RNA-seq-based SNP discovery and functional characterization reveal genetic variation and evolutionary insights in Cinnamomum species

Abstract

Genetic differences are essential for the adaptability, resilience, and evolutionary success of plant species. Cinnamomum, a genus of commercial and therapeutic significance, remains little studied at the genomic level. In this study, we conducted a comprehensive RNA-Seq-based single nucleotide polymorphism (SNP) analysis on six transcriptome samples from C. camphora and C. verum, aligned with the C. kanehirae reference genome. We identified a total of 184,532 high-confidence SNPs, comprising 410,247 missense SNPs and 397,053 synonymous SNPs, yielding a missense-to-synonymous ratio of 1.03. Chromosome-wide analysis revealed that chromosome QPKB01000001.1 contained the highest SNP count (12,458 SNPs), whereas QPKB01000005.1 exhibited the strongest population differentiation, with a mean FST value of 0.342. A strong positive correlation (r = 0.79, p < 0.001) was observed between SNP density and chromosomal length. Functional enrichment analysis demonstrated that SNP-associated genes were significantly enriched (FDR < 0.05) in metabolic processes, cellular architecture, and regulatory pathways. KEGG annotation linked SNPs to significant metabolic pathways, including purine metabolism, phenylpropanoid biosynthesis (-log10(p) > 5), and lignin biosynthesis. Analysis of linkage disequilibrium (LD) decay showed that the mean r² value dropped below 0.2 within approximately 50 kilobases, indicating high recombination rates and low genome-wide LD. The allele frequency spectrum revealed a predominance of low-frequency variants (MAF < 0.1), constituting over 60% of all SNPs, which suggests the influence of genetic drift and recent population expansion. Notably, over 20 genes exhibited an accumulation of more than 50 missense SNPs, highlighting potential targets of evolutionary selection. These results clarify the molecular and evolutionary dynamics of Cinnamomum species and provide a robust basis for additional research into plant adaptation, genetic conservation, and trait-based selection in non-model plant genomes. © 2025 The Author(s)