小麦蛋白质和淀粉品质性状的QTL分析

利用衍生自“川35050×山农483”组合包括131个系的RIL群体,对21个与蛋白质和淀粉相关的品质性状进行了QTL分析．共检测了19个性状的35个加性QTL,单个QTL可解释表型变异的7．99%—40．52％,这些QTL分布在1D,2A,2D,3B,3D,5A,6A,6B,6D和7B等10条染色体．30个QTL的加性效应值为正值,其增加效应来自亲本川35050;其余5个QTL为负值,其增加效应来自亲本山农483．获得了蛋白质性状的15个QTL,主要分布在1D,3B和6D染色体;检测到淀粉性状的20个QTL,主要分布在3D,6B和7B染色体;只有7个（20％）交叠QTL（co—location QTL）涉及蛋白质和淀粉性状两方面性状．蛋白质和淀粉性状的QTL有分布在不同染色体、不同区域的趋势．22个QTL簇集于5条染色体的6个区域．蛋白质性状的2个QTL簇（QTL cluster）位于1D和3B染色体,淀粉性状的3个QTL簇位于3D,6B和7B染色体,而涉及蛋白质和淀粉性状的1个QTL簇位于1D染色体．     

影响小麦加工品质数量性状位点的研究

以M5和M16为亲本构建的重组自交系为材料，对影响小麦加工品质性状的数量性状位点（QTL）进行了研究．检测了群体中籽粒硬度、蛋白质含量、SDS沉降值、拉伸面积等品质性状，它们在群体中呈近似正态的连续分布，为多基因控制的数量性状．利用43个SSR标记和42个AFLP标记构建了相关染色体的分子连锁图．在1A、5D、6D染色体上分别检测到与籽粒硬度相关的QTL各1个，其中位于染色体5D上的Xgwn190对表型变异的贡献率最大，达62．5％，为主效基因；在1B和6A染色体上分别检测到与蛋白质含量相关的QTL各1个，它们对表型变异的贡献率分别为13．2％和15．6％；在染色体1B和3B上分别检测到与SDS沉降值相关的QTL各1个，贡献率最大（10．2％）的一个QTL位于3B染色体上靠近E37M61—286的区域；在1A、3B、5D染色体上分别检测到与拉伸面积相关的QTL各1个，其中5D染色体上的Xgwn190对表型的贡献率最大，为11．5％．     

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.     

玉米产量相关性状的QTL定位与剖析（英文）

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F_(2∶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.     

猪2号染色体MYOD1区域的RH定位和连锁定位

在已经定位的QTL区域中开展基因连锁定位是寻找候选基因的重要途径．运用比较基因组方法筛选出猪2号染色体上生长、胴体和肉质性状QTL区域中与肌肉发育相关的5个基因（MYOD1、LDHA、CSRP3、TEF-1和COPB1）,通过RH和连锁定位方法研究这5个基因的排列顺序和距离,并与人和小鼠基因的顺序进行了比较．结果表明这5个基因在猪2号染色体上的排列顺序和距离是：MYOD1（75．2cM）-LDHA（79cM）-CSRP3（83．8cM）-TEF-1（86．5cM）-COPB1（90cM）,猪与小鼠基因的顺序相同,而与人（TEF-1—COPB1-MYOD1-LDHA—CSRP3）的顺序不一致．本研究结果对于进一步开展这5个基因的功能研究奠定了基础．     

林木多元性状数据QTL区间作图统计分析及其在杨树上的应用

【目的】传统的数量性状基因座(QTL)定位统计分析方法是针对自交系产生实验群体而建立的,不能直接应用到林木这种杂合度较高生长周期较长的异交物种中。针对林木多元性状数据,将传统的QTL区间作图方法应用到林木杂交F₁代作图群体中。【方法】考虑分子标记各种可能的分离比以及连锁相信息,建立林木多元性状数据QTL定位统计分析模型,并用R语言编写了相应的计算软件包mvqtlmap。在美洲黑杨和小叶杨杂交F₁代群体中,对2014年5月29日至9月24日期间调查的6个时间点树高数据进行了QTL定位分析。【结果】有4个QTL定位在母本美洲黑杨的遗传连锁图谱上,有6个QTL分布在父本小叶杨的遗传连锁图谱上,这些QTL分别位于第1、5、7、9、11和19号染色体上,平均解释0.8%～6.7%的表型方差。【结论】研究结果可为在林木上利用多个性状或多个时间点性状数据进行QTL定位提供统计分析方法及计算工具。所建立的程序包可在网站http://www.bioseqdata.com/mvqtlmap/mvqtlmap.htm上自由下载。     

高粱F6代群体分蘖数的QTL定位

分蘖数是高粱重要的农艺性状之一。笔者通过微卫星重复序列(simple sequence repeat,SSR)分子标记,以T70×P607杂交得到的F6代重组自交系(recombinant inbred lines,RIL)群体构建遗传连锁图,运用复合区间作图法(composite interval mapping,CIM),对分蘖数进行数量性状基因座(quantitative trait locus,QTL)分析,在第1、2、4、5和6号染色体上检测到7个与分蘖数相关的QTL,解释性状表型变异在1%～13%之间,所得到的QTL全为超显性。     

玉米营养品质性状的QTL定位

以玉米自交系201×698-3的233个F2:3家系为作图群体,利用SSR分子标记构建遗传图谱.采用随机区组设计,分别在四川雅安和德阳进行田间试验,人工套袋自交种子供性状考查,利用区间作图法进行QTL定位分析.构建了具有134对SSR标记的玉米遗传图谱,覆盖整个基因组1831.4cM,平均图距13.67cM.从16个营养品质性状中共检侧到35个QTL,其中影响蛋白质、淀粉和油份含量的有6个QTL,分别位于第1、2、4和8染色体上,单个性状的QTL为1～3个,每个QTL的作用可解释表型变异的8.1%～21.0%;控制赖氨酸等13种氨基酸含量的有29个QTL,分别位于第1、2、4、8、9和10染色体上,单个性状的QTL为1～5个,每个QTL的作用可解释表型变异的3.5%～30.1%.在本群体的营养品质性状QTL中,超显性效应起主导作用,其次为完全显性效应.     

玉米种皮和穗轴中总酚含量的QTL分析

利用黑玉米自交系SDM作为父本,与黄玉米自交系MO17杂交,构建F2∶3群体,对玉米种皮中总酚含量(PCP)和穗轴中的总酚含量(PCC)进行了QTL分析.结果表明:SDM种皮和穗轴中总酚含量均极显著高于MO17,种皮和穗轴中的总酚含量呈极显著正相关.与玉米种皮和穗轴中总酚含量相关的QTL各检测到4个,分布在第4,6,7,9,10共5条染色体上,增效基因均来自父本SDM.其中位于第6和第10染色体上的4个QTL对表型的贡献率最大.控制种皮中总酚含量的2个QTL PCP-6a和PCP-10b分别解释表型变异的13.00%和17.05%,所在的标记区间分别为mmc0523-umc2006和umc1506-bnlg1028,基因作用方式分别为部分显性和加性.控制穗轴中总酚含量的2个QTL PCC-6a和PCC-10a分别解释表型变异的12.20%和21.10%,所在的标记区间分别为umc1014-mmc0523和umc1506-bnlg1028,基因作用方式均为部分显性.位于第6和第10染色体上控制2个性状的QTL可能是一因多效的同一QTL,也可能是紧密连锁的不同QTL.     

水稻耐淹性的QTL定位与候选基因分析

为研究水稻苗期对淹水胁迫的耐受性,以籼稻品种台中本地1号(TN1)和粳稻品种春江06(CJ06)为亲本构建的DH群体为实验材料,将淹水条件下的成苗率作为考察指标,利用该群体前期构建的分子连锁图谱对淹水数据进行数量性状基因座(quantitative trait loci,QTL)检测分析.利用实时荧光定量PCR(quantitative real-time PCR,qRT-PCR)技术对淹水处理前后相关基因的表达量进行分析,并对表达量存在显著差异的基因进行测序分析.结果表明:挖掘到6个与淹水胁迫相关的QTL,分别位于水稻第1,2,6,8和9号染色体上;位于8号染色体QTL区间内的基因LOC_Os08g42750的表达在两亲本间存在显著差异,该基因在两亲本的编码区域存在4处差异.检测到的QTL位点对QTL精细定位和克隆耐淹相关基因具有重要参考价值,并为研究水稻耐淹分子机制及水稻直播育种提供了新的观点和见解.     

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.     

Resolution of quantitative traits into Mendelian factors by using a complete linkage map of restriction fragment length polymorphisms

The conflict between the Mendelian theory of particulate inheritance and the observation of continuous variation for most traits in nature was resolved in the early 1900s by the concept that quantitative traits can result from segregation of multiple genes, modified by environmental effects. Although pioneering experiments showed that linkage could occasionally be detected to such quantitative trait loci (QTLs), accurate and systematic mapping of QTLs has not been possible because the inheritance of an entire genome could not be studied with genetic markers. The use of restriction fragment length polymorphisms (RFLPs) has made such investigations possible, at least in principle. Here, we report the first use of a complete RFLP linkage map to resolve quantitative traits into discrete Mendelian factors, in an interspecific back-cross of tomato. Applying new analytical methods, we mapped at least six QTLs controlling fruit mass, four QTLs for the concentration of soluble solids and five QTLs for fruit pH. This approach is broadly applicable to the genetic dissection of quantitative inheritance of physiological, morphological and behavioural traits in any higher plant or animal.     

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.     

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。     

Molecular dissection of genetic basis of significant correlation among five morphological traits in rice (Oryza sativa L.)

To enhance understanding of the genetic basis of trait correlation in rice, a recombinant inbred line (RIL) population (F₆ and F₇) from a cross between Zhenshan97 and HR5 was employed to identify main quantitative trait loci (QTLs) and epistatic QTL (E-QTL). Highly significant positive correlations were detected among five traits of heading date (HD), plant height (PH), panicle length (PL), flag leaf length (FLL) and flag leaf width (FLW) in 2 environments. Four to 8 main QTLs were detected for an individual trait. No E-QTL was detected for PH. One, 4, 4 and 5 E-QTLs were detected for FLL, HD, FLW and PL, respectively. Each E-QTL individually explained less than 3% of trait variation except E-QFll1. Comparison of QTL results was made in order to dissect the genetic basis of trait correlation. We found that main QTLs with pleiotropic effects and QTL clusters were the main genetic basis of trait correlation. No E-QTL had pleiotropic effects. E-QTL played an important role in the genetic basis of individual trait, but it made a little contribution to trait correlation.     

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.     

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.     

A correlation method of detecting and estimating interactions of QTLs

More and more studies demonstrate that a great deal of interactions among the quantitative trait loci (QTLs) are far more than those detected by single markers. A correlation method was proposed for estimating the interactions of multiple QTLs detected by multi-markers in several mapping populations. Genetic implication of this method and usage were discussed.     

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.