绿豆5个产量相关性状的QTL分析

利用绿豆(Vigna radiata)品种苏绿16-10和潍绿11杂交构建的F₂和F₃群体发掘调控绿豆产量相关性状的遗传位点。同时对绿豆产量相关性状进行表型鉴定和相关性分析, 并利用构建的遗传连锁图谱进行QTL定位。结果表明, 单株产量与单株荚数、单荚粒数、百粒重和分枝数均呈正相关。单株产量与单株荚数的相关性最高, 这2个性状在F₂和F₃群体中的相关系数分别为0.950和0.914。在F₂群体中, 共检测到8个与产量性状相关的QTL位点, 其中与单株荚数、单荚粒数和单株产量相关的QTL位点各1个, 分别解释11.09% (qNPP3)、17.93% (qNSP3)和14.18% (qYP3)的表型变异; 2个与分枝数相关的QTL位点qBMS3和qBMS11, 分别解释18.51%和7.06%的表型变异; 3个与百粒重相关的QTL位点qHSW3、qHSW7和qHSW10, 分别解释5.33%、46.07%和4.24%的表型变异。在F₃群体中, qNSP3和qHSW7再次被检测到, 表明这2个QTLs有较好的遗传稳定性。同时, 开发了1个与百粒重主效QTL qHSW7紧密连锁的InDel标记R7-13.4, 并利用自然群体对该分子标记辅助筛选的有效性进行了验证。研究结果可为绿豆产量相关性状基因的定位、克隆及分子标记辅助育种提供参考。     

利用RFLP标记定位水稻重要农艺性状的主效基因与微效基因

以一对籼粳交(圭630/02 428)经花药培养产生的双单倍体(DH)群体构建了含233个RFLP标记、覆盖基因组约2070cM的水稻分子图谱.利用QTL区间作图对水稻重要农艺性状如抽穗期、株高、有效穗、着粒数、实粒数、结实率和千粒重等7个性状的基因座位进行了定位分析,检测到8个主效基因和29个微效基因.双亲间性状差异较大有利于主效基因的鉴别.     

谷子SSR分子图谱的构建及主要农艺性状QTL定位

试验拟对谷子重要农艺性状进行数量性状位点QTL分析。以表型差异较大的沈3/晋谷20F2作图群体为材料,观测其株高、穗长等性状,选用SSR做分子标记,利用完备区间作图法(BASTEN C J)进行QTL分析。结果显示,表型数据在作图群体中呈现连续分布,表现为多基因控制的数量性状,被整合的54个SSR标记构建10个连锁群,LOD阈值设置为2.0,检测到与株高相关的主效QTL2个,联合贡献率45.9637%,穗长主效QTL1个,贡献率14.9647%,与穗重、粒重相关的主效QTL为同一位点,贡献率分别为11.9601%和10.1879%。有6组QTL位点之间存在基因互作效应,大小范围为-0.4986-16.6407,对性状的贡献率在2.2716％至6.7478％之间。谷子表型控制复杂,相关QTL的检测受环境影响较大,不同连锁群QTL间互作明显。     

标准切花菊杂交F1代群体侧枝侧蕾性状的杂种优势和遗传分析

以标准切花菊〔Dendranthema morifolium(Ramat.)Tzvel.〕品种'优香'('Yuuka')为母本、品种'神马'('Jinba')为父本进行杂交,对杂交F1代群体的单株侧枝平均长度、单株侧枝数、单株侧枝数与单株叶节数的比值(R1)、主蕾直径与侧蕾直径的比值(R2)、单株侧蕾数以及主蕾与侧蕾间距离6个性状进行杂种优势和相关性分析,并利用主基因+多基因混合遗传模型检测这些性状的主基因效应.结果显示:杂交F1代群体6个侧枝侧蕾性状的变异系数为2378%~5065%,且侧枝性状的变异系数总体上高于侧蕾性状;各性状的频次均呈现连续性的正态分布趋势,说明这些性状可能属于多基因控制的数量性状.杂交F1代群体的6个侧枝侧蕾性状均在001水平上表现出显著的中亲优势,表明各性状均存在显著的杂种优势.6个性状中,单株侧枝平均长度的中亲值最大(6230 mm),R1的中亲值最小(026);单株侧枝平均长度、R2和主蕾与侧蕾间距离的中亲优势均为正值,单株侧枝数、单株侧蕾数和R1的中亲优势均为负值.6个性状的中亲优势率为-5374%~3128%,其中,单株侧枝数的中亲优势率最小,而主蕾与侧蕾间距离的中亲优势率最大.相关性分析结果显示:单株侧枝平均长度和单株侧枝数均与R1呈极显著正相关,并与R2和单株侧蕾数呈极显著负相关;R2与侧蕾数也呈极显著正相关,且二者均与主蕾与侧蕾间距离呈极显著正相关.混合遗传分析结果显示:单株侧枝平均长度、R1、R2和单株侧蕾数均受2对主基因控制,符合B-1模型,主基因表现为"加性-显性-上位性",这4个性状的遗传率分别为7707%、9672%、6438%和5307%;单株侧枝数也受2对主基因控制,符合B-2模型,主基因表现为"加性-显性",该性状的遗传率为7438%,表明这5个性状的遗传存在主基因控制效应.而主蕾与侧蕾间距离符合A-0遗传模型,说明该性状无主基因控制,易受环境影响.     

玉米5个农艺性状的QTL定位

利用“豫玉22”构建的266个玉米F2：3家系为材料,通过一年两点的随机区组田间试验和分子标记分析,研究了玉米穗位高、雄穗分支数、茎粗、抽雄期、吐丝期5个重要农艺性状。相关分析表明,穗位高、雄穗分支数、茎粗与单株产量显著正相关,抽雄期与吐丝期高度正相关,雄穗分支数与茎粗显著正相关。采用复合区间作图法,通过500次排列测验分别确定各性状的LOD阈值,在武汉和襄樊两地共定位了7个穗位高QTL、9个雄穗分支数QTL、8个茎粗QTL、9个抽雄期QTL和7个吐丝期QTL;这些QTL在染色体上分布不均匀,具有集中分布的特点。研究表明,数量性状间的表型相关可能源于控制数量性状的QTL位点间的相关。     

7个烤烟产量相关性状的QTL定位分析

以烤烟Y3和K326为亲本,采用单粒传法(SSD)获得一个包含262个F6株系的重组自交系群体(RILs)。基于该群体构建了一张含有24个连锁群、626个SSR标记,总长为1 120.45cM的遗传图谱。通过两年一点3次重复的随机区组田间试验,测定了株高、节距、叶数、茎围、茎叶角度、腰叶长和腰叶宽7个与产量相关农艺性状,采用混合线性模型的严格复合区间作图法(rMQM)在烟草全基因组范围内进行QTL扫描分析。结果显示:(1)烤烟7个目标性状在RILs群体内各株系间存在较大范围的连续变异,具有显著的双向超亲分离,且各性状的平均值很接近中亲值;7个农艺性状的平均广义遗传率为73.33%,其中株高和节距的广义遗传率在80%以上,而茎围和茎叶角度的广义遗传率则低于60%,表明7个与烤烟产量相关的农艺性状是既受微效多基因控制又受环境条件影响的数量性状。(2)共检测到30个QTLs分布在9条连锁群上,其中与株高、节距、叶数、腰叶长和腰叶宽相关的5个主效QTLs在连续两年中均可检测到,且具有较大的效应值,可解释大于10%的表型变异。(3)7个目标性状之间存在一定程度的相关性,与之对应在基因组中也存在一些较小区域,每个区域包含2个或2个以上紧密连锁的不同性状的QTLs。烟草产量相关农艺性状的QTL分析和主效QTLs的获得,为进一步利用分子标记辅助选择培育烟草高产新品种奠定了理论基础。     

测序水稻品种SSR遗传连锁图谱的构建及其农艺性状基因座分析

利用测序水稻品种"Nipponbare（粳）/广陆矮4号（籼）"杂交F2群体90个单株为作图群体,构建含148个SSR标记的水稻遗传连锁图谱,覆盖基因组全长1737.81cM,标记间平均距11.90cM。利用该图谱及Excel2000和Mapmaker/QTL1.1b软件对分蘖数、穗数、穗长、主穗长、株高、剑叶长等六个农艺性状间的相互关系和基因位点进行分析,结果在LOD>2.2和P<0.005的条件下共检测到28个QTLs,它们分布在水稻所有染色体上,单个QTL对性状的分子贡献率11.1%-42.9%,其中大于20%有10个,并对选用已测序材料为亲本构建图谱来探讨水稻农艺性状的分子基础及其育种意义进行了讨论。     

油菜油分、蛋白质和硫苷含量相关性分析及QTL 定位

为定位与油分、蛋白质和硫苷含量等品质性状相关的数量性状位点(QTL), 以2个含油量较高的甘蓝型油菜(Brassica napus)品系8908B和R1为研究材料, 配置正反交组合。在正反交F₂代群体中, 含油量和蛋白质含量都存在极显著的负相关, 相关系数分别为-0.68和-0.81, 含油量和硫苷含量相关性不显著; 蛋白质含量和硫苷含量在正交群体中相关性不显著, 但在反交群体中存在显著负相关(相关系数r =-0.45)。利用正交F₂代群体中的118个单株, 构建了包含121个标记的遗传连锁图谱, 图谱长1 298.7 cM, 有21个连锁群(LGs)。采用复合区间作图法, 在连锁图上定位了2个与含油量有关的QTL, 分别位于LG8和LG10, 其贡献率分别为4.8%和13.7%, 增效基因都来源于R1; 定位了2个与蛋白质含量有关的QTL: pro1 和 pro2, 分别位于LG1和LG3, 其贡献率分别为15.2%和14.1%, 位点pro1由8908B提供增效基因, pro2则由R1提供增效基因; 定位了4个与硫苷含量有关的QTL, 其中LG20上有2个, LG4和LG8上各1个, 它们的贡献率在1.9%-25.4%之间, 除LG20上glu1的增效基因来自R1外, 其余3个QTL位点均由8908B提供增效基因。     

大豆遗传图谱的构建和若干农艺性状的QTL定位分析

大豆许多重要农艺性状都是由微效多基因控制的数量性状,对这些数量性状进行QTL定位是大豆数量性状遗传研究领域的一个重要内容.本研究利用栽培大豆科新3号为父本、中黄20为母本杂交得到含192个单株的F2分离群体,构建了含122 个SSR标记、覆盖1719.6cM、由33个连锁群组成的连锁遗传图谱.利用复合区间作图法,对该群体的株高、主茎节数、单株粒重和蛋白质含量等农艺性状的调查数据进行QTL分析,共找到两个株高QTL,贡献率分别为9.15%和6.08%;两个主茎节数QTL,贡献率分别为10. 1%和8.6%;一个蛋白质含量QTL,贡献率为9.8%;一个单株粒重QTL,贡献率为11.4% .通过遗传作图共找到与所定位的4个农艺性状QTL连锁的6个SSR标记,这些标记可以应用于大豆种质资源的分子标记辅助选择,从而为大豆分子标记辅助育种提供理论依据.     

小麦-冰草衍生后代 3558-2 穗部相关性状的遗传分析和QTL定位

从普通小麦Fukuho与冰草(Agropyron cristatum,2n=4x=28,PPPP)Z559的衍生系中发现3558-2具有小穗数、小穗粒数和穗粒数多的优异性状.为了揭示衍生系3558-2优异性状的遗传特征,本研究对其与小麦品种京4841间的282个F2单株的穗长、小穗数、小穗粒数、穗粒数等穗部相关性状进行了遗传分析和QTL定位.主基因+多基因混合遗传模型分析结果显示小麦穗部相关性状都符合数量性状特征.利用单标记分析将穗部相关性状的QTL主要定位于小麦1 A染色体上,同时发现在小麦的2A、5B和5D染色体上也有QTL分布.通过加密标记重点构建了1 A染色体短臂的遗传连锁图,利用复合区间作图法解析了小麦1AS染色体上的穗部相关性状的QTL效应,发现在1A染色体上存在与穗长、小穗数、小穗粒数和穗粒数相关的重要QTL各1个,解释变异度分别为14.41%、5.15%、14.84%和10.87%.本研究发现在3558-2的1 AS染色体上成簇分布着涉及穗长、小穗教、小穗粒数和穗粒数重要性状的QTL,这一结果对指导进一步研究与利用3558-2具有重要意义.     

Seed and agronomic QTL in low linolenic acid, lipoxygenase-free soybean (Glycine max (L.) Merrill) germplasm.

Linolenic acid and seed lipoxygenases are associated with off flavours in soybean products. F5 recombinant inbred lines (RILs) from a cross between a low linolenic acid line (RG10) and a seed lipoxygenase-free line (OX948) were genotyped for simple sequence repeats (SSR), random amplified polymorphic DNA (RAPD), sequence-tagged sites (STS), and cleaved amplified polymorphic sequence (CAPS) markers and evaluated for seed and agronomic traits at 3 Ontario locations in 2 years. One hundred twenty markers covering 1247.5 cM were mapped to 18 linkage groups (LGs) in the soybean composite genetic map. Seed lipoxygenases L-1 and L-2 mapped as single major genes to the same location on LG G13-F. L-3 mapped to LG G11-E. This is the first report of a map position for L-3. A major quantitative trait locus (QTL) associated with reduced linolenic acid content was identified on LG G3-B2. QTLs for 12 additional seed and agronomic traits were detected. Linolenic acid content, linoleic acid content, yield, seed mass, protein content, and plant height QTL were present in at least 4 of 6 environments. Three to 8 QTLs per trait were detected that accounted for up to 78% of total variation. Linolenic acid and lipoxygenase loci did not overlap yield QTL, suggesting that it should be possible to develop high-yielding lines resistant to oxidative degradation by marker-assisted selection (MAS).     

QTL analysis of agronomic traits in barley based on the doubled haploid progeny of two elite North American varieties representing different germplasm groups

A better understanding of the genetics of complex traits, such as yield, may be achieved by using molecular tools. This study was conducted to estimate the number, genome location, effect and allele phase of QTLs determining agronomic traits in the two North American malting barley (Hordeum vulgare L.) quality variety standards. Using a doubled haploid population of 140 lines from the cross of two-rowed Harrington×six-rowed Morex, agronomic phenotypic data sets from nine environments, and a 107-marker linkage map, we performed QTL analyses using simple interval mapping and simplified composite interval mapping procedures. Thirty-five QTLs were associated, either across environments or in individual environments, with five grain and agronomic traits (yield, kernel plumpness, test weight, heading date, and plant height). Significant QTL×environment interaction was detected for all traits. These interactions resulted from both changes in the magnitude of response and changes in the sign of the allelic effect. QTLs for multiple traits were coincident. The vrs1 locus on chromosome 2 (2H), which determines inflorescence row type, was coincident with the largest-effect QTL determining four traits (yield, kernel plumpness, test weight, and plant height). QTL analyses were also conducted separately for each sub-population (six-rowed and two-rowed). Seven new QTLs were detected in the sub-populations. Positive transgressive segregants were found for all traits, but they were more prevalent in the six-rowed sub-population.QTL analysis should be useful for identifying candidate genes and introgressing favorable alleles between germplasm groups. Received: 18 August 2000 / Accepted: 15 December 2000     

Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers

Huge efforts have been invested in the last two decades to dissect the genetic bases of complex traits including yields of many crop plants, through quantitative trait locus (QTL) analyses. However, almost all the studies were based on linkage maps constructed using low-throughput molecular markers, e.g. restriction fragment length polymorphisms (RFLPs) and simple sequence repeats (SSRs), thus are mostly of low density and not able to provide precise and complete information about the numbers and locations of the genes or QTLs controlling the traits. In this study, we constructed an ultra-high density genetic map based on high quality single nucleotide polymorphisms (SNPs) from low-coverage sequences of a recombinant inbred line (RIL) population of rice, generated using new sequencing technology. The quality of the map was assessed by validating the positions of several cloned genes including GS3 and GW5/qSW5, two major QTLs for grain length and grain width respectively, and OsC1, a qualitative trait locus for pigmentation. In all the cases the loci could be precisely resolved to the bins where the genes are located, indicating high quality and accuracy of the map. The SNP map was used to perform QTL analysis for yield and three yield-component traits, number of tillers per plant, number of grains per panicle and grain weight, using data from field trials conducted over years, in comparison to QTL mapping based on RFLPs/SSRs. The SNP map detected more QTLs especially for grain weight, with precise map locations, demonstrating advantages in detecting power and resolution relative to the RFLP/SSR map. Thus this study provided an example for ultra-high density map construction using sequencing technology. Moreover, the results obtained are helpful for understanding the genetic bases of the yield traits and for fine mapping and cloning of QTLs.     

Comparative mapping of QTLs for agronomic traits of rice across environments by using a doubled-haploid population

We report here the RFLP mapping of quantitative trait loci (QTLs) which affect some important agronomic traits in cultivated rice. An anther culture-derived doubled-haploid (DH) population was established from a cross between indica and japonica rice varieties. A molecular linkage map comprising 137 markers was constructed based on this population which covered the rice genome at intervals of 14.8 cM on average. The linkage map was used to locate QTLs for such important agronomic traits as heading date, plant height, number of spikelets per panicle, number of grains per panicle, 1 000-grain weight and the percentage of seed set, by interval mapping. Evidence of genotype-by-environment interaction was found by comparing QTL maps of the same population grown in three diverse environments. A total of 22 QTLs for six agronomic traits was detected which were significant in at least one environment, but only seven were significant in all three environments; seven were significant in two environments and eight could only be detected in a single environment. However, QTLs-by-environment interaction was trait dependent. QTLs for spikelets and grains per panicle were common across environments while traits like heading date and plant height were more sensitive to environment. Received: 22 February 1996 / Accepted: 10 May 1996     

Comparative mapping of QTLs for agronomic traits of rice across environments using a doubled haploid population

We report here the RFLP mapping of quantitative triat loci (QTLs) that affect some important agronomic traits in cultivated rice. An anther culturederived doubled haploid (DH) population was established from a cross between an indica and a japonica rice variety. On the basis of this population a molecular linkage map comprising 137 markers was constructed that covered the rice genome at intervals of 14.8cM on average. Interval mapping of the linkage map was used to locate QTLs for such important agronomic traits as heading date, plant height, number of spikelets per panicle, number of grains Per panicle, 1000-grain weight and percentage of seed set. Evidence of genotype-byenvironment interaction was found by comparing QTL maps of the same population grown in three diverse environments. A total of 22 QTLs for six agronomic traits were detected that were significant in at least one environment, but only 7 were significant in all three environments, 7 were significant in two environments and 8 could only be detected in a single environment. However, QTL-by-environment interaction was traitdependent. QTLs for spikelets and grains per panicle were common across environments, while traits like heading date and plant height were more sensitive to environment.     

Genetic mapping of QTLs for sugar-related traits in a RIL population of Sorghum bicolor L. Moench

The productivity of sorghum is mainly determined by quantitative traits such as grain yield and stem sugar-related characteristics. Substantial crop improvement has been achieved by breeding in the last decades. Today, genetic mapping and characterization of quantitative trait loci (QTLs) is considered a valuable tool for trait enhancement. We have investigated QTL associated with the sugar components (Brix, glucose, sucrose, and total sugar content) and sugar-related agronomic traits (flowering date, plant height, stem diameter, tiller number per plant, fresh panicle weight, and estimated juice weight) in four different environments (two locations) using a population of 188 recombinant inbred lines (RILs) from a cross between grain (M71) and sweet sorghum (SS79). A genetic map with 157 AFLP, SSR, and EST-SSR markers was constructed, and several QTLs were detected using composite interval mapping (CIM). Further, additive × additive interaction and QTL × environmental interaction were estimated. CIM identified more than five additive QTLs in most traits explaining a range of 6.0–26.1% of the phenotypic variation. A total of 24 digenic epistatic locus pairs were identified in seven traits, supporting the hypothesis that QTL analysis without considering epistasis can result in biased estimates. QTLs showing multiple effects were identified, where the major QTL on SBI-06 was significantly associated with most of the traits, i.e., flowering date, plant height, Brix, sucrose, and sugar content. Four out of ten traits studied showed a significant QTL × environmental interaction. Our results are an important step toward marker-assisted selection for sugar-related traits and biofuel yield in sorghum.     

Identification of quantitative trait loci for agronomically important traits and their association with genic-microsatellite markers in sorghum

The identification of quantitative trait loci (QTLs) affecting agronomically important traits enable to understand their underlying genetic mechanisms and genetic basis of their complex interactions. The aim of the present study was to detect QTLs for 12 agronomic traits related to staygreen, plant early development, grain yield and its components, and some growth characters by analyzing replicated phenotypic datasets from three crop seasons, using the population of 168 F₇ RILs of the cross 296B × IS18551. In addition, we report mapping of a subset of genic-microsatellite markers. A linkage map was constructed with 152 marker loci comprising 149 microsatellites (100 genomic- and 49 genic-microsatellites) and three morphological markers. QTL analysis was performed by using MQM approach. Forty-nine QTLs were detected, across environments or in individual environments, with 1–9 QTLs for each trait. Individual QTL accounted for 5.2–50.4% of phenotypic variance. Several genomic regions affected multiple traits, suggesting the phenomenon of pleiotropy or tight linkage. Stable QTLs were identified for studied traits across different environments, and genetic backgrounds by comparing the QTLs in the study with previously reported QTLs in sorghum. Of the 49 mapped genic-markers, 18 were detected associating either closely or exactly as the QTL positions of agronomic traits. EST marker Dsenhsbm19, coding for a key regulator (EIL-1) of ethylene biosynthesis, was identified co-located with the QTLs for plant early development and staygreen trait, a probable candidate gene for these traits. Similarly, such exact co-locations between EST markers and QTLs were observed in four other instances. Collectively, the QTLs/markers identified in the study are likely candidates for improving the sorghum performance through MAS and map-based gene isolations.     

Molecular detection of QTLs for agronomic and quality traits in a doubled haploid population derived from two Canadian wheats (Triticum aestivum L.)

Development of high-yielding wheat varieties with good end-use quality has always been a major concern for wheat breeders. To genetically dissect quantitative trait loci (QTLs) for yield-related traits such as grain yield, plant height, maturity, lodging, test weight and thousand-grain weight, and for quality traits such as grain and flour protein content, gluten strength as evaluated by mixograph and SDS sedimentation volume, an F₁-derived doubled haploid (DH) population of 185 individuals was developed from a cross between a Canadian wheat variety “AC Karma” and a breeding line 87E03-S2B1. A genetic map was constructed based on 167 marker loci, consisting of 160 microsatellite loci, three HMW glutenin subunit loci: Glu-A1, Glu-B1 and Glu-D1, and four STS-PCR markers. Data for investigated traits were collected from three to four environments in Manitoba, Canada. QTL analyses were performed using composite interval mapping. A total of 50 QTLs were detected, 24 for agronomic traits and 26 for quality-related traits. Many QTLs for correlated traits were mapped in the same genomic regions forming QTL clusters. The largest QTL clusters, consisting of up to nine QTLs, were found on chromosomes 1D and 4D. HMW glutenin subunits at Glu-1 loci had the largest effect on breadmaking quality; however, other genomic regions also contributed genetically to breadmaking quality. QTLs detected in the present study are compared with other QTL analyses in wheat.     

Efficient construction of high-density linkage map and its application to QTL analysis in barley

Using a High Efficiency Genome Scanning (HEGS) system and recombinant inbred (RI) lines derived from the cross of Russia 6 and H.E.S. 4, a high-density genetic map was constructed in barley. The resulting 1,595.7-cM map encompassed 1,172 loci distributed on the seven linkage groups comprising 1,134 AFLP, 34 SSR, three STS and vrs1 (kernel row type) loci. Including PCR reactions, gel electrophoresis and data processing, 6 months of work by a single person was sufficient for the whole mapping procedure under a reasonable cost. To make an appraisal of the resolution of genetic analysis for the 95 RI lines based on the constructed linkage map, we measured three agronomic traits: plant height, spike exsertion length and 1,000-kernel weight, and the analyzed quantitative trait loci (QTLs) associated with these traits. The results were compared on the number of detected QTLs and their effects between a high-density map and a skeleton map constructed by selected AFLP and anchor markers. The composite interval mapping on the high-density map detected more QTLs than the other analyses. Closely linked markers with QTLs on the high-density map could be powerful tools for marker-assisted selection in barley breeding programs and further genetic analyses including an advanced backcross analysis or a map-based cloning of QTL. Electronic Supplementary Material Supplementary material is available in the online version of this article at Communicated by J.S. Heslop-Harrison