西藏半野生小麦粒型性状的QTL定位

为了解西藏半野生小麦粒型性状的QTL差异,以西藏半野生小麦Q1028和郑麦9023(ZM9023)杂交后获得的重组自交系群体为试验材料,于2012、2013和2015年分别在四川农业大学温江试验田种植,对其粒型性状(粒长、粒宽、粒厚、长宽比、籽粒大小)进行遗传分析。结果表明,重组自交系群体粒型性状均呈正态分布,对籽粒大小的影响依次为粒宽、粒厚、粒长。在三个年度环境中,总共检测到33个控制小麦粒长、粒宽、粒厚、籽粒大小和长宽比的QTL位点。其中,13个控制粒长的QTL分布在1B、2B、2D(3个)、3A、4A、5B、6A、6B、7A(3个)染色体上,每个位点对表型变异的贡献率为5.37%~11.57%。6个控制粒宽的QTL分布在2B、2D、4A、5B、6A、7A染色体上,可以解释表型变异的6.43%~12.69%。3个控制粒厚的QTL位于2B和2D(2个)上,表型贡献率分别为12.75%、10.00%和8.49%。9个控制籽粒大小的QTL分别位于2B、2D(2个)、4A、5B、6A、7A(3个)染色体上,单个QTL可解释6.26%~14.69%的表型变异。另外,本研究还在2B、2D、4A、5B、6A、7A染色体上共发现7个QTL富集区,这些染色体上的QTL和富集区与籽粒性状密切相关,在育种中值得关注。其中,2B染色体上XwPt-3561~XwPt-6932分子标记区间内有控制粒长、粒宽、粒厚、籽粒大小的遗传位点,6A染色体上标记wpt-730109与wpt-7063之间有控制增加籽粒宽度和籽粒大小的位点。     

小麦粒形QTL元分析及候选基因预测

粒形是影响小麦籽粒产量和品质的重要参数,是由多基因控制的复杂数量性状。为发掘控制小麦粒形相关的真实主效数量性状位点(quantitative trait loci, QTL),本研究利用BioMercator 4.2软件,以小麦高密度分子标记遗传图谱为参考图谱,对来自不同遗传作图群体的113个控制小麦粒长的QTL和86个控制粒宽的QTL进行图谱整合、映射以及QTL元分析。通过建立QTL一致性图谱,获得18个控制小麦粒长和8个控制粒宽的一致性QTL(meta quantitative trait loci, MQTL)位点,置信区间最小可达到0.57 cM,主要分布在2B、2D、3A、3B、4B、5A、5B和7D染色体上。在5A染色体Xgwm293～Xgwm304和Xgpw2120～Xgpw2273a标记区间内,预测到7个与小麦粒长和粒宽相关的候选基因。本研究为小麦粒形QTL精细定位以及分子标记辅助选择育种提供理论依据。     

小麦籽粒形态及千粒重性状的QTL初步定位

为研究小麦籽粒形态及千粒重性状的QTL,以普通小麦6044和01-35为杂交组合构建的F8重组自交系（RIL）群体作为试验材料,在山东泰安（山东农业大学试验站）和莱阳（青岛农业大学试验站）两个环境下进行两年田间试验,利用Mapmaker/version 3.0和WinQTLCart软件通过复合区间作图法进行QTL初步定位,在两年两个环境下共检测到12个相关QTL位点,其中关于粒长的2个QTL分别位于2A和2B染色体上,可解释表型变异的25%和12%;4个粒厚QTL位于2A和6A染色体上,可解释表型变异的7%～10%;6个千粒重相关QTL位于染色体2A、4A和6A连锁群上,可解释表型变异的6%～25%;而粒宽QTL在两个地点上都没有检测到。其中相关性高的性状间有一些共同的QTL,表现出一因多效或紧密连锁效应。     

Kernel morphometric traits in hexaploid wheat (Triticum aestivum L.) are modulated by intricate QTL × QTL and genotype × environment interactions

Wheat kernel size and shape influence its flour yield and market price. A hexaploid wheat population of 185 recombinant inbred lines was evaluated for five kernel morphometric traits namely, 1000-kernel weight, kernel length, width, length–width ratio and factor form density in two diverse agro-climatic regions in India in five to eight year–location combinations. Additive main effects and multiplicative interaction analysis revealed significant contributions from genotype (G) and genotype × environment (G × E) effects for these traits. Quantitative trait locus (QTL) analysis by composite interval mapping (CIM) was performed using a linkage map of 251 SSR markers and 59 QTLs distributed on 16 chromosomes were identified. The majority of the QTLs were located on the D genome (44.07%) and the homeologous chromosomes of Group 2 (38.98%). Stable QTLs detected in three or more year–location combinations were identified for four traits. Multi-trait CIM showed 10 chromosomal regions harboring putative pleiotropic loci. Complexity in the genetic effects was further revealed by QTL analysis based on mixed-linear model that indicated 19 QTLs with significant individual effects (main-effect QTLs) and 14 QTL × QTL interactions. Five of these nineteen main-effect QTLs and one of the fourteen QTL × QTL interactions showed environmental influence.     

波兰小麦×普通小麦品系“中13”RIL群体籽粒特性的QTL定位

小麦籽粒特性与籽粒产量和品质密切相关。本研究以波兰小麦(Tiriticum polonicum L.)×普通小麦(Triticum aestivum L.)品系"中13"杂交组合衍生的99个F8重组自交系(Recombinant inbred lines,RIL)群体为材料,利用SSR分子标记构建连锁遗传图谱。根据两年实验数据,利用复合区间作图法对粒重、粒长和粒宽3个籽粒特性相关性状进行了QTL定位分析,共检测到12个与籽粒特性相关的加性QTL位点。其中,3个粒重QTL,1个位于1A染色体上,另外2个都在2A染色体上,单个QTL可解释表型变异的13.35%～20.04%;5个粒长QTL,其中2个位于2A染色体上,其余3个分别位于3A、5A和2B染色体上,单个QTL可解释表型变异的8.53%～21.03%;4个粒宽QTL,分别位于1A、2A、3B和5B染色体上,单个QTL可解释表型变异的9.76%～40.79%。在2A染色体上共检测到5个籽粒特性相关性状的QTL,表明2A染色体与籽粒特性关系密切。     

野生二粒小麦粒重QTLs位点分析

为了挖掘野生二粒小麦的优异基因资源,对从以色列魏茨曼科学院引进的一套以普通小麦品种中国春为遗传背景的野生二粒小麦染色体臂渐渗系(Introgression lines,渐渗系)进行了一年两点的田间试验,考查了构成粒重的三个重要因子即粒长、粒宽和千粒重。结果表明,8个渐渗系(3AS、7AL、5AS、1BS、7AS、3BL、2AL、1BL)的籽粒显著宽于亲本,推断在这些染色体臂上至少有一个正效QTL控制野生二粒小麦的粒宽;同样可以推断,12个控制野生二粒小麦粒长的正效QTLs分别定位在2AS、7AL、1BL、4BS、3AS、7BS、4BL、7AS、5BS、2BS、3AL、6AS上;5个控制野生二粒小麦千粒重的正效QTLs分别定位在7AS、4BS、7AL、1BS、6AS上。各粒重构成因子关联性分析表明,粒长、粒宽和千粒重主要受遗传因素调控,粒长和粒宽都与千粒重显示出较高的遗传相关性。     

Reconciliation of D-genome puroindoline allele designations with current DNA sequence data

Kernel texture is an important trait in cereals, especially wheat (Triticum spp.). Throughout the Triticeae, the puroindoline genes act to soften kernel endosperm. Absence or mutation of either or both of the two puroindolines, ‘a’ and ‘b’, in Triticum aestivum results in harder grain texture. Apparently only one puroindoline haplotype was contributed by the Aegilops tauschii variety that contributed the D-genome during allopolyploidization. Yet, world collections of Ae. tauschii exhibit a range of puroindoline sequence polymorphisms. Consequently, these genes, through synthetic hexaploids (× Aegilotriticum) can enrich the wheat gene pool. Lastly, the puroindolines represent a useful tool for phylogenetic analyses. Here we review original sequence data published and/or available in public databases to reconcile the known gene sequence polymorphisms with a systematic approach to the designating of puroindoline gene and allele symbols in T. aestivum, Ae. tauschii, and × Aegilotriticum. This system follows the recommendations adopted by the International Wheat Genetics Symposium and described in the Catalogue of Gene Symbols for Wheat. Errors, discrepancies and ambiguities in the puroindolines are reviewed; a reconciliation of all existing data is outlined.     

Mapping quantitative trait loci associated with root growth in upland rice (Oryza sativa L.) exposed to soil water-deficit in fields with contrasting soil properties

A mapping population of 114 lines from Bala × Azucena was grown under drought stress at two field sites with contrasting soil physical properties. Drought was imposed between 35 and 65 days after sowing (DAS) and root density at 35 cm depth was measured 70 DAS. Leaf rolling, leaf drying and relative water content were recorded as indicators of drought avoidance. Root density correlated with indicators of drought avoidance. Two significant and two putative quantitative trait loci (QTLs) for root density and 28 QTLs for drought avoidance were identified. Most QTLs did not agree between sites. There was also reasonable agreement between leaf-drying QTLs and previously reported root-growth QTLs detected under controlled conditions (in contrast to a previous screen on soil with a higher penetration resistance). These data also reveal QTL × environment interaction, which will need to be understood more clearly if progress towards breeding for drought resistance via alterations of root morphology is to be achieved.     

小麦产量性状的QTL分析

为寻找更多与小麦产量性状相关的数量性状位点（QTL）,利用江苏地方品种望水白与墨西哥小麦品种Alondra杂交构建的重组自交系群体（104个家系）,在3个试验环境下进行了单株有效穗数、主穗粒数、单穗粒数和千粒重4个性状的QTL分析,结果在5A染色体上检测到与单株有效穗数相关、可以解释10．3％～18．8％表型变异的QTL1个;检测到与主穗粒数相关的QTL8个,分别位于染色体1B、1D、3B、4A、5D、6B上和连锁群4上（未知具体染色体归属）,单个QTL可以解释9．9％～19．9％的表型变异;检测到与单穗粒数相关的QTL11个,分别位于染色体1B、1D、2A、2B、3B、4A、5D、6B和7A上,单个QTL可解释7．5％～43．4％的表型变异;检测到与千粒重相关的QTL5个,分别位于2A、2B、3B、4D和7A染色体上,单个QTL可解释9．6％～25．7％的表型变异。获得的QTL可以用于分子标记辅助育种。     

The influence of temperature extremes on some quality and starch characteristics in bread,biscuit and durum wheat

Environmental conditions during grain-fill can affect the duration of protein accumulation and starch deposition, and thus play an important role in grain yield and flour quality of wheat. Two bread-, one durum- and one biscuit wheat were exposed to extreme low (−5.5 °C for 3 h) and high (32 °C/15 °C day/night for three days) temperatures during grain filling under controlled conditions for two consecutive seasons. Flour protein content was increased significantly in one bread wheat, Kariega, under heat stress. Cold stress significantly reduced SDS sedimentation in both bread wheats. Kernel weight and diameter were significantly decreased at both stress treatments for the two bread wheats. Kernel characteristics of the biscuit wheat were thermo stable. Kernel hardness was reduced in the durum wheat for the heat treatment. Durum wheat had consistently low SDS sedimentation values and the bread wheat high values. Across the two seasons, the starch content in one bread wheat was significantly reduced by both high and low temperatures, as is reflected in the reduction of weight and diameter of these kernels. In the durum wheat, only heat caused a significant reduction in starch content, which is again reflected in the reduction of kernel weight and diameter.     

Genetic mapping and quantitative trait locus analysis of resistance to sterility mosaic disease in pigeonpea [Cajanus cajan (L.) Millsp.]

Sterility mosaic disease (SMD), considered as the “green plague of pigeonpea” and caused by pigeonpea sterility mosaic virus (PPSMV) is one of the major biotic factors, which leads to heavy yield losses and hence poses a big challenge for pigeonpea production in the Indian subcontinent. Variability in the sterility mosaic pathogen revealed the occurrence of five different isolates in India. Among them, three distinct SMD isolates have been characterized, viz., Patancheru, Bangalore and Coimbatore. Molecular tools offer a viable option to tackle these biotic stresses via identification of the genomic regions associated with the trait such as SMD resistance. With an aim of identifying the gene(s)/QTLs linked with SMD resistance, two F₂ populations, i.e. ICP 8863 × ICPL 20097 (segregating for Patancheru SMD isolate) and TTB 7 × ICP 7035 (segregating for both Patancheru and Bangalore SMD isolates) were developed and F_2:3 families were phenotyped for resistance to respective isolate(s) of SMD. After screening over 3000 SSR markers on parental genotypes of each mapping population, intra-specific genetic maps comprising of 11 linkage groups and 120 and 78 SSR loci were developed for ICP 8863 × ICPL 20097 and TTB 7 × ICP 7035 populations, respectively. Composite interval mapping (CIM) based QTL analysis by using genetic mapping and phenotyping data provided four QTLs for Patancheru SMD isolate and two QTLs for Bangalore SMD isolate. Identification of different QTLs for resistance to Patancheru and Bangalore SMD isolates is an indication of involvement of different genes conferring the resistance to these two SMD isolates. One QTL namely qSMD4 identified within an interval of 2.8 cM on LG 7 explaining 24.72% of phenotypic variance, once it is validated in other genetic background, seems to be a promising QTL for use in marker assisted selection. In summary, this is the first study on development of intra-specific genetic maps and identification of QTLs for SMD resistance in pigeonpea.     

小麦籽粒清蛋白和球蛋白条件和非条件QTL分析

小麦蛋白含量的提高对营养和加工品质具有重要的意义。本研究在2年3点6个环境下,以小麦品种“花培3号×豫麦57”构建的双单倍体（doubled haploid,DH）群体为材料,通过条件和非条件QTL鉴定与小麦开花后5个时期籽粒清蛋白和球蛋白含量积累有关的基因或数量性状基因座。结果表明,基于完备区间作图法,共检测到40个非条件QTLs和34个条件QTLs,单个位点的贡献率范围为6.44%~25.13%,其中QAlu1B-3在6个环境下的第4和第5时期均被检测出。本研究结果为了解不同灌浆期QTL选择性表达奠定了理论基础,检测到的QTL可能对小麦籽粒品质的提高有重要贡献。     

水稻粒重粒形QTL的定位及qTGW1.2/qGL1.2的验证

[目的]粒重粒形对水稻的产量和品质均有重要的影响.本研究通过开展水稻粒重粒形QTL的初步定位,并对新鉴定的第1染色体长臂qTGW1.2/qGL1.2区间进行验证,旨在进一步揭示水稻粒重粒形的遗传调控机制.[方法]以大粒的FM9为父本,小粒的EFT为母本,配组衍生遗传群体,先后获得包含277个株系的F2:3群体和211个...     

小麦粒形QTL定位及其与水分环境互作遗传分析

为了解析小麦粒形性状的分子数量遗传特征及其与水分环境的互作关系,以两个冬小麦品种（陇鉴19和Q9086）为亲本创建的重组近交系（recombinant inbred lines,RIL）群体120个株系为供试材料,利用复合区间作图法对两种环境条件下该群体的粒形进行QTL定位和遗传解析。结果表明,小麦RIL群体中各株系呈现广泛的表型变异和超亲分离,对水分环境反应敏感,属于多基因控制的数量性状,遗传模式复杂。在两种环境条件下共检测到控制粒形的26个加性QTL(A-QTL)和22对上位性QTL(AA-QTL),分布在除4D、6D、7A和7D以外的其他17条染色体上,对表型变异的贡献率分别为3.60%～13.90%和0.52%～2.76%,对粒形的表型有正向或负向遗传效应。这些A-QTL和AA-QTL均与水分环境存在显著互作,但对表型变异的贡献率较低（＜3.05%）。在A-QTL中发现了3个对表型变异贡献率大于10%的主效位点( Qkl.acs-1B.1, Qkw.acs-6A.1和 Qkp.acs-1B.1),未检测到两种环境中稳定表达的A-QTL位点。在1B、3B、4B、5A、5B、5D和6A染色体上发现了7个A-QTL热点区域（Xgwm153~Xmag981、Xwmc231~Xbarc173、Xgwm149~Xgwm495、Xgwm186~Xcfa2185、Xbarc59~Xbarc232、Xgwm292~Xwmc161、Xksum255~Xbarc171）,这些标记区间可能是控制小麦粒形基因的重要区域。     

Genetic analysis of grain protein content,grain hardness and dough rheology in a hard×hard bread wheat progeny

Kernel texture (hard vs soft grain) and more subtle within-class variations are known to have a large influence on end-use properties, mostly through the proportion of damaged starch and subsequent water requirement. In this study, quantitative trait loci (QTL) affecting kernel texture and dough rheology in a progeny from a cross between two ‘medium-hard’ wheat cultivars were identified and compared to the QTL locations for both traits. One hundred and sixty-five F₇ recombinant inbred lines were studied in three environments in 1999. Kernel texture was estimated by both near infrared reflectance (NIR: Hard_NIR) and the single-kernel characterisation system (SKCS: Hard_SKCS). Dough rheology, taken as a predictor of end-use quality, was estimated by the empirical parameters measured by Chopin alveograph. The genetic map for this population consisted of 254 loci quite evenly distributed over the wheat genome. Considering only the QTL which were stable (detected in the three locations) and robust (through bootstrap resampling), five genomic regions were found to influence Hard_NIR, but only two of them are significant for Hard_SKCS, which was probably due to a less representative measure of the phenomenon. Eight QTLs were found for rheological traits. Some QTLs for dough rheology co-located with those for hardness or grain protein content, particularly on chromosomes 3A and 5B and close to the unlinked marker Xgwm130. According to trait, individual QTLs explained from 5.4 to 26.6% of the phenotypic variation and when taken together up to 46.0% of the variation.     

两种供氮水平下玉米穗部性状的QTL定位

以优良杂交种豫玉22两亲本Z3和87-1为基础构建一套F8家系的重组自交系群体为研究材料,在正常供氮和低氮两种氮水平下进行田间试验,利用复合区间作图法对玉米穗长、穗行数、行粒数、百粒重和单穗粒数进行QTL定位分析。两种氮水平下共定位到24个玉米穗部性状的QTL位点,其中正常供氮条件下定位到13个QTL,低氮水平下定位到11个QTL,集中分布在第1(8个QTL)、第5(6个QTL)和第8(5个QTL)染色体上。两种氮水平下共位或紧密连锁的QTL位点较少,表明玉米穗部性状在低氮水平下的遗传机制发生很大改变。研究发现,第1染色体umc1122/bnlg1556位点是一个控制低氮水平下玉米单穗粒数的主效QTL,单个QTL可解释19.7%的表型变异,该位点还同时影响低氮水平下玉米穗长、穗行数和百粒重的表型。与前人定位结果比较发现,该位点所在的染色体区域是一个产量及氮效率相关性状的QTL富集区,对此位点附近进行相关分子标记辅助选择,可能会在玉米氮高效分子育种上有所突破。     

不同环境条件下稻谷粒形数量性状的QTL分析

以窄叶青8号和京系17构建的加倍单倍体群体为材料,系统分析了稻谷粒长、粒宽及长宽比3个性状在北京、杭州、海南3个不同环境下的表现,并进行了数量性状基因位点的比较定位。检测结果表明,3个环境下共检测到18个QTLs,分布于水稻第1、2、3、4、6、8和12染色体上,其中与粒长性状相关QTL 3个,LOD值为2.69~4.75,贡献率为9.9%~18.4%;与粒宽性状相关QTL 9个,LOD值为2.43~5.77,贡献率为8.4%~25.6%;与长宽比性状相关QTL 6个,LOD值为2.44~6.02,贡献率为9.8%~22.7%。     

Molecular genetic mapping of quantitative trait loci associated with loaf volume in hexaploid wheat (Triticum aestivum)

Major efforts in wheat research are being made to improve the yield and quality of wheat. Loaf volume (Lv) is the main quality parameter deciding the bread making potential of wheat. To genetically dissect quantitative trait loci (QTLs) for Lv, a Recombinant Inbred Line (RIL) population (F₈) was developed from a cross between two Indian wheat varieties “HI 977” and “HD 2329”. A total of 914 SSR and 100 ISSR primers were used for molecular analysis and the genetic map comprising 19 chromosomes was constructed with 202 SSR markers and 2 HMW glutenin subunit loci: Glu-B1 and Glu-D1. The phenotypic data were collected from six environments including three different agro-climatic zones for 2 consecutive years. Dissection of Lv through AMMI model revealed significant G×E variance for the trait. QTL analysis was performed using composite interval mapping. A total of 30 QTLs for Lv were detected and significant QTLs were identified on 6B and 6D chromosomes; 1B, 1D, 2A, 3A, 5B and 5D also contributed genetically to Lv. Association between 6B and 6D QTLs and variable expression of gliadins on group 6 chromosomes were discussed. QTLs detected in this study were compared with other QTL analysis in wheat.     

利用永久F2群体定位小麦穗部性状相关的QTL

为发掘与小麦穗部性状相关的QTL,利用普通小麦BS366与白玉149杂交组合培育的73个DH群体为材料,构建了一套包含232个杂交组合的小麦永久F2群体,基于90K SNP芯片标记构建了高密度遗传图谱,并利用该图谱对2个环境下的穗长、小穗数、穗粒数和千粒重进行QTL定位.结果发现,所构建的图谱总长19 533 cM,含...     

小麦旗叶大小及穗部相关性状的QTL定位

为了发掘更多控制小麦旗叶大小及穗部相关性状的QTL,以兰考906和小偃81创制的133个F6~F7重组自交系为试验材料,在6个环境下利用SSR标记对旗叶大小及穗部相关性状进行QTL定位。结果表明,有202对SSR标记被用于构建遗传连锁图谱,图谱覆盖小麦21条染色体,全长1 678.93cM,标记间平均距离8.30cM。采用完备区间作图法共检测到30个QTL,分布在1B、2A、3D、4A、4B、4D、5D、6A、6B、6D和7D染色体上。其中,旗叶宽QTL有7个,穗长QTL有9个,小穗数QTL有5个,穗粒数QTL有5个,小穗着生密度QTL有4个,不同环境下单个QTL可解释的表型变异率为4.94%~23.14%,有14个QTL的表型贡献率大于10%,有8个QTL可在2个或2个以上环境中被检测到。其中,Qflw-4A在3个环境中被检测到,贡献率为10.13%~20.77%,是控制旗叶宽的稳定主效QTL;Qsl-4D.2在4个环境中被检测到,贡献率为12.58%~23.14%,是控制穗长的稳定主效QTL;Qker-5D在2个环境中被检测到,贡献率为11.44%~14.32%,是控制穗粒数的稳定主效QTL。这3个稳定主效QTL可作为改良叶宽和增加穗粒数的功能QTL作进一步研究。