Quantitative trait loci mapping and meta-analysis across three generations for popping characteristics in popcorn

Popping characteristics play a determinant role in the utilization of popcorn (Zea mays L.). In this study, the RIL population with 258 recombinant inbred lines was evaluated to detect quantitative trait loci (QTLs) for three popping characteristics (PF, popping fold; PV, popping volume; PR, popping rate) under four environments. Meta-analysis was used to integrate detected QTLs across three generations (RIL, F_2:3 and BC₂F₂) derived from the same cross. All eleven QTLs were detected for three traits, on chromosomes 1, 2, 4, 6 and 10 for PF, on chromosomes 1, 4, 6, 7 and 10 for PV, and on chromosomes 1, 4, 6 and 10 for PR. Three, 1, 3, 6 and 6 QTL were detected in the same marker intervals in 4, 3, 2, 1 cases, respectively. Four QTLs at bins 1.05–1.06, 1.08–1.09 and 7.03–7.04 were commonly detected in the same or near bins in all three generations. Six and 2 QTLs showed consistency across RIL/F_2:3 or RIL/BC₂F₂ generations respectively. Nine meta-QTLs (mQTL) were detected on chromosomes 1, 4, 6, 7, 8 and 10. Except mQTL7-1, only related with PV, other mQTLs included two or three traits, reflecting pleiotropic or tightly linkaged QTLs for popping characteristics. The QTL influencing all the three popping traits at bins 1.05–1.06 were also detected in other previous researches using different populations, which could be put into use in marker assisted breeding for popping characteristics in popcorn.     

Quantitative trait loci for yellow pigment concentration and individual carotenoid compounds in durum wheat

A defining factor for the commercial value of durum wheat pasta is its amber colour, which depends on the semolina yellow pigment concentration and on the oxidative enzymatic activity. Among carotenoids controlling yellow colour, the presence of β-carotene is also important as precursors of vitamin A. The aim of the present study was to detect quantitative trait loci (QTL) for yellow pigment concentration, yellow index and individual carotenoid compounds (lutein, zeaxanthin, β-cryptoxanthin, α-carotene and β-carotene) in a durum segregant population. Total carotenoid concentration amounted to 37% of the yellow pigments, indicating unknown colour-producing compounds in the durum extracts. Lutein was the most abundant carotenoid, followed by zeaxanthin, α-carotene and β-carotene, while β-cryptoxanthin was a minor component. Phytoene synthase marker Psy-A1, 150 SSR and EST-SSR markers, and 345 DArT^® markers, were used to construct the linkage map for subsequent QTL analysis. Clusters of QTL for total and/or one or more carotenoid compounds were detected on the same chromosome regions (2A, 3B, 5A and 7A) where QTL for yellow pigment concentration and yellow index were identified. The molecular markers associated to major QTL would be useful for marker-assisted selection programs to facilitate high carotenoid concentration with high nutritional carotenoid compounds in wheat grain.     

Quantitative trait loci for seedling vigor in rice under field conditions

Previous QTL studies on seedling vigor in rice (Oryza sativa L.) were conducted all based on laboratory germination tests. In the current study, a set of recombinant inbred lines derived from a rice cross were assessed for seedling vigor related traits in natural field environments including two treatments (drained soil and flooded soil). Composite interval mapping identified nine QTL for seedling vigor traits that correlated positively with each other. Individual QTL explained 4–14% of the total trait variation. Among the QTL, three and four were specific to the drained and flooded treatments, respectively, while two others were common between the two treatments. Four QTL (qFV-1-1, qFV-3-2, qFV-5-1 and qFV-10) each simultaneously showed effect on two or more traits with additive effects always in the same direction. The QTL qFV-5-1 could be further resolved into at least two linked loci, qFV-5-1a controlling seedling height and qFV-5-1b controlling seedling dry weight while the QTL qFV-10 could be a single locus with a pleiotropic effect on both seedling height and dry weight. The QTL qFV-1-1 and qFV-3-2 expressed specially under the flooded conditions, each pleiotropically controlling both coleoptile and seedling emergence. These two QTL were completely different from that affecting seedling emergence in the drained conditions. Comparison of the QTL indicated that the QTL mapping results based on field assessments could to some extent coincide with those based on lab tests but the discrepancy between the two kinds of experiments could not be overlooked.     

Molecular genetic mapping of quantitative trait loci associated with loaf volume in hexaploid wheat (Triticum aestivum)

Major efforts in wheat research are being made to improve the yield and quality of wheat. Loaf volume (Lv) is the main quality parameter deciding the bread making potential of wheat. To genetically dissect quantitative trait loci (QTLs) for Lv, a Recombinant Inbred Line (RIL) population (F₈) was developed from a cross between two Indian wheat varieties “HI 977” and “HD 2329”. A total of 914 SSR and 100 ISSR primers were used for molecular analysis and the genetic map comprising 19 chromosomes was constructed with 202 SSR markers and 2 HMW glutenin subunit loci: Glu-B1 and Glu-D1. The phenotypic data were collected from six environments including three different agro-climatic zones for 2 consecutive years. Dissection of Lv through AMMI model revealed significant G×E variance for the trait. QTL analysis was performed using composite interval mapping. A total of 30 QTLs for Lv were detected and significant QTLs were identified on 6B and 6D chromosomes; 1B, 1D, 2A, 3A, 5B and 5D also contributed genetically to Lv. Association between 6B and 6D QTLs and variable expression of gliadins on group 6 chromosomes were discussed. QTLs detected in this study were compared with other QTL analysis in wheat.     

芝麻含油量及脂肪酸含量QTL分析

本研究以较高含油量芝麻品种“中芝13”（56.31%）和低含油量芝麻材料ZZM2748（48.75%）为亲本构建包含548个株系的RIL群体,采用近红外法对群体在2个不同环境下的含油量、油酸、亚油酸、棕榈酸和硬脂酸含量进行分析,发现群体含油量及脂肪酸含量存在较大变异,其中含油量变化在42.43%~58.38%,其与油酸和亚油酸含量无显著相关关系,但与棕榈酸显著负相关;应用软件WinQTLCart2.5和ICIMapping3.0基于构建的遗传连锁图共定位到50个相关QTL,分布在芝麻11个连锁群上,贡献率变化在1.59%~40.62%。其中,有21个QTL被两个软件同时检测到,有7个QTL在2个环境下被重复检测到。位于连锁群LG10上的qSOC_10.3和位于连锁群LG11上的qSOC_11.1遗传贡献率较大,分别为34.38%和40.62%,为控制芝麻含油量的主效QTL,其中qSOC_11.1与定位到的油酸、亚油酸、棕榈酸和硬脂酸位点重合,表现一因多效特征。通过基因组注释和差异表达分析,在两个主效位点发掘出24个候选基因。研究发现的芝麻含油量及不同脂肪酸含量遗传变异特征和获得的QTL及候选基因对相关性状的遗传改良具有指导意义和应用价值。     

大豆四粒荚数QTL分析及位点交互群体验证

为定位年际间稳定、群体间通用的大豆四粒荚QTL,以2013-2016年表型数据为基础,利用RIL群体结合SLAF-seq高密度遗传图谱对大豆四粒荚数进行QTL分析,利用含目标区间的导入系个体对QTL进行表型验证。结果表明:RILs群体大豆四粒荚QTL分析共获得8个QTL,其中在Gm06染色体上检测到4个位置相近的QTLs,加性效应为正值,区间大小0.62Mb,在Gm16染色体上检测到4个位置相同的QTL,加性效应为负值,区间大小1.04Mb,这些QTL是不同年际间稳定存在的位点。共有5个导入系个体含有Gm06染色体目标区间,这些个体在不同年际间的四粒荚表型值均显著高于轮回亲本,共有7个导入系个体含有Gm16染色体目标区间,这些个体在不同年际间的四粒荚数表型值均显著低于轮回亲本,表明目标区间的导入对导入系四粒荚数表型具有相应的增效或减效作用,从而在全基因组导入系群体中验证了QTL的准确性与通用性。研究结果为大豆四粒荚数候选基因挖掘及分子辅助育种提供理论依据。     

Rice and cold stress: methods for its evaluation and summary of cold tolerance-related quantitative trait loci

Cold stress adversely affects rice (Oryza sativa L.) growth and productivity, and has so far determined its geographical distribution. Dissecting cold stress-mediated physiological changes and understanding their genetic causes will facilitate the breeding of rice for cold tolerance. Here, we review recent progress in research on cold stress-mediated physiological traits and metabolites, and indicate their roles in the cold-response network and cold-tolerance evaluation. We also discuss criteria for evaluating cold tolerance and evaluate the scope and shortcomings of each application. Moreover, we summarize research on quantitative trait loci (QTL) related to cold stress at the germination, seedling, and reproductive stages that should provide useful information to accelerate progress in breeding cold-tolerant rice.     

Quantitative trait loci for leaf length in perennial ryegrass (Lolium perenne L.)

Leaf length is an important trait for forage grasses. Molecular marker development offers the opportunity to identify Quantitative Trait Loci (QTLs) and to begin to dissect the genetic regulation of complex traits. The objective of this study was to look for QTLs for leaf length and related traits (plant height, lamina and sheath lengths, leaf elongation rate and leaf elongation duration) in the progeny of a cross between two genotypes of Lolium perenne L. with contrasting leaf length. Measurements were performed in a plant nursery in autumn and spring, and in a heated greenhouse in winter. A high level of variability and heritability was observed for all traits. Lamina lengths at different dates were moderately but significantly correlated. For all traits, QTLs were found and explained between 0·08 and 0·44 of phenotypic variance. Although different leaf length QTLs were found at different dates, linkage groups two, four and seven were particularly important.     

小麦粒形QTL元分析及候选基因预测

粒形是影响小麦籽粒产量和品质的重要参数,是由多基因控制的复杂数量性状。为发掘控制小麦粒形相关的真实主效数量性状位点(quantitative trait loci, QTL),本研究利用BioMercator 4.2软件,以小麦高密度分子标记遗传图谱为参考图谱,对来自不同遗传作图群体的113个控制小麦粒长的QTL和86个控制粒宽的QTL进行图谱整合、映射以及QTL元分析。通过建立QTL一致性图谱,获得18个控制小麦粒长和8个控制粒宽的一致性QTL(meta quantitative trait loci, MQTL)位点,置信区间最小可达到0.57 cM,主要分布在2B、2D、3A、3B、4B、5A、5B和7D染色体上。在5A染色体Xgwm293～Xgwm304和Xgpw2120～Xgpw2273a标记区间内,预测到7个与小麦粒长和粒宽相关的候选基因。本研究为小麦粒形QTL精细定位以及分子标记辅助选择育种提供理论依据。     

Identification of quantitative trait loci for β-glucan concentration in barley grain

The amount of (1 → 3),(1 → 4)-β-d glucan (β-glucan) accumulated in cell walls of barley (Hordeum vulgare L.) kernel is an important determinant for grain end-use. Grain β-glucan concentration is affected by environmental and genetic factors and usually varies from 3 to 6%. In this study, we have analyzed the β-glucan trait in a doubled-haploid (DH) population of 170 lines grown in three separate field trials. Most of the DH lines showed β-glucan values that ranged from that of the low β-glucan parent (cultivar CDC Bold; 3.3%) to that of the high β-glucan parent (breeding line TR251; 5.4%). Eighty-eight lines of the DH population were genotyped using simple sequence repeat (SSR), amplified fragment length polymorphism (AFLP) and diversity array technology (DArT) markers, which were subsequently integrated into a barley genetic map spanning 1059 cM. Interval mapping and multiple-QTL-mapping (MQM) of quantitative trait loci (QTL) from the three trials indicated seven genomic regions associated with low grain β-glucan concentration. For all putative QTLs, the low β-glucan concentration was contributed by alleles from CDC Bold except for two loci on chromosomes 5H that were derived from TR251. A major QTL located to the centromere region of chromosome 7H was identified by both mapping methods for all three trials. The 7H QTL explained up to 39% of the β-glucan concentration and genetic markers associated with the locus may be used to aid selection of high and low β-glucan barley lines.     

Identification of quantitative trait loci for panicle structure and grain filling using a cross between indica- and japonica-type high-yielding rice cultivars

ABSTRACT

To enhance the yield potential of rice by breeding, it is important to reveal the genetic factors affecting yield components in high-yielding cultivars. Quantitative trait loci (QTL) analysis for panicle structure and spikelet weight as an index of grain filling was conducted using recombinant inbred lines (RILs) derived from a cross between an indica-dominant high-yielding cultivar, Takanari, and a japonica-dominant high-yielding cultivar, Momiroman in 2012 and 2013 in eastern Japan. The grain-filling ability of Takanari is reported to be better than that of Momiroman. Since grain filling is generally better near the tip of the panicle and decreases as the number of branches from the rachis increases, we classified whole panicles into upper and lower side panicles and spikelets into primary, secondary, and tertiary spikelets according to the number of branches from the rachis. On chromosomes 1, 4, and 6, QTLs regulating the number of spikelets per panicle and panicle structure were detected and were most likely identical to GN1a, SPIKE, and APO1, respectively, which has been previously reported as QTLs regulating the number of spikelets per panicle. Takanari produced much heavier secondary and tertiary spikelets than Momiroman on the lower side panicle. On chromosome 5, novel QTLs regulating spikelet weight were detected. The Takanari allele enhanced secondary and tertiary spikelet weight on the lower side panicle. These results indicate that it may be possible to enhance sink capacity and translocation of source with a combination of novel QTLs detected on chromosome 5 and GN1, APO1, and SPIKE.     

Heritability and quantitative trait loci of composition and structural characteristics in sorghum grain

Breeding efforts in cereal crops directed toward developing or improving end-use products of grain require assessment of existing phenotypic variance and an understanding of the genetic control of grain quality traits. To this end, a grain sorghum [Sorghum bicolor (L.) Moench] mapping population consisting of 113 F_2:7 recombinant inbred lines (RILs) derived from a cross between Sureño and RTx430 was evaluated in multiple environments for grain composition (fat, fiber, protein, starch) using near-infrared reflectance spectroscopy (NIRS), and size estimates of grain parts (embryo, vitreous endosperm, floury endosperm, kernel area) using an image-based phenotyping software system. Estimates of broad-sense heritability of grain compositional traits ranged from 0.11 to 0.90, whereas those of grain size ranged from 0.16 to 0.72. Composite interval mapping (CIM) was applied to a single nucleotide polymorphism (SNP)-based linkage map to identify marker-trait associations, and through these efforts, a total of 37 quantitative trait loci (QTL) for grain quality were identified across environments. Each QTL explained between 7 and 23% of the phenotypic variation for a given grain trait. Three of the five QTL that colocalized were for traits with significant negative correlation, which included grain protein content that was negatively correlated with grain starch content. In addition, several traits that were positively correlated (e.g. fat and fiber content) also revealed colocalized QTL. Finally, we compared the present study with previous studies identifying grain composition trait loci in an effort to identify genomic regions controlling grain traits across a diversity of environments and sorghum genotypes.     

花生荚果大小和重量相关性状的QTL定位分析

荚果相关性状是花生产量构成的重要成分。为解析花生产量及产量相关性状的遗传基础,挖掘稳定存在的QTL,以荚果大小和重量存在显著差异的中花5号和ICGV 86699为亲本衍生的包含166个重组自交系群体为材料,对3个荚果相关性状中荚果长、荚果宽在5个环境,百果重在6个环境下进行性状考察,并结合群体的基因分型数据进行QTL定位分析。共检测到9个荚果长QTL、10个荚果宽QTL和12个百果重QTL。有10个QTL在多个环境被重复检测到,其中6个QTL在不同地点重复检测到,为稳定表达QTL,且稳定表达的QTL中5个（qPLB06.2、 qPLB06.3、qPWB06.2、qHPWB04.3、qHPWB06.3）在至少1个环境中贡献率超过10%。共发现5个QTL簇,其中位于 B06上的QTL簇Ⅳ和Ⅴ,均在多个环境下检测到稳定调控荚果长、荚果宽和百果重的QTL共定位,表明这些荚果相关性状具有明显的遗传相关性。      

大豆荚皮厚性状QTL定位及候选基因挖掘

大豆(Glycine max L.)的荚皮厚是影响大豆产量的重要因素,同时,大豆荚皮内含有丰富的蛋白质和纤维素等营养物质,是植物饲料的重要来源.因此,大豆荚皮厚性状的相关研究,对大豆的专用品种育种以及大豆深加工都具有重要意义.本研究利用ICIM法对CSSLs群体进行QTL定位,同时构建高低混池,利用ICIMapping...     

大豆苗期耐盐性的遗传及QTL定位分析

利用重组自交系群体NJRIKY进行大豆苗期耐盐性的遗传及QTL定位分析。以每个家系的平均存活时间为耐盐指标,采用主基因+多基因混合遗传模型进行RIL遗传分析,结果表明,NJRIKY群体的耐盐性遗传符合F-3模型,即由3对主基因控制,没有多基因修饰,主基因遗传率是64.4%。利用Cartographer V.2.5进行QTL定位。结果显示,共检测到3个耐盐QTL,它们分别位于B1、G和K三个连锁群上,分别解释8.4%、17.9%和11.3%的表型变异。     

Genetic mapping and quantitative trait locus analysis of resistance to sterility mosaic disease in pigeonpea [Cajanus cajan (L.) Millsp.]

Sterility mosaic disease (SMD), considered as the “green plague of pigeonpea” and caused by pigeonpea sterility mosaic virus (PPSMV) is one of the major biotic factors, which leads to heavy yield losses and hence poses a big challenge for pigeonpea production in the Indian subcontinent. Variability in the sterility mosaic pathogen revealed the occurrence of five different isolates in India. Among them, three distinct SMD isolates have been characterized, viz., Patancheru, Bangalore and Coimbatore. Molecular tools offer a viable option to tackle these biotic stresses via identification of the genomic regions associated with the trait such as SMD resistance. With an aim of identifying the gene(s)/QTLs linked with SMD resistance, two F₂ populations, i.e. ICP 8863 × ICPL 20097 (segregating for Patancheru SMD isolate) and TTB 7 × ICP 7035 (segregating for both Patancheru and Bangalore SMD isolates) were developed and F_2:3 families were phenotyped for resistance to respective isolate(s) of SMD. After screening over 3000 SSR markers on parental genotypes of each mapping population, intra-specific genetic maps comprising of 11 linkage groups and 120 and 78 SSR loci were developed for ICP 8863 × ICPL 20097 and TTB 7 × ICP 7035 populations, respectively. Composite interval mapping (CIM) based QTL analysis by using genetic mapping and phenotyping data provided four QTLs for Patancheru SMD isolate and two QTLs for Bangalore SMD isolate. Identification of different QTLs for resistance to Patancheru and Bangalore SMD isolates is an indication of involvement of different genes conferring the resistance to these two SMD isolates. One QTL namely qSMD4 identified within an interval of 2.8 cM on LG 7 explaining 24.72% of phenotypic variance, once it is validated in other genetic background, seems to be a promising QTL for use in marker assisted selection. In summary, this is the first study on development of intra-specific genetic maps and identification of QTLs for SMD resistance in pigeonpea.     

花生籽仁含油量近红外模型的构建及其应用

花生(Arachis hypogaea L.)籽仁含油量是花生品质评价的重要指标,建立快速高效的含油量检测方法,对加快高油花生品种选育意义重大。本研究选用高油亲本宇花14(含油量59.32%)与低油亲本LOP215(含油量48.97%)杂交构建的RIL群体为建模材料,使用Thermo公司(美国)生产的Antaris Ⅱ型傅立叶变换近红外光谱分析仪对229份样品籽仁进行光谱采集,随后测定籽仁含油量。利用偏最小二乘法(partial least squares,PLS)构建花生籽仁含油量近红外定标模型,该模型的内部验证均方差(root mean square error of cross validation, RMSECV)为0.885,相关系数R²=0.9147。选用未参与建模的21份花生材料对该模型进行外部验证,模型预测值和化学测定值的决定系数R²=0.9492,表明该模型可适用于花生籽仁含油量检测。利用该模型对宇花14与LOP215杂交后代群体进行筛选,获得含油量超过55%的优良株系21个,含油量低于48%的株系9个,可为花生高低含油量品...     

小麦穗粒数QTL整合与元分析

小麦穗粒数是由多基因控制的复杂数量性状。为发掘控制小麦穗粒数(KNS)的真实主效数量性状位点(quantitative trait loci, QTL),本研究利用生物信息学手段,借助小麦高密度分子标记遗传图谱,对来自不同遗传作图群体的控制小麦穗粒数的163个QTL位点进行图谱整合、映射和元分析。结果表明,目标性状QTL在小麦21条染色体上不均匀分布,在2B染色体上最多,在7D染色体上最少;建立控制小麦KNS的QTL一致性图谱,最终获得35个一致性QTL(meta quantitative trait loci, MQTL)位点及其紧密连锁的候选分子标记,置信区间最小可达到0.55 cM。     

花生百果质量和百仁质量性状的QTL定位分析

为探索栽培种花生百果质量和百仁质量遗传机制,以花育28号和P76为亲本构建了包含146个家系的重组自交系（recombinant inbred line,RIL）群体,测定了3个环境下的百果质量与百仁质量表型数据,并利用单环境和多环境联合定位进行QTL的鉴定。结果表明,在不同环境下RIL群体百果质量和百仁质量均表现为超亲遗传。基于多环境QTL分析检测到5个与百果质量、10个与百仁质量相关的QTL。基于单环境QTL分析共检测到3个百果质量相关位点qHPW05.1、qHPW07.1和qHPW19.1,分布于3个连锁群上。其中qHPW07.1在三个环境下稳定表达,表型贡献率4.610%~8.840%;qHPW19.1在两个环境下稳定表达,表型贡献率9.985%~11.224%。检测到4个百仁质量相关位点qHSW05.1、qHSW07.1、qHSW19.1和qHSW20.1,分布于4个连锁群上。其中qHSW 07.1在两个环境下稳定表达,表型贡献率7.155%~10.464%;qHSW 19.1在三个环境下稳定表达,表型贡献率7.239%~13.845%。获得控制百果质量和百仁质量的QTL簇2个,分别位于LG07（Cluster I）和LG19（Cluster II）。本研究结果为后续相关基因克隆和花生产量性状改良提供了理论基础。     

油菜开花期QTL定位和候选基因分析

为辅助选育早熟油菜品种、克隆油菜开花期基因及开发花期分子标记,以已测序的油菜品种中双11 (Z) 和重测序的油菜品系No.73290 (N)为亲本构建的含184个单株的BnaZNF2群体为材料,通过分析该群体的基因型数据和F2:3家系连续三年（2010-2012）在武汉的表型数据,对开花期QTL进行检测和整合,定位到分布在11个连锁群上的14个开花期QTL。其中只有5个QTL能在3年中重复检测到,分别是qDtF.A2-1、qDtF.A6-2、qDtF.C2-1、qDtF. C2-2 和qDtF.C3-1,贡献率在7.1%～21.1%之间。通过查阅文献和在拟南芥、水稻等作物网站上搜索,搜集到442 个与植物开花期有关的基因。基于油菜基因组物理图谱,通过生物信息学分析,在本研究定位的QTL区间上筛选到54个可能的候选基因,可以用于开花期基因的克隆。在5个主要QTL区间内分别定位到8、5、4、2和4个候选基因,其中有15个双亲中存在序列差异,可以开发开花期的功能标记用于分子标记辅助选择育种。