton.M A.Inheritance of expansion volume and yield in two dent corn×popcorn crosses.Crop Sci,1991,31(2): 715-718
    68. Dofing, S.M., Thomas-Compton, M.A.; Buck, J.S. Genotype x popping method interaction for expansion volume in popcorn. Crop Science, 1990, 30: 62-65.
    69. Dorweiler J, Stec A, Kermicle J, Doebley J. Tesominte glume architecture I. A genetic locus controlling a key step in maize evolution. Science, 1993, 262: 233-235.
    70. Dudley J W, Clark D, Rocheford T R, LeDeaux J R. Genetic analysis of corn kernel chemical composition in the random mated 7 generation of the cross of generations 70 of IHP×ILP. Crop Sci, 2007, 47: 45-57.
    71. Dudley JW. Molecular markers in plant improvement: manipulation of genes affecting quantitative traits. Crop Sci., 1993, 33: 660-668.
    72. Fedoroff NV, Furtek DB, Nelson OJ. Cloning of bronze locus in maize by a simple and generalizable procedure using the transposable controlling element activator (AC). Proc Natl Acad Sci USA, 1984,81: 3825-3829.
    73. Flint-Garcia SA. Jampatong C, Darrah LL and McMullen MD.Quantitative Trait Locus Analysis of Stalk Strength in Four Maize Populations. Crop Sci. 43: 13–22 (2003).
    74. Frary A, Nesbitt T C, , Grandillo S, Knaap E, Cong B, Liu J P, Mellor J, Elber R , Alpert K B, Tanksley S D. fw2.2:a quantitative trait locus key to the evolution of tomato fruit size. Science, 2000, 289: 85-88.
    75. Frary A, Nesbitt TC, Grandillo S, Knaap E, Cong B, Liu J, Meller J, Elber R, Alpert KB, Tanksley SD.fw2.2: a quantitative trait locus key to the evolution of tomato fruit size.Science, 2000, 289(5476): 85-88
    76. Fullon TM, T Beck-Bunn, D Emmatty,et al. QTL analysis in an advanced backcross of Lycopersicon peruvianum to the cultivated tomato and comparisons with QTLs found in other wild species. Theor Appl Genet. 1997, 95: 881-894.
    77. Fullon TM, Grandillo S, Beck-Bunn T, Fridman E,et al.Advanced backcross QTL analysis of a Lycopersicon esculentum x L. parviflorum cross. Theor Appl Genet, 2000, 100: 1025-1042.
    78. Gao M, Chibbar RN. Isolation, characterization and expression analysis of starch synthase II a cDNA from wheat (Triticumaes tivumL). Genome, 2000, 43: 768-775
    79. Giraudat J, Hauge BM, Valon C, et al. Isolation of the Arabidopsis ABI3 gene by positional cloning. Plant Cell, 1992, 4: 1251-1261.
    80. Goldman, I.L., T.R. Rocheford, and J.W. Dudley. Quantitative trait loci influencing protein and starch concentration in the lllinois Long Term Selection maize strains. Theor Appl Genet, 1993, 87: 217-224.
    81. Hill W G. Selection with recurrent backcrossing to develop co-genic lines for quantitative trait loci analysis. Genetics, 1998, 148: 1341-1352.
    82. Hospital F, and Charcosset A. Marker-assisted introgression of quantitative trait loci. Genetics, 1997, 147: 1469–1485.
    83. Huang N, Angeles ER, Domingo J, et al. Pyramiding of bacterial blight resistance genes in rice marker assisted selection using RFLP and PCR. Theor Appl Genet, 1997, 95: 313-320.
    84. Jansen R C. Interval mapping of multiple quantitative trait loci. Genetics, 1993, 135: 205-211.
    85. Kao C H, Zeng Z B, Teasdale R D. Multiple interval mapping for quantitative trait loci. Genetics, 1999, 152: 1203-1216.
    86. Keim P, Diers BW, Olson TC, Shoemaker RC. RFLP mapping in soybean: Association between marker loci and variation in quantitative traits. Genetics, 1990, 126: 735-742
    87. Knapp SJ, Stroup WW, Ross WM. Exact confidence intervals for heritability on progeny mean basis. Crop Science, 1985, 25: 192-194.
    88. Kojima S, Takahashi Y, Kobayashi Y, Monna L, Sasaki T, Araki T, Yano M. Hd3a, a rice ortholog of the Arabidopsis FT gene, promotes transition to flowering downstream of Hd1 under short-day condition. Plant Cell Physiol, 2002, 43: 1096-1105.
    89. Lander E S, Botstein D. Mapping Mendelian factors underlying quantitative traits using RFLP likage maps. Genetics, 1989, 121(1): 185-199.
    90. Lander ES, Botstein S. Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics, 1989, 121: 185-199.
    91. Laurie C C, Chasalow S D, LeDeaux J R, McCarroll R, Bush D, Hauge B, Lai C, Clark D, Rocheford T R, Dudley J W. The genetic architecture of oil concentration in the maizekernel after 70 generations of divergent selection. Genetics, 2004, 168: 2141-2155.
    92. Lee M. DNA markers in plant breeding programs. Adv. Agron., 1995, 55: 265-344.
    93. Li D D, Pfeiffer T W, Cornelius P L. Soybean QTL for yield and yield components associated with Glycine soja Alleles. Crop Sci., 2008, 48: 571- 581.
    94. LI Yu-Ling, DONG Yong-Bin, NIU Su-Zhen. QTL analy-sis of popping fold and the consistency of QTLs under two environments in popcorn. Acta Genetica Sinica, 2006, 33 (8): 724-732.
    95. Liu Yanyang, Dong Yongbin, Niu Suzhen, Cui Dangqun, Wang Yanzhao, Wei Mengguan, Li Xuehui, Fu Jiafeng, Zhang Zhongwei, Chen Huangqing, Li Yuling* (Corresponding author). QTL identification of kernel composition traits with popcorn using both F2:3 and BC2F2 populations developed from the same cross. Journal of Cereal Science, 2008a, 48: 625-631.
    96. Y. L. Li, S. Z. Niu, Y. B. Dong, D. Q. Cui, Y. Z. Wang, Y. Y. Liu, M. G. Wei. Identification of trait-improving quantitative trait loci for grain yield components from a dent corn inbred line in an advanced backcross BC2F2 population and comparison with its F2:3 population in popcorn. Theoretical and Applied Genetics, 2007c, 115: 129-140.
    97. Y. L. Li, Y. B. Dong, S. Z. Niu and D. Q. Cui. Identification of QTL for popping characteristics using a BC2F2 population and comparison with its F2:3 population in popcorn. Agricultural Sciences in China, 2009, 8(2): 137-143.
    98. Y. L. Li, Y. B. Dong, S. Z. Niu and D. Q. Cui. QTL for popping characteristics in popcorn. Plant Breeding, 2007b, 12: 509-514.
    99. Yuling Li, Yongbin Dong, Suzhenniu Niu, Dongqun Cui, Yanzhao Wang, Yanyang Liu, Mengguan Wei, Xuehui Li. Identification of agronomically favorable quantitative trait loci alleles from a dent corn inbred Dan232 using advanced backcross QTL analysis and comparison with the F2:3 population in popcorn. Molecular Breeding, 2008b, 21: 1-14.
    100. Li Z K, Luo L J, Mei H W, Shu Q Y. Overdominant epistatic loci are the primary geneticbasis of inbreeding depression and heterosis in rice.Ⅱ. grain yield components. Genetics, 2001, 158: 1755-1771.
    101. Lorieux M, Go net B, Perrier X, Gonzalez D de L and Lanaud C. Maximum—likelihood models for ma pping genetic markers showing segregation distortion.1.Backcross populations. Theor Appl Genet, 1995-90: 73-80.
    102. LorieuxM, Perrier x’GoffinetB, LanaudC and GonzalezD de L.Max imum—likelihood modles for mapping genetic markers showing segregation distortion.2.F2 populations. Theor Appl Genet, 1995b, 90: 81-89.
    103. Lu H, Bernardo J, Ohm H W. Mapping QTL for popping expansion volume in popcorn with simple sequence repeat markers. Theor Appl Genet, 2003, 106 (3): 423-427
    104. Lu H, Romero-Severson J, Bernardo R. Chromosomal regions associated with segregation distortion in maize. Theor Appl Genet, 2002, 105: 622-628
    105. Lubberstedt Thomas, Albrecht E.Melchinger, Chris C.Schon, H.F. Utz, and D.Klein. QTL Mapping in Testcrosses of European Flint Lines of Maize:1.Comparison of Different Testers for Forage Yield Traits. Crop Sci, 1997, 37: 921-931.
    106. Luo L J, Li Z K, Mei H W, Shu Q Y, Tabien R, Zhong D B, Ying C S, Stansel J W, Khush G S, Paterson A H. Overdominant epistatic loci are the primary genetic basis of inbreeding depression and heterosis in rice.II.Grain yield components. Genetics, 2001, 158: 1755-1771.
    107. Luo Z W, Wu C I, Kearsey M J. Precision and high-resolution mapping of quantitative trait loci by use of recurrent selection, backcross or intercross schemes. Genetics, 2002, 161: 915-929.
    108. Mangelsdorf P C, Jones D F. The expression of Mendelian factors in the gametophyte of maize. Genetics, 1926, 11: 423-455
    109. Mei H W, Luo L J, Ying C S, Wang Y P, Yu X Q, Guo L B, Paterson A H, Li Z K. Gene actions of QTLs affecting several agronomic traits resolved in a recombinant inbred rice population and two testcross populations. Theor Apple Genet, 2003, 107: 89-101.
    110. Melchinger A E, Utz H F, Sch?n C C. Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects. Genetics, 1998, 149: 383-403.
    111. Moncada P, Martinez CP, Borrero J, Chatel M, Gauch H.et al. Quantitative trait loci for yield and yield components in an Oryza sativa x Oryza rufipogon BC2F2 population evaluated in an upland environment. Theor Appl Genet, 2001, 102: 41-52.
    112. Murigneux A,Baud S and Beckert M. Molecular and morphological evaluation of doubled-haploid lines in maize.2.Comparison with single-seed descent lines. Theoretical Applied Genetics, 1993, 87: 278-287.
    113. Nelson JC, Sorrells ME, Van Deynze AE, Lu YH. Molecular mapping of wheat: major genes and rearrangements in homoeologous group 4, 5 and 7. Genome, 1995, 141: 721-731.
    114. Paterson A H, Lanter E S, Hewitt J D, Peterson S, Lincoln S E, Tanksley S D. Resolution of quantitative trait loci into Mendelian factors by using a linkage map of RFLP. Nature, 1988, 335: 721-726.
    115. Piepho H P. A quick method for computing approximate thresholds for quantitative trait loci detection. Genetics, 2001, 157: 425-432.
    116. Robbins W A, Asherman R B. Parent-offsping popping expansion correlations in progeny of dent corn×popcorn and flint corn×popcorn crosses. Crop Sci, 1984, 24 (1): 119-121
    117. Saghai Maroof M A, Soliman K M, Jorgensen R A, et al. Ribosomal DNA spacer-length polymorphisms in barley: Mendelian inheritance, chromosomal location, and population dynamics[J]. Proc. Natl. Acad. Sci. USA, 1984, 81: 8014-8018.
    118. Sandbrink J M,Oijen J M Van,Purimahua C C,Vrielink M,Verkerk R and Lindhout P.Localization of genes for bacterial resistance in Lycopersicon peruvianum using RFLPs. Theor Appl Genet, 1995, 90: 444- 450
    119. Sax K. The association of size differences with seed-coat pattern and pigmentation in Phaseolus vulgaris. Genetics, 1923, 8: 552-560.
    120. Soller M, Beckmann J S. 1990. Marker-based mapping of quantitative trait loci using replicated progenies. Theor Appl Genet, 1990, 67: 25-33.
    121. Stuber C.W., Mapping and maniqulating quantitative traits in maize, Trends Genet., 1995, 11: 477-481.
    122. Tanabe Sumiyo, Ashikari Motoyuki, Fujioka Shozo et al. A Novel Cytochrome P450 Is Implicated in Brassinosteroid Biosynthesis via the Characterization of a Rice Dwarf Mutant, dwarf11, with Reduced Seed Length. Plant Cell 2005, 17: 776-790.
    123. Tang J H, Ma X Q, Teng W T, Yan J B, Wu W R, Dai J R, Li J S. Detection of quantitative trait loci and heterotic loci for plant height using an immortalized F2 population in maize. Chinese Science Bulletin, 2006, 51: 2864-2869.
    124. Tanksley S D, Medina Hilho H, Rick C M. Use of naturally occurring enzyme variation to detect and map gene controlling quantitative traits in an interspecific backcross of tomato. Heredity, 1982, 49: 11-25.
    125. Tanksley SD & JC Nelson, Advanced backcross QTL analysis. A method for the simultaneous discovery and transfer of valuable QTLs from unadapted germplasm into elite breeding lines. Theor. Appl. Genet, 1996, 92: 191-203.
    126. Tanksley SD, Ganal MW, Prince JP, et al. High density molecular linkage map of the tomato and potato genomes. Genetics, 1992, 132: 1141-1160
    127. Tanksley S D. Mapping polygenes. Annu Rev Genet, 1993, 37: 205-233.
    128. Tanksley SD, Young ND, Paterson AH & Bonierbale MW. RFLP mapping in plant breeding: new tools for an old science. Bio/Technology, 1989, 7: 257-264.
    129. Thornsberry J M, Goodman M M, Doebley J, Kresovich S, Nielsen D, Buckler E S. Dwarf8 polymorphisms associate with variation in flowering time. Nature Genetics, 2001, 28: 286-289.
    130. Veldboom L R, Lee M. Genetic mapping of quantitative trait loci in maize in stress and nonstress environments:Ⅰ. Grain yield and yield components. Crop Sci., 1996, 36:1310-1319
    131. Veldboom L R, Lee M. Genetic resolution and verification of quantitative trait loci for flowering and plant height with recombinant inbred lines of maize. Genome, 1996, 39: 957-968.
    132. Veldboom L R,Lee M.Genetic mapping of quantitative trait loci in maize in stress and non-stress environments:I.grain yield and yield components[J]. Crop Sci. 1996, 36: 1310-1319.
    133. Veldboom, L.R.and M. Lee. Molecular-marker-facilitated studies of morphological traits in maize.2.Determination of QTLs for grain yield and yield components. Theor Appl Genet, 1994, 89: 451-458.
    134. Wang S, C.J.Basten, and Z-B. Zeng. Windows QTL Cartographer2.5 Department of Statistics, North Carolina State University, Raleigh, NC, 2006.
    135. Wang S, C.J.Basten, and Z-B.Zeng. Windows QTL Cartographer2.5 Department of Statistics, North Carolina State University, Raleigh, NC, 2006.
    136. Wang X, Le Roy L, Nicodeme E, Li R, Wagner R, Petros C, Churchill G A, Harris S, Darvasi A, Kirilovsky J, Roubertoux P L, Paigen B. Using advanced intercross lines for high-resolution mapping of HDL cholesterol quantitative trait loci. Genome Re-search, 2003, 13(7): 1654-1664.
    137. Wassom J, Wong J, Martinez E, King J, Debaene J, Hotchkiss J, Mikkilenini V and Rocheford T. QTL associated with maize kernel composition and related traits among Illinois High Oil×B73 backcross-derived lines. Theor Appl Genet, 2004, in press.
    138. Weaver B L, Thompson A E. Fifteen generations of selection for improved popping expansion in white hulless popcorn. Ill Agric Exp Stn Bull, 616, 1, 1957.
    139. Weller, J. I. Maximum likelihood techniques for the mapping and analysis of quantitative trait loci with the aid of genetic markers. Biometrics, 1986, (42), 627-640.
    140. XIAO, J., J.LI, S.GRANDILLO, S.N.AHN,and L.YUAN.et al.. Identification of trait-improving quantitative trait loci alleles from a wild rice relative, Oryza rufipogon. Genetics, 1998, 150: 899-909.
    141. Yamamoto T, Kuboki Y, Lin S Y. Fine mapping and characterization of quantitative trait loci of heading date in rice. 1996,Abstract for Plant Genome, IV: 57.
    142. Yan J B, Tang H, Huang YQ, Zheng YL, Li JS. Quantitative trait loci mapping and epistatic analysis for grain yield and yield components using molecular markers with an elite maize hybrid. Euphytica, 2006, 149: 121-131.
    143. Yano M, Katayose Y, Ashikari M, Yamanouchi U, Monna L, Fuse T, Tomoya Baba T, Yamamoto K, Umehara Y, Nagamura Y, Sasaki T. Hd1, a major photope riod sensitivity quantitative trait locus in rice, is closely related to the arabidopsis flowering time gene constans. Plant Cell, 2000, 12: 2473-2484.
    144. Yano M, Sasaki T. Genetic and molecular dissection of quantitative traits in rice. Plant Mol Biol, 1997, 35: 145-153.
    145. Yoshimura S, Yoshimura A, Iwata N, et al. Tagging and combining bacterial blight resistance genes in rice using RAPD and RFLP markers. Mol. Breeding, 1995,1: 375-387.
    146. Zeng Z B. Precision mapping of quantitative trait loci. Genetics, 1994,136: 1457-1468.
    147. Zhou WC, Kolb FL, Bai GH, Domier LL, Boze LK, Smith NJ.Validation of a major QTL for scabresistance with SSR markers and use of marker-assisted selection in wheat.Plant Breeding, 2003, 122: 40-44.

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