Back

Mitochondrial Genome Analysis and Phylogeny and Divergence Time Evaluation of the Strix aluco

Wang, Y.; Zhan, H.; Yang, X.; Zhang, Y.; Long, Z.; Li, B.; Lv, X.; Wildlife Rescue Center of Leigong Mountain National Nature Reserve,

2023-01-21 evolutionary biology
10.1101/2023.01.20.524943 bioRxiv
Show abstract

In this study, a complete mitochondrial genome of the Strix aluco was reported for the first time, with a total length of 18,632 bp. There were 37 genes, including 22 tRNAs, 2 rRNAs, 13 protein-coding genes (PCGs), and 2 non-coding control regions (D-loop). The second-generation sequencing of the complete mitochondrial genome of the S. aluco was conducted using the Illumina platform, and then Tytoninae was used as the out-group, PhyloSuite software was applied to build the ML-tree and BI-tree of the Strigiformes, and finally, the divergence time tree was constructed using Beast2.6.7 software, the age of Miosurnia diurna fossil-bearing sediments (6.0-9.5 Ma) was set as the internal correction point. The common ancestor of the Strix was confirmed to have diverged during the Pleistocene(2.59~0.01Ma). The dramatic uplift of the Qinling Mountains in the Middle Pleistocene and the climate oscillation of the Pleistocene together caused Strix divergence between the northern and southern parts of mainland China. The isolation of glacial-interglacial rotation and glacier refuge was the main reason for the divergence of the common ancestor of the Strix uralensis and the S. aluco during this period. This study provides a reference for the evolution history of the Strix. Summary statementThis study was the first time to assemble the complete mitochondrial genome of Strix aluco, and report the divergence time of Strix. A full discussion was made, and it was inferred that the uplift of the Qinling Mountains and the glacial refuge led to the differentiation of this genus.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.