Association genetics can quickly and efficiently delineate regions of the genome that control traits and provide markers to accelerate breeding by marker-assisted selection. But most crops are polyploid, making it difficult to identify the required markers and to assemble a genome sequence to order those markers. To circumvent this difficulty, we developed associative transcriptomics, which uses transcriptome sequencing to identify and score molecular markers representing variation in both gene sequences and gene expression, and correlate this with trait variation. Applying the method in the recently formed tetraploid crop Brassica napus, we identified genomic deletions that underlie two quantitative trait loci for glucosinolate content of seeds. The deleted regions contained orthologs of the transcription factor HAG1 (At5g61420), which controls aliphatic glucosinolate biosynthesis in Arabidopsis thaliana. This approach facilitates the application of association genetics in a broad range of crops, even those with complex genomes.