Utilizing the method of tissue isolation (Rizali et al. 2021), D. eres ZM79-3, D. phaseolorum ZM33-4 and Diaporthe sp. ZM41-5 strains were obtained from branches and trunks of apple trees in Zhengzhou, Henan province, China. The hyphal tips were transferred onto PDA plates for purification, and after approximately 3 days of incubation at 25 °C, the culture plates were stored at 4 °C for short-term preservation. For long-term storage, the fungal colonies were incubated for about 7 days, and edges of the colonies were removed into frozen tubes, which were then stored in 25% glycerol at -80 °C in the fungal collection of Henan Agricultural University. Total genomic DNA (gDNA) extraction of the three isolates was performed by using the cetyltrimethyl ammonium bromide (CTAB) method (Chen et al. 2020). Diaporthe species were identified based on morphological characters and five-locus dataset of ITS, TUB, CAL, TEF1-α, HIS genes (Guo et al. 2020). These sequences have been deposited in GenBank with the accession numbers listed in Suppl. material 1: table S1. The associated taxonomic study will be published in a separate study.

High-quality gDNA samples were then sent to the Novogene Co., Ltd. (Tianjin, China) for library preparation and genome sequencing. Short insert libraries (350 bp) were created using the NEBNext® Ultra DNA Library Prep Kit for Illumina (NEB, USA). Whole-genome sequencing (WGS) was performed on an Illumina Hiseq X Ten platform, producing 150 bp paired-end reads for each sample.

Approximately 5 Gb of raw data were obtained through WGS, and were then processed by trimming adapters and low-quality reads (bases with a Q20 ratio > 30% or containing undetermined bases) using the fastp v0.13.1 (Chen et al. 2018). Subsequently, duplicate removal and error correction were carried out using FastUniq v1.1 (Xu et al. 2012) and Musket v1.1 (Liu et al. 2013) sequentially. The cleaned paired-end reads were assembled de novo using the SPAdes v3.14.1 software with kmers of 21, 33, 55, 77, 99, and 127 (Bankevich et al. 2012). Mitochondria-related contigs were then identified and pooled for each sample by performing BLASTN search against the reference mitogenomes from D. longicolla MSPL 10-6 (Koloniuk et al. 2016). The gaps between these contigs were filled using MITObim v1.9 to construct closed-circular mitochondrial DNA (mtDNA) macromolecules of the three Diaporthe samples (Hahn et al. 2013). Furthermore, the three assembled mitochondrial sequences were verified using NOVO Plasty (Dierckxsens et al. 2017).

The newly obtained complete three mitogenomes (D. eres ZM79-3, D. phaseolorum ZM33-4 and Diaporthe sp. ZM41-5), along with three Diaporthe mitogenomes (D. caulivora VNIIKR SE Dcaul3, D. longicolla MSPL 10-6 and D. sojae VNIIKR SE Dps12) obtained from the NCBI GenBank database, were meticulously annotated following the methods described by Ma et al. (Ma et al. 2022). Initially, Mfannot (Valach et al. 2014) and MITOS (Bernt et al. 2013) were used to predict the protein coding genes (PCGs), unidentified open reading frames (uORFs), rRNAs, tRNAs, and introns of the six Diaporthe mitogenomes based on genetic code 4 (mold mitochondrial). Subsequently, the NCBI Open Reading Frame Finder (https://www.ncbi.nlm.nih.gov/orffinder) was employed to modify or predict the PCGs and uORFs, which were further annotated through BLASTP searches against the NCBI non-redundant protein sequence database (Bleasby and Wootton 1990). The intron and exon boundaries of PCGs were verified using the exonerate v2.2 software (Slater and Birney 2005) with D. longicolla MSPL 10-6 mitogenomes as references (Koloniuk et al. 2016). Secondary structures of the tRNA genes were predicted by MITOS with default parameters (Bernt et al. 2013), and were further verified by utilizing tRNAscan-SE v2.00 (https://lowelab.ucsc.edu/tRNAscan-SE/index.html), and were redrawn in Adobe Illustrator CS6. The graphical maps of the six Diaporthe mitogenomes were created using the online program OGDraw v1.2 (Greiner et al. 2019).

For further comparative analyses of Diaporthales mitogenomes, other seven complete mitogenomes of Diaporthales species were downloaded from the NCBI GenBank database (Kanzi et al. 2016). Their detailed information (such as accession numbers) was provided in Suppl. material 1: table S2.

The strand asymmetries of the thirteen Diaporthales mitogenomes were assessed based on the formulas: AT skew = [A − T] / [A+T], and GC skew = [G − C] / [G + C] (Zou et al. 2022). Mitogenome collinearity analysis of the six Diaporthe species was performed using Mauve v2.4.0 (Darling et al. 2004). The sequence manipulation suite was utilized to analyze the codon usage frequency and preference of the six Diaporthe mitogenomes based on genetic code 4 (Stothard 2000). The KaKs Calculator 3.0 software (Zhang 2022) was used to calculate synonymous (Ks) and nonsynonymous substitution rates (Ka) for 15 core PCGs (atp6, atp8, atp9, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4, nad4L, nad5, nad6 and rps3) in all 13 acquired Diaporthales mitogenomes. Based on the Kimura-2-parameter (K2P) substitution model, MEGA v6.06 was used to calculate the genetic distances between each pair of the 15 core PCGs (Caspermeyer 2016). Additionally, BLASTN searches were conducted within the six Diaporthe mitogenomes to detect interspersed repeats or intragenomic duplications of large fragments with an E-value of <1e-10 (Chen et al. 2015). Tandem Repeats Finder was used to analyze the tandem repeats of six Diaporthe mitogenomes (Benson 1999). In addition, the contribution rates of different genetic compositions to the mitogenome expansion/contraction of six Diaporthe species were calculated using the formulas: [A − B] / [C − D] (A: size of one genetic component in the larger mitogenome; B: size of the same genetic component in the smaller mitogenome; C: size of the larger mitogenome; D: size of the smaller mitogenome).

A comparative mitogenomic analysis was performed to evaluate the variations and conservations between Diaporthales species in terms of genome size, base composition, GC content, gene number, intron number, gene arrangement, and gene content. As mobile genetic elements in mitogenome, introns could significantly alter the organization and size of fungal mitogenomes, which can be divided into different position classes (Pcls) based on their precise insertion position in the coding region of core genes (Ma et al. 2022). Following the method described by Férandon et al. (Férandon et al. 2010), introns within the cox1 genes of the 13 Diaporthales mitogenomes could be categorized into different position classes (Pcls). Using the cox1 gene of Juglanconis juglandina mitogenome as the reference (Kanzi et al. 2016), the cox1 genes from the other 12 Diaporthales species were aligned with Clustal W to detect the insertion sites of introns (Thompson et al. 1994). Pcls were named according to their insertion sites in the corresponding reference sequence. Generally, the same Pcls from different species exhibited high sequence similarity and contained homologous intronic ORFs (Megarioti and Kouvelis 2020).

In order to investigate the phylogenetic relationships of the six Diaporthe species, a phylogenetic tree was constructed with 98 Ascomycetes species using the concatenated mitochondrial gene set, which included 14 core PCGs and the rps3 gene. Taphrina deforman and T. wiesneri from Taphrinomycetes were appointed as outgroups (Tsai et al. 2014). Mitochondrial genes were aligned using Clustal W in MEGA v6.06 software (Caspermeyer 2016), and the FASconCAT v1.0 tool was used to combine 15 genes into a concatenated mitochondrial gene set (Kück and Meusemann 2010). Partition homogeneity test was used to detect potential phylogenetic conflicts between different mitochondrial genes, and PartitionFinder v2.1.1 was applied for determination of best-fit models of phylogeny and partitioning scheme of the gene set (Lanfear et al. 2017). Subsequently, we utilized Bayesian inference (BI) and maximum likelihood (ML) methods for phylogenetic analysis. BI analysis was conducted with MrBayes v.3.1.2 using the GTR substitution model and gamma-distributed rate variation for the site-to-site variance ratio, and four Markov chain Monte Carlo (MCMC) chains were analyzed twice using 2 × 10⁷ generation random trees. During the analysis, samples were taken every 1000 generations and stopped when the mean standard deviation of the splitting frequency fell below 0.01, discarding the 25% aged samples from the obtained samples, and the remaining trees were used to calculate Bayesian posterior probability (BPP) values in the 50% majority-rule consensus trees (Ronquist and Huelsenbeck 2003; Shapiro et al. 2006). The ML analysis was performed in IQtree v.1.6.8 under the GTR + G substitution model. Bootstrap values (BS) were assessed with 1000 replicates using an ultrafast bootstrap approach (Hillis and Bull 1993; Nguyen et al. 2015). Phylogenetic trees were visualized and adjusted with FigTree v1.4.4 (http://tree.bio.ed.ac.uk/software/figtree/).

The complete three mitogenomes of D. eres ZM79-3, D. phaseolorum ZM33-4 and Diaporthe sp. ZM41-5 were deposited in the GenBank database under the accession numbers PQ493439, PQ493438 and PQ493440, respectively, and their raw sequencing data were deposited in the Sequence Read Archive (SRA) database under the accession numbers SRR31801374, SRR31801985 and SRR31806477, respectively.

Mitogenome : Mitochondrial genome; PCG: Protein-coding gene; Pcls: Position classes; Ks: Synonymous substitution rates; Ka: Nonsynonymous substitution rates; BI: Bayesian inference; ML: Maximum Likelihood; ITS: internal transcribed spacer; tef1: translation elongation factor-1 alpha; tub: beta-tubulin; his: histone; cal: calmodulin.

In the present study, the complete mitochondrial genomes of the three Diaporthe species (D. eres ZM79-3, D. phaseolorum ZM33-4 and Diaporthe sp. ZM41-5) were circularly assembled with the total sizes of 89,134 bp, 61,667 bp and 59,327 bp, respectively. In addition, three Diaporthe mitogenomes (D. caulivora VNIIKR SE Dcaul3, D. longicolla MSPL 10-6 and D. sojae VNIIKR SE Dps12) were downloaded from public databases with sizes of 55,068 bp, 53,646 bp, and 108,865 bp, respectively, and compared and analyzed with the three newly assembled Diaporthe mitogenomes (Fig. 1). The GC content of the six Diaporthe mitogenomes ranged from 32.30% to 34.63%, with an average GC content of 33.24% (Suppl. material 1: table S2). The mitogenome of Diaporthe sp. ZM41-5 contained the highest GC content, while D. eres ZM79-3 contained the lowest GC content, among the six investigated species. The six Diaporthe mitogenomes all contained both positive GC skew and negative AT skew. The proportion of protein-coding regions, intronic regions, intergenic regions, and ncRNA regions (including tRNAs and rRNAs genes) are shown in Suppl. material 2: fig. S1. In the mitochondrial genomes of D. eres ZM79-3, D. sojae VNIIKR SE Dps12, and Diaporthe sp. ZM41-5, intronic regions and protein-coding regions accounted for more than 59% of the whole mitogenomes and intergenic regions accounted for 26.09%–27.84% of the entire mitogenomes. In the other three Diaporthe mitogenomes, intergenic regions and protein-coding regions occupied the largest proportion, accounting for more than 60% and intronic regions accounting for 21.83–26.57% of the whole mitogenomes. Their ncRNA genes (including tRNAs and rRNAs) took up the smallest proportion of the six Diaporthe mitogenomes, reaching only 8.99%–15.03%.

The number of PCG identified in the mitogenomes of the six Diaporthe species ranged from 18 to 28 (Suppl. material 1: table S2). The D. sojae VNIIKR SE Dps12 mitogenome was found to contain the most PCG among all six mitogenomes detected. Moreover, all six Diaporthe mitochondrial genomes contained 14 typical core PCGs (atp6, atp8, atp9, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4, nad4L, nad5, and nad6) and a conserved core gene coding for the putative ribosomal protein S3 (rps3). In addition, some PCGs in the mitogenomes of the six Diaporthe species were found to encode homing endonucleases (HEs). Some of the PCGs in the six detected mitogenomes were not similar to any known proteins in public databases, which indicates that there are still a variety of PCGs in the Diaporthe mitochondrial genomes that have yet to be characterized. A number of introns were also detected ranging from 10 to 29 in the six mitogenomes, with D. sojae VNIIKR SE Dps12 containing the highest number of introns and D. caulivora VNIIKR SE Dcaul3 and D. longicolla MSPL 10-6 the lowest (Suppl. material 1: tables S2, S3). Meanwhile, 23 intronic ORFs were found in the mitogenome of D. sojae VNIIKR SE Dps12, 11 in D. caulivora VNIIKR SE Dcaul3, 17 in D. eres ZM79-3, 8 in D. longicolla MSPL 10-6, 10 in D. phaseolorum ZM33-4 and 11 in Diaporthe sp. ZM41-5. These intronic ORFs mainly encoded HEs with LAGLIDADG and GIY-YIG endonuclease motifs, and a few encoded proteins with unknown function (Suppl. material 1: table S3).

Figure 1. 

Circular maps of the six Diaporthe mitogenomes. Genes are represented by different colored blocks. Colored blocks outside each ring indicate that the genes are on the forward strand, while colored blocks within the ring indicates that the genes are located on the reverse strand. Genes on the forward strand are transcribed in a counterclockwise direction, while genes on the reverse strand are transcribed in a clockwise direction. The inner grayscale bar graph shows the GC content of the mitochondrial sequences. The circle inside the GC content graph marks the 50% threshold.

The mitogenomes of six Diaporthe species both contained two rRNA genes, namely the small subunit ribosomal RNA (rns), and the large subunit ribosomal RNA (rnl) (Suppl. material 1: table S3). The lengths of rnl genes in the six detected mitogenomes ranged from 5,952 bp to 14,526 bp and 1,611 bp to 1,727 bp in the rns genes. The longest rnl was found in the mitogenome of D. sojae VNIIKR SE Dps12 and the longest rns was found in the mitogenome of D. caulivora VNIIKR SE Dcaul3 (Suppl. material 1: table S3). The average lengths of the rnl and rns genes were 7,744 bp and 1,647 bp, respectively. In addition, we also found that the rnl genes had 1–4 introns in the six Diaporthe species, while no introns were detected in the rns genes.

We detected 23 to 26 tRNA genes in the six Diaporthe mitogenomes, which encoded 20 standard amino acids (Suppl. material 1: table S3). All six mitogenomes contained three tRNAs that coded for arginine, serine and threonine with different anticodons and two tRNAs that coded for methionine with the same anticodons. We also detected additional tRNA genes, including the trnH, trnM, trnR, and trnY in the six mitogenomes (Fig. 2). The size of the tRNA genes ranged from 71 bp to 86 bp, mainly due to variation in the size of the extra arms (Suppl. material 1: table S3). In addition, we also observed an interesting phenomenon in which a 13-base intron sequence was inserted between the sequences of the antisense codon arm of the trnI-2 in the D. sojae VNIIKR SE Dps12 mitogenome, resulting in a length of 83 bp for this gene. Of the 23 tRNA genes shared by the six Diaporthe mitogenomes, 14 contained mutational sites. A total of 41 mutational sites were detected in the all tRNA genes among the six Diaporthe mitogenomes (Fig. 2 and Suppl. material 1: table S4).

Most core PCGs in the six Diaporthe mitogenomes used ATG as start codons, with an exception of the cox3 gene, which used TGT as start codons in all the six Diaporthe species (Suppl. material 1: table S5). TAA (72.38%) was the most common used stop codon in the core PCGs of six Diaporthe mitogenomes, followed by TAG (27.62%). The stop codons varied among the six Diaporthe species. i.e., the atp6 genes of D. eres ZM79-3, D. sojae VNIIKR SE Dps12, Diaporthe sp. ZM41-5, D. caulivora VNIIKR SE Dcaul3 and D. phaseolorum ZM33-4 used TAA as a stop codon, while D. longicolla MSPL 10-6 used TAG as a stop codon. The nad6 gene of D. phaseolorum ZM33-4 had TAA as a stop codon, and the nad6 genes of the other six species used TAG as a stop codon (Suppl. material 1: table S5). Codon usage analysis showed that the most frequently used codons in the six Diaporthe mitogenomes were TTA (for Leucine; Leu), TTT (for phenylalanine; Phe), AAA (for lysine; Lys), AAT (for asparagine; Asn), and ATA (for isoleucine Ile) (Fig. 3 and Suppl. material 1: table S6). The high frequency of use of A and T in codons resulted in the high AT content of the six Diaporthe mitogenomes (average 66.76%).

Figure 2. 

Putative secondary structures of tRNA genes identified in the mitogenomes of six Diaporthe species. The 23 tRNAs in green fonts represent tRNAs shared by the six Diaporthe species, while the tRNAs in blue font represent in all Diaporthe species except Diaporthe sp. ZM41-5, the tRNA in orange font represents tRNA only in D. sojae VNIIKR SE Dps12, and the tRNA in purple font represents tRNA only in D. eres ZM79-3. Besides, residues conserved across the six mitogenomes are shown in green, while variable sites are shown in red.

We have identified overlapping nucleotides in all six Diaporthe mitochondrial genomes, and the highest degree of overlap was found in the D. caulivora VNIIKR SE Dcaul3 mitogenome, which had three overlapping nucleotides (Suppl. material 1: table S3). Overlapping nucleotides were all observed in the six Diaporthe mitogenomes, located across the adjacent genes nad4L and nad5 (−1 bp). The length of each overlapping nucleotide in the six mitogenomes ranged from 1 bp to 202 bp. The largest overlapping nucleotide among the six Diaporthe mitogenomes was detected in D. longicolla MSPL 10-6 and Diaporthe sp. ZM41-5, which was located between cox3 and orf118 (−202 bp) and between cox3 and orf168 (−202 bp), respectively. Intergenic region sequences ranging from 16,527 bp to 28,755 bp were detected in the six Diaporthe mitogenomes, with occupations ranging from 26.09% to 33.05%. The lengths of these intergenic segments ranged from 1 to 2,590 bp, with the longest intergenic region located between orf170 and cob in the mitogenome of D. longicolla MSPL 10-6 (Suppl. material 1: table S3).

Using BLASTN searches of the six Diaporthe mitogenomes against themselves, we identified 39, 44, 47, 67, 45, and 20 repetitive elements in the mitogenomes of D. caulivora VNIIKR SE Dcaul3, D. eres ZM79-3, D. longicolla MSPL 10-6, D. phaseolorum ZM33-4, D. sojae VNIIKR SE Dps12 and Diaporthe sp. ZM41-5, respectively (Suppl. material 1: table S7). The size of these repeat elements ranged from 36 to 1,283 bp, with pairwise nucleotide similarities ranging from 64.15% to 100%. The largest repeat region was found in the mitogenome of D. sojae VNIIKR SE Dps12, which was located in the protein coding regions of orf474 and intergenic sequences around it, as well as in the protein coding regions of orf518 and intergenic sequences around it. Repetitive sequences accounted for 4.38%, 10.99%, 6.54%, 8.24%, 19.48%and 2.74% of the D. caulivora VNIIKR SE Dcaul3, D. eres ZM79-3, D. longicolla MSPL 10-6, D. phaseolorum ZM33-4, D. sojae VNIIKR SE Dps12 and Diaporthe sp. ZM41-5 mitogenomes, respectively (Suppl. material 1: table S7).

Tandem repeat sequences accounted for 0.67%, 0.98%, 0.32%, 1.74%, 2.00% and 1.41% of the D. caulivora VNIIKR SE Dcaul3, D. eres ZM79-3, D. longicolla MSPL 10-6, D. phaseolorum ZM33-4, D. sojae VNIIKR SE Dps12 and Diaporthe sp. ZM41-5 mitogenomes, respectively. 8, 15, 4, 10, 26, and 13 tandem repeats were identified in D. caulivora VNIIKR SE Dcaul3, D. eres ZM79-3, D. longicolla MSPL 10-6, D. nobilis, D. phaseolorum ZM33-4, D. sojae VNIIKR SE Dps12 and Diaporthe sp. ZM41-5 mitogenomes, respectively (Suppl. material 1: table S8). In addition, the length of repeat units ranged from 3 bp to 168 bp, and the copy number ranged from 1.9 to 22.5, and the longest tandem repeat sequence (168 bp) was detected in the mitogenome of D. sojae VNIIKR SE Dps12, which was located in the protein coding regions of orf458 (Suppl. material 1: tables S3, S8).

A total of 315 introns were detected in the 13 Diaporthales mitogenomes, each of which contained 10 to 48 introns. Most introns in Diaporthales belonged to the Group I. The intron number varied greatly in the Diaporthales mitogenomes which indicated that intron acquire/loss events have occurred in the evolution of Diaporthales species. The cox1 gene of Diaporthales contained the most number of introns, accounting for 31.11% (98/315) of the total introns. Thus, intron dynamics in the cox1 gene was used for further analysis among all the 13 Diaporthales species.

A total of 35 different Pcl types were detected in cox1 genes of 13 Diaporthales species (Suppl. material 2: fig. S2). The number of introns varied greatly between species, with the highest number of Pcls (19) in the cox1 gene of J. juglandina and the lowest number of Pcls (2) in D. caulivora VNIIKR SE Dcaul3 (Fig. 4). It should be emphasized that the cox1 gene of J. juglandina contained the same number of introns as the maximum number of introns (19) reported for the Agaricus bisporus cox1 gene, which has the largest number of introns ever found in the cox1 gene (Férandon et al. 2010). Here, 35 Pcls were identified widely distributed in the 13 Diaporthales species. Among them, P380, P877 and P1225 were the most common Pcls, which were detected 8, 10 and 12 times in 13 Diaporthales species, respectively. Pcls, including P218, P330, P357, P405, P413, P424, P554, P789, P798, P975, P1139, P1284, P1438 and P1482 could only be detected in one of the 13 Diaporthales mitogenomes. These results indicated that ancestors of Diaporthales lost or gained introns to a large extent during evolution. Additionally, 23 Pcls were detected in the cox1 genes of six Diaporthe species, accounting for 23.47% of the total introns in the cox1 gene of 13 Diaporthales species. D. sojae VNIIKR SE Dps12 had the highest number of Pcls (6) and D. caulivora VNIIKR SE Dcaul3 had the lowest number of Pcls (2). Meanwhile, Pcls P380 and P1225 were found to be distributed in five of the six Diaporthe species, and P877 was detected in four of the six Diaporthe species, suggesting that these Pcls might be widespread in Diaporthe species.

Figure 3. 

Codon usage in the mitogenomes of six Diaporthe species. Frequency of codon usage is plotted on the y-axis a Diaporthe caulivora VNIIKR SE Dcaul3 b D. eres ZM79-3 c D. longicolla MSPL 10-6 d D. phaseolorum ZM33-4 e D. sojae VNIIKR SE Dps12 f Diaporthe sp. ZM41-5 g genetic code 4 (mold mitochondrial).

Figure 4. 

Position class (Pcl) information of cox1 genes in the 13 Diaporthales species. Introns in cox1 genes of 13 mitogenomes calibrated were classified into different position classes (Pcls) using the cox1 gene of Juglanconis juglandina as the reference. Each Pcl was constituted by introns inserted at the same position of corresponding cox1 gene of J. juglandina and named according to its insertion site in the aligned corresponding reference sequence (nt). The Pcls in different color represent their different numbers among the 13 Diaporthales mitogenomes. Phylogenetic positions of the 13 species were established using the Bayesian inference (BI) method and Maximum-Likelihood (ML) methods based on combined mitochondrial data sets.

Here, we used 15 core PCGs to calculate the genetic distance and substitution rates between each pair of 13 Diaporthales species. The nad4 gene had the greatest genetic distance (average value 0.24) among the 13 Diaporthales species, followed by the rps3 (average value 0.20), which indicated that they showed the fastest mutation rate among the 15 PCGs. The nad1 gene exhibited the lowest genetic differentiation between the 13 Diaporthales species, with an overall mean K2P distance of 0.10, indicating that the nad1 gene was highly conserved (Fig. 5 and Suppl. material 1: table S5). Across the 15 core PCGs examined, the rps3 gene exhibited the highest non-synonymous substitution rate (Ka) (average value 0.14) between the 13 Diaporthales mitogenomes, followed by nad4 (average value 0.13), while the nad4L gene had the lowest (average value 0.03). The synonymous substitution (Ks) rate of nad3 was the highest (average value 0.97), and that of nad1 was the lowest (average value 0.32) among the 15 PCGs. The overall Ka/Ks values for 15 examined core PCGs were less than 1, which suggested that these genes were subject to purifying selection (Suppl. material 1: table S5).

In addition, we further conducted an in-depth comparison of the similarities and differences between the 15 core PCGs among the six Diaporthe species. Among the 15 core PCGs, the length of the 13 PCGs varied significantly except for the atp8 and atp9 genes, which had identical gene lengths in the six Diaporthe species, with the cox1 gene having maximum length variation of 5,183 bp (Fig. 6). Across the 15 core PCGs we detected, atp9 contained the highest average GC content of 34.89%, followed by cox2 with 30.83%. The atp8 gene contained the lowest GC content with an average of 24.80%. Additionally, we found that the same PCGs also had differences in GC content among the six mitogenomes. i.e., nad6 contained the highest GC content of 36.81% in Diaporthe sp. ZM41-5, while in other five Diaporthe species GC content in nad6 gene only ranged from 22.32% to 23.51% (Suppl. material 1: table S5). These differences indicated that the core PCGs of Diaporthe mitogenomes mutated frequently. The AT skews of atp8, atp9, nad1, nad4, and nad5 in the six mitogenomes were negative, while the AT skew of rps3 was positive (Fig. 6). The AT skew of nad4L was zero in D. caulivora VNIIKR SE Dcaul3 and the AT skew of cox2 was negative in D. sojae VNIIKR SE Dps12, while the AT skews of nad4L and cox2 were positive in the other five Diaporthe species. The nad6 showed positive AT skew in Diaporthe sp. ZM41-5 and negative AT skew in the other five Diaporthe species. The nad2 and nad3 showed positive AT skew in D. eres ZM79-3 and negative AT skew in the other five Diaporthe mitogenomes. The atp6 exhibited negative AT skew in D. longicolla MSPL 10-6 and D. phaseolorum ZM33-4 and positive AT skew in the other four Diaporthe species. The cob exhibited positive AT skew in D. caulivora VNIIKR SE Dcaul3, D. phaseolorum ZM33-4 and Diaporthe sp. ZM41-5. and negative AT skew in the other three Diaporthe species. The cox1 showed positive AT skew in D. eres ZM79-3 and D. longicolla MSPL 10-6, and negative AT skew in the other four Diaporthe species. The cox3 exhibited positive AT skew in D. eres ZM79-3 and D. sojae VNIIKR SE Dps12 and negative AT skew in the other four Diaporthe species. AT skew in core PCGs varied among species within the genus, indicating frequent A/T mutations in core PCGs. The GC skews were positive in most core PCGs, with an exception of atp8, which had negative GC skew (Suppl. material 1: table S5).

Figure 5. 

Genetic analysis of 15 core protein coding genes (including rps3 gene) in 13 Diaporthales species. The black straight and dotted lines indicate the magnitude of the median and mean values, respectively. K2P, pairwise genetic distances between each pair of the 15 core PCGs in the 13 Diaporthales mitogenomes based on the Kimura-2-parameter model; Ka, the number of nonsynonymous substitutions per nonsynonymous site; Ks, the number of synonymous substitutions per synonymous site.

Figure 6. 

Full-length sequence variation in the length and base composition of each of the 15 protein coding genes (PCGs) among six Diaporthe mitochondrial genomes a PCG length variation b GC content across PCGs c AT skew d GC skew.

In the present study, we analyzed the gene arrangements of 15 core PCGs and 2 rRNAs in the 13 Diaporthales mitogenomes, and found that there were large variations in gene arrangement among different genera, except for the genus Cryphonectria and Chrysoporthe which had identical gene arrangement (Fig. 7). Besides, three uninterrupted conserved gene blocks, cob, nad4 and nad1 (Block I), rns, atp6, atp8, nad5 and nad4L (Block II), rnl, rps3 and nad6 (Block III), were also found in the mitochondrial gene arrangement of 13 Diaporthales species. Meanwhile, we also observed the identical gene arrangements between species from the same genus, such as Diaporthe, Juglanconis and Chrysoporthe.

Whole-mitogenome collinearity analysis was performed between six closely related Diaporthe species. A total of 4 locally collinear blocks (A to D) were detected in each of the six Diaporthe mitogenomes using Mauve (Suppl. material 2: fig. S3). The size of these homologous regions varied among different species, when compared to the D. sojae VNIIKR SE Dps12 mitogenome, most of these homologous region blocks in the other five species were significantly reduced in size. Except for the rearrangement of homologous regions B and C in the mitogenome of D. eres ZM79-3, the other homologous regions were in the same order among the six Diaporthe species. In summary, the gene arrangement and collinearity in the mitogenomes of the six Diaporthe species were almost highly conserved within the genus.

Figure 7. 

Mitochondrial gene arrangement analyses of the 13 Diaporthales species. The gene sequence begins with the cox1 gene and contains 15 core protein coding genes (PCGs) and two rRNA genes. The same genes were represented by the same color blocks. Phylogenetic positions of the 13 species were established using the Bayesian inference (BI) method and Maximum-Likelihood (ML) method based on combined mitochondrial data sets.

Across the 13 Diaporthales species examined, there was a large variation in the mitogenome sizes, which ranged from 53,646 to 267,504 bp, with an average size of 125,149 bp (Suppl. material 1: table S2). J. juglandina had the largest mitogenome (267,504 bp), and D. longicolla MSPL 10-6 had the smallest (53,646 bp). The sizes of all the six Diaporthe mitogenomes (53,646 bp to 108,865 bp) were smaller than the average mitogenome size of the 13 Diaporthales species tested (125,419 bp). Meanwhile, the GC content of the 13 mitochondrial genomes also varied, ranging from 29.71 to 34.63%, with an average GC content of 32.46%. The average GC content of the six Diaporthe species (33.24%) was higher than the average GC content of the 13 Diaporthales mitogenomes, and the Diaporthe sp. ZM41-5 mitogenome contained the highest GC content among the 13 mitogenomes tested. All the 13 Diaporthales mitogenomes had positive GC skews, while only 2 of the 13 mitogenomes had positive AT skews (Suppl. material 1: table S2). The number of PCGs in the 13 Diaporthales mitogenomes ranged from 18 to 49, with Chrysoporthe austroafricana containing the highest number of PCGs and D. longicolla MSPL 10-6 and D. phaseolorum ZM33-4 containing the lowest. The J. juglandina mitogenome had the largest numbers of introns (48) and intronic ORFs (83) among the 13 Diaporthales species, followed by the J. oblonga mitogenome with 39 introns and 58 intronic ORFs. In addition, two rRNA genes and 23–28 tRNA genes were detected in the 13 Diaporthales mitogenomes (Suppl. material 1: table S2).

To clarify the phylogenetic status of Diaporthe in the phylum Ascomycota, an identical and well-supported phylogenetic tree for 98 Ascomycota species was constructed using both Bayesian inference (BI) and Maximum likelihood (ML) methods based on the 15 concatenated mitochondrial conserved PCG genes (Fig. 8). We found all the major clades had good supported values within the phylogenetic tree (BPP ≥ 0.95; BS ≥ 72). Both T. deforman and T. wiesneri from Taphrinomycetes were designated as the outgroup, while the other 96 Ascomycota species were divided into five major clades, corresponding to Dothideomycetes, Sordariomycetes, Lecanoromycetes, Eurotiomycetes and Pneumocystidomycetes (Suppl. material 1: table S9). Within the Sordariomycetes, members of Diaporthales were also well separated from members of neighboring Microascales, Ophiostomatales, Xylariales, Sordariales, and Hypocreales. Among the 13 Diaporthales, the different members were well separated with strong BS support and BPP values of 1 for all clades. Particularly, members of the five genera Diaporthe, Juglanconis, Ophiognomonia, Cryphonectria and Chrysoporthe were shown to closely cluster together in the inferred tree, indicating a close relationship. Additionally, members of the same genus clustered together, conforming their generic relationship as sister species in Diaporthe. Overall, phylogenetic analyses highlighted the potential of mitogenomes in aiding taxonomists to differentiate between members of Diaporthe and its closely related genera.

Figure 8. 

Molecular phylogeny of 98 Ascomycota species based on Bayesian inference (BI) and Maximum likelihood (ML) analysis of 15 core protein coding genes. Support values are Bayesian posterior probabilities (BPP) and bootstrap values (BS) placed before and after the slash, respectively. Asterisks indicate BPP and BS values of 1.00 and 100, respectively. Both Taphrina deforman and T. wiesneri from Taphrinomycetes were appointed as the outgroup. Species and NCBI registry numbers of mitogenomes used for phylogenetic analyses can be provided in Suppl. material 1: table S9.

In the present study, we newly sequenced and assembled the mitogenomes of D. eres ZM79-3, D. phaseolorum ZM33-4 and Diaporthe sp. ZM41-5 and compared them with three Diaporthe mitogenomes published previously, namely of D. caulivora VNIIKR SE Dcaul3, D. longicolla MSPL 10-6 and D. sojae VNIIKR SE Dps12, as well as seven other Diaporthales species (Kanzi et al. 2016; Koloniuk et al. 2016; Li et al. 2024). The size of the 13 examined Diaporthales mitogenomes varied largely, with the largest belonging to J. juglandina, which was 4.99 times greater than the smallest mitogenome (D. longicolla MSPL 10-6). Significant genomic size variability was also observed among the mitogenomes of the six Diaporthe species examined, particularly between D. sojae VNIIKR SE Dps12 and D. longicolla MSPL 10-6, with a range of 102.93% ((max-min)/min) (Suppl. material 1: table S2). Previous studies had indicated that fungal mitogenome expansion/contraction was closely linked to the accumulation of repetitive sequences, plasmid-derived genes, intergenic regions, and intron dynamics (Boussau et al. 2011; Zubaer et al. 2018; Chen et al. 2021). In this study, using the mitogenome of D. longicolla MSPL 10-6 as a reference, we found that intron regions contributed the most to mitochondrial expansion of D. caulivora VNIIKR SE Dcaul3, Diaporthe sp. ZM41-5, D. phaseolorum ZM33-4, D. eres ZM79-3 and D. sojae VNIIKR SE Dps12 with 101.41%, 89.33%, 58.33%, 58.56%, and 50.79%, respectively (Suppl. material 2: fig. S1). This result was consistent with previous research indicating the significant role of intron regions in the process of fungal mitogenome size changes (Li et al. 2019b; Li et al. 2020; Ma et al. 2022; Song et al. 2024). Similarly, using the mitogenome of D. sojae VNIIKR SE Dps12 as a reference, we also found that the intronic and intergenic regions played primary and secondary roles in the contraction processes in all Diaporthe species. Our results also highlighted the importance of intergenic regions in Diaporthe mitochondrial size changes. Repetitive sequences also contributed to the expansion/contraction process, although their contribution rates were lower than those of intronic regions. No plasmid-derived genes were identified in any of the six Diaporthe mitogenomes, similar to findings in the mitogenomes of the Cryphonectria and Chrysoporthe genus (Kanzi et al. 2016). In summary, the sequencing of the three new Diaporthe mitogenomes in this study, along with the three previously sequenced Diaporthe mitogenomes, enhanced our understanding of mitogenome size boundaries and variations within the Diaporthe genus (Koloniuk et al. 2016; Li et al. 2024).

During long-term evolution, the mitogenome of fungi experienced gene loss, a common phenomenon in mitochondrial genome studies (Adams et al. 2002; Adams and Palmer 2003; Li et al. 2023; Song et al. 2024). However, certain genes, including a core set of PCGs, 2 rRNAs, and even up to 38 tRNAs, were retained in the mitogenome, playing essential roles in cellular energy metabolism and environmental response (Allen 2015; Wang et al. 2020b). Similarly, to most fungi, the mitogenomes of the six Diaporthe species contained 15 PCGs (including rps3 gene), 2 rRNAs, and 23 to 26 tRNAs, which appeared to be conserved when compared with other Diaporthales species (Suppl. material 1: table S2) (Kanzi et al. 2016; Koloniuk et al. 2016;) .Although the core PCGs in the six Diaporthe species were consistent in number and type, they displayed significant differences in sequence length, GC content, base composition, and codon usages. The impact of these variations on mitochondrial function requires further investigation. K2P results showed that the 15 core PCGs evolved at different rates, but all underwent purifying selection (Fig. 5). Non-conserved PCGs with unknown functions were also present in the mitogenomes of the six Diaporthe species, warranting further research to understand the origin and function of mitogenomes. Moreover, 14 out of the 23 tRNAs shared by the all Diaporthe species exhibited site variation (Suppl. material 1: tables S3, S4 and Fig. 2), suggesting that the frequency of mutations may influence fungal growth or stress responses. Mutations in tRNA were considered to be closely linked to protein synthesis efficiency and may ultimately impact the phenotype of eukaryotes (Giegé et al. 1998; Ding et al. 2019; Lin et al. 2021). The effects of tRNA mutations on Diaporthe species necessitate additional study. Additionally, the unique trnI-2 (uau) presented in D. sojae VNIIKR SE Dps12, with an inserted fragment in the tRNA anticodon arm, but the effects of insertion fragment in tRNA on D. sojae VNIIKR SE Dps12 were unclear. Further investigation is required to understand the effects of the inserted fragment in tRNA on D. sojae VNIIKR SE Dps12.

Introns were commonly found in fungal mitogenomes as mobile genetic elements, and their accumulation, movement and degeneration caused intron polymorphisms in different fungal species, affecting the organization and size of fungal mitogenomes (Hamari et al. 2002; Fan et al. 2019; Song et al. 2024). In the present study, we also observed that introns were the main factor contributing to the size variation of Diaporthe mitogenomes, as shown in Suppl. material 2: fig. S1. Further research had classified these introns into groups I and II, with group I introns being relatively abundant in fungal mitogenomes. Group I introns, containing homing endonucleases, were found to facilitate intron transfer (Megarioti and Kouvelis 2020). Previous studies have identified introns in various genes of fungal mitogenomes, including core PCGs and rRNA genes, with the cox1 gene being the primary host gene for fungal introns (Férandon et al. 2010; Ma et al. 2022). In our study, we also found that the cox1 gene harbored the highest number of introns in the 13 Diaporthales mitogenomes, accounting for 31.11% of the total introns (Suppl. material 1: table S2). Further analysis of introns from the cox1 gene revealed orthologous introns known as Pcls, which were useful for studying genetic variation within fungi and evolutionary relationships between species (Michel and Ferat 1995; Megarioti and Kouvelis 2020). In this research, we found that the number and type of Pcls in Diaporthales mitogenomes varied significantly, indicating frequent intron loss and gain events within Diaporthales species (Fig. 4 and Suppl. material 2: fig. S2). However, this variation appeared to be controlled within certain limits in mitogenomes of six species of the Diaporthe genus. P380, P877 and P1225 as universal Pcls were consistently detected in most Diaporthe species, while others (P554, P783, P899 and P975) were only once found in individual species (Fig. 4 and Suppl. material 2: fig. S2). This suggests that some universal introns may have been inherited from a common ancestor. In contrast, specific Pcls such as P554 and P975 were only detected in D. eres ZM79-3 and D. sojae VNIIKR SE Dps12, respectively, while homologous introns were detected in Arthrobotrys oligospora and Erysiphe necator far from the genus Diaporthe, indicating potential intron transfer events might have occurred between distant species. Future sequencing and analysis of additional mitogenomes from Diaporthales species are needed to uncover the mechanisms behind the origin, transfer, and evolution of these introns fully.

Mitochondrial gene arrangements offer valuable insights into genetic variation and phylogenetic relationships among different species (Satoh et al. 2010; Hikosaka et al. 2011; Zheng et al. 2018; Li et al. 2021). Currently, the study of mitochondrial gene rearrangements in fungi lags behind that in animals. While several models have been proposed to explain mitochondrial gene rearrangements in animals, a lot of studies have suggested that fungal mitogenomes may have more complex rearrangement mechanisms (Lavrov et al. 2002; Xia et al. 2016). Large-scale gene rearrangements were identified in 13 Diaporthales mitogenomes, yet six mitogenomes of Diaporthe species exhibited identical gene arrangements. Notably, similar gene arrangements were observed in different genera, such as Cryphonectria and Chrysoporthe, indicating a shared ancestry. Furthermore, a gene rearrangement involving the displacement of the atp9 gene was found in four different genera, including Diaporthe, Juglanconis, Cryphonectria, and Chrysoporthe (Fig. 7). In contrast to the Juglanconis genus, Ophiognomonia clavigignenti-juglandacearum displayed a distinct set of gene arrangements possibly inherited from unique ancestors. Previous studies suggested that the presence of repetitive DNA elements in intergenic regions played a significant role in mitochondrial gene rearrangements (Aguileta et al. 2014; Li et al. 2018a). However, despite the detection of numerous repeat elements in the six Diaporthe mitogenomes with content ranging from 1.41% to 10.99% (Suppl. material 1: table S7), no gene rearrangement was observed, consistent with findings in Bipolaris (Song et al. 2024). Therefore, factors beyond repetitive sequences may influence the gene rearrangement process in fungal mitogenomes. The mitogenomes of Diaporthe, Juglanconis, Cryphonectria and Chrysoporthe­porthe genera serve as typical examples offering valuable insights for further understanding the mechanism of mitochondrial gene rearrangement in fungi.

Diaporthe species are widely dispersed and can infect a variety of plant hosts, leading to significant economic losses (Bai et al. 2015; Zhao et al. 2022; Gao et al. 2024). Morphological variation within Diaporthe species has repeatedly been shown to be insufficient for species identification and defining novel species, as many closely related species or species complexes in the Diaporthe genus can be easily confused. Incorporating molecular data along with morphology is necessary to accurately describe species in the genus (Gao et al. 2017; Guo et al. 2020; Monkai et al. 2023). The introduction of molecular markers has advanced the taxonomy, population genetics, and biogeography of the genus Diaporthe (Gomes et al. 2013; Norphanphoun et al. 2022). But so far, it has been still often a hard work to distinguish the taxa of Diaporthe species accurately. In recent years, mitogenomes have been increasingly utilized in phylogeny and population study of plants, animals, and some kinds of fungi (Aguileta et al. 2014; Wang et al. 2020b; Song et al. 2024). In most cases, mitochondrial advantages over nuclear genomes, such as uniparental inheritance and accelerated evolutionary rates (Urantowka et al. 2017), have made mitogenomes a powerful tool in studying population genetics, taxonomy, and genetics in fungi (Wang et al. 2018; Johri et al. 2019; Ma et al. 2022). In this study, we constructed a highly supported phylogenetic tree containing 98 Ascomycota species based on the combined mitochondrial gene set and BI and ML analytical methods (Suppl. material 1: table S9 and Fig. 8). All these selected species were well gathered or divided into different independent clades and subclades, each of which exactly corresponded to one fungal taxa (such as class and order). The six Diaporthe species were observed to be closely related to species of the genera Juglanconis, Ophiognomonia, Cryphonectria, and Chrysoporthe, which was consistent with the previous analyses of multigene phylogeny based on five nuclear loci (Fan et al. 2018; Wu et al. 2019). Concluding, phylogenetic inference based on the combined mitochondrial gene set suggested that mitogenomes display a similar resolution power to classic phylogenetic analysis using nuclear DNA, potentially allowing promising applications for species delimitation within and between closely related genera of the genus Diaporthe and beyond in the future. However, the number of known mitogenomes in Diaporthe is still limited, considering the hundreds of described Diaporthe species. Further sequencing of the mitogenomes of closely related species in the genus Diaporthe is necessary to better understand the phylogenetic relationships and mechanisms of genetic variation within the genus.

The authors have declared that no competing interests exist.

No ethical statement was reported.

All the fungal strains used in this study have been legally obtained, respecting the Convention on Biological Diversity (Rio Convention).

This study was supported by National Natural Science Foundation of China (32400008), Natural Science Foundation of Henan (232300420264 & 242300420481), Xinjiang Apple Industry Technology System-Disease Prevention and control and disaster prevention post scientist project and Project of Fund for Stable Support to Agricultural Sci-Tech Renovation (XJLGCYJSTX04-2024-11) and Science and technology project of Henan Province (242102111081).

Conceived and designed experiments: M.Z., Q.M., and S.G. Analyzed the data: S.X., Q.M., X.M., H.W., R.Z and J.L. Wrote the paper: S.X., Q.M., and M.Z. Revised the manuscript: M.Z., Y.G., M.L., H.L. and Q.L. Project management: S.X. and Q.M., All authors read and approved the final manuscript.

Shunpei Xie https://orcid.org/0009-0009-9079-7829

Rui Zang https://orcid.org/0000-0001-8915-9250

Miao Liu https://orcid.org/0000-0003-3223-6010

Qingzhou Ma https://orcid.org/0000-0003-3716-9654

Yashuang Guo https://orcid.org/0000-0003-1299-6207

Meng Zhang https://orcid.org/0000-0003-1941-1136

All of the data that support the findings of this study are available in the main text or Supplementary Information.