小麦品质性状的QTL定位研究进展

本文系统地总结了国内外小麦品质性状QTL定位研究的主要性状、所用群体、标记类型、QTL定位所在的染色体位置及贡献率的大小,提出了小麦品质性状QTL定位中存在的问题,展望了小麦品质性状QTL定位的发展方向。     

Dissecting anxiety-related QTLs in mice by univariate and multivariate mapping

To detect genes underlying anxiety-related traits in mice,we performed univariate and multivariate QTL mapping analyses of phenotypes obtained from 71 mice of the BXD recombinant inbred (RI) strains (n=528 mice) and their parental strains (C57BL/6J and DBA/2J).Separate and joint mapping analyses were carried out using a linkage map composed of 506 simple sequence repeats (SSRs).The main QTL effects,interactions between pairs of QTLs (epistasis),and their environmental interactions were estimated.The results showed that anxiety-related traits were influenced by multiple QTLs (five main effect QTLs and three epistatic QTLs).Ten potential anxiety-related candidate genes within the QTL intervals on chromosomes 5,13 and 15 were identified.Some of these genes have been reported previously to be associated with the anxiety response.Based on our results,it is suggested that the multivariate QTL mapping approach improves the statistical power for detecting QTL and the precision of parameter estimation.Moreover,multivariate mapping can also detect pleiotropic QTL effects.     

Methods for mapping QTLs underlying endosperm traits based on random hybridization design

Cereal grains are mainly composed of endosperms, which are humans’ staple food containing rich nutri- tious substances such as starch, protein and lipid. Many endosperm traits are related to grain yield and quality. Therefore, studying the genetic basis …     

Statistical method for mapping QTLs for complex traits based on two backcross populations

Most important agronomic and quality traits of crops are quantitative in nature.The genetic variations in such traits are usually controlled by sets of genes called quantitative trait loci (QTLs),and the interactions between QTLs and the environment.It is crucial to understand the genetic architecture of complex traits to design efficient strategies for plant breeding.In the present study,a new experimental design and the corresponding statistical method are presented for QTL mapping.The proposed mapping population is composed of double backcross populations derived from backcrossing both homozygous parents to DH (double haploid) or RI (recombinant inbreeding) lines separately.Such an immortal mapping population allows for across-environment replications,and can be used to estimate dominance effects,epistatic effects,and QTL-environment interactions,remedying the drawbacks of a single backcross population.In this method,the mixed linear model approach is used to estimate the positions of QTLs and their various effects including the QTL additive,dominance,and epistatic effects,and QTL-environment interaction effects (QE).Monte Carlo simulations were conducted to investigate the performance of the proposed method and to assess the accuracy and efficiency of its estimations.The results showed that the proposed method could estimate the positions and the genetic effects of QTLs with high efficiency.     

玉米产量相关性状的QTL定位与剖析

玉米因其自身具有高产潜质而成为了当今世界最重要的粮食作物之一.玉米产量是复杂的数量性状,由许多主/微效基因控制,易受各种环境因素影响.果穗是玉米的主要收获器官,籽粒性状是玉米品质的重要体现,因此发掘玉米穗部性状和籽粒性状相关QTL对玉米的遗传改良,培育优质高产的玉米具有重要意义.本研究白刺包谷(P2)和妻染黄(P13)为亲本构建了包含152个家系的F2∶3作图群体,选择在两亲本间具有多态性的176个微卫星标记构建遗传图谱,对产量相关性状进行了单环境的QTL定位与分析.最终定位到了14个QTL,分布在除9号染色体外的其余9条染色体上,单个QTL可解释的表型变异率为4.9％～18.8％.值得注意的是,在6号染色体上的百粒重和穗行数的一致性QTL(qHKW06-1和qERN06-1)与8号染色体上的穗行数QTL(qERN08-1)是本研究中特有的,其中qERN08-1解释了12.4％的表型变异率.     

小麦株高性状的QTL定位分析

以国际小麦作图组织的重组自交系群体W7984×Opata85为材料,在两种不同试验环境(2009年天津东丽区、2009年天津西青区姚村)下,分析其亲本及114个株系群体的株高,并利用QTL作图软件WinQTLCart2.5和区间作图及复合区间作图方法,对控制小麦株高性状的QTL进行定位.共检测到4个与小麦株高相关的QT...     

A new statistical method for mapping QTLs underlying endosperm traits

Genetic expression for an endosperm trait in seeds of cereal crops may be controlled simultaneously by the triploid endosperm genotypes and the diploid maternal genotypes. However, current statistical methods for mapping quantitative trait loci （QTLs） underlying endosperm traits have not been effective in dealing with the putative maternal genetic effects. Combining the quantitative genetic model for diploid maternal traits with triploid endosperm traits, here we propose a new statistical method for mapping QTLs controlling endosperm traits with maternal genetic effects. This method applies the data set of both DNA molecular marker genotypes of each plant in segregation population and the quantitative observations of single endosperms in each plant to map QTL. The maximum likelihood method implemented via the expectation-maximization algorithm was used to the estimate parameters of a putative QTL. Since this method involves the maternal effect that may contribute to endosperm traits, it might be more congruent with the genetics of endosperm traits and more helpful to increasing the precision of QTL mapping. The simulation results show the proposed method provides accurate estimates of the QTL effects and locations with high statistical power.     

Identification of salt-tolerance QTL in rice (Oryza sativa L.)

Quantitative trait loci (QTLs) controlling salt-tolerance at the seedling stage in rice (Oryza sativa L.) were identified by interval mapping (SIM) and composite interval mapping (CIM) using a doubled haploid population ZJDH and its high resolution genetic linkage map. The population was derived from an inter-subspecific cross between an indica variety Zhaiyeqing8 (ZYQ8) and a japonica variety Jingxi17 (JX17). Analysis of survival days of seedlings treated with 0.7% NaCI revealed that a major salt-tolerance quantitative trait locus (QTL), Std, was present between markers RG612 and C131 on chromosome 1 when using both MAPMAKER/QTL 1.1 and PLABQTL 1.0 (SIM). Its allele which contributes to salt-tolerance was from ZYQ8. In addition, seven more QTLs which give additive effect on salt-tolerance are identified when using PLABQTL (CIM), and most of them were from JX17.     

Estimation of statistical power and false discovery rate of QTL mapping methods through computer simulation

Many QTL mapping methods have been developed in the past two decades.Statistically,the best method should have a high detection power but a low false discovery rate (FDR).Power and FDR cannot be derived theoretically for most QTL mapping methods,but they can be properly evaluated using computer simulations.In this paper,we used four genetic models (two for independent loci and two for linked loci) to illustrate power and FDR estimation for interval mapping (IM) and inclusive composite interval mapping (ICIM).For each model,we simulated 1000 populations each of 200 doubled haploids.A support interval (SI) was first defined to indicate to which predefined QTL the significant QTL belonged.Power was calculated by counting the number of simulation runs with significant peaks higher than the logarithm of odds (LOD) threshold in the SI.Quantitative trait loci not identified in any SIs were viewed as false positives.The FDR is the rate at which QTLs are identified as significant when they are actually non-significant.Simulation results allowed us to estimate power and FDR of IM and ICIM for two independent and two linkage genetic models.Our estimates allowed us to readily compare the efficiencies of different statistical methods for QTL mapping,including the ability to separate linkage,under a wide range of genetic models.We used IM and ICIM as examples of how to estimate power and FDR,but the principles shown in this paper can be used for power analysis and comparison of any other QTL mapping methods,especially those based on interval tests.     

Starch RVA profile parameters of rice are mainly controlled byWx gene

Quantitative trait locus (QTLs) mapping for rapid visco analyser (RVA) profile parameters has been carried out by using a double haploid (DH) population derhred from a cross betweenindica variety Zhai-Ye-Qing 8 andjaponica variety Jing-Xi 17 and its genetic linkage map. The results indicate that the segregation of the RVA profiles is continually distributed among the DH lines, and some DH lines show transgressive segregation for all the parameters. A major QTL,Waxy (Wx) gene on chromosome 6 which controls the amylose synthesis, has been detected significantly for 5 traits: hot paste viscosity (HPV), cool paste viscosity (CPV), breakdown viscosity (BDV), consistency viscoslty (CSV) and setback viscoslty (SBV). Therefore, the RVA profile parameters are mainly controlled byWx gene. Other 3 and 2 QTLs have also been identified for BDV and SBV, respectively, and two of them share the same region on chromosomes 1 and 5. However, the peak viscosity (PKV) is controlled by a minor QTL on chromosome 12, qPKV-12.     

QTL analysis of flag leaf in barley （Hordeum vulgate L.） for morphological traits and chlorophyll content

To understand genetic patterns of the morphological and physiological traits in flag leaf of barley, a double haploid （DH） population derived from the parents Yerong and Franklin was used to determine quantitative trait loci （QTL） controlling length, width, length/width, and chlorophyll content of flag leaves. A total of 9 QTLs showing significantly additive effect were detected in 8 intervals on 5 chromosomes. The variation of individual QTL ranged from 1.9% to 20.2%. For chlorophyll content expressed as SPAD value, 4 QTLs were identified on chromosomes 2H, 3H and 6H; for leaf length and width, 2 QTLs located on chromosomes 5H and 7H, and 2 QTLs located on chromosome 5H were detected; and for length/width, I QTL was detected on chromosome 7H. The identification of these QTLs associated with the properties of flag leaf is useful for barley improvement in breeding programs.     

Molecular dissection of plant height QTLs using recombinant inbred lines from hybrids between common wheat （Triticum aestivum L.） and spelt wheat （Triticum spelta L.）

In wheat, plant height is an important agronomic trait, and a number of quantitative trait loci (QTLs) controlling plant height have been located. In this study, using the conditional and unconditional QTL mapping methods, combined with data from five different growth stages over two years of field trials, the developmental behavior for plant height in wheat was dissected. Nine unconditional QTLs and 8 conditional QTLs were identified, of which 6 were detected by both methods. None of the 11 QTLs was detected at all of the 5 investigated developmental stages, but 7 QTLs were detected at certain stages in both years. Further analysis identified 9 unconditional QTLs at different stages, which could explain the phenotypic variation from 4.81% to 17.35%. It was noteworthy that one major QTL designated QHt-4B-2, which was located on chromosome 4B, was detected on May 18 and 25 in both years, and its genetic contributions to plant height ranged from 13.42% to 16.13%. Moreover, of the 8 conditional QTLs identified, six were detected in both years, in the order of QHt-3B→QHt-4B-1→QHt-4B-2→QHt-4D→QHt-5A and QHt-2B expressed at the same developmental stage. The results indicate that QTL expression during plant height development is selective and in a temporal order.     

Dynamic analysis of QTL for plant height at different developmental stages in maize （Zea mays L.）

Plantheightisoneofimportantagronomictraitsinmaizebreeding.Inthepastfewyears,toincreasetheplantingdensityandpreventplantsfromlodging,studiesonthegeneticmechanismofplantheightweregivengreatattentionto.Sincethe1990s,molecularmarkershaveprovidedapowerfultooltostudythetraitofplantheightatthemolecularlevel[1—3].Butmostofresearchforplantheightonlyfocusedondataatmaturestage.Tillnow,about70genesorQTLshavebeenlocated[4].Moreover,somegeneshavebeenevencloned[5—7].Duringthevege-tativegrowthperiod,plant…     

Detecting quantitative trait loci for water use efficiency in rice using a recombinant inbred line population

Breeding rice with high water use efficiency (WUE) can ameliorate water shortage through water-saving irrigation.However,WUE is a complex quantitative trait and very few studies have been conducted to measure WUE directly.In this study,a recombined inbred line population derived from a cross between an indica lowland rice and upland japonica rice was used to dissect the genetic control of WUE by fine-monitored water supply experiments.Quantitative trait loci (QTL) were scanned for 10 traits including heading date (HD),water-consumption per day (water/d),shoot weight gain per day (shootw/d),root weight gain per day (rootw/d),kernel weight gain per day (kernelw/d),average WUE at whole plant level (WUEwhole/d),average WUE for up-ground biomass (WUEup/d),average WUE for grain yield (WUEyield/d),average economic index (econindex/d),and average root/shoot ratio per day (ratio/d).The results show that most of the traits were significantly correlated to each other.Twenty-four QTL (LOD ≥ 2.0) were detected for econindex,econindex/d,WUEyield,WUEyield/d,WUEup,WUEup/d,WUEwhole,WUEwhole/d,kernelw,kernelw/d,rootw,and water/d by composite interval mapping.These QTLs are located on chromosomes 1,2,4,6,7,8,and 12.Individual QTLs accounted for 4.97%-10.78% of the phenotypic variation explained.Some of these QTLs overlapped with previously reported drought resistance QTLs detected in this population.These results provide useful information for further dissection of the genetic basis and marker-assisted selection of WUE in rice.     

Comparative mapping of rice root traits in seedlings grown in nutrient or non-nutrient solution

The component and amount of nutrient in the growth medium are the major factors affecting root growth.For the systematic dissection of root gene expression,evaluation of nutrient and non-nutrient solutions was conducted for their effect on root traits and quantitative trait loci(QTL)mapping.Three rice root parameters,maximum root length(MRL),root dry weight(RDW),and root/ shoot ratio of dry weight(RSR),were characterized within a double haploid(DH)population from a cross of ZYQ8(indica)and JX17(japonica).The value of the three root traits in two parents all decreased under the nutrient condition compared to those under the nonnutrient condition,of which RSR decreased up to 2.6-fold on average.In the DH population,more than 70 % lines in MRL,94 % lines in RDW,and all the lines in RSR were scored lower.In total,eight QTLs were identified in nutrient system(5 from JX17 alleles and 3 from ZYQ8 alleles)while five QTLs were detected in non-nutrient system(4 from JX17 alleles and 1 from ZYQ8 alleles).Of them,one QTL for RSR was shared by both culturing systems,seven QTLs were specific in nutrient system and the other four QTLs were specific in non-nutrient system.All 13 QTLs were distributed over 7 rice chromosomes-2,3,4,5,6,9 and 10,respectively.     

Comparative mapping of QTLs for Al tolerance in rice and identification of positional Al-induced genes

Aluminum (A1) toxicity is the major factor limiting crop productivity in acid soils. In this study, a recombinant inbreed line (RIL) population derived from a cross between an A1 sensitive lowland indica rice variety IR1552 and an A1 tolerant upland japonica rice variety Azucena, was used for mapping quantitative trait loci (QTLs) for A1 tolerance. Three QTLs for relative root length (RRL) were detected on chromosome 1,9, 12, respectively, and 1 QTL for root length under A1 stress is identical on chromosome 1 after one week and two weeks stress. Comparison of QTLs on chromosome 1 from different studies indicated an identical interval between C86 and RZ801 with gene(s) for A1 tolerance. This interval provides an important start point for isolating genes responsible for A1 tolerance and understanding the genetic nature of Al tolerance in rice. Four A1 induced ESTs located in this interval were screened by reverse Northern analysis and confirmed by Northern analysis. They would be candidate genes for the QTL.     

The comparative analysis based on maize integrated QTL map and meta-analysis of plant height QTLs

Since the first publication of quantitative trait locus (QTL) localization using molecular markers[1], a large number of QTLs have been identified in different ge- netic backgrounds and environments. Affected by many factors, such as marker sets, experime…     

Quantitative trait loci （QTLs） for quality traits related to protein and starch in wheat

Quality traits in wheat （Triticum aestirum L.） were studied by quantitative trait locus （QTL） analysis in a recombinant inbred line （RIL） population, a set of 131 lines derived from Chuan 35050 × Shannong 483 cross （ChSh）. Grains from RILs were assayed for 21 quality traits related to protein and starch. A total of 35 putative QTLs for 19 traits with a single QTL explaining 7.99-40.52% of phenotypic variations were detected on 10 chromosomes, 1D, 2A, 2D, 3B, 3D, 5A, 6A, 6B, 6D, and 7B. The additive effects of 30 QTLs were positive, contributed by Chuan 35050, the remaining 5 QTLs were negative with the additive effect contributed by Shannong 483. For protein traits, 15 QTLs were obtained and most of them were located on chromosomes 1 D, 3B and 6D, while 20 QTLs for starch traits were detected and most of them were located on chromosomes 3D, 6B and 7B. Only 7 QTLs for protein and starch traits were co-located in three regions on chromosomes 1D, 2A and 2D. These protein and starch trait QTLs showed a distinct distribution pattern in certain regions and chromosomes. Twenty-two QTLs were clustered in 6 regions of 5 chromosomes. Two QTL clusters for protein traits were located on chromosomes 1D and 3B, respectively, three clusters for starch traits on chromosomes 3D, 6B and 7B, and one cluster including protein and starch traits on chromosome 1D.     

Identification and mapping of genes for improving yield from Chinese common wild rice (O. rufipogon Griff.) using advanced backcross QTL analysis

To identify useful genes from wild rice which have been lost or weakened in cultivated rice has become more and more important for modern breeding strategy. In this study, a BC4 population derived from 94W1, an acces-sion of common wild rice (Oryza rufipogon Griff.) from Dongxiang in Jiangxi Province of China, as the donor, and a high-yielding Indica cultivar (O. sativa L.), "Guichao 2", as the recipient, was used to identify quantitative trait loci (QTL) associated with yield and its components. Based on the analysis for the genotype of BC4F1 population with 87 SSR markers distributed throughout the genome and investigation of the plant height, yield and yield components of BC4F2, a total of 52 QTLs, were detected. Of 7 QTLs associated with grain yield per plant, 2 QTLs on chro-mosome 2 and chromosome 11 for grain yield, explaining 16% and 11% of the phenotypic variance respectively, were identified. The alleles from Dongxiang common wild rice in those two loci could increase the yield of "Guichao 2" by 25.9% and 23.2% respectively. The QTL on chromosome 2 increasing grain yield of cultivar is actually a major gene, which did not coincide with any previously published QTLs in rice.     

Linkage graph analysis: A linkage-group-based QTL synthesis analysis approach

Consensus quantitative trait loci (QTL) in meta-analysis of multiple independent QTL mapping experiments provides a strong foundation for marker-assisted selection and gene cloning. However, meta-analysis suffers from the lack of available genomic information and the results vary when different reference linkage maps are used. Here, to overcome these limitations, we propose a linkage-group-based QTL synthesis analysis approach that we have named linkage graph analysis. First, a graph model is constructed from derived linkage groups. Next, an unsupervised classification approach is used to obtain marker intervals with co-segregating patterns among multiple genomes. Finally, a frequent itemset mining technique is used to identify the markers (or intervals) closely linked to the QTL. The proposed method was validated by one Monte Carlo simulation study and by real data analysis of cotton genomes. Two major advantages of the new method are: (i) A reference linkage group is not required; (ii) the effect of the initial QTL is reduced because false QTLs can be detected and excluded from the dataset. The ability to reliably identify the markers associated with a true QTL is valuable in crop breeding.