【作者】 张中伟；

【导师】 李玉玲；

【作者基本信息】 河南农业大学 ， 作物遗传育种， 2009， 硕士

【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。更多还原

【Abstract】 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.更多还原