Genome-wide identification and expression profiling of the CoVQ gene family in Camellia Oleifera
Zhicheng Fan1, Ziyi Liu1, Xinyi Wan2
1School of Life Science, Nanchang University, Nanchang, Jiangxi, 330031, China.
Background:
Valine-glutamine (VQ) proteins are key regulators of plant growth, development, and stress responses. Camellia oleifera Abel, a major woody oil crop in southern China, is frequently challenged by abiotic stresses (including low phosphorus, drought, chilling, and potassium deficiency) that severely limit its productivity. Understanding the evolutionary and functional diversification of the VQ gene family in this species could offer valuable insights for molecular breeding.
Results:
Using the diploid C. oleifera reference genome (CON v2.0, 2.95 Gb), we identified 39 CoVQ genes through HMMER-based screening and domain validation. Phylogenetic analysis grouped them into eight subclades, with family expansion primarily driven by 12 segmental duplication events (66.7% of duplicated pairs), all under strong purifying selection (Ka/Ks < 1; mean = 0.27). Notably, 84.6% of CoVQ genes are intronless, a feature potentially linked to LTR retrotransposon-mediated chromosomal rearrangements (LTR content: 49.76%). Tissue-specific expression revealed high expression of CoVQ1/6/13 in sepals (5 ~ 120 FPKM), while CoVQ16/22/31 were preferentially expressed in stamens. Under abiotic stresses, CoVQ1 was upregulated 278.2-fold after 12 days of drought, CoVQ18 showed rapid induction (7.96-fold) during early potassium deficiency, and CoVQ27/28 exhibited coordinated responses across low phosphorus, drought, and chilling. Promoter analysis revealed that 94.9% of CoVQ genes contain stress-responsive (e.g., ARE, DRE) and hormone-related (e.g., ABRE, ERE) cis-elements. Notably, CoVQ27/28 harbor nine stress-related elements (nearly twice the family average of 4.3), suggesting their potential as multifunctional regulatory hubs.
Conclusions:
This study presents a systematic analysis of the VQ gene family in C. oleifera, integrating evolutionary, structural, and expression data to prioritize promising candidates for future functional validation and potential use in molecular breeding for improved stress resilience.
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