陆地棉产量相关性状的QTL定位

中棉所28和湘杂棉2号分别是以中棉所12×4133和中棉所12×8891配制而成的两个陆地棉强优势杂交种。以其F₂为作图群体,筛选6000多对SSR引物,利用两群体间27个共有多态位点,通过JoinMap 3.0软件整合了一张包含245个多态位点、全长1847.81 cM的遗传图谱。利用Win QTLCart 2.5复合区间作图法分别对两群体8个产量相关性状在F₂和F_2:3中进行QTL定位,在中棉所28群体多环境平均值的联合分析中检测到16个QTL,三环境分离分析中检测到43个QTL;在湘杂棉2号群体分别检测到20个和66个QTL。在A3、D8、D9等染色体上有QTL成簇分布现象,同时在两个群体中发现一些不受环境影响且稳定遗传的QTL。对考察的8个性状在两个群体中发现12对共有QTL,控制果枝数、衣分和籽指的QTL增效基因位点均来源于共同亲本中棉所12。综合分析推测中棉所12的育种价值主要是通过提高后代的结铃性来实现的。研究结果为棉花产量性状的分子设计育种提供了有用的信息。     

陆地棉早熟基因来源的遗传分析

棉花早熟性相关的性状多为复杂的数量性状,是由多个基因和环境共同作用的结果,其遗传基础研究比较困难。利用连锁作图和关联分析方法,对目标性状进行基因定位,找出与性状相关联的位点,为解析复杂性状的基因来源提供了新的手段。本文分别以早熟亲本新陆早8号和新陆早10号为母本,以陆地棉标准系TM-1为父本构建F₂作图群体,利用在亲本间筛选出的多态性SSR引物,通过JoinMap 3.0软件构建了2张遗传图谱,以Win QTLCart 2.5复合区间作图法在F₂~F_2:3中定位到控制全生育期、苗期、蕾期、花铃期和霜前铃数等早熟性相关性状的37个QTL。控制早熟性的有利等位基因多来自早熟祖先611波和金字棉。多数性状在两类材料中由不同的基因控制,且以加性遗传为主。在由43个陆地棉品种材料构成的自然群体中通过关联分析检测到54个与这些早熟性相关性状极显著关联的位点。研究表明连锁作图和关联分析的检测结果具有较高的可比性。本研究为早熟陆地棉聚合改良以及分子标记辅助育种打下了基础。     

QTLs conferring FOV 7 resistance detected by linkage and association mapping in Upland cotton

Fusarium wilt is a worldwide disease that affects cotton production. Molecular markers tightly linked to resistance genes can be used for marker-assisted and/or genomic selection. We performed both family-based linkage mapping and population-based association mapping (AM) to detect quantitative trait loci (QTLs) conferring resistance against Fusarium oxysporum f. sp. vasinfectum race 7 (FOV 7) in Upland cotton. To identify QTLs underlying FOV 7 resistance by linkage mapping, three Upland cotton cultivars/lines, Xuzhou 142, Yumian 21 and Shang 9901, were used to obtain the composite cross population, designated as Xuzhou 142/Yumian 21//Xuzhou 142/Shang 9901. A linkage map containing 185 simple sequence repeat loci and 40 linkage groups was constructed with an average distance of 7.5 cM between adjacent markers. Seven QTLs were detected by linkage mapping, explaining 2.9–6.6 % of the total phenotypic variance. We also performed marker–trait AM with the MLM model (Q + K) in a panel composed of 356 Upland cotton cultivars. In total, 27 loci were significantly associated with FOV 7 resistance at the α = 0.01 level (?log₁₀ P ≥ 2), which were distributed on 16 chromosomes and explained 1.48–12.99 % of phenotypic variation. Three of the 7 QTLs identified by linkage mapping could be detected in AM. We identified the favorable allele for each of the 27 associated loci and investigated the number of favorable alleles in each accession. The results should increase our understanding of the genetic basis of FOV resistance and facilitate future resistance breeding in Upland cotton.     

Dynamic QTL analysis and validation for plant height using maternal and paternal backcrossing populations in Upland cotton

Plant height determines plant biomass yield, harvest index and economic yield. We analyzed quantitative trait loci (QTL) and gene action controlling plant height. We generated the maternal and paternal testcrossing (TC/M and TC/P) populations based on a recombinant inbred line population. Data for plant height at t1, t2, t3, t4 or t5 stages were collected over 2 years from 3 TC/M field trials and 2 TC/P field trials. At single-locus level, 32 QTLs at five stages and 24 conditional QTLs at four intervals were detected, and 14 QTLs shared in different years or populations or stages. Plant height displayed dynamic characteristics through expression of QTLs. A total of 21 novel QTLs were detected and 11 QTLs validated the previous results. And 19 QTLs explained over 10% of phenotypic variation, such as qPH-Chr9-2, qPH-Chr19-4 and qPH-Chr22-4. The region of NAU5330-NAU1269 on chromosome 19 may be a desired target for genetic improvement of plant height in Upland cotton. In addition, five and eight heterotic loci were identified in TC/M and TC/P populations, respectively. Additive, partial dominance and overdominance effects were observed in both TC populations. We also identified 43 epistatic QTLs and QTLs by environment interactions by inclusive composite interval mapping method. Taken together, additive, partial dominance and overdominance effects together with epistasis explained the genetic basis of plant height in Upland cotton.     

利用海岛棉染色体片段导入系定位衣分和籽指QTL

以染色体片段导入系IL-15-5和IL-15-5-1构建的F2和F2:3分离群体,利用SSR标记对数量性状衣分和籽指QTL进行了定位。应用复合区间作图法分析两个组合的774个F2单株和F2:3家系衣分和籽指,检测到2个衣分的QTL,1个籽指的QTL。衣分QTLqLP-15-1在两世代中都被检测到,位于相同的分子标记置信区间JESPR152～NAU3040,置信的遗传距离分别为5.40cM和3.20cM;qLP-15-2只在F2:3中被检测到,位于分子标记NAU5302～NAU2901之间,置信的遗传距离为0.08cM。籽指QTLqSI-15-1在F2和F2:3中都被检测到,分别位于分子标记NAU2814～NAU3040和JESPR152～NAU3040,置信的遗传距离分别为6.70cM和5.70cM。利用染色体片段导入系能准确地定位产量组分的QTL,为棉花产量的分子设计育种奠定基础。     

陆地棉重组近交系产量及其构成因素的QTL分析

利用爱字棉1517×德州047重组近交系(recombinant inbred lines, RIL)中G6群体构建的SSR遗传连锁图谱及基于混合线性模型的复合区间作图法对QTL进行定位,并对主效QTL,加性×加性上位性QTL及与环境互作效应进行分析,为利用分子聚合方法提高产量提供理论依据。对2006年、2008年以及2009年的产量性状进行分离分析,检测到24个不同年份的主效QTL,其中相关于单株籽棉、单株皮棉、衣分、子指以及单株铃数的分别检测到1个不同年份稳定存在的主效QTL;对3年的产量性状作环境因子联合分析,检测到14个主效QTL,其中6个与环境互作,检测到20对加加上位性QTL,其中7对与环境互作。不同年份检测的稳定且受环境影响小或不受环境影响的与近处标记紧密连锁的主效QTL可用于分子标记辅助选择,以提高育种的效率。     

New QTLs for lint percentage and boll weight mined in introgression lines from two feral landraces into Gossypium hirsutum acc TM‐1

Overuse of a small number of Upland cotton cultivars has narrowed cotton's genetic base, leading to major difficulties in developing cotton cultivars with diverse genetic backgrounds that are able to adapt to adverse conditions. To effectively broaden the genetic base, chromosome introgression lines (ILs) were developed, where TM‐1, the genetic standard of Upland cotton, was used as the common recipient and its two feral landraces, TX‐256 and TX‐1046, were used as the donors. A total of 115 ILs, with an average segment length of 11.15 cM, were first developed via intraspecific hybridization by marker‐assisted selection (MAS) in BC₃F₂ generations, spanning 3887.75 cM of the cotton genome. Association analysis showed that 63 markers were found to be associated with boll weight (BW), lint percentage (LP) and seed index. The percent of phenotypic variance explained by 148 QTLs detected was 4.12% on average. Eleven and five new QTLs for BW and LP (one stable QTL identified for LP in all environments) were detected, respectively, which can be used for efficiently pyramiding favourable alleles into one cultivar by MAS.     

Mapping QTLs of traits contributing to yield and analysis of genetic effects in tetraploid cotton

Fiber yield and yield components – including lint index (LI), seed index (SI), lint yield (LY), seed cotton yield (SCY) and number of seeds per boll (NSPB) – were investigated on the farm of Huazhong Agricultural University in a population of 69 F₂ individuals and corresponding F_2:3 families derived from a cross between high-fiber-yield Gossypium hirsutum CV Handan 208 and a low-fiber-yield Gossypium barbadense CV Pima 90. On the basis of the genetic map constructed previously from the same population by Lin et al. (Plant Breed., 2005), quantitative trait locus (QTL) analysis was performed with the software QTL Cartographer V2.0 using composite interval mapping method (LOD ≥ 3.0). A total of 21 QTLs were identified, which were located in 15 linkage groups. The number of QTLs per trait ranged from one to seven. Of these QTLs detected, one affecting LI explained 24.3% of phenotypic variation (PV), five influencing SI explained 16.15–39.21% of PV, seven controlling LY explained 13.01–28.35% of PV, and two controlling SCY explained 22.76 and 39.97% of PV, respectively. Simultaneously, the detected six QTLs for NSPB were located on five linkage groups, which individually explained 28.01–38.32% of the total phenotypic variation. The results would give breeders further insight into the genetic basis of fiber yield.     

Identification of quantitative trait loci underlying seed protein and oil contents of soybean across multi‐genetic backgrounds and environments

Seed protein and oil contents are important quantitative traits in soybean. Previously, quantitative trait loci (QTL) associated with seed protein and oil were mostly identified in single genetic background. The objective of this work was to identify QTL and their epistatic effects underlying seed protein and oil contents in three recombinant inbred line populations (two of them used one common female parent) across eight environments by composite interval mapping. Forty QTL underlying protein content and 35 QTL underlying oil content were identified. Among them, nine were universal QTL underlying protein content and four were universal QTL underlying oil content. Epistatic interactions between QTL underlying seed protein/oil and different genetic backgrounds were detected. Different pairs of epistatic interactions were observed in diverse genetic backgrounds across multi‐environments. Common marker intervals were observed to simultaneously underlie seed protein and oil contents with different epistatic interactions. The results in this study suggested that a specific genotype with high oil content and low protein content might significantly affect the selection of soybean lines for high seed protein.     

Effects of the dominant glandless gene Gl2e on agronomic and fibre characters of Upland cotton

Seven pairs of near‐isogenic lines (glandless vs. glanded) and the recurrent parents were used to determine the effects of the dominant glandless gene from ‘Hai 1’(Gossypium barbadense) on agronomic, fibre, and seed characters in Upland cotton, Gossypium hirsutum, backgrounds. The results showed that there were no apparent linkage associations of the glandless gene on most agronomic, fibre and seed characters of Upland cotton, except for seed quality. The glandless line derived from ‘Liaomian 7’had significantly more protein (489.6 g/kg), and that from H237 had significantly more oil (362.4 g/kg) and had the largest oil index (2.70 g) and protein index (3.03 g). The gossypol content of seed in dominant glandless lines in Upland cotton was very low (<0.04 g/kg). Therefore, it is suggested that the glandless gene can play an important role in breeding glandless or low seed‐gossypol Upland cotton cultivars.     

海陆渐渗系棉花吐絮期叶绿素含量、荧光参数及相关性状的QTL定位分析

以海陆渐渗系13-1×辽棉12组配的195个单株的F2群体为作图群体,利用SSR(Simple sequence repeat)标记和Join Map3.0软件构建遗传连锁图谱,构建的遗传连锁图谱包含39个多态性标记、13个连锁群,该图谱总长1174.4 c M,覆盖棉花基因组的26.7%,利用Ici Mapping完备区间作图法对F2:3家系进行相关性状的QTL定位,共检测到30个叶绿素荧光参数、7个叶片干物质含量、6个叶面积指数、1个叶绿素含量的QTL位点,分布在8条染色体上,在同一染色体共标记区间内存在多个性状的QTL,部分位点加性遗传效应来自同一亲本,与干物质含量、最大光化学效应相关的QTL位点在3条染色体上不同标记区间内重复出现,与叶面积指数、最大光化学效应相关的QTL位点在4条染色体上不同标记区间内重复出现,表现出遗传上的一因多效或基因连锁效应,可用于高光效聚合育种。     

白芝麻籽粒油脂、蛋白质及芝麻素含量QTL定位分析

芝麻籽粒油脂、蛋白质和芝麻素含量是芝麻品质育种的3个重要目标。为了解析其遗传机制并检测相关QTL,利用近红外谷物品质分析仪对一个包含224个株系的F9代重组自交系(RIL)群体在2年3个环境下的籽粒品质性状检测,结果表明,群体内株系间差异显著且呈典型正态分布,而同一环境不同重复间表现差异不显著。相关性分析显示,籽粒含油量与蛋白质含量显著负相关,籽粒含油量与芝麻素含量显著正相关,蛋白质含量与芝麻素含量显著负相关;利用该RIL群体已构建的高密度遗传图谱,采用基于混合线性模型的复合区间作图法(MCIM)检测到8个QTL,表型贡献率为0.41%~14.55%;采用多重区间作图法(MIM)检测到13个QTL,可解释5.2%~18.6%的表型变异。其中5个主效QTL被2种方法同时检测到且定位区间相同,2个主效QTL在2个或3个环境中被重复检测到。控制含油量的Qoc-5与芝麻素含量的Qsc-5位于LG5连锁群上的相同区段,加性效应均为正值;而控制蛋白质含量的Qpc-5也位于相邻位置,但加性效应为负值。LG2和LG1连锁群上也存在相似情况,反映品质性状相关QTL之间存在一因多效或紧密连锁。因此,在芝麻品质育种中选择高含油量可以兼顾高芝麻素,但应对蛋白质含量进行负向选择。     

四种不同QTL作图方法的比较研究

应用区间作图法(IM)、复合区间作图法(CIM)、基于混合线性模型的复合区间作图法(MCIM)和多重区间作图法(MIM)对水稻杂交组合（培矮64S×日本晴）F₂群体株高性状进行了QTL作图分析。结果表明，（1）在同一显著水平下(α=0.0023)，4种方法共发现10个QTLs，其中IM法7个，CIM法10个，MCIM法3个，MIM法1个。CIM法的发现能力最强。（2）CIM法发现了IM法发现的全部QTLs，和左端标记的距离也基本一致。（3）4种方法检测到了同一QTL，且共同检测到QTL的贡献率最大。（4）4种方法估计的QTL的平均加性效应ā和显性效应 无显著性差异，同一QTL在显性效应的方向上表现一致。（5）建议使用多种作图方法共同作图，并优先标定共同发现的QTL。     

QTL Mapping of Important Agronomic Traits on Chromosomes Showing Marker Segregation Distortion in Interspecific Backcross Cotton Populations

[Objective] The purpose of this study was to map QTLs for yield, maturity, and fiber quality traits of cotton interspecific hybrid populations and to mine favorable alleles from the cotton genome for QTL fine mapping, gene cloning, and molecular marker-assisted selection. [Method] Four BC₁F₁ populations, E(E3), E(3E), (E3)E, and (3E)E, were developed by crossing sea island cotton 3-79 ("3") and upland cotton 'Emian 22' ("E"), and with "Emian 22" as the recurrent parent. BC1F2 populations derived from BC1F1 populations were phenotyped to allow mapping of QTLs for yield-, maturity-, and fiber quality-related traits on chromosomes showing segregation distortion. [Result] A normal distribution test indicated that six fiber quality-related traits, except for the micronaire value in E (E3) and the short fiber ratio in all populations, followed a normal distribution pattern; in contrast, earliness-related traits were not normally distributed in all populations, which suggests that genotype-environment interactions have strong effects on maturity-related traits. Using composite interval mapping, 47 QTLs were detected on three chromosomes (2, 16, and 18): 15 in (E3)E, 13 in (3E)E, 12 in E(E3), and 7 in E(3E), with the phenotypic variation explained (PVE) ranging from 8.8%–30.9%. A total of 27 fiber-related QTLs were discovered, with the PVE ranging from 9.0%–30.9%. Five yield-related QTLs (PVE = 8.8%–17.4%) and 13 maturity-related QTLs (PVE = 9.4%–19.4%) were also identified. [Conclusion] Comparison analysis showed that most QTLs in our study were consistent with the MetaQTL, including QTLs for boll weight, fiber length, fiber length uniformity, lint percentage, and micronaire value on chromosome 2; QTLs for fiber length, fiber strength, and fiber length uniformity on chromosome 16; and QTLs for boll weight, date of boll opening, fiber length, fiber strength, fiber length uniformity, and micronaire value on chromosome 18. Several detected QTLs in our study were not found in the MetaQTL, such as QTLs for date of boll opening and lint percentage on chromosome 16 and a QTL for the date from seedling to flowering stages on chromosome 18. These newly identified QTLs may provide novel insights for cotton QTL analysis.     

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.     

Identification of quantitative trait loci with main and epistatic effects for plant architecture traits in Upland cotton (Gossypium hirsutum L.)

Plant architecture is important for cotton cultivation and breeding. In this study, two mapping generations/populations F₂ and F_2:3 in Upland cotton (Gossypium hirsutum L.), derived from ‘Baimian1’ and TM‐1, were used to identify quantitative trait loci (QTLs) for 10 plant architecture traits. A total of 55 main‐effect QTLs (M‐QTLs) were detected. Four common M‐QTLs, qTFB‐10(F₂/F_2:3) for total fruit branches, qFBL‐26b(F₂)/qFBL‐26(F_2:3) for fruit branch length, qFBA‐5(F₂/F_2:3) for fruit branch angle and qFBN‐26b(F₂)/qFBN‐26(F_2:3) for fruit branch nodes, were found. The synergistic alleles and the negative alleles can be utilized in cotton plant architecture breeding programmes according to specific breeding objectives. Altogether 54 pairs of epistatic QTLs (E‐QTLs) exhibiting the interactions of additive‐by‐additive (AA), additive‐by‐dominant (AD), dominant‐by‐additive (DA) and dominant‐by‐dominant (DD) were detected. The epistasis appeared to be an important contributor to genetic variation in cotton plant architecture traits. Therefore, the identified markers associated with E‐QTLs as well as M‐QTLs will be of importance in future breeding programmes to develop cotton cultivars exhibiting desirable plant architecture.     

不同遗传背景下陆地棉衣分和子指性状QTL定位

为陆地棉产量性状有关的分子标记辅助育种奠定理论基础,以高品质中长绒棉品种‘新陆早24号’为父本,转基因抗虫棉常规品种‘鲁棉研28号’和高产、优质棉花新品种‘冀棉516’为母本,构建F2和F2:3分离群体;利用7638对SSR引物对‘鲁棉研28号’和‘新陆早24号’进行多态性进行筛选,共获得225对多态性引物,对238个F2单株DNA扩增获得238个多态性标记位点,其中185个构建了包括44个连锁群,总长为1509.38 cM的遗传连锁图谱,标记间的平均距离为8.16 cM,覆盖棉花总基因组的33.91%。根据已有图谱的定位结果,40个连锁群与染色体建立联系。利用复合区间作图法定位‘鲁棉研28号’与‘新陆早24号’分离群体F2单株和F2:3家系的衣分和子指性状QTL,其中得到3个衣分和5个子指的QTL;根据定位结果,选择了14对SSR引物,分析‘冀棉516’与‘新陆早24号’的多态性,其中6个标记构建了两个连锁群。1个衣分和1个子指的QTL在两个群体中均检测到,这些共同QTLs为分子标记辅助育种奠定了基础。     

QTLs for uppermost internode and spike length in two wheat RIL populations and their affect upon plant height at an individual QTL level

Spike length (SL) is one of the most important components of spike morphology, and the uppermost internode represents an ideal organ to study the transportation system. We performed conditional and unconditional quantitative trait locus (QTL) mapping in two unrelated recombinant inbred line populations to precisely detect QTLs for uppermost internode length (UIL) and SL, and to dissect the genetic relationship between these two factors with plant height (PH). Both of the populations were derived from crosses with synthetic wheat. Ten repetitive QTLs for UIL and six environment-independent QTLs for SL were identified in this study, and twelve of these were completely independent of PH. Conditional QTL mapping analysis indicated that SL was more independent to PH than UIL was. The results indicated that the conditional QTL mapping method could evaluate PH component effects on PH, and thus accelerate the selection of suitable loci that improve commercial wheat morphology yet avoid changes to PH.     

Genetic detection of node of first fruiting branch in crosses of a cultivar with two exotic accessions of upland cotton

Flowering time has biological and agricultural significance for crops. In Upland cotton (Gossypium hirsutum L.), photoperiodic sensitivity is a major obstacle in the utilization of primitive accessions in breeding programs. Quantitative trait loci (QTLs) analysis was conducted in two F₂ populations from the crosses between a day-neutral cultivar Deltapine 61 (DPL61) and two photoperiod sensitive G. hirsutum accessions (T1107 and T1354). Node of first fruiting branch (NFB) was used to measure relative time of flowering. Different flowering time genetic patterns were observed in the two populations. Two QTLs were found across five scoring dates, accounting 28.5 (qNFB-c21-1) and 15.9% (qNFB-c25-1) of the phenotypic variation at the last scoring date in Pop. 1107 (DPL61 by T1107); whereas, one major QTL (qNFB-c25-1) can be detected across five scoring dates, explained 63.5% of the phenotypic variation at the last scoring date in Pop. 1354 (DPL61 by T1354). QTLs with minor effects appeared at various scoring date(s), indicating their roles in regulating flowering at a lower or higher node number. Genetic segregation analysis and QTL mapping results provide further information on the mechanisms of cotton photoperiodic sensitivity. Part of a Ph.D. dissertation by senior author submitted to the Department of Plant and Soil Sciences, Mississippi State University, December 2007. Contribution of USDA-ARS in cooperation with the Mississippi Agric. and Forestry Exp. Stn. Journal paper J. 11276 of Mississippi Agric. and Forestry Exp. Stn.     

Genetic mapping of quantitative trait loci for fiber quality and yield trait by RIL approach in Upland cotton

The improvement of cotton fiber quality has become more important because of changes in spinning technology. Stable quantitative trait loci (QTLs) for fiber quality will enable molecular marker-assisted selection to improve fiber quality of future cotton cultivars. A simple sequence repeat (SSR) genetic linkage map consisting of 156 loci covering 1,024.4 cM was constructed using a series of recombinant inbred lines (RIL) developed from an F₂ population of an Upland cotton (Gossypium hirsutum L.) cross 7235 × TM-1. Phenotypic data were collected at Nanjing and Guanyun County in 2002 and 2003 for 5 fiber quality and 6 yield traits. We found 25 major QTLs (LOD ≥ 3.0) and 28 putative QTLs (2.0 < LOD < 3.0) for fiber quality and yield components in two or four environments independently. Among the 25 QTLs with LOD ≥ 3, we found 4 QTLs with large effects on fiber quality and 7 QTLs with large effects on yield components. The most important chromosome D8 in the present study was densely populated with markers and QTLs, in which 36 SSR loci within a chromosomal region of 72.7 cM and 9 QTLs for 8 traits were detected.