The Complete Mitochondrial Genome of Conopomorpha sinensis (Lepidoptera: Gracillariidae) Sample from Taiwan

The litchi fruit borer, Conopomorpha sinensis (Lepidoptera: Gracillariidae), is a devastating pest affecting litchi and longan production across Asia. Although a reference mitochondrial genome (mitogenome) has been published, its utility is limited by the lack of precise geographical data and raw sequencing data.

In this study, we sequenced and characterized the complete mitogenome of C. sinensis collected from Taiwan using a hybrid assembly of Illumina and Oxford Nanopore technologies.

The assembled mitogenome is 17,301 bp in length with a mean sequencing depth of 19,155-fold, comprising 13 protein-coding genes (PCGs), 22 transfer RNA genes, two ribosomal RNA genes, and an AT-rich control region. Notably, we identified a rare tRNA gene rearrangement (trnR-trnA-trnN-trnS1-trnE-trnF) that deviates from the ancestral lepidopteran ditrysian pattern. Comparative analysis revealed a 94.65% overall sequence identity with the reference mitogenome, though the PCGs remained highly conserved at 99.35%. Variant analysis demonstrated that this divergence is predominantly driven by structural variations (228 indels) rather than nucleotide substitutions (2 SNPs) across the entire mitogenome; furthermore, 94.7% of the indels were identified in the control region and intergenic spacers. Subtle differences in codon usage were also observed in the ND6 start codon (ATT vs. ATA) and COX1 stop codon (TAA vs. T). Phylogenetic and molecular clock analyses robustly clustered the Taiwan specimen within the C. sinensis clade. Molecular dating estimates that the Conopomorpha lineage originated during the Late Cretaceous (~77.23 Ma). Notably, the divergence between the Taiwan specimen and the reference lineage was estimated to be negligible (<0.01 Ma) within the protein-coding regions, demonstrating a high degree of purifying selection that maintains coding-sequence stability across geographically distinct specimens, even as substantial variation accumulates in non-coding genomic regions.

These findings provide high-resolution genomic resources and a temporal framework for the evolutionary study of Gracillariidae, offering foundational tools for targeted pest management.