【作者】 魏蒙关；

【导师】 李玉玲；

【作者基本信息】 河南农业大学 ， 作物遗传育种， 2009， 博士

【摘要】 玉米秸秆具有丰富的粗纤维,能值高,是我国北方反刍动物的主要粗饲料。我国每年生产玉米秸秆副产品1 500亿公斤,改良秸秆产量和品质对提高玉米生产的综合经济和社会效益,具有重要的现实和长远意义。高油玉米双重的优良籽粒和秸秆品质,使其具有更高的利用价值和更广阔的市场发展前景。以往利用普通玉米种质对部分秸秆产量和品质性状开展了QTL定位研究,利用高油玉米种质进行的相关研究局限于籽粒品质和穗粒性状。本研究选用具有ASK种质背景的高油玉米自交系GY220为父本,同时与两个普通玉米自交系8984和8622杂交构建了分别包含284个(P1F_2:3)和265个(P2F_2:3)F_2:3家系的两个相关群体,同时在两种环境条件下进行田间试验,利用SSR分子标记构建高密度遗传图谱,采用复合区间作图法（CIM）对13个秸秆产量和品质性状进行单个性状的QTL定位和效应分析;利用多区间作图法（MIM）分析定位QTL间的上位效应;对秸秆及其相关籽粒和植株性状进行多性状联合QTL分析;利用BioMercator 2.1软件整合遗传图谱,并采用元分析方法进行“一致性”QTL分析,以探讨秸秆产量和品质性状的分子遗传基础及其与籽粒产量、籽粒品质和植株性状间的遗传关系,同时筛选控制主要秸秆性状的稳定主效QTL及其有效的分子标记,为改良秸秆产量和品质性状的杂交种选育、MAS和关键QTL的精细定位及克隆提供理论依据和材料平台。主要实验和研究结论如下:1.两个F_2:3家系群体13个秸秆性状均存在超双亲分离;P1F_2:3群体3个性状和P2F_2:3群体6个性状呈偏态分布,其余性状均呈连续正态分布;联合方差分析结果表明,大多数秸秆性状的家系间、环境间及家系与环境互作显著或极显著;鲜秸秆产量（FSY）、秸秆粗蛋白含量（CPC）、体外干物质消化率（IVDMD）和中性洗涤纤维含量（NDF）的遗传力较高,为0.781⁰.917,而半纤维素含量（HCC）和体外细胞壁消化率（IVNDFD）的遗传力较低,为0.046⁰.427。2.两个F_2:3家系群体在两种环境条件下及两种环境合并分析共检测到144个与13个秸秆性状相关的QTL,P1F_2:3和P2F_2:3群体分别检测到70个和74个QTL,位于全部10条染色体上,单个QTL贡献率分别为4.8%²0.1%和5.1%²0.4%;定位QTL间互作较少,而且效应较小;表现为加性、部分显性、显性和超显性的QTL为10个、41个、20个和73个,超显性和部分显性效应在玉米秸秆性状的遗传中起着重要作用;高油玉米亲本自交系GY220提供了54.2% IVDMD和IVNDFD QTL的增效基因和64.0% ADF和NDF QTL的减效基因,两个普通玉米亲本自交系提供了77.8% FSY和57.1% DMY QTL的增效基因。3.秸秆产量和品质性状QTL的遗传背景和环境稳定性较低。两个群体没有在相同标记区间检测到控制同一性状的共同QTL,仅在相邻标记区间检测到与FSY、CPC（3个）和IVNDFD相关的QTL,分别位于3.06-3.07,2.04、7.04、7.04-7.05和4.08-4.09 bin位点,在相同bin位点9.03和5.03检测到控制粗脂肪含量（EEC）和粗蛋白产量（CPY）的QTL;86个QTL仅在一种环境条件下被检测到,占75.4%;26个QTL在两种环境条件下或一种环境条件下及合并分析同时被检测到,占22.8%;仅2个QTL在两种环境条件下及合并分析同时被检测到,占1.8%。在49个贡献率大于10%的QTL中,qlFSY1-5-1/qFSY1-5-1、qlDMC2-3-1/qDMC2-3-1、qlCPC1-7-1/qCPC1-7-2、qlCPC1-7-2/qCPC1-7-3、qlCPC2-5-1/ qxCPC2-5-1/qCPC2-5-1、qxCPC2-5-2/qCPC2-5-2和qlIVNDFD2-1-2/qxIVNDFD2-1-1/ qIVNDFD2-1-1具有环境稳定性,可以作为进一步研究和应用于MAS的主要目标QTL。4.两个群体在不同环境条件下3组秸秆产量性状间、13组秸秆品质性状间、6组秸秆产量与品质性状间,以及秸秆CPC与籽粒蛋白质含量、株高（PH）和穗位高（EH）,FSY和秸秆干物质产量（DMY）与PH和EH呈比较一致的显著相关关系。其中ADF与NDF和IVDMD与IVNDFD呈极显著正相关,IVDMD和IVNDFD与ADF和NDF呈极显著负相关;FSY和秸秆干物质含量（DMC）与ADF和NDF呈极显著负相关。5.多性状联合QTL分析可以明显提高相关性状的QTL检测功效,对18组显著正相关性状和12组显著负相关性状进行联合QTL分析,涉及3个秸秆产量、7个秸秆品质、1个籽粒品质和3个植株性状共15个性状,共检测到1004个多性状QTL,其中新检测到674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。6.两个群体的整合遗传图谱总长度2 388.67 cM,包括274个SSR标记,平均间距8.72 cM。13个秸秆性状的144个QTL和32个秸秆、植株、籽粒品质和穗粒性状的465个QTL分别检测到13个和42个“一致性”QTL,控制相关性状的QTL在染色体上多成簇分布,植株与秸秆产量性状、秸秆品质与籽粒品质和穗粒性状QTL多位于同一“一致性”QTL区段。第7、3和5染色体是秸秆性状QTL分布热点染色体,第5染色体98.85 cM、第3染色体197.03 cM和第7染色体114.33 cM可能存在控制秸秆性状的关键真实QTL。7.秸秆CPC是最主要的秸秆品质性状,与多个主要秸秆产量和品质及籽粒品质和植株性状显著相关,其中与FSY、IVDMD、IVNDFDD和籽粒蛋白质含量呈显著正相关,与DMC、ADF、NDF、PH和EH呈显著负相关。多性状联合QTL分析结果表明,位于多条染色体上控制这些相关性状的QTL存在紧密连锁或/一因多效。综合考虑秸秆性状育种目标和各性状间的遗传关系,在显著提高秸秆产量的同时难以改良秸秆品质,可以对籽粒蛋白质含量或秸秆CPC实施正向MAS改善秸秆品质,通过种植大群体提高秸秆产量。更多还原

【Abstract】 Maize stover with rich crude fiber and high energy, is the main coarse forage for ruminant animal in northern china. In china, 150 billion kilograms of maize stover was produced annually. Improving maize stover yield and quality traits has important role in increasing economic benefits and social effects in maize production. High-oil corn has high commercial value and broad developmental prospects owing to its advantages in both kernel nutritional quality and stover quality. Previous researches about QTL mapping for several stover yield and quality traits have been conducted with normal maize germplasms, but such researches using high-oil maize were only limited on grain quality and ear-kernel traits. In this study, an elite high-oil maize inbred line GY220 developed from ASK germplasms was crossed with two elite dent maize inbred lines 8984 and 8622 to generate two connected F2:3 populations （P1F2:3 and P2F2:3）. High-density genetic maps were constructed using SSR markers. The field experiments were conducted under two different environments, at Luoyang in spring and at Xuchang in summer. QTL analyses for 13 stover yield and quality traits were conducted by composite interval mapping （CIM） method. The interactions between detected QTL were analysis by multiple interval mapping （MIM） method. Joint QTL analysis were done using CIM method of multiple traits analysis among stover traits, and stover traits with their significantly related grain quality traits, ear-kernel traits, and plant traits, respectively. An intergrated map was constructed and consensus QTLs were identified using meta-analysis method in Biomercator 2.1. Our first objective was to reveal the molecular genetic mechanism of stover yield and quality traits, and the genetic relationship among stover traits and between them with other traits. The second objective was to identify major QTL for stover traits and their effective linked markers. These results will do great help in breeding for stover yield and quality traits, and in MAS, fine mapping, and map-based cloning for major QTL. The main results were as follows:1. Transgressive segregation was observed for all 13 stover traits in the two F2:3 populations. Normal distribution was observed for most traits except for 3 traits in P1F2:3 population and 6 traits in P2F2:3 population. Joint analysis of variance showed that F2:3 family lines, environments and the interactions between genotype and environment for most traits were all significant or highly significant. Heritabilities for fresh stover yield （FSY）, crude protein content （CPC）, in vitro dry matter digestibility （IVDMD） and neutral detergent fiber （NDF） were relatively high, ranging from 0.781 to 0.917, while those for hemicellulose concentration （HCC） and in vitro cell wall digestibility （INNDFD） were low, from 0.046 to 0.427.2. Totally, one hundred and forty four QTL were detected for 13 stover traits in the two F_2:3 populations under two environments and in combined analysis. 70 and 74 QTL were detected in P1F_2:3 population and P2F_2:3 populations, respectively. They were located on all ten chromosomes. Phenotypic variation explained by a single QTL varied from 4.8% to 20.1% in P1F_2:3 population and from 5.1% to 20.4% in P2F_2:3 population. Limited digenic interactions among detected QTL were found, and their effects were low. The number of QTL expressing additive, partially dominant, dominant and over-dominant effects were 10, 41, 20 and 73, respectively, which reflected that partially dominance and over dominance played the most part role in the genetics of stover traits. The positive alleles of 54.2% QTL for IVDMD and IVNDFD, and the negative alleles of 64.0% QTL for ADF and NDF were contributed by the high-oil parent line GY220, and the positive alleles of 77.8% QTL for FSY, and those of 57.1% QTL for NDF were contributed by the two dent corn parent lines.3. The stability in genetic backgrounds and environments for QTL of stover yield and quality traits were low. No common marker intervals associated with the same trait was found for the two populations. Only three QTL for CPC, and each one QTL for FSY and IVNDFD were detected in adjacent marker intervals, which were located at bin 2.04, 7.04, 7.04-7.05, 3.06-3.07 and 4.08-4.09, respectively. QTL for EEC and CPY were all detected at the same bin 9.03 and 5.03. Eighty-six QTL （accounting for 75.4%） were only detected under one environment. Twenty six QTL （accounting for 22.8%） were detected under both environments or under one environment and in combined analysis. Only 2 QTL （accounting for 1.8%） were commonly detected under two environments and in combined analysis. Among the 49 QTL with phenotypic variations higher than 10%, qlFSY1-5-1/qFSY1-5-1, qlDMC2-3-1/qDMC2-3-1, qlCPC1-7-1/qCPC1-7-2, qlCPC1-7-2/qCPC1-7-3, qlCPC2-5-1/qxCPC2-5-1/qCPC2-5-1, qxCPC2-5-2/qCPC2-5-2 and qlIVNDFD2-1-2/qxIVNDFD2-1-1/qIVNDFD2-1-1 showed high stability across different environments, and they could be used as the main objective QTL in further studies and in MAS.4. Significant correlations were almost consistently observed among three pairs of stover yield traits, thirteen pairs of stover quality traits, six pairs of stover yield with quality traits, between CPC with grain protein content, PH and EH, and between FSY and DMY with PH and EH in both populations and under different environments. Significant positive correlations were observed between ADF with NDF, and between IVDMD with IVNDFD. IVDMD, IVNDFD, FSY and DMC were all negatively correlated with ADF and NDF.5. Multiple trait joint analysis could improve QTL detection for significantly correlated traits. One thousand and four multiple-trait QTL were detected for 18 pairs of positively correlated traits and 12 pairs of negatively correlated traits, including three stover yield traits, seven stover quality traits, one grain quality traits and three plant traits. Six hundreds and seventy four new QTL were detected. Those QTL for correlated traits on several chromosomes might be QTL with pleiotropy or tight linked QTL.6. The linkage length of the integrated map for the two populations was 2 388.67 cM, which included 274 SSR markers, with an average interval of 8.72 cM between adjacent markers. Thirteen and 42“consensus”QTL were detected for 144 QTL associated with 13 stover traits, and 465 QTL associated with all 32 traits （including stover traits, grain quality traits, ear-kernel traits and plant traits）, respectively. Most QTL for correlated traits were distributed on chromosomes in cluster. QTL for plant traits and stover yield traits, and for stover quality traits, grain quality traits and ear-kernel traits, were often located on chromosome regions for the same“consensus”QTL. QTL for stover traits were located on chromosomes 7, 3 and 5 in hotspot. True major QTL for stover traits might exist on three chromosome regions, 98.85 cM on chromosome 5, 197.03 cM on chromosome 3, and 114.33 cM on chromosome 7.7. CPC was the most important stover quality traits, since it was significantly correlated with several stover yield and quality traits, grain quality traits, and plant traits. CPC was positively correlated with FSY, IVDMD, IVNDFDD and grain protein content, and negatively correlated with DMC, ADF, NDF, PH and EH. Multiple trait joint QTL analysis among them reflected that their related QTL were pleiotropic or tight linked. Therefore, it was not easy to improve stover yield and quality traits simultaneously. Considering the breeding objective for stover yield and quality traits and their genetic correlations, it was very difficult to improve stove quality traits while increasing stove yield. It was possible to improve stover quality through conducting positive MAS on grain protein content or CPC, and to increase stover yield by planting large population.更多还原