Genetic analysis of leaf morphology underlying the plant density response by QTL mapping in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

Maize yield increase has been strongly linked to plant population densities over time with changes in plant architecture, but the genetic basis for the plant architecture response to plant density is unknown, as is its stability across environments. To elucidate the genetic basis of the plant architecture response to density in maize, we mapped quantitative trait loci (QTLs) for leaf morphology-related traits in four sets of recombinant inbred line (RIL) populations under two plant density conditions. Forty-five QTLs for six traits were detected in both high and low plant density conditions. Thirty-seven QTLs were only detected when grown under high plant density, and 34 QTLs were only detected when grown under low plant density. Twenty-two meta-QTLs (mQTLs) were identified by meta-analysis, and mQTL1-1, mQTL3-2 and mQTL8 were identified when grown under high and low plant densities, with R ² of some initial QTLs > 10 %, suggesting the mQTLs might be hot spots of the important QTLs for the related traits under planting density stress conditions. The results presented here provide useful information for further research and the marker-assisted selection of varieties targeting increased plant density and will help to reveal the molecular mechanisms related to leaf morphology in response to density.     

Genomic dissection of drought resistance in durum wheat × wild emmer wheat recombinant inbreed line population

Drought is the major factor limiting wheat productivity worldwide. The gene pool of wild emmer wheat, Triticum turgidum ssp. dicoccoides , harbours a rich allelic repertoire for morpho-physiological traits conferring drought resistance. The genetic and physiological bases of drought responses were studied here in a tetraploid wheat population of 152 recombinant inbreed lines (RILs), derived from a cross between durum wheat (cv. Langdon) and wild emmer (acc# G18-16), under contrasting water availabilities. Wide genetic variation was found among RILs for all studied traits. A total of 110 quantitative trait loci (QTLs) were mapped for 11 traits, with LOD score range of 3.0–35.4. Several QTLs showed environmental specificity, accounting for productivity and related traits under water-limited (20 QTLs) or well-watered conditions (15 QTLs), and in terms of drought susceptibility index (22 QTLs). Major genomic regions controlling productivity and related traits were identified on chromosomes 2B, 4A, 5A and 7B. QTLs for productivity were associated with QTLs for drought-adaptive traits, suggesting the involvement of several strategies in wheat adaptation to drought stress. Fifteen pairs of QTLs for the same trait were mapped to seemingly homoeologous positions, reflecting synteny between the A and B genomes. The identified QTLs may facilitate the use of wild alleles for improvement of drought resistance in elite wheat cultivars.     

Genetic Control of the Leaf Angle and Leaf Orientation Value as Revealed by Ultra-High Density Maps in Three Connected Maize Populations

Plant architecture is a key factor for high productivity maize because ideal plant architecture with an erect leaf angle and optimum leaf orientation value allow for more efficient light capture during photosynthesis and better wind circulation under dense planting conditions. To extend our understanding of the genetic mechanisms involved in leaf-related traits, three connected recombination inbred line (RIL) populations including 538 RILs were genotyped by genotyping-by-sequencing (GBS) method and phenotyped for the leaf angle and related traits in six environments. We conducted single population quantitative trait locus (QTL) mapping and joint linkage analysis based on high-density recombination bin maps constructed from GBS genotype data. A total of 45 QTLs with phenotypic effects ranging from 1.2% to 29.2% were detected for four leaf architecture traits by using joint linkage mapping across the three populations. All the QTLs identified for each trait could explain approximately 60% of the phenotypic variance. Four QTLs were located on small genomic regions where candidate genes were found. Genomic predictions from a genomic best linear unbiased prediction (GBLUP) model explained 45±9% to 68±8% of the variation in the remaining RILs for the four traits. These results extend our understanding of the genetics of leaf traits and can be used in genomic prediction to accelerate plant architecture improvement.     

Wide range QTL analysis for complex architectural traits in a 1-year-old apple progeny.

The present study aimed at investigating the genetic determinisms of architectural traits in a 1-year-old apple (Malus x domestica Borkh.). F1 progeny. A precise phenotyping including both tree topology and geometry was performed on 123 offspring. For a wide range of developmental traits, broad-sense heritability was estimated and quantitative trait loci (QTLs) were investigated. Several loci controlling geometry were identified (i) for integrated traits, such as tree surface and volume; (ii) for traits related to the form of long sylleptic axillary shoots (LSAS), such as bending and basis angle; and (iii) for traits of finer components, such as internode length of the trunk and LSAS. Considering topology, 4 QTLs were mapped for the total number of sylleptic branching in the tree, suggesting a strong and complex genetic control that was analysed through colocalisations between QTLs mapped for the different shoot types (long, medium, short). Two QTLs were also mapped for a phenological trait (date of bud break). When several QTLs were detected for a trait, a linear model was built to test epistatic effects and estimate the whole percentage of variability explained. The discussion focuses on particular colocalisations and on the relevance of traits to further tree development.     

QTL analysis of morphological traits in a tomato recombinant inbred line population.

Quantitative trait loci (QTLs) influencing morphological traits were identified by restriction fragment length polymorphism (RFLP) analysis in a population of recombinant inbred lines (RILs) derived from a cross of the cultivated tomato Lycopersicon esculentum with a related wild species, Lycopersicon cheesmanii. One hundred and thirty-two RFLP loci spaced throughout the tomato genome were used as DNA probes on genomic DNA from 97 RIL families. Morphological traits, including plant height, plant fresh mass, number of branches, number of nodes, first flower-bearing node, and leaf length, were evaluated in two controlled environment trials in 1992 and 1993. QTLs were detected via regression analyses at multiple marker loci for each morphological trait. A total of 41 markers were significantly associated with the traits examined. Large additive effects were measured at many of these loci. QTLs for multiple traits were detected on chromosomes 3 (TG74) and 4 (CT188), suggesting the possible association of these chromosome segments with genes controlling growth and development in tomato. These chromosomal regions were also associated with multiple morphological traits in a L. esculentum x Lycopersicon pennellii cross. A total of 13% of the QTLs identified for traits common to both studies occupied similar map positions.     

Genetic variation for N-remobilization and postsilking N-uptake in a set of maize recombinant inbred lines. 3. QTL detection and coincidences

The objective of this study was to map and characterize QTLs for traits related to nitrogen utilization efficiency (NUE), grain N yield, N-remobilization and post-silking N-uptake. Furthermore, to examine whether QTLs detected with recombinant inbred lines (RILs) crossed to a tester are common to those detected with line per se evaluation, both types of evaluations were developed from the same set of RILs. The material was studied over two years at high N-input, and one year at low N-input. We used (15)N-labelling to evaluate with accuracy the proportion of N remobilized from stover to kernels and the proportion of postsilking N-uptake allocated to kernels. With 59 traits studied in three environments, 608 QTLs were detected. Using a method of QTL clustering, 72 clusters were identified, with few QTLs being specific to one environment or to the type of plant material (lines or testcross families). However, considering each trait separately, few QTLs were common to both line per se and testcross evaluation. This shows that genetic variability is expressed differently according to the type of progeny. Studies of coincidences among QTLs within the clusters showed an antagonism between N-remobilization and N-uptake in several QTL-clusters. QTLs for N-uptake, root system architecture and leaf greenness coincided positively in eight clusters. QTLs for remobilization mainly coincided in clusters with QTLs for leaf senescence. On the whole, sign of coincidences between QTLs underlined the role of a "stay-green" phenotype in favouring N-uptake capacity, and thus grain yield and N grain yield.     

Identification of QTLs for Yield and Associated Traits in F₂ Population of Rice

Identification of quantitative trait loci (QTLs) controlling yield and yield-related traits in rice was performed in the F₂ mapping population derived from parental rice genotypes DHMAS and K343. A total of 30 QTLs governing nine different traits were identified using the composite interval mapping (CIM) method. Four QTLs were mapped for number of tillers per plant on chromosomes 1 (2 QTLs), 2 and 3; three QTLs for panicle number per plant on chromosomes 1 (2 QTLs) and 3; four QTLs for plant height on chromosomes 2, 4, 5 and 6; one QTL for spikelet density on chromosome 5; four QTLs for spikelet fertility percentage (SFP) on chromosomes 2, 3 and 5 (2 QTLs); two QTLs for grain length on chromosomes 1 and 8; three QTLs for grain width on chromosomes1, 3 and 8; three QTLs for 1000-grain weight (TGW) on chromosomes 1, 4 and 8 and six QTLs for yield per plant (YPP) on chromosomes 2 (3 QTLs), 4, 6 and 8. Most of the QTLs were detected on chromosome 2, so further studies on chromosome 2 could help unlock some new chapters of QTL for this cross of rice variety. Identified QTLs elucidating high phenotypic variance can be used for marker-assisted selection (MAS) breeding. Further, the exploitation of information regarding molecular markers tightly linked to QTLs governing these traits will facilitate future crop improvement strategies in rice.     

Genetic mapping of QTLs for sugar-related traits in a RIL population of Sorghum bicolor L. Moench

The productivity of sorghum is mainly determined by quantitative traits such as grain yield and stem sugar-related characteristics. Substantial crop improvement has been achieved by breeding in the last decades. Today, genetic mapping and characterization of quantitative trait loci (QTLs) is considered a valuable tool for trait enhancement. We have investigated QTL associated with the sugar components (Brix, glucose, sucrose, and total sugar content) and sugar-related agronomic traits (flowering date, plant height, stem diameter, tiller number per plant, fresh panicle weight, and estimated juice weight) in four different environments (two locations) using a population of 188 recombinant inbred lines (RILs) from a cross between grain (M71) and sweet sorghum (SS79). A genetic map with 157 AFLP, SSR, and EST-SSR markers was constructed, and several QTLs were detected using composite interval mapping (CIM). Further, additive × additive interaction and QTL × environmental interaction were estimated. CIM identified more than five additive QTLs in most traits explaining a range of 6.0–26.1% of the phenotypic variation. A total of 24 digenic epistatic locus pairs were identified in seven traits, supporting the hypothesis that QTL analysis without considering epistasis can result in biased estimates. QTLs showing multiple effects were identified, where the major QTL on SBI-06 was significantly associated with most of the traits, i.e., flowering date, plant height, Brix, sucrose, and sugar content. Four out of ten traits studied showed a significant QTL × environmental interaction. Our results are an important step toward marker-assisted selection for sugar-related traits and biofuel yield in sorghum.     

Genetic mapping of yield traits using RIL population derived from Fuchuan Dahuasheng and ICG6375 of peanut (<Emphasis Type="Italic">Arachis hypogaea</Emphasis> L.)

The genetic architecture determinants of yield traits in peanut (Arachis hypogaea L.) are poorly understood. In the present study, an effort was made to map quantitative trait loci (QTLs) for yield traits using recombinant inbred lines (RIL). A genetic linkage map was constructed containing 609 loci, covering a total of 1557.48 cM with an average distance of 2.56 cM between adjacent markers. The present map exhibited good collinearity with the physical map of diploid species of Arachis. Ninety-two repeatable QTLs were identified for 11 traits including height of main stem, total branching number, and nine pod- and seed-related traits. Of the 92 QTLs, 15 QTLs were expressed across three environments and 65 QTLs were newly identified. Twelve QTLs for the height of main stem and the pod- and seed-related traits explaining more than 10 % of phenotypic variation showed a great potential for marker-assisted selection in improving these traits. 相似文献   

Genetic mapping in maize with hybrid progeny across testers and generations: plant height and flowering

DNA markers were used to identify quantitative trait loci (QTLs) for plant height, ear height, and three flowering traits in hybrid progeny of two generations (F_2:3, F_6:8) of lines from a Mo17×H99 maize population. For both generations, testcross (TC) progeny were developed by crossing the lines to three inbred testers (B91, A632, B73). The hybrid progeny from the two generations were evaluated at the same locations but in different years as per an early generation testing program. QTLs were identified within each TC population and for mean testcross (MTC) performance. Overall, more QTLs were detected in the F_6:8 than the F_2:3 generation. Totalled over all five traits, 41 (B91) to 69% (B73) of the QTLs for tester effects and 67% of the QTLs for MTC detected in the F_2:3 generation were verified in the F_6:8 generation. Although differences in relative rank of the QTL effects across generations were observed, especially for the flowering traits, parental contributions were nearly always consistent. Several (8–11) QTLs were identified with effects for all three tester populations and for all traits except the anthesis-silk interval, which had only two such regions. Over all five traits, previous evaluations in this population identified 26 QTLs with consistent effects for two (F_2:3, F_6:8) inbred-progeny evaluations, and 20 (77%) were also associated with MTC in at least one of the generations evaluated herein. In all instances of common inbred and TC QTLs, parental contributions were the same. Received: 26 November 1999 / Accepted: 18 April 2000     

Mapping QTLs for seedling characteristics under different water supply conditions in rice (Oryza sativa)

A greater understanding of the genetics of responses to water deficit/drought may be helpful in improving water-deficit resistance in the early stages of growth in rice. A recombinant inbred population derived from a cross between Zhenshan 97 and Minghui 63 was grown in hydroponic culture to characterize the responses of seedlings to water deficit imposed by PEG 6000 and to identify quantitative trait loci (QTLs) for seedling characteristics under both well-watered and water-deficit conditions. Generally, the two parents showed significant differences in plant height (PH), maximum root length (MRL), shoot fresh weight (SFW), root fresh weight (RFW), number of roots and root:shoot ratio based on fresh weight under both well-watered and water-deficit conditions. For two parents, PH and SFW were significantly inhibited under water deficit. However, the other four traits had larger values under water deficit. Among 26 and 34 QTLs detected for the six traits studied under the well-watered and water-deficit conditions, respectively, a total of 14 QTLs for SFW, PH, RFW and MRL (23% of total QTLs detected) were detected in similar or tight linkage regions in both conditions. Among 11 intervals on 7 chromosomes identified to harbor multiple QTLs, 8 intervals were found to affect related traits under the two water supply conditions and 3 intervals were observed to be water supply-specific regions and had effects only under well-watered conditions, suggesting that water supply-specific regions or QTLs may be closely associated with the responses of lines to water deficit in the study. Several regions for the traits studied were also found to affect the root-related traits in previous studies and might be used in marker-assisted selection for drought-resistant rice in breeding programs.     

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.     

Natural variation for carbohydrate content in Arabidopsis. Interaction with complex traits dissected by quantitative genetics

Besides being a metabolic fuel, carbohydrates play important roles in plant growth and development, in stress responses, and as signal molecules. We exploited natural variation in Arabidopsis (Arabidopsis thaliana) to decipher the genetic architecture determining carbohydrate content. A quantitative trait locus (QTL) approach in the Bay-0 x Shahdara progeny grown in two contrasting nitrogen environments led to the identification of 39 QTLs for starch, glucose, fructose, and sucrose contents representing at least 14 distinct polymorphic loci. A major QTL for fructose content (FR3.4) and a QTL for starch content (ST3.4) were confirmed in heterogeneous inbred families. Several genes associated with carbon (C) metabolism colocalize with the identified QTL. QTLs for senescence-related traits, and for flowering time, water status, and nitrogen-related traits, previously detected with the same genetic material, colocalize with C-related QTLs. These colocalizations reflect the complex interactions of C metabolism with other physiological processes. QTL fine-mapping and cloning could thus lead soon to the identification of genes potentially involved in the control of different connected physiological processes.     

QTL mapping of root traits in a doubled haploid population from a cross between upland and lowland japonica rice in three environments

To genetically dissect drought resistance associated with japonica upland rice, we evaluated a doubled haploid (DH) population from a cross between two japonica cultivars for seven root traits under three different growing conditions (upland, lowland and upland in PVC pipe). The traits included basal root thickness (BRT), total root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW), ratio of root fresh weight to shoot fresh weight (RFW/SFW) and ratio of root dry weight to shoot dry weight (RDW/SDW). The BRT was significantly correlated with the index of drought resistance, which was defined as the ratio of yield under the stress of the upland condition to that under the normal lowland condition. A complete genetic linkage map with 165 molecular markers covering 1,535 cM was constructed. Seven additive quantitative trait loci (QTLs) and 15 pairs of epistatic loci for BRT and RN were identified under upland and lowland conditions, and 12 additive QTLs and 17 pairs of epistatic QTLs for BRT, RN, MRL, RFW, RFW/SFW and RDW/SDW were identified under the PVC pipe condition. Four additive QTLs and one pair of epistatic QTLs controlling IDR were also found. These QTLs individually explained up to 25.6% of the phenotypic variance. QTL × environment (Q × E) interactions were detected for all root traits, and the contributions of these interactions ranged from 1.1% to 19.9%. Five co-localized QTLs controlling RFW and RDW, RFW/SFW, RDW/SDW and IDR, BRT and RN, RN, MRL and IDR were found. Four types of QTLs governing BRT and RN were classified by their detection in the upland and lowland conditions. Some common QTLs for root traits across different backgrounds were also revealed. These co-localized QTLs and common QTLs will facilitate marker-assisted selection for root traits in rice breeding programs.     

Mapping QTLs of root morphological traits at different growth stages in rice

Roots are a vital organ for absorbing soil moisture and nutrients and influence drought resistance. The identification of quantitative trait loci (QTLs) with molecular markers may allow the estimation of parameters of genetic architecture and improve root traits by molecular marker-assisted selection (MAS). A mapping population of 120 recombinant inbred lines (RILs) derived from a cross between japonica upland rice 'IRAT109' and paddy rice 'Yuefu' was used for mapping QTLs of developmental root traits. All plant material was grown in PVC-pipe. Basal root thickness (BRT), root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW) and root volume (RV) were phenotyped at the seedling (I), tillering (II), heading (III), grain filling (IV) and mature (V) stages, respectively. Phenotypic correlations showed that BRT was positively correlated to MRL at the majority of stages, but not correlated with RN. MRL was not correlated to RN except at the seedling stage. BRT, MRL and RN were positively correlated to RFW, RDW and RV at all growth stages. QTL analysis was performed using QTLMapper 1.6 to partition the genetic components into additive-effect QTLs, epistatic QTLs and QTL-by-year interactions (Q x E) effect. The results indicated that the additive effects played a major role for BRT, RN and MRL, while for RFW, RDW and RV the epistatic effects showed an important action and Q x E effect also played important roles in controlling root traits. A total of 84 additive-effect QTLs and 86 pairs of epistatic QTLs were detected for the six root traits at five stages. Only 12 additive QTLs were expressed in at least two stages. This indicated that the majority of QTLs were developmental stage specific. Two main effect QTLs, brt9a and brt9b, were detected at the heading stage and explained 19% and 10% of the total phenotypic variation in BRT without any influence from the environment. These QTLs can be used in breeding programs for improving root traits.     

Comparative study of QTLs for agronomic traits of riceOriza sativa L.) between salt stress and nonstress environment

Genotype-by-environment interactions (GxE) are commonly observed for quantitative traits. In the present study, a doubled haploid (DH) population and its genetic linkage map were used to comparatively study QTLs in salt stress and nonstress environments. A total of 24 QTLs were detected for five agronomic traits, which were distributed on all the chromosomes except 9 and 11. Under the salt stress, nine (37.5%) QTLs were detected, including one for 1 000-grain weight (GW), two for heading date (HD), one for plant height (PH), two for grains per panicle (GPP), and three for effective tillers (ET), while in the nonstress environment, 17 QTLs (70.8%) were detected, including five for GW, six for HD, three for PH, two for GPP, and one for ET. Two QTLs (8.3%) were consistently detected in both environments. One was identified on chromosome 4 for HD and the other on Chr.6 for GPP. Furthermore, three regions carrying multiple QTLs were identified on chromosomes 1, 4 and 8 respectively. For example, on chromosome 8, three QTLs for HD, GW and PH, respectively were identified between RG885-GA408 in nonstress environment, but not in the stress environment. The comparative study of QTLs detected in extremely different (salt stress and nonstress) environments revealed that there existed several QTLs for important agronomic traits on chromosome 8 which were affected significantly by salt stress.     

Deciphering genetic basis of developmental and agronomic traits by integrating high-throughput optical phenotyping and genome-wide association studies in wheat

Dissecting the genetic basis of complex traits such as dynamic growth and yield potential is a major challenge in crops. Monitoring the growth throughout growing season in a large wheat population to uncover the temporal genetic controls for plant growth and yield-related traits has so far not been explored. In this study, a diverse wheat panel composed of 288 lines was monitored by a non-invasive and high-throughput phenotyping platform to collect growth traits from seedling to grain filling stage and their relationship with yield-related traits was further explored. Whole genome re-sequencing of the panel provided 12.64 million markers for a high-resolution genome-wide association analysis using 190 image-based traits and 17 agronomic traits. A total of 8327 marker-trait associations were detected and clustered into 1605 quantitative trait loci (QTLs) including a number of known genes or QTLs. We identified 277 pleiotropic QTLs controlling multiple traits at different growth stages which revealed temporal dynamics of QTLs action on plant development and yield production in wheat. A candidate gene related to plant growth that was detected by image traits was further validated. Particularly, our study demonstrated that the yield-related traits are largely predictable using models developed based on i-traits and provide possibility for high-throughput early selection, thus to accelerate breeding process. Our study explored the genetic architecture of growth and yield-related traits by combining high-throughput phenotyping and genotyping, which further unravelled the complex and stage-specific contributions of genetic loci to optimize growth and yield in wheat.     

Comparative study of QTLs for agronomic traits of riceOriza sativa L.) between salt stress and nonstress environment

Genotype-by-environment interactions (GxE) are commonly observed for quantitative traits. In the present study, a doubled haploid (DH) population and its genetic linkage map were used to comparatively study QTLs in salt stress and nonstress environments. A total of 24 QTLs were detected for five agronomic traits, which were distributed on all the chromosomes except 9 and 11. Under the salt stress, nine (37.5%) QTLs were detected, including one for 1 000-grain weight (GW), two for heading date (HD), one for plant height (PH), two for grains per panicle (GPP), and three for effective tillers (ET), while in the nonstress environment, 17 QTLs (70.8%) were detected, including five for GW, six for HD, three for PH, two for GPP, and one for ET. Two QTLs (8.3%) were consistently detected in both environments. One was identified on chromosome 4 for HD and the other on Chr.6 for GPP. Furthermore, three regions carrying multiple QTLs were identified on chromosomes 1, 4 and 8 respectively. For example, on chromosome 8, three QTLs for HD, GW and PH, respectively were identified between RG885-GA408 in nonstress environment, but not in the stress environment. The comparative study of QTLs detected in extremely different (salt stress and nonstress) environments revealed that there existed several QTLs for important agronomic traits on chromosome 8 which were affected significantly by salt stress.     

Comparative study of QTLs for agronomic traits of rice (Oriza sativa L.) between salt stress and nonstress environment

Genotype-by-environment interactions (GxE) are commonly observed for quantitative traits. In the present study, a doubled haploid (DH) population and its genetic linkage map were used to comparatively study QTLs in salt stress and nonstress environments. A total of 24 QTLs were detected for five agronomic traits, which were distributed on all the chromosomes except 9 and 11. Under the salt stress, nine (37.5%) QTLs were detected, including one for 1 000-grain weight (GW), two for heading date (HD), one for plant height (PH), two for grains per panicle (GPP), and three for effective tillers (ET), while in the nonstress environment, 17 QTLs (70.8%) were detected, including five for GW, six for HD, three for PH, two for GPP, and one for ET. Two QTLs (8.3%) were consistently detected in both environments. One was identified on chromosome 4 for HD and the other on Chr.6 for GPP. Furthermore, three regions carrying multiple QTLs were identified on chromosomes 1, 4 and 8 respectively. For example, on chromosome     

Mapping quantitative trait loci for yield,yield components and morphological traits in an advanced backcross population between <Emphasis Type="Italic">Oryza rufipogon</Emphasis> and the <Emphasis Type="Italic">Oryza sativa</Emphasis> cultivar Jefferson

An advanced backcross population between an accession of Oryza rufipogon (IRGC 105491) and the U.S. cultivar Jefferson (Oryza sativa ssp. japonica) was developed to identify quantitative trait loci (QTLs) for yield, yield components and morphological traits. The genetic linkage map generated for this population consisted of 153 SSR and RFLP markers with an average interval size of 10.3 cM. Thirteen traits were examined, nine of which were measured in multiple environments. Seventy-six QTLs above an experiment-wise significance threshold of P<0.01 (corresponding to an interval mapping LOD>3.6 or a composite interval mapping LOD>3.9) were identified. For the traits measured in multiple environments, 47% of the QTLs were detected in at least two environments. The O. rufipogon allele was favorable for 53% of the yield and yield component QTLs, including loci for yield, grains per panicle, panicle length, and grain weight. Morphological traits related to the domestication process and/or weedy characteristics, including plant height, shattering, tiller type and awns, were found clustered on chromosomes 1 and 4. Comparisons to previous studies involving wild x cultivated crosses revealed O. rufipogon alleles with stable effects in multiple genetic backgrounds and environments, several of which have not been detected in studies between Oryza sativa cultivars, indicating potentially novel alleles from O. rufipogon. Some O. rufipogon-derived QTLs, however, were in similar regions as previously reported QTLs from Oryza sativa cultivars, providing evidence for conservation of these QTLs across the Oryza genus. In addition, several QTLs for grain weight, plant height, and flowering time were localized to putative homeologous regions in maize where QTLs for these traits have been previously reported, supporting the hypothesis of functional conservation of QTLs across the grasses.