BACKGROUND: The decision for a bud to grow into a branch is a key regulatory process affecting plant architecture. In order to study molecular processes regulating axillary bud outgrowth in the model plant garden pea (Pisum sativum), we sequenced the axillary bud transcriptome and performed de novo transcriptome assembly. RESULTS: We assembled a pea axillary bud transcriptome into 81,774 transcripts comprised of 194,067 isoforms. This new pea transcriptome resource is both comprehensive and representative, as shown by comparison to other available pea sequence resources. Over half of the transcriptome could be annotated based on sequence homology to Arabidopsis thaliana proteins, while almost one quarter of the isoforms were identified as putative long non-coding RNAs (lncRNAs). This transcriptome will be useful in studies of pea buds because it includes genes expressed specifically in buds which are not represented in other transcriptome studies. We also investigated the impact of a short time collection series on gene expression. Differential gene expression analysis identified 142 transcripts changing within the short 170 min time frame that the buds were harvested within. Thirty-three of these transcripts are implicated in diurnal fluctuations in other flowering plants, while the remaining transcripts include 31 putative lncRNA. Further investigation of the differentially expressed transcripts found an enrichment of genes involved in post-transcriptional regulation, including RNA processing and modification, as well as genes involved in fatty acid biosynthesis and oxidative phosphorylation. CONCLUSIONS: We have sequenced and assembled a high quality pea bud transcriptome containing both coding and non-coding RNA transcripts that will be useful for further studies into axillary bud outgrowth. Over the short sample collection time frame of just 170 min, we identified differentially expressed coding and non-coding RNA, some of which are implicated in diurnal regulation, highlighting the utility of our transcriptome resource in identifying gene expression changes and informing future experimental designs.