Identification of QTL markers contributing to plant growth, oil yield and fatty acid composition in the oilseed crop Jatropha curcas L.
Maneno muhimu
Kikemikali
BACKGROUND
Economical cultivation of the oilseed crop Jatropha curcas is currently hampered in part due to the non-availability of purpose-bred cultivars. Although genetic maps and genome sequence data exist for this crop, marker-assisted breeding has not yet been implemented due to a lack of available marker-trait association studies. To identify the location of beneficial alleles for use in plant breeding, we performed quantitative trait loci (QTL) analysis for a number of agronomic traits in two biparental mapping populations.
RESULTS
The mapping populations segregated for a range of traits contributing to oil yield, including plant height, stem diameter, number of branches, total seeds per plant, 100-seed weight, seed oil content and fatty acid composition. QTL were detected for each of these traits and often over multiple years, with some variation in the phenotypic variance explained between different years. In one of the mapping populations where we recorded vegetative traits, we also observed co-localization of QTL for stem diameter and plant height, which were both overdominant, suggesting a possible locus conferring a pleotropic heterosis effect. By using a candidate gene approach and integrating physical mapping data from a recent high-quality release of the Jatropha genome, we were also able to position a large number of genes involved in the biosynthesis of storage lipids onto the genetic map. By comparing the position of these genes with QTL, we were able to detect a number of genes potentially underlying seed traits, including phosphatidate phosphatase genes.
CONCLUSIONS
The QTL we have identified will serve as a useful starting point in the creation of new varieties of J. curcas with improved agronomic performance for seed and oil productivity. Our ability to physically map a significant proportion of the Jatropha genome sequence onto our genetic map could also prove useful in identifying the genes underlying particular traits, allowing more controlled and precise introgression of desirable alleles and permitting the pyramiding or stacking of multiple QTL.
