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 pre...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.展开更多
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 significan...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.展开更多
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 quan...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.展开更多
[ Objective] The objective of this study was to evaluate the genetic diversity and characterization of special maize population consisting of 135 Fl fami- lies. [ Method ] In this study, association analysis was condu...[ Objective] The objective of this study was to evaluate the genetic diversity and characterization of special maize population consisting of 135 Fl fami- lies. [ Method ] In this study, association analysis was conducted in 135 F1 families derived from two maize landraces, and the efficiency of this method was evalua- ted through simulation. [ Result] Association analysis with different kinds of families showed that large population size and robust phenotypic data were required for association mapping. For all the phenotypic traits, the model controlling beth population structure and relative kinship （ Q ＋ K） performed better than the model controlling relative kinship （K）, and similarly to the model controlling population structure （Q）. Across 100 simulation runs in QULINE, the average power of QTL detection for the two models were 88.64% and 83.64% respectively, and the number of false QTL was reduced from 399 with GLM model to 199 with K mod- el. Our simulation results suggested that these F1 families can be used for association analysis, and the power of the QTL detection was related to the maximum al- lele frequency （MAF）and the phenotypic variation （PVE） explained by QTL. [ Conclusion] The results from this study suggest that association analysis using the F1 families is an effective approach to study maize landraces for discovering elite genes which we are interested in from these special populations.展开更多
Quantitative trait loci (QTL) analysis was conducted in bread wheat for 14 important traits utilizing data from four different mapping populations involving different approaches of QTL analysis. Analysis for grain pro...Quantitative trait loci (QTL) analysis was conducted in bread wheat for 14 important traits utilizing data from four different mapping populations involving different approaches of QTL analysis. Analysis for grain protein content (GPC) sug- gested that the major part of genetic variation for this trait is due to environmental interactions. In contrast, pre-harvest sprouting tolerance (PHST) was controlled mainly by main effect QTL (M-QTL) with very little genetic variation due to environmental interactions; a major QTL for PHST was detected on chromosome arm 3AL. For grain weight, one QTL each was detected on chromosome arms 1AS, 2BS and 7AS. QTL for 4 growth related traits taken together detected by different methods ranged from 37 to 40; nine QTL that were detected by single-locus as well as two-locus analyses were all M-QTL. Similarly, single-locus and two-locus QTL analyses for seven yield and yield contributing traits in two populations respectively allowed detection of 25 and 50 QTL by composite interval mapping (CIM), 16 and 25 QTL by multiple-trait composite interval mapping (MCIM) and 38 and 37 QTL by two-locus analyses. These studies should prove useful in QTL cloning and wheat improvement through marker aided selection.展开更多
Quantitative traits often underlie risk for complex diseases. Many studies collect multiple correlated quantitative phenotypes and perform univariate analyses on each of them respectively. However, this strategy may n...Quantitative traits often underlie risk for complex diseases. Many studies collect multiple correlated quantitative phenotypes and perform univariate analyses on each of them respectively. However, this strategy may not be powerful and has limitations to detect plei- otropic genes that may underlie correlated quantitative traits. In addition, testing multiple traits individually will exacerbate perplexing problem of multiple testing. In this study, generalized estimating equation 2 （GEE2） is applied to association mapping of two correlated quantitative traits. We suppose that a quantitative trait locus is located in a chromosome region that exerts pleiotropic effects on multiple quantitative traits. In that region, multiple SNPs are genotyped. Genotypes of these SNPs and the two quantitative traits affected by a causal SNP were simulated under various parameter values： residual correlation coefficient between two traits, causal SNP heritability, minor allele frequency of the causal SNP, extent of linkage disequilibrium with the causal SNP, and the test sample size. By power ana- lytical analyses, it is showed that the bivariate method is generally more powerful than the univariate method. This method is robust and yields false-positive rates close to the pre-set nominal significance level. Our real data analyses attested to the usefulness of the method.展开更多
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
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
Gossypium raimondii(2n=2x=26,D_(5)),an untapped wild species,is the putative progenitor of the D-subgenome of G.hirsutum(2n=4x=52,AD_(1)),an extensively cultivated species.Here,we developed a G.hirsutum(recipient)–G....Gossypium raimondii(2n=2x=26,D_(5)),an untapped wild species,is the putative progenitor of the D-subgenome of G.hirsutum(2n=4x=52,AD_(1)),an extensively cultivated species.Here,we developed a G.hirsutum(recipient)–G.raimondii(donor)introgression population to exploit the favorable QTLs/genes and mapped potential quantitative trait loci(QTLs)from wild cotton species.The introgression population consisted of 256 lines with an introgression rate of 52.33%for the G.raimondii genome.The introgression segment length range was 0.03–19.12 Mb,with an average of 1.22 Mb.The coverage of total introgression fragments from G.raimondii was 386.98 Mb.Further genome-wide association analysis(Q+K+MLM)and QTL mapping(RSTEP-LRT)identified 59 common QTLs,including 14 stable QTLs and six common QTL(co-QTL)clusters,and one hotspot of micronaire(MIC).The common QTLs for seed index all showed positive additive effects,while the common QTLs for boll weight all had negative additive effects,indicating that the linkage between seed index and boll weight could be broken.QTLs for lint percentage showed positive effects and could be beneficial for improving cotton yield.Most QTLs for fiber quality had negative additive effects,implying these QTLs were domesticated/improved in G.hirsutum.A few fiber quality QTLs showed positive additive effects,so they could be used to improve cotton fiber quality.The introgression lines developed could be useful for molecular marker-assisted breeding and mapping QTLs precisely for mining desirable genes from the wild species G.raimondii.Such genes can improve cultivated cotton in the future through a designbreeding approach.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
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
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 microsatel...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
The Clustered Regularly Interspaced Short Palindromic Repeats （CRISPR）-associated protein 9 （CRISPR/Cas9）-based genomeediting system is a revolutionary technology for targeted muta- genesis in molecular biology re...The Clustered Regularly Interspaced Short Palindromic Repeats （CRISPR）-associated protein 9 （CRISPR/Cas9）-based genomeediting system is a revolutionary technology for targeted muta- genesis in molecular biology research and genetic improvement of traits in crops （Cong et al., 2013; Ma et al., 2015, 2016）. Agronomic traits of crops are controlled by major genes and quantitative trait loci （QTL）. Therefore, the CRISPR/Cas9 system can be used to effectively and rapidly produce mutant traits by different strategies （Figure 1A-1C）. The most common application of the targeted editing system in genetic improvement is to knock out completely the functions of target genes, usually by editing site（s） in the coding sequences （CDS） to produce null-allele mutants （Figure 1A）.展开更多
Based on the traditional polygene inheritance model of quantitative traits,the author suggests the major gene and polygene mixed inheritance model.The model was considered as a general one,while the pure major gene an...Based on the traditional polygene inheritance model of quantitative traits,the author suggests the major gene and polygene mixed inheritance model.The model was considered as a general one,while the pure major gene and pure polygene inheritance model was a specific case of the general model.Based on the proposed theory,the author established the segregation analysis procedure to study the genetic system of quantitative traits of plants.At present,this procedure can be used to evaluate the genetic effect of individual major genes(up to two to three major genes),the collective genetic effect of polygene,and their heritability value.This paper introduces how to establish the procedure,its main achievements,and its applications.An example is given to illustrate the steps,methods,and effectiveness of the procedure.展开更多
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 ...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.展开更多
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 ...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.展开更多
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 head...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.展开更多
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...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.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
The present study aims to identify QTL influencing agronomic traits and yield components under well-watered and pre-flowering drought stress conditions. One hundred F5 recombinant inbred lines (RIL) and the parental l...The present study aims to identify QTL influencing agronomic traits and yield components under well-watered and pre-flowering drought stress conditions. One hundred F5 recombinant inbred lines (RIL) and the parental lines of a cross between a drought-tolerant and a susceptible line in a field experiment were carried out at Nong Lam University of Ho Chi Minh City, Vietnam. Drought stress was induced by withholding irrigation water from the plants at four weeks after sowing to flowering. Leaf area of the third leaf, stem diameter, plant height, days to heading, anthesis and maturity, panicle length, number of seeds per plant, hundred kernel weight and grain yield were measured. Plants were genotyped with 117 Diversity Arrays Technology (DArT) and eight expressed sequence tag (EST)-derived simple sequence repeat (SSR) markers. Composite interval mapping was carried out on the traits and significant QTL were claimed at a logarithm of the odds (LOD) score >2.5. A total of 50 QTL were detected on nine chromosomes or 13 linkage groups, respectively. Six promising QTL regions with seven QTL for yield and agronomic traits especially related to pre-flowering drought tolerance were identified on chromosomes SBI-01, SBI-03, SBI-04, SBI-05 and SBI-07.展开更多
基金supported by the National Natural Science Foundation of China (Grant No. 30700494)the Principal Fund of South China Agricultural University, China (Grant No. 2003K053)
文摘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.
文摘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.
基金This research was supported by the National Natural Science Foundation of China to Xu Chenwu （39900080, 30270724 and 30370758）.
文摘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.
基金Surpported by the Key Program of Department of Education of Sichuan Province,China(12ZB097)
文摘[ Objective] The objective of this study was to evaluate the genetic diversity and characterization of special maize population consisting of 135 Fl fami- lies. [ Method ] In this study, association analysis was conducted in 135 F1 families derived from two maize landraces, and the efficiency of this method was evalua- ted through simulation. [ Result] Association analysis with different kinds of families showed that large population size and robust phenotypic data were required for association mapping. For all the phenotypic traits, the model controlling beth population structure and relative kinship （ Q ＋ K） performed better than the model controlling relative kinship （K）, and similarly to the model controlling population structure （Q）. Across 100 simulation runs in QULINE, the average power of QTL detection for the two models were 88.64% and 83.64% respectively, and the number of false QTL was reduced from 399 with GLM model to 199 with K mod- el. Our simulation results suggested that these F1 families can be used for association analysis, and the power of the QTL detection was related to the maximum al- lele frequency （MAF）and the phenotypic variation （PVE） explained by QTL. [ Conclusion] The results from this study suggest that association analysis using the F1 families is an effective approach to study maize landraces for discovering elite genes which we are interested in from these special populations.
基金Project supported by the National Agricultural Technology Projectof Indian Council of Agricultural Research, Department of Biotech-nology of Government of India, Council of Scientific and IndustrialResearch of India and Indian National Science Academy
文摘Quantitative trait loci (QTL) analysis was conducted in bread wheat for 14 important traits utilizing data from four different mapping populations involving different approaches of QTL analysis. Analysis for grain protein content (GPC) sug- gested that the major part of genetic variation for this trait is due to environmental interactions. In contrast, pre-harvest sprouting tolerance (PHST) was controlled mainly by main effect QTL (M-QTL) with very little genetic variation due to environmental interactions; a major QTL for PHST was detected on chromosome arm 3AL. For grain weight, one QTL each was detected on chromosome arms 1AS, 2BS and 7AS. QTL for 4 growth related traits taken together detected by different methods ranged from 37 to 40; nine QTL that were detected by single-locus as well as two-locus analyses were all M-QTL. Similarly, single-locus and two-locus QTL analyses for seven yield and yield contributing traits in two populations respectively allowed detection of 25 and 50 QTL by composite interval mapping (CIM), 16 and 25 QTL by multiple-trait composite interval mapping (MCIM) and 38 and 37 QTL by two-locus analyses. These studies should prove useful in QTL cloning and wheat improvement through marker aided selection.
基金supported by grants from the Natural Science Foundation of China (No.30600364,30470534,and 30230210)the NSFC-Canadian Institutes of Health Research (CIHR) Joint Health Research Initia-tive Proposal (No.30811120436)+3 种基金the NSFC/RGC Joint Research Scheme (No.30731160618)Shanghai Leading Academic Discipline Project (No.S30501)supported by grants from NIH (No.P50AR055081,R01AG026564,R01AR050496,and R01AR057049)the Dickson/Missouri endowment
文摘Quantitative traits often underlie risk for complex diseases. Many studies collect multiple correlated quantitative phenotypes and perform univariate analyses on each of them respectively. However, this strategy may not be powerful and has limitations to detect plei- otropic genes that may underlie correlated quantitative traits. In addition, testing multiple traits individually will exacerbate perplexing problem of multiple testing. In this study, generalized estimating equation 2 （GEE2） is applied to association mapping of two correlated quantitative traits. We suppose that a quantitative trait locus is located in a chromosome region that exerts pleiotropic effects on multiple quantitative traits. In that region, multiple SNPs are genotyped. Genotypes of these SNPs and the two quantitative traits affected by a causal SNP were simulated under various parameter values： residual correlation coefficient between two traits, causal SNP heritability, minor allele frequency of the causal SNP, extent of linkage disequilibrium with the causal SNP, and the test sample size. By power ana- lytical analyses, it is showed that the bivariate method is generally more powerful than the univariate method. This method is robust and yields false-positive rates close to the pre-set nominal significance level. Our real data analyses attested to the usefulness of the method.
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 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.
基金funded by the National Key Research and Development Program of China(2016YFD0100203 and 2016YFD0102000)the Key Scientific and Technological Projects of the Eighth Division of the Xinjiang Production and Construction Corps(XPCC),China(2024NY01,2023 NY09,2023 NY10)+2 种基金the Key Scientific and Technological Project of XPCC,China(2021AB010)the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(KYCX22_0748)supported by the High-performance Computing Platform of the Bioinformatics Center,Nanjing Agricultural University,China。
文摘Gossypium raimondii(2n=2x=26,D_(5)),an untapped wild species,is the putative progenitor of the D-subgenome of G.hirsutum(2n=4x=52,AD_(1)),an extensively cultivated species.Here,we developed a G.hirsutum(recipient)–G.raimondii(donor)introgression population to exploit the favorable QTLs/genes and mapped potential quantitative trait loci(QTLs)from wild cotton species.The introgression population consisted of 256 lines with an introgression rate of 52.33%for the G.raimondii genome.The introgression segment length range was 0.03–19.12 Mb,with an average of 1.22 Mb.The coverage of total introgression fragments from G.raimondii was 386.98 Mb.Further genome-wide association analysis(Q+K+MLM)and QTL mapping(RSTEP-LRT)identified 59 common QTLs,including 14 stable QTLs and six common QTL(co-QTL)clusters,and one hotspot of micronaire(MIC).The common QTLs for seed index all showed positive additive effects,while the common QTLs for boll weight all had negative additive effects,indicating that the linkage between seed index and boll weight could be broken.QTLs for lint percentage showed positive effects and could be beneficial for improving cotton yield.Most QTLs for fiber quality had negative additive effects,implying these QTLs were domesticated/improved in G.hirsutum.A few fiber quality QTLs showed positive additive effects,so they could be used to improve cotton fiber quality.The introgression lines developed could be useful for molecular marker-assisted breeding and mapping QTLs precisely for mining desirable genes from the wild species G.raimondii.Such genes can improve cultivated cotton in the future through a designbreeding approach.
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.
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This work was 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.
文摘The Clustered Regularly Interspaced Short Palindromic Repeats （CRISPR）-associated protein 9 （CRISPR/Cas9）-based genomeediting system is a revolutionary technology for targeted muta- genesis in molecular biology research and genetic improvement of traits in crops （Cong et al., 2013; Ma et al., 2015, 2016）. Agronomic traits of crops are controlled by major genes and quantitative trait loci （QTL）. Therefore, the CRISPR/Cas9 system can be used to effectively and rapidly produce mutant traits by different strategies （Figure 1A-1C）. The most common application of the targeted editing system in genetic improvement is to knock out completely the functions of target genes, usually by editing site（s） in the coding sequences （CDS） to produce null-allele mutants （Figure 1A）.
基金supported by the Natural Science Foundation of China (No.30490250)the National Key Basic Research Program (2002CB111304,2004CB7206).
文摘Based on the traditional polygene inheritance model of quantitative traits,the author suggests the major gene and polygene mixed inheritance model.The model was considered as a general one,while the pure major gene and pure polygene inheritance model was a specific case of the general model.Based on the proposed theory,the author established the segregation analysis procedure to study the genetic system of quantitative traits of plants.At present,this procedure can be used to evaluate the genetic effect of individual major genes(up to two to three major genes),the collective genetic effect of polygene,and their heritability value.This paper introduces how to establish the procedure,its main achievements,and its applications.An example is given to illustrate the steps,methods,and effectiveness of the procedure.
基金supported by the National Natural Science Foundation of China(31771794,91731305 and 31560388)the outstanding Youth Foundation of the Department of Science and Technology of Sichuan Province,China(2016JQ0040)+1 种基金the Key Technology Research and Development Program of the Department of Science and Technology of Sichuan Province,China(2016NZ0057)the International Science&Technology Cooperation Program of the Bureau of Science and Technology of Chengdu,China(2015DFA306002015-GH03-00008-HZ)。
文摘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.
基金supported by the National Key Technologies R&D Program of China (2006BAD13B01)the National Basic Research Program of China(2005DKA21001-01)the National Crop Resources Protect Program of China [NB06-070401(22-27)-01]
文摘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.
基金funded by the Chinese High-Yielding Transgenic Program (Grant No. 2011ZX08001-004)the National High-Tech Research and Development Program (Grant No. 2011AA10A101)the Research Funding of China National Rice Research Institute(Grant No. 2009RG002)
文摘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.
基金the National Natural Science Foundation(No.39900080).
文摘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.
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 would like to thank SiekeSchaepe for DNA extractionWe gratefully acknowledge the Ministry for Education and Training,Vietnam,for financial support.
文摘The present study aims to identify QTL influencing agronomic traits and yield components under well-watered and pre-flowering drought stress conditions. One hundred F5 recombinant inbred lines (RIL) and the parental lines of a cross between a drought-tolerant and a susceptible line in a field experiment were carried out at Nong Lam University of Ho Chi Minh City, Vietnam. Drought stress was induced by withholding irrigation water from the plants at four weeks after sowing to flowering. Leaf area of the third leaf, stem diameter, plant height, days to heading, anthesis and maturity, panicle length, number of seeds per plant, hundred kernel weight and grain yield were measured. Plants were genotyped with 117 Diversity Arrays Technology (DArT) and eight expressed sequence tag (EST)-derived simple sequence repeat (SSR) markers. Composite interval mapping was carried out on the traits and significant QTL were claimed at a logarithm of the odds (LOD) score >2.5. A total of 50 QTL were detected on nine chromosomes or 13 linkage groups, respectively. Six promising QTL regions with seven QTL for yield and agronomic traits especially related to pre-flowering drought tolerance were identified on chromosomes SBI-01, SBI-03, SBI-04, SBI-05 and SBI-07.
