The mitochondrial genome of the terrestrial carnivorous plant Utricularia reniformis (Lentibulariaceae): Structure, comparative analysis and evolutionary landmarks

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Abstract

The carnivorous plants of the family Lentibulariaceae have attained recent attention not only because of their interesting lifestyle, but also because of their dynamic nuclear genome size. Lentibulariaceae genomes span an order of magnitude and include species with the smallest genomes in angiosperms, making them a powerful system to study the mechanisms of genome expansion and contraction. However, little is known about mitochondrial DNA (mtDNA) sequences of this family, and the evolutionary forces that shape this organellar genome. Here we report the sequencing and assembly of the complete mtDNA from the endemic terrestrial Brazilian species Utricularia reniformis. The 857,234bp master circle mitochondrial genome encodes 70 transcriptionaly active genes (42 protein-coding, 25 tRNAs and 3 rRNAs), covering up to 7% of the mtDNA. A ltrA-like protein related to splicing and mobility and a LAGLIDADG homing endonuclease have been identified in intronic regions, suggesting particular mechanisms of genome maintenance. RNA-seq analysis identified properties with putative diverse and important roles in genome regulation and evolution: 1) 672kbp (78%) of the mtDNA is covered by full-length reads; 2) most of the 243kbp intergenic regions exhibit transcripts; and 3) at least 69 novel RNA editing sites in the protein-coding genes. Additional genomic features are hypothetical ORFs (48%), chloroplast insertions, including truncated plastid genes that have been lost from the chloroplast DNA (5%), repeats (5%), relics of transposable elements mostly related to LTR retrotransposons (5%), and truncated mitovirus sequences (0.4%). Phylogenetic analysis based on 32 different Lamiales mitochondrial genomes corroborate that Lentibulariaceae is a monophyletic group. In summary, the U. reniformis mtDNA represents the eighth largest plant mtDNA described to date, shedding light on the genomic trends and evolutionary characteristics and phylogenetic history of the family Lentibulariaceae.

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Reconstructing mitochondrial genomes directly from genomic next-generation sequencing reads—a baiting and iterative mapping approach

Christoph Hahn, Lutz Bachmann, Bastien Chevreux (2013)

We present an in silico approach for the reconstruction of complete mitochondrial genomes of non-model organisms directly from next-generation sequencing (NGS) data—mitochondrial baiting and iterative mapping (MITObim). The method is straightforward even if only (i) distantly related mitochondrial genomes or (ii) mitochondrial barcode sequences are available as starting-reference sequences or seeds, respectively. We demonstrate the efficiency of the approach in case studies using real NGS data sets of the two monogenean ectoparasites species Gyrodactylus thymalli and Gyrodactylus derjavinoides including their respective teleost hosts European grayling (Thymallus thymallus) and Rainbow trout (Oncorhynchus mykiss). MITObim appeared superior to existing tools in terms of accuracy, runtime and memory requirements and fully automatically recovered mitochondrial genomes exceeding 99.5% accuracy from total genomic DNA derived NGS data sets in <24 h using a standard desktop computer. The approach overcomes the limitations of traditional strategies for obtaining mitochondrial genomes for species with little or no mitochondrial sequence information at hand and represents a fast and highly efficient in silico alternative to laborious conventional strategies relying on initial long-range PCR. We furthermore demonstrate the applicability of MITObim for metagenomic/pooled data sets using simulated data. MITObim is an easy to use tool even for biologists with modest bioinformatics experience. The software is made available as open source pipeline under the MIT license at https://github.com/chrishah/MITObim.

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OrganellarGenomeDRAW—a suite of tools for generating physical maps of plastid and mitochondrial genomes and visualizing expression data sets

Marc Lohse, Oliver Drechsel, Sabine Kahlau … (2013)

Mitochondria and plastids (chloroplasts) are cell organelles of endosymbiotic origin that possess their own genetic information. Most organellar DNAs map as circular double-stranded genomes. Across the eukaryotic kingdom, organellar genomes display great size variation, ranging from ∼15 to 20 kb (the size of the mitochondrial genome in most animals) to >10 Mb (the size of the mitochondrial genome in some lineages of flowering plants). We have developed OrganellarGenomeDraw (OGDRAW), a suite of software tools that enable users to create high-quality visual representations of both circular and linear annotated genome sequences provided as GenBank files or accession numbers. Although all types of DNA sequences are accepted as input, the software has been specifically optimized to properly depict features of organellar genomes. A recent extension facilitates the plotting of quantitative gene expression data, such as transcript or protein abundance data, directly onto the genome map. OGDRAW has already become widely used and is available as a free web tool (http://ogdraw.mpimp-golm.mpg.de/). The core processing components can be downloaded as a Perl module, thus also allowing for convenient integration into custom processing pipelines.

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Rapid Evolution of Enormous, Multichromosomal Genomes in Flowering Plant Mitochondria with Exceptionally High Mutation Rates

Daniel Sloan, Andrew J Alverson, John P. Chuckalovcak … (2012)

Introduction Explaining the origins of variation in genome size and complexity has become the defining challenge for the field of molecular evolution in the genomic era. Historically, numerous evolutionary models have been developed, involving mechanisms such as insertion and deletion (indel) bias [1],[2], selfish element proliferation [3],[4], and natural selection on cell size [5], replication rate [6], and evolvability [7]. In recent years, a body of theory known as the mutational burden hypothesis (MBH) has emerged as a potentially unifying explanatory framework rooted in the principles of population genetics and the basic evolutionary processes of mutation and genetic drift [8],[9]. The MBH posits that noncoding elements are generally deleterious but proliferate nonadaptively when small effective population sizes reduce the effectiveness of selection relative to genetic drift, offering an explanation for why noncoding sequences are so abundant in large multicellular eukaryotes. This hypothesis is based on the idea that noncoding elements impose a selective cost associated with the increased chance of mutations disrupting an essential genome function (e.g., alteration of a conserved sequence required for intron splicing) or generating a novel deleterious feature (e.g., an improper transcription-factor binding site in an intergenic region). The MBH has potentially sweeping explanatory power, but some of its tenets are controversial [10]–[13], and its generality as a mechanism of genome evolution remains uncertain [14]–[21]. Mitochondrial genomes display striking diversity in size and complexity [22],[23], reflecting patterns of variation in genome architecture observed more broadly across the tree of life [9],[24]. For example, in contrast to the small (typically 14–20 kb) and streamlined genomes found in most animal mitochondria [25], seed plant mitochondrial genomes are very large (200–2,900 kb), containing introns and abundant intergenic sequences [26]–[28]. Plant mitochondrial genomes are also typically characterized by extremely low point mutation rates, further distinguishing them from their fast-evolving animal counterparts [29]–[31]. The observed disparity in mitochondrial mutation rates across eukaryotes motivated the hypothesis that mutation rates are a major determinant of variation in organelle genome architecture [32]. This argument is a direct extension of the MBH and is based on the premise that the probability of mutational disruption of noncoding elements (which is equivalent to the selective cost associated with maintaining those elements) is directly proportional to the mutation rate. Therefore, genomes with elevated mutation rates are predicted to experience more intense selection for genomic reduction [32]. The discovery that some angiosperms have greatly accelerated mitochondrial mutation rates, sometimes orders of magnitude greater than closely related species [33]–[35], presents an opportunity to test the prediction that high mutation rate environments select for reduced and streamlined genomes. In particular, several species in the genus Silene (Caryophyllaceae) have experienced dramatic increases in mitochondrial mutation rates within just the last 5–10 Myr, while other members of this genus have maintained their ancestrally low rates [35]–[37]. We compared complete mitochondrial genome sequences from four Silene species with very different mutation rates and found that accelerated mutation rates have indeed been associated with dramatic changes in genome size and complexity. However, the direction of these changes is not always consistent with the predictions from existing theory. We discuss the implications of the unprecedented mitochondrial genome diversity found within Silene and possible alternative explanations for the rapid genome evolution in this genus. Results Variation in Mitochondrial Substitution and Indel Rates within Silene Sequencing of purified mitochondrial DNA (mtDNA) from three Silene species generated complete genome assemblies for S. noctiflora and S. vulgaris and a high quality draft assembly for S. conica. We also included the previously published mitochondrial genome of S. latifolia in our analyses [38]. The genomic data extend previous results [35]–[37] by showing that S. noctiflora and S. conica have experienced massive accelerations in nucleotide substitution rates (Figure 1) across all protein genes (Figure 2) with correlated increases in the frequency of both insertions and deletions (Figure 3). 10.1371/journal.pbio.1001241.g001 Figure 1 Sequence divergence, genome size, and gene content in seed plant mitochondria. Branch lengths are scaled to the number of synonymous nucleotide substitution per site (d S) on the basis of an analysis of all shared protein genes. Genome size ranges are reported for species with multiple sequences available. Gene counts exclude duplicates and putative pseudogenes. 10.1371/journal.pbio.1001241.g002 Figure 2 Levels of synonymous (d S) and nonsynonymous (d N) sequence divergence in terms of substitutions per site for protein genes in Silene mitochondrial genomes. Estimates were generated using B. vulgaris and A. thaliana as outgroups. 10.1371/journal.pbio.1001241.g003 Figure 3 Number of indels in mitochondrial protein genes and introns that are unique to each of the four Silene species. Massive Mitochondrial Genome Expansion in High Mutation-Rate Species Contrary to the prediction of genomic streamlining in response to high mutation rate, the fast-evolving mitochondrial genomes of S. noctiflora and S. conica have experienced unprecedented expansions, resulting in sizes of 6.7 Mb and 11.3 Mb, respectively. In contrast, the more typical slowly evolving mitochondrial genomes of S. vulgaris (0.43 Mb) and particularly S. latifolia (0.25 Mb) are on the lower end of the angiosperm size range. Thus, Silene mitochondrial genomes have diverged more than 40-fold in size in just the past few million years. The genomic expansion in S. noctiflora and S. conica does not reflect detectable increases in gene or intron content. Although these genomes contain duplicate copies of some genes (particularly rRNA genes; Table S1), they possess fewer unique genes than other angiosperm mitochondrial genomes (Figures 1 and 4). Notably, the S. conica and S. noctiflora mitochondrial genomes contain only two or three identifiable tRNA genes, which is far fewer than most angiosperms and even less than the already reduced tRNA gene content of S. latifolia and S. vulgaris (Figures 1 and 4) [38]. The four Silene genomes have nearly identical sets of introns (Table 1). With the exception of additional intron copies associated with gene duplications, there were no intron gains among the four Silene species and only one observed intron loss (the third intron of nad4 in S. noctiflora). Interestingly, in contrast to the overall pattern of genome expansion in S. noctiflora and S. conica, average intron lengths in the expanded S. noctiflora and S. conica genomes are actually ∼10%–15% shorter than in their congeners (Figure S1). 10.1371/journal.pbio.1001241.g004 Figure 4 Protein and RNA gene content in sequenced seed plant mitochondrial genomes. Dark shading indicates the presence of an intact reading frame or folding structure, whereas light shading indicates the presence of only a putative pseudogene. The numbers at the bottom of each group indicate the total number of intact genes for that species. Note that the ccmFc gene, which is universally present in all other seed plants surveyed to date [104], is classified as a pseudogene in S. conica. It has experienced numerous structural mutations in this lineage, including multiple frame shifts in the second exon that introduce premature stop codons. However, cDNA sequencing confirmed that this gene is transcribed, spliced, and RNA edited in S. conica (unpublished data), so it is possible that the gene is still functional in its truncated form. In some cases, the presence of an intact gene may not indicate functionality. This is particularly true for tRNA genes embedded within recently transferred regions of plastid DNA [20],[105]. For example, the trnN(guu) and trnR(acg) genes in S. vulgaris may not be functional, as they are within a 2.6-kb region that appears to have been recently transferred from the plastid genome (on the basis of its perfect sequence identity with the exception of a single 18-bp deletion). These two tRNA genes are not orthologous to the plastid-derived copies of trnN(guu) and trnR(acg) in other seed plant mitochondria. Intron-containing plastid-derived tRNA genes such as trnA(ugc) in Bambusa, trnV(uac) in Cycas, trnK(uuu) in Vitis, and trnI(gau) in Zea are also unlikely to be functional. In Cycas, the trnL(uaa), trnP(ugg), trnQ(uug), trnR(ucu), and trnV(uac)- Ψ genes are classified on the basis of sequence homology to other land plant tRNAs even though their genomically encoded anticodons differ (CAA, CGG, CUG, CCU, and CAC, respectively). It is possible that these anticodons undergo C-to-U RNA editing to restore the ancestral codon as has been observed in other vascular plants [106],[107]. Plastid-derived tRNAs with substitutions in their anticodons, such as Citrullus trnT(ugu) and Silene latifolia trnP(ugg), are also classified (as pseudogenes) on the basis of homology. 10.1371/journal.pbio.1001241.t001 Table 1 Summary of four Silene mitochondrial genomes. Genome Characteristics S. latifolia S. vulgaris S. noctiflora S. conica Genome size in kb 253 427 6,728 11,318 Circular chromosomes 1 4 59 128+ Percent G+C content 42.6 41.8 40.8 43.1 Protein genes a 25 25 26 25 tRNA genes a 9 6 3 2 Native 6 3 3 2 Plastid-derived 3 3b 0 0 rRNA genes a 3 3 3 3 Introns a 19 19 18 19 cis-spliced 13 13 12 13 trans-spliced 6 6 6 6 Genic gontent in kb (percent coverage) a 51 (20.3) 48 (11.2) 72 (1.1) 77 (0.7) Exonic 34 (13.6) 31 (7.2) 58 (0.9) 57 (0.5) Intronicc 17 (6.7) 17 (4.0) 14 (0.2) 20 (0.2) Intergenic content in kb (percent coverage) 202 (79.7) 379 (88.8) 6,656 (98.9) 11,241 (99.3) Plastid-derived 2 (1.0) 10 (2.3) 17 (0.3) 35 (0.3) Conserved with other plant mtDNAd 95 (37.7) 73 (17.0) 843 (12.5) 834 (7.4) Conserved with GenBank nr/nte 5 (2.0) 3 (0.7) 20 (0.3) 16 (0.1) Uncharacterized 99 (39.0) 294 (68.9) 5,776 (85.9) 10,356 (91.5) Repetitive content in kb (percent coverage) 17 (6.7) 80 (18.8) 735 (10.9) 4,621 (40.8) Large repeats: >1 kb 12 (4.9) 57 (13.3) 110 (1.6) 1,121 (9.9) Small repeats: ≤1 kb 5 (1.8) 23 (5.5) 625 (9.3) 3,500 (30.9) RNA editing sites 287 271f 189 182f Non-Syn. substitution rate (×10−9/y) 0.08 0.35 8.90 9.98 Syn. substitution rate (×10−9/y) 0.70 1.60 58.17 68.22 d N/ d S 0.12 0.22 0.15 0.15 a Duplicate genes/introns are included in length and coverage statistics but excluded from reported counts. b Two of the S. vulgaris plastid-derived tRNA genes may not be functional (Figure 4). c Intron lengths only include cis-spliced introns. d Excludes regions of plastid-origin. e Excludes regions of plastid-origin and regions conserved in other plant mitochondrial genomes. f Predicted. Intergenic sequences account for 99% of the bloated mitochondrial genomes in S. noctiflora and S. conica. As in other vascular plants [28],[39], the intergenic regions of all four Silene mitochondrial genomes contain sequences of both nuclear and plastid (chloroplast) origin. Although the expanded mitochondrial genomes of S. noctiflora and S. conica contain more of this “promiscuous” DNA than their smaller Silene counterparts (Table 1), contributions from these sources do not scale proportionally with the increases in genome size and constitute less than 1% of the intergenic content in both species (Table 1). A larger fraction of the intergenic regions in each of these two genomes exhibit similarity to sequences in other plant mitochondrial genomes (Table 1), but most of this sequence (>650 kb) is only shared between S. noctiflora and S. conica and not with any other angiosperms. Overall, >85% of the voluminous intergenic sequence in these two species lacks detectable homology with any of the nuclear, plastid, or mitochondrial sequences available in the GenBank nr/nt database. Repeated sequences constitute a variable and often large component of seed plant mitochondrial genomes [40], and Silene species are noteworthy in both respects (Figures 5, S2, and S3; Table 1). The S. conica mitochondrial genome contains a remarkable 4.6 Mb of dispersed repeats, which is more than any other sequenced plant mitochondrial genome in both absolute and percentage (40.8%) terms [40]. The largest repeats are >80 kb in size, but the bulk of the repetitive content consists of an enormous number of small, imperfect, and often partially overlapping repeats (Figures 5, S2, and S3). In contrast, repeat sequences make up just 6.7%–18.8% of the other three Silene mitochondrial genomes. 10.1371/journal.pbio.1001241.g005 Figure 5 Size distribution of repetitive content by the number of repeat pairs (left column) and total repeat length (right column). Both datasets are based on all repeat pairs identified with BLAST by searching each genome against itself. Note that this method is different than counting individual repeat copies, which cannot be unambiguously identified when repeats exist in numerous partially overlapping copies, as they do in these genomes. For example, a repeat with four copies would be associated with six unique repeat pairs. Because of the enormous number of multicopy, overlapping repeats in S. conica, the total length of repeat pairs exceeds the size of the genome even though more than half of it is single-copy. For these same reasons, the distribution of repeat lengths in this figure differs from the repeat coverage statistics reported in Table 1, which consider what fraction of the genome is covered by repeats but not the total number of repeat pairs. The reported 50% coverage threshold represents the median of the total repeat length distribution. Multichromosomal Mitochondrial Genome Structures Silene noctiflora and S. conica have also evolved extraordinary mitochondrial genome structures. Although the relationship between genome maps and in vivo physical structure remains uncertain for angiosperm mtDNAs [41], the entire sequence content of the genome typically can be mapped as a single “master circle,” which can be subdivided into a collection of “subgenomic circles” that arise via high-frequency recombination between large direct repeats (Figure S4A) [42],[43]. This model applies to S. latifolia [38], whereas the S. vulgaris genome assembles into four circular-mapping chromosomes, with the largest (394 kb) comprising most (92%) of the genome and containing numerous repeats inferred to undergo active recombination on the basis of their association with alternative rearranged genome conformations (Figure S4). Two of the three smaller mitochondrial chromosomes in S. vulgaris share recombinationally active repeats with the large chromosome, but the majority of sequencing reads support the smaller subgenomic conformations (see Materials and Methods and Figure S4). In contrast, the smallest of the four S. vulgaris chromosomes appears to be almost completely autonomous. It does not share any repeats longer than 100 bp with the rest of the genome, and in the case of all shorter repeats shared between the smallest chromosome and the main chromosome, >99.5% of sequencing read-pairs support the smaller subgenomic conformation. While the presence of this small chromosome is itself unusual for plant mtDNAs, far more extreme are the S. noctiflora and S. conica mitochondrial genomes, each of which assembled into dozens of mostly autonomous and relatively small, circular-mapping chromosomes. The S. noctiflora mitochondrial genome consists of 59 circular-mapping chromosomes ranging from 66 to 192 kb in size (Table S2). Many of these do not share any large (>1 kb) repeats with other chromosomes. Even when S. noctiflora chromosomes do share large repeats (up to 6.3 kb), the clear majority of paired-end sequencing reads (>90% in all cases) support the conformation consisting of two smaller circles rather than a single combined circle. Although the extremely repetitive nature of the S. conica mitochondrial genome precluded complete genome assembly, its structural organization is similar to that of S. noctiflora. The vast majority (98.2%) of sequence content assembled into 128 circular-mapping chromosomes ranging from 44 to 163 kb in size (Table S2). Most of these chromosomes share only short repeats with other parts of the genome. The number of sequencing reads that cover a given position in a shotgun genome assembly (i.e., the read depth) can be used to estimate the relative abundance of different sequences. The difference in average read depth between the chromosomes with the highest and lowest coverage was only 1.7-fold in S. noctiflora and only 3.1-fold in S. conica (after excluding repetitive regions), indicating that the abundance of the numerous chromosomes was relatively even in both genomes. The different chromosomes also exhibited a high degree of similarity in GC content within each genome (Table S2). Assembly of repetitive genomes is inherently complicated, and this is particularly relevant to the identification of genomic subcircles because tandem duplications within a larger chromosome can misassemble as subcircles. However, such assembly errors leave clear signatures, including dramatic variation in read depth and conflicting read-pairs associated with the boundary between tandem repeats and flanking regions. The absence of such patterns in our dataset indicates that the assembled circles are not an artifact of tandem repeats within larger chromosomes. Nevertheless, it is possible, particularly in the draft assembly of S. conica mitochondrial genome, that some repeat pairs have been “collapsed” into single sequences, leaving open the possibility that the reported 11.3 Mb genome size for S. conica is a slight underestimate. Repeat-Mediated Recombinational Activity Sequencing of the S. latifolia mitochondrial genome showed that it contains a six-copy 1.4-kb repeat that is highly recombinationally active with physical cross-overs between repeat copies generating a suite of rearranged genome conformations [38]. Southern blot analysis confirmed that the many alternative genome conformations occur in roughly equivalent frequencies in S. latifolia [38]. Paired-end sequencing reads can also be used to quantify the relative abundance of alternative genome conformations (see Materials and Methods and Figure S4), and our 454 data suggest a comparably high level of repeat-mediated recombinational activity for the largest repeats in the S. vulgaris mitochondrial genome (Figure 6A). The relative frequency of recombinant genome conformations increases with repeat size, and all surveyed repeats longer than 100 bp exhibit evidence of a history of recombination. The two largest surveyed pairs of repeated sequences (0.9 and 3.0 kb) in the S. vulgaris genome each appear to be at or near a 50∶50 level of alternative genome conformations (Figure 6A). 10.1371/journal.pbio.1001241.g006 Figure 6 Repeat-mediated recombinational activity in the low mutation rate S. latifolia and S. vulgaris mitochondrial genomes (A) and the fast-evolving S. noctiflora and S. conica mitochondrial genomes (B). Each point represents a pair of repeats, and its position on the y-axis denotes the proportion of recombinant genome conformations detected with paired-end 454 reads. The dashed lines indicate the level at which equal frequencies of read pairs support recombinant and nonrecombinant conformations. The S. latifolia mitochondrial genome was not sequenced with 454 paired-end reads, but Southern blot hybridizations indicated that alternative genome conformations associated with its six-copy 1.4-kb repeat exist at roughly equivalent frequencies [38], as indicated by the large X. The rapidly evolving mitochondrial genomes of S. noctiflora and S. conica exhibit reduced frequencies of recombinant genome conformations compared to other Silene genomes (Figure 6B) and all other angiosperm mitochondrial repeats for which recombinational activity has been assessed. Even the largest repeats in the S. noctiflora genome (up to 6.3 kb) are associated with only a small minority of recombinant products (Figure 6B). The largest repeats in the S. conica genome (up to 87 kb) far exceed our paired-end library span and therefore cannot be analyzed for recombinational activity, but analysis of the shorter repeats suggests that the genome has experienced a similar shift in the relationship between repeat length and the frequency of recombinant products (Figure 6B). Recombinational activity (including gene conversion) is expected to homogenize copies of repeated sequences throughout the genome. Therefore, the dramatic increase in the proportion of divergent pairs of repeated sequences within the mitochondrial genomes of S. noctiflora and S. conica (Figures 7 and S5) is consistent with a reduction in recombinational activity in these species, though the existence of divergent repeats could also result from the increased mutation rate in these species or a reduced probability of gene conversion events between physically disparate repeat copies in expanded genomes. 10.1371/journal.pbio.1001241.g007 Figure 7 Distribution of percent sequence identity between pairs of repeats detected by BLAST. Only repeat pairs greater than 300 bp in length were used to calculate these distributions. Maternal Inheritance of Silene Mitochondrial Genomes The coexistence of maternally and paternally derived mitochondrial genomes in a heteroplasmic state within the same individual or maternal family would introduce complications for genome sequencing and assembly. Therefore, we looked for evidence of heteroplasmy and nonmaternal inheritance in the families used in this study. S. vulgaris has been the subject of extensive investigation into the patterns of mitochondrial genome inheritance [44]–[47]. These studies have found that mtDNA transmission is predominantly maternal in S. vulgaris, with a low frequency of biparental inheritance or paternal “leakage.” Because of this evidence, the S. vulgaris family used for genome sequencing was chosen, in part, because the maternal source plant had previously been screened with two highly polymorphic mitochondrial markers and revealed no evidence of heteroplasmy [46]. Although similarly intensive investigations of mtDNA inheritance have not been performed in other Silene species, we found evidence of maternal transmission in S. latifolia, S. noctiflora, and S. conica. An analysis of cleaved amplified polymorphic sequences (CAPS) showed that all progeny (16–48 per species) from controlled greenhouse crosses inherited the maternal variant of a SNP. Mitochondrial inheritance therefore appears to be at least predominantly maternal in all four Silene species, making it unlikely that genome assembly complications arising from biparental inheritance and heteroplasmy can explain the observed differences in mitochondrial genome size and complexity among Silene species. Intraspecific Nucleotide Polymorphism S. noctiflora and S. conica do not show the proportional increases in mitochondrial nucleotide diversity that would be expected on the basis of their accelerated mutation rates (even after accounting for the approximately 2-fold differences in generation times across the four Silene species [48]), suggesting a recent history of lower effective population size (N e) than their congeners and/or a recent reversion to lower mitochondrial mutation rates as observed in other accelerated angiosperm lineages [33],[34]. In S. conica, there is less than a 10-fold increase in mitochondrial synonymous nucleotide diversity relative to the more slowly evolving Silene species, and S. noctiflora exhibits no sequence variation whatsoever across our sample of mitochondrial, plastid, and nuclear loci (Table S3) (see also [49]). Discussion The Mysterious Origins of Expanded Intergenic Regions in Plant mtDNA The dramatic expansion of intergenic content in the mtDNA of S. noctiflora and S. conica has resulted in mitochondrial genomes that are larger than most bacterial genomes (Figure 8) and even some nuclear genomes [50]. These enormous genomes add to the long-standing mystery regarding the origins of intergenic sequences in plant mtDNA [28]. 10.1371/journal.pbio.1001241.g008 Figure 8 Silene mitochondrial genome sizes relative to all sequenced mitochondrial and eubacterial genomes from the National Center for Biotechnology Information (NCBI) Genome database. It is possible that a significant portion of this intergenic content is derived from the nuclear genome, for which sequence data are still limited in Silene. However, by comparing the mitochondrial genomes against a large set of cDNA sequences derived from a recent transcriptome project in S. vulgaris [51], we detected similarity for only a trivial amount ( 3 kb) repeats and to quantify the frequency of alternative genome conformations resulting from recombination among repeat copies (see below). For the smaller, S. vulgaris mitochondrial genome, a single quarter-plate run produced very high coverage (>80×). Preliminary analyses suggested use of the entire dataset increased fragmentation in the assembly. Therefore, a random set of sequence reads totaling 25 Mb was selected for initial assembly. The full S. vulgaris dataset was used for subsequent quantification of alternative genome conformations. For each genome, the 454 sequence reads were assembled with Roche's GS de novo Assembler v2.3 (“Newbler”) using default settings. The resulting assemblies produced average read depths of 20×, 25×, and 42× for the S. conica, S. noctiflora, and S. vulgaris mitochondrial genomes, respectively. Although the assemblies contained few, if any, gaps or low-coverage regions, they were highly fragmented because of the repetitive and recombinational nature of these genomes (Figures 5 and 6). The assemblies also contained contigs from contaminating nuclear, plastid, and viral DNA. True mitochondrial contigs were distinguished on the basis of read depth and connectivity to other contigs in the assembly, which was inferred from two types of data: (1) paired-end reads that mapped to two different contigs and (2) single reads that were split by the assembler and assigned to the ends of two different contigs. On the basis of these data, contigs were organized into “subgenomes,” each of which represented either a closed circular assembly or a single-copy assembly flanked on either side by recombinationally active repeats. Each of these subgenomic contig groups was then reassembled using a custom set of Perl and BASH scripts that identified all sequencing reads uniquely associated with the corresponding contigs and ran a new assembly using only those reads. The resulting subgenomic assemblies were then manually edited and combined as necessary with the aid of Consed v17.0 [85]. The largest repeats in both the S. conica and S. vulgaris mitochondrial genomes exceed the 3-kb span size of their respective paired-end libraries. Therefore, the relationships between the single-copy regions flanking these large repeats are ambiguous. These ambiguities were tentatively resolved on the basis of the pattern observed in smaller repeats within each genome (Figure 6). On the basis of the high level of recombinational activity among smaller repeats in S. vulgaris, we assumed that large repeats also have high recombinational activity. Therefore, we assembled the majority of the S. vulgaris genome content into a single chromosome, analogous to the “master circle” typically reported for plant mitochondrial genomes. This large chromosome contains numerous recombinationally active repeats, and, as discussed previously [38], the arrangement of repeats and single-copy regions within this chromosome should be considered only one of many possible alternative representations. We also identified three small circular-mapping structures that were not included in the main assembly. One of these circles (Chromosome 4) shows almost no evidence of recombinational activity with the rest of the genome, while the other two do share repeats that appear to recombine frequently with the main chromosome. However, in both of these cases, the repeats are small ( 90% in all cases in S. noctiflora and the vast majority of cases in S. conica; Figure 6) support minimally sized circular conformations rather than larger combined circles. Therefore, for assembly ambiguities associated with repeats exceeding the 3-kb paired-end library span in S. conica, it was assumed that minimally sized circles predominate over larger combined conformations. Mapping Illumina Sequence Data To correct base-calling errors including insertion and deletion errors known to be associated with long single-nucleotide repeats (i.e., homopolymers) in 454 sequence data, we mapped Illumina sequence data onto the completed mitochondrial genome assemblies for each species. After removal of multiplex barcodes and quality trimming, Illumina sequencing yielded average read lengths between 53 and 69 bp with a total of 398, 326, and 168 Mb of sequence data for S. noctiflora, S. conica, and S. vulgaris, respectively. Paired-end read mapping was performed with SOAP v2.20 [86] with the following parameters: m 100, x 900, g 3, r 2. A set of custom Perl scripts were used to call SOAP, parse the resulting output, and modify the genome sequence on the basis of well-supported sequence conflicts. These scripts were run recursively until additional iterations did not produce any further improvement to the sequence. For both S. vulgaris and S. noctiflora, Illumina mapping provided high-depth (>10×) coverage for essentially the entire genome (>99.9%). This process identified 55 sequence corrections in S. vulgaris and 1,734 corrections in S. noctiflora, the vast majority of which were associated with homopolymer runs. In contrast, because of the larger size and repetitive complexity of the S. conica mitochondrial genome, more than 10% of the sequence had coverage levels below 10×. Furthermore, the recursive mapping approach described above failed to converge for numerous regions in the genome, indicating low confidence in many of the sequence corrections indicated by the Illumina data. To avoid incorporating false sequence changes, we did not use the Illumina data to perform genome-wide corrections in S. conica. Consequently, the reported genome sequence likely contains some errors associated with homopolymer runs. We did, however, use the Illumina data to verify basecalls in S. conica coding genes and introns, including cases of frameshift mutations. Gene Annotation and Characterization of Intergenic Content The annotation of protein, rRNA, and tRNA genes was performed using a combination of local BLAST [87] and tRNAscan [88] as described previously [20]. Annotated genome sequences were deposited in GenBank (Table S2). To identify sequence of plastid origin in the Silene mitochondrial genomes, each genome was searched against a database of seed plant plastid genomes, using NCBI-BLASTN (v2.2.24+) with the following parameter settings: dust no, gapopen 8, gapextend 6, penalty -4, reward 5, word_size 7. Only hits with a raw score of at least 250 were considered. These hits were subsequently filtered to exclude matches involving mitochondrial protein and rRNA genes known to have ancient plastid homologs (e.g., mitochondrial atp1 and plastid atpA [89]). We also excluded hits with very high AT contents (>72%), because we found these to be almost exclusively false positives resulting from the use of sensitive BLAST parameters. To identify intergenic sequence conserved in other plant mitochondrial genomes, all intergenic regions (excluding those of plastid origin) were searched against a database of all sequenced seed plant mitochondrial genomes using NCBI-BLASTN (v2.2.24+) and the following search parameters: task blastn, dust no, gapopen 5, gapextend 2, reward 2, penalty -3, word_size 9. All hits with a raw score of at least 70 were considered homologous. Note that we included all sequences from “empty” chromosomes in the intergenic category even though such sequences are not technically bounded by genes on either side. To identify additional conserved sequences (particularly ones of nuclear origin), the remaining intergenic regions (i.e., excluding annotated genes, plastid-derived sequence, and regions conserved with other plant mitochondrial genomes) were searched against the GenBank nr and nt databases (release date 12/15/2010) using NCBI-BLASTX and BLASTN (v2.2.24+). Default settings were used for BLASTX, whereas the BLASTN search parameters were as follows: dust yes, gapopen 5, gapextend 2, reward 2, penalty -3, word_size 9. All BLASTX hits with a raw score of at least 140 and all BLASTN hits with a raw score of 70 or above were considered homologous. Searches with these same parameters were also conducted against a set of assembled cDNA sequences from a recent S. vulgaris transcriptome project [51]. Characterization of Repetitive Content Tandem repeats in each Silene mitochondrial genome were identified with Tandem Repeat Finder v4.04 [90], but these represented a negligible fraction of total repeat content in each genome and are not reported separately. Dispersed repeats were identified by searching each genome against itself with NCBI-BLASTN (v2.2.24+) using default parameter settings. All hits with a raw score of at least 30 were considered repeats. The shortest possible sequence that can satisfy this criterion is a perfect 30-bp repeat, but longer sequences with less than 100% sequence identity can also be identified by this method. Finally, Vmatch (http://www.vmatch.de) was used to precisely define the boundaries of all repeats with 100% sequence identity. Analysis of Recombinational Activity We used paired-end reads from 454 sequencing to quantify the relative abundance of alternative genome conformations associated with repeat-mediated recombination (Figure S4). In the absence of any recombination or alternative genome conformations, 454 read pairs should map to positions in the genome that are consistent with the size span of the sequencing library (∼3 or 12 kb in this case). However, the presence of genomic rearrangements will result in read pairs that are inconsistent with the reported genome conformation (Figure S4). Therefore, for each pair of repeated sequences in a genome, we quantified the number of 454 read pairs that are inconsistent with the reported genome assembly but are consistent with either of the predicted products of recombination between the repeats. This number was then compared against the total number of consistent read pairs in the genome that span one of the two repeat copies to determine the relative abundance of the recombinant products. To perform this analysis, 454 paired-end reads were mapped on the corresponding genome sequence using Roche's GS Reference Mapper v2.3 software with default parameters. For S. noctiflora, only reads from the 12-kb paired-end library were used. The resulting output was filtered to exclude duplicate read pairs with identical start positions for both the left and right sequences, as these were assumed to have been generated by the PCR amplification step in paired-end library construction, making them nonindependent data points. Inspection of the mapping output suggested that the analysis was too stringent in identifying consistent read pairs. Therefore, any “inconsistent” read pairs that mapped in a proper orientation within a distance of 4–16 kb for a 12-kb library or 1–6 kb for a 3-kb library were reclassified as consistent. These size ranges were determined on the basis of manual inspection of the distribution of mapping spans. Identified repeats within each genome (see above) were filtered on the basis of multiple criteria prior to inclusion in recombination analyses. First, only repeats of at least 50 bp in length and at least 95% sequence identity were considered. Additional repeat pairs were excluded because their proximity to each other or to other repeats would have led to ambiguity in the interpretation of paired-end mapping results. Specifically, repeats were excluded if the two copies were separated by less than the maximum library span or if there was a “correlated” pair of larger repeats within the maximum library span of each repeat copy. Finally, for S. conica and S. vulgaris (for which only 3-kb paired-end libraries were available), repeat pairs were excluded if one of the repeat copies was within 100 bp of the start of any other repeat >500 bp in size. These cases were excluded because the presence of adjoining repeats would preclude unambiguous mapping of reads to the flanking sequence. Because of the limited physical coverage and short (3 kb) span length in the S. conica paired-end data, there are many repeat pairs (particularly large repeats) in this genome that passed the aforementioned criteria, but have an insufficient number of read pairs to precisely measure the relative frequency of alternative genome conformations. Therefore, frequencies are only reported for repeat pairs that have at least five consistent read pairs spanning each copy. Finally, because of the enormous number of small repeats in the S. conica mitochondrial genome (Figure 5), only a random sample of 5% of repeat pairs shorter than 200 bp was included. To validate our methodological approach, we ran a set of control analyses that used the same set of repeats except that we reversed the coordinates for one of the copies. Therefore, these analyses assessed rearrangements associated with the same genomic regions but would only detect alternative genome conformations if recombination occurred between two homologous sequences lined up in opposite orientations. The frequency of alternative genome conformations was at or near zero for every one of these control analyses (Figure S6). This suggests that baseline level of genome rearrangement and chimeric artifacts is very low in our dataset and that the alternate genome conformations detected by these methods are the genuine result of repeat-mediated recombination. In addition, the differences in assembly methods across species (see above) should have no effect on the reported estimates of recombinational activity because these differences only pertain to large repeats exceeding the span of our paired-end libraries, which were not assayed for recombination. Estimates of Nucleotide Substitution Rate Previous analyses based on individual genes have identified massive variation in mitochondrial substitution rates among genes and species within the genus Silene [35]–[37],[91]. To assess these patterns at a genome-wide scale, all protein genes were aligned with MUSCLE v3.7 [92] and levels of synonymous (d S) and nonsynonymous (d N) divergence were estimated using PAML v4.4 [93] as described previously [37]. Analyses were run both on individual genes and on a concatenated dataset of all shared protein genes. Most analyses included six species (Arabidopsis thaliana, Beta vulgaris, and all four Silene species), but a larger dataset of sequenced seed plant mitochondrial genomes was also analyzed. In all cases, the phylogenetic relationships among the four Silene species were left unresolved (i.e., as a four-way polytomy), reflecting the apparently rapid radiation of these four lineages [37],[54]. Because substitutions at RNA editing sites can artificially inflate estimates of d N [94], we excluded all codons that were found to be edited based on genome-wide datasets from four species [70],[95],[96]. To estimate absolute rates of nucleotide substitution in these genomes, d N and d S values were divided by an approximate divergence time of 6 Myr [35],[37],[97]. However, these estimates should be considered only rough approximations because of the uncertainty in divergence time [37] and the potential bias associated with recent polymorphisms [98],[99]. Indel Analysis To determine the frequency and size distribution of indels, all protein genes (including cis-spliced introns) from the four Silene species and the outgroup B. vulgaris were aligned with MUSCLE v3.7 and adjusted manually. Unalignable regions at the 5′ and 3′ ends of genes were excluded. The resulting alignments were analyzed to identify all indels that were unique to a single species and did not overlap with any other indels. Prediction of RNA Editing Sites A genome-wide analysis of C-to-U RNA editing sites by cDNA sequencing has been reported previously for S. latifolia and S. noctiflora [70]. To estimate the frequency of RNA editing in S. vulgaris and S. conica, protein gene sequences were analyzed with a predictive algorithm (PREP-mt) [100]. Control analyses using Silene sequences with known editing sites suggested that different stringency settings (C-values) are appropriate for species with different rates of sequence evolution. Specifically, the S. conica data were analyzed with C = 0.8 and the S. vulgaris data were analyzed with C = 0.7. PREP-mt does not identify synonymous editing sites, so the reported totals were increased by 10% to approximate the contribution of synonymous edits on the basis of observed rates in other Silene genomes [70]. All intact protein genes were included as well as the following putative pseudogenes: rps13 (S. latifolia), rps3 (S. conica, S. latifolia, and S. noctiflora), and ccmFc (S. conica). For genes with duplicates within the genome, only a single gene copy was included. Estimating Nucleotide Polymorphism To estimate levels of sequence variation within each of the four Silene species in this study, we PCR amplified and Sanger sequenced a sample of five mitochondrial loci as well as a single plastid and nuclear locus for multiple, geographically dispersed populations. Sequencing methods, source populations, and polymorphism data for S. vulgaris and S. latifolia were reported previously [36],[91]. Source populations for S. noctiflora and S. conica are summarized in Table S4. A single individual was sampled from each population. Sequence data from each species were analyzed with DnaSP v5 [101] to calculate nucleotide diversity and the number of segregating sites for each locus. Maximum likelihood estimates of Watterson's Θ and corresponding 95% confidence intervals were calculated as described previously [91]. For the nuclear X4/XY4 locus, a single haplotype was randomly selected from each individual for calculation of polymorphism data. Only X-linked copies were included for S. latifolia males. Haplotypes were inferred from diploid sequence data using the program PHASE v2.1 [102]. Novel sequences were deposited in GenBank (accessions JF722621–JF722652). Testing for Maternal Inheritance of mtDNA We performed a set of greenhouse crosses to test for maternal transmission of mtDNA in S. latifolia, S. noctiflora, and S. conica (S. vulgaris was not included because it has already been the subject of numerous studies examining mitochondrial genome inheritance and heteroplasmy [44]–[47]). Each cross involved an individual from the maternal family used for mitochondrial genome sequencing and an individual from another family in that species known to differ in mtDNA haplotype. For each species, a single pair of reciprocal crosses was performed, and a SNP was used to design a CAPS marker capable of distinguishing the two parental genomes (Table S5) [103]. For each pair of crosses, 16 to 48 progeny were analyzed with the corresponding CAPS marker. Supporting Information Figure S1 Lengths of cis -spliced introns in Silene mitochondrial genomes. (PDF) Click here for additional data file. Figure S2 The effect of sequence identity and repeat length thresholds on estimates of repetitive content in Silene mitochondrial genomes. Perfect repeats were identified with Vmatch, and imperfect repeats were identified with BLAST (see Materials and Methods). (A) The relationship between the percent of the genome covered by repeats and the minimum percent sequence identity (based on repeats pairs of at least 100 bp in length). (B) The relationship between the percent of the genome covered and repeat length (based on perfect repeat pairs only). (PDF) Click here for additional data file. Figure S3 Repeat coverage depth in Silene mitochondrial genomes. For each curve, the y-intercept indicates the proportion of the mitochondrial genome that is single-copy in that species. Other points along the curve indicate the cumulative genomic coverage up to a certain repeat depth. For example, the height of the curve at a value of 10 on the x-axis indicates the fraction of the genome represented by all nucleotide positions that match nine or fewer repeats elsewhere in the genome. The lower position of the S. conica curve reflects the highly repetitive nature of its mitochondrial genome. In particular, the curve does not converge on 100% genome coverage until a copy number of >100, indicating that some positions in the genome exhibit significant similarity with duplicated sequences in more than 100 other places in the genome. (PDF) Click here for additional data file. Figure S4 Alternative genome conformations generated by repeat-mediated recombination. (A) A classic representation of multi-partite genome structure in plant mitochondria with a “master circle” genome conformation (left) interconverting with an alternative conformation consisting of two subcircles (right), based on recombination between a pair of direct repeats (red boxes). (B) Because of recombination, a two-copy repeat can potentially occur in any of four genomic “environments,” identified here as Reference 1 and 2 and Recombinant 1 and 2. (C) Paired-end sequencing reads that span the repeat can be used to quantify the relative abundance of these alternative conformations. Read pairs are generated by sequencing only the ends of a larger fragment from a sheared and size-selected DNA library. The solid blue lines depict read pairs that span the repeat and map consistently relative to the reference assembly with “left” and “right” ends mapping on either side of the repeat in the expected orientation and at the expected distance apart. The dashed blue lines depict read pairs that are inconsistent with the reference genome, but are consistent with one of the expected products of recombination across the shared repeat sequence. The read count data shown correspond to a 168-bp repeat pair in S. vulgaris Chromosome 1. In this example, there are a total of 986 (505+481) read pairs that support the reference assembly and only 20 (8+12) that support the recombinant forms. Therefore, the frequency of recombinant products associated with this repeat pair is approximately 2%. (PDF) Click here for additional data file. Figure S5 Relationship between length and sequence identity for repeats in S. noctiflora (top) and S. conica (bottom) mtDNA. Each point represents a single pair of repeated sequences identified by BLAST, with the x-axis showing the aligned length of those sequences and the y-axis describing the extent of sequence similarity between the pair. Note that, in contrast to the large number of imperfect repeats (sequence identity <100%) in S. noctiflora and S. conica, all S. latifolia and S. vulgaris repeats in this size range are 100% identical or nearly so (Figure 7). (PDF) Click here for additional data file. Figure S6 Assays of repeat-mediated recombinational activity in Silene mitochondrial genomes. (A) The left column shows the data presented in Figure 6 individually for each species (note the change in scale for each species). (B) The right column reports the analysis of the exact same repeats except in reversed orientation as a measure of the baseline level of alternative genome conformations and/or library construction artifacts in each species. Note that not all repeat pairs are shown (see Materials and Methods for filtering criteria). (PDF) Click here for additional data file. Table S1 Duplicate genes in Silene mitochondrial genomes. Values indicate cases where more than one full-length gene or exon copy exists within the corresponding genome. Bold values indicate that the coexisting copies differ in sequence. For cases in which a mixture of identical and divergent copies exist, the total number of copies is shown in plain text and the number of unique sequences is shown parenthetically in bold. Numerous cases of duplicated gene fragments representing less than a full-length gene or exon are not reported here. (DOC) Click here for additional data file. Table S2 Summary of length, GC content, gene content, and GenBank accession numbers for circular chromosomes (and partially assembled genomic fragments in S. conica ). (DOC) Click here for additional data file. Table S3 Nucleotide polymorphism within Silene species. (DOC) Click here for additional data file. Table S4 Source of S. noctiflora and S. conica populations for polymorphism analysis. (DOC) Click here for additional data file. Table S5 CAPS markers used to screen for maternal inheritance of mtDNA in greenhouse crosses. (DOC) Click here for additional data file.

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Saura R. Silva: Role: Data curationRole: InvestigationRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing

Danillo O. Alvarenga: Role: Data curationRole: InvestigationRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – review & editing

Yani Aranguren: Role: Formal analysisRole: MethodologyRole: Resources

Helen A. Penha: Role: Formal analysisRole: MethodologyRole: Resources

Camila C. Fernandes: Role: Formal analysisRole: MethodologyRole: Resources

Daniel G. Pinheiro: Role: Formal analysisRole: InvestigationRole: SoftwareRole: Visualization

Marcos T. Oliveira: Role: InvestigationRole: SupervisionRole: ValidationRole: Writing – review & editing

Todd P. Michael: Role: ConceptualizationRole: InvestigationRole: MethodologyRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – review & editing

Vitor F. O. Miranda: Role: ConceptualizationRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing

Alessandro M. Varani:

ORCID: http://orcid.org/0000-0002-8876-3269

Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing

Zhong-Hua Chen: Role: Editor

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Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, CA USA )

ISSN (Electronic): 1932-6203

Publication date (Electronic): 19 July 2017

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Volume: 12

Issue: 7

Electronic Location Identifier: e0180484

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[1 ] Departamento de Botânica, Instituto de Biociências, Universidade Estadual Paulista (UNESP), Botucatu, São Paulo, Brazil

[2 ] Departamento de Tecnologia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista (Unesp), Jaboticabal, São Paulo, Brazil

[3 ] Departamento de Biologia Aplicada à Agropecuária, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista (Unesp), Jaboticabal, São Paulo, Brazil

[4 ] Computational Genomics, Ibis Bioscience, Carlsbad, CA, United States of America

University of Western Sydney, AUSTRALIA

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Competing Interests: TM is an employee of Ibis Biosciences, an Abbott Laboratories company. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

[¤a]

Current address: Universidad Simón Bolívar, Barranquilla, Colômbia

[¤b]

Current address: J. Craig Venter Institute, La Jolla, CA, United States of America

* E-mail: amvarani@ 123456fcav.unesp.br (AV); vmiranda@ 123456fcav.unesp.br (VM)

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Alessandro M. Varani http://orcid.org/0000-0002-8876-3269

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DOI: 10.1371/journal.pone.0180484

PMC ID: 5516982

PubMed ID: 28723946

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Date received : 10 April 2017

Date accepted : 13 May 2017

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Funded by: funder-id http://dx.doi.org/10.13039/501100001807, Fundação de Amparo à Pesquisa do Estado de São Paulo;

Award ID: 13/25164-6

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ORCID: http://orcid.org/0000-0002-8876-3269

Alessandro M. Varani

Funded by: funder-id http://dx.doi.org/10.13039/501100003593, Conselho Nacional de Desenvolvimento Científico e Tecnológico;

Award ID: 309040/2014-0

Award Recipient : Vitor F. O. Miranda

This study was funded by Fundação de Amparo do Estado de São Paulo, FAPESP (13/25164-6). Ibis Biosciences, an Abbott Laboratories company, provided support to TM in the form of salary. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.

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Data Availability The annotated sequences and raw reads of the Utricularia reniformis mitochondrial genome have been deposited in the GenBank database under accession numbers [GenBank: KY774314, SRX2646180, SRX2646130 and SRX2646131] (BioProject PRJNA290588).

The mitochondrial genome of the terrestrial carnivorous plant Utricularia reniformis (Lentibulariaceae): Structure, comparative analysis and evolutionary landmarks

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