Identification of quantitative trait loci associated with iron deficiency chlorosis resistance in groundnut (Arachis hypogaea)

Iron deficiency chlorosis is an important abiotic stress affecting groundnut production worldwide in calcareous and alkaline soils with a pH of 7.5–8.5. To identify genomic regions controlling iron deficiency chlorosis resistance in groundnut, the recombinant inbred line population from the cross TAG 24 × ICGV 86031 was evaluated for associated traits like visual chlorosis rating and SPAD chlorophyll meter reading across three crop growth stages for two consecutive years. Thirty-two QTLs were identified for visual chlorosis rating (3.9%–31.8% phenotypic variance explained [PVE]) and SPAD chlorophyll meter reading [3.8%–11% PVE] across three stages over 2 years. This is the first report of identification of QTLs for iron deficiency chlorosis resistance-associated traits in groundnut. Three major QTLs (>10% PVE) were identified at severe stage, while majority of other QTLs were having small effects. Interestingly, two major QTLs for visual chlorosis rating at 60 days (2013) and 90 days (2014) were located at same position on LG AhXIII. The identified QTLs/markers after validation across diverse genetic material could be used in genomics-assisted breeding.     

陆地棉光合相关性状的QTL定位分析

光合作用是棉花产量的主要物质来源。本研究以高光效陆地棉冀优861和低光效陆地棉新陆早25号为亲本组配的196个F₂单株为作图群体,利用SSR（Simple Sequence Repeat）标记构建陆陆杂交遗传连锁图谱,共有30个标记位点连锁,包含4个连锁群,全长244.4cM。利用QTL IciMapping 4.1软件的完备区间作图法对冀优861×新陆早25号F_2:3家系的光合相关性状进行QTL作图分析,共定位到光合相关5个性状的10个QTLs,其中1个光合速率QTL和1个胞间CO₂浓度QTL分别定位在D3和D7染色体上。本研究为棉花光合相关性状QTL的精细定位及分离克隆打下基础,为聚合棉花高光效分子标记辅助育种提供理论依据。     

Mapping of quantitative trait loci for seminal root morphology and gravitropic response in rice

In order to gain a better understanding of the complex root traits observed in previous studies using a mapping population derived from a Bala × Azucena cross, an experiment was conducted growing plants in agar-filled Perspex chambers with the aim of identifying quantitative trait loci (QTLs) for both seminal root morphology (SRM) and gravitropic response. A total of four main effect QTLs were detected for SRM (a measurement of the degree of a wavy/curly seminal root phenotype); two were located on chromosome 2, one at the top of chromosome 3 and one on chromosome 11. Two main effect QTLs were detected for the gravitropic response (the degree of bending of the growing seminal root when subjected to a 90° rotation); one on chromosome 6 and 1 on chromosome 11. As well as main effect QTLs, an epistatic interaction was observed for each of the traits. For SRM an interaction was detected between the top and the bottom of chromosome 4. For the gravitropic response an interaction was observed between a location on chromosome 6 and 11. Both these interactions were confirmed by analysis of variance using marker classes and the epistatic gravitropic response was also confirmed using a pair of near isogenic lines. All the SRM QTLs detected in this experiment co-localise with root growth QTLs (root penetration or morphology) detected previously in the mapping population. This information could prove valuable in attempts to identify candidate genes for these potentially valuable QTLs because we could postulate that the underlying genes should be involved in the pathway of gravity detection, signal transduction or the growth response to gravity.     

QTLs for chlorophyll and chlorophyll fluorescence parameters in barley under post-flowering drought

Drought is one of the major factors limiting barley yields in many developing countries worldwide. The identification of molecular markers linked to genes controlling drought tolerance in barley is one way to improve breeding efficiency. In this study, we analyzed the quantitative trait loci (QTL) controlling chlorophyll content and chlorophyll fluorescence in 194 recombinant inbred lines (RILs) developed from the cross between the cultivar ‘Arta’ and Hordeum spontaneum 41-1. Five traits, chlorophyll content, and four chlorophyll fluorescence parameters, namely initial fluorescence (F_o), maximum fluorescence (F_m), variable fluorescence (F_v), and maximum quantum efficiency of PSII (F_v/F_m) which are related to the activity of the photosynthetic apparatus, were measured under well-watered and drought stress conditions at post-flowering stage. QTL analysis identified a total of nine and five genomic regions, under well-watered and drought stress conditions, respectively, that were significantly associated with the expression of the five target traits at post-flowering stage. No common QTL was detected except one for chlorophyll content, which was identified in both growth conditions, demonstrating that the genetic control of the expression of the traits related to photosynthesis differed under different water conditions. A QTL for F_v/F_m, which is related to the drought tolerance of photosynthesis was identified on chromosome 2H at 116 cM in the linkage map under drought stress. This QTL alone explained more than 15% of phenotypic variance of maximum quantum yield of PSII, and was also associated with the expression of four other traits. In addition, another QTL for F_v/F_m was also located on the same chromosome (2H) but at 135.7 cM explaining around 9% of the phenotypic variance under drought conditions. The result presented here suggest that two major loci, located on chromosome 2H, are involved in the development of functional chloroplast at post-flowering stage for drought tolerance of photosynthesis in barley under drought stress. If validated in other populations, chlorophyll fluorescence parameters could be used as selection criteria for drought tolerance.     

Mapping and validation of the quantitative trait loci for leaf stay‐green‐associated parameters in maize

Functional stay‐green is generally regarded as a desirable trait of varieties in major crops including maize. In this study, we used an F_3:4 recombinant inbred line population with 165 lines from a cross between a stay‐green inbred line (Zheng58) and a model inbred line (B73) using 211 polymorphic simple sequence repeat markers to map quantitative trait loci for three stay‐green‐associated parameters, chlorophyll content, photosystem II photochemical efficiency and stay‐green area, at maturity stage, detected a total of 23 quantitative trait loci (QTL) on nine chromosomes. Single QTL explained 3.7–13.5% of the phenotypic variance. Additionally, we validated some important stay‐green QTL using a heterogeneous inbred family approach and found that the stay‐green‐associated parameters were significantly correlated with the plant yield. This study may contribute to a better insight into the regulatory mechanism behind leaf stay‐green in maize and a novel development of elite maize varieties with delayed leaf senescence through molecular marker‐assisted selection.     

Mapping of quantitative trait loci controlling cotton leaf curl disease resistance in upland cotton

Cotton leaf curl disease (CLCuD) is a major threat to cotton production in Asia and Africa. Using marker-assisted breeding can be the best sustainable approach to tackle CLCuD. Identification of new QTLs in the indigenous cotton germplasm is necessary to combat CLCuD. The current study was designed to construct a genetic linkage map of bi-parental F2:F3 populations developed from highly tolerant MNH-886 and highly susceptible S-12 cotton cultivars. One hundred seven CLCuD-associated simple sequence repeat (SSR) marker alleles were identified as polymorphic and three new QTLs were found on chromosomes C11, C19 and C21. Two QTLs on chromosomes C11 and C19 were detected in both F2 and F3 populations in the region flanked by SSR markers CIR316 and BNL4094, and BNL285 and BNL3348, respectively. Whereas, one QTL on chromosome C21 was detected in the region flanked by SSR markers JESPR158 and JESPR135 in both F2 and F3 generations. The CLCuD-associated QTLs identified in this study can help fine-tune the molecular mapping of the QTLs on the cotton genome against CLCuD.     

Mapping quantitative trait loci for growth responses to exogenously applied stress induced hormones in wheat

Biotic and abiotic stresses are responsible for much of the variation in wheat production worldwide. The plant, in responding to stress events, increases the endogenous synthesis of hormones such as Abscisic Acid, Ethylene, Jasmonic Acid and Salicylic Acid. This paper was aimed at determining the location of plant-defence genes triggered by treatment with stress-induced hormones in a set of recombinant doubled haploid substitution lines involving variation for a single chromosome, 6A, previously shown to carry genes for aphid resistance. Eighty-three doubled haploid recombinant substitution (DHR) lines for chromosome 6A derived from the F₁ of “Chinese Spring” (CS) × “Chinese Spring (Synthetic 6A)” (S6A) substitution line, were used as a mapping population. Plants of every genotype at the fully expanded 3rd leaf stage were subjected to four hormone treatments: ethylene (E), jasmonic acid (J), salicylic acid (S) and abscisic acid (A), together with an untreated control. The changes in a range of phenotypic traits were measured, aerial fresh weight (AFWC), aerial dry weight (ADWC), root fresh weight (RFWC), root dry weight (RDWC), foliar area (FAC). These were recorded twice: at the onset of the experiment before spraying with hormones and 72 h later. Nine QTLs were detected which were significantly associated with 6A molecular markers, explaining the variation for ADWC, RDWC and FAC. Most of the QTLs were associated with the interval between loci Xgwm459 and Xgwm334a, located in the telomeric region of the short arm of 6A. The dissection of complex agronomic traits such as tolerance to stress and QTLs related to exogenous hormone treatments could be used in marker-assisted selection for breeding wheat with tolerance to stresses.     

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。     

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。     

玉米籽粒中花色苷和黑色素含量的QTL分析

花色苷和黑色素是黑玉米籽粒中重要而有益的化学成分,深入开展其QTL定位研究,对于色素相关基因的克隆与转化和分子标记辅助育种,具有重要的理论意义和应用价值。本文利用一个黑玉米自交系SDM为共同父本,分别与白玉米自交系木6和黄玉米自交系Mo17杂交,构建2个相关F_2:3群体(分别缩写为WD和YD),对玉米籽粒中花色苷含量(ACK)和黑色素含量(MCK)进行QTL分析。结果表明,黑玉米SDM籽粒中的花色苷和黑色素含量均极显著高于木6和Mo17,2种色素含量间呈极显著正相关。2个群体中共检测到17个色素相关的QTL,其中与花色苷含量相关的QTL在2个群体中各4个,分布在第4、第6、第7和第10染色体上,与黑色素含量相关的QTL在WD和YD群体中分别为4个和5个,分布在第1、第2、第6、第7和第10染色体上。2个群体检测到QTL的数量、分布和对表型的贡献率均高度一致,而且解释花色苷含量和黑色素含量变异大的QTL在2个群体中均有成簇分布的现象,主要表现在bin 6.04处的标记区间umc1796~mmc2006内和bin 10.04处的标记区间umc2043~bnlg1028内,分别解释表型变异的12.7%~21.3%和8.6%~21.3%。它们可能是一因多效的同一QTL或者是在该区段内紧密连锁的不同QTL。上位性分析表明,2个群体中检测到的上位性QTL的数量、位置和对表型的贡献率差别均较大,WD群体的上位性效应明显大于YD群体,说明上位性效应对遗传背景更加敏感,需要进一步深入研究贡献率大的上位性QTL及其利用。     

水稻闭颖授粉QTL的初步定位分析

水稻闭颖授粉遗传位点的发掘旨在研究其闭颖授粉机制。本研究利用闭颖水稻品系RV2429为母本,开颖授粉水稻品系Koshihikari为父本杂交得到F1代,F1自交得到F2,以双亲本及F2为研究材料,对双亲本的粒型及花器官结构进行比较,推测出浆片体积增加较小是RV2429闭颖授粉的原因。统计F2群体的开花表型和基因型,通过QTL IciMapping 4.1软件分析,初步定位到4个与闭颖授粉相关的QTLs,qCL4.1(4.75%),LOD值为2.559 3、qCL6.1 (5.12%),LOD值为2.999 1、qCL11.1 (5.06%),LOD值为2.799 6和qCL12.1(4.77%),LOD值为3.052 1,分别在4、6、11、12染色体上。本研究结果明确了控制水稻闭颖授粉的新基因位置,为以后的精细定位提供了实验依据,为加快闭颖授粉的育种进程提供帮助,对抑制基因漂流具有重要意义。     

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。     

鲁棉研15号纤维品质性状QTL定位研究

 以陆地棉（Gossypium hirsutum L.）杂交种鲁棉研15号的F₂群体为作图群体,利用SSR标记和JoinMap3.0软件构建遗传连锁图谱;利用复合区间作图法分别对随机组成的3个鲁棉研15号的F_2:3家系亚群体进行纤维品质性状QTL定位。构建的遗传连锁图谱包含116个多态位点,25个连锁群,全长892.25 cM,覆盖棉花总基因组的20.05%,平均每个连锁群4.64个标记,标记间平均距离7.76 cM;根据已有图谱的定位结果,19个连锁群与染色体建立了联系。在3个F_2:3家系亚群体中共检测到46个QTL,其中16个为纤维长度（FL）QTL、7个为纤维强度（FS）、12个为麦克隆值（FM）、6个为伸长率（FE）,5个为整齐度指数（FU）。发现在A_h05、A_h08、A_h09、D_h02染色体上QTL有成簇分布的现象,并在3个亚群体中检测到一些受环境影响较小、稳定遗传的QTL。这些QTL可以在今后应用于分子标记辅助选择。     

大白菜干烧心病抗性QTL定位研究

对大白菜干烧心病抗性不同的材料进行研究,明确其抗性遗传规律,并完成抗性基因的QTL定位分析,为分子标记辅助选择(MAS)育种与抗病机理的研究提供理论依据。采用大白菜干烧心病抗性显著不同的青麻叶类型高代自交系黑227(抗干烧心病)和包头型高代自交系B120(感干烧心病)作为材料,将得到的杂种F1进行小孢子培养得到DH群体,将亲本和F1及DH群体种植于日光温室,根据田间干烧心病发病程度进行分级,进而得出病情指数,并结合已构建的大白菜分子遗传图谱,利用Map QTL 5.0软件对大白菜干烧心病抗性基因进行定位。结果表明,试材所含有的大白菜干烧心病抗性基因符合数量性状遗传的特点,共检测到2个与大白菜干烧心病抗性基因连锁的InDel分子标记Br ID10343和Br ID10349,这2个标记均位于Chr.7,其间的遗传距离为1.031 c M,遗传贡献率均达到40%以上。InDel分子标记Br ID10343和Br ID10349与大白菜干烧心病抗性基因紧密连锁,结果为抗性基因主效QTL的精细定位及MAS抗病育种奠定了良好基础。     

甜玉米穗位高的QTL定位

选用穗位高有显著差异的甜玉米自交系T14和T4为亲本配制杂交组合,以330个F2单株为作图群体,用复合区间作图法在玉米全基因组上检测穗位高QTL。结果显示,在F2:3群体中检测到7个与甜玉米穗位高相关的QTL,分别位于玉米第3、4、8、9、10染色体上,可解释3.2%~13.3%的表型变异。这一结果有望为加快高产、耐密和抗倒伏育种进程,实现分子标记辅助选择提供理论依据。     

大豆脂肪及脂肪酸组分含量的QTL定位

脂肪及脂肪酸组分的改良是大豆油脂品质育种的主要方面。本研究旨在构建遗传图谱,定位大豆脂肪及脂肪酸组分的QTL,为大豆油脂品质育种提供参考。以Essex×ZDD2315的114个BC₁F₁单株为作图群体,构建了250个SSR标记和1个形态标记,具有25个连锁群的遗传图谱,覆盖大豆基因组2 963.5 cM,平均每个连锁群上10.0个标记,标记平均间距11.8 cM。用BC₁F₃家系3个重复的表型平均值代表相对应的BC₁F₁单株表型值,采用Win QTL Cartographer 2.5复合区间作图法（CIM）检测到18个控制脂肪及脂肪酸组分含量的QTL,位于9个不同的连锁群上,表型贡献率为9.6%~34.5%;多区间作图法（MIM）检测到与CIM区间相同的7个QTL（fat-1, pal-1, st-1, ole-1, lin-1, lin-4和lio-2）,区间相近的2个QTL（ole-4和lin-5）,位于6个不同的连锁群上,表型贡献率为8.2%~39.3%。CIM法检测到的其他9个QTL有待进一步验证。大豆脂肪及脂肪酸组分含量的主效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,育种中既要注意主效QTL的利用,又要考虑微效多基因的积聚。     

普通小麦对仓储害虫玉米象的抗性QTL分析

以普通小麦品种川农16与人工合成小麦衍生品种川麦42为亲本构建了含有127个株系的重组自交系(RIL)群体,将2008和2009年收获的种子用玉米象(Sitophilus zeamais)虫卵进行接种,并于2009年11月开始储藏,次年8月和10月进行虫害调查。利用复合区间作图法(CIM)对RIL群体的抗虫性进行QTL定位分析。利用2008年收获群体检测到位于3B、2D和3D染色体的3个QTL,贡献率依次为10.2%、8.5%和8.3%;利用2009年收获群体检测到位于3D和4B的2个QTL,贡献率分别为8.5%和11.3%。位于3D染色体Xbarc6–Xgwm112标记区间内的QTL在年度间重复检测到,贡献率为8.3%~8.5%,抗性位点来自川农16。     

马铃薯重要性状QTL定位及3个抗病性状分子标记辅助选育

马铃薯是我国主要粮食作物之一,马铃薯分子育种研究具有重要意义。在二倍体马铃薯中,重要性状控制基因的QTL定位及克隆已经有大量报道。近年,随着同源四倍体分析软件的开发,四倍体马铃薯的遗传图谱构建和QTL定位也取得了突破性进展。分子标记是马铃薯育种的重要辅助手段,可快速准确筛选出多个优良性状。对马铃薯重要农艺性状的QTL定位和克隆,以及3个抗病性状分子标记辅助选育的研究进展进行概述,为加快马铃薯分子育种研究提供参考和实践依据。     

Tagging quantitative trait loci associated with grain yield and root morphological traits in rice (Oryza sativa L.) under contrasting moisture regimes

Plant breeding for drought-prone habitats envisages a favorable combination of grain yield and drought resistance. Though several components enhancing drought resistance have been identified in rice,their association with grain yield, under low-moisture stress, has been established in very few instances. We attempt to study the associations between rice grain yield and root system parameters both at phenotypic and genotypic levels. The doubled haploid population of IR64/Azucena was evaluated for root related traits at peak vegetative stage and grain yield related traits under both low-moisture stress and non stress conditions. ‘Mean environment’ was computed for yield related traits. Correlation and QTL mapping was attempted to find out the associations. The correlation between maximum root length and grain yield was positive under stress and negative in non stress. Genotypes with thicker and deeper roots, manifested higher biomass and grain yield under stress. Only one QTL found to increase days to flowering in non stress was also found to influence root volume and dry weight negatively under stress. The study suggests that loci enhancing grain yield and related traits were not pleiotropic with loci for desirable root morphological traits studied under low-moisture stress at vegetative stage, in the genetic material used in the study. It is thus possible to combine higher grain yield and desirable root morphological traits, favorably, to enhance productivity of rice under low-moisture stress. In rainfed ecologies, where deep roots contribute to enhanced drought resistance in rice, the results indicate the possibility of combining drought resistance with higher levels of grain yield. This revised version was published online in August 2006 with corrections to the Cover Date.