| We have developed a new DH mapping population for oilseed rape, named TNDH,using genetically and phenotypically diverse parental lines. A DH population of Brassicanapus was evaluated in two locations in China for 2 years. 13 traits involving plantdevelopmental trait, seed yield-related and seed quality-related characteristics had beeninvestigated. We used the population in the construction of a genetic linkage map, Aproportion of the markers had been used previously in the construction of linkage mapsfor Brassica species, thus permitting the alignment of maps. The map includes developedSequence Tagged Site (STS), SSR ,RFLP AFLP and Ms-AFLP markers. Three geneticmaps with 277,352 and 532 markers had been constructed by Joinmap3.0. The geneticmap with 277 and 352 markers is a high stringency map. The stringency of 532 markersgenetic map is less than these two mps. The QTL for seed oil content and erucic contenthad been identified by 277 and 352 markers genetic map. Then the QTL analysis,interaction of two loci and conditional QTL analysis for 13 traits had been performed with352 and 532 markers genetic map.(1)We identified four QTL for erucic acid content of seed oil. Two of these, mappingto linkage groups N8 and N13, can be considered "major", accounting for about 45% and30% of the variation in the population, respectively. The QTL we identified on N1,N8and N13 for erucic acid content and seed oil content overlap the portion of each linkagegroup that can be aligned with A. thaliana chromosome 4. This alignment is consistentwith a Brassica FAE1 homologue as a candidate gene for the control of erucic acidbiosynthesis, as orthologous genes are likely to be present in the B. napus genome in thevicinity of each of these three QTL.(2)We identified seven QTL for oil content of seeds. All of these were relatively minor,although accounting for ca. 55% of the variation for the trait in total. The QTLmapping to linkage groups N1, N8 and N13 coincided with QTL for erucic acid content.The coincidence of QTL for oil content and erucic acid content has been noted inprevious studies. However, the control of seed oil content is clearly more complex thanbeing dependent solely upon erucic acid content, as we have identified four reproducibleQTL for oil content that do not coincide with QTL for erucic acid.(3) We had used two different models for the QTL mapping and analysis with 352 markers genetic map. One model of QTL analysis was carried by WinQTLCart2.0 inseparate environment. Another model of QTL analysis is mixed linear model approaches,which combined all the environments together to calculate the value of QE effect (Wanget al. 1999). For the first model, only 12 QTLs of the total 441 QTL (2.7%) for 13 traitswere detected in all environments. Seventy-seven and Sixty-six of QTLs were repeatedlydetected in both locations and both years. 441 QTLs at LOD value 2.0 were detected fromthe four environments concerning the 13 traits. Half of QTLs with lower value of LODand less variance contribution could be only penetrated under particular environments.Compared with years, the geographic locations had slightly stronger effect on the QTLpenetrance in general especially for the individual traits, such as seed mature time, podnumber and seed yield. The QTLs being repeatedly detected across the environment weremore with the seed-quality-related traits and less with the seed-yield-related traits exceptseed weight. 12 QTLs with highest LOD value were constantly detected across the fourenvironments. This indicated that individual QTL seem to be sensitive to the environment.With the second model, to estimate whether the QTLs repeatedly detected in fourenvironments had QE effect, 76 QTLs screened out with QTLMapper for the 13 traitswere analysed. It was fond that most of the repeatedly detected also had significantinteraction effects with environment. Only two out of five QTLs for ERU had significantinteraction effects with environment. But all the QTLs for ST, HP, GLU, PNM, PN andSY interact with environment. The average variances of QTLs for all the traits were 0.11and the average variances of QTL interaction with environment for all the traits were 0.2.(4)A total of 507 interaction loci pairs (ILPs) were detected. However, 97% of the ILPswere environmental specific. Comparing with the QTL effect, the epistasis was muchmore sensitive to the environmental changes. Only 2 ILPs with the highest LOD valueswere significantly contributed to the traits of seed quality, i.e. the oil content, erucic acidcontent across all of the environments. ILPs could be classified into three types based onwhether the QTL for the target trait was involved or not, i.e., interaction pairs between thetarget QTLs (I-QtQt), between target QTL and non-target QTL (I-QtQn), and betweennon-QTL loci (I-QnQn). The total number of I-QtQn and I-QnQn, which looks the same,was much higher than that of I-QtQt. For the three types of ILPs, 52, 229, and 216interaction loci pairs for 13 traits were detected respectively. And the percentage offrequency for the detected epistasis in whole genome is 0.57%, 0.11%, 0.015%. It should beconcerned that all ILPs detected in both environment were I-QtQt and I-QtQn. Weconcluded that the epistasis involved with the Target-QTL is dominant in these three types. (5)Furthermore, each QTL controlling particular trait was programmed conditioned bythe other 12 traits in turn. Consequently, one third of QTLs disappeared and about thesimilar amount of QTLs newly appeared in average after condition. In other words, mostof QTLs that we could detect were actually because of the influence from QTLscontrolling another trait and vice versa. Only 97 QTLs (22%) were independent to QTLscontrolling other 12 traits. It was noticed that all of the environmental constant QTLswere the trait-independent QTLs, and 85% of the trait-independent QTLs were stillenvironmental-depended.(6)Overall, no matter how the environment and the other loci changes, the higher theLOD value, the better the penetrability of the QTL. Such a complexity of QTLpenetration suggested that the gene expression was dependent on the allele itself andregulated by the interactive genes and by the changed environment. To further isolate theQTLs and then analysis the regulation sequence of the environment-dependent QTLs andthe trait-dependent QTLs may provide a powerful insight for plant breeders.
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