Genome-wide association studies are a powerful approach for identifying genes related to complex traits in organisms, but are limited by the requirement for a reference genome sequence of the species under study. To circumvent this problem, we propose a transcriptome-referenced association study (TRAS) that utilizes a transcriptome generated by single-molecule long-read sequencing as a reference sequence to score population variation at both transcript sequence and expression levels. Candidate transcripts are identified when both scores are associated with a trait and their potential interactions are ascertained by expression quantitative trait loci analysis. Applying this method to characterize garlic clove shape traits in 102 landraces, we identified 22 candidate transcripts, most of which showed extensive interactions. Eight transcripts were long non-coding RNAs (lncRNAs), and the others were proteins involved mainly in carbohydrate metabolism, protein degradation, etc. TRAS, as an efficient tool for association study independent of a reference genome, extends the applicability of association studies to a broad range of species.