Spike number per m^2(SN),kernel number per spike(KNPS) and thousand-kernel weight(TKW)are the three main components determining wheat(Triticum aestivum L.) yield.To evaluate the relationships among them a doubled hapl...Spike number per m^2(SN),kernel number per spike(KNPS) and thousand-kernel weight(TKW)are the three main components determining wheat(Triticum aestivum L.) yield.To evaluate the relationships among them a doubled haploid(DH) population consisting of 168 lines grown at three locations for three years was analyzed by unconditional and conditional QTL mapping.Thirty-three unconditional QTL and fifty-nine conditional QTL were detected.Among them,two QTL(QSN-DH-2B and QSN-DH-3A-1.1) improved SN,with no effect on KNPS.QKNPS-DH-2B-2.1 improved KNPS,with no effect on SN.QKNPS-DH-1A-1.1,QKNPS-DH-2D-1.1and QKNPS-DH-6A improved KNPS,with no effect on SN or TKW.QKNPS-DH-6B was associated with increased SN and TKW.In addition,QTKW-DH-4B,QTKW-DH-5B and QTKW-DH-7B increased TKW without decreasing KNPS.These results provide useful information for marker assisted selection(MAS) and improvement in wheat yield.展开更多
Spike number per unit area, number of grains per spike, and thousand-kernel weight（TKW） are important yield components for wheat（Triticum aestivum L.）. TKW has the highest heritability among the three components. ...Spike number per unit area, number of grains per spike, and thousand-kernel weight（TKW） are important yield components for wheat（Triticum aestivum L.）. TKW has the highest heritability among the three components. We validated 27 simple sequence repeat（SSR） loci associated with TKW in an F2：5breeding population grown in four environments. A cfd78265 bpmarker on chromosome 5DS showed the strongest association with TKW and had a significantly positive effect on TKW compared to allele cfd78259 bp, with mean increases of 5.17, 3.63, 4.11, and 5.16 g in the four environments. Markers cfd67 and cfd40 flanking cfd78 also showed significantly positive associations with TKW with increases of 5.11, 3.29, 4.31, and 4.50 g for cfd67205, and4.98, 3.49, 4.06, and 4.84 g for cfd40187 compared with cfd67203 and cfd40190in the four environments, respectively. A major quantitative trait locus for TKW spanning 2.94 c M on chromosome 5DS was detected by association mapping.Strong linkage disequilibrium（LD）（r2〉 0.2） was detected Resear among the three linked markers, which formed three haplotype blocks in the F2：5breeding population. Mean TKW differences between Hap B-I and Hap B-II were 5.80, 4.41, 4.02,and 5.06 g in the four environments, respectively. Moreover,significant LD was detected only between cfd78 and cfd67 and between cfd67 and cfd40 in a germplasm collection. This study provides a base for cloning genes related to TKW on chromosome 5DS.展开更多
Investigation of genetic diversity of geographically distant wheat genotypes is </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">useful ...Investigation of genetic diversity of geographically distant wheat genotypes is </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">useful approach in wheat breeding providing efficient crop varieties. This article presents multivariate cluster and principal component analyses (PCA) of some yield traits of wheat, such as thousand-kernel weight (TKW), grain number, grain yield and plant height. Based on the results, an evaluation of economically valuable attributes by eigenvalues made it possible to determine the components that significantly contribute to the yield of common wheat genotypes. Twenty-five genotypes were grouped into four clusters on the basis of average linkage. The PCA showed four principal components (PC) with eigenvalues ></span><span style="font-family:""> </span><span style="font-family:Verdana;">1, explaining approximately 90.8% of the total variability. According to PC analysis, the variance in the eigenvalues was </span><span style="font-family:Verdana;">the </span><span style="font-family:Verdana;">greatest (4.33) for PC-1, PC-2 (1.86) and PC-3 (1.01). The cluster analysis revealed the classification of 25 accessions into four diverse groups. Averages, standard deviations and variances for clusters based on morpho-physiological traits showed that the maximum average values for grain yield (742.2), biomass (1756.7), grains square meter (18</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;">373.7), and grains per spike (45.3) were higher in cluster C compared to other clusters. Cluster D exhibited the maximum thousand-kernel weight (TKW) (46.6).展开更多
基金funded by the National Natural Science Foundation of China(No.31171554)Major Projects for Development of New Genetically Modified Crops(No.2011ZX08002-003)+1 种基金Fund for the Doctoral Program of Higher Education of China(No.20123702110016)the Natural Science Foundation of Shandong(No.ZR2015CM036)
文摘Spike number per m^2(SN),kernel number per spike(KNPS) and thousand-kernel weight(TKW)are the three main components determining wheat(Triticum aestivum L.) yield.To evaluate the relationships among them a doubled haploid(DH) population consisting of 168 lines grown at three locations for three years was analyzed by unconditional and conditional QTL mapping.Thirty-three unconditional QTL and fifty-nine conditional QTL were detected.Among them,two QTL(QSN-DH-2B and QSN-DH-3A-1.1) improved SN,with no effect on KNPS.QKNPS-DH-2B-2.1 improved KNPS,with no effect on SN.QKNPS-DH-1A-1.1,QKNPS-DH-2D-1.1and QKNPS-DH-6A improved KNPS,with no effect on SN or TKW.QKNPS-DH-6B was associated with increased SN and TKW.In addition,QTKW-DH-4B,QTKW-DH-5B and QTKW-DH-7B increased TKW without decreasing KNPS.These results provide useful information for marker assisted selection(MAS) and improvement in wheat yield.
基金supported by the Chinese Ministry of Science and Technology(2010CB125900)Chinese Agricultural Research System(CARS-3-1-2)the CAAS innovation program
文摘Spike number per unit area, number of grains per spike, and thousand-kernel weight（TKW） are important yield components for wheat（Triticum aestivum L.）. TKW has the highest heritability among the three components. We validated 27 simple sequence repeat（SSR） loci associated with TKW in an F2：5breeding population grown in four environments. A cfd78265 bpmarker on chromosome 5DS showed the strongest association with TKW and had a significantly positive effect on TKW compared to allele cfd78259 bp, with mean increases of 5.17, 3.63, 4.11, and 5.16 g in the four environments. Markers cfd67 and cfd40 flanking cfd78 also showed significantly positive associations with TKW with increases of 5.11, 3.29, 4.31, and 4.50 g for cfd67205, and4.98, 3.49, 4.06, and 4.84 g for cfd40187 compared with cfd67203 and cfd40190in the four environments, respectively. A major quantitative trait locus for TKW spanning 2.94 c M on chromosome 5DS was detected by association mapping.Strong linkage disequilibrium（LD）（r2〉 0.2） was detected Resear among the three linked markers, which formed three haplotype blocks in the F2：5breeding population. Mean TKW differences between Hap B-I and Hap B-II were 5.80, 4.41, 4.02,and 5.06 g in the four environments, respectively. Moreover,significant LD was detected only between cfd78 and cfd67 and between cfd67 and cfd40 in a germplasm collection. This study provides a base for cloning genes related to TKW on chromosome 5DS.
文摘Investigation of genetic diversity of geographically distant wheat genotypes is </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">useful approach in wheat breeding providing efficient crop varieties. This article presents multivariate cluster and principal component analyses (PCA) of some yield traits of wheat, such as thousand-kernel weight (TKW), grain number, grain yield and plant height. Based on the results, an evaluation of economically valuable attributes by eigenvalues made it possible to determine the components that significantly contribute to the yield of common wheat genotypes. Twenty-five genotypes were grouped into four clusters on the basis of average linkage. The PCA showed four principal components (PC) with eigenvalues ></span><span style="font-family:""> </span><span style="font-family:Verdana;">1, explaining approximately 90.8% of the total variability. According to PC analysis, the variance in the eigenvalues was </span><span style="font-family:Verdana;">the </span><span style="font-family:Verdana;">greatest (4.33) for PC-1, PC-2 (1.86) and PC-3 (1.01). The cluster analysis revealed the classification of 25 accessions into four diverse groups. Averages, standard deviations and variances for clusters based on morpho-physiological traits showed that the maximum average values for grain yield (742.2), biomass (1756.7), grains square meter (18</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;">373.7), and grains per spike (45.3) were higher in cluster C compared to other clusters. Cluster D exhibited the maximum thousand-kernel weight (TKW) (46.6).
