玉米株高和穗位高遗传基础的QTL剖析

玉米是世界范围内具有经济重要性的作物之一.株高和穗位高是玉米育种过程中需考虑的2个重要农艺性状,对玉米产量、抗倒伏性及株型等都有较大影响.为进一步明确玉米株高和穗位高的遗传机制,本研究以B73×Zheng58的含有165个株系的F3∶4重组自交系群体为作图群体,利用覆盖玉米10条染色体189个SSR标记对株高和穗位高进行QTL定位分析.总共定位到5个株高QTL和6个穗位高QTL;这11个QTL分布在除2号和6号之外的其他8条染色体上.单个QTL表型变异贡献率的变幅为4.3%~14.2%.其中10个QTL与以前报道过的QTL的位置相近或重叠,而株高QTL(qPH04-01)是新发现的群体专一性的QTL,最靠近标记umc0371,表型变异贡献率为8.8%,是值得进一步研究和利用的位点.     

玉米营养品质性状的QTL定位

以玉米自交系201×698-3的233个F2:3家系为作图群体,利用SSR分子标记构建遗传图谱.采用随机区组设计,分别在四川雅安和德阳进行田间试验,人工套袋自交种子供性状考查,利用区间作图法进行QTL定位分析.构建了具有134对SSR标记的玉米遗传图谱,覆盖整个基因组1831.4cM,平均图距13.67cM.从16个营养品质性状中共检侧到35个QTL,其中影响蛋白质、淀粉和油份含量的有6个QTL,分别位于第1、2、4和8染色体上,单个性状的QTL为1～3个,每个QTL的作用可解释表型变异的8.1%～21.0%;控制赖氨酸等13种氨基酸含量的有29个QTL,分别位于第1、2、4、8、9和10染色体上,单个性状的QTL为1～5个,每个QTL的作用可解释表型变异的3.5%～30.1%.在本群体的营养品质性状QTL中,超显性效应起主导作用,其次为完全显性效应.     

玉米产量相关性状的QTL定位与剖析

玉米因其自身具有高产潜质而成为了当今世界最重要的粮食作物之一.玉米产量是复杂的数量性状,由许多主/微效基因控制,易受各种环境因素影响.果穗是玉米的主要收获器官,籽粒性状是玉米品质的重要体现,因此发掘玉米穗部性状和籽粒性状相关QTL对玉米的遗传改良,培育优质高产的玉米具有重要意义.本研究白刺包谷(P2)和妻染黄(P13)为亲本构建了包含152个家系的F2∶3作图群体,选择在两亲本间具有多态性的176个微卫星标记构建遗传图谱,对产量相关性状进行了单环境的QTL定位与分析.最终定位到了14个QTL,分布在除9号染色体外的其余9条染色体上,单个QTL可解释的表型变异率为4.9％～18.8％.值得注意的是,在6号染色体上的百粒重和穗行数的一致性QTL(qHKW06-1和qERN06-1)与8号染色体上的穗行数QTL(qERN08-1)是本研究中特有的,其中qERN08-1解释了12.4％的表型变异率.     

玉米产量相关性状的QTL定位与剖析（英文）

玉米因其自身具有高产潜质而成为了当今世界最重要的粮食作物之一.玉米产量是复杂的数量性状,由许多主/微效基因控制,易受各种环境因素影响.果穗是玉米的主要收获器官,籽粒性状是玉米品质的重要体现,因此发掘玉米穗部性状和籽粒性状相关QTL对玉米的遗传改良,培育优质高产的玉米具有重要意义.本研究白刺包谷(P2)和妻染黄(P13)为亲本构建了包含152个家系的F_(2∶3)作图群体,选择在两亲本间具有多态性的176个微卫星标记构建遗传图谱,对产量相关性状进行了单环境的QTL定位与分析.最终定位到了14个QTL,分布在除9号染色体外的其余9条染色体上,单个QTL可解释的表型变异率为4.9%~18.8%.值得注意的是,在6号染色体上的百粒重和穗行数的一致性QTL(qHKW06-1和qERN06-1)与8号染色体上的穗行数QTL(qERN08-1)是本研究中特有的,其中qERN08-1解释了12.4%的表型变异率.     

皖草2号RIL群体5个农艺性状的QTL定位

皖草2号是我国育成的第1个高粱和苏丹草的杂交品种,具有产量高、品质优、适应性强的特点。以皖草2号重组自交系（RIL）群体为材料,对其株高（PH）、茎粗（SD）、分蘖数（TN）、单株鲜质量（FW）和单株干质量（DW） 5个农艺性状进行了遗传分析;利用SSR分子标记,构建了皖草2号RIL群体的遗传图谱,并对株高、茎粗、分蘖数、单株鲜质量和干质量5个农艺性状进行QTL定位。结果表明：（1）RIL群体的平均株高、茎粗、分蘖数、单株鲜质量和单株干质量都位于2个亲本之间;除分蘖数外,其他4个性状呈正态分布。（2）利用147个SSR标记构建了10个连锁群的遗传图谱,总遗传距离为1 030.4 cM,标记间的平均距离为7.14 cM;进一步利用遗传图谱定位了控制5个农艺性状的QTL位点共22个,其中PH位点1个、SD位点2个、TN位点6个、FW位点7个、DW位点6个,在这22个QTL位点中,qFW-6位点贡献率最小,为3.61%;qDW-8位点贡献率最大,为34.24%。研究结果可为饲用高粱与苏丹草杂交种的分子标记辅助育种提供一定的理论参考。     

玉米株高和穗位高遗传基础的QTL剖析（英文）

玉米是世界范围内具有经济重要性的作物之一.株高和穗位高是玉米育种过程中需考虑的2个重要农艺性状,对玉米产量、抗倒伏性及株型等都有较大影响.为进一步明确玉米株高和穗位高的遗传机制,本研究以B73×Zheng58的含有165个株系的F3:4重组自交系群体为作图群体,利用覆盖玉米10条染色体189个SSR标记对株高和穗位高进行QTL定位分析.总共定位到5个株高QTL和6个穗位高QTL;这11个QTL分布在除2号和6号之外的其他8条染色体上.单个QTL表型变异贡献率的变幅为4.3%~14.2%.其中10个QTL与以前报道过的QTL的位置相近或重叠,而株高QTL(qPH04-01)是新发现的群体专一性的QTL,最靠近标记umc0371,表型变异贡献率为8.8%,是值得进一步研究和利用的位点.     

玉米穗部性状的QTL定位

以玉米自交系L26和095组配的Fz世代为定位群体,采用SSR分子标记技术构建了包括98个位点的连锁图谱,结合F2穗部性状的鉴定结果,利用复合区间作图法对秃尖长等8个穗部性状进行基因定位,共检出21个QTL.其中穗长检测到3个QTL;穗粗、穗行数分别检测到2个QTL;行粒数检测到3个QTL;轴粗检测到2个QTL;200粒质量检测到3个QTL;穗粒质量检测到6个QTL;秃尖长没有检测到QTL.检出的21个QTL中,有10个QTL的解释变异率超过了20%,表现为主效QTL效应.研究还发现,穗部性状QTL在玉米10条染色体上分布不均匀,且成簇分布.该试验中检测到的21个QTL中,有10个影响不同性状的QTL位于3个染色体区域.各个QTL位点上起增、减效作用的等位基因在亲本间分布不均匀.     

密度对不同株型玉米产量及主要农艺性状的影响

该试验选取平展型长玉13、半紧凑型东单60和紧凑型郑单958等3种株型玉米为试材,分别在39 000,48 000,57 000株/hm2等3个密度下种植,分析了种植密度对不同株型玉米籽粒产量、穗粒性状和植株性状的影响.结果表明:3个品种的玉米产量随种植密度的增加而增加,且半紧凑型东单60产量最高;随种植密度的增加,行粒数、穗长、穗粗、轴粗、穗位叶面积和千粒质量呈下降趋势;株高、穗位高和雄穗分枝数呈上升趋势;各性状受株型与密度的互作影响不大.因此,在重庆提高玉米单产的关键是选取优良的丰产品种,并合理密植.     

基于优质早籼稻品种佳辐占的遗传图谱的构建

以优质常规稻佳辐占为父本,分别以广陆矮4号和明恢86为母本,构建两个重组自交系(以下简称为“广佳”群体和“明佳86”群体).利用559对简单重复序列(SSR)引物对亲本进行多态性分析,获得佳辐占和广陆矮4号、佳辐占和明恢86亲本间有差异的引物分别201对和186对,多态率分别达35.95%和33.33%.利用这些引物构建了两张水稻遗传图谱,其中广佳图谱包含127对SSR标记,全长约1 015.7 cM,平均标记间距为8 cM;明佳86图谱包含131对SSR标记,全长约1 263.6 cM,标记平均间距为9.6 cM.遗传图谱的构建便于研究佳辐占优质性状的遗传规律、外观品质性状间的内在关系,以期为分子标记辅助选育细长、大粒、优质的水稻新品种打下基础.同时,这是两个基于重组自交系的图谱,可长期用于群体内各种性状的遗传规律分析及QTL定位.     

玉米ELM1基因的序列变异及与株型和穗部相关性状的关联分析

 玉米elm1 突变体使得光敏色素载色体合成受阻并导致光敏色素活性下降,从而使得突变体植株表现出对光的不敏感性.为研究玉米ELM1 基因序列的多态性及其与主要农艺性状之间的关联,本研究对玉米ELM1 基因在80 个自交系中进行了目标序列重测序,并与株高和穗位高2 个株型性状以及穗长、穗粗、轴粗、穗重、行粒数、穗行数和穗粒数7 个穗部性状进行关联分析.ELM1 基因在供试玉米自交系中共有85 个变异,包括73 个SNP 和12 个Indel.尽管该基因的编码区不含Indel,但15 个SNP 变异位点依然可以将编码区划分成7 种单倍型,并编码6 种ELM1 蛋白质.关联分析发现,玉米ELM1 基因中1 个非同义突变位点与穗位高存在显著关联,另有2 个非同义突变位点与行粒数存在显著关联.     

QTL mapping of resistance to sheath blight in maize（Zea mays L.）

Maize sheath blight (Rhizoctonia Solani) is a widely occurring fungus disease with great harm to corn-pro- ducing regions in the world. The first happening of sheath blight in China was reported in Jilin Province as early as in 1966[1]. Since the 1970s, the enlargement of corn- growing regions, the application of maize hybrids, the increasing use of fertilizers, especially the nitrogenous fertilizer, and a higher growth-density, all have caused a quick spread of sheath blight, the occurring …     

The comparative analysis based on maize integrated QTL map and meta-analysis of plant height QTLs

Since the first publication of quantitative trait locus (QTL) localization using molecular markers[1], a large number of QTLs have been identified in different ge- netic backgrounds and environments. Affected by many factors, such as marker sets, experime…     

Dynamic analysis of QTL for plant height at different developmental stages in maize （Zea mays L.）

Plantheightisoneofimportantagronomictraitsinmaizebreeding.Inthepastfewyears,toincreasetheplantingdensityandpreventplantsfromlodging,studiesonthegeneticmechanismofplantheightweregivengreatattentionto.Sincethe1990s,molecularmarkershaveprovidedapowerfultooltostudythetraitofplantheightatthemolecularlevel[1—3].Butmostofresearchforplantheightonlyfocusedondataatmaturestage.Tillnow,about70genesorQTLshavebeenlocated[4].Moreover,somegeneshavebeenevencloned[5—7].Duringthevege-tativegrowthperiod,plant…     

小麦株高性状的QTL定位分析

以国际小麦作图组织的重组自交系群体W7984×Opata85为材料,在两种不同试验环境(2009年天津东丽区、2009年天津西青区姚村)下,分析其亲本及114个株系群体的株高,并利用QTL作图软件WinQTLCart2.5和区间作图及复合区间作图方法,对控制小麦株高性状的QTL进行定位.共检测到4个与小麦株高相关的QT...     

Construction of a genetic map and location of quantitative trait loci for dwarf trait in maize by RFLP markers

Using F₂ population derived from the cross of tall inbred 7922 by dwarf inbred 5003, an RFLP linkage map of maize has been constructed, on which 85 markers are distributed among 10 linkage groups and span maize genome about 1827.8 cM with an average distance (24.4 cM) between markers. 106 F_2:3 lines of the population were grown in a 10 × 11 simple rectangular lattice design of one-raw plots with two replications and evaluated for plant height (PH). With interval mapping procedure, 5 QTLs controlling plant height have been identified and their genetic effects and gene action determined. 2 major QTLs with opposite effect have been discovered. One for increasing plant height isph1 which is located at chromosome 2 and accounts for 51.8% of the total phenotypic variation; the other for decreasing plant height isph3 which is located at chromosome 5 and accounts for 38.6% of the total phenotypic variation. The chromosomal location ofph3 might be the same as or close to the position ofbv1, a dwarf mutant of maize.     

Molecular dissection of genetic basis of significant correlation among five morphological traits in rice (Oryza sativa L.)

To enhance understanding of the genetic basis of trait correlation in rice, a recombinant inbred line (RIL) population (F₆ and F₇) from a cross between Zhenshan97 and HR5 was employed to identify main quantitative trait loci (QTLs) and epistatic QTL (E-QTL). Highly significant positive correlations were detected among five traits of heading date (HD), plant height (PH), panicle length (PL), flag leaf length (FLL) and flag leaf width (FLW) in 2 environments. Four to 8 main QTLs were detected for an individual trait. No E-QTL was detected for PH. One, 4, 4 and 5 E-QTLs were detected for FLL, HD, FLW and PL, respectively. Each E-QTL individually explained less than 3% of trait variation except E-QFll1. Comparison of QTL results was made in order to dissect the genetic basis of trait correlation. We found that main QTLs with pleiotropic effects and QTL clusters were the main genetic basis of trait correlation. No E-QTL had pleiotropic effects. E-QTL played an important role in the genetic basis of individual trait, but it made a little contribution to trait correlation.     

A genome scan for quantitative trait loci affecting grain yield and its components of maize both in single-and two-locus levels

Maize is one of the most important cereal crops in the world. The hybrid yield advantage is responsible for about 10 percent of the total global maize production of 550 Mt[1]. It is exigent to study the yield traits so as to improve the hybrids per se in …     

Mapping QTLs on BTA6 affecting milk production traits in a Chinese Holstein population

To make marker-assisted selection (MAS) more effi-cient in improving economically important traits for farm animals, one important factor is to find markers linked to the quantitative trait loci (QTL) as closely as possible. So it is best to use the gene per se underlying the QTL. A whole genome scan for QTL is the prerequisite in the be-ginning, then mapping on some special important chro-mosomes, and then fine mapping in some target region on given chromosome aiming at gene cloning and c…     

A new statistical method for mapping QTLs underlying endosperm traits

Genetic expression for an endosperm trait in seeds of cereal crops may be controlled simultaneously by the triploid endosperm genotypes and the diploid maternal genotypes. However, current statistical methods for mapping quantitative trait loci （QTLs） underlying endosperm traits have not been effective in dealing with the putative maternal genetic effects. Combining the quantitative genetic model for diploid maternal traits with triploid endosperm traits, here we propose a new statistical method for mapping QTLs controlling endosperm traits with maternal genetic effects. This method applies the data set of both DNA molecular marker genotypes of each plant in segregation population and the quantitative observations of single endosperms in each plant to map QTL. The maximum likelihood method implemented via the expectation-maximization algorithm was used to the estimate parameters of a putative QTL. Since this method involves the maternal effect that may contribute to endosperm traits, it might be more congruent with the genetics of endosperm traits and more helpful to increasing the precision of QTL mapping. The simulation results show the proposed method provides accurate estimates of the QTL effects and locations with high statistical power.     

Construction of a genetic map and localization of QTLs for yield traits in tomato by SSR markers

Using an F2 population derived from the hybrid of Lycopersicon esculentum Mill. ‘XF 98-7’× Lycopersicon pimpinellifolium LA2184, a SSR genetic linkage map of tomato is constructed. The map contains 112 markers and spans 808.4 cM with an average distance of 7.22 cM between loci. Two quantitative trait loci (QTLs) for first flower node on chromosomes 5 and 11, two QTLs for number of flowers per truss on chromosomes 2 and 5, and five QTLs for fruit weight on chromosomes 1, 2, 3, 9 and 12 are identified.