Conditional and unconditional QTL mapping of drought-tolerance-related traits of wheat seedling using two related RIL populations

For discovering the quantitative trait loci (QTLs) contributing to early seedling growth and drought tolerance during germination, conditional and unconditional analyses of 12 traits of wheat seedlings: coleoptile length, seedling height, longest root length, root number, seedling fresh weight, stem and leaves fresh weight, root fresh weight, seedling dry weight, stem and leaves dry weight, root dry weight, root to shoot fresh weight ratio, root-to-shoot dry weight ratio, were conducted under two water conditions using two F_8:9 recombinant inbred line (RIL) populations. The results of unconditional analysis are as follows: 88 QTLs accounting for 3.33–77.01% of the phenotypic variations were detected on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 4A, 4B, 4D, 5A, 5B, 5D, 6A, 6B, 6D, 7A, 7B and 7D. Among these QTLs, 19 were main-effect QTLs with a contribution rate greater than 10%. The results of the conditional QTL analysis of 12 traits under osmotic stress on normal water conditions were as follows: altogether 22 QTLs concerned with drought tolerance were detected on chromosomes 1B, 2A, 2B, 3B, 4A, 5D, 6A, 6D, 7B, and 7D. Of these QTLs, six were main-effect QTLs. These 22 QTLs were all special loci directly concerned with drought tolerance and most of them could not be detected by unconditional analysis. The finding of these QTLs has an important significance for fine-mapping technique, map-based cloning, and molecular marker-assisted selection of early seedling traits, such as growth and drought tolerance.     

QTL mapping for some grain traits in bread wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Grain traits are important agronomic attributes with the market value as well as milling yield of bread wheat. In the present study, quantitative trait loci (QTL) regulating grain traits in wheat were identified. Data for grain area size (GAS), grain width (GWid), factor form density (FFD), grain length-width ratio (GLWR), thousand grain weight (TGW), grain perimeter length (GPL) and grain length (GL) were recorded on a recombinant inbred line derived from the cross of NW1014?×?HUW468 at Meerut and Varanasi locations. A linkage map of 55 simple sequence repeat markers for 8 wheat chromosomes was used for QTL analysis by Composite interval mapping. Eighteen QTLs distributed on 8 chromosomes were identified for seven grain traits. Of these, five QTLs for GLWR were found on chromosomes 1A, 6A, 2B, and 7B, three QTLs for GPL were located on chromosomes 4A, 5A and 7B and three QTLs for GAS were mapped on 5D and 7D. Two QTLs were identified on chromosomes 4A and 5A for GL and two QTLs for GWid were identified on chromosomes 7D and 6A. Similarly, two QTLs for FFD were found on chromosomes 1A and 5D. A solitary QTL for TGW was identified on chromosome 2B. For several traits, QTLs were also co-localized on chromosomes 2B, 4A, 5A, 6A, 5D, 7B and 7D. The QTLs detected in the present study may be validated for specific crosses and then used for marker-assisted selection to improve grain quality in bread wheat.     

Phenotype/genotype associations for yield and salt tolerance in a barley mapping population segregating for two dwarfing genes

Barley traits related to salt tolerance are mapped in a population segregating for a dwarfing gene associated with salt tolerance. Twelve quantitative trait loci (QTLs) were detected for seven seedling traits in doubled haploids from the spring barley cross Derkado x B83-12/21/5 when given saline treatment in hydroponics. The location of QTLs for seedling growth stage (leaf appearance rate), stem weight prior to elongation, and tiller number are reported for the first time. In addition, four QTLs were found for the mature plant traits grain nitrogen and plot yield. In total, seven QTLs are co-located with the dwarfing genes sdw1, on chromosome 3H, and ari-e.GP, on chromosome 5H, including seedling leaf response (SGa) to gibberellic acid (GA(3)). QTLs controlling the growth of leaves (GS2) on chromosomes 2H and 3H and emergence of tillers (TN2) and grain yield were independent of the dwarfing genes. Field trials were grown in eastern Scotland and England to estimate yield and grain composition. A genetic map was used to compare the positions of QTLs for seedling traits with the location of QTLs for the mature plant traits. The results are discussed in relation to the study of barley physiology and the location of genes for dwarf habit and responses to GA.     

High-Density Genetic Linkage Map Construction and QTL Mapping of Grain Shape and Size in the Wheat Population Yanda1817 × Beinong6

High-density genetic linkage maps are necessary for precisely mapping quantitative trait loci (QTLs) controlling grain shape and size in wheat. By applying the Infinium iSelect 9K SNP assay, we have constructed a high-density genetic linkage map with 269 F ₈ recombinant inbred lines (RILs) developed between a Chinese cornerstone wheat breeding parental line Yanda1817 and a high-yielding line Beinong6. The map contains 2431 SNPs and 128 SSR & EST-SSR markers in a total coverage of 3213.2 cM with an average interval of 1.26 cM per marker. Eighty-eight QTLs for thousand-grain weight (TGW), grain length (GL), grain width (GW) and grain thickness (GT) were detected in nine ecological environments (Beijing, Shijiazhuang and Kaifeng) during five years between 2010–2014 by inclusive composite interval mapping (ICIM) (LOD≥2.5). Among which, 17 QTLs for TGW were mapped on chromosomes 1A, 1B, 2A, 2B, 3A, 3B, 3D, 4A, 4D, 5A, 5B and 6B with phenotypic variations ranging from 2.62% to 12.08%. Four stable QTLs for TGW could be detected in five and seven environments, respectively. Thirty-two QTLs for GL were mapped on chromosomes 1B, 1D, 2A, 2B, 2D, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6B, 7A and 7B, with phenotypic variations ranging from 2.62% to 44.39%. QGl.cau-2A.2 can be detected in all the environments with the largest phenotypic variations, indicating that it is a major and stable QTL. For GW, 12 QTLs were identified with phenotypic variations range from 3.69% to 12.30%. We found 27 QTLs for GT with phenotypic variations ranged from 2.55% to 36.42%. In particular, QTL QGt.cau-5A.1 with phenotypic variations of 6.82–23.59% was detected in all the nine environments. Moreover, pleiotropic effects were detected for several QTL loci responsible for grain shape and size that could serve as target regions for fine mapping and marker assisted selection in wheat breeding programs.     

小麦幼苗耐热性的QTL定位分析

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

QTL mapping of 1000-kernel weight, kernel length, and kernel width in bread wheat (Triticum aestivum L.)

Kernel size and morphology influence the market value and milling yield of bread wheat (Triticum aestivum L.). The objective of this study was to identify quantitative trait loci (QTLs) controlling kernel traits in hexaploid wheat. We recorded 1000-kernel weight, kernel length, and kernel width for 185 recombinant inbred lines from the cross Rye Selection 111 × Chinese Spring grown in 2 agro-climatic regions in India for many years. Composite interval mapping (CIM) was employed for QTL detection using a linkage map with 169 simple sequence repeat (SSR) markers. For 1000-kernel weight, 10 QTLs were identified on wheat chromosomes 1A, 1D, 2B, 2D, 4B, 5B, and 6B, whereas 6 QTLs for kernel length were detected on 1A, 2B, 2D, 5A, 5B and 5D. Chromosomes 1D, 2B, 2D, 4B, 5B and 5D had 9 QTLs for kernel width. Chromosomal regions with QTLs detected consistently for multiple year-location combinations were identified for each trait. Pleiotropic QTLs were found on chromosomes 2B, 2D, 4B, and 5B. The identified genomic regions controlling wheat kernel size and shape can be targeted during further studies for their genetic dissection.     

QTL mapping for grain filling rate and yield-related traits in RILs of the Chinese winter wheat population Heshangmai × Yu8679

A set of 142 winter wheat recombinant inbred lines (RILs) deriving from the cross Heshangmai x Yu8679 were tried in four ecological environments during the seasons 2006 and 2007. Nine agronomic traits comprising mean grain filling rate (GFR(mean)), maximum grain filling rate (GFR(max)), grain filling duration (GFD), grain number per ear (GNE), grain weight per ear (GWE), flowering time (FT), maturation time (MT), plant height (PHT) and thousand grain weight (TGW) were evaluated in Beijing (2006 and 2007), Chengdu (2007) and Hefei (2007). A genetic map comprising 173 SSR markers and two EST markers was generated. Based on the genetic map and phenotypic data, quantitative trait loci (QTL) were mapped for these agronomic traits. A total of 99 putative QTLs were identified for the nine traits over four environments except GFD, PHT and MT, measured in two environments (BJ07 and CD07), respectively. Of the QTL detected, 17 for GFR(mean), 16 for GFR(max), 21 for TGW and 10 for GWE involving the chromosomes 1A, 1B, 2A, 2D, 3A, 3B, 3D, 4A, 4D, 5A, 5B, 6D and 7D were identified. Moreover, 13 genomic regions showing pleiotropic effects were detected in chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 4B, 4D, 5B, 6D and 7D; these QTL revealing pleiotropic effects may be informative for a better understanding of the genetic basis of grain filling rate and other yield-related traits, and represent potential targets for multi-trait marker aided selection in wheat.     

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 quantitative trait loci for ABA responsiveness at the seedling stage associated with ABA-regulated gene expression in common wheat

Responsiveness to abscisic acid (ABA) during vegetative growth plays an important role in regulating adaptive responses to various environmental conditions, including activation of a number of ABA-responsive genes. However, the relationship between gene expression and responsiveness to ABA at the seedling stage has not been well studied in wheat. In the present study, quantitative trait locus (QTL) analysis for ABA responsiveness at the seedling stage was performed using recombinant inbred lines derived from a cross between common wheat cultivars showing different ABA responsiveness. Five QTLs were found to be significant, located on chromosomes 1B, 2A, 3A, 6D and 7B. The QTL with the greatest effect was located on chromosome 6D and explained 11.12% of the variance in ABA responsiveness. The other QTLs each accounted for approximately 5–8% of the phenotypic variation. Expression analyses of three ABA-responsive Cor/Lea genes, Wdhn13, Wrab15 and Wrab17, showed that allelic differences in QTLs on chromosomes 2A, 6D and 7B influenced expression of these genes in seedlings treated with ABA. The 3A QTL appeared to be involved in the regulatory system of Wdhn13 and Wrab15, but not Wrab17. The effects of the 2A and 6D QTLs on gene expression were relatively large. The combination of alleles at the QTLs resulted in an additive or synergistic effect on Cor/Lea expression. These results indicate that the QTLs influencing ABA responsiveness are associated with ABA-regulated gene expression and suggest that the QTL on chromosome 6D with the largest effect acts as a key regulator of ABA responses including seedling growth arrest and gene expression during the vegetative stage.     

QTL mapping of flag leaf-related traits in wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Key message

QTL controlling flag leaf length, flag leaf width, flag leaf area and flag leaf angle were mapped in wheat.

Abstract

This study aimed to advance our understanding of the genetic mechanisms underlying morphological traits of the flag leaves of wheat (Triticum aestivum L.). A recombinant inbred line (RIL) population derived from ND3331 and the Tibetan semi-wild wheat Zang1817 was used to identify quantitative trait loci (QTLs) controlling flag leaf length (FLL), flag leaf width (FLW), flag leaf area (FLA), and flag leaf angle (FLANG). Using an available simple sequence repeat genetic linkage map, 23 putative QTLs for FLL, FLW, FLA, and FLANG were detected on chromosomes 1B, 2B, 3A, 3D, 4B, 5A, 6B, 7B, and 7D. Individual QTL explained 4.3–68.52% of the phenotypic variance in different environments. Four QTLs for FLL, two for FLW, four for FLA, and five for FLANG were detected in at least two environments. Positive alleles of 17 QTLs for flag leaf-related traits originated from ND3331 and 6 originated from Zang1817. QTLs with pleiotropic effects or multiple linked QTL were also identified on chromosomes 1B, 4B, and 5A; these are potential target regions for fine-mapping and marker-assisted selection in wheat breeding programs.

     

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

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

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 dissection of interactions between wheat flour starch and its components in two populations using two QTL mapping methods

Starch content and its components are important for determining wheat end-use quality and yield. However, little information is available about their interactions at the QTL/gene level in more than one population using different QTL mapping methods. Therefore, to dissect these interactions, two mapping populations from two locations over 2 years were used. The QTLs for the populations were analyzed by unconditional and conditional QTL mapping by two different analysis methods. In the two populations, there were a total of 24 unconditional additive QTLs detected for flour amylose (FAMS), flour amylopectin (FAMP), flour total starch (FTSC), and the ratio of FAMS to FAMP using ICIMapping4.1 methods, but 26 unconditional QTLs were found using QTLNetwork2.0 methods. Of these QTLs, 10 stable major additive QTLs were identified in more than one environment, mainly distributed on chromosomes 3B, 4A, 5A, and 7D. The maximum percentage of phenotypic variance explained (PVE) reached 54.31%. Two new unconditional major additive QTLs on chromosome 3B (Qftsc3B and Qfamp3B) were found. A total of 23 and 19 conditional additive QTLs were identified in the two populations using two different methods, respectively. Of which, eight and six stable major conditional QTLs were detected on chromosomes 3B, 4A, and 7D, respectively. New repressed QTLs were identified, such as Qftsc/fams5B-1 and Qftsc/fams5B-2. There were 20 epistatic unconditional and 15 conditional QTLs detected. In all, important QTLs on chromosomes 3B, 4A, and 7A were found in both populations. However, the number of important QTLs in the special recombinant inbred line (RIL) population was higher than that in the double haploid (DH) population, especially on chromosomes 7D and 5B. Moreover, the QTLs on chromosomes 4A, 7A, and 7D were close to the Wx-1 loci in the RIL population. These indicated better results can be obtained by a special population to target traits than by a common population. The important QTLs on key chromosomes can always be detected no matter what kinds of populations are used, such as the QTLs on chromosome 4A. In addition, QTL clusters were found on chromosomes 4A, 3B, 7A, 7D, and 5A in the two populations, indicating these chromosome regions were very important for starch biosynthesis.     

A major QTL for powdery mildew resistance is stable over time and at two development stages in winter wheat

Despite the large impact of powdery mildew in wheat cultivated areas, little has been done to study powdery mildew resistance by QTL analysis up to now. The objective of the present paper is to present how the genetic basis of powdery mildew resistance in the resistant wheat line RE714 have been studied by QTL analysis at the adult plant stage over the course of 3 years, and at the vernalized seedling plant stage, and a comparison between the results obtained. Two segregating populations (DH and F_2:3) were derived from the cross between the resistant line (RE714), and a susceptible line (Hardi); these were analysed for powdery mildew resistance at the adult plant stage in the field under natural infection conditions in 1996, 1997 and 1998. The DH population was also tested for powdery mildew resistance at the vernalized seedling stage with four different isolates of powdery mildew. At the adult plant stage, a total of three QTLs (on chromosomes 5D, 4A and 6A) and five QTLs (on chromosomes 5D, 6A, 7A and 7B) were found for the DH and F_2:3 populations, respectively. The genetic control of resistance was found to be polygenic but involved a major QTL (on chromosome 5D), which was detected each year and which explained a high proportion of the variability observed (28.1%–37.9%). At the vernalized seedling stage, two QTLs were found (on chromosomes 5D and 7B) and the QTL detected on chromosome 5D was common to the four isolates tested. The comparison between the two development stages showed that the QTL on chromosome 5D was detected in all the different environments tested and again explained a high proportion of the variability. Different molecular interpretations of this QTL have also been discussed. Received: 5 October 2000 / Accepted: 1 March 2001     

Inheritance and localisation of resistance to <Emphasis Type="Italic">Mycosphaerella graminicola</Emphasis> causing septoria tritici blotch and plant height in the wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.) genome with DNA markers

Resistance to the disease septoria tritici blotch of wheat (Triticum aestivum L.), caused by the fungus Mycosphaerella graminicola (Fuckel.) J. Schrot in Cohn (anamorph Septoria tritici Roberge in Desmaz.) was investigated in a doubled-haploid (DH) population of a cross between the susceptible winter wheat cultivar Savannah and the resistant cultivar Senat. A molecular linkage map of the population was constructed including 76 SSR loci and 244 AFLP loci. Parents and DH progeny were tested for resistance to single isolates of M. graminicola in a growth chamber at the seedling stage, and to an isolate mixture at the adult plant stage, in field trials. A gene located at or near the Stb6 locus mapping to chromosome 3A provided seedling resistance to IPO323. Two complementary genes, mapping to chromosome 3A, one of which was the IPO323 resistance gene, were needed for resistance to the Danish isolate Ris?97-86. In addition, a number of minor loci influenced the expression of resistance in the growth chamber. In the field, four QTLs for resistance to septoria tritici blotch were detected. Two QTLs, located on chromosomes 3A and 6B explained 18.2 and 67.9% of the phenotypic variance in the mean over two trials. Both these QTLs were also detected at the seedling stage with isolate Ris?97-86, whereas isolate IPO323 only detected the QTL on 3A. Additionally, two QTLs identified in adult plants on chromosomes 2B and 7B were not detected at the seedling stage. Four QTLs were detected for plant height located on chromosomes 2B, 3A, 3B and on a linkage group not assigned to a chromosome. The major QTLs on 3A and on the unassigned linkage group were consistent over two trials, and the QTL on 3A seemed to be linked to a QTL for septoria tritici blotch resistance.     

Mapping quantitative trait loci controlling seed longevity in rice ( Oryza sativa L.)

Quantitative trait loci (QTLs) controlling seed longevity in rice were identified using 98 backcross inbred lines (BILs) derived from a cross between a japonica variety Nipponbare and an indica variety Kasalath. Seeds of each BIL were kept for 12 months at 30 degrees C in dry conditions to promote loss of viability. To measure seed longevity, we performed an additional aging-processing treatment for 2 months at 30 degrees C maintaining seeds at 15% moisture content. We measured the germination percent of these treated seeds at 25 degrees C for 7 days as the degree of seed longevity. The germination of BILs ranged from 0 to 100% with continuous variation. Three putative QTLs for seed longevity, qLG-2, qLG-4 and qLG-9, were detected on chromosome 2, 4 and 9, respectively. Kasalath alleles increased the seed longevity at these QTLs. The QTL with the largest effect, qLG-9, explained 59.5% of total phenotypic variation in BILs. The other two QTLs, qLG-2 and qLG-4, explained 13.4 and 11.6% of the total phenotypic variation, respectively. We also verified the effect of the Kasalath allele of qLG-9 using chromosome segment substitution lines. Furthermore, QTLs for seed dormancy were identified on chromosomes 1, 3, 5, 7 and 11. Based on the comparison of the chromosomal location of QTLs for seed longevity and seed dormancy, these traits seem to be controlled by different genetic factors.     

Quantitative trait loci mapping of dark-induced senescence in winter wheat (Triticum aestivum)

In order to explore the genetics of dark-induced senescence in winter wheat(Triticum aestivum L.),a quantitative trait loci(QTL)analysis was carried out in a doubled haploid population developed from a cross between the varieties Hanxuan 10(HX)and Lumai 14(LM).The senescence parameters chlorophyll content(Chl a+b,Chl a,and Chl b),original fluorescence(Fo),maximum fluorescence level(Fm),maximum photochemical efficiency(Fv/Fm),and ratio of variable fluorescence to original fluorescence(Fv/Fo)were evaluated in the second leaf of whole three-leaf seedlings subjected to 7 d of darkness.A total of 43 QTLs were identified that were associated with dark-induced senescence using composite interval mapping.These QTLs were mapped to 20 loci distributed on 11 chromosomes:1B,1D,2A,2B,3B,3D,5D,6A,6B,7A,and 7B.The phenotypic variation explained by each QTL ranged from 7.5% to 19.4%.Eleven loci coincided with two or more of the analyzed parameters.In addition,14 loci co-located or were linked with previously reported QTLs regulating flag leaf senescence,tolerance to high light stress,and grain protein content(Gpc),separately.     

Mapping of quantitative trait loci for field resistance to Fusarium head blight in an European winter wheat

Fusarium head blight (FHB) caused by Fusarium culmorum is an economically important disease of wheat that may cause serious yield and quality losses under favorable climate conditions. The development of disease-resistant cultivars is the most effective control strategy. Worldwide, there is heavy reliance on the resistance pool originating from Asian wheats, but excellent field resistance has also been observed among European winter wheats. The objective of this study was to map and characterize quantitative traits loci (QTL) of resistance to FHB among European winter wheats. A population of 194 recombinant inbred lines (RILs) was genotyped from a cross between two winter wheats Renan (resistant)/Récital (susceptible) with microsatellites, AFLP and RFLP markers. RILs were assessed under field conditions For 3 years in one location. Nine QTLs were detected, and together they explained 30-45% of the variance, depending on the year. Three of the QTLs were stable over the 3 years. One stable QTL, QFhs.inra.2b, was mapped to chromosome 2B and two QTLs QFhs.inra.5a2 and QFhs.inra5a3, to chromosome 5A; each of these QTLs explained 6.9-18.6% of the variance. Other QTLs were identified on chromosome 2A, 3A, 3B, 5D, and 6D, but these had a smaller effect on FHB resistance. One of the two QTLs on chromosome 5A was linked to gene B1 controlling the presence of awns. Overlapping QTLs for FHB resistance were those for plant height or/and flowering time. Our results confirm that wheat chromosomes 2A, 3A, 3B, and 5A carry FHB resistance genes, and new resistance factors were identified on chromosome arms 2BS and 5AL. Markers flanking these QTLs should be useful tools for combining the resistance to FHB of Asian and European wheats to increase the resistance level of cultivars.     

水稻米粒延伸性的遗传剖析

以籼稻ZYQ8与粳稻JX17为亲本的DH群体作为研究材料,考察DH群体及双亲的米粒延伸率相关性状,并使用该群体的分子连锁图谱进行QTL分析.共检测到14个与稻米延伸性有关的QTL,包括2个粒长QTL、7个饭粒长QTL和5个米粒延伸率QTL,分别位于第1、2、3、5、6、7、10、11和12染色体.所有QTL的LOD值介于2.26～9.25,分别解释性状变异的5.31%～17.21%.在第3染色体上的G249～G164、第6染色体上的G30～RZ516和第10染色体上的G1082～GA223区间同时检测到控制饭粒长和米粒延伸率的QTL.米粒延伸性受多基因控制,Wx基因与位于第6染色体上的qCRE-6的G30～RZ516区间相近,对米饭的延伸性具重要影响.     

Genetic mapping of maize streak virus resistance from the Mascarene source. II. Resistance in line CIRAD390 and stability across germplasm

The streak disease has a major effect on maize in sub-Saharan Africa. Various genetic factors for resistance to the virus have been identified and mapped in several populations; these factors derive from different sources of resistance. We have focused on the Réunion island source and have recently identified several factors in the D211 line. A second very resistant line, CIRAD390, was crossed to the same susceptible parent, B73. The linkage map comprised 124 RFLP markers, of which 79 were common with the D211×B73 map. A row-column design was used to evaluate the resistance to maize streak virus (MSV) of 191 F_2:3 families under artificial infestation at two locations: Harare (Zimbabwe) and in Réunion island. Weekly ratings of resistance were taken and disease incidence and severity calculated. QTL analyses were conducted for each scoring date and for the integration over time of the disease scores, of incidence, and of severity. Heritability estimates (71–98%) were as high as for the D211×B73 population. Eight QTLs were detected on chromosomes 1, 2, 3, 5 (two QTLs), 6, 8, and 10. The chr1-QTL explained the highest proportion of phenotypic variation, about 45%. The QTLs on chromosomes 1, 2, and 10 were located in the same chromosomal bin as QTLs for MSV resistance in the D211×B73 population. In a simultaneous fit, QTLs explained together 43–67% of the phenotypic variation. The QTLs on chromosomes 3, 5, and 6 appeared to be specific for one or the other component of the resistance. For the chr3-QTL, resistance was contributed by the susceptible parent. There were significant QTL × environment interactions for some of the variables studied, but QTLs were stable in the two environments. They also appeared to be stable over time. Global gene action ranged from partial dominance to overdominance, except for disease severity. Some additional putative QTLs were also detected. The major QTL on chromosome 1 seemed to be common to the other sources of resistance, namely Tzi4, a tolerant line from IITA, and CML202 from CIMMYT. However, the distribution of the other QTLs within the genome revealed differences in Réunion germplasm and across these other resistance sources. This diversity is of great importance when considering the durability of the resistance. Received: 15 June 1998 / Accepted: 30 January 1999