QTL identification on two genetic systems for rapeseed glucosinolate and erucic acid contents over two seasons

It is now possible to use complete genetic linkage maps to locate major quantitative trait loci (QTLs) on chromosome regions. The current methods of QTL mapping (e.g., interval mapping, which uses a pair or two pairs of flanking markers at a time for mapping) can be subject to the effects of other linked QTLs on a chromosome because the genetic background is not controlled. As a result, mapping of QTLs can be biased, and the resolution of mapping is not very high. Ideally when we test a marker interval for a QTL, we would like our test statistic to be independent of the effects of possible QTLs at other regions of the chromosome so that the effects of QTLs can be separated. This test statistic can be constructed by using a pair of markers to locate the testing position and at the same time using other markers to control the genetic background through a multiple regression analysis. Theory is developed in this paper to explore the idea of a conditional test via multiple regression analysis. Various properties of multiple regression analysis in relation to QTL mapping are examined. Theoretical analysis indicates that it is advantageous to construct such a testing procedure for mapping QTLs and that such a test can potentially increase the precision of QTL mapping substantially.

Yield is the most important and complex trait for the genetic improvement of crops. Although much research into the genetic basis of yield and yield-associated traits has been reported, in each such experiment the genetic architecture and determinants of yield have remained ambiguous. One of the most intractable problems is the interaction between genes and the environment. We identified 85 quantitative trait loci (QTL) for seed yield along with 785 QTL for eight yield-associated traits, from 10 natural environments and two related populations of rapeseed. A trait-by-trait meta-analysis revealed 401 consensus QTL, of which 82.5% were clustered and integrated into 111 pleiotropic unique QTL by meta-analysis, 47 of which were relevant for seed yield. The complexity of the genetic architecture of yield was demonstrated, illustrating the pleiotropy, synthesis, variability, and plasticity of yield QTL. The idea of estimating indicator QTL for yield QTL and identifying potential candidate genes for yield provides an advance in methodology for complex traits.

We have developed a new DH mapping population for oilseed rape, named TNDH, using genetically and phenotypically diverse parental lines. We used the population in the construction of a high stringency genetic linkage map, consisting of 277 loci, for use in quantitative genetic analysis. A proportion of the markers had been used previously in the construction of linkage maps for Brassica species, thus permitting the alignment of maps. The map includes 68 newly developed Sequence Tagged Site (STS) markers targeted to the homologues of defined genes of A. thaliana. The use of these markers permits the alignment of our linkage map with the A. thaliana genome sequence. An additional 74 loci (31 newly developed STS markers and 43 loci defined by SSR and RFLP markers that had previously been used in published linkage maps) were added to the map. These markers increased the resolution of alignment of the newly constructed linkage map with existing Brassica linkage maps and the A. thaliana genome sequence. We conducted field trials with the TNDH population at two sites, and over 2 years, and identified reproducible QTL for seed oil content and erucic acid content. The results provide new insights into the genetic control of seed oil and erucic acid content in oilseed rape, and demonstrate the utility of the linkage map and population.