Molecular mapping of quantitative trait loci for drought tolerance in maize plants

Drought tolerance is one of the most important but complex traits of crops. We looked for quantitative trait loci (QTLs) that affect drought tolerance in maize. Two maize inbreds and their advanced lines were evaluated for drought-related traits. A genetic linkage map developed using RFLP markers was used to identify QTLs associated with drought-related traits. Twenty-two QTLs were detected, with a minimum of one and a maximum of nine for drought-related traits. A single-QTL was detected for sugar concentration accounting for about 52.2% of the phenotypic variation on chromosome 6. A single-QTL was also identified for each of the traits root density, root dry weight, total biomass, relative water content, and leaf abscisic acid content, on chromosomes 1 and 7, contributing to 24, 0.2, 0.4, 7, and 19% of the phenotypic variance, respectively. Three QTLs were identified for grain yield on chromosomes 1, 5, and 9, explaining 75% of the observed phenotypic variability, whereas four QTLs were detected for osmotic potential on chromosomes 1, 3, and 9, together accounting for 50% of the phenotypic variance. Nine QTLs were detected for leaf surface area on chromosomes 3 and 9, with various degrees of phenotypic variance, ranging from 25.8 to 42.2%. Four major clusters of QTLs were identified on chromosomes 1, 3, 7, and 9. A QTL for yield on chromosome 1 was found co-locating with the QTLs for root traits, total biomass, and osmotic potential in a region of about 15 cM. A cluster of QTLs for leaf surface area were coincident with a QTL for osmotic potential on chromosome 3. The QTLs for leaf area also clustered on chromosome 9, whereas QTLs for leaf abscisic acid content and relative water content coincided on chromosome 7, 10 cM apart. Co-location of QTLs for different traits indicates potential pleiotropism or tight linkage, which may be useful for indirect selection in maize improvement for drought tolerance.     

Genetic analysis of cold-tolerance of photosynthesis in maize

The genetic basis of cold-tolerance was investigated by analyzing the quantitative trait loci (QTL) of an F₂:3 population derived from a cross between two lines bred for contrasting cold-tolerance using chlorophyll fluorescence as a selection tool. Chlorophyll fluorescence parameters, CO₂ exchange rate, leaf greenness, shoot dry matter and shoot nitrogen content were determined in plants grown under controlled conditions at 25/22 °C or 15/13 °C (day/night). The analysis revealed the presence of 18 and 19 QTLs (LOD > 3.5) significantly involved in the variation of nine target traits in plants grown at 25/22 °C and 15/13 °C, respectively. Only four QTLs were clearly identified in both temperatures regimes for the same traits, demonstrating that the genetic control of the performance of the photosynthetic apparatus differed, depending on the temperature regime. A major QTL for the cold-tolerance of photosynthesis was identified on chromosome 6. This QTL alone explained 37.4 of the phenotypic variance in the chronic photoinhibition at low temperature and was significantly involved in the expression of six other traits, including the rate of carbon fixation and shoot dry matter accumulation, indicating that the tolerance to photoinhibition is a key factor in the tolerance of maize to low growth temperature. An additional QTL on chromosomes 2 corresponded to a QTL identified previously in another population, suggesting some common genetic basis of the cold-tolerance of photosynthesis in different maize germplasms.     

玉米抗甘蔗花叶病毒基因的比较定位

收集了玉米抗甘蔗花叶病毒基因/QTL定位信息, 借助玉米遗传图谱IBM2 2005 Neighbors进行了整合。在国内外研究中, 累计报道81个抗病毒基因位点, 分布在玉米7条染色体上, 比较定位发现这些位点集中分布于第3和6染色体。采用元分析技术, 确定3个“一致性”抗病毒QTL, 其中1个位于第3染色体, 在遗传图谱IBM2 2005 Neighbors上覆盖的范围为6.44 cM; 2个位于第6染色体, 覆盖范围分别为6.16 cM和27.48 cM。借助比较基因组学策略, 在第3染色体“一致性”QTL区间内筛选出4个抗病位置候选基因。该研究结果为确定和克隆抗病主效基因提供了基础。     

拔节期与抽穗期玉米抗纹枯病相关QTL的初步定位

以玉米自交系R15(抗)×478(感)的F_2分离群体为作图群体,构建了包含146个SSR标记位点的遗传连锁图谱,覆盖玉米基因组1666 cM,平均图距11．4 cM。通过麦粒嵌入法对229个F_(2：4)家系进行人工接种纹枯病菌,于玉米拔节期和抽穗期进行纹枯病的抗性鉴定。应用复合区间作图法分析两个时期的抗病QTL及遗传效应。结果共检测到17个抗性QTL,其中以拔节期病情指数为指标共检测到9个QTL,分别位于第1、2、3、4、5、6、和10染色体上,可解释的表型变异为3．72%-9．26%;以抽穗期的病情指数为指标共在7条染色体上检测到10个抗玉米纹枯病的QTL,分布于第2、3、4、5、6、8和9染色体上。单个QTL可解释的表型变异为4．27%-9．27%。两个时期共检测出2个共同QTL,它们分别位于第2染色体的bnlgl662-bnlg1940区间和第6染色体的umc1006-umc1723区间。定位结果表明两个时期检测出的抗性QTL的差异表达与玉米不同发育时期基因的时空表达有密切关系,从而反映在纹枯病的抗性位点差异性上．这为玉米抗病选育提供新的信息。     

QTLs for grain dry milling properties, composition and vitreousness in maize recombinant inbred lines

Vitreousness and kernel hardness are important properties for maize processing and end-product quality. In order to examine the genetic basis of these traits, a recombinant inbred line population resulting from a cross between a flint line (F-2) and a semident line (Io) was used to search for vitreousness and kernel composition QTLs. Vitreousness was measured by image processing from a kernel section, while NIR spectroscopy was used to estimate starch, protein, cellulose, lipid and semolina yield. In addition, thousand-grain weight and grain weight per ear were measured. The MQTL method was used to map the QTLs for the different traits. An additional program allowed for the detection of interaction QTLs between markers. The total number of main-effect and interaction QTLs was similar. The QTLs were not evenly distributed but tended to cluster. Such clusters, mixing main-effect and interaction QTLs, were observed at six positions : on chromosomes 1, 2, 3, 6, 8 and 9. Two of them, on chromosomes 6 and 9, concerned both QTLs for kernel-weight traits and QTLs for kernel-composition traits (protein and cellulose). Technological-trait QTLs (vitreousness or semolina yield) were located less than 16 cM from a protein-content QTL on chromosome 2, and were co-located with lipid- and starch-content QTLs on chromosome 8. The co-location of a vitreousness and a semolina-yield QTL at the telomeric end of the chromosome 2 (Bin 2.02) is likely to be meaningful since measurement of these related traits, made by completely different methods (NIRS vs image processing), yielded very close QTLs. A similar location was previously reported independently for a kernel-friability QTL. Comparing the map location of the numerous loci for known-function genes it was shown that three zein loci were closely linked to QTLs for vitreousness on chromosome 3, for semolina yield and starch on chromosome 4, and for protein, cellulose and grain weight on chromosome 9. Some other candidate genes linked to starch precursor metabolism were also suggested on chromosomes 6 and 8. Received: 27 April 2000 / Accepted: 3 July 2000     

Genetic loci mapping associated with maize kernel number per ear based on a recombinant inbred line population grown under different nitrogen regimes

Kernel number per ear (KNE) is one of the most important yield-related agronomic traits in maize (Zea mays). To clarify its genetic basis, we made a quantitative trait locus (QTL) analysis of KNE in a recombinant inbred line population derived from lines Mo17 and Huangzao4, under two nitrogen (N) regimes. Seven QTLs, on chromosomes 4, 6 and 9, were mapped under the high N regime, which explained phenotypic variation ranging from 5.03 to 15.49%. Under the low N regime, three QTLs were located on chromosomes 6 and 9, which accounted for phenotypic variation ranging from 8.54 to 12.21%. These QTLs had different mapping intervals to their nearest markers, ranging from 0 to 16.5 cM. According to the chromosome positions and genetic effects of these QTLs, only seven QTLs for KNE were identified in our experiment, out of which three were found under both N regimes, on chromosomes 6 (one) and 9 (two); the other four were mapped only under the high N regime, on chromosomes 4 (three) and 6 (one). This information could be useful for developing marker-assisted selection in maize-breeding projects.     

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.     

Mapping of quantitative trait loci associated with chilling tolerance in maize (Zea mays L.) seedlings grown under field conditions

The effect of low growth temperature on morpho-physiological traits of maize was investigated by the means of a QTL analysis in a segregating F(2:3) population grown under field conditions in Switzerland. Chlorophyll fluorescence parameters, leaf greenness, leaf area, shoot dry weight, and shoot nitrogen content were investigated at the seedling stage for two years. Maize was sown on two dates in each year; thus, plants sown early were exposed to low temperature, whereas those sown later developed under more favourable conditions. The main QTLs involved in the functioning of the photosynthetic apparatus at low temperature were stable across the cold environments and were also identified under controlled conditions with suboptimal temperature in a previous study. Based on the QTL analysis, relationships between chlorophyll fluorescence parameters and leaf greenness were moderate. This indicates that the extent and functioning of the photosynthetic machinery may be under different genetic control. The functioning of the photosynthetic apparatus in plants developed at low temperature in the field did not noticeably affect biomass accumulation; since there were no co-locations between QTLs for leaf area and shoot dry weight, biomass accumulation did not seem to be carbon-limited at the seedling stage under cool conditions in the field.     

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

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

Identification of QTLs for eight agronomically important traits using an ultra-high-density map based on SNPs generated from high-throughput sequencing in sorghum under contrasting photoperiods

The productivity of sorghum is mainly determined by agronomically important traits. The genetic bases of these traits have historically been dissected and analysed through quantitative trait locus (QTL) mapping based on linkage maps with low-throughput molecular markers, which is one of the factors that hinder precise and complete information about the numbers and locations of the genes or QTLs controlling the traits. In this study, an ultra-high-density linkage map based on high-quality single nucleotide polymorphisms (SNPs) generated from low-coverage sequences (~0.07 genome sequence) in a sorghum recombinant inbred line (RIL) population was constructed through new sequencing technology. This map consisted of 3418 bin markers and spanned 1591.4 cM of genome size with an average distance of 0.5 cM between adjacent bins. QTL analysis was performed and a total of 57 major QTLs were detected for eight agronomically important traits under two contrasting photoperiods. The phenotypic variation explained by individual QTLs varied from 3.40% to 33.82%. The high accuracy and quality of this map was evidenced by the finding that genes underlying two cloned QTLs, Dw3 for plant height (chromosome 7) and Ma1 for flowering time (chromosome 6), were localized to the correct genomic regions. The close associations between two genomic regions on chromosomes 6 and 7 with multiple traits suggested the existence of pleiotropy or tight linkage. Several major QTLs for heading date, plant height, numbers of nodes, stem diameter, panicle neck length, and flag leaf width were detected consistently under both photoperiods, providing useful information for understanding the genetic mechanisms of the agronomically important traits responsible for the change of photoperiod.     

玉米叶绿素含量的QTL定位

为了探讨玉米叶绿素含量的遗传规律, 以A150-3-2×Mo17杂交组配的189个F2单株作为作图群体, 构建了具有112个标记位点的玉米分子遗传图谱, 于喇叭口期和开花期分别进行了玉米叶绿素a含量(chla), 叶绿素b含量(chlb), 其他叶绿素含量(chlc)和叶绿素总含量(chlz)4个性状的测定, 并进行QTL分析。在喇叭口期和开花期共检测到32个QTL, 分布在除第6和10染色体以外的其他染色体上。在喇叭口期检测到24个QTL, 分布于第1、2、3、5、7、8和9染色体上, 叶绿素a、叶绿素b、其他叶绿素和叶绿素总含量各检测到6个QTL, 在同一区间内检测到的4个性状的QTL之间的距离在0~2 cM之间。喇叭口期检测到控制叶绿素a、叶绿素b、其他叶绿素和叶绿素总含量的4个主效QTL位于第5染色体上的umc1098~bnlg557区间, 分别可解释表型变异的11.63%、10.3%、10.77%和11.51%。开花期检测到8个QTL, 分布于第4和5染色体上。其中叶绿素a、叶绿素b、其他叶绿素和叶绿素总含量各2个QTL。标记umc1098和bnlg557之间同时存在控制喇叭口期4个叶绿素含量性状的QTL和开花期控制叶绿素a和叶绿素b的QTL。标记umc2308和bnlg386之间只存在控制开花期4个叶绿素含量性状的QTL。     

Enrichment of a common wheat genetic map and QTL mapping for fatty acid content in grain

DArT and SSR markers were used to saturate and improve a previous genetic map of RILs derived from the cross Chuan35050 × Shannong483. The new map comprised 719 loci, 561 of which were located on specific chromosomes, giving a total map length of 4008.4 cM; the rest 158 loci were mapped to the most likely intervals. The average chromosome length was 190.9 cM and the marker density was 7.15 cM per marker interval. Among the 719 loci, the majority of marker loci were DArTs (361); the rest included 170 SSRs, 100 EST-SSRs, and 88 other molecular and biochemical loci. QTL mapping for fatty acid content in wheat grain was conducted in this study. Forty QTLs were detected in different environments, with single QTL explaining 3.6-58.1% of the phenotypic variations. These QTLs were distributed on 16 chromosomes. Twenty-two QTLs showed positive additive effects, with Chuan35050 increasing the QTL effects, whereas 18 QTLs were negative with increasing effects from Shannong483. Six sets of co-located QTLs for different traits occurred on chromosomes 1B, 1D, 2D, 5D, and 6B.     

Mapping of QTL for downy mildew resistance in maize

Quantitative trait loci (QTLs) of maize involved in mediating resistance to Peronosclerospora sorghi, the causative agent of sorghum downy mildew (SDM), were detected in a population of recombinant inbred lines (RILs) derived from the Zea mays L. cross between resistant (G62) and susceptible (G58) inbred lines. Field tests of 94 RILs were conducted over two growing seasons using artificial inoculation. Heritability of the disease reaction was high (around 70%). The mapping population of the RILs was also scored for restriction fragment length polymorphic (RFLP) markers. One hundred and six polymorphic RFLP markers were assigned to ten chromosomes covering 1648 cM. Three QTLs were detected that significantly affected resistance to SDM combined across seasons. Two of these mapped quite close together on chromosome 1, while the third one was on chromosome 9. The percentage of phenotypic variance explained by each QTL ranged from 12.4% to 23.8%. Collectively, the three QTLs identified in this study explained 53.6% of the phenotypic variation in susceptibility to the infection. The three resistant QTLs appeared to have additive effects. Increased susceptibility was contributed by the alleles of the susceptible parent. The detection of more than one QTL supports the hypothesis that several qualitative and quantitative genes control resistance to P. sorghi.     

Quantitative trait loci associated with body weight and abdominal fat traits on chicken chromosomes 3, 5 and 7

Body weight and abdominal fat traits in meat-type chickens are complex and economically important factors. Our objective was to identify quantitative trait loci (QTL) responsible for body weight and abdominal fat traits in broiler chickens. The Northeast Agricultural University Resource Population (NEAURP) is a cross between broiler sires and Baier layer dams. We measured body weight and abdominal fat traits in the F(2) population. A total of 362 F(2) individuals derived from four F(1) families and their parents and F(0) birds were genotyped using 29 fluorescent microsatellite markers located on chromosomes 3, 5 and 7. Linkage maps for the three chromosomes were constructed and interval mapping was performed to identify putative QTLs. Nine QTL for body weight were identified at the 5% genome-wide level, while 15 QTL were identified at the 5% chromosome-wide level. Phenotypic variance explained by these QTL varied from 2.95 to 6.03%. In particular, a QTL region spanning 31 cM, associated with body weight at 1 to 12 weeks of age and carcass weight at 12 weeks of age, was first identified on chromosome 5. Three QTLs for the abdominal fat traits were identified at the 5% chromosome-wide level. These QTLs explained 3.42 to 3.59% of the phenotypic variance. This information will help direct prospective fine mapping studies and can facilitate the identification of underlying genes and causal mutations for body weight and abdominal fat traits.     

A region of maize chromosome 2 affects response to downy mildew pathogens

Quantitative trait loci (QTLs) for downy mildew resistance in maize were identified based on co-segregation with linked restriction fragment length polymorphisms or simple sequence repeats in 220 F2 progeny from a cross between susceptible and resistant parents. Disease response was assessed on F3 families in nurseries in Egypt, Thailand, and South Texas and after inoculation in a controlled greenhouse test. Heritability of the disease reaction was high (around 93% in Thailand). One hundred and thirty polymorphic markers were assigned to the ten chromosomes of maize with LOD scores exceeding 4.9 and covering about 1,265 cM with an average interval length between markers of 9.5 cM. About 90% of the genome is located within 10 cM of the nearest marker. Three putative QTLs were detected in association with resistance to downy mildew in different environments using composite interval mapping. Despite environmental and symptom differences, one locus on chromosome 2 had a major effect and explained up to 70% of the phenotypic variation in Thailand where disease pressure was the highest. The other two QTLs on chromosome 3 and chromosome 9 had minor effects; each explained no more than 4% of the phenotypic variation. The three QTLs appeared to have additive effects on resistance, identifying one major gene and two minor genes that contribute to downy mildew resistance.     

QTL analysis of seed germination and pre-emergence growth at extreme temperatures in <Emphasis Type="Italic">Medicago truncatula</Emphasis>

Enhancing the knowledge on the genetic basis of germination and heterotrophic growth at extreme temperatures is of major importance for improving crop establishment. A quantitative trait loci (QTL) analysis was carried out at sub- and supra-optimal temperatures at these early stages in the model Legume Medicago truncatula. On the basis of an ecophysiological model framework, two populations of recombinant inbred lines were chosen for the contrasting behaviours of parental lines: LR5 at sub-optimal temperatures (5 or 10°C) and LR4 at a supra-optimal temperature (20°C). Seed masses were measured in all lines. For LR5, germination rates and hypocotyl growth were measured by hand, whereas for LR4, imbibition and germination rates as well as early embryonic axis growth were measured using an automated image capture and analysis device. QTLs were found for all traits. The phenotyping framework we defined for measuring variables, distinguished stages and enabled identification of distinct QTLs for seed mass (chromosomes 1, 5, 7 and 8), imbibition (chromosome 4), germination (chromosomes 3, 5, 7 and 8) and heterotrophic growth (chromosomes 1, 2, 3 and 8). The three QTL identified for hypocotyl length at sub-optimal temperature explained the largest part of the phenotypic variation (60% together). One digenic interaction was found for hypocotyl width at sub-optimal temperature and the loci involved were linked to additive QTLs for hypocotyl elongation at low temperature. Together with working on a model plant, this approach facilitated the identification of genes specific to each stage that could provide reliable markers for assisting selection and improving crop establishment. With this aim in view, an initial set of putative candidate genes was identified in the light of the role of abscissic acid/gibberellin balance in regulating germination at high temperatures (e.g. ABI4, ABI5), the molecular cascade in response to cold stress (e.g. CBF1, ICE1) and hypotheses on changes in cell elongation (e.g. GASA1, AtEXPA11) with changes in temperatures based on studies at the whole plant scale.     

粳稻蒸煮食味品质相关性状的QTL分析

以沈农265和丽江新团黑谷杂交衍生的重组自交系群体(RILs)为实验材料,对12个粳稻(Oryza sativa subsp.japonica)蒸煮食味品质相关性状进行QTL分析。共检测到29个蒸煮食味品质相关的QTLs,分布于除第8染色体外的11条染色体上,LOD值介于2.50–16.47之间,加性效应值为–132.69–471.85,单个QTL贡献率为10.36%–73.24%。在第6染色体RM508–RM253区域检测到1个蒸煮营养食味品质多效性QTL簇,其中q AC6表型贡献率最大,解释73.24%的表型变异;在第10染色体PM166–RM258区域检测到2个与蒸煮食味品质相关的QTLs,分别是控制口感的q CTS10和综合评分的q CCS10。此外,检测到15个与RVA特征谱相关的QTLs,在第6染色体RM253–RM402区域检测到3个与RVA谱特征值相关的QTLs,表型贡献率均大于12%。这些定位结果将为粳稻蒸煮食味相关品质的分子遗传机理研究奠定基础。     

GBS-SNP and SSR based genetic mapping and QTL analysis for drought tolerance in upland cotton

A recombinant inbred line mapping population of intra-species upland cotton was generated from a cross between the drought-tolerant female parent (AS2) and the susceptible male parent (MCU13). A linkage map was constructed deploying 1,116 GBS-based SNPs and public domain-based 782 SSRs spanning a total genetic distance of 28,083.03 cM with an average chromosomal span length of 1,080.12 cM with inter-marker distance of 10.19 cM.A total of 19 quantitative trait loci (QTLs) were identified in nine chromosomes for field drought tolerance traits. Chromosomes 3 and 8 harbored important drought tolerant QTLs for chlorophyll stability index trait while for relative water content trait, three QTLs on chromosome 8 and one QTL each on chromosome 4, 12 were identified. One QTL on each chromosome 8, 5, and 7, and two QTLs on chromosome 15 linking to proline content were identified. For the nitrate reductase activity trait, two QTLs were identified on chromosome 3 and one on each chromosome 8, 13, and 26. To complement our QTL study, a meta-analysis was conducted along with the public domain database and resulted in a consensus map for chromosome 8. Under field drought stress, chromosome 8 harbored a drought tolerance QTL hotspot with two in-house QTLs for chlorophyll stability index (qCSI01, qCSI02) and three public domain QTLs (qLP.FDT_1, qLP.FDT_2, qCC.ST_3). Identified QTL hotspot on chromosome 8 could play a crucial role in exploring abiotic stress-associated genes/alleles for drought trait improvement.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12298-021-01041-y.     

Genetic analysis of grain protein-content,grain yield and thousand-kernel weight in bread wheat

Grain yield and grain protein content are two very important traits in bread wheat. They are controlled by genetic factors, but environmental conditions considerably affect their expression. The aim of this study was to determine the genetic basis of these two traits by analysis of a segregating population of 194 F(7) recombinant inbred lines derived from a cross between two wheat varieties, grown at six locations in France in 1999. A genetic map of 254 loci was constructed, covering about 75% of the bread wheat genome. QTLs were detected for grain protein-content (GPC), yield and thousand-kernel weight (TKW). 'Stable' QTLs (i.e. detected in at least four of the six locations) were identified for grain protein-content on chromosomes 2A, 3A, 4D and 7D, each explaining about 10% of the phenotypic variation of GPC. For yield, only one important QTL was found on chromosome 7D, explaining up to 15.7% of the phenotypic variation. For TKW, three QTLs were detected on chromosomes 2B, 5B and 7A for all environments. No negative relationships between QTLs for yield and GPC were observed. Factorial Regression on GxE interaction allowed determination of some genetic regions involved in the differential reaction of genotypes to specific climatic factors, such as mean temperature and the number of days with a maximum temperature above 25 degrees C during grain filling.     

测序水稻品种SSR遗传连锁图谱的构建及其农艺性状基因座分析

利用测序水稻品种"Nipponbare（粳）/广陆矮4号（籼）"杂交F2群体90个单株为作图群体,构建含148个SSR标记的水稻遗传连锁图谱,覆盖基因组全长1737.81cM,标记间平均距11.90cM。利用该图谱及Excel2000和Mapmaker/QTL1.1b软件对分蘖数、穗数、穗长、主穗长、株高、剑叶长等六个农艺性状间的相互关系和基因位点进行分析,结果在LOD>2.2和P<0.005的条件下共检测到28个QTLs,它们分布在水稻所有染色体上,单个QTL对性状的分子贡献率11.1%-42.9%,其中大于20%有10个,并对选用已测序材料为亲本构建图谱来探讨水稻农艺性状的分子基础及其育种意义进行了讨论。