利用水稻重组自交系群体定位谷粒外观性状的数量性状基因

用区间作图和混合线性模型的复合区间作图两种方法,对水稻（Oryza sativa L）珍汕97和明恢63组合的重组自交系群体的谷粒外观性状－粒长,粒宽和粒形进行了数量性状基因（QTL）定位,用区间作图法在LOD≥2．4水平上（近拟于a=0.005),1998年对粒长,粒宽和粒形分别检测到6,2放2个QTLs,1999年对以上3个性状分别检测到3,2和2个QTLs,其中7个QTLs在两年均检测到,位于第3染色体RG393－C1087区间的QTL效应大,同时影响粒长和粒形,两年贡献分别为57．5％,61．4％和26．7％,29．9％,位于第5染色体RG360－C734B区间的QTL效应大,同时影响粒宽和粒形,两年贡献率分别为44．2％,53．2％和32．1％和36．0％,用混合线性模型的复合区间作图法在P＝0．005水平上,对粒长,粒宽和粒形分别检测到8,5和5个QTLs,共解释各自性状变异的58．81％,44．75％和57．47％,只检测到1个QTL与环境之间存在的显互作。     

云南粳稻碾磨品质性状稳定性分析

利用AMMI模型对2年5点12个粳稻品种的糙米率、精米率和整精米率进行了稳定性分析,并以碾磨品质性状的表型值及其相应的稳定性参数(Di)为指标,对供试品种进行聚类分析和评价.结果表明,糙米率、精米率和整精米率在不同品种和环境间的差异以及品种×环境互作效应均达极显著水平;碾磨品质性状的稳定性随品种和环境不同而变化较大,其稳定性顺序为糙米率>精米率>整精米率.综合考虑糙米率、精米率和整精米率及其稳定性,云粳优14号、滇元1号、云粳18号和滇元2号的碾磨品质和稳定性好,可作育种亲本,以改良水稻品种的碾磨品质及其稳定性.     

稻米粒形的QTL定位及上位性和QE互作分析

利用'广陆矮4号'×'佳辐占'水稻重组自交系构建了SSR标记的遗传图谱.联合2007年和2008年获得的两组稻米粒长(GL)、粒宽(GW)、长宽比(L/W)数据应用混合线性模型方法进行QTL定位,并作加性效应、加性×加性上位互作效应以及加性QTL、上位性QTL与环境的互作效应分析.结果显示;(1)在加性效应分析中两个群体共检测到4个控制粒长的QTL,4个控制粒宽的QTL,5个控制长宽比的QTL,贡献率分别为13.81%、15.36%和 16.29%.(2)在上位互作效应分析中两个群体共检测到2对控制粒长的互作QTL,1对控制粒宽的互作QTL,3对控制长宽比的互作QTL,贡献率分别为5.77%、2.59%和7.42%.(3)环境互作检测中,发现共有13个加性QTL和4对QTL的加性×加性上位性与环境产生了互作效应.结果表明,上位性效应和加性效应都影响稻米粒形遗传,QE互作效应也对粒形有着显著的影响.     

水稻叶片性状和根系活力的QTL定位

应用由247个株系组成的珍汕97B/密阳46重组自交系(RIL)群体及其分子标记连锁图谱,检测控制剑叶、倒二叶、倒三叶的5个形态性状和控制根系伤流量性状的数量性状座位(QTL)。在9个标记区间检测到控制叶片形态性状的24个QTL,LOD值为2．9～11．8,单个QTL的表型变异贡献率为4．0％～32．5％;分别检测到56对和4对控制叶片形态和根系活力的上位性互作,绝大多数互作发生在2个不表现加性效应的座位之间。与该群体产量性状QTL的研究结果相比较,发现控制叶片性状和根系活力的QTL与产量性状QTL往往处于相似的染色体区间。     

亚麻主要农艺与品质相关性状的QTL定位

为了全面了解亚麻产量和品质相关性状的遗传基础,为亚麻基因克隆和分子标记辅助育种提供理论依据,在已构建SNP连锁遗传图谱的基础上,以LH-89为父本,R43为母本构建F2:3家系QTL定位群体,用R/QTL软件采用复合区间作图法对13个农艺和品质性状进行QTL定位。结果表明:(1)该研究共检测出35个QTL位点,与粗脂肪及其组成成分相关的QTL有20个,与农艺性状相关的QTL有15个;其中:亚油酸和粗脂肪各5个,亚麻酸、千粒重各4个,棕榈酸、株高、工艺长度各3个,硬脂酸、分枝数各2个,单株果数、果粒数、单株粒重、油酸各1个。(2)共有18个QTL的表型贡献率超10%(主效基因),其中农艺性状定位8个主效基因,品质性状定位10个主效基因。     

稻米外观品质性状遗传与分子定位研究进展

稻米外观品质主要是指稻米的粒形、垩白、透明度和籽粒色泽等,它不仅直接影响到人们的喜好,还与其他品质性状诸如蒸煮食用、加工等密切相关。因此,外观品质对稻米的商品价值有着十分重要的影响。本文从经典遗传与现代分子生物学两个方面对稻米主要外观品质的遗传研究进展进行了较全面的综述,包括粒长、粒宽、长宽比、粒厚、垩白、透明度和籽粒色泽等。综合近年来的遗传研究结果发现,大多数稻米外观品质性状都是由数量基因控制的。利用分子标记技术已将控制外观品质的QTL（qualitative trait locus）定位在不同的染色体上,为下一步的稻米外观品质改良提供了有利条件。     

水稻外观品质的数量性状基因位点分析

利用由98个家系组成的Nipponbare(粳)／Kasalath(秒)∥Nipponbare回交重组自交系(backcross inbred lines,BILs)群体(BC1F9)及其分子连锁图谱,采用复合区间作图的方法,在2个不同年份对粒长、粒宽、粒形、垩白率、垩白大小、垩白度和透明度等7个稻米外观品质性状的数量性状基因位点(Quantiative trait loci,QTL)进行了定位分析。共定位到33个四QTLs,单个性状QTL数目在4-7个之间,以垩白率最多,为7个;粒长和垩白大小次之,为5个;其他性状均为4个,表明该组合外观品质是由多基因控制的数量性状。单个QTL对性状变异解释率粒长为6．2％-15．2％,粒宽为8．3％-32．5％,长宽比为6．8％-19．8％,垩白率为6．4％-28．5％,垩白大小为6．1％-16．9％,垩白度为9．3％-17．2％,透明度为5．6％-25．2％．QTL在染色体上成集中分布的特点,第3染色体C1488-C563、第5染色体R830-R3166和R1436-R2289、第6染色体R2147-R2171均有3个以上的QTLs分布。比较2年的检测结果表明,外观品质性状的QTL定位都受环境影响,但不同性状受影响的程度差异很大。粒长和粒形的QTL定位受环境影响很小,垩白率、垩白大小和垩白度的QTL定位受环境影响很大。     

稻米碾磨品质性状遗传主效应及其与环境互作的遗传分析

采用包括遗传主效应和基因型与环境互作效应的种子三倍体遗传模型,分析了不同环境条件下籼稻稻米碾磨品质的遗传特性。结果表明,各碾磨品质性状除了受制于种子基因效应、细胞质效应和母体植株基因效应等遗传主效应外,还会明显受到各遗传效应与环境互作效应的影响。其中精米重和精米率两个性状的表现主要是以遗传主效应为主,而糙米重和糙米率则以基因型ｘ环境互作效应为主。在各遗传体系中,除了精米率性状的种子直接遗传效应与环境的互作效应略大于母体植株遗传效应与环境的互作效应外,其他碾磨品质性状的母体植株基因的表达受环境条件的影响程度要大于种子基因。细胞质ｘ环境互作效应对精米重和糙米率的影响也较为重要。遗传效应预测值结果表明,Ｐ７和Ｐ８两个亲本的遗传主效应表现突出,可以明显改良杂交后代多数碾磨品质性状。Ｐ１和Ｐ２两个亲本的碾磨品质性状预测值在两年中的环境互作效应较为－致,不易受到外界条件的影响。上述亲本在水稻品质育种中可加以利用。     

籼稻稻米蛋白质含量与外观品质性状间不同遗传体系的条件遗传相关分析

选用稻米蛋白质含量等品质差异较大的7个籼型不育系(A)及相应的保持系(B)与5个籼型恢复系(R)杂交,组成7×5不完全双列杂交组合。应用包括胚乳、细胞质和母体植株基因的遗传主效应以及基因型×环境互作效应的数量性状遗传模型及非条件和条件分析方法,研究了籼稻稻米蛋白质含量与外观品质性状间的遗传相关性,进一步揭示了籼稻糙米重、稻米直链淀粉含量对稻米蛋白质含量与外观品质性状间遗传相关性的影响。非条件分析的结果表明,除了与糙米厚的相关性未达到显著水平以外,蛋白质含量与其它稻米外观品质性状间的遗传相关性均达极显著水平,其中与糙米宽间的相关性表现为正值,其余为负向相关。条件分析的结果显示,糙米重和直链淀粉含量对稻米蛋白质含量与外观品质性状间的遗传相关性均可产生较大的影响。糙米重主要通过基因型×环境互作效应影响蛋白质含量与外观品质性状间的遗传相关性,其中对蛋白质含量与糙米长、糙米宽、糙米厚间遗传相关性的影响主要表现为负向作用,而对蛋白质含量与糙米长宽比、糙米长厚比间遗传相关性的影响则表现为正向作用。稻米直链淀粉主要通过细胞质遗传主效应和母体加性效应影响蛋白质含量与糙米长、糙米长宽比、糙米长厚比间的遗传相关性,而对蛋白质含量与糙米宽间的相关性影响主要表现为负向作用。     

籼型杂种稻米品质性状的数量遗传分析

应用新近提出的ｐ＾＋ｑ＾＋ｐｑ交配设计的种子性状遗传表达鉴别方法,分析了籼型水稻３个不育系和１０个恢复系配组的３０个杂种Ｆ１植株上的Ｆ２种子及其亲本的９个稻米品质性状。结果表明：（１）粒长、粒宽、粒重、糙米率和完整精米率５个性状在Ｆ２米粒间没有发生遗传分离,它们的遗传受二倍体母体基因型（Ｆ１植株）控制。（２）垩白率、直链淀粉含量、糊化温度和胶稠度４个性状则在Ｆ２米粒间有极显著的遗传分离,帮主要受三     

Mapping QTL main and interaction influences on milling quality in elite US rice germplasm

Rice (Oryza sativa L.) head-rice yield (HR) is a key export and domestic quality trait whose genetic control is poorly understood. With the goal of identifying genomic regions influencing HR, quantitative-trait-locus (QTL) mapping was carried out for quality-related traits in recombinant inbred lines (RILs) derived from crosses of common parent Cypress, a high-HR US japonica cultivar, with RT0034, a low-HR indica line (129 RILs) and LaGrue, a low-HR japonica cultivar (298 RILs), grown in two US locations in 2005–2007. Early heading increased HR in the Louisiana (LA) but not the Arkansas (AR) location. Fitting QTL-mapping models to separate QTL main and QTL × environment interaction (QEI) effects and identify epistatic interactions revealed six main-effect HR QTLs in the two crosses, at four of which Cypress contributed the increasing allele. Multi-QTL models accounted for 0.36 of genetic and 0.21 of genetic × environment interaction of HR in MY1, and corresponding proportions of 0.25 and 0.37 in MY2. The greater HR advantage of Cypress in LA than in AR corresponded to a genomewide pattern of opposition of HR-increasing QTL effects by AR-specific effects, suggesting a selection strategy for improving this cultivar for AR. Treating year–location combinations as independent environments resulted in underestimation of QEI effects, evidently owing to lower variation among years within location than between location. Identification of robust HR QTLs in elite long-grain germplasm is suggested to require more detailed attention to the interaction of plant and grain development parameters with environmental conditions than has been given to date.     

Mapping QTL for agronomic traits in breeding populations

Detection of quantitative trait loci (QTL) in breeding populations offers the advantage that these QTL are of direct relevance for the improvement of crops via knowledge-based breeding. As phenotypic data are routinely generated in breeding programs and the costs for genotyping are constantly decreasing, it is tempting to exploit this information to unravel the genetic architecture underlying important agronomic traits in crops. This review characterizes the germplasm from breeding populations available for QTL detection, provides a classification of the different QTL mapping approaches that are available, and highlights important considerations concerning study design and biometrical models suitable for QTL analysis.     

Association studies of dormancy and cooking quality traits in direct-seeded indica rice

Association analysis was applied to a panel of accessions of Assam rice (indica) using 98 SSR markers for dormancy-related traits and cooking quality. Analysis of population structure revealed 10 subgroups in the population. The mean r ² and D ^′ value for all intrachromosomal loci pairs was 0.24 and 0.51, respectively. Linkage disequilibrium between linked markers decreased with distance. Marker-trait associations were investigated using the unified mixed-model approach, considering both population structure (Q) and kinship (K). Genome-wide scanning, detected a total of seven significant marker-trait associations (P < 0.01), with the R ² values ranging from 12.0 to 18.0%. The significant marker associations were for grain dormancy (RM27 on chromosome 2), α-amylase activity (RM27 and RM234 on chromosomes 2 and 7, respectively), germination (RM27 and RM106 on chromosome 2), amylose (RM282 on chromosome 3) and grain length elongation ratio (RM142 on chromosome 4). The present study revealed the association of marker RM27 with traits like dormancy, α-amylase activity and germination. Simple correlation analysis of these traits revealed that these traits were positively correlated with each other and this marker may be useful for simultaneous improvement of these traits. The study indicates the presence of novel QTLs for a few traits under consideration. The study reveals association of traits like dormancy, α-amylase activity, germination, amylose content, grain length elongation ratio with SSR markers indicating the feasibility of undertaking association analysis in conjunction with germplasm characterization.     

Genetic and heterosis analysis for cooking quality traits of indica rice in different environments

Genetic effects and genotype×environment (GE) interaction effects on the cooking quality traits of indica rice (Oryza sativa L.) were analyzed based on a genetic model for quantitative traits of triploid endosperm in cereal crops. Nine cytoplasmic male-sterile lines as females and 5 restoring lines as males were used in an incomplete diallel cross over 2 years. The cooking quality traits studied were observed to be mainly controlled by genetic effects, but GE interaction effects, especially for amylose content (AC) and alkali spreading score (ASS), were also indicated. Among the genetic effects, seed direct effects and maternal effects were the main components of AC and ASS, respectively; cytoplasmic effects were the main components of gel consistency (GC). Among the GE interaction effects, AC and ASS were mainly affected by maternal interaction effects and GC by direct interaction effects. Additive effects and/or additive interaction effects were the main factors controlling the performance of rice cooking quality traits except for GC which was affected by dominant interaction effects. For AC and GC, there were seed heterosis and/or maternal heterosis. The predicated genetic effects indicated that four parents were better than the others in improving the rice cooking quality traits of the progenies. It was shown that genetic heterosis and GE interaction heterosis were important, especially for amylose content trait in early season indica rice.     

Analysis of genetic effects on nutrient quality traits in indica rice

Nine cytoplasmic male-sterile lines and five restorer lines were used in an incomplete diallel cross to analyze seed effects, cytoplasmic effects, and maternal gene effects on nutrient quality traits of indica rice (Oryza sauva L.). The results indicated that nutrient quality traits were controlled by cytoplasmic and maternal effects as well as by seed direct effects. Maternal effects for lysine content (LC), lysine index (LI), and the ratio of lysine content to protein content (RLP) were more important than seed direct effects, while protein content (PC) and protein index (PI) were mainly affected by seed direct effects. Cytoplasmic effects accounted for 2.41–20.80% of the total genetic variation and were significant for all nutrient quality traits. Additive genetic effects were much more important than dominance effects for all of the traits studied, so that selection could be applied for these traits in early generations.     

Mapping QTLs for root traits in a recombinant inbred population from two indica ecotypes in rice

Evaluation of root traits in rainfed lowland rice is very difficult. Molecular genetic markers could be used as an alternative strategy to phenotypic selection for the improvement of rice root traits. This research was undertaken to map QTLs associated with five root traits using RFLP and AFLP markers. Recombinant inbred lines (RILs) were developed from two indica parents, IR58821–23-B-1–2-1 and IR52561-UBN-1–1-2, that were adapted to rainfed lowland production systems. Using wax-petrolatum layers to simulate a hardpan in the soil, 166 RILs were evaluated for total root number (TRN), penetrated root number (PRN), root penetration index (RPI, the ratio of PRN to TRN), penetrated root thickness (PRT) and penetrated root length (PRL) under greenhouse conditions during the summer and the fall of 1997. A genetic linkage map of 2022 cM length was constructed comprising 303 AFLP and 96 RFLP markers with an average marker space of 5.0 cM. QTL analysis via interval mapping detected 28 QTLs for these five root traits, which were located on chromosomes 1, 2, 3, 4, 6, 7, 10 and 11. Individual QTLs accounted for between 6 and 27% of the phenotypic variation. Most of the favorable alleles were derived from the parent IR58821–23-B-1–2-1, which was phenotypically superior in root traits related to drought resistance. Three out of six QTLs for RPI were detected in both summer and fall experiments and they also were associated with PRN in both experiments. Out of eight QTLs for RPT, five were common in both seasons. Two genomic regions on chromosome 2 were associated with three root traits (PRN, PRT and RPI), whereas three genomic regions on chromosomes 2 and 3 were associated with two root traits (PRT and RPI). Two QTLs affecting RPI and two QTLs affecting PRT were also found in similar genomic regions in other rice populations. The consistent QTLs across genetic backgrounds and the common QTLs detected in both experiments should be good candidates for marker-assisted selection toward the incorporation of root traits in a drought resistance breeding program, especially for rainfed lowland rice. Received: 17 November 1999 / Accepted: 19 March 2000     

水稻蒸煮品质相关QTL定位及候选基因分析

挖掘与稻米蒸煮品质相关的数量性状基因座(quantitative trait locus, QTL)，分析候选基因，并通过遗传育种手段改良稻米蒸煮品质相关性状，可有效提升稻米的口感。以籼稻华占(Huazhan, HZ)、粳稻热研2号(Nekken2)及由其构建的120个重组自交系(recombinant inbred lines, RILs)群体为实验材料，测定成熟期稻米的糊化温度(gelatinization temperature, GT)、胶稠度(gel consistency, GC)和直链淀粉含量(amylose content, AC)。结合高密度分子遗传图谱进行QTL定位，共检测到26个与稻米蒸煮品质相关的QTLs (糊化温度相关位点1个、胶稠度相关位点13个、直链淀粉含量相关位点12个)，其中最高奇数的可能性(likelihood of odd, LOD)值达30.24。通过实时荧光定量PCR (quantitative real-time polymerase chain reaction, qRT-PCR)分析定位区间内候选基因的表达量，发现6个基因在双亲间的表达量差异显著，推测LOC_Os04g20270和LOC_Os11g40100的高表达可能会极大地提高稻米的胶稠度，而LOC_Os01g04920和LOC_Os02g17500的高表达以及LOC_Os03g02650和LOC_Os05g25840的低表达有助于降低直链淀粉含量。这些结果为培育优质水稻新品种奠定了分子基础，并为揭示稻米蒸煮品质的分子调控机制提供了重要的遗传资源。     

QTL mapping for nitrogen-use efficiency and nitrogen-deficiency tolerance traits in rice

Plant and Soil - The improvement of nitrogen-deficiency tolerance (NDT) and nitrogen-use efficiency (NUE) traits is an important objective of many rice breeding programs. A better understanding of...     

Mapping and characterization of major QTL for spike traits in common wheat

Physiology and Molecular Biology of Plants - The spike traits of wheat can directly affect yield. F2 and F2:3 lines derived from the cross of the multi-spikelet female 10-A and the uni-spikelet...     

QTL and QTL x environment effects on agronomic and nitrogen acquisition traits in rice

Agricultural environments deteriorate due to excess nitrogen application.Breeding for low nitrogen responsive genotypes can reduce soil nitrogen input.Rice genotypes respond variably to soil available nitrogen.The present study attempted quantification of genotype x nitrogen level interaction and mapping of quantitative trait loci (QTLs) associated with nitrogen use efficiency (NUE) and other associated agronomic traits.Twelve parameters were observed across a set of 82 double haploid (DH) lines derived from IR64/Azucena.Three nitrogen regimes namely,native (0 kg/ha; no nitrogen applied),optimum (100 kg/ha) and high (200 kg/ha) replicated thrice were the environments.The parents and DH lines were significantly varying for all traits under different nitrogen regimes.All traits except plant height recorded significant genotype x environment interaction.Individual plant yield was positively correlated with nitrogen use efficiency and nitrogen uptake.Sixteen QTLs were detected by composite interval mapping.Eleven QTLs showed significant QTL x environment interactions.On chromosome 3,seven QTLs were detected associated with nitrogen use,plant yield and associated traits.A QTL region between markers RZ678,RZ574 and RZ284 was associated with nitrogen use and yield.This chromosomal region was enriched with expressed gene sequences of known key nitrogen assimilation genes.