| QTL analysis for yield related traits and grain size traits using a high density genetic mapprovid a convenient way to resolve the genetic basis of wheat yield formation. Tainong18(TN18) was a winter wheat variety bred by us with high yield, good quality, dwarf andexcellent lodging resistance. In order to resolve the genetic basis of high yield of TN18, a RIL(Recombinant Inbred Line) population was developed by single-seed descent (SSD) from thecross between TN18and Linmai6(LM6), and was used for the construction of high densitygenetic map and the location of QTLs (quantitative trait loci). The high throughput markers ofDArTs and SNPs were engaged in construction of genetic map. The RILs were planted inthree years and the yield traits and grain size traits were investigate. Important QTLs for thesetraits are useful for the further research of gene cloning and breeding programs. The mianresults are as follows.A total of more than156thousands of SSR, DArT and SNP markers were used for markeranalysis. A genetic map with10739loci was constructed covering all of the21wheatchromosomes. In which,5399loci were unique loci, including3788DArT,1506SNP and105SSR loci; and the other5340loci showed co-segregation with other markers. The mapspanned a total length of3394.47cM across43linkage groups, with an average chromosomelength of161.64cM amd the average distance of0.63cM between markers. The largestchromosome was3B (308.98cM), with a marker density of0.57cM/marker. Chromsome1Bgave the highest density of0.27cM/marker.The results of ANOVA showed that the variance for either genotype or environment effectsfor all the14investigated traits were significant at the p≤0.001level, except for that theenvironment effect of TSSS wasn’t significant and the genotype effect of GY was significantat the p≤0.05level. The two parents exhibited distinct differences in most of the investigatedtraits and transgressive segregations were observed for all the investigated traits. Theheritability (hB2) for the investigated traits ranged from12.95(GY) to67.79%(GLW).A total of416additive QTLs (662QTLs for trait-environment combines) were detected on the21chromosomes for all of the investigated traits in the three environments and their AV.An individual QTL in different environments explained4.38~37.70%of the phenotypicvariations. The highest LOD value for a single QTL in the different environments was20.78.A number of103QTLs for yield and its component factors traits (GY, SN, GN and TGW),102QTLs for spike traits (BSSS, TSSS, TSS and SL) and211QTLs for grain size traits (GL,GW, GH, GLW, FFD and GV) were detected. A single QTL in different environmentsexplained4.76~23.05%,4.63~37.70%and4.38~22.24%of the phenotypic variations foryield traits, for spike traits and grain size traits, respectively.A number of76relatively high-frequency (RHF) including233single environmentQTLs (35.2%) in more than two environments and/or in AV were located. These RHF-QTLsdistributed on17chromosomes except for3A,3D,4D and5D, and were consistant of10,21and45QTLs of yield and its component factors, spike and grain size traits. Eighteen of theseRHF-QTLs (QSl-5A.2; QSl-6A.3; QSl-6B.1; QTss-5A.1; QBsss-6A.2; QTgw-1B.1; QTgw-1B.4;QTgw-6A.3; QGl-2D.1; QGl-4A.1; QGl-5B.1; QGl-5B.3; QGw-1B.1; QGlw-1B.1; QGlw-2D.4;QGlw-5B.1; QGlw-7A.3; QGlw-7B.2; QGv-5B.1; QGv-6B.1; QGv-6D.1and QGv-7B.1) canbe detected in all the three environments and AV. And each four QTLs for GH (QGh-1B.1;QGh-6A.2; QGh-7B.1and QGh-7B.2) and GV (QGv-5B.1; QGv-6B.1; QGv-6D.1andQGv-7B.1) were detected in all the two investigated environments and AV.A number of56QTL clusters (C1-C56) with more than three traits were mapped on17chromosomes except for1A,3A,3D and4D, which were related to all of the investigatedtraits and involved168QTLs (168/416×100%=40.38%) and55RHF-QTLs (55/76×100%=72.37%). These QTL clusters were involved into five types according to the traits releated:Type I: related to yield and its component factors, spike and grain size traits, including25QTL clusters. Of these,12QTL clusters (C1; C24; C26; C29; C30; C31; C36; C37; C38; C39;C43and C44) involved RHF-QTL. Type II: related to yield and its component factors,including3QTL clusters. Of these, clusters C5involved RHF-QTL. Type Ⅲ: related toyieldand its component factors and grain size traits, including11QTL clusters. Of these,6QTLclusters (C3; C20; C40; C42; C54and C56) involved RHF-QTL. Type Ⅳ: related tospikeand grain size traits, including12QTL clusters. Of these,5QTL clusters (C6; C10; C16; C32and C51.) involved RHF-QTL. Type Ⅳ: related tograin size traits, including5QTL clusters.Of these,3QTL clusters (C25; C41and C53.) involved RHF-QTL. Analysis from thecorrelation between traits, additive effects of QTLs and conditional QTL analysis, weconsider three of these QTLclusters were of very importance.Three important QTL cluster (C1, C38and C54) were obtained according to the relation of QTL clusters, the additive effects between QTLs and conditional QTLs. We infer thatincrease of grain yield was caused by the increase TGW, while GW and GH promoted theraise of TGW in the cluster C1interval on chromesome1B. In the C38interval onchromesome6A, the increase of GN was mainly caused by reduce of BSSS, while SLprovided a certain effect on it. For C54on chromesome7B, GL, GW and GH provided anincrease effect together on a high TGW. We also conjectured that GW and GH provided anincrease effect on the high TGW, and promoted a high grain yield finally.The results of conditional QTL analysis about spike traits on GN and grain size traits onTGW show the following conclusion: factors impacted on GN were in proper order ofBSSS> TSS> SL or TSSS; while on TGW, the effects of GW and GH were larger than GL... |
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