| Fusarium Head Blight(FHB),caused mainly by Fusarium graminearum Schwabe, is a destructive disease of wheat(Triticum aestivum)worldwide. It occurs widely in warm, humid and sub-humid areas.FHB is an important factor which affected yield and quality in wheat.In China,One quarter of the wheat growing area(about6.7million hectares)is being jeopardized by wheat FHB.Due to global climate warming and farming systems changing, FHB is expanding to the northern areas, thus affecting the food security and food safety FHB is controlled by multiple genes and its genetic mechanism is complicated. The study of these quantitative trait loci can not only understand the genetic development, but also can use the locations to clone genes and marker-assisted selection.The association analysis based on linkage disequilibrium (LD) to identification the relationship between the trait and genetic markers or candidate genes.It became one of the effective means to study plant genes(QTL). Compared with the linkage analysis, the advantages of the association analysis are less time spent, breadth,and more accuracy. At present, through the linkage mapping method we had obtained a large number of QTLs, which provide a basis for in-depth analysis of FHB resistance mechanism and Breeding. But we must recognize that, due to its limitations, it is difficult to use into the marker-assisted breeding and need to improve the efficiency by fine mapping. Linkage mapping can make an initial control of the location of the target trait,association mapping can quickly and more accurately locate the target gene. Association analysis and QTL mapping are complementary,The integration of the two methods will accelerate the identification and isolation and cloning of quantitative trait lociIn this study, we extensively collect423wheat materials for research, including the existing bred varieties and local varieties as well as part of the backbone parent materials.We use122SSR markers covering the genome-wide to analysis the genetic diversity,and build groups for the associated anaysis. We combinate the phenotypic identification datas by multi-year and multi-area with the genotype data to screen markers which are relate with FHB resistance QTL.These will provide the necessary information to fine mapping relation genes,assist anti-breeding.The results of this study are mainly as follows:1.We use103genome microsatellite markers to do the whole genome scan and anaylsis for423wheat varieties.A total of453allelic variations were detected with an average allele number of4.4.The average PIC (polymorphism information content)and gene diversity values were0.62and0.57,respectively,The results showed that the genetic diversity was relatively high among the assecions used in this study.2.we detected the rate of diseased spikelets and disease index in the assecions,the coefficient of variation of which were relatively high.The ANOVA between3locations in2years showed the differences were significance between wheat varieties and locations,but not significance between the repeats.Traits showed relatively stable.The correlation analysis found that there had a significant positive correlation between3locations in2years,and the trend of resistance and susceptibility was relatively between warieties.3.By NJ cluster and population structure(Bayesian clustering)analysis, the423assecions were clustered into3and4main groups.Population structure analysis showed83%assecions had a single ancestor relatively,while the other assecions were from mixed ancestors.NJ cluster showed the second of the3groups could be clustered into2groups.The population structure analysis and cluster analysis were consistency in some extent.4.By using122markers on wheat genome mapping, we found whether it is a total-linear or non-linear SSR loci combinations exists LD in some degree.the LD between linear SSR loci is higher than the nonlinear SSR loci, and to determine the baseline LD decay distance r2=0.014on the genome-wide. LD in genetic distance<50cM was common.5.Marker-trait association analysis was calculated by mixed linear model in software TASSEL2.1.Nearby the QTL located by previous,we detected the markers which linked closely with the resistance of the FHB and could explained higher phenotypic waration,e.g. gwm484is better than gwm261,barc238and barc233on2D;wmc264is better than gwm5on3A; gwm192(3.7%) is better than wmc238,gwm495and barc20on4B, gwm415(6.6%) is better than barc117and barc186on5A, gdm113(2.9%) and gwm193(1.6%) is better than gwm518on6B.6. According to Breseghello proposed"null alleles" method The Phenotypic allele effect was estimated through comparison between the average Phenotypic value over accessions with the specific allele and that of accessions with "null allele" and a set of elite alleles, loci were screened out, ineluding the barc133-105(0.342) for largest Positive for FHB resistance and the barc133-105(0.342) for largest negative for FHB resistance. |
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