BMC Genomics. 2024 Nov 18;25(1):1097. doi: 10.1186/s12864-024-11006-6.
ABSTRACT
Quantifying the features of mitochondrial genome structural variation is crucial for understanding its contribution to complexity. Accurate quantification and interpretation of organizational diversity can help uncover biological evolutionary laws and patterns. The current qMGR approach accumulates the changes in two adjacent genes to calculate the rearrangement frequency RF of each single gene and the rearrangement score RS for specific taxa in the mitogenomes of a given taxonomic group. However, it may introduce bias, as it assigns scores to adjacent genes rather than to rearranged genes. To overcome this limitation, we propose a novel statistical method called qGO to quantify the diversity of gene organization. The qGO method, which is based on the homology of gene order, provides a more accurate representation of genome organizational diversity by partitioning gene strings and individually assigning weights to genes spanning different regions. Additionally, a comprehensive approach is employed for distance computation, generating an extensive matrix of rearrangement distances. Through experiments on more than 5500 vertebrate mitochondrial genomes, we demonstrated that the qGO method outperforms existing methods in terms of accuracy and interpretability. This method improves the comparability of genomes and allows a more accurate comparison of the diversity of mitochondrial genome organization across taxa. These findings have significant implications for unraveling genome evolution, exploring genome function, and investigating the process of molecular evolution.
PMID:39558268 | DOI:10.1186/s12864-024-11006-6
