Interaction between polymorphisms in aspirin metabolic pathways, regular aspirin use and colorectal cancer risk: A case-control study in unselected white European populations

Regular aspirin use is associated with reduced risk of colorectal cancer (CRC). Variation in aspirin’s chemoprevention efficacy has been attributed to the presence of single nucleotide polymorphisms (SNPs). We conducted a meta-analysis using two large population-based case-control datasets, the UK-Leeds Colorectal Cancer Study Group and the NIH-Colon Cancer Family Registry, having a combined total of 3325 cases and 2262 controls. The aim was to assess 42 candidate SNPs in 15 genes whose association with colorectal cancer risk was putatively modified by aspirin use, in the literature. Log odds ratios (ORs) and standard errors were estimated for each dataset separately using logistic regression adjusting for age, sex and study site, and dataset-specific results were combined using random effects meta-analysis. Meta-analysis showed association between SNPs rs6983267, rs11694911 and rs2302615 with CRC risk reduction (All P<0.05). Association for SNP rs6983267 in the CCAT2 gene only was noteworthy after multiple test correction (P = 0.001). Site-specific analysis showed association between SNPs rs1799853 and rs2302615 with reduced colon cancer risk only (P = 0.01 and P = 0.004, respectively), however neither reached significance threshold following multiple test correction. Meta-analysis of SNPs rs2070959 and rs1105879 in UGT1A6 gene showed interaction between aspirin use and CRC risk (Pinteraction = 0.01 and 0.02, respectively); stratification by aspirin use showed an association for decreased CRC risk for aspirin users having a wild-type genotype (rs2070959 OR = 0.77, 95% CI = 0.68–0.86; rs1105879 OR = 0.77 95% CI = 0.69–0.86) compared to variant allele cariers. The direction of the interaction however is in contrast to that published in studies on colorectal adenomas. Both SNPs showed potential site-specific interaction with aspirin use and colon cancer risk only (Pinteraction = 0.006 and 0.008, respectively), with the direction of association similar to that observed for CRC. Additionally, they showed interaction between any non-steroidal anti-inflammatory drugs (including aspirin) use and CRC risk (Pinteraction = 0.01 for both). All gene x environment (GxE) interactions however were not significant after multiple test correction. Candidate gene investigation indicated no evidence of GxE interaction between genetic variants in genes involved in aspirin pathways, regular aspirin use and colorectal cancer risk

Genetic and physical mapping of flowering time loci in canola (Brassica napus L.)

We identified quantitative trait loci (QTL) underlying variation for flowering time in a doubled haploid (DH) population of vernalisation-responsive canola (Brassica napus L.) cultivars Skipton and Ag-Spectrum and aligned them with physical map positions of predicted flowering genes from the Brassica rapa genome. Significant genetic variation in flowering time and response to vernalisation were observed among the DH lines from Skipton/Ag-Spectrum. A molecular linkage map was generated comprising 674 simple sequence repeat, sequence-related amplified polymorphism, sequence characterised amplified region, Diversity Array Technology, and candidate gene based markers loci. QTL analysis indicated that flowering time is a complex trait and is controlled by at least 20 loci, localised on ten different chromosomes. These loci each accounted for between 2.4 and 28.6 % of the total genotypic variation for first flowering and response to vernalisation. However, identification of consistent QTL was found to be dependant upon growing environments. We compared the locations of QTL with the physical positions of predicted flowering time genes located on the sequenced genome of B. rapa. Some QTL associated with flowering time on A02, A03, A07, and C06 may represent homologues of known flowering time genes in Arabidopsis; VERNALISATION INSENSITIVE 3, APETALA1, CAULIFLOWER, FLOWERING LOCUS C, FLOWERING LOCUS T, CURLY LEAF, SHORT VEGETATIVE PHASE, GA3 OXIDASE, and LEAFY. Identification of the chromosomal location and effect of the genes influencing flowering time may hasten the development of canola varieties having an optimal time for flowering in target environments such as for low rainfall areas, via marker-assisted selection

Molecular mapping of qualitative and quantitative loci for resistance to Leptosphaeria maculans causing blackleg disease in canola (Brassica napus L.)

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 F2 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.Rosy Raman, Belinda Taylor, Steve Marcroft, Jiri Stiller, Paul Eckermann, Neil Coombes, Ata Rehman, Kurt Lindbeck, David Luckett, Neil Wratten, Jacqueline Batley, David Edwards, Xiaowu Wang, Harsh Rama