Quantitative trait loci analysis for the developmental behavior of tiller number in rice (Oryza sativa L.)

 A doubled-haploid rice population of 123 lines from Azucena/IR64 was used for analyzing the developmental behavior of tiller number by conditional and unconditional QTL mapping methods. It was indicated that the number of QTLs significantly affecting tiller number was different at different measuring stages. Many QTLs controlling tiller growth identified at the early stages were undetectable at the final stage. Only one QTL could be detected across the whole growth period. By conditional QTL mapping, more QTLs for tiller number could be detected than that by unconditional mapping. The temporal patterns of gene expression for tiller number could be different at different stages. Even an individual gene or genes at the same genomic region might have opposite genetic effects at various growth stages. Received: 7 July 1997 / Accepted: 10 February 1998     

Unconditional and conditional QTL mapping for the developmental behavior of tiller number in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

A single segment substitution population of 26 lines and their recipient parent Hua-jing-xian 74 (HJX74) were selected as experimental materials for analyzing the developmental behavior of tiller number in rice. By the unconditional QTL (quantitative trait locus) mapping method, a total number of 14 SSSLs were detected with QTLs controlling rice tiller number. The number of QTLs significantly affecting tiller number and their effect values estimated differed across measuring stages. More QTLs could be detected based on time-dependent measures of different stages. By the conditional QTL mapping method, it is possible to reveal net expression of gene in a time interval. 14 QTLs on tiller number expressed their effects in dynamic patterns of themselves during whole ontogeny. They exhibited mainly negative effects within 7 days after transplanting. During 7–21 days, QTLs were in active status and expressed larger positive effects. In the mid-period of 21–35 days, they had opposite genetic effects to wither tillers. Since then these QTLs expressed positive effects again to cause the appearance of noneffective tillers. The dynamics of QTL effects was in agreement with the actual change of tillers. Mapping QTL combining unconditional with conditional analysis for time-dependent measures is helpful to understand roundly the genetic bases for the development of quantitative traits.     

直播条件下水稻6个穗部性状的QTL分析

在大田直播条件下,利用来源于＂Lemont/特青＂的重组自交系群体,对水稻6个穗部性状及其相互间遗传相关的分子基础进行了QTL分析,共检测到19个QTL,各性状QTL数为2～4个,单个QTL贡献率为4%～22%。共检测到3个染色体区段能同时影响多个穗部性状,其中第1染色体RM212-RM104和第2染色体RM263-RM221区段的QTL能同时影响单株产量、每穗颖花数、着粒密度和二次枝梗数中的3个或4个性状,且这2个区段的QTL对各性状的效应方向相同,增效等位基因均来自‘特青’,为各性状间表型正相关提供了重要的遗传解释。第11染色体RG1022附近的QTL对着粒密度的效应值为负,来自‘特青’的等位基因增加性状值,而对穗长的效应值为正,来自‘特青’的等位基因降低性状值,为这2个性状间表型负相关也提供了一定的遗传解释。此外,对水稻穗部性状QTL在多种环境和遗传背景下的稳定表达及其在分子标记辅助育种中的应用进行了讨论。     

Impact of epistasis and QTL×environment interaction on the developmental behavior of plant height in rice (Oryza sativa L.)

QTLs with epistatic effects and environmental interaction effects for the developmental behavior of plant height in rice were studied by conventional and conditional methods for quantitative trait loci (QTLs) by mapping with a doubled-haploid population of 123 lines from IR64/Azucena in three environments. The results showed that epistatic effects were important and most epistasis could be detected only by conditional QTL mapping, while most non–epistatic QTLs could be detected by both conventional and conditional methods. Many modificative QTLs showed only epistatic effects without their own additive effects at some stages. QTL×environment (QE) interaction effects were detected more often than QTL main effects for plant-height behavior, which might indicate that gene expression could be greatly affected by the environment. No QTLs had effects during the whole of ontogeny. Conditional QTL mapping might be a valid way to reveal dynamic gene expression for the development of quantitative traits, especially for epistatic effects. Received: 19 May 2000 / Accepted: 27 October 2000     

Conditional QTL mapping of oil content in rapeseed with respect to protein content and traits related to plant development and grain yield

Oil content in rapeseed (Brassica napus L.) is generally regarded as a character with high heritability that is negatively correlated with protein content and influenced by plant developmental and yield related traits. To evaluate possible genetic interrelationships between these traits and oil content, QTL for oil content were mapped using data on oil content and on oil content conditioned on the putatively interrelated traits. Phenotypic data were evaluated in a segregating doubled haploid population of 282 lines derived from the F₁ of a cross between the old German cultivar Sollux and the Chinese cultivar Gaoyou. The material was tested at four locations, two each in Germany and in China. QTLMapper version 1.0 was used for mapping unconditional and conditional QTL with additive (a) and locus pairs with additive × additive epistatic (aa) effects. Clear evidence was found for a strong genetic relationship between oil and protein content. Six QTL and nine epistatic locus pairs were found, which had pleiotropic effects on both traits. Nevertheless, two QTL were also identified, which control oil content independent from protein content and which could be used in practical breeding programs to increase oil content without affecting seed protein content. In addition, six additional QTL with small effects were only identified in the conditional mapping. Some evidence was apparent for a genetic interrelationship between oil content and the number of seeds per silique but no evidence was found for a genetic relationship between oil content and flowering time, grain filling period or single seed weight. The results indicate that for closely correlated traits conditional QTL mapping can be used to dissect the genetic interrelationship between two traits at the level of individual QTL. Furthermore, conditional QTL mapping can reveal additional QTL with small effects that are undetectable in unconditional mapping.     

玉米株高和穗位高的遗传基础与分子机制*

株高和穗位高是玉米重要育种性状,直接影响植株的养分利用效率及抗倒伏性,进而影响玉米产量。玉米株高和穗位高属于典型数量性状,目前通过数量性状位点(quantitative trait loci mapping,QTL)定位和全基因组关联分析(genome-wide association study, GWAS)等方法已挖掘到较多相关遗传位点,通过QTL精细定位及利用突变体克隆了一些调控株高和穗位高关键基因。但是由于各研究组所利用的群体类型和大小、标记类型和密度以及统计方法不同,所鉴定QTL差异较大,单个研究难以揭示玉米株高和穗位高遗传结构。早期QTL定位的结果多以遗传距离来展示,不同时期GWAS研究所使用参考基因组版本不同,这进一步增加了借鉴和利用前人研究结果的难度。首次将目前已鉴定株高和穗位高遗传定位信息统一锚定至玉米自交系B73参考基因组V4版本,构建了株高和穗位高性状定位的一致性图谱,并鉴定出可被多个独立研究定位的热点区间。进一步对已克隆玉米株高和穗位高调控基因进行总结与分类,揭示株高和穗位高性状调控机制,对深度解析株高和穗位高遗传结构、指导基因克隆和利用分子标记辅助选择优化玉米株高和穗位高性状均具有重要意义。     

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.     

不同发育阶段大豆株高和茎粗QTL的动态分析

利用中豆29×中豆32的重组自交系,以复合区间作图法对不同发育阶段的大豆株高和茎粗同时进行非条件和条件QTL定位,在11个连锁群检测到18个株高QTL,在9个连锁群检测到19个茎粗QTL。不同发育时期影响大豆株高和茎粗QTL的数量、加性效应和贡献率均不相同,QTL表达具有时序性和选择性,有些QTL仅表达1次,有些可多次连续表达。有3个株高QTL和1个茎粗QTL在3个年度重复表达,有6个株高QTL和2个茎粗QTL在2个年度重复表达。F连锁群上株高和茎粗QTL存在共位性,R1～R4期均有株高和茎粗QTL同时表达,但株高和茎粗QTL的增效基因不同,株高QTL表达次数多而茎粗QTL表达次数较少,前期(V4～R3)QTL表达数量多而后期(R4～R5)表达数量较少。株高和茎粗QTL的动态变化与表型相关分析结果一致,对于适期选择粗秆抗倒的高产材料具有指导作用。     

Genetic Relationships Among Panicle Characteristics of Rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) Using Unconditional and Conditional QTL Analyses

Using mixed-model-based composite interval mapping and conditional statistical methods, we studied quantitative trait loci (QTLs) with epistatic effects and QTLs by environment interaction effects for rice seed set percent (SSP), filled grain number per plant (FGP), and panicle length (PL). A population of 241 recombinant inbred lines was used which was derived from a cross between “Zhenshan 97” and “Minghui 63.” Its linkage map included 221 molecular markers. Our QTL analysis detected 28, 25, and 32 QTLs for SSP, FGP, and PL, respectively. Each QTL explained 1.37%∼13.19% of the mean phenotypic variation. A comparison of conventional and conditional mapping provided information about the genetic control system involved in the synthetic process of SSP, FGP, and PL at the level of individual QTLs. Conditional QTLs with reduced (or increased) effects were identified for SSP, which were significantly influenced by FGP or PL. Some QTLs could express independently for the given traits, thereby providing possibilities for simultaneous improvement of SSR and PL, and SSR and FGP. Epistasis was more sensitive to environmental conditions than were additive effects.     

Conditional QTL mapping of protein content in wheat with respect to grain yield and its components

Grain protein content in wheat (Triticum aestivum L.) is generally considered a highly heritable character that is negatively correlated with grain yield and yield-related traits. Quantitative trait loci (QTL) for protein content was mapped using data on protein content and protein content conditioned on the putatively interrelated traits to evaluate possible genetic interrelationships between protein content and yield, as well as yield-related traits. Phenotypic data were evaluated in a recombinant inbred line population with 302 lines derived from a cross between the Chinese cultivar Weimai 8 and Luohan 2. Inclusive composite interval mapping using IciMapping 3.0 was employed for mapping unconditional and conditional QTL with additives. A strong genetic relationship was found between protein content and grain yield, and yield-related traits. Unconditional QTL mapping analysis detected seven additive QTL for protein content, with additive effects ranging in absolute size from 0.1898% to 0.3407% protein content, jointly accounting for 43.45% of the trait variance. Conditional QTL mapping analysis indicated two QTL independent from yield, which can be used in marker-assisted selection for increasing yield without affecting grain protein content. Three additional QTL with minor effects were identified in the conditional mapping. Of the three QTLs, two were identified when protein content was conditioned on yield, which had pleiotropic effects on those two traits. Conditional QTL mapping can be used to dissect the genetic interrelationship between two traits at the individual QTL level for closely correlated traits. Further, conditional QTL mapping can reveal additional QTL with minor effects that are undetectable in unconditional mapping.     

Genetic dissection of seed shattering,agronomic, and color traits in American wildrice ( Zizania palustris var. interior L.) with a comparative map

A comparative map of American wildrice ( Zizania palustris var. interior L.) was used to identify loci controlling seed shattering, plant height, maturity, tiller number, plant habit, panicle length seed length, and color traits. Two to six significant quantitative-trait-loci (QTLs, P < 0.05) were detected for each trait evaluated, representing the first trait-mapping in wildrice. The chosen population was designed to emphasize the mapping of loci controlling the shattering trait, which is the most important trait in the management of this newly domesticated species. Three loci were detected that controlled the discretely categorized variation between shattering and non-shattering plants. Seed-shattering loci were detected and validated among the F(2) and F(3) generations. A multiple regression model with these three loci described 49.6% of the additive genetic variation. A genetic model with the same three loci including dominance and locus interactions predicted the shattering versus non-shattering phenotype at a success rate of 87%. The comparative map was based on mapped RFLP markers used in white rice ( Oryza sativa L.) and other grass species. Anchor loci provided a reference point for the identification of potential orthologous genes on the basis of white rice mutant loci and consensus grass species QTLs. Candidate orthologous loci were identified among all traits evaluated. The study underscores the benefits of extending trait analysis through comparative mapping, as well as challenges of QTL analysis in a newly domesticated species.     

Whole-Genome Quantitative Trait Locus Mapping Reveals Major Role of Epistasis on Yield of Rice

Although rice yield has been doubled in most parts of the world since 1960s, thanks to the advancements in breeding technologies, the biological mechanisms controlling yield are largely unknown. To understand the genetic basis of rice yield, a number of quantitative trait locus (QTL) mapping studies have been carried out, but whole-genome QTL mapping incorporating all interaction effects is still lacking. In this paper, we exploited whole-genome markers of an immortalized F₂ population derived from an elite rice hybrid to perform QTL mapping for rice yield characterized by yield per plant and three yield component traits. Our QTL model includes additive and dominance main effects of 1,619 markers and all pair-wise interactions, with a total of more than 5 million possible effects. The QTL mapping identified 54, 5, 28 and 4 significant effects involving 103, 9, 52 and 7 QTLs for the four traits, namely the number of panicles per plant, the number of grains per panicle, grain weight, and yield per plant. Most identified QTLs are involved in digenic interactions. An extensive literature survey of experimentally characterized genes related to crop yield shows that 19 of 54 effects, 4 of 5 effects, 12 of 28 effects and 2 of 4 effects for the four traits, respectively, involve at least one QTL that locates within 2 cM distance to at least one yield-related gene. This study not only reveals the major role of epistasis influencing rice yield, but also provides a set of candidate genetic loci for further experimental investigation.     

Molecular Genetics of Submergence Tolerance in Rice: QTL Analysis of Key Traits

Flash flooding of young rice plants is a common problem forrice farmers in south and south-east Asia. It severely reducesgrain yield and increases the unpredictability of cropping.The inheritance and expression of traits associated with submergencestress tolerance at the seedling stage are physiologically andgenetically complex. We exploited naturally occurring differencesbetween certain rice lines in their tolerance to submergenceand used quantitative trait loci (QTL) mapping to improve understandingof the genetic and physiological basis of submergence tolerance.Three rice populations, each derived from a single cross betweentwo cultivars differing in their response to submergence, wereused to identify QTL associated with plant survival and variouslinked traits. These included total shoot elongation under water,the extent of stimulation of shoot elongation caused by submergence,a visual submergence tolerance score, and leaf senescence underdifferent field conditions, locations and years. Several majorQTL determining plant survival, plant height, stimulation ofshoot elongation, visual tolerance score and leaf senescenceeach mapped to the same locus on chromosome 9. These QTL weredetected consistently in experiments across all years and inthe genetic backgrounds of all three mapping populations. SecondaryQTL influencing tolerance were also identified and located onchromosomes 1, 2, 5, 7, 10 and 11. These QTL were specific toparticular traits, environments, or genetic backgrounds. Allidentified QTL contributed to increased submergence tolerancethrough their effects on decreased underwater shoot elongationor increased maintenance of chlorophyll levels, or on both.These findings establish the foundations of a marker-assistedscheme for introducing submergence tolerance into agriculturallydesirable cultivars of rice.     

Dynamic QTL analysis of the Na+ content,K+ content,and Na+/K+ ratio in rice roots during the field growth under salt stress

Rice (Oryza sativa L.) is seriously impacted by global soil salinization. To determine the quantitative trait loci (QTLs) related to salt tolerance in rice roots, F_2:3 and BC₁F_2:3 populations derived from a cross between the cv. Dongnong 425 of high quality and yield and the salt-tolerant cv. Changbai 10, were studied at different development stages. Two genetic linkage maps of F_2:3 and BC1F_2:3 populations were constructed. A 66 mM NaCl solution was used to irrigate the field and to analyze the dynamic QTL of some rice root traits. Using unconditional and conditional QTL mapping methods, 30 unconditional QTLs and 16 conditional QTLs related to the 6 root traits were detected on the 9 rice chromosomes during different developmental stages. Fourteen pairs of unconditional and conditional QTLs were detected at the identical developmental stage in the identical population. A number of QTLs were detected at different developmental stages, however, many did not appear at the last stage. Remarkably, qRKC1 appeared continuously at multiple stages in both the populations suggesting its key role in regulating the salt tolerance of rice roots.     

Association mapping of salt tolerance in barley (Hordeum vulgare L.)

A spring barley collection of 192 genotypes from a wide geographical range was used to identify quantitative trait loci (QTLs) for salt tolerance traits by means of an association mapping approach using a thousand SNP marker set. Linkage disequilibrium (LD) decay was found with marker distances spanning 2–8 cM depending on the methods used to account for population structure and genetic relatedness between genotypes. The association panel showed large variation for traits that were highly heritable under salt stress, including biomass production, chlorophyll content, plant height, tiller number, leaf senescence and shoot Na⁺, shoot Cl^? and shoot, root Na⁺/K⁺ contents. The significant correlations between these traits and salt tolerance (defined as the biomass produced under salt stress relative to the biomass produced under control conditions) indicate that these traits contribute to (components of) salt tolerance. Association mapping was performed using several methods to account for population structure and minimize false-positive associations. This resulted in the identification of a number of genomic regions that strongly influenced salt tolerance and ion homeostasis, with a major QTL controlling salt tolerance on chromosome 6H, and a strong QTL for ion contents on chromosome 4H.     

Quantitative Trait Locus Mapping and Candidate Gene Analysis for Plant Architecture Traits Using Whole Genome Re-Sequencing in Rice

Plant breeders have focused on improving plant architecture as an effective means to increase crop yield. Here, we identify the main-effect quantitative trait loci (QTLs) for plant shape-related traits in rice (Oryza sativa) and find candidate genes by applying whole genome re-sequencing of two parental cultivars using next-generation sequencing. To identify QTLs influencing plant shape, we analyzed six traits: plant height, tiller number, panicle diameter, panicle length, flag leaf length, and flag leaf width. We performed QTL analysis with 178 F₇ recombinant in-bred lines (RILs) from a cross of japonica rice line ‘SNUSG1’ and indica rice line ‘Milyang23’. Using 131 molecular markers, including 28 insertion/deletion markers, we identified 11 main- and 16 minor-effect QTLs for the six traits with a threshold LOD value > 2.8. Our sequence analysis identified fifty-four candidate genes for the main-effect QTLs. By further comparison of coding sequences and meta-expression profiles between japonica and indica rice varieties, we finally chose 15 strong candidate genes for the 11 main-effect QTLs. Our study shows that the whole-genome sequence data substantially enhanced the efficiency of polymorphic marker development for QTL fine-mapping and the identification of possible candidate genes. This yields useful genetic resources for breeding high-yielding rice cultivars with improved plant architecture.     

Quantitative trait loci analysis for the developmental behavior of Soybean (Glycine max L. Merr.)

Quantitative trait loci (QTLs) identified so far in soybean were mainly derived in the final stage of plant development, which did not apply to the exploitation of genetic effects that were expressed during a specific developmental stage. Thus, the aim of this study was to identify conditional QTLs associated with yield traits at a specific developmental interval of soybean plant. The 143 recombinant inbred lines developed from the cross of soybean cultivars ‘Charleston’ and ‘Dongnong 594’ were used for the developmental QTLs analysis of pod number in the main stem and plant height by composite interval mapping method combined with mixed genetic model. The results indicated that the number and type of QTLs and their genetic effects for the two agronomic traits were different in a series of measuring stages. A total of 10 unconditional QTLs in 6 linkage groups and 5 conditional QTLs in 3 linkage groups were identified for the pod number of the main stem, while 13 unconditional QTLs in 7 linkage groups and 12 conditional QTLs in 6 linkage groups were identified for plant height. Many QTLs that were detected in the early stages were different from those detected at the later stages. Some QTLs existed only at one stage and others existed across two or three stages. Five marker intervals (satt509-satt251, sat_099-sat_113, sat_113-OPAW19_4, satt457-OPC10_85, sat_095-OPBA08_5) were proven to be associated both with the development of pod number in the main stem and the development of plant height. The present study suggested that the development of pods and plant height in soybean were governed by time-dependent gene expression.     

Potential for Marker-Assisted Simultaneous Improvement of Grain and Biomass Yield in Triticale

Triticale is a promising crop for agricultural biomass production but breeding has until now mainly focused on grain yield. Here, we evaluated the potential of marker-assisted simultaneous improvement of grain yield and biomass yield. To this end, we employed a large triticale doubled haploid population with 647 individuals derived from four families that were phenotyped for grain yield and biomass yield, as well as thousand-kernel weight, tiller density, and plant height in multi-environment field trials. Employing an association mapping approach, we identified quantitative trait loci (QTL) for all the five traits. The phenotypic correlation between grain yield and biomass yield was low, and we detected only one overlapping QTL suggesting different genetic architectures underlying both traits. Our results indicate that a marker-based selection for either grain yield or biomass yield does not adversely affect the other traits. Furthermore, an improvement of the multiplicative yield traits can to some extent also be achieved by selection for QTL identified for the component traits. Taken together, our results suggest that marker-assisted breeding can assist the establishment of dual-purpose triticale cultivars with high grain and biomass yield.     

水稻株高构成因素的QTL剖析

利用水稻籼粳杂交 (圭 6 30× 0 2 42 8) F1 的花药离体培养建立的一个含 81个 DH家系的作图群体 ,对水稻株高构成因素 (穗长、第 1节间长、……、第 5节间长 )进行基因定位。DH群体中株高构成因素均呈正态分布。相邻的构成因素间呈极显著的正相关 ,而相距较远的构成因素间的相关较弱或不显著。采用 QTL(Quantitative trait lo-cus)分析 ,定位了影响株高构成因素的 6个 QTL:qtl7同时影响穗长和第 1、2、3节间长 ,qtl1 和 qtl2 同时影响第 4和第 5节间长 ,qtl1 0 a和 qtl1 0 b仅影响第 1节间长 ,qtl3 仅影响第 3节间长。采用 QTL 互作分析 ,检测到 19对显著的互作 ,每个构成因素受 2个或 2个以上的 QTL 互作对的影响。并且还发现 ,同一个 QTL 互作对可能影响不同的性状 ,以及一个 QTL 可以分别与不同的 QTL 产生互作而影响同一个性状或影响不同的性状 ,但总的看来 ,加性效应是主要的。这些结果揭示了株高构成因素间相关的遗传基础 ,在水稻育种中运用这些 QTL 将有助于对株高 ,以及对穗长和上部节间长度进行精细的遗传调控。     

Identification of genomic regions determining flower and pod numbers development in soybean （Glycine max L.）

Flower and pod numbers per plant are important agronomic traits underlying soybean yield.So far quantitative trait loci (QTL) detected for flower and pod-related traits have mainly focused on the final stage,and might therefore have ignored genetic effects expressed during a specific developmental stage.Here,dynamic expressions of QTL for flower and pod numbers were identified using 152 recombinant inbred lines (RILs) and a linkage map of 306 markers.Wide genetic variation was found among RILs;17 unconditional and 18 conditional QTL were detected for the two traits at different developmental stages over two years.Some QTL were detected only at one stage and others across two or more stages,indicating that soybean flower and pod numbers development may be governed by time-dependent gene expression.Three main QTL (qfn-Chr18-2,qfn-Chr20-1,and qfn-Chr19) were detected for flower number,and two main QTL (qpn-Chr11 and qpn-Chr20) were detected for pod number.The phenotypic variation explained by them ranged from 6.1% to 34.7%.The markers linked to these QTL could be used in marker-assisted selection for increasing soybean flower and pod numbers,with the ultimate aim of increasing soybean yield.Comparison of the QTL regions for flower and pod numbers traits with the related genes reported previously showed that seven and four related genes were located in the QTL regions of qfn-Chr11 and qfn-Chr19,respectively.Tbese results provide a basis for fine mapping and cloning of flower and pod development-related genes.