Identification of quantitative trait loci controlling heading date in rice using a high-density linkage map

 Quantitative trait locus (QTL) analysis has been carried out to identify genes conferring heading date in rice. One hundred and eighty six F₂ plants derived from a cross between a japonica variety, Nipponbare, and an indica variety, Kasalath, were used as a segregating population for QTL mapping and more than 850 markers were employed to identify QTLs. Scan-analysis revealed the existence of two QTLs with large effects, Hd-1 and Hd-2, one in the middle of chromosome 6 and one at the end of chromosome 7, respectively. For both loci, the Kasalath alleles reduced days-to-heading. In addition, three QTLs with minor effects, Hd-3, Hd-4 and Hd-5, were found to be located on chromosomes 6, 7 and 8 based on a secondary scan analysis which was carried out by removing the phenotypic effects of Hd-1 and Hd-2. For the three secondary loci, the Nipponbare alleles reduced days-to-heading. The five QTLs explained 84% of the total phenotypic variation in the F₂ population based on a multiple-QTL model. The presence of a digenic interaction between Hd-1 and Hd-2 was clearly suggested. Received: 18 March 1997 / Accepted: 24 June 1997     

Detection of quantitative trait loci controlling pre-harvest sprouting resistance by using backcrossed populations of japonica rice cultivars

Backcrossed inbred lines (BILs) and a set of reciprocal chromosome segment substitution lines (CSSLs) derived from crosses between japonica rice cultivars Nipponbare and Koshihikari were used to detect quantitative trait loci (QTLs) for pre-harvest sprouting resistance. In the BILs, we detected one QTL on chromosome 3 and one QTL on chromosome 12. The QTL on the short arm of chromosome 3 accounted for 45.0% of the phenotypic variance and the Nipponbare allele of the QTL increased germination percentage by 21.3%. In the CSSLs, we detected seven QTLs, which were located on chromosomes 2, 3 (two), 5, 8 and 11 (two). All Nipponbare alleles of the QTLs were associated with an increased rate of germination. The major QTL for pre-harvest sprouting resistance on the short arm of chromosome 3 was localized to a 474-kbp region in the Nipponbare genome by the SSR markers RM14240 and RM14275 by using 11 substitution lines to replace the different short chromosome segments on chromosome 3. This QTL co-localized with the low-temperature germinability gene qLTG3-1. The level of germinability under low temperature strongly correlated with the level of pre-harvest sprouting resistance in the substitution lines. Sequence analyses revealed a novel functional allele of qLTG3-1 in Nipponbare and a loss-of-function allele in Koshihikari. The allelic difference in qLTG3-1 between Nipponbare and Koshihikari is likely to be associated with differences in both pre-harvest sprouting resistance and low-temperature germinability.     

A quantitative trait locus for cold tolerance at the booting stage on rice chromosome 8

A quantitative trait locus (QTL) for cold tolerance at the booting stage of a cold-tolerant rice breeding line, Hokkai-PL9, was analyzed. A total of 487 simple sequence repeat (SSR) markers distributed throughout the genome were used to survey for polymorphism between Hokkai-PL9 and a cold-sensitive breeding line, Hokkai287, and 54 markers were polymorphic. Single marker analysis revealed that markers on chromosome 8 are associated with cold tolerance. By interval mapping using an F₂ population between Hokkai-PL9 and Hokkai287, a QTL for cold tolerance was detected on the short arm of chromosome 8. The QTL explains 26.6% of the phenotypic variance, and its additive effect is 11.4%. Substitution mapping suggested that the QTL is located in a 193-kb interval between SSR markers RM5647 and PLA61. We tentatively designated the QTL as qCTB8 (quantitative trait locus for cold tolerance at the booting stage on chromosome 8).     

QTL Analysis of Aluminum Resistance in Rice (Oryza sativa L.)

Aluminum (Al) toxicity is considered as one of the primary causes of low-rice productivity in acid soils. In the present study, quantitative trait loci (QTLs) controlling Al resistance based on relative root elongation (RRE) were dissected using a complete linkage map and a recombinant inbred lines (RILs) derived from a cross of Al-tolerant japonica cultivar Asominori (Oryza sativa L.) and Al-sensitive indica cultivar IR24 (O. sativa L.). A total of three QTLs (qRRE-1, qRRE-9, and qRRE-11) were detected on chromosomes 1, 9, and 11 with LOD score ranging from 2.64 to 3.60 and the phenotypic variance explained from 13.5 to 17.7%. The Asominori alleles were all associated with Al resistance at all the three QTLs. The existence of these QTLs was confirmed using Asominori chromosome segment substitution lines (CSSLs) in IR24 genetic background (IAS). By QTL comparative analysis, the two QTLs (qRRE-1and qRRE-9) on chromosomes 1 and 9 appeared to be consistent among different rice populations while qRRE-11 was newly detected and syntenic with a major Al resistance gene on chromosome 10 of maize. This region may provide an important case for isolating genes responsible for different mechanisms of Al resistance among different cereals. These results also provide the possibilities of enhancing Al resistance in rice breeding program by marker-assisted selection (MAS) and pyramiding QTLs.     

Molecular Genetic Analysis of QTLs for Ferulic Acid Content in Dried Straw of Rice (Oryza sativa L.)

Phenolic acids are secondary metabolic organic compounds produced by plants and often are mentioned as allelochemicals. This study was conducted to determine the genetic basis controlling the ferulic acid content of rice straw in a recombinant inbred (RI) population derived from a cross between a japonica variety, Asominori, with a higher content of ferulic acid, and an indica variety, IR24, with a lower content, using 289 RFLP markers. Continuous distributions and transgressive segregations of ferulic acid content were observed in the RI population, which showed that ferulic acid content in rice straw was quantitatively inherited. Single marker analysis and composite interval mapping identified three quantitative trait loci (QTLs) for ferulic acid content with LOD values of 2.03 (chromosome 3), 3.16 (chromosome 6), and 3.06 (chromosome 7); all three had increased additive effects (13.5, 18.3, and 18.1 g g ^–1) from the Asominori parent and accounted for 5.5, 16.9, and 12.8% of total phenotypic variation, respectively. This is the first report on the identification of QTLs associated with ferulic acid and their chromosomal localization on the molecular map of rice. The tightly linked molecular markers that flank the QTLs might be useful in breeding and selection of varieties with higher phenolic acid content.     

Genetic dissection and pyramiding of quantitative traits for panicle architecture by using chromosomal segment substitution lines in rice

To understand the genetic basis of yield-related traits of rice, we developed 39 chromosome segment substitution lines (CSSLs) from a cross between an average-yielding japonica cultivar, Sasanishiki, as the recurrent parent and a high-yielding indica cultivar, Habataki, as the donor. Five morphological components of panicle architecture in the CSSLs were evaluated in 2 years, and 38 quantitative trait loci (QTLs) distributed on 11 chromosomes were detected. The additive effect of each QTL was relatively small, suggesting that none of the QTLs could explain much of the phenotypic difference in sink size between Sasanishiki and Habataki. We developed nearly isogenic lines for two major QTLs, qSBN1 (for secondary branch number on chromosome 1) and qPBN6 (for primary branch number on chromosome 6), and a line containing both. Phenotypic analysis of these lines revealed that qSBN1 and qPBN6 contributed independently to sink size and that the combined line produced more spikelets. This suggests that the cumulative effects of QTLs distributed throughout the genome form the major genetic basis of panicle architecture in rice. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. T. Ando and T. Yamamoto contributed equally to this work.     

Quantitative trait loci mapping of resistance to Laodelphax striatellus (Homoptera: Delphacidae) in rice using recombinant inbred lines

Laodelphax striatellus Fallén (Homoptera: Delphacidae), is a serious pest in rice, Oryza sativa L., production. A mapping population consisting of 81 recombinant inbred lines (RILs), derived from a cross between japonica' Kinmaze' and indica' DV85' rice, was used to detect quantitative trait loci (QTLs) for the resistance to L. striatellus. Seedbox screening test (SST), antixenosis test, and antibiosis test were used to evaluate the resistance response of the two parents and 81 RILs to L. striatellus at the seedling stage, and composite interval mapping was used for QTL analysis. When the resistance was measured by SST method, two QTLs conferring resistance to L. striatellus were mapped on chromosome 11, namely, Qsbph11a and Qsbph11b, with log of odds scores 2.51 and 4.38, respectively. The two QTLs explained 16.62 and 27.78% of the phenotypic variance in this population, respectively. In total, three QTLs controlling antixenosis against L. striatellus were detected on chromosomes 3, 4, and 11, respectively, accounting for 37.5% of the total phenotypic variance. Two QTLs expressing antibiosis to L. striatellus were mapped on chromosomes 3 and 11, respectively, explaining 25.9% of the total phenotypic variance. The identified QTL located between markers XNpb202 and C1172 on chromosome 11 was detected repeatedly by three different screening methods; therefore, it may be important to confer the resistance to L. striatellus. Once confirmed in other mapping populations, these QTLs should be useful in breeding for resistance to L. striatellus by marker-assisted selection of different resistance genes in rice varieties.     

Identification of major quantitative trait loci qSBR11-1 for sheath blight resistance in rice

Sheath blight caused by Rhizoctonia solani Kühn is one of the important diseases of rice, resulting in heavy yield loss in rice every year. No rice line resistant to sheath blight has been identified till date. However, in some rice lines a high degree of resistance to R. solani has been observed. An indica rice line, Tetep, is a well documented source of durable and broad spectrum resistance to rice blast as well as quantitative resistance to sheath blight. The present study identified genetic loci for quantitative resistance to sheath blight in rice line Tetep. A mapping population consisting of 127 recombinant inbred lines derived from a cross between rice cultivars HP2216 (susceptible) and Tetep (resistant to sheath blight) was evaluated for sheath blight resistance and other agronomic traits for 4 years across three locations. Based on sheath blight phenotypes and genetic map with 126 evenly distributed molecular markers, a quantitative trait loci (QTLs) contributing to sheath blight resistance was identified on long arm of chromosome 11. Two QTL mapping approaches i.e., single marker analysis and composite interval mapping in multi environments were used to identify QTLs for sheath blight resistance and agronomical traits. The QTL qSBR11-1 for sheath blight resistance was identified between the marker interval RM1233 (26.45 Mb) to sbq33 (28.35 Mb) on chromosome 11. This region was further narrowed down to marker interval K39516 to sbq33 (~0.85 Mb) and a total of 154 genes were predicted including 11 tandem repeats of chitinase genes which may be responsible for sheath blight resistance in rice line Tetep. A set of 96 varieties and a F₂ population were used for validation of markers linked to the QTL region. The results indicate that there is very high genetic variation among varieties at this locus, which can serve as a starting point for allele mining of sheath blight resistance.     

Identification and analysis of QTLs controlling cold tolerance at the reproductive stage and validation of effective QTLs in cold-tolerant genotypes of rice (Oryza sativa L.)

Low temperature or cold stress is one of the major constraints of rice production and productivity in temperate rice-growing countries and high-altitude areas in the tropics. Even though low temperature affects the rice plant in all stages of growth, the percent seed set is damaged severely by cold and this reduces the yield potential of cultivars significantly. In this study, a new source of cold-tolerant line, IR66160-121-4-4-2, was used as a donor parent with a cold-sensitive cultivar, Geumobyeo, to produce 153 F₈ recombinant inbred lines (RILs) for quantitative trait locus (QTL) analysis. QTL analysis with 175 polymorphic simple sequence repeat (SSR) markers and composite interval mapping identified three main-effect QTLs (qPSST-3, qPSST-7, and qPSST-9) on chromosomes 3, 7, and 9. The SSR markers RM569, RM1377, and RM24545 were linked to the identified QTLs for cold tolerance with respect to percent seed set using cold-water (18–19°C) irrigation in the field and controlled air temperature (17°C) in the greenhouse. The total phenotypic variation for cold tolerance contributed by the three QTLs was 27.4%. RILs with high percent seed set under cold stress were validated with linked DNA markers and by haplotype analysis that revealed the contribution of progenitor genomes from the tropical japonica cultivar Jimbrug (Javanica) and temperate japonica cultivar Shen-Nung89-366. Three QTLs contributed by the cold-tolerant parent were identified which showed additive effect on percent seed set under cold treatment. This study demonstrated the utility of a new phenotyping method as well as the identification of SSR markers associated with QTLs for selection of cold-tolerant genotypes to improve temperate rice production.     

Grain yield responses to moisture regimes in a rice population: association among traits and genetic markers

Drought is a major constraint to rice (Oryza sativa L.) production in rainfed and poorly irrigated environments. Identifying genomic regions influencing the response of yield and its components to water deficits will aid our understanding of the genetic mechanism of drought tolerance (DT) of rice and the development of DT varieties. Grain yield (GY) and its components of a recombinant inbred population developed from a lowland rice and an upland rice were investigated under different water levels in 2003 and 2004 in a rainout DT screening facility. Correlation and path analysis indicated that spikelet fertility (SF) was particularly important for grain yield with direct effect (P=0.60) under drought stress, while spikelet number per panicle (SN) contributed the most to grain yield (P=0.41) under well-watered condition. A total of 32 quantitative trait loci (QTLs) for grain yield and its components were identified. The phenotypic variation explained by individual QTLs varied from 1.29% to 14.76%. Several main effect QTLs affecting SF, 1,000-grain weight (TGW), panicle number (PN), and SN were mapped to the same regions on chromosome 4 and 8. These QTLs were detected consistently across 2 years and under both water levels in this study. Several digenic interactions among yield components were also detected. The identification of genomic regions associated with GY and its components under stress will be useful to improve drought tolerance of rice by marker-aided approaches.G. H. Zou and H. W. Mei contribute equally to this work.     

Location of genes involved in ear compactness in wheat (Triticum aestivum) by means of molecular markers

Quantitative trait loci (QTLs) for three traits related to ear morphology (spike length, number of spikelets, and compactness as the ratio between number of spikelets and spike length) in wheat (Triticum aestivum L.) were mapped in a doubled-haploid (DH) population derived from the cross between the cultivars Courtot and Chinese Spring. A molecular marker linkage map of this cross that had previously been constructed based on 187 DH lines and 380 markers was used for QTL mapping. The genome was well covered (85%) except chromosomes 1D and 4D and a set of anchor loci regularly spaced (one marker each 15.5 cM) were chosen for marker regression analysis. The presence of a QTL was declared at a significance threshold = 0.001. The population was grown in one location under field conditions during three years (1994, 1995 and 1998). For each trait, 4 to 6 QTLs were identified with individual effects ranging between 6.9% and 21.8% of total phenotypic variation. Several QTLs were detected that affected more than one trait. Of the QTLs 50% were detected in more than one year and two of them (number of spikelets on chromosome 2B, and compactness on chromosome 2D) emerged from the data from the three years. Only one QTL co-segregated with the gene Q known to be involved in ear morphology, namely the speltoid phenotype. However, this chromosome region explained only a minor part of the variation (7.5–11%). Other regions had a stronger effect, especially two previously unidentified regions located on chromosomes 1A and 2B. The region on the long arm of chromosome 1A was close to the locus XksuG34-1A and explained 12% of variation in spike length and 10% for compactness. On chromosome 2B, the QTL was detected for the three traits near the locus Xfbb121-2B. This QTL explained 9% to 22% of variation for the traits and was located in the same region as the gene involved in photoperiod response (Ppd2). Other regions were located at homoeologous positions on chromosomes 2A and 2D.     

水稻粒长QTL定位与主效基因的遗传分析

该研究利用短粒普通野生稻矮杆突变体和长粒栽培稻品种KJ01组配杂交组合F_1,构建分离群体F_2;并对该群体粒长进行性状遗传分析,利用平均分布于水稻的12条染色体上的132对多态分子标记对该群体进行QTL定位及主效QTLs遗传分析,为进一步克隆新的主效粒长基因奠定基础,并为水稻粒形育种提供理论依据。结果表明:(1)所构建的水稻杂交组合分离群体F_2的粒长性状为多基因控制的数量性状。(2)对543株F_2分离群体进行QTL连锁分析,构建了控制水稻粒长的连锁遗传图谱,总长为1 713.94 cM,共检测出24个QTLs,只有3个表现为加性遗传效应,其余位点均表现为遗传负效应。(3)检测到的3个主效QTLs分别位于3号染色体的分子标记PSM379～RID24455、RID24455～RM15689和RM571～RM16238之间,且三者对表型的贡献率分别为54.85%、31.02%和7.62%。(4)在标记PSM379～RID24455之间已克隆到的粒长基因为该研究新发现的主效QTL位点。     

Quantitative trait locus analysis of tuber dormancy in diploid potato (Solanum spp.)

Quantitative trait locus (QTL) analysis for tuber dormancy was performed in a diploid potato population (TRP133) consisting of 110 individuals. The female parent was a hybrid between haploid S. tuberosum (2x) and S. chacoense, while the male parent was a S. phureja clone. The population was characterized for ten isozyme loci, 44 restriction fragment length polymorphisms (RFLPs) and 63 random amplified polymorphic DNAs (RAPDs). Eighty-seven of these loci segregating from the female parent were utilized to develop a linkage map that comprised 10 of the 12 chromosomes in the genome. Dormancy, as measured by days-to-sprouting after harvest, ranged from 10 to 90 days, with a mean of 19 days. QTLs were mapped by conducting one-way analyses of variance for each marker locus by dormancy combination. Twenty-two markers had a significant association with dormancy, identifying six putative QTLs localized on each of chromosomes 2, 3, 4, 5, 7 and 8. The QTL with the strongest effect on dormancy was detected on chromosome 7. A multilocus model was developed using the locus with highest R² value in each QTL. This model explained 57.5% of the phenotypic variation for dormancy. Seven percent of possible epistatic interactions among significant markers were significant when tested through two-way analyses of variance. When these were included in the main-effects model, it explained 72.1% of the phenotypic variation for dormancy. QTL analysis in potato, the methodology to transfer traits and interactions into the 4x level, and QTLs of value for marker-assisted selection, are discussed.     

Genetic mapping identifies a rice naringenin O-glucosyltransferase that influences insect resistance

Naringenin, the biochemical precursor for predominant flavonoids in grasses, provides protection against UV damage, pathogen infection and insect feeding. To identify previously unknown loci influencing naringenin accumulation in rice (Oryza sativa), recombinant inbred lines derived from the Nipponbare and IR64 cultivars were used to map a quantitative trait locus (QTL) for naringenin abundance to a region of 50 genes on rice chromosome 7. Examination of candidate genes in the QTL confidence interval identified four predicted uridine diphosphate-dependent glucosyltransferases (Os07g31960, Os07g32010, Os07g32020 and Os07g32060). In vitro assays demonstrated that one of these genes, Os07g32020 (UGT707A3), encodes a glucosyltransferase that converts naringenin and uridine diphosphate-glucose to naringenin-7-O-β-d -glucoside. The function of Os07g32020 was verified with CRISPR/Cas9 mutant lines, which accumulated more naringenin and less naringenin-7-O-β-d -glucoside and apigenin-7-O-β-d -glucoside than wild-type Nipponbare. Expression of Os12g13800, which encodes a naringenin 7-O-methyltransferase that produces sakuranetin, was elevated in the mutant lines after treatment with methyl jasmonate and insect pests, Spodoptera litura (cotton leafworm), Oxya hyla intricata (rice grasshopper) and Nilaparvata lugens (brown planthopper), leading to a higher accumulation of sakuranetin. Feeding damage from O. hyla intricata and N. lugens was reduced on the Os07g32020 mutant lines relative to Nipponbare. Modification of the Os07g32020 gene could be used to increase the production of naringenin and sakuranetin rice flavonoids in a more targeted manner. These findings may open up new opportunities for selective breeding of this important rice metabolic trait.     

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.     

水稻糙米重金属Cd含量的QTL分析

镉(Cd²⁺)是一种分布较广泛、毒性较强的一种重金属, 文章利用韭菜青×IR26杂交衍生的一个重组自交系群体(Recombinant inbred lines, RIL)及构建的SSR分子遗传图谱, 对控制糙米中Cd²⁺含量的QTL进行分析, 为选育籽粒中Cd²⁺低吸收或低积累的水稻品种提供参考。结果表明, 在Cd²⁺胁迫(5 mg/kg)处理条件下, 共检测到2个与糙米Cd²⁺含量有关的QTLs, 分别位于水稻第11染色体上的标记RM6288-RM6544和RM167-RM5704之间, 其中qCCBR-11a对表型贡献率为11.17%, 加性效应0.089; qCCBR-11b对表型变异贡献率为7.66%, 加性效应0.075。相关分析显示, 糙米Cd²⁺含量与株高、每穗总粒数、每穗实粒数、结实率和千粒重等产量性状的相关性均不显著, 糙米中Cd²⁺含量是一个相对独立、由基因控制的遗传性状。     

QTL analysis for rice grain length and fine mapping of an identified QTL with stable and major effects

Grain length in rice plays an important role in determining rice appearance, milling, cooking and eating quality. In this study, the genetic basis of grain length was dissected into six main-effect quantitative trait loci (QTLs) and twelve pairs of epistatic QTLs. The stability of these QTLs was evaluated in four environments using an F₇ recombinant inbred line (RIL) population derived from the cross between a Japonica variety, Asominori, and an Indica variety, IR24. Moreover, chromosome segment substitution lines (CSSLs) harboring each of the six main-effect QTLs were used to evaluate gene action of QTLs across eight environments. A major QTL denoted as qGL-3a, was found to express stably not only in the isogenic background of Asominori but also in the recombinant background of Asominori and IR24 under multiple environments. The IR24 allele at qGL-3a has a positive effect on grain length. Based on the test of advanced backcross progenies, qGL-3a was dissected as a single Mendelian factor, i.e., long rice grain was controlled by a recessive gene gl-3. High-resolution genetic and physical maps were further constructed for fine mapping gl-3 by using 11 simple sequence repeat (SSR) markers designed using sequence information from seven BAC/PAC clones and a BC₄F₂ population consisting of 2,068 individuals. Consequently, the gl-3 gene was narrowed down to a candidate genomic region of 87.5 kb long defined by SSR markers RMw357 and RMw353 on chromosome 3, which provides a basis for map-based cloning of this gene and for marker-aided QTL pyramiding in rice quality breeding.     

Mapping of the quantitative trait locus (QTL) conferring partial resistance to rice leaf blast disease

Malaysian rice, Pongsu Seribu 2, has wide-spectrum resistance against blast disease. Chromosomal locations conferring quantitative resistance were detected by linkage mapping with SSRs and quantitative trait locus (QTL) analysis. For the mapping population, 188 F₃ families were derived from a cross between the susceptible cultivar, Mahsuri, and a resistant variety, Pongsu Seribu 2. Partial resistance to leaf blast in the mapping population was assessed. A linkage map covering ten chromosomes and consisting of 63 SSR markers was constructed. 13 QTLs, including 6 putative and 7 putative QTLs, were detected on chromosomes 1, 2, 3, 5, 6, 10, 11 and 12. The resulting phenotypic variation due to a single QTL ranged from 2 to 13 %. These QTLs accounted for approx. 80 % of the total phenotypic variation within the F₃ population. Therefore, partial resistance to blast in Pongsu Seribu 2 is due to combined effects of multiple loci with major and minor effects.     

Mapping of quantitative trait loci controlling low-temperature germinability in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

Low-temperature germination is one of the major determinants for stable stand establishment in the direct seeding method in temperate regions, and at high altitudes of tropical regions. Quantitative trait loci (QTLs) controlling low-temperature germinability in rice were identified using 122 backcross inbred lines (BILs) derived from a cross between temperate japonica varieties, Italica Livorno and Hayamasari. The germination rate at 15°C was measured to represent low-temperature germination and used for QTL analysis. The germination rate at 15°C for 7 days of Italica Livorno and Hayamasari was 98.7 and 26.8%, respectively, and that of BILs ranged from 0 to 83.3%. Using restriction fragment length polymorphism (RFLP) and simple sequence repeat (SSR) markers, we constructed a linkage map which corresponded to about 90% of the rice genome. Three putative QTLs associated with low-temperature germination were detected. The most effective QTL, qLTG-3-1 on chromosome 3, accounted for 35.0% of the total phenotypic variation for low-temperature germinability. Two additional QTLs, qLTG-3-2 on chromosome 3 and qLTG-4 on chromosome 4, were detected and accounted for 17.4 and 5.5% of the total phenotypic variation, respectively. The Italica Livorno alleles in all detected QTLs increased the low-temperature germination rate.Communicated by F. Salamini     

Identification of QTLs affecting traits of agronomic importance in a recombinant inbred population derived from a subspecific rice cross

To detect QTLs controlling traits of agronomic importance in rice, two elite homozygous lines 9024 and LH422, which represent the indica and japonica subspecies of rice (Oryza sativa), were crossed. Subsequently a modified single-seed-descent procedure was employed to produce 194 recombinant inbred lines (F₈). The 194 lines were genotyped at 141 RFLP marker loci and evaluated in a field trial for 13 quantitative traits including grain yield. Transgressive segregants were observed for all traits examined. The number of significant QTLs (LOD 2.0) detected affecting each trait ranged from one to six. The percentage of phenotypic variance explained by each QTL ranged from 5.1% to 73.7%. For those traits for which two or more QTLs were detected, increases in the traits were conditioned by indica alleles at some QTLs Japonica alleles at others. No significant evidence was found for epistasis between markers associated with QTLs and all the other markers. Pleitropic effects of single QTLs on different traits are suggested by the observation of clustering of QTLs. No QTL for traits was found to map to the vicinity of major gene loci governing the same traits qualitatively. Evidence for putative orthologous QTLs across rice, maize, oat, and barley is discussed.