Mapping quantitative trait loci underlying the cooking and eating quality of rice using a DH population

The cooking and eating quality of rice has attracted more attention recently. In a comprehensive effort to unravel its genetic basis, we conducted a genome-wide analysis of six traits representing the cooking and eating quality of rice grain, namely, amylose content (AC), gel consistency (GC), gelatinization temperature (GT), water absorption (WA), cooked rice elongation (CRE) and volume expansion (VE) using a DH population derived from the anther culture of an F₁ hybrid between WYJ 2 (japonica) and Zhenshan 97B (indica). For each trait, one to three quantitative trait loci (QTL) were found, which were located on chromosomes 1, 2, 3, 6, 11. QTL analysis revealed a major QTL specifying GT, located at the interval RM276-RM121, which should be the same locus as the alkali degeneration gene (alk), while for each of the remaining five traits the QTL explaining the largest proportion of variance was located on the short arm of chromosome 6, centered at RM190 (found in the waxy gene). Our results, in combination with previous reports, further confirmed that either the waxy gene itself or a genomic region tightly linked to it plays a major role in determining the cooking and eating quality of rice.     

Identification of quantitative trait loci associated with germination using chromosome segment substitution lines of rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

Rapid and uniform seed germination under diverse environmental conditions is a desirable characteristic for most crop plants, such as rice, wheat, and maize. However, the genetic base of the variations in the rate of germination is not well understood. In this study, quantitative trait loci (QTL) for germination rate were mapped with a set of 143 chromosome segment substitution lines (CSSL) each contains a small genomic fragment from a japonica variety Nipponbare in the uniform genetic background of an indica variety Zhenshan97. Nine CSSL showed significantly lower germination rate than that in Zhenshan97. Four germination-related QTL were identified located on chromosomes 2, 5, 6 and 10, at which all japonica alleles decreased germination rate. By using the CSSL-derived F2 population, a major QTL (qGR2) on chromosome 2 was confirmed, and delimited to a 10.4 kb interval containing three putative candidate genes, of which OsMADS29 was only expressed preferentially in the seed. These results would facilitate cloning of the major gene that affects germination rate, and provide an insight into the genetic basis of germination.     

Comparison of quantitative trait loci controlling seedling characteristics at two seedling stages using rice recombinant inbred lines

A better understanding of the genetics of seedling characteristics in rice could be helpful in improving rice varieties. Zhenshan 97 and Minghui 63, the parents of Shanyou 63, an elite hybrid developed during the last decade in China, vary greatly with respect to their physiological and morphological traits at the seedling growth stage. In this study, we used a population of 240 recombinant inbred lines derived from a cross between Zhenshan 97 and Minghui 63 to identify quantitative trait loci (QTL) for seedling characteristics. All plant material was grown in hydroponic culture. Data for the following characters were collected at 30 days and 40 days post-sowing: plant height, shoot dry matter weight (SDW), maximum root length, root dry weight (RDW), total dry weight , and root-shoot ratio (the ratio of SDW to RDW). Analysis using composite interval mapping detected 16 QTL for the six traits in 30-day-old seedlings. Of these 16 QTL, Minghui 63 alleles increased trait values at only two of them. The QTL in the vicinity of R3166 on chromosome 5 simultaneously influenced PH, SDW, MRL, RDW, and TDW in the same direction. Twenty QTL were detected for the same traits in the 40-day-old seedlings. However, at this stage Minghui 63 alleles increased trait values at eight QTL. The QTL linked to R3166 also affected PH, SDW, MRL, RDW, and TDW. Only four QTL were common to the two stages. These results clearly indicate that different genes (QTL) control the same traits during different time intervals. Zhenshan 97 alleles had positive effects during the first 30 days of seedling growth, but thereafter the positive effects of Minghui 63 alleles on seedling growth gradually became more pronounced.     

Improving rice yield and quality by QTL pyramiding

To facilitate marker-assisted transfer of desirable genes for improvement of yield traits, we used a set of backcross recombinant inbred lines (BRIL) derived from two elite parental lines, ‘Zhenshan97’ and ‘93-11’, to resolve a quantitative trait loci (QTL) cluster for heading date and yield-related traits in rice. Four main-effect QTL (qHD6.1, qHD6.2, qHD7, and qHD8) and four epistatic QTL affecting heading date in the BRIL were detected in two experimental trials. The major QTL (qHD8) was confirmed in three heterogeneous inbred families (HIF) that segregated for this target region, and narrowed down to a 20-kb segment in a large HIF-derived population. qHD8 was found to interact with qHD7 and had a pleiotropic effect responsible for heading date and yield components. To test usability of the identified QTL in rice improvement, we further developed near-isogenic lines (NIL) containing one or more target genes by marker-assisted transfer of ‘93-11’ alleles at qHD8, qHD7, and qHD6.1, and the GS3 gene for grain size into ‘Zhenshan97’. The pyramid line NIL(qHD8 + GS3) had higher yield potential, longer grains, and a more suitable heading date than ‘Zhenshan97’. Comparison of the NIL showed existence of epistasis between alleles at different loci and background effect on qHD8, which are very important for pyramiding of desirable alleles at the target QTL. These results will be particularly useful not only to understand the genetic basis of yield-related traits but also to improve the efficiency of marker-assisted selection for favorable loci in rice breeding programs.     

Genetic basis of 17 traits and viscosity parameters characterizing the eating and cooking quality of rice grain

A recombinant inbred line population derived from a cross between Zhenshan 97 and Delong 208 was used to analyze the genetic basis of the cooking and eating quality of rice as reflected by 17 traits (or parameters). These traits include amylose content (AC), gel consistency (GC), alkali spreading value (ASV), cooked rice elongation (CRE), and 13 parameters from the viscosity profile. All the traits, except peak paste viscosity (PKV), time needed from gelatinization to peak (BAtime), and CRE, can be divided into two classes according to their interrelationship. The first class consists of AC, GC, and most of the paste viscosity parameters that form a major determinant of eating quality. The second class includes ASV, pasting temperature (Atemp) and pasting time (Atime), which characterize cooking process. We identified 26 QTL (quantitative trait locus or loci) in 2 years; nine QTL clusters emerged. The two major clusters, which correspond to the Wx and Alk loci, control the traits in the first and second classes, respectively. Some QTL are co-located for the traits belonging to the same class and also for the traits to a different class. The Wx locus also affects on ASV while the Alk locus also makes minor contributions to GC and some paste viscosity parameters. The QTL clusters on other chromosomes are similar to the Wx locus or Alk locus, although the variations they explained are relatively minor. QTL for CRE and PKV are dispersed and independent of the Wx locus. Low paste viscosity corresponds to low AC and soft gel, which represents good eating quality for most Chinese consumers; high ASV and low Atemp, together with reduced time to gelatinization and PKV, indicate preferred cooking quality. The genetic basis of Atemp, Atime, BAtime, peak temperature, peak time, paste viscosity at 95 degrees C, and final paste viscosity is newly examined to reveal a complete and dynamic viscosity profile.     

The main effects, epistatic effects and environmental interactions of QTLs on the cooking and eating quality of rice in a doubled-haploid line population

Amylose content (AC), gel consistency (GC) and gelatinazation temperature (GT) are three important traits that influence the cooking and eating quality of rice. The objective of this study was to characterize the genetic components, including main-effect quantitative trait loci (QTLs), epistatic QTLs and QTL-by-environment interactions (QEs), that are involved in the control of these three traits. A population of doubled haploid (DH) lines derived from a cross between two indica varieties Zhenshan 97 and H94 was used, and data were collected from a field experiment conducted in two different environments. A genetic linkage map consisting of 218 simple sequence repeat (SSR) loci was constructed, and QTL analysis performed using qtlmapper 1.6 resolved the genetic components into main-effect QTLs, epistatic QTLs and QEs. The analysis detected a total of 12 main-effect QTLs for the three traits, with a QTL corresponding to the Wx locus showing a major effect on AC and GC, and a QTL corresponding to the Alk locus having a major effect on GT. Ten digenic interactions involving 19 loci were detected for the three traits, and six main-effect QTLs and two pairs of epistatic QTLs were involved in QEs. While the main-effect QTLs, especially the ones corresponding to known major loci, apparently played predominant roles in the genetic basis of the traits, under certain conditions epistatic effects and QEs also played important roles in controlling the traits. The implications of the findings for rice quality improvement are discussed.     

Evaluation of near-isogenic lines for drought resistance QTL and fine mapping of a locus affecting flag leaf width, spikelet number, and root volume in rice

Drought stress is a major limiting factor for crop production and breeding for drought resistance is very challenging due to the complex nature of this trait. Previous studies in rice suggest that the upland japonica variety IRAT109 shows better drought resistance than the lowland indica variety Zhenshan 97. Numerous quantitative trait loci (QTL) have been previously mapped using a recombinant inbred line population derived from these two genotypes. In this study, near-isogenic lines (NILs) for 17 drought resistance-related QTL were constructed and phenotypic variations of these NILs were investigated under drought and normal conditions. Fourteen of these NILs showed significant phenotypic differences relative to the recurrent parent under at least one of the conditions and nine NILs showed significant differences under both conditions. After eliminating the effect of heading date on drought resistance, only four NILs carrying seven QTL (four for the same grain yield-related traits and three for the same or similar root traits QTL) showed differences consistent with the original QTL mapping results. One of these lines (N19) contains qFSR4, a QTL on chromosome 4 controlling root volume per tiller and co-segregating with flag leaf width and spikelet number per panicle. Using a population derived from N19, qFSR4 was mapped to a 38-kb region containing three open reading frames including the previously characterized NARROW LEAF 1 (NAL1) gene. NAL1, which controls leaf width and also affects vein patterning and polar auxin transport, is the most promising candidate genes for qFSR4. Our results underscore the importance of the development of NILs to confirm the identification of QTL affecting complex traits such as drought resistance.     

Mapping and Isolation of Quantitative Trait Loci Controlling Plant Height and Heading Date in Rice

Quantitative trait loci (QTL) were identified for heading date and plant height in rice ( Oryza sativa L.) using a recombinant inbred line population consisting of 241 lines. Totally 4 QTLs for heading date and 4 QTLs for plant height were detected in three years. The QTL with large effects located in the interval C1023-R1440 on chromosome 7 was simultaneously detected in three years for both traits. In order to distinguished the interval whether contained one QTL with pleiotropy effect or two close linked QTLs, a recombinant line RIL50, whose genetic background was high similar to Zhenshan 97 except the regions covered the major QTL from Minghui 63, was selected to cross with Zhenshan 97. A BC1F2 population from the cross, which could be regarded as near isogenic lines (NIL) with the targeted QTL (QTL-NIL), was used to collect heading date and plant height data. The frequency distribution of the two traits in the BC1F2 population was bimodal, and their segregation ratios were in accordance with the expected Mendelian inheritance ratios. Normally, the short plants flowered early in the population, the high plants with late heading date, but the relationships between the plant height and the heading date of 6 plants conflicted with the case. The above results clearly demonstrated that QTL could be treated as single Mendelian factor. Moreover, there are two close linked genes controlling the heading date and the plant height on chromosome 7, respectively.     

Clustered QTL for source leaf size and yield traits in rice (Oryza sativa L.)

Improvement of plant type plays an important role in super-high yield breeding in rice (Oryza sativa L.). In the present study, a set of backcross recombinant inbred lines derived from a cross of 9311 and Zhenshan97, both elite indica hybrid parents, were developed to identify quantitative trait loci (QTL) for flag leaf size, panicle and yield traits. Forty-seven QTL for 14 traits were detected in common in the two environmental trials, of which nine genomic regions contained clustered QTL affecting plant type traits and yield traits. Four co-localized QTL on chromosomes 1, 6, 7 and 8 involving QTL for flag leaf size (flag leaf length, width and area) contained the QTL for yield traits such as panicle weight (PW) and secondary branch number (SBN), and in all cases alleles from 9311 increased source leaf size and were associated with increased sink size and yield (SBN and PW). Using a subset of overlapping substitution lines for the QTL region on chromosome 1, the QTL were validated and narrowed into a 990?kbp interval (RM3746?CRM10435) with pleiotropic effects on flag leaf size, PW, SBN and spikelet number per panicle. These QTL clusters with large effects on source leaf size and yield-related traits provide good targets for marker-assisted breeding for plant type improvement and high-yield potential in rice.     

The genetic architecture of branched-chain amino acid accumulation in tomato fruits

Previous studies of the genetic architecture of fruit metabolic composition have allowed us to identify four strongly conserved co-ordinate quantitative trait loci (QTL) for the branched-chain amino acids (BCAAs). This study has been extended here to encompass the other 23 enzymes described to be involved in the pathways of BCAA synthesis and degradation. On coarse mapping the chromosomal location of these enzymes, it was possible to define the map position of 24 genes. Of these genes eight co-localized, or mapped close to BCAA QTL including those encoding ketol-acid reductoisomerase (KARI), dihydroxy-acid dehydratase (DHAD), and isopropylmalate dehydratase (IPMD). Quantitative evaluation of the expression levels of these genes revealed that the S. pennellii allele of IPMD demonstrated changes in the expression level of this gene, whereas those of KARI and DHAD were invariant across the genotypes. Whilst the antisense inhibition of IPMD resulted in increased BCAA, the antisense inhibition of neither KARI nor DHAD produced a clear effect in fruit BCAA contents. The results are discussed both with respect to the roles of these specific enzymes within plant amino acid metabolism and within the context of current understanding of the regulation of plant branched-chain amino acid metabolism.     

Identification of quantitative trait loci for grain size and the contributions of major grain-size QTLs to grain weight in rice

Grain weight, one of the three major components of rice yield, is largely determined by grain size, which is controlled by quantitative trait loci (QTLs). In a previous study, we identified qGS5 as a major QTL for grain width. Here, we report our identification of two more major grain-size QTLs (qGL3 and qGW2a) by using a recombinant inbred line (RIL) population from a cross of two indica varieties, ‘Zhenshan 97’ and ‘SLG’. To investigate the contribution of the three grain-size QTLs to final grain weight, we developed near-isogenic lines (NILs) NIL-qGL3, NIL-qGW2a, and NIL-qGS5 and used these to build the combined QTLs–NIL in the genetic background of ‘Zhenshan 97’ by marker-assisted selection and conventional backcrossing, respectively. A BCF₂ population of 957 individuals was developed from the combined QTLs-NIL for further study of the genetic control of grain size. The QTL analysis revealed that qGW2a and qGL3 played more important roles in grain weight gain than qGS5. All three QTLs showed additive effects with respect to grain weight, with no interaction. These results clearly indicate that pyramiding of major grain-size QTLs is a useful approach for improving rice yield.     

Genetic Relationships Among Panicle Characteristics of Rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) Using Unconditional and Conditional QTL Analyses

Using mixed-model-based composite interval mapping and conditional statistical methods, we studied quantitative trait loci (QTLs) with epistatic effects and QTLs by environment interaction effects for rice seed set percent (SSP), filled grain number per plant (FGP), and panicle length (PL). A population of 241 recombinant inbred lines was used which was derived from a cross between “Zhenshan 97” and “Minghui 63.” Its linkage map included 221 molecular markers. Our QTL analysis detected 28, 25, and 32 QTLs for SSP, FGP, and PL, respectively. Each QTL explained 1.37%∼13.19% of the mean phenotypic variation. A comparison of conventional and conditional mapping provided information about the genetic control system involved in the synthetic process of SSP, FGP, and PL at the level of individual QTLs. Conditional QTLs with reduced (or increased) effects were identified for SSP, which were significantly influenced by FGP or PL. Some QTLs could express independently for the given traits, thereby providing possibilities for simultaneous improvement of SSR and PL, and SSR and FGP. Epistasis was more sensitive to environmental conditions than were additive effects.     

Retracted: Screening of candidate genes and fine mapping of drought tolerance quantitative trait loci on chromosome 4 in rice (Oryza sativa L.) under drought stress

Due to severe water resource shortage, genetics of and breeding for DT (drought tolerance) in rice (Oryza sativa L.) have become one of the hot research topics. Identification of grain yield QTLs (quantitative trait loci) directly related to the DT trait of rice can provide useful information for breeding new drought‐resistant and water‐saving rice varieties via marker‐assisted selection. A population of 105 advanced BILs (backcross introgression lines) derived from a cross between Zhenshan97B and IRAT109 in Zhenshan97B background were grown under drought stress in a field experiment and phenotypic traits were investigated. The results showed that in the target interval of RM273‐RM255 on chromosome 4, three main‐effect QTLs related to panicle length, panicle number, and spikelet number per panicle were identified (LOD [logarithm of the odds] > 2.0). The panicle length‐related QTL had two loci located in the neighboring intervals of RM17308‐RM17305 and RM17349‐RM17190, which explained 18.80% and 20.42%, respectively, of the phenotypic variation, while the panicle number‐related QTL was identified in the interval of RM1354‐RM17308, explaining 11.47% of the phenotypic variation. As far as the spikelet number per panicle‐related QTL was concerned, it was found to be located in the interval of RM17308‐RM17305, which explained 28.08% of the phenotypic variation. Using the online Plant‐GE query system, a total of 13 matched ESTs (expressed sequence tags) were found in the target region, and of the 13 ESTs, 12 had corresponding predicted genes. For instance, the two ESTs CB096766 and CA765747 were corresponded to the same predicted gene LOC_Os04g46370, while the other four ESTs, CA754286, CB000011, CX056247, and CX056240, were corresponded to the same predicted gene LOC_Os04g46390.     

Application of an Effective Statistical Technique for an Accurate and Powerful Mining of Quantitative Trait Loci for Rice Aroma Trait

When a phenotype of interest is associated with an external/internal covariate, covariate inclusion in quantitative trait loci (QTL) analyses can diminish residual variation and subsequently enhance the ability of QTL detection. In the in vitro synthesis of 2-acetyl-1-pyrroline (2AP), the main fragrance compound in rice, the thermal processing during the Maillard-type reaction between proline and carbohydrate reduction produces a roasted, popcorn-like aroma. Hence, for the first time, we included the proline amino acid, an important precursor of 2AP, as a covariate in our QTL mapping analyses to precisely explore the genetic factors affecting natural variation for rice scent. Consequently, two QTLs were traced on chromosomes 4 and 8. They explained from 20% to 49% of the total aroma phenotypic variance. Additionally, by saturating the interval harboring the major QTL using gene-based primers, a putative allele of fgr (major genetic determinant of fragrance) was mapped in the QTL on the 8th chromosome in the interval RM223-SCU015RM (1.63 cM). These loci supported previous studies of different accessions. Such QTLs can be widely used by breeders in crop improvement programs and for further fine mapping. Moreover, no previous studies and findings were found on simultaneous assessment of the relationship among 2AP, proline and fragrance QTLs. Therefore, our findings can help further our understanding of the metabolomic and genetic basis of 2AP biosynthesis in aromatic rice.     

多效性基因Ghd7调控水稻剑叶面积

光合作用是植物的唯一能量来源,剑叶是水稻开花后进行光合作用的主要部位。Ghd7是一个多效性产量基因,能显著提高水稻产量。为了研究Ghd7对水稻剑叶形态的遗传效应,文章利用一个包含190个家系的BC2F2群体对水稻剑叶长度(FLL)、剑叶宽(FLW)和剑叶面积(FLA)进行QTL定位分析。在BC2F2群体,FLL、FLW和FLA性状表型值均显示为双峰分布,符合孟德尔单基因分离比,并均与每穗实粒数呈现显著正相关。在第7染色体上RM3859和C39分子标记间定位到FLL、FLW和FLA的QTL,分别解释变异的73.3%、62.3%和71.8%,均与Ghd7共分离。以珍汕97为轮回亲本,特青和明恢63分别为供体亲本,获得两个Ghd7近等基因系NIL(MH63)和NIL(TQ),FLL、FLW和FLA表型值均比珍汕97显著提高。另外,超表达Ghd7的合江19转基因植株的FLL、FLW和FLA表型值分别比合江19增加了8.9 cm、0.5 cm和17.8 cm2。这些结果表明Ghd7对调控剑叶面积起重要作用。     

水稻籽粒淀粉分支酶活性的遗传分析

用由247个株系组成的珍汕97B/密阳46重组自交系群体及其含207个分子标记的连锁图谱,在2002年和2003年分别测定亲本和重组自交系群体开花后10 d和20 d籽粒的淀粉分支酶的活性,检测到3个控制开花后10 d Q酶活性的主效应QTL(qnantitative trait loci),联合贡献率为10%,其中qQ10-6与环境发生显著的互作;分别检测到5对和2对染色体区间对开花后10 d、20 d Q酶活性的影响具有加性×加性上位性作用,其中开花后10 d的3对染色体区间具有显著的上位性×环境互作效应.由此可见,水稻籽粒Q酶活性相关基因的表达,受到环境因子的极大影响.     

The QTL analysis on maternal and endosperm genome and their environmental interactions for characters of cooking quality in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L<Emphasis Type="Italic">.</Emphasis>)

Investigations to identify quantitative trait loci (QTLs) governing cooking quality traits including amylose content, gel consistency and gelatinization temperature (expressed by the alkali spread value) were conducted using a set of 241 RIL populations derived from an elite hybrid cross of “Zhenshan 97” × “Minghui 63” and their reciprocal backcrosses BC₁F₁ and BC₂F₁ populations in two environments. QTLs and QTL × environment interactions were analyzed by using the genetic model with endosperm and maternal effects and environmental interaction effects on quantitative traits of seed in cereal crops. The results suggested that a total of seven QTLs were associated with cooking quality of rice, which were subsequently mapped to chromosomes 1, 4 and 6. Six of these QTLs were also found to have environmental interaction effects.     

Four rice QTL controlling number of spikelets per panicle expressed the characteristics of single Mendelian gene in near isogenic backgrounds

Development of quantitative trait loci (QTL) near isogenic lines is a crucial step to QTL isolation using the strategy of map-based cloning. In this study, a recombinant inbred line (RIL) population derived from two indica rice varieties, Zhenshan 97 and HR5, was employed to map QTL for spikelets per panicle (SPP). One major QTL (qSPP7) and three minor QTL (qSPP1, qSPP2 and qSPP3) were identified on chromosomes 7, 1, 2 and 3, respectively. Four sets of near isogenic lines (NILs) BC₄F₂ targeted for the four QTL were developed by following a standard procedure of consecutive backcross, respectively. These QTL were not only validated in corresponding NILs, but also explained amounts of phenotypic variation with much larger LOD scores compared with those identified in RILs. SPP in the four QTL-NILs expressed bimodal or discontinuous distributions and followed the expected segregation ratio of single Mendelian factor by progeny test. Finally, qSPP1, qSPP2, qSPP3 and qSPP7 were respectively mapped to a locus, 0.5 cM from MRG2746, 0.6 cM from MRG2762, 0.8 cM from RM49 and 0.7 cM from MRG4436, as co-dominant markers on the basis of progeny tests. These results indicate no matter how small effect minor QTL is, QTL may still express the characteristics of single Mendelian factor in NILs and isolation of minor QTL will be possible using high quality NILs. Pyramiding these QTL into a variety will largely enhance rice grain yield.     

Identification of Quantitative Trait Loci for Grain Appearance and Milling Quality Using a Doubled-Haploid Rice Population

Improving grain quality, which is composed primarily of the appearance of the grain and its cooking and milling attributes, is a major objective of many rice-producing areas in China. In the present study, we conducted a marker-based genetic analysis of the appearance and milling quality of rice （Oryza sativa L.） grains using a doubled-haploid population derived from a cross between the indica inbred Zhenshan 97 strain and the japonica inbred Wuyujing 2 strain. Quantitative trait locus （QTL） analysis using a mixed linear model approach revealed that the traits investigated were affected by one to seven QTLs that individually explained 4.0%-30.7% of the phenotypic variation. Cumulatively, the QTL for each trait explained from 12.9% to 61.4% of the phenotypic variation. Some QTLs tended to have a pleiotropic or location-linked association as a cause of the observed phenotypic correlations between different traits. Improvement of the characteristics of grain appearance and grain weight, as well as an improvement in the milling quality of rice grains, would be expected by a recombination of different QTLs using marker-assisted selection.     

Identification and characterization of quantitative trait loci for grain yield and its components under different nitrogen fertilization levels in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

A set of rice (Oryza sativa L.) recombinant inbred lines from a cross between Zhenshan 97 (indica) and HR5 (indica) was planted for four different growing seasons in two locations at three nitrogen (N) fertilization levels (N300, 300 kg urea/ha; N150, 150 kg urea/ha; and N0, 0 kg urea/ha). Grain yield and its components were evaluated, including grain yield per plant (GYPP), panicle number per plant (PNPP), grain number per panicle (GNPP), filled grains per panicle (FGPP), spikelet fertility percentage (SFP) and 100-grain weight (HGW). Correlation and path analysis indicated that SFP had the greatest contribution to GYPP at the N300 and N150 levels, but FGPP contributed the most to GYPP at the N0 level. Quantitative trait loci (QTL) were mapped based on a mixed linear model; genetic components (main effects, epistatic effects and QTL-by-environment interactions) were estimated separately. Six to 15 QTL with main effects were detected for each trait except SFP. Clusters of main-effect QTL associated with PNPP, GNPP, SFP and HGW were observed in regions on chromosomes 1, 2, 3, 5, 7 and 10. The main-effect QTL (qGYPP-4b and qGNPP-12) were only detected at the N0 level and explained 10.9 and 10.2% of the total phenotypic variation, respectively. A total of 33 digenic interactions among grain yield and its components were also identified. The identification of genomic regions associated with yield and its components at different nitrogen levels will be useful in marker-assisted selection for improving the nitrogen use efficiency of rice.