Identification and verification of pleiotropic QTL controlling multiple amino acid contents in soybean seed

Soybean is important throughout the world due to its high seed protein and oil, while the quality and quantity of seed amino acids need to be improved. To improve the multiple amino acid concentrations in soybean simultaneously, detecting and utilizing the pleiotropic quantitative trait loci (QTL) and related genes become increasingly important. In view of this, a F_6:7 recombinant inbred line population was genotyped using 1739 polymorphic SNP and 127 SSR markers in the present study and was phenotyped for seventeen types of amino acids simultaneously. In total, twelve co-located or overlapped pleiotropic additive QTL clusters, which explained 2.38–16.79% of the amino acid variation, were identified. Of them, one novel pleiotropic QTL cluster with a phenotypic variation explained ranging from 8.84 to 16.79% for ten kinds of amino acid contents (glycine, alanine, isoleucine, leucine, valine, methionine, aspartic acid, glutamic acid, lysine and phenylalanine), was located at the same position on linkage group D2, and the confidence interval was only 0.8 cM. Moreover, the individuals in this family-based population (345 lines) and another cultivar-based population (254 varieties) with different genotypes at the common flanking markers for this QTL cluster showed significantly different amino acid contents, which further validated the QTL mapping results. Additionally, some candidate genes that might participate in the amino acid biosynthesis process were found in these pleiotropic QTL regions. Thus, novel pleiotropic QTL clusters could be applied in marker-assisted selection breeding or map-based candidate gene cloning in soybean for multiple amino acid genetic improvements in seed in the future.     

Meta‐analysis and overview analysis of quantitative trait locis associated with fatty acid content in soybean for candidate gene mining

As soybean seed fatty acid content is valued in food, animal feed and some industrial applications, plant breeders continually aim to improve seed fatty acid constituent value. This study analysed 163 original quantitative trait loci (QTLs) related to soybean fatty acid content from databases and references and revealed 43 consensus QTLs. Meta‐analysis using BioMercator ver.2.1 indicated that these were located across 16 linkage groups (LGs) excluding LG D1a, LG C1, LG M and LG H. Moreover, the overview method was used to optimize these QTLs based on statistical analysis. Some valid QTL regions were narrowed down to 0.5 Mb and mapped on the same LGs as the meta‐analysis result. Furthermore, the functions of all genes located in these consensus QTL intervals were predicted and eight candidate genes were identified. KEGG pathway analysis indicated that Glyma.13G127900 and Glyma.18G232000 were involved in the fatty acid synthesis metabolic (pathway ID ko00071, ko00062, ko01040). These results lay a foundation for fine mapping of QTLs related to fatty acid content and marker‐assisted breeding in soybean.     

大豆产量和产量构成因子及倒伏性的QTL分析

随机选取中豆29×中豆32重组自交系群体中165个家系作为2年田间试验材料,分析大豆单株产量、产量构成因子及倒伏性等性状的相关性和遗传效应,并检测各性状QTL。结果表明,38个与产量、产量构成因子及倒伏性状等有关的QTL,主要集中在C2、F和I连锁群。表型相关分析结果与QTL定位结果一致。在F连锁群上,2年均检测到倒伏QTL qLD-15-1,解释的表型变异超过20%,与百粒重和分枝荚数QTL分别位于相同和相邻标记区间,表明产量相关性状与倒伏性存在一定的关联。在I连锁群上,每荚粒数QTL和二、三、四粒荚数QTL不仅于同一位置,解释的表型变异为32%~65%,并且2个年份均重复出现,每荚粒数和四粒荚数QTL与二、三粒荚数QTL的增效基因分别来自不同的亲本。这4个粒荚性状QTL的共位性与表型相关分析结果一致,证实每荚粒数和四粒荚数与二、三粒荚数分别由不同的机制调控,对于育种上探讨以改良大豆粒荚性状为途径提高大豆产量,提供了重要依据。     

Genetic and QTL analyses of yield and a set of physiological traits in pepper

An interesting strategy for improvement of a complex trait dissects the complex trait in a number of physiological component traits, with the latter having hopefully a simple genetic basis. The complex trait is then improved via improvement of its component traits. As first part of such a strategy to improve yield in pepper, we present genetic and QTL analyses for four pepper experiments. Sixteen traits were analysed for a population of 149 recombinant inbred lines, obtained from a cross between the large-fruited pepper cultivar ‘Yolo Wonder’ (YW) and the small fruited pepper ‘Criollo de Morelos 334’ (CM334). The marker data consisted of 493 markers assembled into 17 linkage groups covering 1,775 cM. The trait distributions were unimodal, although sometimes skewed. Many traits displayed heterosis and transgression. Heritabilities were high (mean 0.86, with a range between 0.43 and 0.96). A multiple QTL mapping approach per trait and environment yielded 24 QTLs. The average numbers of QTLs per trait was two, ranging between zero and six. The total explained trait variance by QTLs varied between 9 and 61 %. QTL effects differed quantitatively between environments, but not qualitatively. For stem-related traits, the trait-increasing QTL alleles came from parent CM334, while for leaf and fruit related traits the increasing QTL alleles came from parent YW. The QTLs on linkage groups 1b, 2, 3a, 4, 6 and 12 showed pleiotropic effects with patterns that were consistent with the genetic correlations. These results contribute to a better understanding of the genetics of yield-related physiological traits in pepper and represent a first step in the improvement of the target trait yield.     

Mapping and analysis of QTLs related to seed length and seed width in Glycine max

Both seed length and seed width are important traits for soybean yield. In the present study, 89 Quantitative trait loci (QTLs) of seed length and 65 QTLs of seed width were collected from published papers and our study. QTLs in this study were evaluated by the soymap2, then totally 23 consensus QTLs were located on 17 linkage groups (LGs) through the meta‐analysis. The minimum confidence interval was 0.28 cM and the mean phenotypic variance (R²) was ranged from 5.33% to 23.36%. To optimize these QTLs based on statistic analysis, overview method was further used to narrow down CI, the number of QTLs was narrowed down to 84. Furthermore, 2,750 candidate genes were screened from the consensus QTL intervals by informatics, a total of 37 genes were found to be associated with seed size. All results could lay a foundation for MAS (Molecular Assisted Selection) and gene cloning.     

Identification of soybean genes related to fatty acid content based on a soybean genome collinearity analysis

Seed fatty acid content is an important consideration for soybean produced for food, feed, and industrial applications. In this study, MCScanX was used to analyze the entire soybean genome to generate a collinearity block, which was then used to assess the collinearity among the soybean fatty acid quantitative trait loci (QTL) in the SoyBase database. The hub‐QTLs located in the Gm06, Gm07, and Gm10 segments were identified. The Kyoto Encyclopedia of Genes and Genomes and gene ontology databases were used to analyze the genes in hub‐QTL regions, resulting in the identification of 17 candidate genes related to soybean fatty acid content. Two lines with different fatty acid contents and a recurrent parent were selected from a chromosome segment substitution line library for a subsequent quantitative real‐time polymerase chain reaction (qRT‐PCR) assay to verify the candidate gene expression patterns. Four genes were related to the total soybean fatty acid content, while three genes were related to the content of specific fatty acid types. The results of this study may be relevant for the fine mapping of soybean fatty acid QTLs/genes.     

甘蓝型油菜产量及其构成因素的QTL定位与分析

产量性状是复杂的数量性状, 对种子的单株产量及其构成因素(全株总有效角果数、每角粒数、千粒重)进行QTL定位和上位性分析,确定其在染色体上的位置及其遗传效应,可以探讨油菜杂种优势产生原因,提高育种中对产量性状优良基因型选择的效率,达到提高油菜产量的目的。在双低油菜细胞质雄性不育保持系1141B和双高恢复系垦C₁构建的F₂作图群体中,运用SRAP、AFLP和SSR三种标记技术构建了一个甘蓝型油菜(Brassica napus L.)的分子标记遗传连锁图谱。共包含244个标记,分布于20个主要连锁群、1个三联体上,图谱总长度为2 769.5 cM。采用Windows QTL Cartographer Version 2.0统计软件及复合区间作图法,对油菜单株产量及其3大构成因素进行QTL定位,共检测到QTLs 16个分布在9个连锁群上,其中第6和13连锁群最多,均有3个。单个QTL解释性状表型变异的0.38%～73.34%。对于同一性状,等位基因的增效作用既来自母本,亦源自父本;采用双向方差分析法对位点间互作及其上位性进行分析,检测到26对影响产量构成性状的上位性互作效应QTL,说明油菜基因组中存在大量控制产量的互作位点,油菜产量性状的上位性存在着多效性,上位性互作包括QTL与非QTL位点,其中以非QTL位点较多。一般互作位点的独立效应值较小,而互作的效应值显著增大,且一般超过两位点独立效应值之和。反映了控制产量性状基因的复杂性。上位性是甘蓝型油菜产量性状杂种优势的重要遗传基础。     

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.     

开花后不同光周期条件下大豆农艺性状和品质性状的QTL分析

以开花期相近的181个大豆重组自交系(RIL)为材料,研究开花后不同光照长度对大豆主要农艺性状的影响,并在利用SSR标记构建大豆遗传图谱的基础上,分别在长日(16 h)和短日(12 h)条件下检测与主要农艺性状及其光周期敏感度(PS)相关的QTL。结果表明,开花后光照处理对大豆农艺性状和品质性状有较大影响,不同性状的光周期敏感度差异明显,株高＞主茎节数＞蛋白质含量、脂肪含量＞百粒重＞单株荚数＞蛋白质和脂肪总量。利用复合区间作图法检测到12个与株高、主茎节数、单株荚数、百粒重、蛋白质和脂肪总量等性状及各性状对开花后光周期处理的敏感度相关的QTL,分别定位于A1、A2、B1、B2、C1、D1a、F、L等8个连锁群上。其中,在短日条件下检测到4个QTL,可解释的遗传变异范围在11.37%~26.63%之间;在长日条件下检测到3个QTL,可解释的遗传变异范围在11.84%~27.85%之间;检测到5个与不同性状光周期敏感度有关的QTL,可解释相对应性状表型变异的范围在6.15%~21.44%之间。针对同一性状,未检测到在长日和短日条件下均起作用的主效QTL, 说明开花后光周期对大豆产量和品质性状相关基因的表达有较大影响。     

越冬栽培稻产量性状相关QTL定位

越冬栽培稻是一类能越过自然冷冬季节并在第2年春季萌芽、正常开花结实、收获稻谷的水稻品种。本文通过对越冬栽培稻产量性状QTL分析,明确产量相关性状的遗传规律,旨在进一步解析越冬栽培稻产量性状的遗传机制,为育种创新利用提供理论依据。以3份越冬栽培稻构建的3个半同胞F2群体为材料。各考察15个产量相关性状,利用Excel 2003、GraphPad Prism 5.0和QTL IciMapping 4.10软件分析数据、绘制遗传图谱、定位QTL和联合分析。结果表明,产量性状表型值在3群体中呈连续正态分布,表现为数量性状遗传。共检测到37个QTL和26对上位性QTL,贡献率分别介于2.32%～36.31%和1.04%～2.05%;检测到9个同时影响2个及以上产量性状(一因多效)QTL标记区间;以联合分析检测到13个产量性状相关QTL,其中4个QTL区间与单群体检测QTL区间重叠;越冬栽培稻产量相关性状QTL以加–显性效应遗传为主、上位性遗传效应为辅。本研究将为越冬栽培稻产量相关基因挖掘及育种创新利用奠定基础。     

大豆脂肪酸含量的QTL分析

利用Charleston(♀)×东农594(♂)的F14和F15代永久自交系群体154个单株后代,在2年3点条件下用气相色谱法测得其籽粒5种脂肪酸的含量,利用Win QTL Cartographer2.5复合区间作图法(CIM)进行QTL分析。结果共检测到47个相关的QTL,分布在13个连锁群上。多年多点同时检测到的QTL共有15个,其中控制软脂酸性状的2个,包括qPal-C2-2和qPal-A1-1;控制硬脂酸性状的4个,包括qSt-B1-1、qSt-B1-2、qSt-D1a-1和qSt-C2-1;控制油酸性状的3个,包括qOle-B2-1、qOle-G-1和qOle-H-1;控制亚油酸性状的有2个,包括qLin-C2-1和qLin-H-1;控制亚麻酸性状的4个,包括qLino-B1-1、qLino-C2-1、qLino-D1b-1和qLino-J-1。这些QTL的一致性较高,为特异脂肪酸含量标记辅助育种奠定了基础。大豆脂肪酸含量的主效QTL数量不多,效应大的不多,可能还受许多未能检测出来的微效基因控制。     

陆地棉种子物理性状QTL定位

定位棉花种子性状的基因对揭示棉花种子性状的遗传规律,以及明确棉花种子、产量、纤维品质等性状间的遗传关系具有重要意义。以(渝棉1号×T586) F_2:7重组近交系群体构建的遗传连锁图谱,在鉴定270个家系3个环境种子物理性状的基础上,利用MQM作图方法,共检测到34个种子物理性状QTL,包括9个种子重(qSW)、5个短绒重(qFW)、3个短绒率(qFP)、8个种仁重(qKW)、6个种子壳重(qHW)和3个种仁率(qKP)QTL,它们可解释4.6%~80.1%的性状表型变异。9个QTL在2个或3个环境中被检测到,其中包括第12染色体显性光子位点的短绒重与短绒率QTL,以及另外7个微效应QTL。34个QTL分布于15条染色体,其中A染色体组20个,D染色体组14个。有12个染色体区段分布有2个或2个以上的QTL,而且同一染色体区域同一亲本所具有的不同性状QTL的方向大多数与性状表型相关系数的正负一致。     

Quantitative trait locus analysis for soybean (Glycine max) seed protein and oil concentrations using selected breeding populations

Soybean seed protein and oil concentrations are important traits that directly affect the quality of soyfoods. Many studies and breeding programmes have been conducted to find major quantitative trait loci (QTL) that regulate protein and oil concentrations and to develop soybean cultivars with high protein and/or oil content. The purpose of this study was to identify these QTL using a selected breeding population. The population was tested in field conditions over a period of 3 years. Seed protein and oil concentrations were measured each year. Single‐nucleotide polymorphisms (SNPs) were used to construct genetic map using a 180K SoyaSNP array, which identified 1,570 SNPs. We identified 12 QTL for seed protein, 11 for seed oil concentration and four for both traits. Among these, 17 QTL were closely mapped to previously reported QTL, whereas ten sites were novel. Several QTL were detected across at least two experimental years. These loci are good candidate QTL for optimal seed protein and oil concentrations. Our results demonstrate that favourable target QTL can be successfully identified using selected breeding populations.     

Identification of quantitative trait loci for grain yield, seed protein concentration and maturity in field pea (Pisum sativum L.)

Breeding efforts to improve grain yield, seed protein concentration and early maturity in pea (Pisum sativum L.) have proven to be difficult. The use of molecular markers will improve our understanding of the genetic factors conditioning these traits and is expected to assist in selection of superior genotypes. This study was conducted to identify genetic loci associated with grain yield, seed protein concentration and early maturity in pea. A population of 88 recombinant inbred lines (RILs) that was developed from a cross between 'Carneval' and 'MP1401' was evaluated at 13 environments across the provinces of Alberta, Manitoba and Saskatchewan, Canada in 1998, 1999 and 2000. A linkage map consisting of 193 AFLPs (amplified fragment length polymorphism), 13 RAPDs (random amplified polymorphic DNA) and one STS (sequence tagged site) marker was used to identify putative quantitative trait loci (QTL) for grain yield, seed protein concentration and early maturity. Four QTL were identified each for grain yield and days to maturity, and three QTL were identified for seed protein concentration. A multiple QTL model for each trait showed that these genomic regions accounted for 39%, 45% and 35% of the total phenotypic variation for grain yield, seed protein concentration and days to maturity, respectively. The consistency of these QTL across environments and their potential for marker-assisted selection are discussed in this report.     

玉米产量相关性状QTL通用图谱的构建及功能候选基因的开发

通过生物信息学手段,收集整理玉米基因组数据库中产量相关性状的QTL信息,借助高密度玉米遗传连锁图谱IBM 2005 Neighbors和临近分子标记,建立了涵盖干物质和淀粉产量、籽粒相关性状、粒重相关性状以及穗部相关性状四大类共计18个指标的QTL通用图谱。并将位于QTL分布密集区域的基因,与水稻基因序列进行比对,找到了与水稻木质素合成有关的gh2具有高同源性的基因AY109876,同时改进了利用生物信息学手段筛选功能候选基因的路线图。     

大豆数量性状定位的研究进展

大豆的许多重要农艺性状和经济性状是受多基因控制的数量性状。针对大豆产量性状、种子品质性状和重要病害的抗性等，综述了近年来大豆数量性状基因座位(quantitative trait locus, QTL)定位研究的进展,并讨论了目前大豆QTL定位研究存在的问题及解决途径。     

作物产量性状QTL定位的研究现状及应用前景

作物的许多农艺性状和经济性状是数量性状。研究作物数量性状遗传对农作物育种具有十分重要的意义。本文综述了数量性状基因座QTL（quantitative trait locus）定位的原理和常用方法及分子标记在水稻、小麦、玉米、棉花、大豆、番茄、大麦和油菜等重要作物产量性状基因定位中的研究现状,并对目前产量性状QTL定位存在的问题和发展前景进行了探讨     

QTL analysis of variation for vigour in rose

The improvement of energy efficiency in the greenhouse production of cut rose and pot rose can be achieved through the use of rose cultivars having vigorous growth. A better understanding of the inheritance of vigour and its related traits will assist the breeding activities. Quantitative trait locus (QTL) analyses were performed with the help of an integrated linkage map of a diploid rose population originating from a cross between Rosa multiflora-derived genotypes. The underlying datasets for ten vigour-related traits were collected in an evaluation study of this population in two greenhouse experiments with suboptimal temperatures for growth. We identified ten chromosomal regions, scattered over the seven linkage groups, containing QTLs for these traits. Considering each trait separately, we detected a total of 42 QTLs. Among these QTLs, 24 were found in both of the experiments, eight and ten were specific to either of the two experiments. The number of QTLs for individual traits varied from three to five with a respective contribution to the phenotypic variation from 12 to 35%. QTLs for highly correlated traits frequently co-localized, indicating a common genetic basis. Clustering of QTLs for different traits was noted in some chromosome regions, for instance, one on chromosome 2 included major QTLs for eight of ten traits under study, suggesting co-localization of several separate genes or/and the occurrence of various genes having pleiotropic effects. The discovery of markers associated to QTL regions is in roses the first step towards marker-assisted selection for vigour improvement enabling the transfer of useful QTL-alleles of R. multiflora to pot and cut roses.     

大豆不同环境下脂肪酸组分含量的QTL分析

大豆油的品质取决于脂肪酸各组分在大豆中的比例, 为发掘控制大豆5种脂肪酸含量的数量性状位点(QTL), 利用冀豆12和黑豆重组自交系群体构建遗传图谱, 采用Windows QTL Cartographer 2.5和QTL Network-2.0软件的CIM和MCIM法对大豆5种脂肪酸组分进行数量性状定位。结果表明,在石家庄和三亚各环境下共检测到16个QTL, 位于连锁群A2、B2、C2、F、G、I、L上。对2个环境联合分析, 检测到13个QTL, 其中9个用2种方法被检测到, 但这13个位点与环境互作的贡献率明显小于加性效应。其中在B2连锁群Satt168~Satt556控制硬脂酸的QTL Ste-1在河北石家庄和海南三亚均能被检测到, 贡献率均为12%, 在双尾群体和间隔挑选群体中也能检测到控制硬脂酸的QTL Ste-1, 说明这一QTL稳定存在于本组合群体中, 为今后大豆硬脂酸的QTL精细定位奠定了基础。     

Identification of quantitative trait loci across interspecific F2, F2:3 and testcross populations for agronomic and fiber traits in tetraploid cotton

The most widely grown tetraploid Gossypium hirsutum and G. barbadense differ greatly in yield potential and fiber quality and numerous quantitative trait loci (QTLs) have been reported. However, correspondence of QTLs between experiments and populations is poor due to limited number of markers, small population size and inaccurate phenotyping. The purpose of the present study was to map QTLs for yield, yield components and fiber quality traits using testcross progenies between a large interspecific F₂ population and a commercial cotton cultivar as the tester. The results were compared to these from its F₂ and F_2:3 progenies. Of the 177 QTLs identified from the three populations, 65 fiber QTLs and 51 yield QTLs were unique with an average of 8–12 QTLs per traits. All the 26 chromosomes carried QTLs, but differed in the number of QTLs and the number of QTLs between fiber and yield QTLs. The congruence of QTLs identified across populations was higher (20–60 %) for traits with higher heritabilities including fiber quality, seed index and lint percentage, but lower (10–25 %) for lower heritability traits-seedcotton and lint yields. Major QTLs, QTL clusters for the same traits and QTL ‘hotspots’ for different traits were also identified. This research represents the first report using a testcross population in QTL mapping in interspecific cotton crosses and provides useful information for further comparative analysis and marker-assisted selection.