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Fig 1.

Circular maps of the mitochondrial genome of Cladonia subulata.

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Table 1.

PCGs and rRNA gene composition of Cladonia subulata.

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Table 2.

Comparison of Cladonia mitogenomes.

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Table 2 Expand

Fig 2.

Predicted secondary structure of the 27 typical tRNA genes in the Cladonia subulata mitogenome.

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Fig 3.

Codon usage in the Cladonia subulata mitochondrial genome.

Codon families are indicated below the X-axis. The frequency of codon usage is plotted on the Y-axis.

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Fig 4.

Collinearity analysis of eight mitogenomes from Cladonia.

Homologous regions between different mitogenomes are represented by blocks of the same colour linked by lines. Note: The C. subulata mitogenome was adjusted beginning with the cox1 gene.

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Fig 5.

Variation in the length and base composition of each of 15 protein-coding genes (PCGs) in 8 mitochondrial genomes in the order Cladonia.

A: PCG length variation; B: GC content; C: AT-skew; D: GC-skew. Different species are indicated by different colours.

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Fig 6.

Location of repeats in Cladonia subulata.

A: Detected by REUPuter; B: Detected by Tandem Repeat Finder; C: Detected by MISA; D: The tRNA location. The PCGs, rrnS and rrnL and their length in C. subulata are shown by arrows, and the direction is the direction of translation. Orange lines indicated forward repeats, blue lines indicated palindromic repeats, and grey lines indicated reverse repeats. The circos map was drawn by TBtools [72].

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Table 3.

Numbers of SSRs identified in the mitogenome of Cladonia subulata.

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Table 3 Expand

Fig 7.

Phylogeny of Lecanorales based on the 23 available mitochondrial genomes based on the Bayesian inference (BI) and maximum likelihood (ML).

Numbers on branches indicate posterior probability (BI) and bootstrap support (ML). Cladonia is framed with a dotted blue box. The species and GenBank accession numbers of the mitogenomes used in the phylogenetic analysis are provided in S3 Table.

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Fig 8.

Phylogenetic analysis of eighteen complete mitochondrial genome in Cladonia.

ModelFinder was used to select the best-fit model using AIC criterion. Best-fit model of ML tree according to AIC: GTR+F+R4. Best-fit model of BI tree according to AIC: GTR+F+G4. (ML/BI).

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