Molecular mapping of qualitative and quantitative loci for resistance to Leptosphaeria maculans causing blackleg disease in canola (Brassica napus L.).
ABSTRACT Blackleg, caused by Leptosphaeria maculans, is one of the most important diseases of oilseed and vegetable crucifiers worldwide. The present study describes (1) the construction of a genetic linkage map, comprising 255 markers, based upon simple sequence repeats (SSR), sequence-related amplified polymorphism, sequence tagged sites, and EST-SSRs and (2) the localization of qualitative (race-specific) and quantitative (race non-specific) trait loci controlling blackleg resistance in a doubled-haploid population derived from the Australian canola (Brassica napus L.) cultivars Skipton and Ag-Spectrum using the whole-genome average interval mapping approach. Marker regression analyses revealed that at least 14 genomic regions with LOD ≥ 2.0 were associated with qualitative and quantitative blackleg resistance, explaining 4.6-88.9 % of genotypic variation. A major qualitative locus, designated RlmSkipton (Rlm4), was mapped on chromosome A7, within 0.8 cM of the SSR marker Xbrms075. Alignment of the molecular markers underlying this QTL region with the genome sequence data of B. rapa L. suggests that RlmSkipton is located approximately 80 kb from the Xbrms075 locus. Molecular marker-RlmSkipton linkage was further validated in an F(2) population from Skipton/Ag-Spectrum. Our results show that SSR markers linked to consistent genomic regions are suitable for enrichment of favourable alleles for blackleg resistance in canola breeding programs.
Article: A consensus map of rapeseed (Brassica napus L.) based on diversity array technology markers: applications in genetic dissection of qualitative and quantitative traits.[show abstract] [hide abstract]
ABSTRACT: BACKGROUND: Dense consensus genetic maps based on high-throughput genotyping platforms are valuable for making genetic gains in Brassica napus through quantitative trait locus identification, efficient predictive molecular breeding, and map-based gene cloning. This report describes the construction of the first B. napus consensus map consisting of a 1,359 anchored array based genotyping platform; Diversity Arrays Technology (DArT), and non-DArT markers from six populations originating from Australia, Canada, China and Europe. We aligned the B. napus DArT sequences with genomic scaffolds from Brassica rapa and Brassica oleracea, and identified DArT loci that showed linkage with qualitative and quantitative loci associated with agronomic traits. RESULTS: The integrated consensus map covered a total of 1,987.2 cM and represented all 19 chromosomes of the A and C genomes, with an average map density of one marker per 1.46 cM, corresponding to approximately 0.88 Mbp of the haploid genome. Through in silico physical mapping 2,457 out of 3,072 (80%) DArT clones were assigned to the genomic scaffolds of B. rapa (A genome) and B. oleracea (C genome). These were used to orientate the genetic consensus map with the chromosomal sequences. The DArT markers showed linkage with previously identified non-DArT markers associated with qualitative and quantitative trait loci for plant architecture, phenological components, seed and oil quality attributes, boron efficiency, sucrose transport, male sterility, and race-specific resistance to blackleg disease. CONCLUSIONS: The DArT markers provide increased marker density across the B. napus genome. Most of the DArT markers represented on the current array were sequenced and aligned with the B. rapa and B. oleracea genomes, providing insight into the Brassica A and C genomes. This information can be utilised for comparative genomics and genomic evolution studies. In summary, this consensus map can be used to (i) integrate new generation markers such as SNP arrays and next generation sequencing data; (ii) anchor physical maps to facilitate assembly of B. napus genome sequences; and (iii) identify candidate genes underlying natural genetic variation for traits of interest.BMC Genomics 04/2013; 14(1):277. · 4.07 Impact Factor