Fine mapping of loci involved with glucosinolate biosynthesis in oilseed mustard (Brassica juncea) using genomic information from allied species

Fine mapping of six seed glucosinolate QTL (J2Gsl1, J3Gsl2, J9Gsl3, J16Gsl4, J17Gsl5 and J3Gsl6) (Ramchiary et al. in Theor Appl Genet 116:77-85, 2007a) was undertaken by the candidate gene approach. Based on the DNA sequences from Arabidopsis and Brassica oleracea for the different genes involved in the aliphatic glucosinolate biosynthesis, candidate genes were amplified and sequenced from high to low glucosinolate Brassica juncea lines Varuna and Heera, respectively. Of the 20 paralogues identified, 17 paralogues belonging to six gene families were mapped to 12 of the 18 linkage groups of B. juncea genome. Co-mapping of candidate genes with glucosinolate QTL revealed that the candidate gene BjuA.GSL-ELONG.a mapped to the QTL interval of J2Gsl1, BjuA.GSL-ELONG.c, BjuA.GSL-ELONG.d and BjuA.Myb28.a mapped to the QTL interval of J3Gsl2, BjuA.GSL-ALK.a mapped to the QTL interval of J3Gsl6 and BjuB.Myb28.a mapped to the QTL interval of J17Gsl5. The QTL J9Gsl3 and J16Gsl4 did not correspond to any of the mapped candidate genes. The functionality and contribution of different candidate genes/QTL was assessed by allelic variation study using phenotypic data of 785 BC(4)DH lines. It was observed that BjuA.Myb28.a and J9Gsl3 contributed significantly to the base level glucosinolate production while J16Gsl4, probably GSL-PRO, BjuA.GSL-ELONG.a and BjuA.GSL-ELONG.c contributed to the C3, C4 and C5 elongation pathways, respectively. Three A genome QTL: J2Gsl1harbouring BjuA.GSL-ELONG.a, J3Gsl2 harbouring both BjuA.GSL-ELONG.c and BjuA.Myb28.a and J9Gsl3, possibly the 'Bronowski genes', were identified as most important loci for breeding low glucosinolate B. juncea. We observed two-step genetic control of seed glucosinolate in B. juncea mainly effected by these three A genome QTL. This study, therefore, provides clues to the genetic mechanism of 'Bronowski genes' controlling the glucosinolate trait and also provides efficient markers for marker-assisted introgression of low glucosinolate trait in B. juncea.

QTL analysis reveals context-dependent loci for seed glucosinolate trait in the oilseed Brassica juncea: importance of recurrent selection backcross scheme for the identification of 'true' QTL

Seed glucosinolate content in Brassica juncea is a complex quantitative trait. A recurrent selection backcross (RSB) method with a doubled haploid (DH) generation interspersing backcross generations was used for the introgression of low glucosinolate alleles from an east European gene pool B. juncea line, Heera into an Indian gene pool variety, Varuna. Phenotypic comparisons among the DH populations derived from early to advanced backcrosses revealed a shift in the mean values for various glucosinolates with the advancement of backcrossing, indicating a change in the selective values of the alleles with change in the genetic background due to the existence of epistasis and context dependencies. QTL mapping for various seed glucosinolates from early (F(1)DH) and advanced generation (BC(4)DH) populations confirmed the presence of epistasis and context dependency. The common QTL detected in both F(1)DH and BC(4)DH changed their R (2) values from the former to the later generation. Some of the QTL detected in the F(1)DH became irrelevant in the BC(4)DH population. Further, new QTL were detected in the BC(4)DH population for various glucosinolates. A validation study on a population of low glucosinolate DH lines derived from all the backcross generations of the RSB breeding programme revealed that the QTL detected in BC(4)DH were the 'true' QTL. Using glucosinolate as an example, the study provides strong evidence for the importance of the RSB method for the identification of the 'true' QTL which would be significant for marker assisted introgression of a complex quantitative trait whose expression is influenced by epistatic interactions.

Mapping of yield influencing QTL in Brassica juncea: implications for breeding of a major oilseed crop of dryland areas

Quantitative trait loci (QTL) analysis of yield influencing traits was carried out in Brassica juncea (AABB) using a doubled haploid (DH) mapping population of 123 lines derived from a cross between Varuna (a line representing the Indian gene pool) and Heera (representing the east European gene pool) to identify potentially useful alleles from both the parents. The existing AFLP based map of B. juncea was further saturated with RFLP and SSR markers which led to the identification of the linkage groups belonging to the A (B. rapa) and B (B. nigra) genome components of B. juncea. For QTL dissection, the DH lines were evaluated at three different environments and phenotyped for 12 quantitative traits. A total of 65 QTL spread over 13 linkage groups (LG) were identified from the three environments. QTL analysis showed that the A genome has contributed more than the B genome to productivity (68% of the total QTL detected) suggesting a more prominent role of the A genome towards domestication of this crop. The east European line, Heera, carried favorable alleles for 42% of the detected QTL and the remaining 58% were in the Indian gene pool line, Varuna. We observed clustering of major QTL in a few linkage groups, particularly in J7 and J10 of the A genome, with QTL of different traits having agronomically antagonistic allelic effects co-mapping to the same genetic interval. QTL analysis also identified some well-separated QTL which could be readily transferred between the two pools. Based on the QTL analysis, we propose that improvement in yield could be achieved more readily by heterosis breeding rather than by pure line breeding.