Pythium stalk rot(PSR)is a destructive disease of maize,severely affecting yield and grain quality.The identification of quantitative trait loci(QTL)or genes for resistance to PSR forms the basis of diseaseresistant h...Pythium stalk rot(PSR)is a destructive disease of maize,severely affecting yield and grain quality.The identification of quantitative trait loci(QTL)or genes for resistance to PSR forms the basis of diseaseresistant hybrids breeding.In this study,a major QTL,Resistance to Pythium stalk rot 1(RPSR1),was identified from a set of recombinant inbred lines derived from MS71 and POP.Using a recombinant progeny testing strategy,RPSR1 was fine-mapped in a 472 kb interval.Through candidate gene expression,gene knock-down and knock-out studies,a leucine-rich repeat receptor-like kinase gene,PEP RECEPTOR 2(ZmPEPR2),was assigned as a PSR resistance gene.These results provide insights into the genetic architecture of resistance to PSR in maize,which should facilitate breeding maize for resistance to stalk rot.展开更多
Heading date is one of the most important agronomic traits that directly affect rice yield and determines the regional adaptability in specific growing environments.As a short-day plant,rice can grow under long-day(LD...Heading date is one of the most important agronomic traits that directly affect rice yield and determines the regional adaptability in specific growing environments.As a short-day plant,rice can grow under long-day(LD)conditions due to the synergistic regulation of many photosensitive genes.Using a set of chromosome segment substitution lines(CSSLs)with the indica cultivar Huanghuazhan(HHZ)as the recipient parent and Basmati Surkh 89-15(BAS)as the donor parent,we identified a QTL locus.展开更多
Genome-wide association study（GWAS） can be used to identify genes that increase the risk of psychiatric diseases.However,much of the disease heritability is still unexplained,suggesting that there are genes to be di...Genome-wide association study（GWAS） can be used to identify genes that increase the risk of psychiatric diseases.However,much of the disease heritability is still unexplained,suggesting that there are genes to be discovered.Functional annotation of the genetic variants may increase the power of GWAS to identify disease genes,by providing prior information that can be used in Bayesian analysis or in reducing the number of tests.Expression quantitative trait loci（eQTLs） are genomic loci that regulate gene expression.Genetic mapping of eQTLs can help reveal novel functional effects of thousands of single nucleotide polymorphisms（SNPs）.The present review mainly focused on the current knowledge on brain eQTL mapping,and discussed some major methodological issues and their possible solutions.The frequently ignored problems of batch effects,covariates,and multiple testing were emphasized,since they can lead to false positives and false negatives.The future application of eQTL data in GWAS analysis was also discussed.展开更多
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 hav...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.展开更多
Thousand-grain weight (TGW) is a key component of grain yield in rice. This study was conducted to validate and fine-map qTGW1.2a, a quantitative trait locus for grain weight and grain size previously located in a 933...Thousand-grain weight (TGW) is a key component of grain yield in rice. This study was conducted to validate and fine-map qTGW1.2a, a quantitative trait locus for grain weight and grain size previously located in a 933.6-kb region on the long arm of rice chromosome 1. Firstly, three residual heterozygotes (RHs) were selected from a BC2F11 population of the indica rice cross Zhenshan 97 (ZS97)///ZS97//ZS97/Milyang 46. The heterozygous segments in these RHs were arranged successively in physical positions, forming one set of sequential residual heterozygotes (SeqRHs). In each of the populations derived, non-recombinant homozygotes were identified to produce near isogenic lines (NILs) comprising the two homozygous genotypes. The NILs were tested for grain weight, grain length and grain width. QTL analyses for the three traits were performed. Then, the updated QTL location was followed for a new run of SeqRHs identification-NIL development-QTL mapping. Altogether, 11 NIL populations derived from four sets of SeqRHs were developed and used. qTGW1.2a was finally delimitated into a 77.5-kb region containing 13 annotated genes. In the six populations segregating this QTL, which were in four generations and were tested across four years, the allelic direction of qTGW1.2a remained consistent and the genetic effects were stable. For TGW, the additive effects ranged from 0.23 to 0.38 g and the proportions of phenotypic variance explained ranged from 26.15% to 41.65%. These results provide a good foundation for the cloning and functional analysis of qTGW1.2a.展开更多
Genetic linkage maps are essential for studies of genetics, genomic structure, and genomic evolution, and for mapping quantitative trait loci (QTL). Identification of molecular markers and construction of genetic link...Genetic linkage maps are essential for studies of genetics, genomic structure, and genomic evolution, and for mapping quantitative trait loci (QTL). Identification of molecular markers and construction of genetic linkage maps in tobacco (Nicotiana tabacum L.), a classical model plant and important economic crop, have remained limited. In the present study we identified a large number of single nucleotide polymorphism (SNP) markers and constructed a high-density SNP genetic map for tobacco using restriction site-associated DNA sequencing. In 1216.30 Gb of clean sequence obtained using the Illumina HiSeq 2000 sequencing platform, 99,647,735 SNPs were identified that differed between 203 sequenced plant genomes and the tobacco reference genome. Finally, 13,273 SNP markers were mapped on 24 high-density tobacco genetic linkage groups. The entire linkage map spanned 3421.80 cM, with a mean distance of 0.26 cM between adjacent markers. Compared with genetic linkage maps published previously, this version represents a considerable improvement in the number and density of markers. Seven QTL for resistance to cucumber mosaic virus (CMV) in tobacco were mapped to groups 5 and 8. This high-density genetic map is a promising tool for elucidation of the genetic bases of QTL and for molecular breeding in tobacco.展开更多
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 und...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.展开更多
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...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.展开更多
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...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.展开更多
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 locat...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.展开更多
Efficient and accurate identification of candidate causal genes within quantitative trait loci(QTL)is a significant challenge in genetic research.Conventional linkage analysis methods often require substantial time an...Efficient and accurate identification of candidate causal genes within quantitative trait loci(QTL)is a significant challenge in genetic research.Conventional linkage analysis methods often require substantial time and resources to identify causal genes.This paper proposes a QTG-LGBM method for prioritizing causal genes in maize based on the Light GBM algorithm.QTG-LGBM dynamically adjusts gene weights and sample proportions during training to mitigate the effects of class imbalance.The method prevents overfitting in datasets with small samples by introducing a regularization term.Experimental results on maize traits,including plant height(PH),flowering time(FT),and tassel branch number(TBN),demonstrated that QTG-LGBM outperforms the commonly used methods QTG-Finder,GBDT,XGBoost,Bernoulli NB,SVM,CNN,and ensemble learning.We validated the generalization of QTG-LGBM using Arabidopsis,rice,Setaria,and sorghum.We also applied QTG-LGBM using reported QTL that affect traits of maize PH,FT and TBN,and FT in Arabidopsis,rice,and sorghum,as well as known causal genes within the QTL.When examining the top 20%of ranked genes,QTG-LGBM demonstrated a significantly higher recall rate of causal genes compared to random selection methods.We identified key gene features affecting phenotypes through feature importance analysis.QTG-LGBM is available at http://www.deepcba.com/QTG-LGBM.展开更多
Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interacti...Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interaction network for these QTGs has not yet been established.In this study,we use 18K-rice lines to identify QTGs and their epistatic interactions affecting rice heading date.We identify 264 pairs of interacting quantitative trait loci(QTL)and construct a comprehensive genetic network of these QTL.On average,the epistatic effects of QTL pairs are estimated to be approximately 12.5%of additive effects of identified QTL.Importantly,epistasis varies among different alleles of several heading date genes.Additionally,57 pairs of interacting QTGs are also significant in their epistatic effects on 12 other agronomic traits.The identified QTL genetic interactions are further validated using near-isogenic lines,yeast two-hybrid,and split-luciferase complementation assays.Overall,this study provides a genetic network of rice heading date genes,which plays a crucial role in regulating rice heading date and influencing multiple related agronomic traits.This network serves as a foundation for understanding the genetic mechanisms of rice quantitative traits and for advancing rice molecular breeding.展开更多
A genetic linkage map with 89 SSR marker loci was constructed based on a maize (Zea mays L.) population consisting of 184 F-2 individuals from the cross, Huangzao 4 X Ye 107. The 184 F-3 families were evaluated in the...A genetic linkage map with 89 SSR marker loci was constructed based on a maize (Zea mays L.) population consisting of 184 F-2 individuals from the cross, Huangzao 4 X Ye 107. The 184 F-3 families were evaluated in the field under well-watered and drought-stressed regimes in Shanxi Province of China. The objectives of the study were to identify genetic segments responsible for the expression of anthesis-silking interval (ASI), ear setting and grain yield, and to examine if the quantitative trait loci (QTLs) for ASI or yield components can be used in marker-assisted selection (MAS) to improve grain yield under drought conditions. Results showed that under well-watered and drought-stressed regimes, three and two QTLs involved in the expression of ASI were detected on chromosomes 1, 2 and 3, and 2 and 5, respectively. Under well-watered regime, two QTLs for ear setting were detected on chromosomes 3 and 6, explaining about 19.9% of the phenotypic variance, and displayed additive and partial dominant effects, respectively. Under drought-stressed condition, four QTLs for ear setting were detected on chromosomes 3, 7 and 10, which were responsible for interpreting 60.4% of the phenotypic variance, and showed dominant or partial dominant effects. Under well-watered condition, four QTLs controlling grain yield were identified on chromosomes 3, 6 and 7, while five QTLs were identified under drought stress on chromosomes 1, 2, 4 and 8. The gene action was of additive or partial dominant effects, and each QTL could explain 7.3% to 22.0% of the phenotypic variance, respectively. Under drought conditions, ASI and ear setting percentage were highly correlated with grain yield, which can be used as secondary traits for grain yield selection. Based on linked markers detected and gene action analyzed, an MAS strategy for yield improvement under drought condition could be established, which consists of QTLs contributing to decreased ASI and to increased ear setting and grain yield, respectively.展开更多
Quantitative trait loci(QTL)were detected for 8 internal organ traits,3 carcass length traits,and teat number trait in 214 pigs in a resource population that included 180 F2 individuals.A total of 39 microsatellite ma...Quantitative trait loci(QTL)were detected for 8 internal organ traits,3 carcass length traits,and teat number trait in 214 pigs in a resource population that included 180 F2 individuals.A total of 39 microsatellite markers were examined on SSC4,SSC6,SSC7,SSC8,and SSC13.The genetic traits included heart weight(HW),lung weight(LW),liver and gallbladder weight(LGW),spleen weight(SPW),stomach weight(STW),small intestine weight(S1W),large intestine weight(LIW),kidney weight(KW),carcass length to the first cervical vertebra(CL1),carcass length to the first thoracic vertebra(CL2),rib numbers(RNS),and teat numbers(TNS).Results indicated that,3 highly significant QTL(P≤0.01 at chromosome-wise level)for HW(at 30 cM on SSC6),RNS(at 115 cM on SSC7),TNS(at 110 cM on SSC7),and 6 significant QTL(P≤0.05 at chromosome-wise level)for LW(at 119 cM on SSC13),LGW(at 94 cM on SSC6),SPW(at 106 cM on SSC8),SIW(0 cM on SSC4),LIW(170 cM on SSC 4),and TNS(at 95 cM on SSC6)were detected.The phenotypic variances for which these QTL were accounted ranged from 0.04%to 14.06%.Most of these QTL had not been previously reported.展开更多
In order to identify the resistant gene of rice false smut in rice, a recombi- nant inbred line （RILs） population with 157 lines derived from an inter-subspecies cross of Daguandao/IR28 by the single seed descent me...In order to identify the resistant gene of rice false smut in rice, a recombi- nant inbred line （RILs） population with 157 lines derived from an inter-subspecies cross of Daguandao/IR28 by the single seed descent method was used to detect quantitative trait loci （QTLs） conferring resistance to strain Pi-1 of rice false smut caused by Usti/aginoiclea virens （Cooke） Takahashi in 2012 and 2013. The disease rate indexes of the two parents and 157 RILs caused by the strain Pi-1 of rice false smut were scored and the QTLs for rice false smut resistance were detected accordingly by QTL Cartographer software. Seven QTLs controlling false smut re- sistance were detected on chromosomes 2, 7, 8, 11 and 12, respectively, with the phenotypic variance of 8.5%-17.2%. There were four QTLs detected in 2012 and 2013, respectively, and only one QTL was found in both two years, the phenotypic variation explained by this individual QTL was 13.5% and 17.2%, and the additive effects of this QTL contributed to the 9.9% and 14.3% decrease of disease index and therefore the disease resistance increased. The direction of the additive effects at five loci qFsr2a, qFsr8a, qFsr8b, qFsr11 and qFsr12 coincided with that predicted by phenotypes of the parents, and the IR28 alleles at these loci had positive effect against rice false smut while the negative effects were found in Daguandao alleles at qFsr2b and qFsr7. The qFsr11 should be useful in rice breeding for resistance to rice false smut in marker-assisted selection （MAS） program.展开更多
To identify genetic factors underlying phosphorus (P) uptake and use efficiency under low_P stress in rice (Oryza sativa L.), 84 selected genotypes (recombinant inbred lines) and their parents (which differed in toler...To identify genetic factors underlying phosphorus (P) uptake and use efficiency under low_P stress in rice (Oryza sativa L.), 84 selected genotypes (recombinant inbred lines) and their parents (which differed in tolerance for low_P stress) “IR20” and IR55178_3B_9_3, were cultured in liquid medium supplemented with adequate and low P levels in a greenhouse. Plants were sampled after 6 weeks in culture for measurements of plant dry weight, P concentration, P uptake and P use efficiency under both P sufficient and stress conditions. A total of 179 molecular markers, including 26 RFLPs and 153 AFLPs, mapped on all 12 chromosomes of rice based on the 84 selected genotypes were used to detect the quantitative trait loci (QTLs) underlying tolerance for low_P stress. Three QTLs were detected on chromosomes 6, 7 and 12, respectively, for relative plant dry weight (RPDW) and relative P uptake (RPUP). One of the QTLs flanked by RG9 and RG241 on chromosome 12 had a major effect which explained about 50% of the variations in the two parameters across the population. The results coincided with the QTLs for low_P stress based on relative tillering ability from the same population from a cross between Nipponbare and Kasalath under soil condition. The identical major QTL for P uptake and plant growth under low_P stress in both liquid medium and soil strongly suggests that the ability of P uptake mainly controls rice tolerance for low_P stress.展开更多
Rice (Oryza sativa L.) eating and cooking quality is mainly influenced by its starch properties. Mapping quantitative trait loci (QTL) for starch properties not only helps us understand their genetic basis leading to ...Rice (Oryza sativa L.) eating and cooking quality is mainly influenced by its starch properties. Mapping quantitative trait loci (QTL) for starch properties not only helps us understand their genetic basis leading to acceleration of quality improvement, but also helps us find possible genes participating in the synthesis of starch. A recombinant inbred line (RIL) population consisting of 107 lines, derived from an indica (Zaiyeqing 8, ZYQ 8) and a japonica (Jingxi 17, JX 17) rice, was used to investigate the genetic factors affecting starch quality parameters, such as apparent amylose content (AAC), gel consistency (GC), starch pasting viscosity parameters, gel textural properties, gelatinization temperature (GT) and starch retrogradation properties. A total of 44 QTLs covered chromosomes 2-6, 8, 9 and 11 were detected for the 22 traits, with at least one QTL and as many as four QTLs for each individual trait. The results indicated that two major genes were responsible for most starch property traits. The Wx gene that encodes granule bound starch synthase on chromosome 6 was significant for AAC, GC, starch pasting viscosity parameters, gel textural properties and starch retrogradation properties. The alk gene linked with Wx on chromosome 6 was significant for starch gelatinization temperature characteristics. All other QTLs were minor genes. One QTL on chromosome 9 flanked by RZ404 and G295 was significant for gel hardness (HD), gumminess (GUM), chewiness (CHEW), peak temperature of retrogradated starch (RTp), and percentage retrogradation (R%) and all these traits were not tested before.展开更多
Seed vigor is an important characteristic of seed quality,and rice cultivars with strong seed vigor are desirable in direct-sowing rice production for optimum stand establishment.In the present study,the quantitative ...Seed vigor is an important characteristic of seed quality,and rice cultivars with strong seed vigor are desirable in direct-sowing rice production for optimum stand establishment.In the present study,the quantitative trait loci (QTLs) of three traits for rice seed vigor during the germination stage,including germination rate,final germination percentage,and germination index,were investigated using one recombinant inbred line (RIL) population derived from a cross between japonica Daguandao and indica IR28,and using the multiple interval mapping (MIM) approach.The results show that indica rice presented stronger seed vigor during the germination stage than japonica rice.A total of ten QTLs,and at least five novel alleles,were detected to control rice seed vigor,and the amount of variation (R2) explained by an individual QTL ranged from 7.5% to 68.5%,with three major QTLs with R2>20%.Most of the QTLs detected here are likely to coincide with QTLs for seed weight,seed size,or seed dormancy,suggesting that the rice seed vigor might be correlated with seed weight,seed size,and seed dormancy.At least five QTLs are novel alleles with no previous reports of seed vigor genes in rice,and those major or minor QTLs could be used to significantly improve the seed vigor by marker-assisted selection (MAS) in rice.展开更多
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 co...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.展开更多
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 pop...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.展开更多
基金supported by National Natural Science Foundation of China(32302371 to Junbin Chen)the National Key Research and Development Program,Ministry of Science and Technology of China(2022YFD1201802 to Wangsheng Zhu)Research Program from State Key Laboratory of Maize Biobreeding(SKLMB2424 to Wangsheng Zhu).
文摘Pythium stalk rot(PSR)is a destructive disease of maize,severely affecting yield and grain quality.The identification of quantitative trait loci(QTL)or genes for resistance to PSR forms the basis of diseaseresistant hybrids breeding.In this study,a major QTL,Resistance to Pythium stalk rot 1(RPSR1),was identified from a set of recombinant inbred lines derived from MS71 and POP.Using a recombinant progeny testing strategy,RPSR1 was fine-mapped in a 472 kb interval.Through candidate gene expression,gene knock-down and knock-out studies,a leucine-rich repeat receptor-like kinase gene,PEP RECEPTOR 2(ZmPEPR2),was assigned as a PSR resistance gene.These results provide insights into the genetic architecture of resistance to PSR in maize,which should facilitate breeding maize for resistance to stalk rot.
基金supported by the Zhejiang Provincial Natural Science Foundation of China(Grant Nos.LZ24C130004 and LQ24C130008)。
文摘Heading date is one of the most important agronomic traits that directly affect rice yield and determines the regional adaptability in specific growing environments.As a short-day plant,rice can grow under long-day(LD)conditions due to the synergistic regulation of many photosensitive genes.Using a set of chromosome segment substitution lines(CSSLs)with the indica cultivar Huanghuazhan(HHZ)as the recipient parent and Basmati Surkh 89-15(BAS)as the donor parent,we identified a QTL locus.
文摘Genome-wide association study（GWAS） can be used to identify genes that increase the risk of psychiatric diseases.However,much of the disease heritability is still unexplained,suggesting that there are genes to be discovered.Functional annotation of the genetic variants may increase the power of GWAS to identify disease genes,by providing prior information that can be used in Bayesian analysis or in reducing the number of tests.Expression quantitative trait loci（eQTLs） are genomic loci that regulate gene expression.Genetic mapping of eQTLs can help reveal novel functional effects of thousands of single nucleotide polymorphisms（SNPs）.The present review mainly focused on the current knowledge on brain eQTL mapping,and discussed some major methodological issues and their possible solutions.The frequently ignored problems of batch effects,covariates,and multiple testing were emphasized,since they can lead to false positives and false negatives.The future application of eQTL data in GWAS analysis was also discussed.
基金supported by the National Natural Science Foundation of China (31521064)the Chinese 863 Program (2014AA10A603)project of the China National Rice Research Institute (2014RG003-1)
文摘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.
基金funded by the National Key R&D Program of China (Grant No. 2017YFD0100305)the National Natural Science Foundation of China (Grant No. 31521064)a project of the China National Rice Research Institute (Grant No. 2017RG001-2)
文摘Thousand-grain weight (TGW) is a key component of grain yield in rice. This study was conducted to validate and fine-map qTGW1.2a, a quantitative trait locus for grain weight and grain size previously located in a 933.6-kb region on the long arm of rice chromosome 1. Firstly, three residual heterozygotes (RHs) were selected from a BC2F11 population of the indica rice cross Zhenshan 97 (ZS97)///ZS97//ZS97/Milyang 46. The heterozygous segments in these RHs were arranged successively in physical positions, forming one set of sequential residual heterozygotes (SeqRHs). In each of the populations derived, non-recombinant homozygotes were identified to produce near isogenic lines (NILs) comprising the two homozygous genotypes. The NILs were tested for grain weight, grain length and grain width. QTL analyses for the three traits were performed. Then, the updated QTL location was followed for a new run of SeqRHs identification-NIL development-QTL mapping. Altogether, 11 NIL populations derived from four sets of SeqRHs were developed and used. qTGW1.2a was finally delimitated into a 77.5-kb region containing 13 annotated genes. In the six populations segregating this QTL, which were in four generations and were tested across four years, the allelic direction of qTGW1.2a remained consistent and the genetic effects were stable. For TGW, the additive effects ranged from 0.23 to 0.38 g and the proportions of phenotypic variance explained ranged from 26.15% to 41.65%. These results provide a good foundation for the cloning and functional analysis of qTGW1.2a.
基金supported by the Agricultural Science and Technology Innovation Program (ASTIP-TRIC01)
文摘Genetic linkage maps are essential for studies of genetics, genomic structure, and genomic evolution, and for mapping quantitative trait loci (QTL). Identification of molecular markers and construction of genetic linkage maps in tobacco (Nicotiana tabacum L.), a classical model plant and important economic crop, have remained limited. In the present study we identified a large number of single nucleotide polymorphism (SNP) markers and constructed a high-density SNP genetic map for tobacco using restriction site-associated DNA sequencing. In 1216.30 Gb of clean sequence obtained using the Illumina HiSeq 2000 sequencing platform, 99,647,735 SNPs were identified that differed between 203 sequenced plant genomes and the tobacco reference genome. Finally, 13,273 SNP markers were mapped on 24 high-density tobacco genetic linkage groups. The entire linkage map spanned 3421.80 cM, with a mean distance of 0.26 cM between adjacent markers. Compared with genetic linkage maps published previously, this version represents a considerable improvement in the number and density of markers. Seven QTL for resistance to cucumber mosaic virus (CMV) in tobacco were mapped to groups 5 and 8. This high-density genetic map is a promising tool for elucidation of the genetic bases of QTL and for molecular breeding in tobacco.
基金supported by the National Natural Science Foundation of China (Grant No. 31200916)the Zhejiang Provincial Project for Rice Seed Industry of Scientific and Technological Innovation Team (Grant No. 2010R50024-16)the Academy of Institute Foundation for Basic Scientific Research of China (Grant No. 2012RG002-7)
文摘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.
基金The authors thank the reviewers for their valuable comments on this manuscript and gratefully acknowledge the financial support for this study provided by grants from the Collaborative Research Key Project between China and EU(granted by the Ministry of Science and Technology of China,2017YFE0111000)the China Forage and Grass Research System(CARS-34)+1 种基金the Agricultural Science and Technology Innovation Program of CAAS(ASTIP-IAS14)the National Natural Science Foundation of China(31772656).
文摘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.
基金supported by the National Natural Science Foundation of China (31401377)the Science and Technology Project of Sichuan Province, China (2017JY0126)the Key Project of Education Department of Sichuan Province, China (14ZA0002)
文摘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.
基金supported by the National Science Foundation of China (Grant No. 31221004)a research grant of the China National Rice Research Institute (Grant No. 2012RG002-3)
文摘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.
基金supported by the Biological Breeding-Major Projects(2023ZD04067)Hubei Provincial Natural Science Foundation of China(2023AFB832)+1 种基金Guizhou Provincial Basic Research Program(Natural Science)(MS[2025]096)Major Project of Hubei Hongshan Laboratory(2022HSZD031)。
文摘Efficient and accurate identification of candidate causal genes within quantitative trait loci(QTL)is a significant challenge in genetic research.Conventional linkage analysis methods often require substantial time and resources to identify causal genes.This paper proposes a QTG-LGBM method for prioritizing causal genes in maize based on the Light GBM algorithm.QTG-LGBM dynamically adjusts gene weights and sample proportions during training to mitigate the effects of class imbalance.The method prevents overfitting in datasets with small samples by introducing a regularization term.Experimental results on maize traits,including plant height(PH),flowering time(FT),and tassel branch number(TBN),demonstrated that QTG-LGBM outperforms the commonly used methods QTG-Finder,GBDT,XGBoost,Bernoulli NB,SVM,CNN,and ensemble learning.We validated the generalization of QTG-LGBM using Arabidopsis,rice,Setaria,and sorghum.We also applied QTG-LGBM using reported QTL that affect traits of maize PH,FT and TBN,and FT in Arabidopsis,rice,and sorghum,as well as known causal genes within the QTL.When examining the top 20%of ranked genes,QTG-LGBM demonstrated a significantly higher recall rate of causal genes compared to random selection methods.We identified key gene features affecting phenotypes through feature importance analysis.QTG-LGBM is available at http://www.deepcba.com/QTG-LGBM.
基金supported by the National Natural Science Foundation of China(32222064 and 32341030)the Natural Science Foundation of Shanghai(22ZR1445800)Zhejiang Provincial Natural Science Foundation of China(LQ24C130008).
文摘Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interaction network for these QTGs has not yet been established.In this study,we use 18K-rice lines to identify QTGs and their epistatic interactions affecting rice heading date.We identify 264 pairs of interacting quantitative trait loci(QTL)and construct a comprehensive genetic network of these QTL.On average,the epistatic effects of QTL pairs are estimated to be approximately 12.5%of additive effects of identified QTL.Importantly,epistasis varies among different alleles of several heading date genes.Additionally,57 pairs of interacting QTGs are also significant in their epistatic effects on 12 other agronomic traits.The identified QTL genetic interactions are further validated using near-isogenic lines,yeast two-hybrid,and split-luciferase complementation assays.Overall,this study provides a genetic network of rice heading date genes,which plays a crucial role in regulating rice heading date and influencing multiple related agronomic traits.This network serves as a foundation for understanding the genetic mechanisms of rice quantitative traits and for advancing rice molecular breeding.
文摘A genetic linkage map with 89 SSR marker loci was constructed based on a maize (Zea mays L.) population consisting of 184 F-2 individuals from the cross, Huangzao 4 X Ye 107. The 184 F-3 families were evaluated in the field under well-watered and drought-stressed regimes in Shanxi Province of China. The objectives of the study were to identify genetic segments responsible for the expression of anthesis-silking interval (ASI), ear setting and grain yield, and to examine if the quantitative trait loci (QTLs) for ASI or yield components can be used in marker-assisted selection (MAS) to improve grain yield under drought conditions. Results showed that under well-watered and drought-stressed regimes, three and two QTLs involved in the expression of ASI were detected on chromosomes 1, 2 and 3, and 2 and 5, respectively. Under well-watered regime, two QTLs for ear setting were detected on chromosomes 3 and 6, explaining about 19.9% of the phenotypic variance, and displayed additive and partial dominant effects, respectively. Under drought-stressed condition, four QTLs for ear setting were detected on chromosomes 3, 7 and 10, which were responsible for interpreting 60.4% of the phenotypic variance, and showed dominant or partial dominant effects. Under well-watered condition, four QTLs controlling grain yield were identified on chromosomes 3, 6 and 7, while five QTLs were identified under drought stress on chromosomes 1, 2, 4 and 8. The gene action was of additive or partial dominant effects, and each QTL could explain 7.3% to 22.0% of the phenotypic variance, respectively. Under drought conditions, ASI and ear setting percentage were highly correlated with grain yield, which can be used as secondary traits for grain yield selection. Based on linked markers detected and gene action analyzed, an MAS strategy for yield improvement under drought condition could be established, which consists of QTLs contributing to decreased ASI and to increased ear setting and grain yield, respectively.
基金supported by the State Key Basic Research and Development Plan of China(No.2006CB102102)the National Natural Science Foundation of China(No.30500358).
文摘Quantitative trait loci(QTL)were detected for 8 internal organ traits,3 carcass length traits,and teat number trait in 214 pigs in a resource population that included 180 F2 individuals.A total of 39 microsatellite markers were examined on SSC4,SSC6,SSC7,SSC8,and SSC13.The genetic traits included heart weight(HW),lung weight(LW),liver and gallbladder weight(LGW),spleen weight(SPW),stomach weight(STW),small intestine weight(S1W),large intestine weight(LIW),kidney weight(KW),carcass length to the first cervical vertebra(CL1),carcass length to the first thoracic vertebra(CL2),rib numbers(RNS),and teat numbers(TNS).Results indicated that,3 highly significant QTL(P≤0.01 at chromosome-wise level)for HW(at 30 cM on SSC6),RNS(at 115 cM on SSC7),TNS(at 110 cM on SSC7),and 6 significant QTL(P≤0.05 at chromosome-wise level)for LW(at 119 cM on SSC13),LGW(at 94 cM on SSC6),SPW(at 106 cM on SSC8),SIW(0 cM on SSC4),LIW(170 cM on SSC 4),and TNS(at 95 cM on SSC6)were detected.The phenotypic variances for which these QTL were accounted ranged from 0.04%to 14.06%.Most of these QTL had not been previously reported.
基金Supported by the National Natural Science Foundation of China(31071397)the Agricultural Science and Technology Innovation Fund Project of Jiangsu Province(CX(15)1054)~~
文摘In order to identify the resistant gene of rice false smut in rice, a recombi- nant inbred line （RILs） population with 157 lines derived from an inter-subspecies cross of Daguandao/IR28 by the single seed descent method was used to detect quantitative trait loci （QTLs） conferring resistance to strain Pi-1 of rice false smut caused by Usti/aginoiclea virens （Cooke） Takahashi in 2012 and 2013. The disease rate indexes of the two parents and 157 RILs caused by the strain Pi-1 of rice false smut were scored and the QTLs for rice false smut resistance were detected accordingly by QTL Cartographer software. Seven QTLs controlling false smut re- sistance were detected on chromosomes 2, 7, 8, 11 and 12, respectively, with the phenotypic variance of 8.5%-17.2%. There were four QTLs detected in 2012 and 2013, respectively, and only one QTL was found in both two years, the phenotypic variation explained by this individual QTL was 13.5% and 17.2%, and the additive effects of this QTL contributed to the 9.9% and 14.3% decrease of disease index and therefore the disease resistance increased. The direction of the additive effects at five loci qFsr2a, qFsr8a, qFsr8b, qFsr11 and qFsr12 coincided with that predicted by phenotypes of the parents, and the IR28 alleles at these loci had positive effect against rice false smut while the negative effects were found in Daguandao alleles at qFsr2b and qFsr7. The qFsr11 should be useful in rice breeding for resistance to rice false smut in marker-assisted selection （MAS） program.
文摘To identify genetic factors underlying phosphorus (P) uptake and use efficiency under low_P stress in rice (Oryza sativa L.), 84 selected genotypes (recombinant inbred lines) and their parents (which differed in tolerance for low_P stress) “IR20” and IR55178_3B_9_3, were cultured in liquid medium supplemented with adequate and low P levels in a greenhouse. Plants were sampled after 6 weeks in culture for measurements of plant dry weight, P concentration, P uptake and P use efficiency under both P sufficient and stress conditions. A total of 179 molecular markers, including 26 RFLPs and 153 AFLPs, mapped on all 12 chromosomes of rice based on the 84 selected genotypes were used to detect the quantitative trait loci (QTLs) underlying tolerance for low_P stress. Three QTLs were detected on chromosomes 6, 7 and 12, respectively, for relative plant dry weight (RPDW) and relative P uptake (RPUP). One of the QTLs flanked by RG9 and RG241 on chromosome 12 had a major effect which explained about 50% of the variations in the two parameters across the population. The results coincided with the QTLs for low_P stress based on relative tillering ability from the same population from a cross between Nipponbare and Kasalath under soil condition. The identical major QTL for P uptake and plant growth under low_P stress in both liquid medium and soil strongly suggests that the ability of P uptake mainly controls rice tolerance for low_P stress.
文摘Rice (Oryza sativa L.) eating and cooking quality is mainly influenced by its starch properties. Mapping quantitative trait loci (QTL) for starch properties not only helps us understand their genetic basis leading to acceleration of quality improvement, but also helps us find possible genes participating in the synthesis of starch. A recombinant inbred line (RIL) population consisting of 107 lines, derived from an indica (Zaiyeqing 8, ZYQ 8) and a japonica (Jingxi 17, JX 17) rice, was used to investigate the genetic factors affecting starch quality parameters, such as apparent amylose content (AAC), gel consistency (GC), starch pasting viscosity parameters, gel textural properties, gelatinization temperature (GT) and starch retrogradation properties. A total of 44 QTLs covered chromosomes 2-6, 8, 9 and 11 were detected for the 22 traits, with at least one QTL and as many as four QTLs for each individual trait. The results indicated that two major genes were responsible for most starch property traits. The Wx gene that encodes granule bound starch synthase on chromosome 6 was significant for AAC, GC, starch pasting viscosity parameters, gel textural properties and starch retrogradation properties. The alk gene linked with Wx on chromosome 6 was significant for starch gelatinization temperature characteristics. All other QTLs were minor genes. One QTL on chromosome 9 flanked by RZ404 and G295 was significant for gel hardness (HD), gumminess (GUM), chewiness (CHEW), peak temperature of retrogradated starch (RTp), and percentage retrogradation (R%) and all these traits were not tested before.
基金Project supported by the National Natural Science Foundation of China (No. 31000748)the Natural Science Foundation of Jiangsu Province (No. BK2010452)the Science and Technology Innovation Foun-dation of Nanjing Agricultural University (No. KJ09003), China
文摘Seed vigor is an important characteristic of seed quality,and rice cultivars with strong seed vigor are desirable in direct-sowing rice production for optimum stand establishment.In the present study,the quantitative trait loci (QTLs) of three traits for rice seed vigor during the germination stage,including germination rate,final germination percentage,and germination index,were investigated using one recombinant inbred line (RIL) population derived from a cross between japonica Daguandao and indica IR28,and using the multiple interval mapping (MIM) approach.The results show that indica rice presented stronger seed vigor during the germination stage than japonica rice.A total of ten QTLs,and at least five novel alleles,were detected to control rice seed vigor,and the amount of variation (R2) explained by an individual QTL ranged from 7.5% to 68.5%,with three major QTLs with R2>20%.Most of the QTLs detected here are likely to coincide with QTLs for seed weight,seed size,or seed dormancy,suggesting that the rice seed vigor might be correlated with seed weight,seed size,and seed dormancy.At least five QTLs are novel alleles with no previous reports of seed vigor genes in rice,and those major or minor QTLs could be used to significantly improve the seed vigor by marker-assisted selection (MAS) in rice.
基金supported by the National 863 Program of China (2011AA10A101)the Chinese High-Yielding Transgenic Program (2011ZX08001-004)a project of the State Key Laboratory of Rice Biology,China(ZZKT201101)
文摘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.
文摘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.
