Validation of qGSIO, a quantitative trait locus for grain size on the long arm of chromosome 10 in rice (Oryza sativa L.)

Grain size is a major determinant of grain weight and a trait having important impact on grain quality in rice. The objective of this study is to detect QTLs for grain size in rice and identify important QTLs that have not been well characterized before. The QTL mapping was first performed using three recombinant inbred line populations derived from indica rice crosses Teqing/IRBB lines, Zhenshan 97/Milyang 46, Xieqingzao/Milyang 46. Fourteen QTLs for grain length and 10 QTLs for grain width were detected, including seven shared by two populations and 17 found in one population. Three of the seven com- mon QTLs were found to coincide in position with those that have been cloned and the four others remained to be clarified. One of them, qGSIO located in the interval RM6100-RM228 on the long arm of chromosome 10, was validated using F2：3 populations and near isogenic lines derived from residual heterozygotes for the interval RM6100-RM228. The QTL was found to have a considerable effect on grain size and grain weight, and a small effect on grain number. This region was also previously detected for quality traits in rice in a number of studies, providing a good candidate for functional analysis and breeding utilization.

Quantitative Trait Locus Analysis for Rice Yield Traits under Two Nitrogen Levels

A recombinant inbred line population derived from a super hybrid rice Xieyou 9308（Xieqingzao B/Zhonghui 9308） and its genetic linkage map were used to detect quantitative trait loci（QTLs） for rice yield traits under the low and normal nitrogen（N） levels. A total of 52 QTLs for yield traits distributed in 27 regions on 9 chromosomes were detected, with each QTL explaining 4.93%–26.73% of the phenotypic variation. Eleven QTLs were simultaneously detected under the two levels, and 30 different QTLs were detected under the two N levels, thereby suggesting that the genetic bases controlling rice growth under the low and normal N levels were different. QTLs for number of panicles per plant, number of spikelets per panicle, number of filled grains per panicle, and grain density per panicle under the two N levels were detected in the RM135–RM168 interval on chromosome 3. QTLs for number of spikelets per panicle and number of filled grains per panicle under the two N levels, as well as number of panicles per plant and grain density per panicle, under the low N level, were detected in the RM5556–RM310 interval on chromosome 8. The above described QTLs shared similar regions with previously reported QTLs for rice N recycling.

A major quantitative trait locus controlling phosphorus utilization efficiency under different phytate-P conditions at vegetative stage in barley

Organic phosphorus（P） is an important component of the soil P pool, and it has been proven to be a potential source of P for plants. The phosphorus utilization efficiency（PUE） and PUE related traits（tiller number（TN）, shoot dry weight（DW）, and root dry weight） under different phytate-P conditions（low phytate-P, 0.05 mmol L^-1 and normal phytate-P, 0.5 mmol L^-1） were investigated using a population consisting of 128 recombinant inbred lines（RILs） at the vegetative stage in barley. The population was derived from a cross between a P-inefficient genotype（Baudin） and a P-efficient genotype（CN4027, a Hordeum spontaneum accession）. A major locus（designated Qpue.sau-3 H） conferring PUE was detected in shoots and roots from the RIL population. The quantitative trait locus（QTL） was mapped on chromosome 3 H and the allele from CN4027 confers high PUE. This locus explained up to 30.3 and 28.4% of the phenotypic variance in shoots under low and normal phytate-P conditions, respectively. It also explains 28.3 and 30.7% of the phenotypic variation in root under the low and normal phytate-P conditions, respectively. Results from this study also showed that TN was not correlated with PUE, and a QTL controlling TN was detected on chromosome 5 H. However, dry weight（DW） was significantly and positively correlated with PUE, and a QTL controlling DW was detected near the Qpue.sau-3 H locus. Based on a covariance analysis, existing data indicated that, although DW may affect PUE, different genes at this locus are likely involved in controlling these two traits.

Mapping of qTGW1.1,a Quantitative Trait Locus for 1000-Grain Weight in Rice (Oryza sativa L.)

1000-grain weight （ TGW） is one ot the three component traits ot the grain yiela in rice （Oryza sativa L）. This study was conducted to validate and fine-map qTGWl. 1, a minor QTL for TGW which was previously located in a 3.7-Mb region on the long arm of rice chromosome 1. Five sets of near isogenic lines （NILs） were developed from two BC2F4 populations of the indica rice cross Zhenshan 973/Milyang 46 The NIL sets consisted of two homozygous genotypic groups differing in the regions RM11448-RM11522, RM11448-RM11549, RM1232-RM11615, RM11543-RM11554 and RM11569-RM11621, respectively. Four traits, including TGW, grain length, grain width and heading date, were measured. Phenotypic difference between the two genotypic groups in each NIL population was analyzed using SAS procedure GLM. Significant QTL effects were detected on TGW with the Zhenshan 97 allele increasing grain weight by 0.12 g to 0.14 g and explaining 8.30% to 15.19% of the phenotypic variance. Significant effects were also observed for grain length and width, whereas no significant effect was found for heading date. Based on comparison among the five NILs on the segregating regions and the results of QTL analysis, qTGWl. 1 was delimited to a 376.9-kb region flanked by DNA markers Wn28382 and RMl1554. Our results indicate that the effects of minor QTLs could be steadily detected in a highly isogenic background and suggest that such QTLs could be utilized in the breeding of high-yielding rice varieties.

A Sequential Quantitative Trait Locus Fine-Mapping Strategy Using Recombinant-Derived Progeny

A thorough understanding of the quantitative trait loci （QTLs） that underlie agronomically important traits in crops would greatly increase agricultural productivity. Although advances have been made in QTL cloning, the majority of QTLs remain unknown because of their low heritability and minor contributions to phenotypic performance. Here we summarize the key advantages and disad- vantages of current QTL fine-mapping methodologies, and then introduce a sequential QTL fine-mapping strategy based on both genotypes and phenotypes of progeny derived from recombinants. With this mapping strategy, experimental errors could be dramat- ically diminished so as to reveal the authentic genetic effect of target QTLs. The number of progeny required to detect QTLs atvarious R2 values was calculated, and the backcross generation suitable to start QTL fine-mapping was also estimated. This mapping strategy has proved to be very powerful in narrowing down QTL regions, particularly minor-effect QTLs, as revealed by fine-mapping of various resistance QTLs in maize. Application of this sequential QTL mapping strategy should accelerate cloning of agronomically important QTLs, which is currently a substantial challenge in crops.

Identification and Validation of a Major Quantitative Trait Locus for Slow-rusting Resistance to Stripe Rust in Wheat

Stripe （yellow） rust, caused by Puccinia striiformis Westend. f. sp. tritici Eriks （Pst）, is one of the most important wheat （Triticum aestivum L.） diseases and causes significant yield losses. A recombinant inbred （RI） population derived from a cross between Yanzhan 1 and Xichang 76-9 cultivars was evaluated for resistance to wheat stripe rust strain CYR32 at both the seedling and adult plant stages. Four resistance quantitative trait loci （QTLs） were detected in this population, in which the major one, designated as Yrql, was mapped on chromosome 2DS. The strategy of using the Brachypodium distachyon genome, wheat expressed sequence tags and a draft DNA sequences （scaffolds） of the D-genome （Aegilops tauschfi Coss.） for the development of simple sequence repeat （SSR） markers was successfully used to identify 147 SSRs in hexaploid wheat. Of the 19 polymorphic SSRs in the RI population, 17 SSRs were mapped in the homeologous group 2 chromosomes near Yrql region and eight SSRs were genetically mapped in the 2.7 cM region of Yrql, providing abundant DNA markers for fine-mapping of Yrql and marker-assisted selection in wheat breeding program. The effectiveness of Yrql was validated in an independent population, indicating that this resistance QTL can be successfully transferred into a susceptible cultivar for improvement of stripe rust resistance.

Quantitative trait locus mapping with background control in genetic populations of clonal F_1 and double cross

In this study, we considered five categories of molecular markers in clonal F1 and double cross populations, based on the number of distinguishable alleles and the number of distinguishable genotypes at the marker locus. Using the completed linkage maps, incomplete and missing markers were imputed as fully informative markers in order to simplify the linkage mapping approaches of quantitative trait genes. Under the condition of fully informative markers, we demonstrated that dominance effect between the female and male parents in clonal F1 and double cross populations can cause the interactions between markers. We then developed an inclusive linear model that includes marker variables and marker interactions so as to completely control additive effects of the female and male parents, as well as the dominance effect between the female and male parents. The linear model was finally used for background control in inclusive composite interval mapping （ICIM） of quantitative trait locus （QTL）. The efficiency of ICIM was demonstrated by extensive simulations and by comparisons with simple interval mapping, multiple-QTLmodels and composite interval mapping. Finally, ICIM was applied in one actual double cross population to identify QTL on days to silking in maize.

High-resolution linkage and quantitative trait locus mapping using an interspecific cross between Argopecten irradians irradians(♀) and A. purpuratus (♂)

The bay scallop and Peruvian scallop are economically important species.Interspecific hybrids of these two scallops outperformed both of their parent species in multiple growth traits but exhibited decreased fertility,which provides good models for the study of heterosis and species divergence.Genetic mapping serves as a chromosomal-level framework to investigate the molecular mechanisms of hybridization and introgression.In this study,high-resolution linkage maps were constructed for the bay and Peruvian scallops with an interspecific hybrid family.The linkage map of the bay scallop covered over 98.9% of the whole genome with 2994 mapped markers and the average marker interval of 0.32 cM.For the Peruvian scallop,1585 markers were mapped with the average maker interval of 0.51 cM,covering 97.7% of the genome.Both the two linkage maps have 16 linkage groups,corresponding to the haploid chromosome number of the two species.Approximately,54.5% of markers exhibited significant deviation from the expected Mendelian ratio of segregation,lending in sights into the intrinsic incompatibility between the two species.QTLs related to growth and shell coloration were detected,which could explain 13.1%and 74.9% of the phenotypic variance,respectively.This represents important information for further evaluation.These findings are an important addition to the genomic resources for scallop genetic studies,and are especially useful for investigations on genomic incompatibility for hybridization,genome evolution of closely related species,and genetic enhancement programs in aquaculture.

Generalized fiducial methods for testing quantitative trait locus effects in genetic backcross studies

In this paper,we propose generalized fiducial methods and construct four generalized p-values to test the existence of quantitative trait locus effects under phenotype distributions from a location-scale family.Compared with the likelihood ratio test based on simulation studies,our methods perform better at controlling type I errors while retaining comparable power in cases with small or moderate sample sizes.The four generalized fiducial methods support varied sce-narios:two of them are more aggressive and powerful,whereas the other two appear more conservative and robust.A real data example involving mouse blood pressure is used to illustrate our proposed methods.

Identification of quantitative trait loci for the dead leaf rate and the seedling dead rate under alkaline stress in rice

The quantitative trait loci （QTLs） for the dead leaf rate （DLR） and the dead seedling rate （DSR） at the different rice growing periods after transplanting under alkaline stress were identified using an F2：3 population, which included 200 individuals and lines derived from a cross between two japonica rice cultivars Gaochan 106 and Changbai 9 with microsatellite markers. The DLR detected at 20 days to 62 days after transplanting under alkaline stress showed continuous normal or near normal distributions in F3 lines, which was the quantitative trait controlled by multiple genes. The DSR showed a continuous distribution with 3 or 4 peaks and was the quantitative trait controlled by main and multiple genes when rice was grown for 62 days after transplanting under alkaline stress. Thirteen QTLs associated with DLR were detected at 20 days to 62 days after transplanting under alkaline stress. Among these, qDLR9-2 located in RM5786-RM160 on chromosome 9 was detected at 34 days, 41 days, 48 days, 55 days, and 62 days, respectively; qDLR4 located in RM3524-RM3866 on chromosome 4 was detected at 34 days, 41 days, and 48 days, respectively; qDLR7-1 located in RM3859-RM320 on chromosome 7 was detected at 20 days and 27 days; and qDLR6-2 in RM1340-RM5957 on chromosome 6 was detected at 55 days and 62 days, respectively. The alleles of both qDLR9-2 and qDLR4 were derived from alkaline sensitive parent ＂Gaochanl06＂. The alleles of both qDLR7-1 and qDLR6-2 were from alkaline tolerant parent Changbai 9. These gene actions showed dominance and over dominance primarily. Six QTLs associated with DSR were detected at 62 days after transplanting under alkaline stress. Among these, qDSR6-2 and qDSR8 were located in RM1340-RM5957 on chromosome 6 and in RM3752-RM404 on chromosome 8, respectively, which were associated with DSR and accounted for 20.32% and 18.86% of the observed phenotypic variation, respectively; qDSR11-2 and qDSR11-3 were located in RM536-RM479 and RM2596-RM286 on chromosome 11, respectively, which were associated with DSR explaining 25.85% and 15.41% of the observed phenotypic variation, respectively. The marker flanking distances of these QTLs were quite far except that of qDSR6-2, which should be researched further.

Identification of Quantitative Trait Loci for Grain Traits in Japonica Rice

Quantitative trait loci（QTLs） of grain traits were detected to provide theoretical basis for fine mapping and molecular marker-assisted breeding of grain traits in japonica rice.Using an F2 population including 200 individuals derived from a cross combination between two japonica rice DL115 with large grain and XL005 with small grain,the grain length,grain width,grain thickness,ratio of grain length to width and 1 000-grain weight were evaluated in Beijing;and the quantitative trait loci for above five grain traits were identified by composite interval mapping using SSR markers.The results showed that the five grain traits exhibited a normal continuous distribution in F2 population,indicating they were quantitative traits controlled by multiple genes.A total of 16 QTLs conferring the five grain traits were detected on chromosomes 2,3,5 and 12,respectively.Eight QTLs,namely qGL3a,qGW2,qGW5,qGT2,qRLW2,qRLW3,qGWT2 and qGWT3,were major QTLs and explained 15.42,40.89,13.54,33.43,13.82,13.61,12.51 and 10.1% of the observed phenotypic variance,respectively.Among them,qGW2,qGT2,qRLW2 and qGWT2 were mapped in same interval RM12776-RM324 on chromosome 2.The marker interval RM12776-RM324 on chromosome 2 was common marker intervals of four major QTLs,and the two SSR markers RM12776 and RM324 would be used in molecular markerassisted breeding in japonica rice.The modes of gene action were mainly additive and partial dominance.Four QTLs＇ alleles were derived from small grain parent XL005,and other 12 QTLs＇ alleles were derived from large grain parent DL115.The alleles from larger parent were showed significant effects to grain length,grain width,grain thickness and 1 000-grain weight.

Quantitative Trait Loci for Heading Date and Their Relationship with Genetic Control of Yield Traits in Rice (Oryza sativa)

Grain yield and heading date are key factors determining the commercial potential of a rice variety. Mapping of quantitative trait loci （QTLs） in rice has been advanced from primary mapping to gene cloning, and heading date and yield traits have always attracted the greatest attention. In this review, genomic distribution of QTLs for heading date detected in populations derived from intra-specific crosses of Asian cultivated rice （Oryza sativa） was summarized, and their relationship with the genetic control of yield traits was analyzed. The information could be useful in the identification of QTLs for heading date and yield traits that are promising for the improvement of rice varieties.

Confirmation of Novel Quantitative Trait Loci for Seed Dormancy at Different Ripening Stages in Rice

Seed dormancy contributes resistance to pre-harvest sprouting. Effects on respective quantitative trait loci （QTLs） for dormancy should be assessed by using fresh seeds before germinability altered through storage. We investigated QTLs related to seed dormancy using backcross inbred lines derived from a cross between Nipponbare and Kasalath. Four putative QTLs for seed dormancy were detected immediately after harvest using composite interval mapping. These putative QTLs were mapped near C1488 on chromosome 3 （qSD-3.1）, R2171 on chromosome 6 （qSD-6.1）, R1245 on chromosome 7 （qSD-7.1） and C488 on chromosome 10 （qSD-IO.1）. Kasalath alleles promoted dormancy for qSD-3.1, qSD-6.1 and qSD-7.1, and the respective proportions of phenotypic variation explained by each QTL were 12.9%, 9.3% and 8.1%. We evaluated the seed dormancy harvested at different ripening stages during seed development using chromosome segment substitution lines （CSSLs） to confirm gene effects. The germination rates of CSSL27 and CSSL28 substituted with the region including qSD-6.1 were significantly lower than those of Nipponbare and other CSSLs at the late ripening stage. Therefore, qSD-6.1 is considered the most effective novel QTL for pre-harvest sprouting resistance among the QTLs detected in this study.

Quantitative Trait Loci for Grain Chalkiness and Endosperm Transparency Detected in Three Recombinant Inbred Line Populations of Indica Rice

Quantitative trait loci（QTL） for percentage of chalky grain,degree of chalkiness,and endosperm transparency were detected using 3 recombinant inbred line populations derived from crosses between parental lines of commercial three-line hybrids of indica rice.Two of the populations showed great variations on heading date,and the other had a short range of heading date variation.A total of 40 QTLs were detected and fell into 15 regions of 10 chromosomes,of which 5 regions were detected for 1 or more same traits over different populations,2 were detected for different traits in different populations,3 were detected for 2 or all the 3 traits in a single population,and 5 were detected for a single trait in a single population.Most of these QTLs have been reported previously,but a region located on the long arm of chromosome 10 showing significant effects in all the 3 populations has not been reported before.It was shown that a number of gene cloned,including the Wx and Alk for the physiochemical property of rice grain,and GW2,GS3 and GW5 for grain weight and grain size,could have played important roles for the genetic control of grain chalkiness in rice,but there are many more QTLs exerting stable effects for rice chalkiness over different genetic backgrounds.It is worth paying more attentions to these regions which harbor QTL such as the qPCG5.2/qDC5.2/qET5.2 and qPCG10/qDC10/qET10 detected in our study.Our results also showed that the use of segregating populations having high-uniform heading date could greatly increase the efficiency of the identification of QTL responsible for traits that are subjected to great environmental influence.

Quantitative Trait Loci for Mercury Tolerance in Rice Seedlings

Mercury （Hg） is one of the most toxic heavy metals to living organisms and its conspicuous effect is the inhibition of root growth. However, little is known about the molecular genetic basis for root growth under excess Hg2＋ stress. To map quantitative trait loci （QTLs） in rice for Hg2＋ tolerance, a population of 120 recombinant inbred lines derived from a cross between two japonica cultivars Yuefu and IRAT109 was grown in 0.5 mmol/L CaCI2 solution. Relative root length （RRL）, percentage of the seminal root length in ＋HgCI2 to -HgCI2, was used for assessing Hg2＋ tolerance. In a dose-response experiment, Yuefu had a higher RRL than IRAT109 and showed the most significant difference at the Hg2＋ concentration of 1.5 tJmol/L. Three putative QTLs for RRL were detected on chromosomes 1, 2 and 5, and totally explained about 35.7% of the phenotypic variance in Hg2＋ tolerance. The identified QTLs for RRL might be useful for improving Hg2＋ tolerance of rice by molecular marker-assisted selection.

Quantitative Trait Loci for Panicle Size and Grain Yield Detected in Interval RM111-RM19 784 on the Short Arm of Rice Chromosome 6

A rice residual heterozygous line （RHL） carrying a heterozygous segment extending from RM111 to RM19784 on the short arm of rice chromosome 6 was selected from a RHL-derived population used previously. The resultant F2：3 population was used to detect quantitative trait loci （QTLs） for three yield traits, the number of spikelets per panicle （NSP）, the number of grains per panicle （NGP） and grain yield per plant （GY）. Two QTLs for NSP, one QTL for NGP and one QTL for GY were detected, all of which were partially dominant and had the enhancing alleles from the maternal line Zhenshan 97B. Analysis based on the genotypic groups of the markers closely linked to the two QTLs for NSP indicated that they did not interact with each other. Two F2 populations and two near isogenic line （NIL） sets segregating in two sub-regions of interval RM111-RM19784 were developed. The two QTLs for NSP were validated, of which one had major effect and was co-segregated with heading date gene Hdl, and the other had smaller effect and was located in an upper region linked to Hdl. The two regions also showed significant effects on the number of filled grain and grain yield, although the effect on the number of filled grain was less consistent.

Identification of quantitative trait loci and candidate genes associated with ABA sensitivity in common wild rice (Oryza rufipogon Griff,)

Abscisic acid （ABA）, as one of the foremost signaling molecules in plants, is an important hormone which plays versatile functions in regulating developmental process and adaptive stress process. A set of introgression lines were previously generated via a backcrossing program using an elite indica cultivar rice Teqing （O. sativa L.） as recipient and an accession of Yuanjiang common wild rice （O. rufipogon Griff.） as donor. In this study, the previously developed introgression lines were evaluated for ABA sensitivity. Here we reported that a total of 14 quantitative trait loci （QTLs） associated with ABA sensitivity were identified. An ABA sensitive introgression line, YIL53, was identified and characterized. Physiological characterization, including chlorophyll content, malondialdehyde content, soluble sugar content, and stomata movement, demonstrated that YIL53 exhibited the characteristics associated with ABA sensitivity. Genotypic analysis revealed that YIL53 harbored one QTL related to ABA sensitivity, qASS1-2, which was located on chromosome 1 within one introgressed segment derived from the Yuanjiang common wild rice. Furthermore, the qASS1-2 was finally narrowed down to a 441-kb region between simple sequence repeats （SSR） marker RM212 and single nucleotide polymorphism （SNP） marker M3 using the segregation population derived from the cross between Teqing and YIL53, and three candidate genes associated with ABA sensitivity were identified using a strategy combined gene expression analysis with QTL mapping. Identification of the QTLs related to ABA sensitivity and characterization of the ABA sensitive line YIL53 would provide a helpful basis for isolating novel genes related to ABA sensitivity.

Detection of QTLs for Important Agronomic Traits and Analysis of Their Stabilities Using SSSLs in Rice

Single segment substitution lines （SSSLs） each with a single chromosome segment from a donor under the same genetic background as the recipient were developed in rice by advanced backcrossing and molecular marker-assisted selection. Using the SSSLs, the QTLs for the important agronomic traits in rice would be detected under different environmental conditions. Detection of the QTLs controlling 22 important traits in rice was done with 32 SSSLs by the randomized block design in 2-4 cropping seasons. 59 QTLs were detected and distributed on chromosomes 1, 2, 3, 4, 6, 7, 8, 10, and 11, of which 18 QTLs were detected more than twice. Only 30.5% of the QTLs were detected repeatedly in different cropping seasons. Most of the QTLs of important agronomic traits were of little additive effects and instability. The QTLs controlling the traits, such as grain weight, grain length, ratio of grain length to width, and heading date were relatively stable. The stable QTLs usually had larger additive effects and were less affected by environment. The QTLs for the important agronomic traits were detected using the SSSLs in rice with high resolution under different environmental conditions. The instability of the QTLs may be the basis of the variation of rice plants during growth and development. It would be the genetic basis for improving yield and quality in rice cultivars by farming methods.

Dissection of QTLs for Yield Traits on the Short Arm of Rice Chromosome 6

This study was undertaken to dissect quantitative trait loci （QTLs） controlling yield traits on the short arm of rice chromosome 6. A residual heterozygous line that carries a heterozygous segment extending from RM587 to RM19784 on the short arm of rice chromosome 6 was selected from an F7 population of the indica rice cross Zhenshan 97B/Milyang 46. An F2：3 population consisting of 221 lines was derived and grown in two trial sites. Six yield traits including number of panicles per plant, number of filled grains per panicle, total number of spikelets per panicle, spikelet fertility, 1 000-grain weight, and grain yield per plant were measured. An SSR marker linkage map was constructed and employed to determine QTLs for yield traits with Windows QTL Cartographer 2.5. QTLs were detected in the target interval for all the traits analyzed except NP, with phenotypic variance explained by a single QTL ranging between 6.3% and 35.2%. Most of the QTLs for yield components acted as additive QTLs, while the three QTLs for grain yield had dominance degrees of 1.65, 0.84, and -0.42, respectively. It was indicated that three or more QTLs for yield traits were located in the target region. The genetic action mode, the direction of the QTL effect, and the magnitude of the QTL effect varied among different QTLs for a given trait, and among QTLs for different traits that were located in the same interval.