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1.
Improvement of rice grain yield (YD) is an important goal in rice breeding. YD is determined by its related traits such as spikelet fertility (SF), 1,000-grain weight (TGW), and the number of spikelets per panicle (SPP). We previously mapped quantitative trait loci (QTLs) for SPP and TGW using the recombinant inbred lines (RILs) derived from the crosses between Minghui 63 and Teqing. In this study, four QTLs for SF and four QTLs for YD were detected in the RILs. Comparison of the locations of QTLs for these three yield-related traits identified one QTL cluster in the interval between RM3400 and RM3646 on chromosome 3. The QTL cluster contained three QTLs, SPP3a, SF3 and TGW3a, but no YD QTL was located there. To validate the QTL cluster, a BC4F2 population was obtained, in which SPP3a, SF3 and TGW3a were simultaneously mapped to the same region. SPP3a, SF3 and TGW3a explained 36.3, 29.5 and 59.0 % of phenotype variance with additive effect of 16.4 spikelets, 6 % SF and 1.8 g grain weight, respectively. In the BC4F2 population, though the region has opposite effects on TGW and SPP/SF, a YD QTL YD3 identified in this cluster region can increase 4.6 g grains per plant, which suggests this QTL cluster is a yield-enhancing QTL cluster and can be targeted to improve rice yield by marker aided selection.  相似文献   

2.
Nitrogen (N) is one of the most important plant nutrients, controlling growth and, ultimately, yield of a cultivar. Hordeum vulgare ssp. spontaneum, the wild barley progenitor of cultivated barley, is known to possess genes that can improve tolerance against biotic and abiotic stresses. A quantitative trait locus (QTL) study with two levels of N fertilization was conducted under glasshouse in order to locate wild barley alleles that improve N stress tolerance in the genetic background of an elite barley cultivar. For this, a set of 28 barley introgression lines (S42ILs), which originate from the cross ??Scarlett???×???ISR42-8??, was studied. The S42ILs, containing single or multiple wild barley introgressions, and ??Scarlett?? were evaluated in regard to a total of 15 traits, related to morphological parameters, grain parameters as well as to carbon (C) and N content parameters. A mixed model analysis and a subsequent Dunnett test was conducted to identify S42ILs that significantly deviate from the recurrent parent ??Scarlett??, either tested separately for each N level, or simultaneously across both N levels. In total, 65 QTLs were detected for the S42IL set. Most QTLs were found for chlorophyll content during heading (10 QTLs) and the fewest for C/N ratio of straw (1 QTL). The individual S42ILs possessed different numbers of QTLs. For S42IL-108, a maximum of eight QTLs were found whereas S42IL-145 did not show any significant difference from ??Scarlett??. Wild barley alleles revealed decreasing effects at 32 QTLs and increasing effects at 33 QTLs. Although 25 QTLs exhibited similar effects across both N levels, 18 and 22 QTLs exhibited effects that were only detected under N0 or N1, respectively. We, thus, conclude that it may be worth to select improved barley cultivars for N stress tolerance separately under low N fertilization, rather than extrapolating trait performances from experiments carried out under standard N fertilization conditions. A number of wild barley QTL alleles improved N stress tolerance. For example, a wild barley QTL allele on chromosome 4H, present in the Hsp introgression of S42IL-119, was associated with a 13.0?% increase of thousand grain weight across both N levels and a 20?% increase under low N supply. QTLs detected in the present study were compared with those of previous field studies of the same cross and with other QTL studies in barley and other small grains. Accordance between QTL studies (QTLs showing similar effects at the same map location) is documented and discussed. Based on our study, promising wild barley QTL alleles are available in S42ILs, which can be readily utilized to select for improved N use efficiency in barley breeding.  相似文献   

3.
The ability to detect quantitative trait loci (QTLs) in a bi-allelic population is often limited. The power of QTL detection and identification of the most beneficial allele at each QTL could be greatly improved by comparing QTLs among different populations derived from connecting multi-parents. In this study, three sets of connected recombinant inbred lines (RILs) derived from the crosses between Zhenshan 97 and Minghui 63 (PZM), Zhenshan 97 and Teqing (PZT), and Minghui 63 and Teqing (PMT), respectively, were used. QTL analyses for the number of spikelets per panicle (SPP) and 1,000-grain weight (TGW) were performed in PZT, and five SPP QTLs on chromosomes 1, 6, and 7 and two TGW QTLs on chromosome 1 were detected. QTL for SPP was also identified in PMT, and six QTLs were detected on chromosomes 1, 2, 3, 6, and 7 in this population. In an earlier study, we identified five SPP QTLs and four TGW QTLs in PMT and nine TGW QTLs in PZM. Comparison of the QTL mapping results of these two studies showed that one QTL was common to the three populations, 11 QTLs were detected in two populations, and six QTLs were found in only one population. Comparison of genetic effect and the action direction of the QTLs detected in the three populations showed that additive effects of QTLs estimated in different populations were also expressed additively among three parental alleles. Additive effects of SPP7a estimated in three near-isogenic line F2 populations supported this finding. Based on these results, we suggest that pyramiding the most beneficial alleles among the three parents could efficiently improve rice yield.  相似文献   

4.
Additive effects (A) and additive‐by‐environment interactions (A×E) for five rice yield components were analysed using 20 SSSLs under mixed linear model methodology. Thirty‐one QTLs were detected. Different yield components have different QTL‐by‐environment (Q×E) interaction patterns. No A×E interaction effects were detected for the four QTLs for panicle number (PN). Four QTLs detected for spikelets per panicle (SPP) had A×E interactions. Five of seven QTLs detected for grains per panicle (GPP), two of 10 QTLs detected for 1000‐grains weight (GWT) and three of six QTLs detected for seed set ratio (SSR) showed significant A×E interaction. Most of these QTLs were distributed in clusters across the genome. The complexity of linkage and pleiotropy of these QTLs plus environmental effect may result in the diversity of the yield phenotype in the SSSLs. Only S19 exhibited a significant increase in yield with a predicted gain by 281.58 kg ha?1. The results may be useful to design a better breeding strategy that takes advantage of QTL‐by‐environment interaction effects in each of the SSSLs.  相似文献   

5.
Summary One main reason for the slow improvement of durum wheat in water-limited environments is the lack of clear understanding of the interrelationships among yield components and their compensatory changes under low and erratic moisture availability. Five cultivars, varying in many physiological attributes, were tested under different drought-stress conditions in field and greenhouse experiments. The cause-effect relationships of duration of vegetative period, duration of grain-filling period, number of spikes per m2, kernels per spike, kernel weight and grain yield per m2 were assessed. Furthermore, yield stability was evaluated. Yield reduction was largest under mid-season stress (58%), followed by terminal stress (30%) and early stress (22%). Cultivar Po was very sensitive to terminal stress.Path-coefficient analysis revealed a complex pattern of relationships among the six variables. An increase in vegetative period reduced the grain-filling period under all conditions. It increased number of kernels per spike under non-stress conditions. The direct effect of spikes per m2 on grain yield was significantly positive. However, more spikes per m2 resulted in fewer kernels per spike and a low kernel weight and, as a result, a negative relationship with grain yield under early stress. Grain-filling period had a strong influence on grain yield via kernel weight. Kernels per spike had the largest direct effect on grain yield. However, it was negatively correlated with kernel weight, especially under terminal stress. Grain yield heavily depended on kernels per spike under early stress and grain-filling period and kernels per spike under terminal stress.Variation in drought susceptibility index among cultivars was significant under early and terminal stress conditions, but not under mid-stress conditions. Yield potential and stability were not correlated for the different drought-stress conditions.Longer grain-filling period, increased number of kernels per spike and limited spike number per m2 can be used as selection criteria for sustainable yield in water-limited environments.  相似文献   

6.
M. R. Foolad    G. Y. Lin  F. Q. Chen 《Plant Breeding》1999,118(2):167-173
The purpose of this study was to examine whether rate of tomato seed germination under non-stress, cold-stress and salt-stress conditions was under similar genetic control by identifying and comparing quantitative trait loci (QTLs) which affect germination rate under these conditions. A fast-germinating accession (LA722) of the wild tomato species Lycopersicon pimpinellifolium Jusl. and a slow-germinating cultivar (NC84173, maternal and recurrent parent) of tomato (Lycopersicon esculentum Mill.) were hybridized and BC1 and BC1S1 progeny produced. The BC1 population was used to construct a linkage map with 151 restriction fragment length polymorphism (RFLP) markers. The BC1S1 population (consisting of 119 BC1S1 families) was evaluated for germination under non-stress (control), cold-stress and salt-stress conditions and the mean time to 50% germination (T50) in each treatment was determined. Germination analyses indicated the presence of significant (P < 0.01) phenotypic correlations between T50 under control and cold stress (r = 0.71), control and salt stress (r = 0.58) and cold stress and salt stress (r = 0.67). The QTL analysis indicated the presence of genetic relationships between germination under these three conditions: a few QTLs were identified which commonly affected germination under both stress- (cold-, salt- or both) and non-stress conditions, and thus were called stress-nonspecific QTLs. A few QTLs were also identified which affected germination only under cold or salt stress and thus were called stress-specific QTLs. However, the stress-nonspecific QTLs generally exhibited larger individual effects and together accounted for a greater portion of the total phenotypic variation under each condition than the stress-specific QTLs. Whether the effects of stress-nonspecific QTLs were due to pleiotropic effects of the same genes, physical linkage of different genes, or a combination of both could not be determined in this study. The results, however, indicate that the rate of tomato seed germination under different stress and nonstress conditions is partly under the same genetic control.  相似文献   

7.
P. Wu  G. Zhang  N. Huang 《Euphytica》1996,89(3):349-354
Summary Segregation of plant height (PH), tiller number (TN), panicle number (PN), average panicle length per plant (PL), average primary branch number per panicle per plant (PBN) and 1000 grain weight (1000G) were specific in an F2 population derived from a cross of Palawan, a tall Javanica variety, and IR42, an Indica semidwarf variety. One hundred and four informative RFLP markers covering all 12 chromosomes were used for detecting putative QTLs controlling the traits. Orthogonal contrasts and interval mapping analysis were used for the analysis. QTL detected for PH on the region of chromosome 1, where semidwarfing gene sd-1 locus is located, seems to be a multiple allelic locus. An additional QTL for PH was identified on chromosome 2. Two QTLs for TN were detected on chromosomes 4 and 12. The QTL on chromosome 4 seemed also to govern the variation in PN. Four QTLs were found for the other traits, two of them for PL were located on chromosomes 6 and 2, one for PBN on chromosome 6 and the other for 1000G on chromosome 1. Additive gene actions were found to be predominant, except one QTL for PH and one QTL for PL, but partial or incomplete dominance also existed for the QTLs detected.  相似文献   

8.
A mapping population of 96 BC1F9lines (Backcross Inbred Lines: BILs),derived by a single-seed descent method rom a backcross of Nipponbare (japonica) / Kasalath (indica // Nippon are, was used to detect quantitative trait loci (QTLs) for leaf bronzing index (LBI), stem dry weight (SDW), tiller number (TN) and root dry weight (RDW) under Fe2+ stress condition in rice. Two parents and 96 BILs were phenotyped for the traits by growing them in Fe2+ toxicity nutrient solution. A total of four QTLs were detected on chromosome 1 and 3, respectively, with LOD of QTLs ranging from 3.17 to 7.03. One QTL controlling LBI, DW, N and RDW was located at the region of C955-C885 on chromosome 1, and their contributions to whole variation were 20.5%, 36.9%, 43.9% and 38.8%,respectively. The QTL located at the region of C955-C885 on chromosome 1 may be important to ferrous iron toxicity tolerance in rice. Another QTL for SDW and RDW was located at the region of C25-C515 on chromosome 3, with respective contributions of 47.9% and 35.0% to whole variation. Further, two QTLs on chromosome 1 were located for RDW at the region of R2329-R210 and for TN at the region of R1928-C178. Comparing with the other mapping results, the QTL located at the region of C955-C885 on chromosome 1 was identical with the results reported previously. There is a linkage between a TL detected under Fe2+ stress condition for stem and root dry weight and a QTL detected under phosphorus-deficiency condition for dry weight on chromosome 3. This revised version was published online in July 2006 with corrections to the Cover Date.  相似文献   

9.
Salt tolerance of rice (Oryza sativa L.) at the seed germination stage is one of the major determinants for the stable stand establishment in salinity soil. One population of recombinant inbred lines (RILs, F2:9), derived from a cross between a japonica rice landrace tolerant to salt stress and a sensitive indica rice variety, was used to determine the germination traits including imbibition rate and germination percentage under control (water) and salt stress (100 mM NaCl) for 10 days at 30 °C. The multiple interval mapping (MIM) were applied to conduct QTL for the traits. The results showed that seed germination was a quantitative trait controlled by several genes, and strongly affected by salt stress. A total of 16 QTLs were detected in this study, and each QTL could explain 4.6–43.7% of the total phenotypic variance. The expression of these QTLs might be developmentally regulated and growth stage-specific. In addition, only one digenic interaction was detected under salt stress, showing small effect on germination percentage with R2 2.7%. Among sixteen QTLs detected in this study, four were major QTLs with R2 > 30%, and some novel alleles of salt tolerance genes in rice. The results demonstrated that the japonica rice Jiucaiqing is a good source of gene(s) for salt tolerance and the major or minor QTLs identified could be used to improve the salt tolerance by marker-assisted selection (MAS) in rice.  相似文献   

10.
A wheat (Triticum aestivum L.) recombinant inbred line (RIL) population was used to identify quantitative trait loci (QTL) associated with yield, yield components, and canopy temperature depression (CTD) under field conditions. The RIL population, consisting of 118 lines derived from a cross between the stress tolerant cultivar ‘Halberd’ and heat stress sensitive cultivar ‘Karl92’, was grown under optimal and late sown conditions to impose heat stress. Yield and yield components including biomass, spikes m?2, thousand kernel weight, kernel weight and kernel number per spike, as well as single kernel characteristics were determined. In addition, CTD was measured during both moderate (32–33 °C) and extreme heat stress (36–37 °C) during grain-filling. Yield traits showed moderate to high heritability across environments with a large percentage of the variance explained by genetic effects. Composite interval mapping detected 25 stable QTL for the 15 traits measured, with the amount of phenotypic variation explained by individual QTL ranging from 3.5 to 27.1 %. Two QTL for both yield and CTD were co-localized on chromosomes 3BL and 5DL and were independent of phenological QTL. At both loci, the allele from Halberd was associated with both higher yield and a cooler crop canopy. The QTL on 3BL was also pleiotropic for biomass, spikes m?2, and heat susceptibility index. This region as well as other QTL identified in this study may serve as potential targets for fine mapping and marker assisted selection for improving yield potential and stress adaptation of wheat.  相似文献   

11.
Multi-environment trials represent a highly valuable tool for the identification of the genetic bases of crop yield potential and stress adaptation. A Diversity Array Technology®-based barley map has been developed in the ‘Nure’ × ‘Tremois’ biparental Doubled Haploid population, harbouring the genomic position of a gene set with a putative role in the regulation of flowering time and abiotic stress response in barley. The population has been evaluated in eighteen location-by-year combinations across the Mediterranean basin. QTL mapping identified several genomic regions responsible for barley adaptation to Mediterranean conditions in terms of phenology, grain yield and yield component traits. The most frequently detected yield QTL had the early flowering HvCEN_EPS2 locus (chromosome 2H) as peak marker, showing a positive effect from the early winter parent ‘Nure’ in eight field trials, and explaining up to 45.8 % of the observed variance for grain yield. The HvBM5A_VRN-H1 locus on chromosome 5H and the genomic region possibly corresponding to PPD-H2 on chromosome 1H were significantly associated to grain yield in five and three locations, respectively. Environment-specific QTLs for grain yield, and clusters of yield component QTLs not related to phenology and or developmental genes (e.g. on chromosome 4H, BIN_09) were observed as well. The results of this work provide a valuable source of knowledge and tools for both explaining the genetic bases of barley yield adaptation across the Mediterranean basin, and using QTL-associated markers for MAS pre-breeding and breeding programmes.  相似文献   

12.
The advanced backcross quantitative trait locus (AB-QTL) analysis has proven its usefulness to identify and localize favourable alleles from exotic germplasm and to transfer those alleles into elite varieties. In a balanced design with up to six environments and two nitrogen fertilization (N treatment) levels, a 4-factorial mixed model analysis of variance (ANOVA) was used to identify QTL main effects, QTL × environment interaction effects and QTL × N treatment interaction effects in the spring barley BC2DH population S42. The yield-related traits studied were number of ears per m2, days until heading, plant height, thousand grain weight (TGW) and grain yield. In total, 82 QTLs were detected for all traits. This finding was compared to a previous QTL study of the same population S42, where the current field data was reduced to one half through restriction of the analysis to the standard N treatment level (von Korff et al., Theor Appl Genet 112: 1221–1231, 2006). These authors located 54 QTLs for the same traits by applying a 3-factorial mixed model similar to the current model but excluding the factor N treatment. We found that QTL × environment interaction, alone or in combination, accounted for 24 of the newly uncovered QTLs, whereas QTL × N treatment interaction was of lesser importance with six new cases in total. A valuable QTL interacting with N treatment has been identified on chromosome 7H where lines carrying the wild barley allele were superior in number of ears per m2 in either N treatment. We conclude that in population S42 the extension of the phenotype data set and the inclusion of N treatment into the mixed model increased the power of QTL detection by providing an additional replication rather than by revealing specific N treatment QTLs.  相似文献   

13.
以优质粳稻品种Lemont与高产籼稻品种特青为亲本培育的高代双向回交导入系为材料,在温室140 mmol L-1 NaCl胁迫条件下定位影响苗期叶片盐害级别(SST)、幼苗存活天数(SDS)、地上部K+浓度(SKC)和地上部Na+浓度(SNC)及人工气候室条件下影响地上部K+、Na+浓度的QTL。双向导入系的大部分遗传背景与各自的受体亲本相同,其中Lemont背景导入系中轮回亲本Lemont的基因组平均占83.8%,特青背景导入系中轮回亲本特青基因组平均占88.9%。各耐盐相关性状在两个背景群体中均出现超亲分离,多数性状的频率分布呈相互重叠状态,表明双亲作为供体相互导入各耐盐性状基因的效应大致相当。两个背景导入系群体中分别检测到影响上述耐盐相关性状的QTL各18个,同一性状在两个背景导入系中未能检测到任何相同表达的QTL,表明耐盐QTL表达具有很强的遗传背景效应,同时也说明这些耐盐QTL的效应可能较小。温室和人工气候室两种环境下仅在特青背景导入系中检测到1个影响SKC的相同QTL,表明耐盐QTL与环境的互作非常明显。虽然双亲均表现中等感盐,但QTL定位结果表明双亲中都存在一些提高耐盐相关性状的有利等位基因。研究认为,利用分子标记技术挖掘“隐蔽”于育成品种中的耐盐基因,进一步利用分子标记辅助选择技术对这些非等位耐盐基因进行聚合,完全有可能提高育成品种的耐盐水平。  相似文献   

14.
Although many screening criteria have been suggested to distinguish between genotypes for their salt tolerance under controlled environmental conditions, there is a need to test these criteria in the field. Saline soils are often complex and, therefore, unlikely to show a simple relationship to controlled conditions. To address this deficit, different agronomic and physiological screening criteria for salt tolerance in wheat at different stages were examined under both field and controlled conditions. Four wheat genotypes differing in their salt‐tolerance levels were grown in salt‐affected soil at two different locations and also under greenhouse conditions. Dry weight and leaf area of the upper and lower two leaves of the main stem and total dry weight at Zadoks scale 47 were measured in plants grown under field conditions. The concentrations of Cl?, Na+, K+ and Ca2+ in the upper and lower two leaves of the main stem at Zadoks scale 47 and different yield components were measured in plants grown under both conditions. Our results indicate that measurements derived from the upper two leaves of the main stem were generally more effective as screening criteria than those from the lower two leaves. Correlation coefficients between grain yield and either dry weight or leaf area of the upper two leaves of the main stem indicated that dry weight is inferior to leaf area as a screening criterion under field conditions. Number of sterile spikelets per plant performed well under both conditions, whereas the number of spikelets per plant and 1000‐grain weight failed to distinguish the differences of salt‐tolerance levels among genotypes accurately. Weight and number of grains per plant and number of fertile spikes per plant were poor criteria under controlled conditions, but effective under field conditions. The maintenance of low Cl? and Na+ concentrations in the upper two leaves offered the best guide to salt tolerance under both conditions. Potassium concentration was a poor criterion compared with the selectivity of K+ over Na+, which was useful under both field and controlled conditions. Calcium concentration and Ca2+ over Na+ selectivity in the upper and/or lower two leaves of the main stem were also effective in ranking genotypes according to their salt tolerance under both field and controlled conditions. Therefore, we conclude that simple measurements of the upper two leaves of the main stem including a straightforward measurement of leaf area, visually estimating the number of sterile spikelets, and a quick, practical determination of Na+ and Ca2+ concentration constitute effective criteria to screen wheat genotypes for salt tolerance under both field and controlled conditions.  相似文献   

15.
Tiller number per plant (TN) and plant height (PH) are important agronomic traits related to grain yield (GY) in rice (Oryza sativa L.). A total of 30 additive quantitative trait loci (A-QTL) and 9 significant additive × environment interaction QTLs (AE-QTL) were detected, while the phenotypic and QTL correlations confirmed the intrinsic relationship of the three traits. These QTLs were integrated with 986 QTLs from previous studies by metaanalysis. Consensus maps contained 7156 markers for a total map length of 1112.71 cM, onto which 863 QTLs were projected; 78 meta-QTLs (MQTLs) covering 11 of the 30 QTLs were detected from the cross between Dongnong422 and Kongyu131 in this study. A total of 705 predicted genes were distributed over the 21 MQTL intervals with physical length <0.3 Mb; 13 of the 21 MQTLs, and 34 candidate genes related to grain yield and plant development, were screened. Five major QTLs, viz. qGY6-2, qPH7-2, qPH6-3, qTN6-1, and qTN7-1, were not detected in the MQTL intervals and could be used as newly discovered QTLs. Candidate genes within these QTL intervals will play a meaningful role in molecular marker-assisted selection and map-based cloning of rice TN, PH, and GY.  相似文献   

16.
Summary Quantitative trait loci (QTL) analysis for Al tolerance was performed in rice using a mapping population of 98 BC1F10 lines (backcross inbred lines: BILs), derived from a cross of Al-tolerant cultivar of rice (Oryza sativa L. cv. Nipponbare) and Al-sensitive cultivar (cv. Kasalath). Three characters related to Al tolerance, including root elongation under non-stress conditions (CRE), root elongation under Al stress (SRE) and the relative root elongation (RRE) under Al stress versus non-stress conditions, were evaluated for the BILs and the parents at seedling stage. A total of seven QTLs for the three traits were identified. Among them, three putative QTLs for CRE (qCRE-6, qCRE-8 and qCRE-9) were mapped on chromosomes 6, 8 and 9, respectively. One QTL for SRE (qSRE-4) was identified on chromosome 4. Three QTLs (qRRE-5, qRRE-9 and qRRE-10) for RRE were detected on chromosomes 5, 9, 10 and accounted for 9.7–11.8% of total phenotypic variation. Interestingly, the QTL qRRE-5 appears to be syntenic with the genomic region carrying a major Al tolerance gene on chromosome 6 of maize. Another QTL, qRRE-9, appears to be similar among different rice populations, while qRRE-10 is unique in the BIL population. The common QTLs for CRE and RRE indicate that candidate genes conferring Al tolerance in the rice chromosome 9 may be associated with root growth rates. The existence of QTLs for Al tolerance was confirmed in substitution lines for corresponding chromosomal segments. These results also provide the possibilities of enhancing Al tolerance in rice through using marker-assisted selection (MAS) and pyramiding QTLs.  相似文献   

17.
In wheat, strong genetic correlations have been found between grain yield (GY) and tiller number per plant (TN), fertile spikelet number per spike (FSN), kernel number per spike (KN) and thousand‐kernel weight (TKW). To investigate their genetic relationships at the individual quantitative trait locus (QTL) level, we performed both normal and multivariate conditional QTL analysis based on two recombinant inbred lines (RILs) populations. A total of 79 and 48 normal QTLs were identified in the International Triticeae Mapping Initiative (ITMI)/SHW‐L1 × Chuanmai 32 (SC) populations, respectively, as well as 55 and 35 conditional QTLs. Thirty‐two QTL clusters in the ITMI population and 18 QTL clusters in the SC population explained 0.9%–46.2% of phenotypic variance for two to eight traits. A comparison between the normal and conditional QTL mapping analyses indicated that FSN made the smallest contribution to GY among the four GY components that were considered at the QTL level. The effects of TN, KN and TKW on GY were stronger at the QTL level.  相似文献   

18.
Temperature and photoperiod fluctuate rapidly in different seasons of the year, and analyzing their effects on rice yield components is crucial for adaptation of rice under various climatic conditions. To study the effects of seasonal changes on yield components, 168 recombinant inbred lines derived from a cross between two Oryza sativa L. indica varieties, Zhenshan 97 and Zhongzao 18 were grown for phenotype collection, in three different seasons, within a year. The results implied that temperatures across the three seasons played a crucial role in determining the trait effects. Spikelets per panicle (SPP), panicle length (PL) and plant height (PH) traits increased with high temperatures in middle season. Genetic analysis detected major quantitative trait loci (QTLs) qSPP10, qPL10 and qPH10 for SPP, PL and PH in the interval between markers RM1375 and RM3229 on chromosome 10, in all the three seasons. Two-way ANOVA showed that genotype by environment and QTL by environment interactions for these traits were highly significant (P < 0.0001). The region with a cluster of QTLs detected in all three seasons could be the preferred target to breeders in developing rice varieties that can be accustomed to different seasonal changes.  相似文献   

19.
Two hundred ninety-six Asian barley (Hordeum vulgare L.) accessions were assessed to detect QTLs underlying salt tolerance by association analysis using a 384 single nucleotide polymorphism (SNP) marker system. The experiment was laid out at the seedling stage in a hydroponic solution under control and 250 mM NaCl solution with three replications of four plants each. Salt tolerance was assessed by leaf injury score (LIS) and salt tolerance indices (STIs) of the number of leaves (NL), shoot length (SL), root length (RL), shoot dry weight (SDW) and root dry weight (RDW). LIS was scored from 1 to 5 according to the severity of necrosis and chlorosis observed on leaves. There was a wide variation in salt tolerance among Asian barley accessions. LIS and STI (SDW) were the most suitable traits for screening salt tolerance. Association was estimated between markers and traits to detect QTLs for LIS and STI (SDW). Seven significant QTLs were located on chromosomes 1H (2 QTLs), 2H (2 QTLs), 3H (1 QTL), 4H (1 QTL) and 5H (1 QTL). Five QTLs were associated with LIS and 2 QTLs with STI (SDW). Two QTLs associated with LIS were newly identified on chromosomes 3H and 4H.  相似文献   

20.
不同生态环境下玉米产量性状QTL分析   总被引：35，自引：10，他引：25  
以玉米（Zea mays L.）自交系黄早四和Mo17为亲本得到的191个F2单株为作图群体,衍生的184个F2∶3 家系作为性状评价群体,分析了单株穗数、穗行数、行粒数、百粒重和单株籽粒产量在北京和新疆2个生态环境下的表现和数量性状基因位点的定位结果。QTL检测结果表明,2个环境共检测出47个QTL,分布于除第10染色体以外的9条染色体,其中与单株穗数相关的QTL共10个,可解释的表型变异为5.3%~25.6%;与穗行数相关的QTL共13个,可解释的表型变异为4.5%~23.2%;与行粒数相关的QTL有9个,解释的表型变异为5.4%~13.7%;与百粒重相关的QTL达10个,可解释的表型变异为4.9%~13.3%;与单株籽粒产量相关的QTL有5个,可解释的表型变异为6.1%~35.8 %。大部分产量QTL只在单一环境下被检测到,说明产量相关QTL与环境之间存在明显的互作。表型相关显著的产量性状,它们的QTL容易在相同或相邻标记区间检测到。研究还发现了若干个QTL富集区域,可能是发掘通用QTL的候选位点。  相似文献   

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