棉花枯萎病抗性的QTL定位

棉花抗病育种是棉花遗传改良的重要内容.本研究以高抗枯萎病的陆地棉品系(Gossypium hirsutum L.)98134和海岛棉(Gossypium barbadence L.)感病品种新海14号为亲本,构建98134×新海14的F2及F2:3分离群体.运用SSR标记构建连锁图谱,用复合区间作图法对F2:3家系的病情指数(RD进行基因组QTL扫描,共检测到4个与棉花枯萎病相关QTL效应,分别位于3、15、23和26连锁群上.经标记值分析,该QTL能解释高值亲本的增效作用,分别解释F2:3家系变异的12.4%、20.96%、4.7%和11.9%.本研究为分子标记辅助选择抗枯萎病棉花育种提供了重要理论依据.     

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。     

大豆品种Bell中控制茎褐腐病抗性QTL的定位

许多源于PI88788抗孢囊线虫的大豆基因型同时也抗茎褐腐病。本研究目的是对品种Bell的抗茎褐腐病QTL进行定位和绘制图谱。Bell品种既抗茎褐腐病，也具有来源于PI88788的孢囊线虫抗性。最初的图谱是采用源于Bell与茎褐腐病和孢囊线虫敏感品种Colfax组合的93个F4衍生品系的群体绘制的。在2种田间环境和一种温室环境条件下，采用连锁群J的遗传标记评价了各品系的茎褐腐病抗性。     

水稻细菌性条斑病抗性QTL的定位

水稻细菌性条斑病(BLS)是水稻主要病害之一。挖掘水稻细菌性条斑病抗性基因/数量性状位点(QTL),为培育水稻抗病品种提供参考依据。以多生育期表现高抗BLS且抗病性稳定的栽培稻品系‘HD10’与全生育期高感BLS且感病性稳定的籼稻品种‘9311’为亲本,构建了F₂定位作图群体,筛选双亲本间多态性分子标记,采用混合分组分析法(BSA)结合SSR和InDel分子标记对群体的苗期和分蘖期抗性位点进行初步定位。分子标记B03021、B03045在双亲及苗期、分蘖期的抗感基因混池之间都存在多态性,并将抗性QTL位点初步定位于第2号染色体分子标记B03021和B03029之间的7 cM区域内,表型贡献率分别为13.1%和17.5%。表明‘HD10’在第2号染色体该区间稳定存在一个主效抗性QTL位点,此位点效应值较大,值得进一步挖掘和利用。     

玉米丝裂病的抗性QTL定位

选用感丝裂病的玉米自交系R08与抗丝裂病的自交系Es40组配F₂群体共348个单株,构建了包含115个SSR标记的分子遗传连锁图谱,覆盖玉米基因组2 178.6 cM,平均图距为18.9 cM。采用复合区间作图法,对F_2:4家系丝裂病数据进行抗性QTL分析,共检测到12个QTL,分别位于第1、2、4、5和7染色体,贡献率为4.22%~37.95%。其中在第1、3染色体上检测到主效QTL,贡献率均大于30%,基因作用方式均为显性,其余10个QTL的作用方式多为加性或部分显性。     

烟草抗赤星病主效QTL的候选基因初步筛选

为克隆烟草赤星病主效抗性QTL,在本实验室对抗性基因初步定位的基础上,以净叶黄与NC82组合产生的回交导入系群体BC3F2为材料,在目标区间内加密26个SNP分子标记,利用Mass ARRAY飞行质谱技术检测基因型,进一步缩小目标区间。进而利用生物信息学、RT-PCR等方法在DNA水平和RNA水平对候选基因进行了初步筛选。分析表明,主效抗病QTL所在区间被进一步定位在1.6 c M范围内,对抗感品种主效区间内基因进行DNA序列及生物信息学分析,最终将53M-1和54M-3基因确定为候选基因。两个候选基因在抗感品种中表达差异明显,分别为O-甲基转移酶和谷胱甘肽过氧化物酶类基因,与植物抗逆性相关,与烟草抗病性过程关系紧密。相关结果为进一步挖掘抗赤星病主效基因提供帮助,同时也对烟草赤星病抗性分子辅助改良具有重要意义。     

利用DH群体定位白叶枯病抗性QTL

以珍汕97和武育粳2号构建的籼粳杂交DH群体及其双亲为材料,通过接种8种白叶枯病菌株(菲律宾菌系的PX071、PX099、PX061,中国菌系的GX325、Zhe173、LN44、KS-1-21和日本本菌系的T7133),考察了该DH群体对白叶枯病抗性,并进行数量性状位点(QTL)分析.共检测到了26个QTL,分别位于除第7、第11染色体外其它10条染色体上,其中检测到有2个位点分别对4种不同的菌株有抗性,有2个位点对3种不同的菌株有抗性,3个位点对2种菌株有抗性.表明这些QTL对水稻白叶枯病均具有广谱抗性,通过分子标记辅助选择利用并聚合这些广谱抗性的QTL可以较好地改良水稻对白叶枯病的抗性.     

棉花抗黄萎病基因的QTL定位

以高感黄萎病的陆地棉品种"邯郸208"与高抗黄萎病海岛棉品种"Pima90"的136个F2单株为作图群体,构建了一个包括17个连锁群、标记间平均间距18.61cM、全长1842.8cM的陆海种间分子标记遗传连锁图,该图约覆盖棉花基因组的36.8%。单因子方差分析和复合区间作图检测到与黄萎病抗性相关的3个QTL,分别位于第四连锁群和第七连锁群上,分别解释表型变异方差的15.39%、54.11%和57.18%。初步认为海岛棉"Pima90"对陆地棉"邯郸208"的黄萎病抗性由两个主效QTL和一个微效QTL共同控制。     

大豆细菌性斑点病抗性评价及QTL定位

为了筛选获得稳定抗细菌性斑点病种质和挖掘有效抗病基因,本研究以野生型大豆ZYD00006与‘绥农14’构建的全基因组回交导入系群体为试验材料,利用高压喷雾法接种丁香假单胞杆菌Psgneau001进行细菌性斑点病抗病性鉴定。运用复合区间作图法(composite interval mapping,CIM)进行细菌性斑点病QTL定位,并针对定位区间进行基因功能注释和相关抗病基因的筛选和预测。结果表明:QTL分析共检测到6个位点与抗病相关(qbsd-D1a-1,qbsd-A1-1,qbsd-C2-1,qbsd-A2-1,qbsd-D2-1,qbsd-D2-2);分别位于1号(LG D1a)、5号(LG A1)、6号(LG C2)、8号(LG A2)、17号(LG D2)染色体上。经基因注释和筛选共获得41个候选基因,它们多与富含亮氨酸重复序列受体蛋白(LRR protein)相关。本研究通过QTL初定位明确了大豆细菌性斑点病相关区间,为进一步精细定位和分子标记辅助育种提供科学依据。     

Mapping of quantitative trait loci conferring resistance to bacterial wilt in tobacco (Nicotiana tabacum L.)

Tobacco bacterial wilt (TBW) is one of the most serious tobacco diseases in the world. Studies have shown that tobacco resistance to TBW is quantitatively inherited. This study aimed to map quantitative trait loci (QTL) conferring TBW resistance. An F_2 : 3 population containing 237 lines was developed from a cross between two flue‐cured tobacco cultivars, ‘Yanyan 97’ (YY97; moderately resistant to TBW) and ‘Honghua Dajinyuan’ (HD; highly susceptible to TBW), and a linkage map consisting of 201 simple sequence repeats (SSR) markers and spanning a total length of 2326.7 cM was constructed based on the population. Field experiments were conducted 2011 and 2012, and disease symptoms were investigated three times in each year. The phenotypic data were analysed either separately or jointly for QTL mapping using the software QTLNetwork 2.1. Eight QTL with significant main effects were mapped on chromosomes 2, 6, 12, 17 and 24. A major QTL (qBWR17a) was detected on chromosome 17, which explained up to 30% of the phenotypic variation. The results can facilitate marker‐assisted selection (MAS) in TBW resistance breeding programme.     

Mapping quantitative trait loci and expressed sequence tags related to brown planthopper resistance in rice

To map genes responsible for brown planthopper (BPH) resistance in rice, a rice genetic map was constructed based on a recombinant inbred line population from a cross between a BPH‐resistant line ‘B5’ and a susceptible variety ‘Minghui 63’. Four quantitative trait loci (QTLs) for BPH resistance were detected. ESTs differentially regulated by BPH feeding were isolated by suppressive subtractive hybridization (SSH) and assigned to chromosomes based on RFLP mapping and searches of the rice genome database. The distribution of ESTs showed some clustering, and some ESTs are related to known QTLs and known BPH resistance genes. These findings suggest that the mapping of differentially induced ESTs may be a useful strategy for the identification of candidate plant defence genes, which could be beneficial in the development of a BPH‐resistant rice variety.     

Evaluation of newly developed SSR markers and identification of quantitative trait loci for bast fibre cellulose in white jute (Corchorus capsularis)

Cellulose is one of the main chemical component of bast fibre in jute. However, quantitative trait loci (QTL) for bast fibre cellulose content remains elusive. In this study, we identified 846 new SSR markers from 70,792 unigenes in the NCBI and validated them in a panel of 24 diverse jute accessions. Of 846 SSRs, 748 (88.41%) were successfully amplified, and 585 (69.14%) showed polymorphisms, implying that these are high‐quality SSRs. Furthermore, 585 SSRs along with 5,074 polymorphic SLAF (specific locus amplified fragment) and 173 InDel markers were used to reconstruct a high‐dense linkage map in a recombinant inbred population with 104 F₈ lines. Totally, 835 markers were successfully mapped to a whole length of 604.5 cM with a mean distance of 2.84 cM between adjacent markers. Furthermore, five QTLs for bast fibre cellulose were identified. One major QTL (qBFC1‐1) was stable in 2 years and explained average phenotypic variance with 14.34%. These results may be useful for developing enhanced bast fibre quality in white jute through marker‐assisted selection (MAS) breeding.     

Identification of quantitative trait loci underlying resistance of soybean to Fusarium graminearum

Fusarium graminearum could cause serious yield loss of soybean. Host resistance could offer an economical and effective way to control F. graminearum. The aims of this study were to identify and confirm quantitative trait loci (QTLs) underlying resistance to F. graminearum, and to analyse the genetic effects of pyramid resistance QTL on resistance level. A total of 140 F_2:14 recombinant inbred lines (RILs) were constructed via the cross between 'Hefeng 25' (moderate resistance to F. graminearum) and 'Conrad' (resistance to F. graminearum). The molecular genetic linkage map was constructed based on 164 simple sequence repeat (SSR) markers. A total of seven QTLs underlying F. graminearum resistance, located on six chromosomes, were identified. Among these seven identified QTLs, beneficial allele of qFG-1, qFG-2 and qFG-3 derived from 'Hefeng 25' and beneficial allele of qFG-4, qFG-5, qFG-6, qFG-7 derived from 'Conrad'. Of these seven identified QTLs, qFG-1, qFG-3, qFG-4 and qFG-5 were novel for F. graminearum resistance. Four pairs of QTLs with significant epistatic effects were found. The accumulation of resistance QTL was positively correlated with decreases in disease severity index, which was valuable for improving efficiency of marker-assistant breeding in F. graminearum resistance.     

Mapping quantitative trait loci for yield-related traits in soybean (Glycine max L.)

Development of soybean cultivars with high seed yield is a major focus in soybean breeding programs. This study was conducted to identify genetic loci associated with seed yield-related traits in soybean and also to clarify consistency of the detected QTLs with QTLs found by previous researchers. A population of 135 F_2:3 lines was developed from a cross between a vegetable soybean line (MJ0004-6) and a landrace cultivar from Myanmar ({"type":"entrez-nucleotide","attrs":{"text":"R18500","term_id":"772110","term_text":"R18500"}}R18500). They were evaluated in the experimental field of Kasetsart University, Kamphaeng Saen, Nakhon Pathom, Thailand in a randomized complete block design with two replications each in 2011 and 2012 growing seasons. The two parents exhibited contrasting characteristics for most of the traits that were mapped. Analysis of variance showed that the main effects of genotype and environment (year) were significant for all studied traits. Genotype by environment interaction was also highly significant for all the traits. The population was genotyped by 149 polymorphic SSR markers and the genetic map consisted of 129 SSR loci which converged into 38 linkage groups covering 1156 cM of soybean genome. There were 10 QTLs significantly associated with seed yield-related traits across two seasons with single QTLs explaining between 5.0% to 21.9% of the phenotypic variation. Three of these QTLs were detected in both years for days to flowering, days to maturity and 100 seed weight. Most of the detected QTLs in our research were consistent with earlier QTLs reported by previous researchers. However, four novel QTLs including SF1, SF2 and SF3 on linkage groups L and N for seed filling period and PN1 on linkage group D1b for pod number were identified in the present study.     

Potential for effective marker-assisted selection of three quantitative trait loci conferring adult plant resistance to powdery mildew in elite wheat breeding populations

Three quantitative trait loci (QTL) associated with adult plant resistance (APR) to powdery mildew (Blumeria graminis) in wheat (Triticum aestivum) cultivar ‘Massey’ were mapped in a previous study. The three QTL were located on chromosomes 2A, 2B and 1B, and explained 50% of the total phenotypic variation. A 293 recombinant inbred line (RIL) breeding population (UJ) derived from the cross of ‘USG 3209’, a derivative of ‘Massey’, and ‘Jaypee’ was used to evaluate the potential effectiveness of marker‐assisted selection (MAS) for APR. Powdery mildew severities of the 293 UJ RILs were evaluated in 2002 (F_{5 : 6}) and 2003 (F_{6 : 7}) under natural disease pressure in the field. The 293 RILs were also evaluated for disease severity in a 2004 (F_{7 : 8}) greenhouse experiment using a composite of five different isolates of B. graminis. Selection of RILs possessing the QTL on chromosome 2A, and to a lesser extent, the one on chromosome 1B was effective in identifying powdery mildew resistance in both greenhouse and field experiments. Overall, selecting RILs with QTL on chromosomes 2A and 2B was most successful in identifying highly resistant RILs, which had mean mildew severities of 4.4% and 3.2% in 2002 and 2003 field experiments, respectively. Breeders implementing MAS programs for APR to powdery mildew via selection of RILs containing the two QTL on chromosomes 2A and 2B likely will obtain RILs having high levels of resistance in the field, however combining all three QTL may ensure greater durability.     

Fine mapping of quantitative trait loci using linkage disequilibrium in inbred plant populations

Linkage disequilibrium (LD)-based methods capitalize on the number of generations that occurred since the appearance of a mutation at a QTL and can produce extremely accurate estimates of the QTL position. Here, we describe a regression methodology to estimate the effect of marker haplotypes on a quantitative trait for the case of inbred plant populations. The method builds upon probabilities of being 'Identical by Descent' that are obtained via a gene-dropping simulation, where inbreeding is assumed to be due to a single seed descent process. The method was empirically tested via Monte Carlo simulation and results showed that the power to detect the true QTL position depended on the age of the QTL mutation, effective population size and marker distances. Also, increased marker polymorphism dramatically improved power and the method seemed fairly robust to differences in genetic and population assumptions. This revised version was published online in July 2006 with corrections to the Cover Date.     

An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: The basic concepts

Recognizing the enormous potential of DNA markers in plant breeding, many agricultural research centers and plant breeding institutes have adopted the capacity for marker development and marker-assisted selection (MAS). However, due to rapid developments in marker technology, statistical methodology for identifying quantitative trait loci (QTLs) and the jargon used by molecular biologists, the utility of DNA markers in plant breeding may not be clearly understood by non-molecular biologists. This review provides an introduction to DNA markers and the concept of polymorphism, linkage analysis and map construction, the principles of QTL analysis and how markers may be applied in breeding programs using MAS. This review has been specifically written for readers who have only a basic knowledge of molecular biology and/or plant genetics. Its format is therefore ideal for conventional plant breeders, physiologists, pathologists, other plant scientists and students.     

QTL mapping of maize (Zea mays) stay-green traits and their relationship to yield

A maize genetic linkage map derived from 115 simple sequence repeat (SSR) markers was constructed from an F₂ population. The F₂ was generated from a cross between a stay-green inbred line (Q319) and a normal inbred line (Mo17). The map resolved 10 linkage groups and spanned 1431.0 cM in length with an average genetic distance of 12.44 cM between two neighbouring loci. A total of 14 quantitative trait loci (QTL) were detected for stay-green traits at different postflowering time intervals and identified by composite interval mapping. The respective QTL contribution to phenotypic variance ranged from 5.40% to 11.49%, with trait synergistic action from Q319. Moreover, maize stay-green traits were closely correlated to grain yield. Additional QTL analyses indicated that multiple intervals of stay-green QTL overlapped with yield QTL.