Identification of QTLs associated with potassium use efficiency and underlying candidate genes by whole-genome resequencing of two parental lines in Brassica napus

Breeding crops that acquire and/or utilize potassium (K) more effectively could reduce the use of K fertilizers. Sixteen traits affecting K use efficiency (KUE) at the seedling stage were investigated in a B. napus double haploid population grown at an optimal K supply (OK) and a low K supply (LK) in a hydroponic culture system. In total, 50 and 62 QTLs associated with these traits were identified at OK and LK, respectively. A total of 25 orthologues of 23 Arabidopsis genes regulating K transport were identified in the confidence intervals of nine QTLs impacting shoot dry weight at LK, and 22 of these showed variations in coding sequences and/or exhibited significant differences in mRNA abundances in roots at LK between the two parental lines. This study provided insights to the genetic basis of KUE in B. napus, which will accelerate the breeding of K-efficient rapeseed cultivars by marker-assisted selection.     

Mapping quantitative trait loci associated with yield and yield components under reproductive stage salinity stress in rice (Oryza sativa L.)

Salinity tolerance in rice is critical at reproductive stage because it ultimately determines grain yield. An F₂ mapping population derived from a Sadri/FL478 cross was exposed to saline field conditions (6–8 dS m^???1) after the active tillering stage to identify reproductive stage specific QTLs for salinity tolerance. Genetic linkage map was constructed using 123 microsatellite markers on 232 F₂ progenies. Totally 35 QTLs for 11 traits under salinity stress were detected with LOD > 3, out of which 28 QTLs that explained from 5.9 to 30.0% phenotypic variation were found to be significant based on permutation test. Three major QTL clusters were found on chromosomes 2 (RM423–RM174), 4 (RM551–RM518) and 6 (RM20224–RM528) for multiple traits under salinity stress. Both parental lines contributed additively for QTLs identified for the yield components. A majority of the QTLs detected in our study are reported for the first time for reproductive stage salinity stress. Fine-mapping of selected putative QTLs will be the next step to facilitate marker-assisted backcrossing and to detect useful genes for salinity tolerance at the reproductive stage in rice.     

Potassium (K) effects and QTL mapping for K efficiency traits at seedling and adult stages in wheat

Aims

Potassium (K) is one of the most important mineral nutrients limiting plant growth in agricultural systems. This study investigated the effects of low-K treatments and detected quantitative trait loci (QTLs) for K efficiency traits at the seedling and adult stages of wheat.

Methods

Eleven seedling traits under a hydroponic culture trial with five K treatments and nine adult traits in a pot trial and a field trial with three K treatments were investigated using a set of wheat recombinant inbred lines (RILs).

Results

Values of most of the seedling and adult traits decreased with decreasing K supply, but the K-use efficiency and ratio of dry weight between seedling roots and shoots (RSDW) increased. A total of 87 QTLs for seedling traits in the hydroponic culture trial and 51 and 29 QTLs for adult traits in the pot and field trials, respectively, were detected. We also identified 15 relatively high-frequency QTLs (RHF-QTLs) which can be detected in over half of the treatments and 21 QTL clusters which is defined as the co-location of QTLs for more than two traits.

Conclusions

K efficiency traits and the related QTLs of wheat were greatly affected by K treatments. Several relatively stable QTLs and important QTL clusters may be potential targets for marker-assisted selection for wheat nutrient efficiency.     

Quantitative Trait Loci Mapping for Leaf Length and Leaf Width in Rice cv. IR64 Derived Lines

The present study was conducted to identify quantitative trait loci (QTLs) for leaf size traits in IR64 introgression lines (INLs). For this purpose, selected F2 populations derived from crosses between recurrent parent IR64 and its derived INLs, unique for leaf length and leaf width, were used to confirm QTLs. A total of eight QTLs, mapped on three chromosomes, were identified for the four leaf size traits in six F2 populations. A QTL for leaf length, qLLnpt-1, in HKL69 was identified around simple sequence repeat (SSR) marker RM3709 on chromosome 1. Two QTLs for flag leaf length, qFLLnpt-2 and qFLLnpt-4, in HFG39 were indentified on chromosomes 2 and 4, respectively. For flag leaf width, a QTL, qFLWnpt-4, in HFG39 was identified around RM17483 on chromosome 4. While another QTL for flag leaf width, qFLWnpt-1, in HFG27 was identified around RM3252 on chromosome 1. A QTL for leaf width, qLWnpt-2, in HKL75 was identified around RM7451 on chromosome 2. For leaf width, two QTLs, qLWnpt-4a, qLWnpt-4b, in HKL48 and HKL99 were identified around RM7208 and RM6909, respectively on chromosome 4. Results from this study suggest the possibilities to use marker-assisted selection and pyramiding these QTLs to improve rice water productivity.     

Quantitative trait loci for rice yield-related traits using recombinant inbred lines derived from two diverse cultivars

The thousand-grain weight and spikelets per panicle directly contribute to rice yield. Heading date and plant height also greatly influence the yield. Dissection of genetic bases of yield-related traits would provide tools for yield improvement. In this study, quantitative trait loci (QTL) mapping for spikelets per panicle, thousand-grain weight, heading date and plant height was performed using recombinant inbred lines derived from a cross between two diverse cultivars, Nanyangzhan and Chuan7. In total, 20 QTLs were identified for four traits. They were located to 11 chromosomes except on chromosome 4. Seven and five QTLs were detected for thousand-grain weight and spikelets per panicle, respectively. Four QTLs were identified for both heading date and plant height. About half the QTLs were commonly detected in both years, 2006 and 2007. Six QTLs are being reported for the first time. Two QTL clusters were identified in regions flanked by RM22065 and RM5720 on chromosome 7 and by RM502 and RM264 on chromosome 8, respectively. The parent, Nanyangzhan with heavy thousand-grain weight, carried alleles with increased effects on all seven thousand-grain weight QTL, which explained why there was no transgressive segregation for thousand-grain weight in the population. In contrast, Chuan7 with more spikelets per panicle carried positive alleles at all five spikelets per panicle QTL except qspp5. Further work on distinction between pleiotropic QTL and linked QTL is needed in two yield-related QTL clusters.     

Fine Mapping QTL for Drought Resistance Traits in Rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) Using Bulk Segregant Analysis

Drought stress is a major limitation to rice (Oryza sativa L.) yields and its stability, especially in rainfed conditions. Developing rice cultivars with inherent capacity to withstand drought stress would improve rainfed rice production. Mapping quantitative trait loci (QTLs) linked to drought resistance traits will help to develop rice cultivars suitable for water-limited environments through molecular marker-assisted selection (MAS) strategy. However, QTL mapping is usually carried out by genotyping large number of progenies, which is labour-intensive, time-consuming and cost-ineffective. Bulk segregant analysis (BSA) serves as an affordable strategy for mapping large effect QTLs by genotyping only the extreme phenotypes instead of the entire mapping population. We have previously mapped a QTL linked to leaf rolling and leaf drying in recombinant inbred (RI) lines derived from two locally adapted indica rice ecotypes viz., IR20/Nootripathu using BSA. Fine mapping the QTL will facilitate its application in MAS. BSA was done by bulking DNA of 10 drought-resistant and 12 drought-sensitive RI lines. Out of 343 rice microsatellites markers genotyped, RM8085 co-segregated among the RI lines constituting the respective bulks. RM8085 was mapped in the middle of the QTL region on chromosome 1 previously identified in these RI lines thus reducing the QTL interval from 7.9 to 3.8 cM. Further, the study showed that the region, RM212–RM302–RM8085–RM3825 on chromosome 1, harbours large effect QTLs for drought-resistance traits across several genetic backgrounds in rice. Thus, the QTL may be useful for drought resistance improvement in rice through MAS and map-based cloning.     

QTLs mapping of morphological traits related to salt tolerance in <Emphasis Type="Italic">Medicago truncatula</Emphasis>

To understand the complex inheritance of tolerance to salt stress in Medicago truncatula, quantitative trait loci (QTLs) analysis was performed using a set of recombinant inbred lines (RILs) derived from a cross between the tolerant line Jemalong A17 and susceptible line F83005.5. The RILs and parental lines were grown in individual pots filled with sterilized sand in a greenhouse under 0 and 50 mM NaCl. Plants were harvested after a period of 60 days. Fourteen quantitative traits related to aerial and root growths were measured. Broad-sense heritability of measured traits ranged from 0.21 to 0.83 and from 0.05 to 0.62 in control and in salt-stressed conditions, respectively. Established correlations between measured traits are dependent on treatment effect. We identified and mapped 10 QTLs in control conditions and 19 in salt stress. No major QTL was identified indicating that tolerance to salt stress is governed by several genes with low effects. The QTLs detected under control and under salt-stressed conditions almost did not share the same map locations suggesting that the loci that are not stable across treatments reflect adaptation to this constraint. The maximum of QTLs was observed on the chromosome 8. The usefulness of these QTLs, identified in greenhouse conditions, for marker-assisted selection should therefore be evaluated under field conditions, and validated in other genetic backgrounds.     

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.     

Mapping QTLs for root morphology of a rice population adapted to rainfed lowland conditions

In the rainfed lowlands, rice ( Oryza sativa L.) develops roots under anaerobic soil conditions with ponded water, prior to exposure to water stress and aerobic soil conditions that arise later in the season. Constitutive root system development in anaerobic soil conditions has been reported to have a positive effect on subsequent expression of adaptive root traits and water extraction during progressive water stress in aerobic soil conditions. We examined quantitative trait loci (QTLs) for constitutive root morphology traits using a mapping population derived from a cross between two rice lines which were well-adapted to rainfed lowland conditions. The effects of phenotyping environment and genetic background on QTLs identification were examined by comparing the experimental data with published results from four other populations. One hundred and eighty-four recombinant inbred lines (RILs) from a lowland indica cross (IR58821/IR52561) were grown under anaerobic conditions in two experiments. Seven traits, categorized into three groups (shoot biomass, deep root morphology, root thickness) were measured during the tillering stage. Though parental lines showed consistent differences in shoot biomass and root morphology traits across the two seasons, genotype-by-environment interaction (GxE) and QTL-by-environment interaction were significant among the progeny. Two, twelve, and eight QTLs for shoot biomass, deep root morphology, and root thickness, respectively, were identified, with LOD scores ranging from 2.0 to 12.8. Phenotypic variation explained by a single QTL ranged from 6% to 30%. Only two QTLs for deep root morphology, in RG256-RG151 in chromosome 2 and in PC75M3-PC11M4 in chromosome 4, were identified in both experiments. Comparison of positions of QTLs across five mapping populations (the current population plus populations from four other studies) revealed that these two QTLs for deep root morphology were only identified in populations that were phenotyped under anaerobic conditions. Fourteen and nine chromosome regions overlapped across different populations as putative QTLs for deep root morphology and root thickness, respectively. PC41M2-PC173M5 in chromosome 2 was identified as an interval that had QTLs for deep root morphology in four mapping populations. The PC75M3-PC11M4 interval in chromosome 4 was identified as a QTL for root thickness in three mapping populations with phenotypic variation explained by a single QTL consistently as large as 20-30%. Three QTLs for deep root morphology were found only in japonica/indica populations but not in IR58821/IR52561. The results identifying chromosome regions that had putative QTLs for deep root morphology and root thickness over different mapping populations indicate potential for marker-assisted selection for these traits.     

Genetic analysis of potassium use efficiency in Brassica oleracea

MethodsGenetic variation in [K]_shoot was estimated using a structured diversity foundation set (DFS) of 376 accessions and in 74 commercial genotypes grown in glasshouse and field experiments that included phosphorus (P) supply as a treatment factor. Chromosomal quantitative trait loci (QTL) associated with [K]_shoot and KUpE were identified using a genetic mapping population grown in the glasshouse and field. Putative QTL were tested using recurrent backcross substitution lines in the glasshouse.ConclusionsThere is sufficient genetic variation in B. oleracea to breed for both KUtE and KUpE. However, as QTL associated with these traits differ between glasshouse and field environments, marker-assisted breeding programmes must consider carefully the conditions under which the crop will be grown.Key words: Arabidopsis, Brassica oleracea, genetics, potassium (K), potassium use efficiency (KUE), quantitative trait loci (QTL), shoot     

Using chromosome introgression lines to map quantitative trait loci for photosynthesis parameters in rice (Oryza sativa L.) leaves under drought and well-watered field conditions

Photosynthesis is fundamental to biomass production, but sensitive to drought. To understand the genetics of leaf photosynthesis, especially under drought, upland rice cv. Haogelao, lowland rice cv. Shennong265, and 94 of their introgression lines (ILs) were studied at flowering and grain filling under drought and well-watered field conditions. Gas exchange and chlorophyll fluorescence measurements were conducted to evaluate eight photosynthetic traits. Since these traits are very sensitive to fluctuations in microclimate during measurements under field conditions, observations were adjusted for microclimatic differences through both a statistical covariant model and a physiological approach. Both approaches identified leaf-to-air vapour pressure difference as the variable influencing the traits most. Using the simple sequence repeat (SSR) linkage map for the IL population, 1-3 quantitative trait loci (QTLs) were detected per trait-stage-treatment combination, which explained between 7.0% and 30.4% of the phenotypic variance of each trait. The clustered QTLs near marker RM410 (the interval from 57.3?cM to 68.4?cM on chromosome 9) were consistent over both development stages and both drought and well-watered conditions. This QTL consistency was verified by a greenhouse experiment under a controlled environment. The alleles from the upland rice at this interval had positive effects on net photosynthetic rate, stomatal conductance, transpiration rate, quantum yield of photosystem II (PSII), and the maximum efficiency of light-adapted open PSII. However, the allele of another main QTL from upland rice was associated with increased drought sensitivity of photosynthesis. These results could potentially be used in breeding programmes through marker-assisted selection to improve drought tolerance and photosynthesis simultaneously.     

Analysis of factors influencing milling yield and their association to other traits by QTL analysis in two hexaploid oat populations

Milling yield, or the grain weight from which 100 kg of rolled groats is obtained upon milling, is an important quality characteristic of cultivated oat (Avena sativa L.). Kernel morphology and the groat (caryopsis) percentage of the whole kernel including hull are factors that influence milling yield. We mapped QTLs for kernel area, kernel length, kernel width, and groat percentage in two populations of 137 recombinant inbred lines by RFLP and AFLP analysis to evaluate the prospects of marker-assisted selection (MAS). Phenotypic correlations between kernel morphology traits and groat percentage were not significant. For kernel morphology traits and groat percentage, one to five QTLs were detected, explaining 7.0–60.7% of the total phenotypic variance depending on the trait. One QTL for kernel length in each population and one QTL for kernel width in one population were found at the same location as a QTL for groat percentage, indicating that a change in kernel size or shape could have an influence on groat percentage. The positions and effects of QTLs for kernel morphology and groat percentage were compared to QTLs detected previously for chemical grain composition (oil andβ-glucanconcentration) and agronomic traits to evaluate the selection response on these traits through MAS. Several regions of the oat genome were identified that contained clusters of QTLs influencing two or more traits. While the allele from one parent at a QTL could simultaneously improve two or more traits in one population, it could have opposite effects on the same traits at another QTL or in the other population. Associations among traits were complex and will require careful consideration when employing QTL-marker associations in MAS to avoid negative selection response. Future research to discover candidate genes for those QTL clusters could provide information about trait associations and help in designing selection programs. Received: 17 February 2000 / Accepted: 27 October 2000     

两种供氮水平下水稻生长后期相关性状的QTL定位

以特青为母本与Lemont杂交,然后用特青为轮回亲本回交,建立特青背景下的染色体片段置换系（CSSL）群体。在正常和低氮条件下分别在生长后期对株高（PH）、单株穗数（PN）、叶绿素含量（CC）、地上部干物重（SDW）和单株籽粒产量（YD）等性状进行了QTL分析,共检测到31个QTL。其中在正常供氮水平下控制PH、PN、CC、SDW和YD的QTL数目均为3个;在低氮水平下检测到5、4、5和2个影响PH、PN、CC和SDW的QTL,在低氮水平下没有检测到控制YD的位点。大部分QTL集中在第2、3、7、11和12染色体上,影响不同性状或在两种供氮水平下影响同一性状的QTL在染色体上成串或成簇分布。其中RM30-RM439、RM18-RM478、RM309-RM270、RM235-RM17等区域同时检测到控制两个以上性状的QTL,表现出明显的一因多效现象。推测仅在低氮水平下检测到的QTL可能跟水稻对低氮胁迫耐性有一定的关联。     

Identification of Related QTLs at Late Developmental Stage in Rice (Oryza sativa L.) Under Two Nitrogen Levels

QTL underlying related traits at the late developmental stage under two different nitrogen levels were investigated in rice using a population of chromosome segment substitution lines (CSSL) derived from a cross between Teqing and Lemont. A total of 31 QTLs referring 5 traits, that is, plant height (PH), panicle number per plant (PN), chlorophyll content (CC), shoot dry weight (SDW) and grain yield per plant (YD), were detected. Under normal N level, 3 QTLs were detected for each trait, while under low N level, 5,4, 5 and 2 QTLs were detected for PH, PN, CC and SDW respectively. Most of the QTLs were located on chromosome 2, 3, 7, 11 and 12. QTLs controlling different traits or the same trait under different N levels were mapped on the same or adjacent intervals, forming several clusters in rice chromosomes. More than two traits were controlled by QTLs on one of four intervals (RM30-RM439, RM18-RM478, RM309-RM270, and RM235-RM17), suggesting that there were some pleiotropic effects. It was supposed that some QTLs only detected at low N level might be associated with the ability to tolerate the low N stress in rice.     

QTL mapping of bread wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.) grown under controlled conditions of an agroecobiological testing ground

To determine the effects of physiological and genetic interaction between the genotype and environment, QTL (quantitative trait loci) mapping of valuable traits of bread wheat (Triticum aestivum L.) manifesting under controlled conditions of an agroecobiological testing ground has been first carried out. In the course of two experiments, differing from each other only by temperature and illumination regimes and providing the strict control and invariability of other growing parameters, 99 QTLs determining 30 different agronomically important traits have been identified. According to the results of the QTL mapping and a single-factor ANOVA, changes in the temperature and illumination regimes did not influence 21 of 30 studied traits, which remained stable in their manifestation; only nine traits varied under these conditions, which indicates that their manifestation is dependent on changes in these environmental factors. Both statistical approaches used in this study demonstrated complementary results; for each of them, the maximum likelihood criterion was used, statistical significance was determined, and significance of results was evaluated. The significance of a correlation between the identified QTLs and the polymorphism of individual traits studied was assessed using the threshold value of LOD (logarithm of odds) score. In addition, QTL analysis allowed a block structure of the T. aestivum genome to be revealed, the percentage of a phenotypic variability determined by each of the identified QTLs to be calculated, and the determination of which of the parents donated individual QTL alleles. The obtained results can be used for the further study of the physiological and genetic mechanisms of realization of traits evaluated within the framework of the “genotype–environment” interaction and also for the marker-assisted breeding of wheat.     

Marker-assisted selection to introgress rice QTLs controlling root traits into an Indian upland rice variety

A marker-assisted back-crossing (MABC) breeding programme was conducted to improve the root morphological traits, and thereby drought tolerance, of the Indian upland rice variety, Kalinga III. This variety, the recurrent parent in the MABC, had not previously been used for quantitative trait locus (QTL) mapping. The donor parent was Azucena, an upland japonica variety from Philippines. Five segments on different chromosomes were targeted for introgression; four segments carried QTLs for improved root morphological traits (root length and thickness) and the fifth carried a recessive QTL for aroma. Some selection was made at non-target regions for recurrent parent alleles. We describe the selection made in three backcross (BC) generations and two further crosses between BC₃ lines to pyramid (stack) all five target segments. Pyramids with four root QTLs were obtained in eight generations, completed in 6 years using 3,000 marker assays in a total of 323 lines. Twenty-two near-isogenic lines (NILs) were evaluated for root traits in five field experiments in Bangalore, India. The target segment on chromosome 9 (RM242-RM201) significantly increased root length under both irrigated and drought stress treatments, confirming that this root length QTL from Azucena functions in a novel genetic background. No significant effects on root length were found at the other four targets. Azucena alleles at the locus RM248 (below the target root QTL on chromosome 7) delayed flowering. Selection for the recurrent parent allele at this locus produced early-flowering NILs that were suited for upland environments in eastern India.     

QTL mapping for seedling traits in wheat grown under varying concentrations of N,P and K nutrients

Nutrient use efficiency (NuUE), comprising nutrient uptake and utilization efficiency, is regarded as one of the most important factors for wheat yield. In the present study, six morphological, nine nutrient content and nine nutrient utilization efficiency traits were investigated at the seedling stage using a set of recombinant inbred lines (RILs), under hydroponic culture of 12 treatments including single nutrient levels and two- and three-nutrient combinations treatments of N, P and K. For the 12 designed treatments, a total of 380 quantitative trait loci (QTLs) on 20 chromosomes for the 24 traits were detected. Of these, 87, 149 and 144 QTLs for morphological, nutrient content and nutrient utilization efficiency traits were found, respectively. Using the data of the average value (AV) across 12 treatments, 70 QTLs were detected for 23 traits. Most QTLs were located in new marker regions. Twenty-six important QTL clusters were mapped on 13 chromosomes, 1A, 1B, 1D, 2B, 3A, 3B, 4A, 4B, 5D, 6A, 6B, 7A and 7B. Of these, ten clusters involved 147 QTLs (38.7%) for investigated traits, indicating that these 10 loci were more important for the NuUE of N, P and K. We found evidence for cooperative uptake and utilization (CUU) of N, P and K in the early growth period at both the phenotype and QTL level. The correlation coefficients (r) between nutrient content and nutrient utilization efficiency traits for N, P and K were almost all significantly positive correlations. A total of 32 cooperative CUU loci (L1–L32) were found, which included 190 out of the 293 QTLs (64.8%) for the nutrient uptake and utilization efficiency traits, indicating that the CUU-QTLs were common for N, P and K. The CUU-QTLs in L3, L7, L16 and L28 were relatively stable. The CUU-QTLs may explain the CUU phenotype at the QTL level.     

Identification of QTLs influencing agronomic traits in <Emphasis Type="Italic">Miscanthus sinensis</Emphasis> Anderss. I. Total height,flag-leaf height and stem diameter

We have developed the first quantitative trait locus (QTL) analyses for agronomic traits in a cross between F(1.1) (P1) and F(1.7) (P7) entries of Miscanthus sinensis Anderss. Both lines are offspring of the cross between MS-90-2 and MS-88-110. A map based on random amplified polymorphic DNA markers previously constructed was used to perform the QTL analyses. This map was developed using a new mapping strategy that has been designated offspring cross. Eleven QTLs were detected for height, panicle height and diameter using the programme mapqtl 4.0 and the multiple QTL method. QTL significance was determined using several analyses, including Kruskal-Wallis analyses, empirical determination of LOD critical values using permutation tests, QTLs validation with field data over 2 years and co-localization of QTLs for correlated traits. The results obtained could be the first step in developing a marker-assisted selection programming in this species for biomass production.     

Drought stress and tropical maize: QTL-by-environment interactions and stability of QTLs across environments for yield components and secondary traits

A recombinant inbred line (RIL) population was evaluated in seven field experiments representing four environments: water stress at flowering (WS) and well-watered (WW) conditions in Mexico and Zimbabwe. The QTLs were identified for each trait in each individual experiment (single-experiment analysis) as well as per environment, per water regime across locations and across all experiments (joint analyses). For the six target traits (male flowering, anthesis-to-silking interval, grain yield, kernel number, 100-kernel fresh weight and plant height) 81, 57, 51 and 34 QTLs were identified in the four step-wise analyses, respectively. Despite high values of heritability, the phenotypic variance explained by QTLs was reduced, indicating epistatic interactions. About 80, 60 and 6% of the QTLs did not present significant QTL-by-environment interactions (QTL × E) in the joint analyses per environment, per water regime and across all experiments. The expression of QTLs was quite stable across years at a given location and across locations under the same water regime. However, the stability of QTLs decreased drastically when data were combined across water regimes, reflecting a different genetic basis of the target traits in the drought and well-watered trials. Several clusters of QTLs for different traits were identified by the joint analyses of the WW (chromosomes 1 and 8) and WS (chromosomes 1, 3 and 5) treatments and across water regimes (chromosome 1). Those regions are clear targets for future marker-assisted breeding, and our results confirm that the best approach to breeding for drought tolerance includes selection under water stress.     

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.