Abstract: Toona fargesii A. Chev., a versatile tree in the Toona genus of the Meliaceae family, is renowned for its exquisite timber and medicinal properties, offering promising benefits. Due to natural regeneration obstacles and long-term excessive exploitation, it has been threatened in China. Intriguingly, root sprouting, which may diminish the genetic diversity and hinder population development, dominates the reproductive pattern of T. fargesii in the wild. However, the lack of complete genome information has hampered basic studies on the regeneration, classification, evolution and conservation of this species. Here, we report the genome of T. fargesii, which was sequenced using the PacBio platform and assembled into a high-quality genome with a total size of 535.24 Mb. Of this, 97.93% of the assembled contigs were anchored onto 28 pseudochromosomes, achieving a chromosome-level genome. The long terminal repeat assembly index score was 21.34, and the consensus quality value was 39.90%, indicating the accuracy and completeness of the genome. Comparative genome analysis suggested that a recent whole genome duplication event occurred between 22.1 and 50.1 Mya in the Toona genus, with the divergence time between T. fargesii and its relative T. sinensis estimated at approximately ~16.7 Mya. Additionally, 13 TfARR genes, which play integral roles in root sprouting by mediating cytokinin signaling, underwent rapid gene expansion and showed significant enrichment in the plant hormone signal transduction pathway. Furthermore, transcriptomic analysis demonstrated that differentially expressed genes between root sprouts and nonroot sprouts were significantly enriched in the zeatin biosynthesis pathway, indicating that cytokinin regulation is involved in root sprouting development. Collectively, the findings provide valuable genomic resources for the Toona genus and genetic insights into the mechanisms of root sprouting in T. fargesii.

Key words: hormone regulation, long read sequencing, root sprouting, Toona fargesii, transcriptome analysis.