爆裂玉米膨化倍数QTL分析及其环境稳定性

膨化倍数是爆裂玉米最重要的品质指标。以普通玉米自交系丹232和爆裂玉米自交系N04杂交构建的259个F2：3家系为定位群体,采用完全随机区组设计在郑州春播和夏播条件下测定了膨化倍数。利用覆盖玉米10条染色体的183对多态性分子标记构建连锁图,采用复合区间作图法（CIM）进行QTL定位分析,采用多区间作图法（MIM）分析定位QTL间的互作效应。共检测出22个QTLs,单个QTL的贡献率为3．07％～12．84％,累计贡献率为66．46％和51．90％。其中5个QTLs在两种环境条件下均检测到,3个QTLs（qPF-6-1、qPF-8-1和qPF-1-3）的贡献率大于10％。大多数QTLs的加性效应值大于显性效应,表现为加性、部分显性、显性和超显性基因作用方式的QTLs数目在两种环境下分别为4、5、0、2和2、5、2、2。仅6对（占2．60％）QTLs或标记区间存在显著互作效应,表现为AA、DA或DD互作方式。     

胡萝卜(Daucus carota L.)中主要胡萝卜素和番茄红素含量的QTL分析

以高胡萝卜素自交系P50006和HCM A.C.为亲本构建的F2群体为作图群体,对胡萝卜中α-胡萝卜素、α-胡萝卜素、总胡萝卜素和番茄红素含量进行QTL定位及遗传分析。结果表明,α、β-胡萝卜素、总胡萝卜素和番茄红素含量的广义遗传力分别为0.75、0.50、0.31和0.93。遗传图谱包含91个SRAP(Sequence-related amplified polymorphism)标记,分布于9个连锁群,总长度502.9cM,标记间平均距离5.5cM。除α-胡萝卜素含量外,α-胡萝卜素、总胡萝卜素和番茄红素含量分别检测到1个主效QTL,均为加性遗传效应,分别解释表型变异为12.79%、12.87%和14.61%。此外,α-胡萝卜素和番茄红素含量还分别检测到1对上位性QTL,最大遗传效应分别为显性×加性互作和显性×显性互作,分别解释表型变异为15.1%和6.5%。文章中与QTL连锁的分子标记可用于高胡萝卜素、番茄红素的种质筛选和聚合育种。     

玉米SSR连锁图谱构建及叶面积的QTL定位

叶片是玉米进行光合作用的主要器官,叶面积的大小(尤其是穗三叶面积)对于玉米干物质的积累及产量形成起着至关重要的作用。研究玉米叶面积的遗传基础对于指导玉米高产育种具有理论意义。文章以两个叶面积差异显著的亲本478×武312为基础材料所构建的218个F8代的重组自交系为作图群体,构建了一张包含184个SSR标记的遗传连锁图谱,图谱总长度为2084.1cM,平均图距为11.3cM。通过两年的田间试验对玉米叶面积(穗三叶)进行了QTL定位分析。两年共定位到7个和叶面积相关的QTL位点,2006年定位到4个QTL位点;2007年定位到3个QTL位点。在第2染色体umc1542-umc1518标记区间发现一个主效QTL位点,该位点可以在两年同时检测到,两年分别解释12.5%和17.3%的表型变异。该位点能稳定地检测到且具有较大的贡献率,可能会在玉米叶面积分子标记辅助选择上有所应用。     

拔节期与抽穗期玉米抗纹枯病相关QTL的初步定位

以玉米自交系R15(抗)×478(感)的F_2分离群体为作图群体,构建了包含146个SSR标记位点的遗传连锁图谱,覆盖玉米基因组1666 cM,平均图距11．4 cM。通过麦粒嵌入法对229个F_(2：4)家系进行人工接种纹枯病菌,于玉米拔节期和抽穗期进行纹枯病的抗性鉴定。应用复合区间作图法分析两个时期的抗病QTL及遗传效应。结果共检测到17个抗性QTL,其中以拔节期病情指数为指标共检测到9个QTL,分别位于第1、2、3、4、5、6、和10染色体上,可解释的表型变异为3．72%-9．26%;以抽穗期的病情指数为指标共在7条染色体上检测到10个抗玉米纹枯病的QTL,分布于第2、3、4、5、6、8和9染色体上。单个QTL可解释的表型变异为4．27%-9．27%。两个时期共检测出2个共同QTL,它们分别位于第2染色体的bnlgl662-bnlg1940区间和第6染色体的umc1006-umc1723区间。定位结果表明两个时期检测出的抗性QTL的差异表达与玉米不同发育时期基因的时空表达有密切关系,从而反映在纹枯病的抗性位点差异性上．这为玉米抗病选育提供新的信息。     

小麦籽粒干物质积累的动态QTL定位

以波兰小麦品系‘XN555’与普通小麦品系‘中13’杂交产生的99个F10重组自交系(RILs)为材料,构建了包含241个SSR分子标记的A、B染色体组14个连锁群的遗传图谱,并采用Logistic方程拟合籽粒灌浆过程,对粒重增长的缓慢增长期、快速增长期和平稳期进行千粒重条件QTL和非条件QTL定位分析。结果显示:(1)在小麦A、B染色体组上共检测到5个非条件QTL和5个条件QTL。(2)在小麦粒重缓慢增长期和快速增长期各有2个非条件QTL,平稳期有1个非条件QTL,它们分别位于2B、3A、3B和7A染色体上,单个QTL可解释表型变异的9.66%～15.18%。(3)在小麦粒重快速增长期检测到1个条件QTL,平稳期检测到4个条件QTL,涉及1A、2B、5B和7B染色体,单个QTL可解释表型变异的13.01%～29.27%。(4)于2B染色体Xbarc361～Xwmc422标记区间距Xbarc361标记0.05cM处,在粒重快速增长期同时检测到一个条件QTL和非条件QTL,且在平稳期检测到一个非条件QTL。研究表明,小麦不同灌浆时期粒重增长相关QTL的数量和遗传效应各不同,同一QTL在不同灌浆时期的遗传效应也不同,即QTL的表达具有时序选择性。     

玉米杂交种掖单13号的SSR连锁图谱构建与叶夹角和叶向值的QTL定位与分析

为了增加单位面积产量, 玉米育种者已经开始了更密植更紧凑株型的选育。叶夹角和叶向值是评价玉米株型的重要指标。本研究以掖478×丹340的500个F2单株为作图群体, 构建了具有138个位点的SSR标记连锁图谱, 图谱总长度为1 394.9 cM, 平均间距10.1 cM。利用397个F2：3家系对叶夹角和叶向值进行QTL定位分析, 结果表明: 叶夹角和叶向值分别检测到6和8个QTL, 累计解释表型变异41.0%和60.8%, 单个QTL的贡献率在2.9%~13.6%之间。与叶夹角和叶向值有关的基因主要作用方式为加性和部分显性。此外两个性状共检测到9对上位性互作位点, 表明上位性互作在叶夹角和叶向值的遗传中也起较重要的作用。     

甘蓝型油菜遗传图谱的构建及单株产量构成因素的QTL分析

采用常规品系04-1139与高产多角果品系05-1054构建的F2代群体为作图群体, 运用SSR(Simple sequence repeat)和SRAP(Sequence-related amplified polymorphism)构建分子标记遗传图谱并对甘蓝型油菜单株产量构成因素进行QTL分析。遗传图谱包含200个分子标记, 分布于19个连锁群上, 总长度1 700.23 cM, 标记间的平均距离8.50 cM。采用复合区间作图法(Composite interval mapping, CIM)对单株产量构成因素(单株有效角果数、每果粒数和千粒重)进行QTL分析, 共检测到12个QTL: 其中单株有效角果数4个QTL, 分别解释表型变异为35.64%、12.96%、28.71%和34.02%; 每果粒数获得5个QTL, 分别解释表型变异为8.41%、7.87%、24.37%、8.57%和14.31%; 千粒重获得３个QTL, 分别解释表型变异为2.33%、1.81%和1.86%。结果表明: 同一性状的等位基因增效作用可以同时来自高值亲本和低值亲本; 文章中与主效QTL连锁的标记可用于油菜产量性状的分子标记辅助选择和聚合育种。     

玉米抗南方锈病基因的QTL定位

为发掘新的抗南方锈病基因资源,本研究以感病自交系黄早四为母本、抗病自交系W456为父本,构建F2群体并开展抗病基因定位研究。采用人工接种鉴定的方法对两个亲本、F1、F2群体及对照材料进行表型鉴定和遗传分析。利用均匀覆盖10条染色体的200个SSR标记,分析240个F2单株的基因型并构建含有200个SSR位点的遗传连锁图,连锁图总长度3331 cM,标记间平均距离16.6 cM。使用QTL IciMapping V4.1软件中的完备区间作图法对抗病QTL进行分析,共检测到6个控制南方锈病的QTL:qSCR3、qSCR7、qSCR8-1、qSCR8-2、qSCR9和qSCR10,邻近标记分别为umc2105和umc1729、umc1066和bnlg2271、umc1904和umc1984、umc1984和bnlg1651、umc1957和bnlg1401、umc2034和umc1291,分别位于3、7、8、9和10号染色体上,其中8号染色体上有两个位点,标记区间长度在5～19 cM之间。单个QTL的表型贡献率在2.61%～24.19%之间,可以解释表型总变异的62.3%,其中3个QTL贡献率大于10%,位于10号染色体上的qSCR10贡献率最大,可解释表型变异的24.19%。通过对目标区间标记加密,将该位点的定位区间进一步缩小到2.51 cM内,与两侧标记的距离分别是2.15 cM和0.36 cM。初步定位得到10号染色体上存在抗南方锈病的主效QTL,可为抗病品种的培育提供参考。     

陆地棉遗传图谱构建与纤维品质性状QTL定位

以陆地棉(Gossypium hirsutum L.)品种Bar19/1和Acala1517-77杂交的108个F2单株为材料,应用85个标记(70个SSR标记和15个AFLP标记)构建了总长为814cM的遗传图谱,覆盖棉花基因组的18.3%。该图谱包含25个连锁群,分别对应到17条染色体和4个未知连锁群。应用复合区间作图法分析了该组合的108个F2单株和F3家系纤维品质性状,从遗传图谱上检测到19个纤维品质数量性状基因座(QTL),包括5个纤维长度、6个纤维比强度、4个伸长率及4个马克隆值QTL,分别解释各性状表型变异的15.11%~28.45%、8.46%~24.51%、11.08%~27.55%和9.23%~42.21%。纤维长度和伸长率的QTL以部分显性为主,少数具有超显性,比强度QTL以加性和部分显性为主,4个马克隆值QTL中有3个表现为超显性。研究结果表明,陆地棉Bar19/1和Acala1517-77间多态性位点丰富,有利于构建高密度遗传图谱,纤维品质性状的QTL分析从分子水平上揭示了纤维品质的遗传基础。     

玉米雌雄开花间隔天数、结穗率与产量的数量性状位点(QTL)分析

采用SSR标记连锁图谱和复合区间作图法在山西灌溉和干旱胁迫条件下,对玉米(Zea mays L.)自交系黄早四×掖107组合的F3群体雌雄开花间隔天数(ASI)、结穗率和籽粒产量进行了数量性状位点(QTL)定位及基因效应分析.结果表明,在两种水分处理下,ASI、结穗率与籽粒产量的相关性均达到显著水平(P＜0.05).在灌溉和干旱胁迫下,分别检测到3个和2个控制ASI的QTL,位于第1、2、3和第2、5染色体上.在灌溉条件下,在第3和第6染色体上各检测到1个控制结穗率的QTL,基因作用方式呈加性或部分显性,可解释19.9%的表型变异;在干旱条件下,在第3、 7、10染色体上共检测到4个控制结穗率的QTL,基因作用方式为显性或部分显性,可解释60.4%的表型变异.在灌溉和干旱胁迫下,控制产量的QTL分别定位在第3、6、7和第1、2、4、8染色体上,基因作用方式均以加性或部分显性为主,可解释的表型变异为7.3%～22.0%.在干旱条件下,借助连锁分子标记和基因效应分析,可构建包含ASI、结穗率和产量QTL的选择指数,用于分子标记辅助育种.     

Identification of agronomically favorable quantitative trait loci alleles from a dent corn inbred Dan232 using advanced backcross QTL analysis and comparison with the F<Subscript>2:3</Subscript> population in popcorn

Specific traits are an important consideration in plant breeding. In popcorn, inferior agronomic traits could be improved using dent or flint corn backcrossed with popcorn. In this study, we used advanced backcross quantitative trait locus (AB-QTL) analysis to identify trait-improving QTL alleles from a dent maize inbred Dan232, and compared the detection of QTL in the BC₂S₁ population with QTL results using F_2:3 families of the same population. Two hundred and twenty BC₂S₁ families developed from a cross between Dan232 and an elite popcorn inbred N04 were evaluated for nine plant traits in replicated field trials under two environments. Using composite interval mapping (CIM), a total of 28 significant QTL were detected, and of these, 23 (82.14%) had favorable alleles contributed by the dent corn parent Dan232. Nine QTL (32.14%) detected in the BC₂S₁ population were also located in or near the same chromosome intervals in the F_2:3 population. All of the favorable QTL alleles from Dan232 could be used in marker-assisted selection (MAS) to improve the respective plant traits in popcorn breeding. In addition, their near isogenic lines (QTL-NILs) could be obtained through selfing or another 1–2 backcross with N04. Also, N04 improved for the studied plant traits could be developed from the BC₂S₁ families used in this study. This study demonstrated that the AB-QTL method can be applied to identify favorable QTL from dent corn inbred in popcorn breeding and, once identified, the alleles could be used in marker-assisted selection to improve the respective plant traits.     

QTL Analysis of Popping Fold and the Consistency of QTLs Under Two Environments in Popcorn

Popping fold (PF) is the most important quality trait in popcorn. In this study, a total of 259 F_2:3 families, derived from the cross between a dent corn inbred Dan232 and a popcorn inbred N04, were evaluated for their popping folds in replicated experiments under two environments. Of 613 simple sequence repeat (SSR) primer pairs screened, 183 pairs were selected to construct a genetic linkage map with the genetic distance of 1 762.2 cM (centimorgan) and on average 9.63 cM every marker. Quantative trait loci (QTL) were identified, and their genetic effects were estimated using CIM (composite interval mapping) method. The interactions among QTLs detected were calculated using MIM (multiple interval mapping) method. In all, 22 QTLs were detected, and only 5 of them were common under two environments. Contribution to phenotypic variation of a single QTL varied from 3.07% to 12.84%, and total contributions of all QTLs under two environments were 66.46% and 51.90%, respectively. Three QTLs (qPF-6-1, qPF-8-1 and qPF-1-3) with more than 10% contributions were observed. The additive effects were larger than dominant effects for most QTLs. The amount of QTLs showing additive, partially dominant, dominant and over-dominant effects were 4, 5, 0, 2 in spring sowing and 2, 5, 2, 2 in summer sowing, respectively. There were only 2.60% pairs of QTLs or maker intervals expressing AA, DA or DD interactions.     

Identification of trait-improving quantitative trait loci for grain yield components from a dent corn inbred line in an advanced backcross BC<Subscript>2</Subscript>F<Subscript>2</Subscript> population and comparison with its F<Subscript>2:3</Subscript> population in popcorn

Normal maize germplasm could be used to improve the grain yield of popcorn inbreds. Our first objective was to locate genetic factors associated with trait variation and make first assessment on the efficiency of advanced backcross quantitative trait locus (AB-QTL) analysis for the identification and transfer of favorable QTL alleles for grain yield components from the dent corn inbred. A second objective was to compare the detection of QTL in the BC₂F₂ population with results using F_2:3 lines of the same parents. Two hundred and twenty selected BC₂F₂ families developed from a cross between Dan232 and an elite popcorn inbred N04 were evaluated for six grain yield components under two environments, and genotyped by means of 170 SSR markers. Using composite interval mapping (CIM), a total of 19 significant QTL were detected. Eighteen QTL had favorable alleles contributed by the dent corn parent Dan232. Sixteen of these favorable QTL alleles were not in the same or near marker intervals with QTL for popping characteristics. Six QTL were also detected in the F_2:3 population. Improved N04 could be developed from 210 and 208 families with higher grain weight per plant and/or 100-grain weight, respectively, and 35 families with the same or higher popping expansion volume than N04. In addition, near isogenic lines containing detected QTL (QTL-NILs) for grain weight per plant and/or 100-grain weight could be obtained from 12 families. Our study demonstrated that the AB-QTL method can be applied to identify and manipulate favorable QTL alleles from normal corn inbreds and combine QTL detection and popcorn breeding efficiently.     

Mapping of QTL for downy mildew resistance in maize

Quantitative trait loci (QTLs) of maize involved in mediating resistance to Peronosclerospora sorghi, the causative agent of sorghum downy mildew (SDM), were detected in a population of recombinant inbred lines (RILs) derived from the Zea mays L. cross between resistant (G62) and susceptible (G58) inbred lines. Field tests of 94 RILs were conducted over two growing seasons using artificial inoculation. Heritability of the disease reaction was high (around 70%). The mapping population of the RILs was also scored for restriction fragment length polymorphic (RFLP) markers. One hundred and six polymorphic RFLP markers were assigned to ten chromosomes covering 1648 cM. Three QTLs were detected that significantly affected resistance to SDM combined across seasons. Two of these mapped quite close together on chromosome 1, while the third one was on chromosome 9. The percentage of phenotypic variance explained by each QTL ranged from 12.4% to 23.8%. Collectively, the three QTLs identified in this study explained 53.6% of the phenotypic variation in susceptibility to the infection. The three resistant QTLs appeared to have additive effects. Increased susceptibility was contributed by the alleles of the susceptible parent. The detection of more than one QTL supports the hypothesis that several qualitative and quantitative genes control resistance to P. sorghi.     

QTL consistency and meta-analysis for grain yield components in three generations in maize

Grain yield is the most important and complex trait in maize. In this study, a total of 258 F₉ recombinant inbred lines (RIL), derived from a cross between dent corn inbred Dan232 and popcorn inbred N04, were evaluated for eight grain yield components under four environments. Quantitative trait loci (QTL) and their epistatic interactions were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL across three generations (RIL, F_2:3 and BC₂F₂) derived from the same cross. In total, 103 QTL, 42 pairs of epistatic interactions and 16 meta-QTL (mQTL) were detected. Twelve out of 13 QTL with contributions (R ²) over 15% were consistently detected in 3–4 environments (or in combined analysis) and integrated in mQTL. Only q100GW-7-1 was detected in all four environments and in combined analysis. 100qGW-1-1 had the largest R ² (19.3–24.6%) in three environments and in combined analysis. In contrast, 35 QTL for 6 grain yield components were detected in the BC₂F₂ and F_2:3 generations, no common QTL across three generations were located in the same marker intervals. Only 100 grain weight (100GW) QTL on chromosome 5 were located in adjacent marker intervals. Four common QTL were detected across the RIL and F_2:3 generations, and two between the RIL and BC₂F₂ generations. Each of five important mQTL (mQTL7-1, mQTL10-2, mQTL4-1, mQTL5-1 and mQTL1-3) included 7–12 QTL associated with 2–6 traits. In conclusion, we found evidence of strong influence of genetic structure and environment on QTL detection, high consistency of major QTL across environments and generations, and remarkable QTL co-location for grain yield components. Fine mapping for five major QTL (q100GW-1-1, q100GW-7-1, qGWP-4-1, qERN-4-1 and qKR-4-1) and construction of single chromosome segment lines for genetic regions of five mQTL merit further studies and could be put into use in marker-assisted breeding.     

Validation of mega-environment universal and specific QTL associated with seed yield and agronomic traits in soybeans

The value of quantitative trait loci (QTL) is dependant on the strength of association with the traits of interest, allelic diversity at the QTL and the effect of the genetic background on the expression of the QTL. A number of recent studies have identified QTL associated with traits of interest that appear to be independent of the environment but dependant on the genetic background in which they are found. Therefore, the objective of this study was to validate universal and/or mega-environment-specific seed yield QTL that have been previously reported in an independent recombinant inbred line (RIL) population derived from the cross between an elite Chinese and Canadian parent. The population was evaluated at two field environments in China and in five environments in Canada in 2005 and 2006. Of the seven markers linked to seed yield QTL reported by our group in a previous study, four were polymorphic between the two parents. No association between seed yield and QTL was observed. The result could imply that seed yield QTL were either not stable in this particular genetic background or harboured different alleles than the ones in the original mapping population. QTL_U Satt162 was associated with several agronomic traits of which lodging was validated. Both the non-adapted and adapted parent contributed favourable alleles to the progeny. Therefore, plant introductions have been validated as a source of favourable alleles that could increase the genetic variability of the soybean germplasm pool and lead to further improvements in seed yield and other agronomic traits.     

Mapping of a major QTL for pre-harvest sprouting tolerance on chromosome 3A in bread wheat

Quantitative trait loci (QTL) analysis was conducted for pre-harvest sprouting tolerance (PHST) in bread wheat for a solitary chromosome 3A, which was shown to be important for this trait in earlier studies. An intervarietal mapping population in the form of recombinant inbred lines (RILs) developed from a cross between SPR8198 (a PHS tolerant genotype) and HD2329 (a PHS susceptible cultivar) was used for this purpose. The parents and the RIL population were grown in six different environments and the data on PHS were collected in each case. A framework linkage map of chromosome 3A with 13 markers was prepared and used for QTL analysis. A major QTL (QPhs.ccsu-3A.1) was detected on 3AL at a genetic distance of ∼183 cM from centromere, the length of the map being 279.1 cM. The QTL explained 24.68% to 35.21% variation in individual environments and 78.03% of the variation across the environments (pooled data). The results of the present study are significant on two counts. Firstly, the detected QTL is a major QTL, explaining up to 78.03% of the variation and, secondly, the QTL showed up in all the six environments and also with the pooled data, which is rather rare in QTL analysis. The positive additive effects in the present study suggest that a superior allele of the QTL is available in the superior parent (SPR8198), which can be used for marker-aided selection for the transfer of this QTL allele to obtain PHS-tolerant progeny. It has also been shown that the red-coloured grain of PHS tolerant parent is not associated with the QTL for PHST identified during the present study, suggesting that PHS tolerant white-grained cultivars can be developed.Electronic Supplementary Material Supplementary material is available for this article at     

玉米株高和穗位高的QTL定位

摘要: 用玉米自交系掖478和丹340构建了397个F_2:3家系群体, 利用双亲间多态的150个共显性SSR标记绘制分子连锁图谱, 图谱总长度1 478.7 cM, 标记间平均距离10.0 cM。在5种环境下对株高和穗位高性状进行鉴定, 复合区间作图法检测到21个株高QTL和25个穗位高QTL。于第1和5染色体的umc2025－umc1035及umc1822－bnlg1118区域检测到平均贡献率分别为12.2%和14.9%的株高QTL。于第3和5染色体的phi029－umc1102及phi109188－bnlg1118区域检测到平均贡献率达到10.2%和22.8%的穗位高QTL。第5染色体的Bin5.05－5.07区域可能存在控制株高和穗位高的主效QTL。株高和穗位高的基因作用方式主要是加性和部分显性效应。文章还分析了群体大小及试验环境对株高和穗位高QTL定位结果的影响