Two consensus quantitative trait loci clusters controlling anthesis–silking interval, ear setting and grain yield might be related with drought tolerance in maize

Unravelling the molecular basis of drought tolerance will provide novel opportunities for improving crop yield under water-limited conditions. The present study was conducted to identify quantitative trait loci (QTLs) controlling anthesis–silking interval (ASI), ear setting percentage (ESP) and grain yield (GY). The mapping population included 234 F₂ plants derived from the cross X178 (drought tolerant) × B73 (drought susceptible). The corresponding F_2:3 progenies, along with their parents, were evaluated for the above-mentioned traits under both well-watered and water-stressed field conditions in three different trials carried out in central and southern China. Interval mapping and composite interval mapping identified 45 and 65 QTLs for the investigated traits, respectively. Two QTL clusters influencing ASI and ESP on chromosomes 1 (bin 1.03) and 9 (bins 9.03–9.05) were identified in more than two environments, showing sizeable additive effects and contribution to phenotypic variance; these two QTL clusters influenced GY only in one environment. No significant interaction was detected between the two genomic regions. A comparative analysis of these two QTL clusters with the QTLs controlling maize drought tolerance previously described in three mapping populations confirmed and extended their relevance for marker-assisted breeding to improve maize production under water-limited conditions.     

Identification of quantitative trait loci under drought conditions in tropical maize. 2. Yield components and marker-assisted selection strategies

In most maize-growing areas yield reductions due to drought have been observed. Drought at flowering time is, in some cases, the most damaging. In the experiment reported here, trials with F₃ families, derived from a segregating F₂ population, were conducted in the field under well-watered conditions (WW) and two other water-stress regimes affecting flowering (intermediate stress, IS, and severe stress, SS). Several yield components were measured on equal numbers of plants per family: grain yield (GY), ear number (ENO), kernel number (KNO), and 100-kernel weight (HKWT). Correlation analysis of these traits showed that they were not independent of each other. Drought resulted in a 60% decrease of GY under SS conditions. By comparing yield under WW and SS conditions, the families that performed best under WW conditions were found to be proportionately more affected by stress, and the yield reductions due to SS conditions were inversely proportional to the performance under drought. Moreover, no positive correlation was observed between a drought-tolerance index (DTI) and yield under WW conditions. The correlation between GY under WW and SS conditions was 0.31. Therefore, in this experiment, selection for yield improvement under WW conditions only, would not be very effective for yield improvement under drought. Quantitative trait loci (QTLs) were identified for GY, ENO and KNO using composite interval mapping (CIM). No major QTLs, expressing more then 13% of the phenotypic variance, were detected for any of these traits, and there were inconsistencies in their genomic positions across water regimes. The use of CIM allowed the evaluation of QTL-by-environment interactions (Q×E) and could thus identify “stable” QTLs CIMMYT, Apartado Postal 6-641, 06600 Mexico D.F., Mexico across drought environments. Two such QTLs for GY, on chromosomes 1 and 10, coincided with two stable QTLs for KNO. Moreover, four genomic regions were identified for the expression of both GY and the anthesis-silking interval (ASI). In three of these, the allelic contributions were for short ASI and GY increase, while for that on chromosome 10 the allelic contribution for short ASI corresponded to a yield reduction. From these results, we hypothesize that to improve yield under drought, marker-assisted selection (MAS) using only the QTLs involved in the expression of yield components appears not to be the best strategy, and neither does MAS using only QTLs involved in the expression of ASI. We would therefore favour a MAS strategy that takes into account a combination of the “best QTLs” for different traits. These QTLs should be stable across target environments, represent the largest percentage possible of the phenotypic variance, and, though not involved directly in the expression of yield, should be involved in the expression of traits significantly correlated with yield, such as ASI.     

QTL mapping in three tropical maize populations reveals a set of constitutive and adaptive genomic regions for drought tolerance

Despite numerous published reports of quantitative trait loci (QTL) for drought-related traits, practical applications of such QTL in maize improvement are scarce. Identifying QTL of sizeable effects that express more or less uniformly in diverse genetic backgrounds across contrasting water regimes could significantly complement conventional breeding efforts to improve drought tolerance. We evaluated three tropical bi-parental populations under water-stress (WS) and well-watered (WW) regimes in Mexico, Kenya and Zimbabwe to identify genomic regions responsible for grain yield (GY) and anthesis-silking interval (ASI) across multiple environments and diverse genetic backgrounds. Across the three populations, on average, drought stress reduced GY by more than 50 % and increased ASI by 3.2 days. We identified a total of 83 and 62 QTL through individual environment analyses for GY and ASI, respectively. In each population, most QTL consistently showed up in each water regime. Across the three populations, the phenotypic variance explained by various individual QTL ranged from 2.6 to 17.8 % for GY and 1.7 to 17.8 % for ASI under WS environments and from 5 to 19.5 % for GY under WW environments. Meta-QTL (mQTL) analysis across the three populations and multiple environments identified seven genomic regions for GY and one for ASI, of which six mQTL on chr.1, 4, 5 and 10 for GY were constitutively expressed across WS and WW environments. One mQTL on chr.7 for GY and one on chr.3 for ASI were found to be ‘adaptive’ to WS conditions. High throughput assays were developed for SNPs that delimit the physical intervals of these mQTL. At most of the QTL, almost equal number of favorable alleles was donated by either of the parents within each cross, thereby demonstrating the potential of drought tolerant × drought tolerant crosses to identify QTL under contrasting water regimes.     

Mapping QTLs for root traits under different nitrate levels at the seedling stage in maize (Zea mays L.)

Nitrogen (N) loss is a worldwide problem in crop production. Apart from reasonable N fertilizer application, breeding N efficient cultivars provides an alternative way. Root architecture is an important factor determining N acquisition. However, little is known about the molecular genetic basis for root growth in relation to N supply. In the present study, an F₈ maize (Zea may L.) recombinant inbred (RI) population consisting of 94 lines was used to identify the QTLs for root traits under different nitrate levels. The lateral root length (LRL), axial root length (ARL), maximal axial root length (MARL), axial root number (ARN) and average axial root length (AARL) were evaluated under low N (LN) and high N (HN) conditions in a hydroponics system. A total of 17 QTLs were detected among which 14 loci are located on the same chromosome region as published QTLs for root traits. A major QTL on chromosome 1 (between bnlg1025 and umc2029) for the AARL under LN could explain 43.7% of the phenotypic variation. This QTL co-localizes with previously reported QTLs that associate with root traits, grain yield, and N uptake. Our results indicate that longer axial roots are important for efficient N acquisition and the major QTL for AARL may be used as a marker in breeding N efficient maize genotypes.     

Molecular mapping in tropical maize (Zea mays L.) using microsatellite markers. 2. Quantitative trait loci (QTL) for grain yield, plant height, ear height and grain moisture

A previous genetic map containing 117 microsatellite loci and 400 F(2) plants was used for quantitative trait loci (QTL) mapping in tropical maize. QTL were characterized in a population of 400 F(2:3) lines, derived from selfing the F(2) plants, and were evaluated with two replications in five environments. QTL determinations were made from the mean of these five environments. Grain yield (GY), plant height (PH), ear height (EH) and grain moisture (GM) were measured. Variance components for genotypes (G), environments (E) and GxE interaction were highly significant for all traits. Heritability was 0.69 for GY, 0.66 for PH, 0.67 for EH and 0.23 for GM. Using composite interval mapping (CIM), a total of 13 distinct QTLs were identified: four for GY, four for PH and five for EH. No QTL was detected for GM. The QTL explained 32.73 % of the phenotypic variance of GY, 24.76 % of PH and 20.91 % of EH. The 13 QTLs displayed mostly partial dominance or overdominance gene action and mapped to chromosomes 1, 2, 7, 8 and 9. Most QTL alleles conferring high values for the traits came from line L-14-4B. Mapping analysis identified genomic regions associated with two or more traits in a manner that was consistent with correlation among traits, supporting either pleiotropy or tight linkage among QTL. The low number of QTLs found, can be due to the great variation that exists among tropical environments.     

Mapping Quantitative Trait Loci Associated with Toot Traits Using Sequencing-Based Genotyping Chromosome Segment Substitution Lines Derived from 9311 and Nipponbare in Rice (Oryza sativa L.)

Identification of quantitative trait loci (QTLs) associated with rice root morphology provides useful information for avoiding drought stress and maintaining yield production under the irrigation condition. In this study, a set of chromosome segment substitution lines derived from 9311 as the recipient and Nipponbare as donor, were used to analysis root morphology. By combining the resequencing-based bin-map with a multiple linear regression analysis, QTL identification was conducted on root number (RN), total root length (TRL), root dry weight (RDW), maximum root length (MRL), root thickness (RTH), total absorption area (TAA) and root vitality (RV), using the CSSL population grown under hydroponic conditions. A total of thirty-eight QTLs were identified: six for TRL, six for RDW, eight for the MRL, four for RTH, seven for RN, two for TAA, and five for RV. Phenotypic effect variance explained by these QTLs ranged from 2.23% to 37.08%, and four single QTLs had more than 10% phenotypic explanations on three root traits. We also detected the correlations between grain yield (GY) and root traits, and found that TRL, RTH and MRL had significantly positive correlations with GY. However, TRL, RDW and MRL had significantly positive correlations with biomass yield (BY). Several QTLs identified in our population were co-localized with some loci for grain yield or biomass. This information may be immediately exploited for improving rice water and fertilizer use efficiency for molecular breeding of root system architectures.     

Identification of QTLs for root characteristics in maize grown in hydroponics and analysis of their overlap with QTLs for grain yield in the field at two water regimes

We investigated the overlap among quantitative trait loci (QTLs) in maize for seminal root traits measured in hydroponics with QTLs for grain yield under well-watered (GY-WW) and water-stressed (GY-WS) field conditions as well as for a drought tolerance index (DTI) computed as GY-WS/GY-WW. In hydroponics, 11, 7, 9, and 10 QTLs were identified for primary root length (R1L), primary root diameter (R1D), primary root weight (R1W), and for the weight of the adventitious seminal roots (R2W), respectively. In the field, 7, 8, and 9 QTLs were identified for GY-WW, GY-WS, and DTI, respectively. Despite the weak correlation of root traits in hydroponics with GY-WW, GY-WS, and DTI, a noticeable overlap between the corresponding QTLs was observed. QTLs for R2W most frequently and consistently overlapped with QTLs for GY-WW, GY-WS, and/or DTI. At four QTL regions, an increase in R2W was positively associated with GY-WW, GY-WS, and/or DTI. A 10 cM interval on chromosome 1 between PGAMCTA205 and php20644 showed the strongest effect on R1L, R1D, R2W, GY-WW, GY-WS, and DTI. These results indicate the feasibility of using hydroponics in maize to identify QTL regions controlling root traits at an early growth stage and also influencing GY in the field. A comparative analysis of the QTL regions herein identified with those described in previous studies investigating root traits in different maize populations revealed a number of QTLs in common.     

QTLs affecting morph-physiological traits related to drought tolerance detected in overlapping introgression lines of rice (Oryza sativa L.)

Plant photosynthetic traits such as net photosynthetic rate (P_n), stomata conductance (g_s), transpiration rate (T_r), and intercellular CO₂ concentration (C_i), are known to relate to drought tolerance in plants, but the genetic basis of these traits remains largely uncharacterized because of the difficulty in phenotyping physiological traits in a large mapping population. In this study, a set of 55 overlapping introgression lines (ILs) in the Teqing (indica) background were used to genetically dissect several morph-physiological traits and their relationship with grain yield under water stress and non-stress conditions. These traits included specific leaf weight (SLW), chlorophyll content (CC), leaf stomata frequency (SF), P_n, g_s, T_r, and C_i. A total of 40 QTLs affecting the measured traits were identified and mapped to 21 genomic regions in the rice genome. Clustered QTLs affecting P_n, g_s, T_r, and C_i in the same genomic regions suggest common genetic bases for the physiological traits. Low or no phenotypic correlations between leaf morphological traits and photosynthetic traits and between morph-physiological traits and grain yield (GY) appeared to be due to inconsistence in QTL effect for clustered QTLs, unlinked QTLs affecting different traits, and to possible epistasis that could not be adequately addressed in this study. Our results indicate that improving drought tolerant (DT) of rice by selecting any single secondary traits is not expected to be effective and the identified QTLs for GY and related morph-physiological traits should be carefully confirmed before to be used for improving DT in rice by MAS.     

QTL analysis of shading sensitive related traits in maize under two shading treatments

During maize development and reproduction, shading stress is an important abiotic factor influencing grain yield. To elucidate the genetic basis of shading stress in maize, an F(2:3) population derived from two inbred lines, Zhong72 and 502, was used to evaluate the performance of six traits under shading treatment and full-light treatment at two locations. The results showed that shading treatment significantly decreased plant height and ear height, reduced stem diameter, delayed day-to-tassel (DTT) and day-to-silk (DTS), and increased anthesis-silking interval (ASI). Forty-three different QTLs were identified for the six measured traits under shading and full light treatment at two locations, including seven QTL for plant height, nine QTL for ear height, six QTL for stem diameter, seven QTL for day-to-tassel, six QTL for day-to-silk, and eight QTL for ASI. Interestingly, three QTLs, qPH4, qEH4a, and qDTT1b were detected under full sunlight and shading treatment at two locations simultaneously, these QTL could be used for selecting elite hybrids with high tolerance to shading and high plant density. And the two QTL, qPH10 and qDTS1a, were only detected under shading treatment at two locations, should be quit for selecting insensitive inbred line in maize breeding procedure by using MAS method.     

QTLs for days to silking in a recombinant inbred line maize population subjected to high and low nitrogen regimes

Days to silking (DTS) is one of the most important traits in maize (Zea mays). To investigate its genetic basis, a recombinant inbred line population was subjected to high and low nitrogen (N) regimes to detect quantitative trait loci (QTLs) associated with DTS. Three QTLs were identified under the high N regime; these explained 25.4% of the phenotypic variance. Due to additive effects, the QTL on chromosome 6 increased DTS up to 0.66 days; while the other two QTLs mapped on chromosome 9 (one linked with Phi061 and the other linked with Nc134) decreased DTS 0.89 and 0.91 days, respectively. Under low N regime, two QTLs were mapped on chromosomes 6 and 9, which accounted for 25.9% of the phenotypic variance. Owing to additive effects, the QTL on chromosome 6 increased DTS 0.67 days, while the other QTL on chromosome 9 decreased it 1.48 days. The QTL on chromosome 6, flanked by microsatellite markers Bnlg1600 and Phi077, was detected under both N regimes. In conclusion, we identified four QTLs, one on chromosome 6 and three on chromosome 9. These results contribute to our understanding of the genetic basis of DTS and will be useful for developing marker-assisted selection in maize breeding programs.     

Phenotypic evaluation and QTL analysis of yield and symbiotic nitrogen fixation in a common bean population grown with two levels of phosphorus supply

Common bean is an important staple crop in Eastern Africa and Latin America. Low soil fertility is a major limitation to agronomic productivity. Symbiotic nitrogen fixation (SNF) is an important property of legumes, leading to high protein levels and high nutritional value. Nitrogen (N) metabolism and yield traits were evaluated in the common bean population DOR 364 × BAT 477 in field experiments under moderate and low phosphorus (P) soil conditions resembling environments found on farmers’ fields. Low P availability in soil severely limits seed yield, and trait correlations with yield reveal that high biomass as well as early maturity and efficient seed filling are important for good performance in low P stress, resembling drought resistance. Investigation of SNF and soil N uptake under low P stress showed reduced seed nitrogen levels and major variation in soil-derived N. In low P conditions, no significant reduction of %N derived from the atmosphere (%Ndfa) was observed; however, %Ndfa was correlated with yield, indicating that under stress SNF becomes an important asset. Significant genetic variation was observed for yield, yield components, and SNF ability suggesting that traits can be improved by breeding. Quantitative trait loci (QTLs) for %Ndfa and seed N concentration were discovered on chromosomes Pv07 and Pv02; independent yield QTLs were identified on the same chromosomes. Two QTL hotspots that affect several traits including yield components were found on Pv02 and Pv06; the latter represents a constitutive QTL hotspot independent from the environment. QTLs may be used for marker design and molecular breeding.     

Identification of QTL for maize grain yield and kernel-related traits

Grain yield (GY) is one of the most important and complex quantitative traits in maize (Zea mays L.) breeding practice. Quantitative trait loci (QTLs) for GY and three kernel-related traits were detected in a set of recombinant inbred lines (RILs). One hundred and seven simple sequence repeats (SSRs) and 168 insertion/deletion polymorphism markers (Indels) were used to genotype RILs. Eight QTLs were found to be associated with four yield-related traits: GY, 100-kernel weight (HKW), 10-kernel length (KL), and 10-kernel length width (KW). Each QTL explained between 5.96 (qKL2-1) and 13.05 (qKL1-1) per cent of the phenotypic variance. Notably, one common QTL, located at the marker interval between bnlg1893 and chr2-236477 (chromosomal bin 2.09) simultaneously controlled GY and HKW; another common QTL, at bin 2.03 was simultaneously responsible for HKW and KW. Of the QTLs identified, only one pair of significant epistatic interaction involved in chromosomal region at bin 2.03 was detected for HKW; no significant QTL × environment interactions were observed. These results provide the common QTLs and for marker-assisted breeding.     

Identification of quantitative trait loci controlling winter hardiness in an annual × perennial ryegrass interspecific hybrid population

Winter hardiness is a quantitative trait and the lack of it limits geographic distribution of ryegrass. Improving winter hardiness is an important breeding goal in ryegrass breeding programs. An understanding of the genetic basis for the component traits of winter hardiness would allow more efficient selection. A three-generation interspecific population of an annual × perennial ryegrass consisting of 152 progenies was used to map quantitative trait loci (QTL) that control winter hardiness-related traits including fall growth (FG), freezing tolerance (FT), and winter survival (WS) over 2 years. A total of 39 QTL were identified for the three traits from both the female parental (MFA) and the male parental (MFB) maps, of which 13 were for FG, 6 for FT, and 20 for WS. The proportion of phenotypic variation explained by individual QTL ranged from 10.4 to 22.1%. Both FG and FT were positively correlated with WS. Common QTL were detected between FG, FT, and WS. The QTL associated with WS on linkage groups (LGs) 4 and 5, and the QTL for FT on LG 5 were consistently identified over years and maps. These consistent QTL might serve as potential tools for marker-assisted selection to improve ryegrass winter hardiness.     

Meta-analysis of quantitative trait loci for grain yield and component traits under reproductive-stage drought stress in an upland rice population

A recombinant inbred population developed from a cross between high-yielding lowland rice (Oryza sativa L.) subspecies indica cv. IR64 and upland tropical rice subspecies japonica cv. Cabacu was used to identify quantitative trait loci (QTLs) for grain yield (GY) and component traits under reproductive-stage drought stress. One hundred fifty-four lines were grown in field trials in Indonesia under aerobic conditions by giving surface irrigation to field capacity every 4 days. Water stress was imposed for a period of 15 days during pre-flowering by withholding irrigation at 65 days after seeding. Leaf rolling was scored at the end of the stress period and eight agronomic traits were evaluated after recovery. The population was also evaluated for root pulling force, and a total of 201 single nucleotide polymorphism markers were used to construct the molecular genetic linkage map and QTL mapping. A QTL for GY under drought stress was identified in a region close to the sd1 locus on chromosome 1. QTL meta-analysis across diverse populations showed that this QTL was conserved across genetic backgrounds and co-localized with QTLs for leaf rolling and osmotic adjustment (OA). A QTL for percent seed set and grains per panicle under drought stress was identified on chromosome 8 in the same region as a QTL for OA previously identified in three different populations.     

Identification of quantitative trait loci under drought conditions in tropical maize. 1. Flowering parameters and the anthesis-silking interval

Drought is an important climatic phenomenon which, after soil infertility, ranks as the second most severe limitation to maize production in developing countries. When drought stress occurs just before or during the flowering period, a delay in silking is observed, resulting in an increase in the length of the anthesis-silking interval (ASI) and in a decrease in grain yield. Selection for reduced ASI in tropical open-pollinated varieties has been shown to be correlated with improved yields under drought stress. Since efficient selection for drought tolerance requires carefully managed experimental conditions, molecular markers were used to identify the genomic segments responsible for the expression of ASI, with the final aim of developing marker-assisted selection (MAS) strategies. An F₂population of 234 individuals was genotyped at 142 loci and F₃ families were evaluated in the field under several water regimes for male flowering (MFLW), male sterility (STER), female flowering (FFLW) and ASI. The genetic variance of ASI increased as a function of the stress intensity, and the broad-sense heritabilites of MFLW, FFLW and ASI were high under stress conditions, being 86%, 82% and 78%, respectively. Putative quantitative trait loci (QTLs) involved in the expression of MFLW and/or FFLW under drought were detected on chromosomes 1, 2, 4, 5, 8, 9 and 10, accounting for around 48% of the phenotypic variance for both traits. For ASI, six putative QTLs were identified under drought on chromosomes 1, 2, 5, 6, 8 and 10, and together accounted for approximately 47% of the phenotypic variance. Under water stress conditions, four QTLs were common for the expression of MFLW and FFLW, one for the expression of ASI and MFLW, and four for the expression of ASI and FFLW. The number of common QTLs for two traits was related to the level of linear correlation between these two traits. Segregation for ASI was found to be transgressive with the drought-susceptible parent contributing alleles for reduced ASI (4 days) at two QTL positions. Alleles contributed by the resistant line at the other four QTLs were responsible for a 7-day reduction of ASI. These four QTLs represented around 9% of the linkage map, and were stable over years and stress levels. It is argued that MAS based on ASI QTLs should be a powerful tool for improving drought tolerance of tropical maize inbred lines.     

QTL Mapping of Growth-Related Traits in a Full-Sib Family of Rubber Tree (Hevea brasiliensis) Evaluated in a Sub-Tropical Climate

The rubber tree (Hevea spp.), cultivated in equatorial and tropical countries, is the primary plant used in natural rubber production. Due to genetic and physiological constraints, inbred lines of this species are not available. Therefore, alternative approaches are required for the characterization of this species, such as the genetic mapping of full-sib crosses derived from outbred parents. In the present study, an integrated genetic map was obtained for a full-sib cross family with simple sequence repeats (SSRs) and expressed sequence tag (EST-SSR) markers, which can display different segregation patterns. To study the genetic architecture of the traits related to growth in two different conditions (winter and summer), quantitative trait loci (QTL) mapping was also performed using the integrated map. Traits evaluated were height and girth growth, and the statistical model was based in an extension of composite interval mapping. The obtained molecular genetic map has 284 markers distributed among 23 linkage groups with a total length of 2688.8 cM. A total of 18 QTLs for growth traits during the summer and winter seasons were detected. A comparison between the different seasons was also conducted. For height, QTLs detected during the summer season were different from the ones detected during winter season. This type of difference was also observed for girth. Integrated maps are important for genetics studies in outbred species because they represent more accurately the polymorphisms observed in the genitors. QTL mapping revealed several interesting findings, such as a dominance effect and unique segregation patterns that each QTL could exhibit, which were independent of the flanking markers. The QTLs identified in this study, especially those related to phenotypic variation associated with winter could help studies of marker-assisted selection that are particularly important when the objective of a breeding program is to obtain phenotypes that are adapted to sub-optimal regions.     

QTL x environment interactions in rice. I. heading date and plant height

One hundred twenty six doubled-haploid (DH) rice lines were evaluated in nine diverse Asian environments to reveal the genetic basis of genotype × environment interactions (GEI) for plant height (PH) and heading date (HD). A subset of lines was also evaluated in four water-limited environments, where the environmental basis of G × E could be more precisely defined. Responses to the environments were resolved into individual QTL × environment interactions using replicated phenotyping and the mixed linear-model approach. A total of 37 main-effect QTLs and 29 epistatic QTLs were identified. On average, these QTLs were detectable in 56% of the environments. When detected in multiple environments, the main effects of most QTLs were consistent in direction but varied considerably in magnitude across environments. Some QTLs had opposite effects in different environments, particularly in water-limited environments, indicating that they responded to the environments differently. Inconsistent QTL detection across environments was due primarily to non- or weak-expression of the QTL, and in part to significant QTL × environment interaction effects in the opposite direction to QTL main effects, and to pronounced epistasis. QTL × environment interactions were trait- and gene-specific. The greater GEI for HD than for PH in rice were reflected by more environment-specific QTLs, greater frequency and magnitude of QTL × environment interaction effects, and more pronounced epistasis for HD than for PH. Our results demonstrated that QTL × environment interaction is an important property of many QTLs, even for highly heritable traits such as height and maturity. Information about QTL × environment interaction is essential if marker-assisted selection is to be applied to the manipulation of quantitative traits.Communicated by G. Wenzel     

Genetic Analysis of Carbon Isotope Discrimination and its Relation to Yield in a Wheat Doubled Haploid Population

Carbon isotope discrimination (Δ¹³C) is considered a useful indicator for indirect selection of grain yield (GY) in cereals. Therefore, it is important to evaluate the genetic variation in Δ¹³C and its relationship with GY. A doubled haploid (DH) population derived from a cross of two common wheat varieties, Hanxuan 10 (H10) and Lumai 14 (L14), was phenotyped for Δ¹³C in the flag leaf, GY and yield associated traits in two trials contrasted by water availability, specifically, rain‐fed and irrigated. Quantitative trait loci (QTLs) were identified by single locus and two locus QTL analyses. QTLs for Δ¹³C were located on chromosomes 1A, 2B, 3B, 5A, 7A and 7B, and QTLs for other traits on all chromosomes except 1A, 4D, 5A, 5B and 6D. The population selected for high Δ¹³C had an increased frequency of QTL for high Δ¹³C, GY and number of spikes per plant (NSP) when grown under rain‐fed conditions and only for high Δ¹³C and NSP when grown under irrigated conditions, which was consistent with agronomic performance of the corresponding trait values in the high Δ¹³C progeny; that is, significantly greater than that in the low Δ¹³C. Therefore, selection for Δ¹³C was beneficial in increasing grain yield in rain‐fed environments.     

QTLs linked to leaf epicuticular wax,physio-morphological and plant production traits under drought stress in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

Drought stress is the major constraint to rice (Oryza sativa L.) production and yield stability in rainfed ecosystems. Identifying genomic regions contributing to drought resistance will help to develop rice cultivars suitable for rainfed regions through marker-assisted breeding. Quantitative trait loci (QTLs) linked to leaf epicuticular wax, physio-morphological and plant production traits under water stress and irrigated conditions were mapped in a doubled haploid (DH) line population from the cross CT9993-5-10-1-M/IR62266-42-6-2. The DH lines were subjected to water stress during anthesis. The DH lines showed significant variation for epicuticular wax (EW), physio-morphological and plant production traits under stress and irrigated conditions. A total of 19 QTLs were identified for the various traits under drought stress and irrigated conditions in the field, which individually explained 9.6%–65.6% of the phenotypic variation. A region EM15_10-ME8_4-R1394A-G2132 on chromosome 8 was identified for leaf EW and rate of water loss i.e., time taken to reach 70% RWC from excised leaves in rice lines subjected to drought stress. A large effect QTL (65.6%) was detected on chromosome 2 for harvest index under stress. QTLs identified for EW, rate of water loss from excised leaves and harvest index under stress in this study co-located with QTLs linked to shoot and root-related drought resistance traits in these rice lines and might be useful for rainfed rice improvement.