Quantitative trait loci (QTL) analysis for rice grain width and fine mapping of an identified QTL allele gw-5 in a recombination hotspot region on chromosome 5

Rice grain width and shape play a crucial role in determining grain quality and yield. The genetic basis of rice grain width was dissected into six additive quantitative trait loci (QTL) and 11 pairs of epistatic QTL using an F(7) recombinant inbred line (RIL) population derived from a single cross between Asominori (japonica) and IR24 (indica). QTL by environment interactions were evaluated in four environments. Chromosome segment substitution lines (CSSLs) harboring the six additive effect QTL were used to evaluate gene action across eight environments. A major, stable QTL, qGW-5, consistently decreased rice grain width in both the Asominori/IR24 RIL and CSSL populations with the genetic background Asominori. By investigating the distorted segregation of phenotypic values of rice grain width and genotypes of molecular markers in BC(4)F(2) and BC(4)F(3) populations, qGW-5 was dissected into a single recessive gene, gw-5, which controlled both grain width and length-width ratio. gw-5 was narrowed down to a 49.7-kb genomic region with high recombination frequencies on chromosome 5 using 6781 BC(4)F(2) individuals and 10 newly developed simple sequence repeat markers. Our results provide a basis for map-based cloning of the gw-5 gene and for marker-aided gene/QTL pyramiding in rice quality breeding.     

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.     

Stability of QTLs for rice grain dimension and endosperm chalkiness characteristics across eight environments

Rice appearance quality, including traits specifying grain dimension and endosperm chalkiness, represents a major problem in many rice-producing areas of the world. In this study, the genetic basis of six appearance quality traits of milled rice was dissected into quantitative trait loci (QTL) main effects, and the stability of these QTLs was assessed in a population of 66 chromosome segment substitution lines (CSSLs) across eight environments. The CSSLs showed transgressive segregation for many of the traits, and significant correlations were detected among most of the traits. Twenty-two QTLs were identified on eight chromosomes, and numerous QTLs affecting related traits were mapped in the same regions, probably reflecting pleiotropic effects. Nine QTLs, namely qGL-1,qGL-3, qGW-5,qLWR-3, qLWR-5,qPGWC-8, qPGWC-9, qACE-8, and qDEC-8, were consistently detected across the eight environments. The additive main effect and multiplicative interaction (AMMI) analysis showed that genotype (G) × environment (E) interaction was significant for all six traits, with the first three iPCA terms accounting for over 80% of the G × E variance. Both D_I values and the iPCA1-iPCA2 biplots showed that the CSSLs harboring the nine QTL alleles were more stable than those carrying any of the additional 13 QTL alleles, thereby confirming their environmental stability and pointing to their appropriateness as targets for marker-assisted selection for high-quality rice varieties.     

Combination of Eight Alleles at Four Quantitative Trait Loci Determines Grain Length in Rice

Grain length is an important quantitative trait in rice (Oryza sativa L.) that influences both grain yield and exterior quality. Although many quantitative trait loci (QTLs) for grain length have been identified, it is still unclear how different alleles from different QTLs regulate grain length coordinately. To explore the mechanisms of QTL combination in the determination of grain length, five mapping populations, including two F₂ populations, an F₃ population, an F₇ recombinant inbred line (RIL) population, and an F₈ RIL population, were developed from the cross between the U.S. tropical japonica variety ‘Lemont’ and the Chinese indica variety ‘Yangdao 4’ and grown under different environmental conditions. Four QTLs (qGL-3-1, qGL-3-2, qGL-4, and qGL-7) for grain length were detected using both composite interval mapping and multiple interval mapping methods in the mapping populations. In each locus, there was an allele from one parent that increased grain length and another allele from another parent that decreased it. The eight alleles in the four QTLs were analyzed to determine whether these alleles act additively across loci, and lead to a linear relationship between the predicted breeding value of QTLs and phenotype. Linear regression analysis suggested that the combination of eight alleles determined grain length. Plants carrying more grain length-increasing alleles had longer grain length than those carrying more grain length-decreasing alleles. This trend was consistent in all five mapping populations and demonstrated the regulation of grain length by the four QTLs. Thus, these QTLs are ideal resources for modifying grain length in rice.     

Dynamic QTL Analysis of Rice Protein Content and Protein Index Using Recombinant Inbred Lines

Protein content (PC) and protein index (PI) play important roles in determining nutritional quality in rice (Oryza sativa L.). We used 71 lines derived from “Asominori/IR24” to analyze the developmental behavior of PC and PI through unconditional and conditional QTL mapping methods. In all, 10 unconditional QTLs and 6 conditional QTLs for PC, and 11 unconditional QTLs and 9 conditional QTLs for PI, were identified at four stages of grain filling. More were identified in the first three stages than at the final stage. Temporal patterns of gene expression for PC and PI differed over time, with several QTLs being expressed across two or three stages but many being expressed at only one stage. Some of these QTLs were closely linked with maturity QTLs reported previously. Many QTLs for PC and PI were co-localized, supporting the significant correlation found between PC and PI. Our results suggest that dynamic QTL mapping might be a valid means for revealing more genetic information about protein accumulations during seed development.     

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.     

Identification of quantitative trait loci for yield and yield components in an advanced backcross population derived from the<Emphasis Type="Italic"> Oryza sativa</Emphasis> variety IR64 and the wild relative<Emphasis Type="Italic"> O. rufipogon</Emphasis>

A BC₂F₂ population developed from an interspecific cross between Oryza sativa (cv IR64) and O. rufipogon (IRGC 105491) was used in an advanced backcross QTL analysis to identify and introduce agronomically useful genes from this wild relative into the cultivated gene pool. The objectives of this study were: (1) to identify putative yield and yield component QTLs that can be useful to improve the elite cultivar IR64; (2) to compare the QTLs within this study with previously reported QTLs in rice as the basis for identifying QTLs that are stable across different environments and genetic backgrounds; and (3) to compare the identified QTLs with previously reported QTLs from maize to examine the degree of QTL conservation across the grass family. Two hundred eighty-five families were evaluated in two field environments in Indonesia, with two replications each, for 12 agronomic traits. A total of 165 markers consisting of 131 SSRs and 34 RFLPs were used to construct the genetic linkage map. By employing interval mapping and composite interval mapping, 42 QTLs were identified. Despite its inferior performance, 33% of the QTL alleles originating from O. rufipogon had a beneficial effect for yield and yield components in the IR64 background. Twenty-two QTLs (53.4%) were located in similar regions as previously reported rice QTLs, suggesting the existence of stable QTLs across genetic backgrounds and environments. Twenty QTLs (47.6%) were exclusively detected in this study, uncovering potentially novel alleles from the wild, some of which might improve the performance of the tropical indica variety IR64. Additionally, several QTLs for plant height, grain weight, and flowering time detected in this study corresponded to homeologous regions in maize containing previously detected maize QTLs for these traits.     

Characterization and precise mapping of a QTL increasing spike number with pleiotropic effects in wheat

Tiller number (TN) and spike number per plant (SN) are key components of grain yield and/or biomass in wheat. In this study, an introgression line 05210, developed by introgression of chromosomal segments from a synthetic exotic wheat Am3 into an elite cultivar Laizhou953, showed a significantly increased TN and SN, but shorter spike length (SL) and fewer grain number per spike (GNS) than Laizhou953. To investigate the quantitative trait locus (QTL) responsible for these variations, the introgressed segments in 05210 were screened by SSR markers and one follow-up segregation population was developed from the cross 05210/Laizhou953. The population showed 3:1 segregation ratios for SN, SL and GNS, indicating that QTLs for these traits have been dissected into single Mendelian factors. Bulked segregation analysis showed that the markers located on the 4B introgressed segment were polymorphic between the two bulks. Therefore, they were further analyzed in the F₂ population to construct a linkage map. Three new QTLs, QSn.sdau-4B, QSl.sdau-4B and QGns.sdau-4B, were detected for SN, SL and GNS, respectively, which explained a large portion of the phenotypic variation (30.1–67.6%) for these traits with overlapping peaks. Correlation analysis and multiple-trait, multiple-interval mapping (MMIM) suggested pleiotropic effects of the QTL on SN, SL and GNS. Therefore, the QTL was designated as QSn.sdau-4B. By a progeny test based on F₃ families using SN, the QTL was mapped as a Mendelian factor to the proximal region of 4BL. It is a key QTL responsible for variation in spike number and size, which had not been reported previously. Thus, it is an important QTL for wheat to achieve high and stable biomass and grain yield. Dissection and mapping of this QTL as a Mendelian factor laid a solid foundation for map-based cloning of grain yield-related QTLs in wheat.     

Fine mapping of grain length QTLs on chromosomes 1 and 7 in Basmati rice (Oryza sativa L.)

Grain dimensions (length, breadth and length/breadth ratio) are important quality attributes of Basmati rice for its high consumer acceptance. Earlier we identified two significant quantitative trait loci (QTL) intervals on chromosomes 1 and 7 for grain dimensions in Basmati rice using a population of recombinant inbred lines (RILs) from cross between Basmati variety Pusa 1121 and a short grain non-aromatic variety Pusa 1342. For fine mapping of these QTLs, 184 F₆ RILs were grown and phenotyped in the normal rice growing season at two different locations. Forty-nine new SSR markers targeting these QTL intervals were tested and nine were found polymorphic between the parents. Using revised genetic maps adding new markers, the grain length QTL qGRL1.1 on chromosome 1 was narrowed down to 108?kbp from the earlier reported 6,133?kbp. There were total 13 predicted gene models in this interval which includes the probable candidate gene for the exceptionally high grain length of Basmati variety Pusa 1121. Similarly, two tandem QTL intervals qGRL7.1 and qGRL7.2 on chromosome 7 were merged into a single one narrowed down to 2,390?kbp from the earlier reported length of 5,269?kbp. This region of chromosome 7 also has co-localized QTLs for grain breadth and length to breadth ratio. SSR markers tightly linked to the QTL at a map distance of ??0.2?cM were developed for the qGRL1.1 and qGRL7.1 loci that could be used for marker-assisted breeding. Validation of earlier published markers for the grain length gene GS3 on chromosome 3 showed no difference between Pusa 1121 and Pusa 1342, highlighting the significance of qGRL1.1 and qGRL7.1 for the extra grain length of Basmati variety Pusa 1121.     

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.     

QTL analysis and mapping of pi21, a recessive gene for field resistance to rice blast in Japanese upland rice

Field resistance is defined as the resistance that allows effective control of a parasite under natural field conditions and is durable when exposed to new races of that parasite. To identify the genes for field resistance to rice blast, quantitative trait loci (QTLs) conferring field resistance to rice blast in Japanese upland rice were detected and mapped using RFLP and SSR markers. QTL analysis was carried out in F₄ progeny lines from the cross between Nipponbare (moderately susceptible, lowland) and Owarihatamochi (resistant, upland). Two QTLs were detected on chromosome 4 and one QTL was detected on each of chromosomes 9 and 12. The phenotypic variation explained by each QTL ranged from 7.9 to 45.7% and the four QTLs explained 66.3% of the total phenotypic variation. Backcrossed progeny lines were developed to transfer the QTL with largest effect using the susceptible cultivar Aichiasahi as a recurrent parent. Among 82 F₃ lines derived from the backcross, resistance segregated in the expected ratio of resistant 1 : heterozygous 2 : susceptible 1. The average score for blast resistance measured in the field was 4.2 ± 0.67, 7.5 ± 0.51and 8.2 ± 0.66, for resistant, heterozygous and susceptible groups, respectively. The resistance gene, designated pi21, was mapped on chromosome 4 as a single recessive gene between RFLP marker loci G271 and G317 at a distance of 5.0 cM and 8.5 cM, respectively. The relationship to previously reported major genes and QTLs conferring resistance to blasts, and the significance of marker-assisted selection to improve field resistance, are discussed. Received: 8 June 2000 / Accepted: 24 November 2000     

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。     

A Kelch Motif-Containing Serine/Threonine Protein Phosphatase Determines the Large Grain QTL Trait in Rice

A thorough understanding of the genetic basis of rice grain traits is critical for the improvement of rice (Oryza sativa L.) varieties. In this study, we generated an F₂ population by crossing the large‐grain japonica cultivar CW23 with Peiai 64 (PA64), an elite indica small‐grain cultivar. Using QTL analysis, 17 QTLs for five grain traits were detected on four different chromosomes. Eight of the QTLs were newly‐identified in this study. In particular, qGL3‐1, a newly‐identified grain length QTL with the highest LOD value and largest phenotypic variation, was fine‐mapped to the 17 kb region of chromosome 3. A serine/threonine protein phosphatase gene encoding a repeat domain containing two Kelch motifs was identified as the unique candidate gene corresponding to this QTL. A comparison of PA64 and CW23 sequences revealed a single nucleotide substitution (C→A) at position 1092 in exon 10, resulting in replacement of Asp (D) in PA64 with Glu (E) in CW23 for the 364^th amino acid. This variation is located at the D position of the conserved sequence motif AVLDT of the Kelch repeat. Genetic analysis of a near‐isogenic line (NIL) for qGL3‐1 revealed that the allele qGL3‐1 from CW23 has an additive or partly dominant effect, and is suitable for use in molecular marker‐assisted selection.     

Genetic analysis and QTL mapping for grain chalkiness characteristics of brown rice (Oryza sativa L.)

Grain chalkiness is one of the important appearance qualities in rice marketing. But it is a complex trait, controlled by polygenes and easily influenced by the environment. Genetic analysis and QTL detection was carried out on six characteristics of grain chalkiness consisting of the percentage of chalkiness (PGC), white belly (PWB) and white core grains (PWC), and the area of chalkiness (CA), white belly (WBA) and white core (WCA) in brown rice. A total of 16 main-effect QTLs associated with chalkiness characteristics of brown rice were mapped on seven chromosomes over two years. Among them,qPGC7.1 andqPWB7.2 were simultaneously located on chromosome 7 flanked by 7038 and 7042 at LOD scores 4.34 and 3.76, whileqPWC2.1 andqWCA2.1 were simultaneously located on chromosome 2 flanked by RM492 and RM324 with LOD scores of 2.50 and 3.39. Twelve epistatic combinations were detected for five chalkiness characteristics except for CA. Results indicated that WBA was mainly influenced by the additive effects of main-effect QTLs. PGC and PWC were affected by the effects of epistatic QTLs and the interactions between additive-by-additive effects and the environment. The effects of epistatic QTLs and the main-effect QTLs played important roles on CA, PWB and WCA. For the genetic improvement of grain chalkiness in breeding system, more attention should be paid to epistatic effects and the additive effects of main-effect QTLs.     

The<Emphasis Type="Italic"> Rxo1</Emphasis>/<Emphasis Type="Italic">Rba1</Emphasis> locus of maize controls resistance reactions to pathogenic and non-host bacteria

The genetic mechanism underlying six palatability properties of cooked rice and three physico-chemical traits was dissected in 66 BC₃F₂ chromosome segment substitution lines (CSSLs), using a complete linkage map in three successive years. The CSSLs showed transgressive segregation for all traits studied. Significant correlation was detected among most palatability traits. A total of 25 QTLs for the nine traits were identified on nine chromosomes, and many QTLs affecting different quality traits were mapped in the same regions. Six QTLs—qLT-8 for luster, qTD-6 and qTD-8 for tenderness, qIVOE-6 and qIVOE-8 for integrated value of organoleptic evaluation, and qAC-8 for amylose content—were repeatedly detected across the 3 years. Phenotypic values were significantly different between the recurrent parent, cultivar Asominori, and the CSSLs harboring any of the six QTL alleles across the three environments, indicating that these six QTLs were non-environment-specific and could be used for marker-assisted selection in rice quality improvement.     

QTL x environment interactions in rice. I. heading date and plant height

One hundred twenty six doubled-haploid (DH) rice lines were evaluated in nine diverse Asian environments to reveal the genetic basis of genotype × environment interactions (GEI) for plant height (PH) and heading date (HD). A subset of lines was also evaluated in four water-limited environments, where the environmental basis of G × E could be more precisely defined. Responses to the environments were resolved into individual QTL × environment interactions using replicated phenotyping and the mixed linear-model approach. A total of 37 main-effect QTLs and 29 epistatic QTLs were identified. On average, these QTLs were detectable in 56% of the environments. When detected in multiple environments, the main effects of most QTLs were consistent in direction but varied considerably in magnitude across environments. Some QTLs had opposite effects in different environments, particularly in water-limited environments, indicating that they responded to the environments differently. Inconsistent QTL detection across environments was due primarily to non- or weak-expression of the QTL, and in part to significant QTL × environment interaction effects in the opposite direction to QTL main effects, and to pronounced epistasis. QTL × environment interactions were trait- and gene-specific. The greater GEI for HD than for PH in rice were reflected by more environment-specific QTLs, greater frequency and magnitude of QTL × environment interaction effects, and more pronounced epistasis for HD than for PH. Our results demonstrated that QTL × environment interaction is an important property of many QTLs, even for highly heritable traits such as height and maturity. Information about QTL × environment interaction is essential if marker-assisted selection is to be applied to the manipulation of quantitative traits.Communicated by G. Wenzel     

A QTL for rice grain yield in aerobic environments with large effects in three genetic backgrounds

A large-effect QTL associated with grain yield in aerobic environments was identified in three genetic backgrounds, Apo/²*Swarna, Apo/²*IR72, and Vandana/²*IR72, using bulk-segregant analysis (BSA). Apo and Vandana are drought-tolerant aerobic-adapted varieties, while Swarna and IR72 are important lowland rice varieties grown on millions of hectares in Asia but perform poorly in aerobic conditions. Two closely linked rice microsatellite (RM) markers, RM510 and RM19367, located on chromosome 6, were found to be associated with yield under aerobic soil conditions in all three backgrounds. The QTL linked to this marker, qDTY6.1 (DTY, grain yield under drought), was mapped to a 2.2 cM region between RM19367 and RM3805 at a peak LOD score of 32 in the Apo/²*Swarna population. The effect of qDTY6.1 was tested in a total of 20 hydrological environments over a period of five seasons and in five populations in the three genetic backgrounds. In the Apo/²*Swarna population, qDTY6.1 had a large effect on grain yield under favorable aerobic (R ² ≤ 66%) and irrigated lowland (R ² < 39%) conditions but not under drought stress; Apo contributed the favorable allele in all the conditions where an effect was observed. In the Apo/IR72 cross, Apo contributed the favorable allele in almost all the aerobic environments in RIL and BC₁-derived populations. In the Vandana/IR72 RIL and BC₁-derived populations, qDTY6.1 had a strong effect on yield in aerobic drought stress, aerobic non-stress, and irrigated lowland conditions; the Vandana allele was favorable in aerobic environments and the IR72 allele was favorable in irrigated lowland environments. We conclude that qDTY6.1 is a large-effect QTL for rice grain yield under aerobic environments and could potentially be used in molecular breeding of rice for aerobic environments.     

Quantitative Trait Locus Mapping and Candidate Gene Analysis for Plant Architecture Traits Using Whole Genome Re-Sequencing in Rice

Plant breeders have focused on improving plant architecture as an effective means to increase crop yield. Here, we identify the main-effect quantitative trait loci (QTLs) for plant shape-related traits in rice (Oryza sativa) and find candidate genes by applying whole genome re-sequencing of two parental cultivars using next-generation sequencing. To identify QTLs influencing plant shape, we analyzed six traits: plant height, tiller number, panicle diameter, panicle length, flag leaf length, and flag leaf width. We performed QTL analysis with 178 F₇ recombinant in-bred lines (RILs) from a cross of japonica rice line ‘SNUSG1’ and indica rice line ‘Milyang23’. Using 131 molecular markers, including 28 insertion/deletion markers, we identified 11 main- and 16 minor-effect QTLs for the six traits with a threshold LOD value > 2.8. Our sequence analysis identified fifty-four candidate genes for the main-effect QTLs. By further comparison of coding sequences and meta-expression profiles between japonica and indica rice varieties, we finally chose 15 strong candidate genes for the 11 main-effect QTLs. Our study shows that the whole-genome sequence data substantially enhanced the efficiency of polymorphic marker development for QTL fine-mapping and the identification of possible candidate genes. This yields useful genetic resources for breeding high-yielding rice cultivars with improved plant architecture.     

Mapping and validation of quantitative trait loci for spikelets per panicle and 1,000-grain weight in rice (Oryza sativa L.)

This study identified four and five quantitative trait loci (QTLs) for 1,000-grain weight (TGW) and spikelets per panicle (SPP), respectively, using rice recombinant inbred lines. QTLs for the two traits (SPP3a and TGW3a, TGW3b and SPP3b) were simultaneously identified in the two intervals between RM3400 and RM3646 and RM3436 and RM5995 on chromosome 3. To validate QTLs in the interval between RM3436 and RM5995, a BC₃F₂ population was obtained, in which TGW3b and SPP3b were simultaneously mapped to a 2.6-cM interval between RM15885 and W3D16. TGW3b explained 50.4% of the phenotypic variance with an additive effect of 1.81 g. SPP3b explained 29.1% of the phenotypic variance with an additive effect of 11.89 spikelets. The interval had no effect on grain yield because it increased SPP but decreased TGW and vice versa. Grain shape was strongly associated with TGW and was used for QTL analysis in the BC₃F₂ population. Grain length, grain width, and grain thickness were also largely controlled by TGW3b. At present, it is not clear whether one pleiotropic QTL or two linked QTLs were located in the interval. However, the conclusion could be made ultimately by isolation of TGW3b. The strategy for TGW3b isolation is discussed.