Genetic bases of appearance quality of rice grains in Shanyou 63, an elite rice hybrid

Appearance quality of the rice grain represents a major problem of rice production in many rice-producing areas of the world, especially in hybrid rice production in China. In this study, we conducted a molecular marker-based genetic analysis of the traits that are determinants of the appearance quality of rice grains, including traits specifying grain shape and endosperm opacity. The materials used in the analysis included an F_2:3 population and an F₁₀ recombinant inbred line population from a cross between the parents of Shanyou 63, the most widely grown rice hybrid in China. Molecular marker-based QTL (quantitative trait locus) analyses revealed that grain length and grain width were each controlled by a major QTL accounting for a very large proportion of the genetic variation, plus one or two minor QTLs each explaining a small proportion of the genetic variation. The major QTLs can be detected in both the F_2:3 and recombinant inbred line population using both paddy rice and brown rice, whereas the minor QTLs were detected only occasionally. The QTL located in the interval of RG393-C1087 on chromosome 3 is the major locus for grain length, and the one in the interval RG360-C734a on chromosome 5 plays a major role in determining grain width. Similarly, white belly, which largely determines the opacity of the endosperm, is almost entirely controlled by a major locus on chromosome 5, located in the same genomic region as the major QTL for grain width. The implications of the results with respect to hybrid rice improvement were discussed. Received: 20 February 2000 / Accepted: 21 March 2000     

Multi-Environmental Genetic Analysis of Grain Size Traits Based on Chromosome Segment Substitution Line in Rice (<i>Oryza sativa</i> L.)

Grain size traits are critical agronomic traits which directly determine grain yield, but the genetic bases of these traits are still not well understood. In this study, a total of 154 chromosome segment substitution lines (CSSLs) population derived from a cross between a japonica variety Koshihikari and an indica variety Nona Bokra was used to investigate grain length (GL), grain width (GW), length-width ratio (LWR), grain perimeter (GP), grain area (GA), and thousand grain weight (TGW) under four environments. QTL mapping analysis of six grain size traits was performed by QTL IciMapping 4.2 with an inclusive composite interval mapping (ICIM) model. A total of 64 QTLs were identified for these traits, which mapped to chromosomes 1, 2, 3, 4, 6, 7, 8, 10, 11, and 12 and accounted for 1.6%–27.1% of the total phenotypic variations. Among these QTLs, thirty-six loci were novel and seven QTLs were identified under four environments. One locus containing the known grain size gene, qGL3/GL3.1/OsPPKL1, also have been found. Moreover, five pairs of digenic epistatic interactions were identified except for GL and GP. These findings will facilitate fine mapping of the candidate gene and QTL pyramiding to genetically improve grain yield in rice.     

Association mapping of grain color,phenolic content,flavonoid content and antioxidant capacity in dehulled rice

Phytochemicals such as phenolics and flavonoids in rice grain are antioxidants that are associated with reduced risk of developing chronic diseases including cardiovascular disease, type-2 diabetes and some cancers. Understanding the genetic basis of these traits is necessary for the improvement of nutritional quality by breeding. Association mapping based on linkage disequilibrium has emerged as a powerful strategy for identifying genes or quantitative trait loci (QTL) underlying complex traits in plants. In this study, genome-wide association mapping using models controlling both population structure (Q) and relative kinship (K) were performed to identify the marker loci/QTLs underlying the naturally occurring variations of grain color and nutritional quality traits in 416 rice germplasm accessions including red and black rice. A total of 41 marker loci were identified for all the traits, and it was confirmed that Ra (i.e., Prp-b for purple pericarp) and Rc (brown pericarp and seed coat) genes were main-effect loci for rice grain color and nutritional quality traits. RM228, RM339, fgr (fragrance gene) and RM316 were important markers associated with most of the traits. Association mapping for the traits of the 361 white or non-pigmented rice accessions (i.e., excluding the red and black rice) revealed a total of 11 markers for four color parameters, and one marker (RM346) for phenolic content. Among them, Wx gene locus was identified for the color parameters of lightness (L*), redness (a*) and hue angle (H ^o). Our study suggested that the markers identified in this study can feasibly be used to improve nutritional quality or health benefit properties of rice by marker-assisted selection if the co-segregations of the marker–trait associations are validated in segregating populations.     

Whole-Genome Quantitative Trait Locus Mapping Reveals Major Role of Epistasis on Yield of Rice

Although rice yield has been doubled in most parts of the world since 1960s, thanks to the advancements in breeding technologies, the biological mechanisms controlling yield are largely unknown. To understand the genetic basis of rice yield, a number of quantitative trait locus (QTL) mapping studies have been carried out, but whole-genome QTL mapping incorporating all interaction effects is still lacking. In this paper, we exploited whole-genome markers of an immortalized F₂ population derived from an elite rice hybrid to perform QTL mapping for rice yield characterized by yield per plant and three yield component traits. Our QTL model includes additive and dominance main effects of 1,619 markers and all pair-wise interactions, with a total of more than 5 million possible effects. The QTL mapping identified 54, 5, 28 and 4 significant effects involving 103, 9, 52 and 7 QTLs for the four traits, namely the number of panicles per plant, the number of grains per panicle, grain weight, and yield per plant. Most identified QTLs are involved in digenic interactions. An extensive literature survey of experimentally characterized genes related to crop yield shows that 19 of 54 effects, 4 of 5 effects, 12 of 28 effects and 2 of 4 effects for the four traits, respectively, involve at least one QTL that locates within 2 cM distance to at least one yield-related gene. This study not only reveals the major role of epistasis influencing rice yield, but also provides a set of candidate genetic loci for further experimental investigation.     

Molecular detection of QTLs for agronomic and quality traits in a doubled haploid population derived from two Canadian wheats (Triticum aestivum L.)

Development of high-yielding wheat varieties with good end-use quality has always been a major concern for wheat breeders. To genetically dissect quantitative trait loci (QTLs) for yield-related traits such as grain yield, plant height, maturity, lodging, test weight and thousand-grain weight, and for quality traits such as grain and flour protein content, gluten strength as evaluated by mixograph and SDS sedimentation volume, an F₁-derived doubled haploid (DH) population of 185 individuals was developed from a cross between a Canadian wheat variety “AC Karma” and a breeding line 87E03-S2B1. A genetic map was constructed based on 167 marker loci, consisting of 160 microsatellite loci, three HMW glutenin subunit loci: Glu-A1, Glu-B1 and Glu-D1, and four STS-PCR markers. Data for investigated traits were collected from three to four environments in Manitoba, Canada. QTL analyses were performed using composite interval mapping. A total of 50 QTLs were detected, 24 for agronomic traits and 26 for quality-related traits. Many QTLs for correlated traits were mapped in the same genomic regions forming QTL clusters. The largest QTL clusters, consisting of up to nine QTLs, were found on chromosomes 1D and 4D. HMW glutenin subunits at Glu-1 loci had the largest effect on breadmaking quality; however, other genomic regions also contributed genetically to breadmaking quality. QTLs detected in the present study are compared with other QTL analyses in wheat.     

Genetic analysis of morphological index and its related taxonomic traits for classification of indica/japonica rice

A doubled haploid population derived from anther culture of ZYQ8/JX17 F₁, a typical indica and japonica hybrid, was used in this study. Morphological index and its related taxonomic traits were investigated in 121 DH lines. The quantitative trait loci (QTLs) for morphological index and its related taxonomic traits were analyzed. Two major QTLs for leaf hairiness, three QTLs for length/width of grain, one QTL for color of hull when heading, one QTL for hairiness of hull, two QTLs for length of the first and second panicle internode, and one major QTL and two QTLs for phenol reaction were detected. Four QTLs for morphological index were also identified on chromosomes 1, 3, 4 and 6, respectively, three of which on chromosomes 1, 3 and 6, respectively, were found to be located in the same chromosome regions where some QTLs for the related taxonomic traits were located.     

RFLP mapping of QTLs for yield and related characters in rice (Oryza sativa L.)

Quantitative triat loci (QTLs) for yield and related traits in rice were mapped based on RFLP maps from two indica/indica F₂ populations, Tesanai 2/CB and Waiyin 2/CB. In Tesanai 2/CB, 14 intervals carrying QTLs for eight traits were detected, including 3 for grain weight per plant (GWT), 2 for number of panicles per plant (NP), 2 for number of grains per panicle (NG), 1 for total number of spikelets per panicle (TNS), 1 for spikelet fertility (SF), 3 for 1000-grain weight (TGWT), 1 for spikelet density (SD), and 1 for number of first branches per main panicle. The 3 QTLs for GWT were located on chromosomes 1, 2, and 4, with 1 in each chromosome. The additive effect of the single locus ranged from 2.0 g to 9.1 g. A major gene (np4) for NP was detected on chromosome 4 within the interval of RG143–RG214, about 4cM for RG143, and this locus explained 26.1% of the observed phenotypic variance for NP. The paternal allele of this locus was responsible for reduced panicles per plant (3 panicles per plant). In another population, Waiyin 2/CB, 12 intervals containing QTLs for six of the above-mentioned traits were detected, including 3 for GWT, 2 for each of NP, TNS, TGWT and SD, 1 for SF. Three QTLs for GWT were located on chromosome 1, 4, and 5, respectively. The additive effect of the single locus for GWT ranged from 6.7 g to 8.8 g, while the dominance effect was 1.7–11.5 g. QTL mapping in two populations with a common male parent is compared and discussed.     

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.     

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.     

Genetic analysis of rice grain quality

 The inheritance of grain quality is more complicated than that of other agronomic traits in cereals due to epistasis, maternal and cytoplasmic effects, and the triploid nature of endosperm. In the present study, an established rice DH population derived from anther culture of an indica/japonica hybrid was used for genetic analysis of rice grain quality. A total of five parameters, amylose content (AC), alkali-spreading score (ASS), gel consistency (GC), percentage of grain with a white core (PGWC) and the square of the white core (SWC), were estimated for the DH lines and the parent varieties. For each parent, the value of each parameter was relatively stable in three locations, Beijing, Hangzhou and Chengdu, while the differences between the parents were significant for all five parameters. AC showed a bimodal distribution, and the distribution of ASS was skewed toward the value of JX17, while the other three parameters displayed continuous distributions among the DH lines with partially transgressive segregations. For AC, a minor and a major gene were found on chromosomes 5 and 6 respectively. The major gene, which should be an allele of wx, explained 91.9% of the total variation. For GC, two QTLs were identified on chromosomes 2 and 7 respectively. For ASS, a minor and a major gene were both located on chromosome 6. The major gene should be the same locus as the alkali degeneration gene (alk). Genetic linkage between alk and wx was found in QTL mapping. For PGWC, two QTLs were located on chromosomes 8 and 12. Only a minor QTL was found for SWC on chromosome 3. The results and the molecular markers presented here may be useful in rice breeding for grain quality improvement. Received: 24 April 1998 / Accepted: 13 August 1998     

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.     

Functional mapping of quantitative trait loci associated with rice tillering

Several biologically significant parameters that are related to rice tillering are closely associated with rice grain yield. Although identification of the genes that control rice tillering and therefore influence crop yield would be valuable for rice production management and genetic improvement, these genes remain largely unidentified. In this study, we carried out functional mapping of quantitative trait loci (QTLs) for rice tillering in 129 doubled haploid lines, which were derived from a cross between IR64 and Azucena. We measured the average number of tillers in each plot at seven developmental stages and fit the growth trajectory of rice tillering with the Wang–Lan–Ding mathematical model. Four biologically meaningful parameters in this model––the potential maximum for tiller number (K), the optimum tiller time (t ₀), and the increased rate (r), or the reduced rate (c) at the time of deviation from t ₀––were our defined variables for multi-marker joint analysis under the framework of penalized maximum likelihood, as well as composite interval mapping. We detected a total of 27 QTLs that accounted for 2.49–8.54% of the total phenotypic variance. Nine common QTLs across multi-marker joint analysis and composite interval mapping showed high stability, while one QTL was environment-specific and three were epistatic. We also identified several genomic segments that are associated with multiple traits. Our results describe the genetic basis of rice tiller development, enable further marker-assisted selection in rice cultivar development, and provide useful information for rice production management.     

Genetic analysis of morphological index and its related taxonomic traits for classification of indica/japonica rice

A doubled haploid population derived from anther culture of ZYQ8/JX17 F1, a typical indica and japonica hybrid, was used in this study. Morphological index and its related taxonomic traits were investigated in 121 DH lines. The quantitative trait loci (QTLs) for morphological index and its related taxonomic traits were analyzed. Two major QTLs for leaf hairiness, three QTLs for length/width of grain, one QTL for color of hull when heading, one QTL for hairiness of hull, two QTLs for length of the first and second panicle internode, and one major QTL and two QTLs for phenol reaction were detected. Four QTLs for morphological index were also identified on chromosomes 1, 3, 4 and 6, respectively, three of which on chromosomes 1, 3 and 6, respectively, were found to be located in the same chromosome regions where some QTLs for the related taxonomic traits were located.     

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.     

Genetic and molecular dissection of quantitative traits in rice

Recent progress in the generation of a molecular genetic map and markers for rice has made possible a new phase of mapping individual genes associated with complex traits. This type of analysis is often referred to as quantitative trait locus (QTL) analysis. Increasing numbers of QTL analyses are providing enormous amounts of information about QTLs, such as the numbers of loci involved, their chromosomal locations and gene effects. Clarification of genetic bases of complex traits has a big impact not only on fundamental research on rice plant development, but it also has practical benefits for rice breeding. In this review, we summarize recent progress of QTL analysis of several complex traits in rice. A strategy for positional cloning of genes at QTLs is also discussed.     

Quantitative trait loci for root-penetration ability and root thickness in rice: comparison of genetic backgrounds.

Drought is the major abiotic stress limiting rice (Oryza sativa) production and yield stability in rainfed lowland and upland ecosystems. Root systems play an important role in drought resistance. Incorporation of root selection criteria in drought resistance improvement is difficult due to lack of reliable and efficient screening techniques. Using a wax-petrolatum layer system simulated to compacted soil layers, root traits were evaluated in a doubled haploid (DH) population derived from the cross between 'IR64' and 'Azucena'. Twelve putative QTLs (quantitative trait loci) were detected by interval mapping comprising four QTLs for root-penetration ability, four QTLs for root thickness, two QTLs for penetrated root number, and two QTLs for total root number. These QTLs individually explained 8.4% to 16.4% of the phenotypic variation. No QTL was detected for maximum penetrated root length by interval mapping. One QTL located between RG104 and RG348 was found to influence both root-penetration ability and root thickness. QTLs for root-penetration ability and root thickness were compared across two populations, 'IR64'-'Azucena' and 'CO39'-'Moroberekan', and different testing conditions. The identified consistent QTLs could be used for marker-assisted selection for deep and thick roots with high root-penetration ability in rice.     

Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers

Huge efforts have been invested in the last two decades to dissect the genetic bases of complex traits including yields of many crop plants, through quantitative trait locus (QTL) analyses. However, almost all the studies were based on linkage maps constructed using low-throughput molecular markers, e.g. restriction fragment length polymorphisms (RFLPs) and simple sequence repeats (SSRs), thus are mostly of low density and not able to provide precise and complete information about the numbers and locations of the genes or QTLs controlling the traits. In this study, we constructed an ultra-high density genetic map based on high quality single nucleotide polymorphisms (SNPs) from low-coverage sequences of a recombinant inbred line (RIL) population of rice, generated using new sequencing technology. The quality of the map was assessed by validating the positions of several cloned genes including GS3 and GW5/qSW5, two major QTLs for grain length and grain width respectively, and OsC1, a qualitative trait locus for pigmentation. In all the cases the loci could be precisely resolved to the bins where the genes are located, indicating high quality and accuracy of the map. The SNP map was used to perform QTL analysis for yield and three yield-component traits, number of tillers per plant, number of grains per panicle and grain weight, using data from field trials conducted over years, in comparison to QTL mapping based on RFLPs/SSRs. The SNP map detected more QTLs especially for grain weight, with precise map locations, demonstrating advantages in detecting power and resolution relative to the RFLP/SSR map. Thus this study provided an example for ultra-high density map construction using sequencing technology. Moreover, the results obtained are helpful for understanding the genetic bases of the yield traits and for fine mapping and cloning of QTLs.     

Dissecting the genetic basis for the effect of rice chalkiness, amylose content, protein content, and rapid viscosity analyzer profile characteristics on the eating quality of cooked rice using the chromosome segment substitution line population across eight environments

Quantitative trait locus (QTL) mapping and stability analysis were carried out for 16 rice (Oryza sativa L.) quality traits across eight environments, by using a set of chromosome segment substitution lines with 'Asominori' as genetic background. The 16 quality traits include percentage of grain with chalkiness (PGWC), area of chalky endosperm (ACE), amylose content (AC), protein content (PC), peak viscosity, hot paste viscosity, cool paste viscosity, breakdown viscosity (BDV), setback viscosity (SBV), consistency viscosity, cooked-rice luster (LT), scent, tenderness (TD), viscosity, elasticity, and the integrated values of organleptic evaluation (IVOE). A total of 132 additive effect QTLs are detected for the 16 quality straits in the eight environments. Among these QTLs, 56 loci were detected repeatedly in at least three environments. Interestingly, several QTL clusters were observed for multiple quality traits. Especially, one QTL cluster near the G1149 marker on chromosome 8 includes nine QTLs: qPGWC-8, qACE-8, qAC-8, qPC-8a, qBDV-8a, qSBV-8b, qLT-8a, qTD-8a, and qIVOE-8a, which control PGWC, ACE, AC, PC, BDV, SBV, LT, TD, and IVOE, respectively. Moreover, this QTL cluster shows high stability and repeatability in all eight environments. In addition, one QTL cluster was located near the C2340 marker on chromosome 1 and another was detected near the XNpb67 marker on chromosome 2; each cluster contained five loci. Near the C563 marker on chromosome 3, one QTL cluster with four loci was found. Also, there were nine QTL clusters that each had two or three loci; however, their repeatability in different environments was relatively lower, and the genetic contribution rate was relatively smaller. Considering the correlations among all of the 16 quality traits with QTL cluster distributions, we can conclude that the stable and major QTL cluster on chromosome 8 is the main genetic basis for the effect of rice chalkiness, AC, PC, and rapid viscosity analyzer profile characteristics on the eating quality of cooked rice. Consequently, this QTL cluster is a novel gene resource for controlling rice high-quality traits and should be of great significance for research on formation mechanism and molecule improvement of rice quality.     

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.     

两个水稻骨干恢复系重要农艺性状的遗传基础研究

水稻骨干恢复系是指在杂交稻育种中广泛应用的一类恢复系。探明骨干恢复系的遗传基础,发掘其重要农艺性状基因/QTL,对分子标记辅助选择水稻恢复系育种具有重要应用价值。本研究以生产上广泛应用的三系骨干恢复系成恢727和两系骨干恢复系9311为亲本,培育了具有250个系的重组自交系群体。分别在2015年三亚和2016年合肥两个环境下进行了9个重要农艺性状表型和SSR分子标记基因型鉴定,用SAS9.2分析表型数据,用QTL Ici Mapping v4.1进行QTL定位分析。在三亚和合肥两个环境下共检测到39个QTL,三亚检测到16个,分布于第1、2、4、7、8、10、11和12染色体上;合肥检测24个,分布于第1、2、3、7、8、9、10和12染色体上。其中qPH1-1在三亚和合肥两个环境下都能检测到,加性效应分别为-1.75和-2.46。在检测到的39个QTL中,有24个QTL的增效等位基因来自恢复系成恢727,15个QTL的增效等位基因来自9311。共计有26个QTL曾被前人定位,13个属于尚未见文献报道的新QTL。另外,在RM279~RM521、RM336~RM3534、RM25~RM547、RM553~RM160、RM222~RM271区段内检测到5个多效性QTL位点。其中RM25~RM547位点与已经克隆的基因Ghd8位置相近。RM553~RM160位点是一个新的多效性位点,分别控制每穗实粒数、单株产量和结实率,而且效应和表型变异贡献率都较大。其余3个位点在前人的研究中分别有所报道,但其多效性则是在本研究中首次发现。在本研究新发掘到的QTL中,控制穗数的QTL qPN12-1,控制穗长的QTL qPL1-2和qPL10-1,控制总粒数的QTL qSNP2-1和qSNP10-1,控制结实率的QTL qSF3-1,控制千粒重QTL qTGW7-1和控制产量的QTL qGY1-1效应均比较大,解释的表型遗传变异比例也较高。本研究的结果将会为相关性状QTL的精细定位、克隆和育种应用奠定基础。