Analyses and identifications of quantitative trait loci and candidate genes controlling mesocotyl elongation in rice

Rice direct seeding has the significant potential to save labor and water,conserve environmental resources,and reduce greenhouse gas emissions tremendously.Therefore,rice direct seeding is becoming the major cultivation technology applied to rice production in many countries.Identifying and utilizing genes controlling mesocotyl elongation is an effective approach to accelerate breeding procedures and meet the requirements for direct-seeded rice(DSR) production.This study used a permanent mapping population with 144 recombinant inbred lines(RILs) and 2 828 bin-markers to detect quantitative trait loci(QTLs) associated with mesocotyl length in 2019 and 2020.The mesocotyl lengths of the rice RILs and their parents,Lijiangxintuanheigu(LTH) and Shennong 265(SN265),were measured in a growth chamber at 30°C in a dark environment.A total of 16 QTLs for mesocotyl length were identified on chromosomes 1(2),2(4),3(2),4,5,6,7,9,11(2),and 12.Seven of these QTLs,including qML1a,qML1b,qML2d,qML3a,qML3b,qML5,and qML11b,were reproducibly detected in both years via the interval mapping method.The major QTL,qML3a,was reidentified in two years via the composite interval mapping method.A total of 10 to 413 annotated genes for each QTL were identified in their smallest genetic intervals of 37.69 kb to 2.78 Mb,respectively.Thirteen predicted genes within a relatively small genetic interval(88.18 kb) of the major mesocotyl elongation QTL,qML3a,were more thoroughly analyzed.Finally,the coding DNA sequence variations among SN265,LTH,and Nipponbare indicated that the LOC_Os03g50550 gene was the strongest candidate gene for the qML3a QTL controlling the mesocotyl elongation.This LOC_Os03g50550 gene encodes a mitogen-activated protein kinase.Relative gene expression analysis using qRT-RCR further revealed that the expression levels of the LOC_Os03g50550 gene in the mesocotyl of LTH were significantly lower than in the mesocotyl of SN265.In conclusion,these results further strengthen our knowledge about rice’s genetic mechanisms of mesocotyl elongation.This investigation’s discoveries will help to accelerate breeding programs for new DSR variety development.

Strategies on Sample Size Determination and Qualitative and Quantitative Traits Integration to Construct Core Collection of Rice (Oryza sativa)

The development of a core collection could enhance the utilization of germplasm collections in crop improvement programs and simplify their management. Selection of an appropriate sampling strategy is an important prerequisite to construct a core collection with appropriate size in order to adequately represent the genetic spectrum and maximally capture the genetic diversity in available crop collections. The present study was initiated to construct nested core collections to determine the appropriate sample size to represent the genetic diversity of rice landrace collection based on 15 quantitative traits and 34 qualitative traits of 2 262 rice accessions. The results showed that 50-225 nested core collections, whose sampling rate was 2.2%-9.9%, were sufficient to maintain the maximum genetic diversity of the initial collections. Of these, 150 accessions （6.6%） could capture the maximal genetic diversity of the initial collection. Three data types, i.e. qualitative traits （QT1）, quantitative traits （QT2） and integrated qualitative and quantitative traits （QTT）, were compared for their efficiency in constructing core collections based on the weighted pair-group average method combined with stepwise clustering and preferred sampling on adjusted Euclidean distances. Every combining scheme constructed eight rice core collections （225, 200, 175, 150, 125, 100, 75 and 50）. The results showed that the QTT data was the best in constructing a core collection as indicated by the genetic diversity of core collections. A core collection constructed only on the information of QT1 could not represent the initial collection effectively. QTT should be used together to construct a productive core collection.

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.

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.

Quantitative traits correlative analysis and growth comparison among different populations of bay scallop,Argopecten irradians

The shell traits and weight traits are measured in cultured populations of bay scallop, Argopecten irradians. The results of regression analysis show that the regression relationships for all the traits are significant (P<0.01). The correlative coefficients between body weight, as well as tissue weight with shell length, shell height and shell width are significant (P<0.05). But the correlative coefficients between the anterior and posterior auricle length with body weight as well as tissue weight are not significant (P>0.05). The multiple regression equation is obtained to estimate live body weight and tissue weight. The above traits except anterior and posterior auricle length are used for the growth and production comparison among three cultured populations, Duncan's new multiple range procedure analysis shows that all the traits in the Lingshuiqiao (LSQ) population are much more significant than those of the other two populations (P<0.01), and there is no significant difference between the Qipanmo (QPM) and Dalijia (DLJ) populations in all traits (P>0.05). The results indicate that the LSQ population has a higher growth rate and is expected to be more productive than the other two populations.

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.

Mapping Quantitative Trait Loci Associated with Photoperiod Sensitivity in Maize(Zea mays L.)

Photoperiod sensitivity in maize plays an essential role in utilizing tropic and sub-tropic germplasm to temperate areas. This study aims to identify and map the QTLs responsible for the characteristics measuring photoperiod sensitivity, days from planting to silking （SD）, photoperiod response coefficient of silking （PRC）, and anthesis-silking interval （ASI）. Using the population derived from Zheng 58, photoperiod-insensitive parent, and Ya 8701, photoperiod-sensitive parent, a linkage map was constructed with 93 single sequence repeat （SSR） markers. Phenotyping of 296 F2-3 families of the population in replicated-field test was conducted in both long-day （Beijing, China） and short-day （Sichuan, China） conditions. Ten QTLs were identified to be associated with the SD and ASI on chromosomes 3, 4, 6, 8, and 10 in the longday conditions, and 11 QTLs were detected to be related to the SD and ASI on chromosomes 2, 3, 4, 5, 6, 8, and 10 in the short-day conditions, respectively. A QTL associated with the PRC as a major effect in the long-day conditions located in the same position as the QTL related to the SD and ASI in the map, and was on chromosome 10 linked with marker bnlg1655. Using these QTLs in the marker-assisted selection, the photoperiod sensibility could be reduced by selection of the alleles responsible for the SD, PRC, and ASI in breeding programs.

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 analysis for root traits in synthetic hexaploid wheat under drought stress conditions

Synthetic hexaploid wheat(SHW),possesses numerous genes for drought that can help breeding for drought-tolerant wheat varieties.We evaluated 10 root traits at seedling stage in 111 F9 recombinant inbred lines derived from a F2 population of a SHW line(SHW-L1)and a common wheat line,under normal(NC)and polyethylene glycol-simulated drought stress conditions(DC).We mapped quantitative trait loci(QTLs)for root traits using an enriched high-density genetic map containing 120370 single nucleotide polymorphisms(SNPs),733 diversity arrays technology markers(DArT)and 119 simple sequence repeats(SSRs).With four replicates per treatment,we identified 19 QTLs for root traits under NC and DC,and 12 of them could be consistently detected with three or four replicates.Two novel QTLs for root fresh weight and root diameter under NC explained 9 and 15.7%of the phenotypic variation respectively,and six novel QTLs for root fresh weight,the ratio of root water loss,total root surface area,number of root tips,and number of root forks under DC explained 8.5–14%of the phenotypic variation.Here seven of eight novel QTLs could be consistently detected with more than three replicates.Results provide essential information for fine-mapping QTLs related to drought tolerance that will facilitate breeding drought-tolerant wheat cultivars.

Joint Analysis Method for Major Genes Controlling Multiple Correlated Quantitative Traits

Based on the major gene and polygene mixed inheritance model for multiple correlated quantitative traits, the authors proposed a new joint segregation analysis method of major gene controlling multiple correlated quantitative traits, which include major gene detection and its effect and variation estimation. The effect and variation of major gene are estimated by the maximum likelihood method implemented via expectation-maximization （EM） algorithm. Major gene is tested with the likelihood ratio （LR） test statistic. Extensive simulation studies showed that joint analysis not only increases the statistical power of major gene detection but also improves the precision and accuracy of major gene effect estimates. An example of the plant height and the number of tiller of F2 population in rice cross Duonieai x Zhonghua 11 was used in the illustration. The results indicated that the genetic difference of these two traits in this cross refers to only one pleiotropic major gene. The additive effect and dominance effect of the major gene are estimated as -21.3 and 40.6 cm on plant height, and 22.7 and -25.3 on number of tiller, respectively. The major gene shows overdominance for plant height and close to complete dominance for number of tillers.

Mapping quantitative trait loci associated with starch paste viscosity attributes by using double haploid populations of rice (Oryza sativa L.)

The paste viscosity attributes of starch,measured by rapid visco analyzer(RVA),are important factors for the evaluation of the cooking and eating qualities of rice in breeding programs.To determine the genetic roots of the paste viscosity attributes of rice grains,quantitative trait loci(QTLs)associated with the paste viscosity attributes were mapped,using a double haploid(DH)population derived from Zhongjiazao 17(YK17),a super rice variety,crossed with D50,a tropic japonica variety.Fifty-four QTLs,for seven parameters of the RVA profiles,were identified in three planting seasons.The 54 QTLs were located on all of the 12 chromosomes,with a single QTL explaining 5.99 to 47.11%of phenotypic variation.From the QTLs identified,four were repeatedly detected under three environmental conditions and the other four QTLs were repeated under two environments.Most of the QTLs detected for peak viscosity(PKV),trough viscosity(TV),cool paste viscosity(CPV),breakdown viscosity(BDV),setback viscosity(SBV),and peak time(PeT)were located in the interval of RM 6775-RM 3805 under all three environmental conditions,with the exception of pasting temperature(PaT).For digenic interactions,eight QTLs with six traits were identified for additivexenvironment interactions in all three planting environments.The epistatic interactions were estimated only for PKV,SBV and PaT.The present study will facilitate further understanding of the genetic architecture of eating and cooking quality(ECQ)in the rice quality improvement program.

Quantitative trait locus mapping of yield and plant height in autotetraploid alfalfa(Medicago sativa L.)

Alfalfa(Medicago sativa L.)is the most widely grown forage legume crop worldwide.Yield and plant height are important agronomic traits influenced by genetic and environmental factors.The objective of this study was to identify quantitative trait loci(QTL)and molecular markers associated with alfalfa yield and plant height.To understand the genetic basis of these traits,a full-sib F1 population composed of 392 individuals was developed by crossing a low-yielding precocious alfalfa genotype(male parent)with a high-yielding latematuring alfalfa cultivar(female parent).The linkage maps were constructed with 3818 single-nucleotide polymorphism(SNP)markers on 64 linkage groups.QTL for yield and plant height were mapped using phenotypic data for three years.Sixteen QTL associated with yield and plant height were identified on chromosomes 1 to 8.Six QTL explained more than 10%of phenotypic variation,representing major loci controlling yield and plant height.One locus on chromosome 1 controlling yield traits had not been identified in previous studies.Three QTL co-located with other QTL(qyield-1 and qheight-7,qheight-5 and qyield-4,qheight-6,and qyield-6).With further validation,the markers closely linked with these QTL may be used for marker-assisted selection in breeding new alfalfa varieties with high yield.

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 Resistance to Stripe Disease in Rice(Oryza sativa)

In order to map the quantitative trait loci for rice stripe resistance, a molecular linkage map was constructed based on the F2 population derived from a cross between Zhaiyeqing 8 and Wuyujing 3. Reactions of the two parents, F1 individual and 129 F2：3 lines to, rice stripe were JnvestJgated by both artificial Jnoculation at laboratory and natural infection in the field, and the ratios of disease rating index were scored. The distribution of the ratios of disease rating index in Zhaiyeqing 8/Wuyujing 3 F2：3 population ranged from 0 to 134,08 and from 6.25 to 133.6 under artificial inoculation at laboratory and natural infection in the field, respectively, and showed a marked bias towards resistant parent （Zhaiyeqing 8）, indicating that the resistance to rice stripe was controlled by quantitative trait loci （QTL）. QTL analysis showed that the QTLs detected by the two inoculation methods were completely different. Only one QTL, qSTVT, was detected under artificial inoculation, at which the Zhaiyeqing 8 allele increased the resistance to rice stripe, while two QTLs, qSTV5 and qSTV1, were detected under natural infection, in which resistant alleles came from Zhaiyeqing 8 and Wuyujing 3, respectively. These results showed that resistant parent Zhaiyeqing 8 carried the alleles associated with the resistance to rice stripe virus and the small brown planthopper, and susceptible parent Wuyujing 3 also carried the resistant allele to rice stripe virus. In comparison with the results previously reported, QTLs detected in the study were new resistant genes to rice stripe disease. This will provide a new resistant resource for avoiding genetic vulnerability for single utilization of the resistant gene Stvb-i.

Mapping of Quantitative Trait Loci Affecting Eggshell Quality in an F_2 Population Derived from Strong and Weak Eggshell Lines of the White Leghorn Chicken Breed

Broken and cracked eggshells cause major economic losses to the egg production industry. An F2 population of 262 hens obtained by crossing a strong egg shell line with a weak egg shell line of the White Leghorn breed was used for detecting the quantitative trait loci （QTL） affecting eggshell quality. The 2 lines were developed from the same founder population by two-way selection for egg shell strength with nondestructive deformation. Of the 1 014 microsatellite markers tested, 35 were mapped on 10 autosomal linkage groups. There was no informative marker on chromosome Z. The QTLs associated with 7 traits, i.e., body weight, short length of egg, long length of egg, eggshell strength, eggshell thickness （EST）, eggshell weight （ESW）, and egg weight （EW）, were identified. Highly significant （P〈0.01） QTLs associated with EST and ESW and a significant （P〈 0.05） QTL associated with EW were mapped to a region flanking ABR0545 and ABR0362 on chromosome 9. These QTLs are good candidates to be employed in the development of strategies for reducing the number of broken and cracked eggs in commercial layer houses by employing marker assisted selection.

Mapping Quantitative Trait Loci Controlling Endosperm Traits with Molecular Marker

Based on the genetic models for triploid endosperm traits and on the methods for mapping diploid quantitative traits loci (QTLs), the genetic constitutions, components of means and genetic variances of QTL controlling endosperm traits under flanking marker genotypes of different generations were presented. From these results, a multiple linear regression method for mapping QTL underlying endosperm traits in cereals was proposed, which used the means of endosperm traits under flanking marker genotypes as a dependent variable, the coefficient of additive effect (d) and dominance effect (h1 and/or h2) of a putative QTL in a given interval as independent variables. This method can work at any position in a genome covered by markers and increase the estimation precision of QTL location and their effects by eliminating the interference of other relative QTLs. This method can also be easily used in other uneven data such as markers and quantitative traits detected or measured in plants and tissues different either in generations or at chromosomal ploidy levels, and in endosperm traits controlled by complicated genetic models considering the effects produced by genotypes of both maternal plants and seeds on them.

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.