小麦白粉病成株抗性和抗倒伏性及穗下节长度的QTL定位

由小麦品种花培3号和豫麦57杂交获得了DH群体168个株系, 利用305个SSR标记对白粉病成株抗性、抗倒伏性和穗下节长度进行了QTL定位研究。DH群体及两亲本于2005年和2006年种植于山东泰安, 2006年种于安徽宿州。利用基于混合线性模型的QTLNetwork 2.0软件, 共检测到12个加性效应位点和10对上位效应位点。在4D染色体上控制白粉病成株抗性的qApr4D, 贡献率为20.0%, 在各环境中稳定表达, 其抗病等位基因来源于抗病亲本豫麦57; 在7D染色体上控制小麦穗下节长度的qIlbs7D, 贡献率为12.9%, 在各环境中稳定表达。加性效应和上位效应对小麦白粉病成株抗性、抗倒伏性和穗下节长度的遗传起重要作用, 并且基因与环境常常具有互作效应。以上两个QTL可分别用于小麦白粉病成株抗性和穗下节长度的分子标记辅助选择。     

小麦籽粒产量及穗部相关性状的QTL定位

由小麦品种花培3号和豫麦57杂交获得DH群体168个株系,种植于3个环境中,利用305个SSR标记对籽粒产量和穗部相关性状(穗长、穗粒数、总小穗数、可育小穗数、小穗着生密度、千粒重和粒径)进行了QTL定位。利用基于混合线性模型的QTLNetwork 2.0软件,共检测到27个加性效应和13对上位效应位点,其中 8个加性效应位点具有环境互作效应。相关性高的性状间有一些共同的QTL位点,表现出一因多效或紧密连锁效应。5D染色体区段Xwmc215–Xgdm63,检测到控制籽粒产量、穗粒数、总小穗数、可育小穗数和小穗着生密度5个性状的QTL位点,各位点的遗传贡献率较大且遗传效应方向相同,增效等位基因均来源于豫麦57,适用于分子标记辅助育种和聚合育种。控制千粒重与穗粒数的QTL位于染色体不同区段,有利于实现穗粒数与粒重的遗传重组。     

玉米籽粒深度等穗部性状QTL定位及上位性效应分析

[目的]为从分子水平上解析玉米穗长、穗粗和籽粒深度的遗传基础,[方法]以豫82×豫87-1衍生的一套重组近交系(RIL)群体为材料,通过多点的表型鉴定,采用SNP标记构建的遗传连锁图谱进行QTL定位及上位性效应分析,[结果]结果表明,3个穗部性状共检测到的18个QTL,这些QTL与环境的互作均未达到显著水平,说明所检测到的控制穗长、穗粗和粒深的QTL在三个环境间的遗传是稳定的。在这些QTL中,位于第1染色体调控穗长的qEL1-1和第2染色体调控粒深的qKD2-1、qKD2-2,分别解释表型变异的6.11%和10.22%、8.88%,说明这三个主效QTL是调控穗部性状的重要区域。上位性效应分析结果表明,共检测到三对位点间互作,互作效应为1.23%~6.54%,其中有一对位点属于显著QTL位点对互作。[结论]由此可见,上位性互作效应在穗部性状的遗传中占有一定的比例,但作用比重相对较小。这些研究结果为进一步图位克隆相关关键基因及分子标记辅助育种提供了重要的参考价值。     

2种环境下水稻灌浆期穗长的动态遗传研究

为了探知水稻穗长的动态遗传机制,利用由穗型差异大的水稻品种Milyang 46和FJCD建立的包含130个株系的F10重组自交系,测定福建武夷山和莆田环境下穗长灌浆期的动态变化值,并进行了QTL定位及其互作研究。结果检测到35个加性QTL,16个加性×环境互作QTL,1对加加上位性效应。QTL定位分析检测到的35个加性QTL,位于1、2、4、5、7、8、9、10、11号染色体上,对表型变异贡献率0.5%~16.52%。环境互作分析检测到的16个GE互作位点,分布在水稻1、2、3、4、5、7、8、9、11号染色体上,大部分为微效QTL。武夷山环境中,还检出1对加加上位性QTL,对表型变异贡献率达到33.14%。此研究一定程度上揭示了穗长遗传机制,为水稻育种提供了依据。     

利用永久F2群体定位小麦株高的QTL

为研究小麦株高的遗传机制,利用DH群体构建了一套包含168个杂交组合的小麦永久F₂群体, 并于2007年种植于山东泰安和山东聊城。构建了一套覆盖小麦21条染色体的遗传连锁图谱并利用该图谱的324个SSR标记对小麦株高进行QTL定位研究,使用基于混合线性模型的QTLNetwork 2.0软件进行QTL分析。在永久F₂群体中定位了7个株高QTL,包括4个加性QTL,一个显性QTL,一对上位性QTL,共解释株高变异的20%,其中位于4D染色体的qPh4D,具有最大的遗传效应,贡献率为7.5%;位于2D 染色体显性效应位点qPh2D,可解释1.6%的表型变异;位于5B~6D染色体上位效应位点,可解释1.7%的表型变异。还发现加性效应、显性效应和上位效应对小麦株高的遗传起重要作用,并且基因与环境具有互作效应,结果表明利用永久F₂群体进行QTL定位研究的方法有助于分子标记辅助育种。     

大豆叶片性状和叶绿素含量QTL间的上位性和环境互作效应

以丰产性好、抗旱力强的栽培大豆晋豆23为母本,山西农家品种半野生大豆灰布支黑豆为父本杂交衍生的447个RIL作为供试群体。将亲本及447个家系分别于2011、2012和2013年采用随机试验种植,按照标准测量叶长、叶宽和叶柄长3个性状,并于2012年8月1日和8月8日和2013年8月2日和8月9日各测量1次叶绿素含量。采用QTLNETwork 2.0混合线性模型分析方法和主基因+多基因混合遗传分离分析法,对大豆叶片性状和叶绿素含量进行遗传分析和QTL间的上位性和环境互作效应研究。结果表明,叶长受2对加性-加性×加性上位性混合主基因控制,叶宽受3对等效主基因控制,叶柄长受4对加性-加性×加性上位性主基因控制,叶绿素含量受4对加性主基因控制;检测到10个与叶长、叶宽、叶柄长和叶绿素含量相关的QTL,分别位于A1、A2、C2、H_1、L和O染色体。其中2个叶长QTL分别位于C2和L染色体,是2对加性×加性上位互作效应及环境互作效应QTL;3个叶宽加性与环境互作QTL分别位于A2、C2和O染色体;2个叶柄长QTL分别位于L和O染色体;3个叶绿素含量QTL分别位于A1、C2和H_1染色体。叶片性状和叶绿素含量的遗传机制较复杂,加性效应、加性×加性上位互作效应及环境互作效应是大豆叶片性状和叶绿素含量的重要遗传基础。建议大豆分子标记辅助育种中,一方面要考虑起主要作用的QTL,另一方面要注重上位性QTL的影响,这对于性状的遗传和稳定表达具有积极的意义。     

小麦苗期光合作用及其相关性状的QTL分析

将小麦品种花培3号和豫麦57构建的DH群体的168个株系及其亲本,盆栽于两个环境中,利用324个SSR标记位点构建遗传图谱,对单叶净光合速率及相关参数、叶绿体色素含量和叶绿素荧光参数进行QTL定位和分析。利用基于混合线性模型的QTLNetwork 2.0,共检测到17个加性效应和20对上位性效应位点,其中所有加性效应位点和16对上位性效应位点具有环境互作效应。相关性较高的性状间有一些共同的QTL,表现出一因多效或者紧密连锁效应。在5D染色体上的Xwmc215至Xgdw63区段,检测到控制叶绿素a、叶绿素b和类胡萝卜素含量的3个主效QTL,各位点的遗传效应贡献率较大,增效基因均来源于花培3号,适用于分子标记辅助选择和聚合育种。另外,该区段与控制单叶净光合速率(Pn)、气孔导度(Gs)、胞间CO2浓度(Ci)和胞间CO2浓度与胞外CO2浓度比值(Ci/Cr)的QTL的定位区间相近。位于5B染色体控制胞间CO2浓度的QTL是个微效基因,但是QTL与两种环境的互作效应表现的遗传贡献比较大。     

陆地棉中G6主要性状主效和上位性QTL分析

利用基于混合线性模犁的复合区间作图法对重组近交系(recombinant inbreed line,RIL)"中G6"进行QTL定位,生育期性状共定位了主效QTL位点5个,上位性QTL位点4对,纤维品质性状定位了主效QTL位点1个,上位性QTL位点6对,产量性状定位了主效QTL位点3个,上位性QTL位点5对.其中定位的果枝始节、吐絮期、上半部平均长度、衣分的主效QTL位点均距离最近标记1 cM以下,这有利于在育种实践中主效QTL跟踪检测.定位的霜前花率主效QTL位点具有较高的加性效应和遗传贡献率,应进行QTL精细定位、图位克隆,将会对早熟性育种工作有一定的推动意义.定位的马克隆值、衣分和予指总的遗传贡献率均在30%以上,对性状特征均影响显著.对主效及上位性QTL位点进行遗传效应分析,验证了前人有关数量性状遗传符合主基因与多基因混合遗传的论断,认为此模型是研究数量性状遗传的有效途经;对主效及上位性QTL位点进行A、D亚基因组定位,并对主效及上位性QTL位点在A、D亚基因组上的分布及互作方式进行了详细的分析.全文认为上位性QTL位点和主效QTL位点一样在物种遗传变异和聚合育种中起着重要作用.     

玉米叶型相关性状QTL定位及上位性效应分析

为了研究玉米叶型性状的QTL以及它们的上位性效应,本研究以豫82为母本、豫87-1为父本发展而成的一套重组自交系群体为材料,通过一年3点的表型鉴定,利用遍布玉米全基因组的SNP标记,对玉米叶向值、叶夹角、叶长、叶高点长和叶宽5个性状进行QTL定位及上位性效应分析。定位结果表明,5个性状共定位到24个QTL,贡献率6.89%~13.43%,所有主效QTL均与环境没有显著的互作效应。其中,q LA1-1、q LA8-1、q Lf2-1、q Lf5-1、q LOV3-1、q LL2-1、q LL4-1、q LW1-1和q LW3-1的贡献率均在10%以上,说明这些位点对叶型的影响较为重要。上位性效应分析结果表明,共检测有15对上位性互作位点表现出显著性,并且所有的互作位点对都发生在不同染色体之间;多数互作位点对,均发生在未显著性效应的位点之间;所有的上位性互作位点对间的互作效应与环境也无显著的互作效应,这表明叶型相关性状的加性效应和上位性效应,均不受地点间环境条件的影响。本研究为进一步图位克隆相关关键基因及分子标记辅助育种改良玉米株型提供了重要的参考价值。     

寒地粳稻发芽期和芽期的耐冷性QTL定位

为定位水稻发芽期和芽期耐冷性的加性QTL和上位性QTL,本试验以粳稻品种空育131和东农422构建的F:代重组自交系(RIL)190个家系为作图群体,利用104个SSR标记构建遗传连锁图谱,利用完备区间作图法分别对低温发芽力和芽期耐冷性进行QTL定位并分析其加性效应和上位性效应。结果检刚到控制芽期耐冷性的1个加性QTL位于4号染色体上,贡献率为16.84%;17个控制低温发芽力的加性QTL分别位于第1,2,3,6,7,9,12染色体上,贡献率为5.64%~35.67%;控制芽期耐冷性的上位性QTL2对,累积贡献率19.3%;控制发芽期耐冷性的上位性QTL33对,各性状累计贡献率介于18.35%~91.08%,分别控制第7,10,11,15天的发芽率和平均发芽天数的表达,累积贡献率分别为87.88%,87.38%,91.08%,78.68%和18.35%。上位性在水稻发芽期和芽期耐冷性遗传中作用重大,因此,在分子标记育种中加性QTL和上位性QTL是很重要的。     

QTL analysis for wheat falling number in a recombinant inbred line population segregated with 1BL/1RS translocation in a rainfed agricultural area of China

Falling number (FN) is an inner quality trait in wheat (Triticum aestivum L.) ultimately determining the end use of wheat kernels. In this 3-year study, 171 recombinant inbred lines derived from Chuannong17 (a 1BL/1RS tranlocation parent) × Mianyang11 were planted in the Sichuan Basin, a rainfed agricultural area in southwestern China. In this climate, we found that FN had significant differences between 1BL/1RS translocation lines and non-1BL/1RS translocation lines in two of the 3 years and the heavy fluctuation of rainfall and temperature resulted in decreasing FN in grain filling period. We used 191 simple sequence repeats markers to construct a genetic linkage map and then detected 11 additive effect FN quantitative trait loci (QTL) on chromosomes 2B, 3D, 4A, 4D, 6B and 7D, explaining 5.48–31.91% of the phenotypic variance. The FN QTL on chromosomes 4A, 4D and 6B were major or stable and detected at least in 2 years, whereas the Qfn.sicau-3D.1 in 2015 year explained the maximum phenotypic variation (about 31.91%). Furthermore, FN QTLs additive and epistatic effects as well as their interactions with environment were estimated by a mixed linear model approach. We found that the additive effect QTLs had no significant additive × environment interaction, while the paired QTLs had significant additive × additive epistatic effects however none had a significant additive × additive epistasis × environment interaction effect, excluding the paired QTLs Qfn.sicau-3B/Qfn.sicau-5B.     

A comparison of grain protein content QTLs and flour protein content QTLs across environments in cultivated wheat

The protein content of cultivated wheat (Triticum aestivum L.) is an important determinant factor of the nutritional value of the grain and the technological properties and rheological properties of flour. In order to examine the genetic basis of protein content, we searched for grain protein content quantitative trait loci (QTLs) and flour protein content QTLs in a newly developed doubled haploid (DH) line and identified the genetic correlation between grain protein content and flour protein content in the same DH population. Both the DH population and its parental lines were evaluated for grain protein content and flour protein content in three field trials. Four additive effect QTLs, two pairs of epistatic QTLs, and two QTLs × environment (QE) interaction for grain protein content were identified. The model explained 51.52% of the phenotypic variation (PVE), with epistatic effects being better explained by the higher PVE than additive effects. Four additive effect QTLs, five pairs of epistatic QTLs, and one QE were detected for flour protein content. The model explained 45.8% of the PVE. Of the 15 QTLs identified, three additive QTLs and one pair of epistatic QTLs were determined for both grain protein content and flour protein content; of these, the QTLs for protein content were considered to be more 'stable' than those detected for only grain protein content or for only flour protein content. The data reported here may be useful for manipulating the QTLs for protein content by marker-assisted selection in future wheat breeding programs.     

QTL analysis of textural property traits for Chinese northern-style steamed bread

Quantitative trait loci (QTLs) influencing textural properties (hardness, adhesiveness, springiness, cohesiveness, gumminess, chewiness, and resilience)of wheat for Chinese northern-style steamed bread were studied using a doubled haploid (DH) population containing 168 lines derived from a cross between elite Chinese wheat cultivars Huapei 3 and Yumai 57 (Triticum aestivum L.). The DH population and parents were grown in 2007 and 2008 in Tai’an and 2008 in Suzhou. QTL analyses were performed using the software QTL Network version 2.0 and IciMapping v2.2 based on the mixed linear model. Thirty nine putative QTLs were detected on 14 chromosomes: viz. 1A, 2A, 3A, 4A, 6A, 1B, 2B, 3B, 5B, 6B, 7B, 5D, 6D, and 7D, and single QTLs explained 3.91–35.17% of the phenotypic variation. Eight pairs of QTLs with epistatic effects and/or epistasis × environment (AAE) effects were detected for adhesiveness, resilience, hardness, and cohesiveness on chromosomes 2A, 1B and 3D. Several co-located QTLs with additive effects were detected on chromosomes 2B, 5D, 6A, 3A, 3B and 6D. Two clusters of three QTLs for steamed bread textural properties (chewiness, gumminess, and hardness) and for adhesiveness, cohesiveness and resilience were detected on chromosome 2B. Two co-located QTLs with epistatic effects were detected on chromosomes 1B and 3A. Both additive effects and epistatic effects were important for Chinese steamed bread textural properties, which were also subject to environmental modifications. The information obtained in this study will be useful for manipulating QTLs determining Chinese steamed bread textural properties by molecular marker-assisted selection.     

Molecular genetic analysis of flour color using a doubled haploid population in bread wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Flour color is an important trait in the assessment of flour quality for the production of many end products. In this study, quantitative trait loci (QTLs) with additive effects, epistatic effects, and QTL × environment (QE) interactions for flour color in bread wheat (Triticum aestivum L.) were studied, using a set of 168 doubled haploid (DH) lines derived from a Huapei 3 × Yumai 57 cross. A genetic map was constructed using 283 simple sequence repeats (SSR) and 22 expressed sequence tags (EST)-SSR markers. The DH and parents were evaluated for flour color in three environments. QTL analyses were performed using QTLNetwork 2.0 software based on a mixed linear model approach. A total of 18 additive QTLs and 24 pairs of epistatic QTLs were detected for flour color, which were distributed on 19 of the 21 chromosomes. One major QTL, qa1B, closely linked to barc372 0.1 cM, could account for 25.64% of the phenotypic variation of a* without any influence from the environments. So qa1B could be used in the molecular marker-assisted selection (MAS) in wheat breeding programs. The results showed that both additive and epistatic effects were important genetic basis for flour color, and were also sometimes subject to environmental modifications. The information obtained in this study should be useful for manipulating the QTLs for flour color by MAS in wheat breeding programs. Kun-Pu Zhang and Guang-Feng Chen contributed equally to this study.     

利用“永久F2”群体进行小麦幼苗根系性状QTL分析

为了研究小麦苗期根系性状的遗传,以小麦品种花培3号和豫麦57的杂交DH群体组配了一套含168个杂交组合的“永久F₂”群体。利用WinRHIZO根系分析系统测定四叶一心期小麦水培幼苗根系总长度、直径、表面积、体积、根尖数、最大根长、茎叶干重、根干重及根茎干重比9个性状。采用复合区间作图法分析幼苗根系8个性状的QTL,定位了7个加性效应QTL和12对上位性互作QTL,包括加性效应、显性效应,加加互作、加显互作和显显互作,分布在1A、1D、2A、2B、2D、3A、3B、5D、6D和7D染色体上,单个QTL可解释0.01%~11.91%的遗传变异。在染色体2D上XWMC41至XBARC349.2区间检测到同时控制总根长和根干重的一个QTL。上位性对苗期根系生长发育有重要作用。试验结果表明,苗期根系性状的遗传机制较复杂, 因此在育种中要综合考虑根系各性状之间的关系,保证根系协调统一、发达健壮。     

Identification of quantitative trait loci (QTLs) for seed protein concentration in soybean and analysis for additive effects and epistatic effects of QTLs under multiple environments

Soybean protein concentration is a key trait driver of successful soybean quality. A recombination inbred lines derived from a cross between ‘Charleston’ and ‘Dongnong594’, were planted in three environments across four years in China. Then, the genetic effects were partitioned into additive main effects, epistatic main effects and their environment interaction effects by using composite interval mapping, multiple interval mapping and composite interval mapping in a mixed linear model. Forty‐three quantitative trait loci QTLs were identified on 17 of 20 soybean chromosomes excluding Ch 7, Ch 8 and Ch 17. Two QTLs showed a good stability across multiple environments, qPRO20‐1 was detected under four environments, which explained 4.4–9.95% phenotypic variances and the allele was from ‘Charleston’ among four environments. qPRO7‐5 was detected under three environments, which explained 7.2–14.5% phenotypic variances and the allele was from ‘Dongnong 594’, three pathway genes of protein biosynthesis were detected in the interval of qPRO7‐5. The additive main‐effect QTLs contributed more phenotypic variation than the epistasis and environmental interaction. This indicated that it is feasible by marker‐assisted selection to improve soybean protein concentration.     

Mapping of quantitative trait loci (QTLs) for rice protein and fat content using doubled haploid lines

Rice protein content (RPC) and rice fatcontent (RFC) are two important componentsof rice nutritional quality. In order toexamine the genetic basis of these traits,a doubled haploid (DH) population and anRFLP linkage map consisting of 232 markerloci were used to search QTLs for thetraits with the computer programQTLMapper1.0. This program is based onmixed linear models and allows simultaneousmapping of both main-effect and digenicepistastic QTLs in a DH population. RPC andRFC were evaluated based on a dry weightbasis of head rice by the Kjeldahl andSoxhlet methods respectively. A total offive main-effect QTLs for RPC wereresolved. The five QTLs collectivelyexplained 74% of the phenotypic variationwith LOD=15.2. Among these QTLs, the majorQTL qRPC-5 with the largest effectwas mapped in the interval of RG435-RG172aon chromosome 5. It accounted for 35% ofthe phenotypic variation with a LOD of16.7. At this locus the allele from theparent `Gui 630' increased RPC by 1.32%.The second QTL qRPC-7 was mapped inthe interval ZG34B-G20 on chromosome 7. Itexplained 23% of the phenotypic variancewith a LOD of 6.1. Its positive alleles,also from the parent `Gui 630', increasedRPC by 1.05%. As for the remaining threeQTLs, their additive effects wererelatively small and their positive alleleswere all inherited from the parent `02428'.Three QTLs for RFC were mapped onchromosome 1, 2 and 5 respectively. Theycollectively explained 44% of thephenotypic variation. Among these loci,QTLs qRFC-2 and qRFC-5 withlarger effects individually accounted for24% and 26% of the phenotypic variancerespectively. At QTL qRFC-2 thepositive allele came from the parent `Gui630', while at QTL qRFC-5 thepositive allele from the parent `02428'.The fact that both parents possess thepositive alleles at the QTLs for the twotraits provides an appropriate explanationfor the large transgressive segregationobserved in the DH lines. Furthermore, onlyone pair of epistatic loci explaining only5.1% of the phenotypic variance wasdetected for RPC, whereas seven pairs ofepistatic loci were resolved for RFC. Thetotal absolute effects of these RFCinteractions amounted to 0.97% which ismuch larger than that (0.42%) of the threemain-effect QTLs for the trait. Alongwith the observation that RPC showed a highheritability (78%), these resultsdemonstrate that RPC in the DH populationcould be mainly controlled by relativelyfew QTLs with large main-effects. As forRFC, epistatic interactions might be aneven more important component of thegenetic basis and the segregation of the DHlines could be largely explained by a fewmain-effect QTLs and many epistatic loci.In addition, a highly negative correlation(r = –0.45) between RPC and RFC inthe DH population was observed. Thiscorrelation could be largely explained bythe linkage of qRPC-5 and qRFC-5 with the directions of effectsopposite and the co-locations of the twoepistatic loci for RFC respectively withtwo different main-effect QTLs for RPC. Theinformation reported in the present papermay be useful for improving ricenutritional quality by means ofmarker-assisted selection.     

Detection of QTLs for bread‐making quality in wheat using a recombinant inbred line population

Whereas gluten fraction accounts for 30–60% of the variation in wheat bread‐making quality, there remains substantial variation determined by non‐gluten factors. The objective of this study was to detect new loci for wheat quality. The genetics of sodium dodecyl sulphate‐sedimentation volume (Ssd), grain hardness (GH), grain protein content, wet gluten content (WGC) and water absorption (Abs) in a set of 198 recombinant inbred lines derived from two commercial varieties was studied by quantitative trait loci (QTL) analysis. A genetic map based on 255 marker loci, consisting of 250 simple sequence repeat markers and five glutenin loci, Glu‐A1, Glu‐B1, Glu‐D1, Glu‐B3 and Glu‐D3, was constructed. A total of 73 QTLs were detected for all traits. A major QTL for GH was detected on chromosome 1B and its relative contribution to phenotypic variation was 27.7%. A major QTL for Abs on chromosome 5D explained more than 30% of the phenotypic variation. Variations in Ssd were explained by four kinds of genes. Some QTLs for correlated traits mapped to the same regions forming QTL clusters or indicated pleiotropic effects.