小麦籽粒干物质积累的动态QTL定位

以波兰小麦品系‘XN555’与普通小麦品系‘中13’杂交产生的99个F10重组自交系(RILs)为材料,构建了包含241个SSR分子标记的A、B染色体组14个连锁群的遗传图谱,并采用Logistic方程拟合籽粒灌浆过程,对粒重增长的缓慢增长期、快速增长期和平稳期进行千粒重条件QTL和非条件QTL定位分析。结果显示:(1)在小麦A、B染色体组上共检测到5个非条件QTL和5个条件QTL。(2)在小麦粒重缓慢增长期和快速增长期各有2个非条件QTL,平稳期有1个非条件QTL,它们分别位于2B、3A、3B和7A染色体上,单个QTL可解释表型变异的9.66%～15.18%。(3)在小麦粒重快速增长期检测到1个条件QTL,平稳期检测到4个条件QTL,涉及1A、2B、5B和7B染色体,单个QTL可解释表型变异的13.01%～29.27%。(4)于2B染色体Xbarc361～Xwmc422标记区间距Xbarc361标记0.05cM处,在粒重快速增长期同时检测到一个条件QTL和非条件QTL,且在平稳期检测到一个非条件QTL。研究表明,小麦不同灌浆时期粒重增长相关QTL的数量和遗传效应各不同,同一QTL在不同灌浆时期的遗传效应也不同,即QTL的表达具有时序选择性。     

小麦幼苗耐热性的QTL定位分析

以小麦DH群体(‘旱选10号’ב鲁麦14’)为材料,在高温(热胁迫)及常温(对照)两种条件下考察小麦幼苗的根干重、苗干重、幼苗生物量、叶片叶绿素含量、叶绿素荧光参数及其耐热指数,并应用基于混合线性模型的复合区间作图法分析幼苗性状及其耐热指数QTL的数量、染色体分布及表达情况,以及QTL与环境的互作效应。结果显示:(1)亲本‘旱选10号’的耐热性明显优于‘鲁麦14’,且杂交后代的耐热性出现超亲分离。(2)控制幼苗耐热相关性状的QTL位点在染色体2D、6B、3A、4A、5A和7A上分布较多,而控制幼苗性状耐热指数的QTL在染色体6A、6B、3A、2D、5A和7A上分布较多,QTL位点在染色体上的分布有区域化的趋势。(3)控制幼苗性状的单个加性QTL和上位性QTL解释的表型变异分别平均为2.48%和2.65%;而控制耐热指数的单个加性QTL和上位性QTL解释的表型变异分别平均为8.84%和1.98%。(4)在热胁迫和对照条件下共检测到与幼苗性状及其耐热指数有关的加性效应QTL 13个和上位性效应QTL 28对,分布在除4D和6D以外的19条染色体上。研究表明,控制幼苗性状的QTL以上位性效应为主,而其耐热指数的QTL以加性效应为主。     

小麦萌发期抗旱和耐盐性状的QTL分析

该研究以‘山农0431×鲁麦21’RIL群体及其父母本为材料,用20%PEG-6000溶液和100 mmol·L-1 NaCl溶液分别模拟干旱和盐环境,对12个小麦萌发期抗旱耐盐相关性状进行测定,结合已构建的分子标记遗传图谱对小麦萌发期抗旱、耐盐的相关性状进行QTL分析,为小麦抗旱、耐盐基因的克隆和分子标记辅助选择提供参考。结果表明:(1)正常、干旱和盐胁迫3种处理下共检测到143个QTL。检测到相对高频QTL(RHF-QTL)29个,平均贡献率范围为4.39%~13.28%,贡献率在10%以上的主效RHF-QTL有10个。(2)检测到胁迫下特异表达的RHF-QTL共17个,正常处理下特异表达的RHF-QTL为8个,稳定表达的RHF-QTL为4个。(3)QTL分析结果表明,7个RHF-QTL形成了3个QTL簇,且分布在2D、4D和5B等3条染色体上,其中:QC1位于2D染色体的wPt-6847~D-1172783区间,包括3个QTL(QRl-2D.2、QSdw-2D.3、QTdw-2D);QC2位于4D染色体短臂的D-2245724~D-1108531区间,包括2个QTL(QSl-4D、QShl-4D);QC3位于5B染色体的D-982263~S-1083095区间,包括2个QTL(QSl-5B.2、QTdw-5B.1)。     

控制水稻重要农艺性状的QTL在盐胁迫与非胁迫条件下的对比研究

基因型与环境的互作(G×E)对数量性状的影响常常掩盖了遗传因子引起的性状变化. 在盐胁迫环境与非胁迫环境下分别调查了水稻(Oriza sativa L.) 5个重要的农艺性状, 总共检测到24个QTL, 分布在除第9, 11号染色体外的各染色体上. 盐胁迫环境中检出了9个QTL: 千粒重1个; 抽穗期2个; 株高1个; 每穗粒数2个; 有效分蘖3个, 占总数的37.5%; 非胁迫环境中则检出了17个QTL: 千粒重5个; 抽穗期6个; 株高3个; 每穗粒数2个; 有效分蘖1个, 占总数的70.8%; 有两个QTL在两种环境中都检测到, 占总数的8.3%, 它们分别是位于第4染色体上控制抽穗期的QTL和位于第6染色体上控制每穗粒数的QTL. 此外, 还检测出3个包含多个QTL的区间, 它们分别位于第1, 4和8染色体上, 其中第1染色体上RG612分子标记附近检出两个QTL, 在盐胁迫环境与非胁迫环境中分别控制有效分蘖和抽穗期这两个重要的农艺性状, 其加性效应均由来源于JX17的等位基因提供; 第4染色体上的C975-RG449区间检测到2个QTL, qrHD-4c在非协迫环境中控制抽穗期, qrGPP-4s则在胁迫环境中控制每穗粒数; 第8染色体上的RG885-GA408区间检测到3个QTL, 在非胁迫环境下分别控制抽穗期、千粒重、株高3个性状, 在胁迫环境下则未能检测到. 通过对水稻在盐胁迫环境与非胁迫环境下的QTL对比研究, 发现水稻第8染色体上几个控制水稻重要农艺性状的QTL明显受盐胁迫的影响.     

不同发育时期小麦粒重性状QTL的动态分析

利用6044×01-35构建的重组自交系(RIL)群体为试验材料,对小麦粒重性状进行发育动态QTL分析。结果表明,在小麦花后子粒灌浆的7个不同时期,两个试验点共检测到16个与粒重性状相关的QTL。其中开花后20d检测到的单穗粒重QTL位于2A染色体上,解释率达12%,遗传效应超过10;两环境下控制千粒重QTL在7个时期均被检测到。花后的各个时期均能在Xgwm448-Xgpw7399标记区间定位到千粒重QTL。其中花后10d检测到1个千粒重QTL,位于2A染色体的Xgwm448-Xgpw7399标记区间,解释较大的表型变异,达到18%。Qtl8、Qtl13和Qtl14均定位在Xgwm448-Xgpw7399标记区间的同一位置,共同解释11%的表型变异。花后20d和花后25d均检测到1个QTL,位于2A染色体的Xgwm372-Xgwm95标记区间的不同位点,均能解释4%的表型变异。花后40d检测到1个QTL,位于1D染色体的Xwmc93-Xgpw2224标记区间,解释1%的表型变异。从连锁群的位置上看,控制千粒重的QTL主要集中在2A染色体的Xgwm448-Xgpw7399标记区间,这是一个控制千粒重QTL的富集区域,以期进行精细定位和图位克隆。     

小麦旗叶长、宽及面积的QTL分析

以小麦品种‘小偃81’和‘西农1376’构建的含236个家系的自交重组系(RIL)群体(F2:7、F2:8代)为研究材料,采用完全随机区组设计,连续2年在陕西杨陵、河南驻马店和山东济南于灌浆期(花后20d)随机取每个株系10株测量旗叶长、宽,并利用172个SSR标记构建了遗传连锁图谱,通过基于完备区间作图法的QTL IciMapping V3.2软件,对控制小麦旗叶长、宽和面积的数量性状位点(QTL)进行了加性效应分析。结果发现:(1)9个旗叶长QTLs位于1A、4A、3B、5D和7D染色体上,单个QTL可解释5.10%~16.44%的表型变异;10个旗叶宽QTLs位于1A、3A、5A、7A、3B和5D染色体上,单个QTL可解释4.63%~14.24%的表型变异;12个旗叶面积QTLs位于1A、4A、3B、2D和5D染色体上,单个QTL可解释4.25%~22.67%的表型变异。(2)控制小麦旗叶长、宽和面积的QTLs存在差异,同一QTL在不同性状中的遗传贡献率也不同。(3)同一性状在同一年份,不同地点和在不同年份,相同地点下检测到的QTLs有的相同,但有的差异明显。(4)有些控制不同性状的QTLs在染色体的同一标记区间,表现一因多效。研究表明:位于1A和5D染色体上的2个加性QTLs都同时控制旗叶长、宽和面积,且前者为主效基因,后者遗传贡献率也较大,可用于标记辅助育种和分子聚合育种。     

小麦重组自交系(RILs)群体碳同位素分辨率的QTL分析

为了探知小麦水分利用效率(WUE)碳同位素分辨率(Δ)的遗传机理,以小麦重组自交系(RILs)群体为材料,在不同水分条件下研究Δ的遗传规律,并进行QTL定位。结果表明:(1)RILs群体的Δ值呈正态分布,Δ属于数量性状遗传。(2)共检测到11个主效QTL,主要位于2B、3B、7B、1D和3D染色体上,表型贡献率在10.83%~46.87%之间,有9个加性QTL(A-QTL)与环境发生互作,互作贡献率在1.02%~3.15%之间。(3)检测到5对影响Δ的上位QTL(AA-QTL),其中3对AA-QTL与环境发生互作,互作贡献率在0.86%~2.01%之间。(4)加性效应及贡献率大于上位性效应及贡献率,A-QTL与环境互作贡献率大于AA-QTL与环境互作贡献率,表明RILs群体中Δ遗传变异主要受加性效应影响,控制Δ的主效基因作用较大,受水分环境影响较小。     

玉米雄穗分枝数与主轴长的QTL鉴定

在包含103个SSR标记的连锁图谱基础上, 运用复合区间作图法检测玉米组合(N87-1×9526 )F3家系在正常与干旱胁迫环境下的雄穗分枝数与主轴长性状QTL。雄穗分枝数在正常环境下被检测到2个QTL座位, 分别位于第5和7连锁群上; 在胁迫环境下被检测到4个QTL座位分别位于 2、5、7和10连锁群上, 其中位于第5和7连锁群上的QTL不仅具有一致性而且与本作图群体中曾检测到的耐旱相关性状QTL存在连锁。雄穗主轴长在正常环境下被检测到2个QTL位于第2和第6连锁群上, 在干旱胁迫环境下被检测到了3个QTL分别于第2、4和10连锁群上, 其中位于第2染色体上的QTL是两种环境下所共同检测到的QTL。分析QTL的遗传作用方式表明, 雄穗分枝数以部分加性效应为主, 而雄主轴长全部表现为显性和超显性。     

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。     

水稻低温发芽性QTL的分子标记定位

利用1个粳／籼交来源的重组自交系群体,采用纸卷法在15℃低温条件下进行发芽试验,在发芽培养的6～14d中每天观测统计1次发芽率(％)。结合一张含有198个DNA标记的连锁图谱,用复合区间作图法定位水稻低温发芽性QTL。共检测到7个主效应QTL,分别位于水稻1、3、5、6和8号染色体上,单个QTL对性状的贡献率为5％～16％。其中,位于3号染色体标记区间RM148-RM85的qLTG-3-2和位于8号染色体标记区间RM223-RM210的qLTG-8-1对性状的贡献率最大,分别达16％和14％。QTL qLTG-3-2在发芽培养6～10d中表达,其效应由强渐弱,对性状的贡献率由发芽培养6d时的16．4％逐渐降低为发芽11d时的5．1％;而QTL qLTG-8-1则在发芽培养9～14d中起作用,其效应值由小逐渐增大,对性状的贡献率由发芽9d时的8．6％逐渐上升为发芽13～14d的14％。尽管这2个QTL加性效应的大小在低温发芽过程中按一定趋势变化,但加性效应的方向始终是一致的。QTL qLTG-3-2的增效基因来源于亲本特青,而QTL qLTG-8-1的增效基因来自于亲本Lemont。这2个QTL的增效等位基因有望作为分子标记辅助育种的操作对象,用于水稻品种低温发芽性的遗传改良。     

Quantitative trait loci associated with constitutive traits control water use in pearl millet [Pennisetum glaucum (L.) R. Br.]

There is substantial genetic variation for drought adaption in pearl millet in terms of traits controlling plant water use. It is important to understand genomic regions responsible for these traits. Here, F₇ recombinant inbred lines were used to identify quantitative trait loci (QTL) and allelic interactions for traits affecting plant water use, and their relevance is discussed for crop productivity in water‐limited environments. Four QTL contributed to increased transpiration rate under high vapour pressure deficit (VPD) conditions, all with alleles from drought‐sensitive parent ICMB 841. Of these four QTL, a major QTL (35.7%) was mapped on linkage group (LG) 6. The alleles for 863B at this QTL decreased transpiration rate and this QTL co‐mapped to a previously detected LG 6 QTL, with alleles from 863B for grain weight and panicle harvest index across severe terminal drought stress environments. This provided additional support for a link between water saving from a lower transpiration rate under high VPD and drought tolerance. 863B alleles in this same genomic region also increased shoot weight, leaf area and total transpiration under well‐watered conditions. One unexpected outcome was reduced transpiration under high VPD (15%) from the interaction of two alleles for high VPD transpiration (LG 6 (B), 40.7) and specific leaf mass and biomass (LG 7 (A), 35.3), (A, allele from ICMB 841, B, allele from 863B, marker position). The LG 6 QTL appears to combine alleles for growth potential, beneficial for non‐stress conditions, and for saving water under high evaporative demand, beneficial under stressful conditions. Mapping QTL for water‐use traits, and assessing their interactions offers considerable potential for improving pearl millet adaptation to specific stress conditions through physiology‐informed marker‐assisted selection.     

Detection of QTL for phosphorus efficiency at vegetative stage in Brassica napus

Phosphorus (P) deficiency in soils is a major limiting factor for plant growth worldwide. Plants have developed adaptive strategies in response to P deficiency. The objective of this study was to map quantitative trait loci (QTL) for P efficiency using a recombinant inbred (RI) population consisting of 124 lines derived from a cross between Brassica napus P-inefficient cv. B104-2 and P-efficient cv. Eyou Changjia. Six traits (shoot dry weight, root dry weight, root/shoot ratio, P concentration, shoot P uptake and shoot P use efficiency) at vegetative stage were examined under high P (HP, 1 mM) and low P (LP, 5 ??M) conditions during three separate experimental trial periods. Their relative values (i.e., the ratio of a trait value under the LP condition to that under the HP condition) of these six traits were also determined. Eyou Changjia produced more biomass and acquired more P under the LP condition and, thus, had a higher relative dry weight and relative P uptake than B104-2, indicating Eyou Changjia was high P efficiency. A total of 71 QTL were detected on 13 linkage groups, including 28 QTL under the LP condition, 22 QTL under the HP condition and 21 QTL for relative traits. Nineteen and nine QTL were specific for the LP and HP conditions, respectively, suggesting that different mechanisms existed under the two P condition. Twelve of the twenty-one QTL for relative traits co-localized with QTL identified under the two P conditions. In addition, 18 orthologous genes involved in the P metabolic pathway of Arabidopsis were in silico mapped to the QTL confidence intervals identified in B. napus by comparative genomic analysis. These QTL and their corresponding candidate genes should be further investigated to better understand P efficiency in B. napus.     

Genetic Control of Water Use Efficiency and Leaf Carbon Isotope Discrimination in Sunflower (Helianthus annuus L.) Subjected to Two Drought Scenarios

High water use efficiency (WUE) can be achieved by coordination of biomass accumulation and water consumption. WUE is physiologically and genetically linked to carbon isotope discrimination (CID) in leaves of plants. A population of 148 recombinant inbred lines (RILs) of sunflower derived from a cross between XRQ and PSC8 lines was studied to identify quantitative trait loci (QTL) controlling WUE and CID, and to compare QTL associated with these traits in different drought scenarios. We conducted greenhouse experiments in 2011 and 2012 by using 100 balances which provided a daily measurement of water transpired, and we determined WUE, CID, biomass and cumulative water transpired by plants. Wide phenotypic variability, significant genotypic effects, and significant negative correlations between WUE and CID were observed in both experiments. A total of nine QTL controlling WUE and eight controlling CID were identified across the two experiments. A QTL for phenotypic response controlling WUE and CID was also significantly identified. The QTL for WUE were specific to the drought scenarios, whereas the QTL for CID were independent of the drought scenarios and could be found in all the experiments. Our results showed that the stable genomic regions controlling CID were located on the linkage groups 06 and 13 (LG06 and LG13). Three QTL for CID were co-localized with the QTL for WUE, biomass and cumulative water transpired. We found that CID and WUE are highly correlated and have common genetic control. Interestingly, the genetic control of these traits showed an interaction with the environment (between the two drought scenarios and control conditions). Our results open a way for breeding higher WUE by using CID and marker-assisted approaches and therefore help to maintain the stability of sunflower crop production.     

Mapping QTLs for Plant Phenology and Production Traits Using Indica Rice (Oryza sativa L.) Lines Adapted to Rainfed Environment

Drought is a major abiotic stress limiting rice production and yield stability in rainfed ecosystems. Identifying quantitative trait loci (QTL) for rice yield and yield components under water limited environments will help to develop drought resilient cultivars using marker assisted breeding (MAB) strategy. A total of 232 recombinant inbred lines of IR62266/Norungan were used to map QTLs for plant phenology and production traits under rainfed condition in target population of environments. A total of 79 QTLs for plant phenology and production traits with phenotypic variation ranging from 4.4 to 72.8% were detected under non-stress and drought stress conditions across two locations. Consistent QTLs for phenology and production traits were detected across experiments and water regimes. The QTL region, RM204-RM197-RM217 on chromosome 6 was linked to days to 50% flowering and grain yield per plant under both rainfed and irrigated conditions. The same genomic region, RM585-RM204-RM197 was also linked to harvest index under rainfed condition with positive alleles from Norungan, a local landrace. QTLs for plant production and drought resistance traits co-located near RM585-RM204-RM197-RM217 region on chromosome 6 in several rice genotypes. Thus with further fine mapping, this region may be useful as a candidate QTL for MAB, map-based cloning of genes and functional genomics studies for rainfed rice improvement.     

Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas fir. III. Quantitative trait loci-by-environment interactions

Quantitative trait loci (QTL) were mapped in the woody perennial Douglas fir (Pseudotsuga menziesii var. menziesii [Mirb.] Franco) for complex traits controlling the timing of growth initiation and growth cessation. QTL were estimated under controlled environmental conditions to identify QTL interactions with photoperiod, moisture stress, winter chilling, and spring temperatures. A three-generation mapping population of 460 cloned progeny was used for genetic mapping and phenotypic evaluations. An all-marker interval mapping method was used for scanning the genome for the presence of QTL and single-factor ANOVA was used for estimating QTL-by-environment interactions. A modest number of QTL were detected per trait, with individual QTL explaining up to 9.5% of the phenotypic variation. Two QTL-by-treatment interactions were found for growth initiation, whereas several QTL-by-treatment interactions were detected among growth cessation traits. This is the first report of QTL interactions with specific environmental signals in forest trees and will assist in the identification of candidate genes controlling these important adaptive traits in perennial plants.     

Genetic analysis of tolerance to photo-oxidative stress induced by high light in winter wheat （Triticum aestivum L.）

High light induced photooxidation (HLIP) usually leads to leaf premature senescence and causes great yield loss in winter wheat. In order to explore the genetic control of wheat tolerance to HLIP stress, a quantitative trait loci (QTL) analysis was conducted on a set of doubled haploid population, derived from two winter wheat cultivars. Actual values of chlorophyll content (Chl), minimum fluorescence level (Fo), maximum fluorescence level (Fm), and the maximum quantum efficiency of photosystem Ⅱ (Fv/Fm) under both HLIP and non-stress conditions as well as the ratios of HLIP to non-stress were evaluated. HLIP considerably reduced Chl, Fm, and Fv/Fm, but increased Fo, compared with that under non-stress condition. A total of 27, 16, and 28 QTLs were associated with the investigated traits under HLIP and non-stress and the ratios of HLIP to non-stress, respectively. Most of the QTLs for the ratios of HLIP to non-stress collocated or nearly linked with those detected under HLIP condition. HLIP-induced QTLs were mapped on 15 chromosomes, involving in 1A, 1B, 1D,2A, 2B, 2D, 3A, 3B, 4A, 4D, 5B, 6A, 6B, 7A, and 7D while those expressed under non-stress condition involved in nine chromosomes, including 1B, 1D, 2A, 2B, 3B, 4A, 5A, 5B, and 7A. The expression patterns of QTLs under HLIP condition were different from that under non-stress condition except for six loci on five chromosomes. The phenotypic variance explained by individual QTL ranged from 5.0% to 19.7% under HLIP, 8.3% to 20.8% under non-stress, and 4.9% to 20.2% for the ratios of HLIP to non-stress, respectively. Some markers, for example,Xgwm192 and WMC331 on 4D regulating Chl, Fo, Fm, and Fv/Fm under HLIP condition, might be used in marker assistant selection.     

Quantitative Trait Loci Mapping of Maize Yield and Its Components Under Different Water Treatments at Flowering Time

Drought or water stress is a serious agronomic problem resulting in maize (Zea mays L.) yield loss throughout the world. Breeding hybrids with drought tolerance is one important approach for solving this problem. However, lower efficiency and a longer period of breeding hybrids are disadvantages of traditional breeding programs. It is generally recognized that applying molecular marker techniques to traditional breeding programs could improve the efficiency of the breeding of drought‐tolerant maize. To provide useful information for use in studies of maize drought tolerance, the mapping and tagging of quantitative trait loci (QTL) for yield and its components were performed in the present study on the basis of the principle of a mixed linear model. Two hundred and twenty‐one recombinant inbred lines (RIL) of Yuyu 22 were grown under both well‐watered and water‐stressed conditions. In the former treatment group, plants were well irrigated, whereas those in the latter treatment group were stressed at flowering time. Ten plants of each genotype were grown in a row that was 3.00 m × 0.67 m (length × width). The results show that a few of the QTL were the same (one additive QTL for ear length, two additive QTL and one pair of epistatic QTL for kernel number per row, one additive QTL for kernel weight per plant), whereas most of other QTL were different between the two different water treatment groups. It may be that genetic expression differs under the two different water conditions. Furthermore, differences in the additive and epistatic QTL among the traits under water‐stressed conditions indicate that genetic expression also differs from trait to trait. Major and minor QTL were detected for the traits, except for kernel number per row, underwater‐stressed conditions. Thus, the genetic mechanism of drought tolerance in maize is complex because the additive and epistatic QTL exist at the same time and the major and minor QTL all contribute to phenotype under water‐stressed conditions. In particular, epidemic QTL under water‐stressed conditions suggest that it is important to investigate the drought tolerance of maize from a genetic viewpoint. (Managing editor: Wei Wang)     

Quantitative trait loci for water-use efficiency in barley (Hordeum vulgare L.) measured by carbon isotope discrimination under rain-fed conditions on the Canadian Prairies

Barley (Hordeum vulgare L.) yield is commonly limited by low rainfall and high temperature during the growing season on the Canadian Prairies. Empirical knowledge suggests that carbon isotope discrimination (Δ(13)C), through its negative relationship with water-use efficiency (WUE), is a good index for selecting stable yielding crops in some rain-fed environments. Identification of quantitative trait loci (QTL) and linked markers for Δ(13)C will enhance its use efficiency in breeding programs. In the present study, two barley populations (W89001002003?×?I60049 or W?×?I, six-row type, and Merit?×?H93174006 or M?×?H, two-row type), containing 200 and 127 recombinant inbred lines (RILs), were phenotyped for leaf Δ(13)C and agronomic traits under rain-fed environments in Alberta, Canada. A transgressive segregation pattern for leaf Δ(13)C was observed among RILs. The broad-sense heritability (H (2)) of leaf Δ(13)C was 0.8, and there was no significant interaction between genotype and environment for leaf Δ(13)C in the W?×?I RILs. A total of 12 QTL for leaf Δ(13)C were detected in the W?×?I RILs and 5 QTL in the M?×?H RILs. For the W?×?I RILs, a major QTL located on chromosome 3H near marker Bmag606 (9.3, 9.4 and 10.7?cM interval) was identified. This major QTL overlapped with several agronomic traits, with W89001002003 alleles favoring lower leaf Δ(13)C, increased plant height, and reduced leaf area index, grain yield, harvest index and days to maturity at this locus or loci. This major QTL and its associated marker, when validated, maybe useful in breeding programs aimed at improving WUE and yield stability of barley on the Canadian Prairies.