Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Plastid and mitochondrial genomes of Coccophora langsdorfii (Fucales, Phaeophyceae) and the utility of molecular markers

  • Louis Graf,

    Roles Data curation, Investigation, Writing – original draft

    Affiliation Department of Biological Sciences, Sungkyunkwan University, Suwon, Korea

  • Yae Jin Kim,

    Roles Data curation, Formal analysis

    Affiliation Department of Biological Sciences, Sungkyunkwan University, Suwon, Korea

  • Ga Youn Cho,

    Roles Resources, Writing – review & editing

    Affiliation National Institute of Biological Resources, Incheon, Korea

  • Kathy Ann Miller,

    Roles Writing – review & editing

    Affiliation University Herbarium, University of California, Berkeley, CA, United States of America

  • Hwan Su Yoon

    Roles Conceptualization, Funding acquisition, Supervision, Writing – review & editing

    hsyoon2011@skku.edu

    Affiliation Department of Biological Sciences, Sungkyunkwan University, Suwon, Korea

    ORCID http://orcid.org/0000-0001-9507-0105

Plastid and mitochondrial genomes of Coccophora langsdorfii (Fucales, Phaeophyceae) and the utility of molecular markers

  • Louis Graf, 
  • Yae Jin Kim, 
  • Ga Youn Cho, 
  • Kathy Ann Miller, 
  • Hwan Su Yoon
PLOS
x

Abstract

Coccophora langsdorfii (Turner) Greville (Fucales) is an intertidal brown alga that is endemic to Northeast Asia and increasingly endangered by habitat loss and climate change. We sequenced the complete circular plastid and mitochondrial genomes of C. langsdorfii. The circular plastid genome is 124,450 bp and contains 139 protein-coding, 28 tRNA and 6 rRNA genes. The circular mitochondrial genome is 35,660 bp and contains 38 protein-coding, 25 tRNA and 3 rRNA genes. The structure and gene content of the C. langsdorfii plastid genome is similar to those of other species in the Fucales. The plastid genomes of brown algae in other orders share similar gene content but exhibit large structural recombination. The large in-frame insert in the cox2 gene in the mitochondrial genome of C. langsdorfii is typical of other brown algae. We explored the effect of this insertion on the structure and function of the cox2 protein. We estimated the usefulness of 135 plastid genes and 35 mitochondrial genes for developing molecular markers. This study shows that 29 organellar genes will prove efficient for resolving brown algal phylogeny. In addition, we propose a new molecular marker suitable for the study of intraspecific genetic diversity that should be tested in a large survey of populations of C. langsdorfii.

Introduction

Coccophora langsdorfii (Turner) Greville is a brown algal species (Sargassaceae, Fucales) found in intertidal habitats along the cold waters of the Northeast Asia. Its range includes the East Sea in Korea [1], Hokkaido and the northern part of Japan [2], and the Far East coast of Russia and the Sakhalin Islands [3]. It forms dense bushy stands that stabilize the sandy sediment in which they grow and serve as support for epiphytic algae and associated herbivores. While the general morphology of the sporophyte is similar to species in the genus Sargassum, C. langsdorfii exhibits apical reproductive structures that clearly separate it from Sargassum species. Recent molecular phylogenetic studies demonstrated that C. langsdorfii is a close sister taxon to the genera Bifurcaria and Cystoseira within the family Sargassaceae [46].

In recent years, likely due to global climate change and/or habitat loss, C. langsdorfii populations in Korea have dramatically decreased and the species has been designated as an endangered species [7]. It has become urgent to establish coherent and efficient management for the populations of this alga. Conservation strategies and marine reserve design need to be based on knowledge of dispersal processes and gene flow among populations [8]. As sequencing technologies become less expensive and faster, it is possible to characterize such processes in wild populations [9]. In the genus Sargassum, cox3, a mitochondrial molecular marker, has been used to investigate population genetic structure [10]. Despite increasing interest in this kind of information, only a handful of population studies have been conducted on brown algae [1012] and no such study is available for C. langsdorfii. In an effort to provide insight into the evolution of C. langsdorfii and to help develop robust conservation strategies, we sequenced the complete plastid genome (ptDNA) and mitochondrial genome (mtDNA) of this alga. Using this genomic information, we conducted a study of the utility for phylogenetic studies of the genes encoded in the ptDNA and mtDNA. We suggest that 29 organellar genes are informative in phylogenetic studies of brown algae. Furthermore, we demonstrate the utility of this genomic information as a source of molecular markers for elucidating population structure for conservation purposes.

Materials and methods

Field samples and DNA extraction

Fresh thalli of Coccophora langsdorfii were collected on 28 March 2015 from the shallow subtidal zone of Gonghyunjin, Gangwon-do, South Korea (38°21'22''N, 128°30'45''E). Thalli were washed in autoclaved seawater, dried with paper towels, and preserved in silica gel. Voucher specimens were deposited in the herbarium of Sungkyunkwan University (SKKU003999). Genomic DNA was extracted from 2 mg of dried material following the protocol of Sahu et al. [13] with a subsequent purification step using the PowerClean® DNA Clean-Up Kit (Qiagen, Carlsbad, CA).

Whole-genome de novo sequencing and assembly

A 400 bp sequencing library was built using the IonXpress Plus gDNA Fragment Library Kit following manufacturer's instructions (Thermo Fisher Scientific, San Francisco, CA) and was sequenced using the Ion Torrent Personal Genome Machine (Thermo Fisher Scientific, San Francisco, CA). Organelle genome assemblies and annotations were summarized as in [14]. A total of 5,996,144 sequencing reads were assembled using MIRA assembler v4.0.2.1 [15] and the CLC de novo assembler included in CLC Genomics Workbench v5.5.1 (CLC Bio, Aarhus, Denmark). The contigs were sorted using a combination of BLAST [16] and Mummer plotting [17] with the plastid genome of Fucus vesiculosus (NC_016735) and the mitochondrial genome of Sargassum thunbergii (NC_026700) as references. Contigs identified as part of the plastid genome or the mitochondrial genome were independently assembled using Geneious Pro v7 [18], which generated one circular contig each. Ambiguous sequences were confirmed by Sanger sequencing (Macrogen Inc., Seoul, Korea). All sequencing reads were mapped on both sequences with an average coverage of 213X and 119X for the plastid and mitochondrial genomes, respectively. The complete plastid genome was annotated by using a combination of DOGMA [19] and BLASTx [16] for protein-coding sequences; tRNA scan-SE [20] for the tRNA sequences and RNAmmer [21] for ribosomal RNA sequences. All annotations were then manually checked. Finalized genome maps were created with GenomeVx [22].

Gene content comparison for organelle genomes

All available plastid genomes of the Stramenopiles were downloaded from NCBI GenBank (https://www.ncbi.nlm.nih.gov/genbank/, consulted on 17 May 2016). A list of annotated genes was extracted and compared using newly written R scripts (R core team, 2012; https://www.R-project.org). Protein-coding genes not shared among all taxa were submitted to local BLASTp [16] search (e-value cut-off ≤10−6) against the other phaeophycean plastid genomes, with the result that some genes, especially those coding for hypothetical proteins, were annotated under different names. Based on those results, we propose a revised and unified annotation for the plastid genome of the class Phaeophyceae (S1 Table). Gene names of the extracted annotations were manually checked, and unmatched names were modified for consistency (e.g., “psb28” was changed to “psbW”).

Organelle genome co-linear analysis

Plastid genome architecture (i.e., arrangements of conserved regions) was investigated using Mauve V.2.3.1 [23] with the progessiveMauve algorithm and default settings with the first anchor position in rpl9 gene for all plastid genomes. The ''backbone'' file produced by Mauve was used to compare synteny among the taxa using the R library genoPlotR [24]. Brown algal plastid genome distances were calculated using UniMoG [25]. For further analysis, only the double cut and join (DCJ) and Hannenhalli and Pevzner (HP) models were used, as their results were exactly identical to the restricted DJC and the inversion and translocation models, respectively.

Preliminary co-linear analysis conducted for 33 brown mitochondrial genomes did not reveal major rearrangements. This allowed us to use a BLAST Ring Image Generator (BRIG) map [26] to study full-length mitochondrial genome alignments. BRIG was run with standard blastn settings and identity thresholds set at 70% and 50%.

Phylogenetic analysis and gene evolutionary rates

The thirty-five mitochondrial protein-coding genes common to all brown algae in our study were used for the phylogenetic analysis. They were the atp6, atp8, atp9, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4, nad4L, nad5, nad6, nad7, nad9, nad11, rpl2, rpl5, rpl6, rpl14, rpl16, rpl31, rps2, rps3, rps4, rps7, rps8, rps10, rps11, rps12, rps13, rps14, rps19 and tatC. For each of them the DNA sequences were aligned at the amino acid level using MAFFT version 7 [27] in combination with TranslatorX [28] and the alignment was subsequently refined manually using Se-Al version 2.0a11 (http://tree.bio.ed.ac.uk/software/seal/). The thirty-five mitochondrial protein-coding gene alignments were concatenated into one dataset using SequenceMatrix 1.7.6 [29] where each gene represented a partition. Maximum likelihood reconstruction was conducted with IQ-Tree v1.3.0 [30] with an independent GTR substitution model with a 4-class gamma distributed rate heterogeneity (G) for each partition of the concatenated data. Branch supports were obtained with the ultrafast bootstrap (UFBoot) implemented in IQ-Tree [31].

Evolutionary rates were estimated for 170 genes common to all phaeophycean taxa (i.e., 35 genes from the mitochondrial genome and 135 genes from the plastid genome). They were individually aligned following the same strategy as for the phylogenetic analysis (see above). Pairwise nonsynonymous substitution rates (dN) of all 170 proteins were estimated using the R library seqinr [32]. The interquartile range (IQR) of the pairwise dN estimates of each gene and the Pearson’s product moment correlation between the IQR and the median dN of each gene were calculated with a newly designed R script. Single gene trees of the 170 genes common to all phaeophycean taxa were reconstructed following the method used for the concatenated tree. Tree topologies of single genes were compared to the topology of the concatenated trees for the mitochondrial and plastid genes. Comparisons were performed using the R library PhySortR [33] with a minimum support value threshold of 50%.

Protein structure prediction and analysis of the cox2 gene

The predictions of secondary structure of the cox2 protein of Coccophora langsdorfii were conducted using the I-TASSER suite [34, 35] implemented on the I-TASSER server (http://zhanglab.ccmb.med.umich.edu/I-TASSER/) [36]. Three independent predictions were performed: (1) prediction of the N-terminal part of the cox2 gene (i.e. the sequence before the insertion), (2) prediction of the C-terminal part of the cox2 gene (i.e. the sequence after the insertion) and (3) prediction of the full cox2 sequence. For the first two predictions I-TASSER was run with default settings. For the third prediction, the I-TASSER algorithm was constrained by using the PDB structure of the cytochrome c oxidase from Thermus thermophilus (PDB ID: 3S8F) and excluding PDB structures (PDB IDs: 5FVM; 5IJO; 3MLI; 3HB3; 1QGR; 4JSP and 3W3T) and their homologous templates with a cutoff of 70% homology.

Molecular markers for population study

Using the mtDNA BRIG map (S3 Fig), PCR primers were designed with the dedicated tool implemented in Geneious Pro v7 [18]. Primers were further tested for potential dimers using AmplifX v1.7.0 (http://crn2m.univ-mrs.fr/pub/amplifx-dist). The new primer set used in this study was atp6-cox3_F (TAA CTA TTT ACT GGT GGG GGT) and atp6-cox3_R (GTA ATC ATT GCG TTA GTT ATC G). PCR amplifications were conducted as described in [37] on two individuals (Gonghyunjin-2, -3) collected on the same day and in the same population as the individual used for genome sequencing (Gonghyunjin-1), and on one individual collected on 25 May 2011 at Jangsa, Gangwon-do, South Korea (Jangsa-1). Sequences were aligned manually in Se-Al version 2.0a11 (http://tree.bio.ed.ac.uk/software/seal/).

Results and discussion

The plastid genome of Coccophora langsdorfii

Description and gene content.

The plastid genome (ptDNA) of Coccophora langsdorfii is a 124,450 bp circular molecule (GenBank accession number KU255795). This genome size is within the range of others reported for species in the Fucales (124,068–124,986 bp) but is smaller than those of the Ectocarpales (139,954 bp) and Laminariales species (129,947–130,584 bp) (Table 1). The average GC-content of C. langsdorfii ptDNA is 29.8%, which falls in the range of reported phaeophycean ptDNAs (28.9–31.1%). The phaeophycean plastid genome has a typical quadripartite organization that is divided into large (LSC) and small (SSC) single-copy regions by two 5,423 bp inverted repeats (IRs) (S1 Fig). The sizes of the different components of brown algal ptDNAs are comparable, with the exception of E. siliculosus, which has significantly larger IRs (8,615 bp) than those of the other species (5,015–5,446 bp). Without plastid genome sequences from earlier divergent lineages (e.g., Ishigeaceae, Desmarestiales or Dictyotales), it is hard to determine if the IRs in the Ectocarpales have expanded or if IRs have been reduced independently in the Fucales and Laminariales.

thumbnail
Table 1. Summary of the general features of the complete plastid genomes of the class Phaeophyceae.

https://doi.org/10.1371/journal.pone.0187104.t001

Coccophora langsdorfii ptDNA contains 139 protein-coding genes (including 16 hypothetical proteins and two orfs), 28 tRNAs and 6 rRNAs. The plastid gene set of C. langsdorfii is identical to that of other algae in the Fucales that have been studied (F. vesiculosus, Sar. horneri and Sar. thunbergii). This gene set is largely shared among phaeophyceaen taxa. The conservation of gene contents appears to be common to most plastid genomes. For instance, the ptDNA in land plants and florideophycean red algae have been shown to be remarkably conserved [3840].

On the basis of all published brown algal ptDNA datasets, we determined a 178 core gene set that is putatively ancestral and mapped the specific gene loss or gain of lineages in the brown algal phylogenetic tree (Fig 1A). The fucalean ptDNAs lack syfB, ycf17 and tRNAArg[tct] genes whereas the Laminariales lack petL and ycf54 (Cos. costata also lacks tRNAArg[tct]). The ptDNA of E. siliculosus is distinguished by four additional orfs (Escp36, Escp99, Escp117 and Escp161) and five duplicated genes found in the IRs (rpl21, rpl32, psbA, tRNALeu[taa] and tRNAGlu[ttc]). Because genes that are missing in the Fucales and Laminariales are found in the ptDNAs of other stramenopile lineages (e.g., Xanthophyceae, Bacillariophyceae), it is highly likely that the ancestral plastid genome of brown algae contains these genes. On the other hand, the four orfs specific to E. siliculosus showed no similarity with other brown algal sequences in our BLAST search (data not shown), suggesting independent gene gains in this lineage. Because ptDNA of E. siliculosus retains all 178 core genes plus nine additional genes, the genome of E. siliculosus represents the closest approximation to the ancestral plastid genome of the Phaeophyceae.

thumbnail
Fig 1. Evolutionary history of the plastid genome in the class Phaeophyceae.

The tree topology is based on the current view of the phylogeny of the class Phaeophyceae [41, 42]. Boxes near the nodes represent evolutionary events that occurred along the Phaeophyceae plastid tree. Symbol of minus (–) indicates loss event, whereas symbol of plus (+) indicates gain event. Full alignments were performed using progressiveMauve algorithm [23] and visualized with the genoPlotR library [24]. Colored boxes indicate Locally Collinear Blocks (LCBs) that represent homologous gene clusters.

https://doi.org/10.1371/journal.pone.0187104.g001

Codon usage.

The vast majority of the protein coding genes (137 genes, 98.5%) present in the plastid genome of C. langsdorfii uses ATG as the start codon, as reported in most of the protein coding genes of the Phaeophyceae [45, 48] (Table 2). Only rpl3 and rps8 genes of C. langsdorfii use ATT as alternate start codon. Interestingly, rpl3 and rps8 in other brown algal species have the alternative start codon GTG rather than ATT. This start codon diversity indicates relaxed selection on the rpl3 and rps8 genes.

thumbnail
Table 2. Codon usage comparison of the complete plastid genomes of the class Phaeophyceae.

https://doi.org/10.1371/journal.pone.0187104.t002

Translational termination codons in the C. langsdorfii ptDNA are TAA (107 genes, 77%), TAG, (26 genes, 19%) and TGA (6 genes, 4%), similar to codon usages in other phaeophycean species (see Table 2). The stop codon TAG is used for an average of 16.5% of the genes in the Fucales and 15.5% in the Laminariales, whereas it is used in only 9.5% of the genes of the E. siliculosus. The stop codon TGA is used in only one or two genes in the Laminariales (less than 1% of the total encoded protein coding genes) whereas it is used more broadly in the Fucales and Ectocarpales (average 5% and 3.3% of the total encoded protein-coding genes, respectively).

Co-linear genome rearrangement analysis.

To investigate rearrangement events in the ptDNAs of brown algal species, we performed a co-linear analysis of all available phaeophyceaen species with the xanthophycean Vaucheria litorea (NC_011600) as outgroup (Fig 1). Syntenies of the four Fucales ptDNAs (C. langsdorfii, F. vesiculosus, Sar. horneri and Sar. thunbergii) are identical. Similarly, three Laminariales species (Cos. costata, Sac. japonica and U. pinnatifida) show identical genome architecture. This indicates that no recombination events occurred after the divergence of the phaeophycean orders. The genome architecture is therefore fixed at the ordinal level. To test this ordinal level of conservation in genome architecture, additional plastid genome data are needed.

In contrast, numerous recombinations are observed in the ptDNAs among different orders (Fig 1B). To assess the number of recombination events, we calculated genome distances between different taxa. The DJC and HP distances were used to represent the number of rearrangement steps necessary to ''reconstruct'' one genome from another. Interestingly, the distances between the genome pairs are not correlated with their phylogenetic relationships. The genome alignment of E. siliculosus and three Laminariales species (Cos. costata, Sac. japonica and U. pinnatifida) shows a DJC distance of 50 and a HP distance of 52. The Fucales diverged from an ancestor of the Ectocarpales and Laminariales [41] (Fig 1A). However, the DJC and HP distances between the phylogenetically distantly related Fucales (C. coccophora, F. vesiculosus, Sar. horneri and Sar. thunbergii) and Laminariales are 32 and 34, respectively, while the DJC distance is 58 and HP distance is 59 between E. siliculosus and the three Fucales species. Thus, architectural rearrangements in ptDNA likely occurred, independent of phylogenetic relationship, in the ancestors of each order. Additional plastid genome sequences from diverse lineages of the brown algae are necessary to fill the gaps in our limited understanding of the evolution of the plastid genome in the Phaeophyceae.

The mitochondrial genome of Coccophora langsdorfii

Description and comparison.

The mitochondrial genome (mtDNA) of C. langsdorfii is a circular molecule of 35,660 bp (GenBank accession number KU255794) (S2 Fig). Compared to other fucalean mtDNAs, it is longer than those of six Sargassum species and Turbinaria ornata but smaller than F. vesiculosus (Table 3). The overall GC-content is 36.44% and is comparable to that of other fucalean species (i.e., 34.45–37.53%). Non-coding sequences (1,640 bp) represent 4.6% of the C. langsdorfii mtDNA. This percentage is within the range of that observed in other fucalean species (4.29–5.62%). The mtDNA of C. langsdorfii contains 38 protein-coding genes (including 3 conserved orfs), three rRNAs (rnl, rns and rrns), and 25 tRNAs. All protein-coding and rRNA genes are also found in other fucalean mtDNAs. However, tRNATyr[aua] genes located between the tRNA-Ala[ugc] and rps10 in F. vesiculosus and C. langsdorfii are absent in the six Sargassum species and T. ornata. However, orf379, which is also present in F. vesiculosus and T. ornata, is present in C. langsdorfii, indicating that the loss of the tRNATyr[aua] gene occurred in the common ancestor of the Sargassaceae (including Coccophora, Turbinaria, and Sargassum), whereas orf379 was lost in the common ancestor of the genus Sargassum (Fig 2A).

thumbnail
Fig 2. Evolutionary history of the mitochondrial genome in the class Phaeophyceae.

The tree was reconstructed with a 35 gene concatenation. Black dots on the branches represent fully supported nodes (100% Maximum Likelihood Support). Bootstrap support values of non-supported nodes are shown near the nodes. Boxes near the nodes represent evolutionary events that occurred along the Phaeophyceae mitochondria tree. Symbol of minus (–) indicates loss event, whereas symbol of plus (+) indicates gain event. Schematic representation of the cox2 gene in the class Phaeophyceae. The two transmembrane helices are colored in red; the CUA center in blue and the in-frame insert in green.

https://doi.org/10.1371/journal.pone.0187104.g002

thumbnail
Table 3. Summary of the general features of the complete mitochondrial genomes of the class Phaeophyceae.

https://doi.org/10.1371/journal.pone.0187104.t003

Codon usage.

Of the 38 mitochondrial protein coding genes in C. langsdorfii, 37 use ATG as a start codon, similar to other brown algae (Table 4). The orf379 of C. langsdorfii and F. vesiculosus has the alternative start codons ATA or GTG, respectively. Interestingly, in all the Ectocarpales sequenced, the nad11 gene uses various alternative start codons but never ATG. For example, the nad11 gene in Colpomenia peregrina, Petalonia fascia and Pylaiella littoralis, uses TTG [64, 66, 67], in Scytosiphon lomentaria GTG [68], and in E. siliculosus, CTG (Table 4). As in the plastid genomes, this suggests that alternative start codon usage is gene-specific and could be related to the transcription efficiency of each gene.

thumbnail
Table 4. Codon usage comparison for the complete mitochondrial genomes of the class Phaeophyceae.

https://doi.org/10.1371/journal.pone.0187104.t004

Genome rearrangement analysis.

Using a BRIG map [26], we compared the identity of C. langsdorfii mtDNA to 30 brown algal mtDNAs. In general, gene orders among brown algal mtDNAs are highly conserved with only minor rearrangements. They are mostly insertion/deletion of orfs and/or tRNA genes, but the gene order of protein-coding genes (atp8, atp9, rpl31 and rps10) in D. dichotoma differs from those of other species [49]. In C. langsdorfii mtDNA, the genome has a 50 to 70% identity to the genomes of other brown algal species (S3 Fig), and the rns and rnl genes have an identity with other species higher than 70%.

Seven regions show higher genetic divergences than the rest of genomic regions: the tRNAPro[ugg]-rnl spacer, the rnl-tRNALys[uuu] spacer, the cox3-atp6 spacer (containing various orfs), the cob-cox2 spacer, the cox2 gene, the nad6 gene, and the region between the rps14 and rns genes (S3 Fig). In Sargassum species, the cox3-atp6 spacer was found to be the most variable region in terms of both sequence identity and spacer length [55]. This spacer contains the conserved orf379 that is found only in F. vesiculosus and C. langsdorfii. The reduced size (1,140 bp in F. vesiculosus compared to 849 bp in C. langsdorfii) suggests potential pseudogenization in C. langsdorfii.

The cytochrome c oxidase subunit 2.

The high variability observed in the cox2 region is due to the presence of a large in-frame insertion found only in the orders of Fucales, Desmarestiales, Laminariales and Ectocarpales (S4 and S5 Figs). Because of this insertion, the length of the cox2 gene in the Stramenopiles varies from 687–906 bp (without insertion, as in the Dictyotales, Bacillariophyceae, and Oomycota) to 3,129–3,921 bp (with insertion) (S5 Fig). This in-frame insertion shows a high level of conservation among brown algal species (S4 Fig). Furthermore, the insert-containing lineages form a well-supported monophyletic group (Fig 2A). Therefore, it is likely that there was a single in-frame insertion event in the cox2 gene of the ancestor of these four brown algal orders. Similarly, a large insert was also found in the cox2 gene of the ciliate genera Euplotes (3,051–3,063 bp), Tetrahymena (1,812 bp) and Paramecium (1,728 bp) [69, 70], which might be derived from a common ancestor [69]. Interestingly, despite its independent origins, the insertion in the cox2 gene is situated at the same position in brown algae and ciliates. Those inserts separate the two functional domains of the cox2 subunit: the two N-terminal transmembrane helices and the C-terminal copper A center (CUA) (Fig 2B). Furthermore, the cox2 genes found in alveolates, chlorophycean algae and in one species of Hymenoptera (insects) have been independently split into two subunits corresponding to the N-terminal and C-terminal domains of the canonical cox2 gene [7174]. The split of the cox2 gene occurred at the same location as the insertions in other lineages. All of these events appear to be lineage-specific and independent. Other genes have been reported as split (e.g. SdhB in euglenozoans [75], rpl2 in some angiosperms [76] or nad1 in ciliates [70]) but it is remarkable that the cox2 gene is undergoing independent evolutionary events in many different lineages. Furthermore, most of the split mitochondrial genes were subsequently transferred to the nucleus [7274]. The insert observed in the brown algae might represent an early stage in a similar split and later transfer to the nucleus. However, this is extremely speculative and further analyses, especially regarding expression, are required.

Predictions of the secondary structure of the N-terminal and C-terminal yielded structures comparable to the canonical cox2 protein (Fig 2C and 2D). Conservation of those domains would suggest that despite the large insert, the brown algal cox2 gene still encodes a functional cox2 protein. However, the cox2 protein is a subunit of the cytochrome c oxidase complex and therefore has to be precisely assembled with the cox1 and cox3 subunits to form a functional complex [77]. This correct assemblage is the foundation of the entire mitochondrial transport chain [78]. To determine how the insert could affect the assemblage of the cytochrome c oxidase complex, we predicted the structure of the cox2 protein in C. langsdorfii. The prediction failed to recover a three dimensional organization that would bring the C-terminal CUA center close to the position in which it is normally found (Fig 2E). If the CUA center of the cox2 subunit is not in the right position, electrons might not be transferred from the cox2 subunit to the cox1 subunit. In mammals, a misassembled cytochrome c oxidase causes serious pathologies and can be lethal [78]. Yet the highly modified cox2 subunit in the brown algae has not been eliminated by natural selection, suggesting that the brown algal cytochrome c oxidase has an assemblage that differs from those found so far in other organisms. Understanding the structure and assemblage of this unique cytochrome c oxidase would contribute considerable insight into the physiology of the brown algae and possibly into their ecological success. This, however, remains to be explored.

Molecular markers

Evolutionary divergence rates of organelle genes.

In general, organelle genomes are present in multiple copies in a cell and their genes can be easily amplified and sequenced, making them an important source of molecular markers for phylogenetic studies or barcoding. Despite their advantages, only a handful of organelle genes have been widely used (mainly 16S rRNA, rbcL, psbA, cox1) in phylogenetic studies [41, 79, 80].

To investigate their value as molecular markers, we estimated the evolutionary divergence rate for the genes found in the plastid and mitochondrial genomes of the Phaeophyceae, following the approach developed by Janouškovec et al. [39]. Briefly, we used 35 complete mitochondrial and eight complete plastid genomes to calculate pairwise comparisons of nonsynonymous substitutions per site (dN) and their standard deviation (interquantile range, IQR) for a total of 170 genes. These dNs were used to estimate the divergence rate of individual genes, while the IQRs were used to estimate the uniformity of dN rates among species. Genes were ordered by their median dN (S6 Fig).

The mitochondrial genes generally showed a higher dN than those of the plastid genes. A similar trend was observed in plastid-bearing species and especially in the species containing red-algal-derived plastids [80]. As in red algal plastid genomes [39], the dNs of the plastid and mitochondrial genes of the brown algae were positively correlated with the IQR (S6 Fig). This means that larger dN correlated with unequal dN distances among species, whereas suitable markers for phylogenies should have close to equal dN rates among species (i.e., low IQR value). Therefore, the 27 genes with the highest IQR may not be appropriate for phylogenetic or studies at the intraspecific level (Figs 3A and 4A). Out of the 143 genes with low to medium IQR, we further excluded genes with lengths less than 900 nucleotides, because shorter genes are not practical for primer design and PCR. More importantly, short sequences may not contain sufficient genetic information to resolve phylogenetic relationships. This analysis resulted in 42 genes in the plastid (34 genes underlined in Fig 3A) and mitochondrial (eight genes underlined in Fig 4A) genomes that we identified as candidates for markers in phylogenetic studies.

thumbnail
Fig 3. Genetic evolutionary rates of the plastid encoded genes of the Phaeophyceae.

(a) Summary of the characteristics of individual genes by dN bin and IQR bin. Bins highlighted are potential candidate genes for phylogenies and discrimination of orders or families. Underlined genes are 900 bp or more length. (b) Maximum likelihood phylogeny reconstructed from the concatenation of genes with a size larger than 300 amino acids. Numbers near the nodes represent the number of single gene trees that support the node.

https://doi.org/10.1371/journal.pone.0187104.g003

thumbnail
Fig 4. Genetic evolutionary rates of the mitochondrial encoded genes of the Phaeophyceae.

(a) Summary of the characteristics of individual genes by dN bin and IQR bin. Bins highlighted are potential candidate genes for phylogenies and discrimination of orders or families. Underlined genes are 900 bp or more. (b) Maximum likelihood phylogeny reconstructed from the concatenation of genes with a size larger than 300 amino acids. Numbers near the nodes represent the number of single gene trees that support the node.

https://doi.org/10.1371/journal.pone.0187104.g004

Phylogenetic analysis using single gene datasets.

To test the suitability of these 42 candidate genes for the phylogenetic analysis, we compared the tree topologies of 42 single genes with the concatenated multigene topologies (34 plastid genes and eight mitochondrial genes, see Figs 3B and 4B). The concatenated multigene trees were generally congruent with the published phaeophycean phylogenies [41, 42]. The single gene trees were mostly congruent with the concatenated trees, indicating that information content is consistent over the single genes. This is a valuable finding if those genes are to be used in a concatenated tree for phylogenetic analysis. However, four nodes were poorly supported or not supported by the single gene trees. In the plastid tree, the node E joining S. japonica and C. costata was found in only 20 out of 34 single gene trees (Fig 3B). In the remaining trees, U. pinnatifida was sister to S. japonica. Internal relationships within kelps (Laminariales) are generally unresolved due to rapid diversification [41, 81].

In the mitochondrial tree, nodes F, I and N were not supported. These nodes occurred at different levels in the tree. The interordinal node F was recovered in four out of eight trees with maximum likelihood bootstrap support (MLB) higher than 50%, and in two other trees with lower MLB support. The interfamilial node I grouping the families of Acinetosporaceae and Ectocarpaceae was recovered in only two out of eight trees. In the remaining six trees, the family Ectocarpaceae was sister to the family Scytosiphonaceae, but this position was strongly supported in only one tree. The node N that grouped the genera Costaria and Laminaria was not recovered in seven single gene trees. This is not congruent with the latest phylogenetic study of the order Laminariales [82] and could point to a lack of phylogenetic information in our 42 candidate genes and/or be an artifact of the limited number of taxa included in our analysis. As in the plastid trees, this lack of resolution might also be explained by rapid diversification of the order Laminariales [41, 81].

Proposed markers for phylogenetic analysis.

We propose a set of 29 genes that would be efficient and effective for phylogenetic analysis: the plastid-encoded atpA, atpB, cbbX, chlB, chlI, chlN, clpC, dnaK, ftsH, groEL, petA, psaA, psaB, psbA, psbB, psbC, psbD, rbcL, rpoB, rpoC1, secA, secY, sufB, tufA genes and the mitochondria-encoded cox1, cox2, nad1, nad4 and nad5 genes. Although the limited number of species used in our analyses might affect the delimitation of the IQR categories and the topology of trees, all the phaeophycean organelle genomes reported so far contained these genes, so they may assist in resolving problematic brown algal phylogenetic relationships at various levels [41, 82]. Other genes, such as the plastid encoded acsF, rbcR, rpoA, and rpoC2, with higher dN values (0.15–0.31) and lengths greater than 900 bp could be used for the study of subspecies and populations, including a study of gene flow and connectivity among populations of C. langsdorfii.

Proposed marker for population genetic structure and conservation studies.

Conservationists use molecular markers to determine threats menacing endangered species (e.g., genetic homogeneity or isolation of populations, small effective population size). Indeed, an understanding of the level of genetic diversity among individuals and populations promotes the understanding of population dynamics and the consequences of those threats [9]. Organellar genomes are valuable sources for molecular markers potentially suitable for the analysis of population genetic structure and processes. We mined the mtDNA sequence of C. langsdorfii in an effort to develop such molecular markers.

Using a BRIG map [26] we identified five regions of genetic diversity higher than the rest of the genome in the fucalean mtDNA (S3 Fig). These were the tRNAPro[ugg]-rnl spacer, the rnl-tRNALys[uuu] spacer, the cox3-atp6 spacer, the cox2 gene, and the region between the rps14 and rns genes These regions were chosen as candidate markers. We removed the tRNAPro[ugg]-rnl spacer and the rnl-tRNALys[uuu] spacer from consideration because they were too short (48 bp and 160 bp, respectively). We also removed the cox2 gene and the region between the rps14 and rns genes because they were too long (3,144 bp and 1,433 bp, respectively).

To test intraspecific diversity in the atp6-cox3 spacer, we sequenced this region for additional three individuals of C. langsdorfii belonging to two populations in Gonghyunjin and Jangsa, Korea. We obtained a 970 bp alignment that contained four polymorphic sites (Fig 5). To verify the stability of these polymorphic sites, we conducted independent PCR and Sanger sequencing, using the chromatogram to confirm the quality of the sequencing at those sites. The four sites showed clear single peak in their respective chromatograph, validating these polymorphisms. Interestingly, polymorphisms were identified among individuals belonging to the same population (Gonghyunjin-1, Gonghyunjin-2 Gonghyunjin-3 from Gonghyunjin, Korea). This suggests that the atp6-cox3 spacer is a strong candidate as a marker to quantify genetic diversity within and between populations of C. langsdorfii. Our new primer set (atp6-cox3_F and atp6-cox3_R) should be used to conduct a large-scale investigation of the population structure of C. langsdorfii to establish an efficient conservation strategy for this alga.

thumbnail
Fig 5. Sequence alignment of the atp6-cox3 spacer in Coccophora langsdorfii.

Asterisks represent sites with no polymorphism. Blue frames represent conserved regions. Red characters represent the reference polymorphism and blue bold characters represent individual polymorphism. Chromatograms illustrate the sequencing quality at the polymorphic sites (grey box) and 5 bp up- and downstream.

https://doi.org/10.1371/journal.pone.0187104.g005

Supporting information

S1 Fig. Plastid genome map of Coccophora langsdorfii.

Annotated genes are color-coded according to their function. Genes on the outside of the circles are transcribed clockwise and those on the inside counter clockwise. Abbreviations: IR, Inverse Repeats; SSC, Small Single-Copy; LSC, Large Single-Copy.

https://doi.org/10.1371/journal.pone.0187104.s001

(PDF)

S2 Fig. Mitochondrial genome map of Coccophora langsdorfii.

Annotated genes are color-coded according to their function. Genes on the outside of the circles are transcribed clockwise and those on the inside counter clockwise.

https://doi.org/10.1371/journal.pone.0187104.s002

(PDF)

S3 Fig. Full length comparison of 31 mitochondrial genomes of the class Phaeophyceae.

The innermost ring represents the mitochondrial genome map of Coccophora langsdorfii, annotated as in Fig 1. Every colored rings represent BLAST comparisons of a complete mitochondrial genomes against Coccophora langsdorfii. From the inside to the outside are represented the Fucales in red (Sargassum thunbergii, Sargassum vachellianum, Sargassum fusiforme, Sargassum hemiphyllum, Sargassum horneri, Sargassum muticum, Turbinaria ornata, Fucus vesiculosus), the Desmarestiales in blue (Desmarestia viridis), the Laminariales in brown (Undaria pinnatifida, Costaria costata, Laminaria digitata, Laminaria hyperborea, Saccharina angustata, Saccharina latissima, Saccharina coriaceae, Saccharina japonica, Saccharina sp. ye-C12, Saccharina religiosa, Saccharnia ochotensis, Saccharina japonicaXlatissima, Saccharina longissima, Saccharina longipedalis, Saccharina diabolica, Saccharina sp. ye-B), the Ectocarpales in green (Colpomenia peregrina, Scytosiphon lomentaria, Petalonia fascia, Pylaiella littoralis) and the Dictyotales in purple (Dictyota dichotoma). Intensity of the ring color denotes the degree of identity whereas gaps represent highly divergent regions.

https://doi.org/10.1371/journal.pone.0187104.s003

(PDF)

S4 Fig. Aligned sequences of the cox2 gene in the class Phaeophyceae.

White characters in a red box represent strict identity between all sequences. Red characters represent similarity in a group of sequences. Blue frame represent a conserved region. Green highlight represent the in frame insertion found in the Fucales, Desmarestiales, Ectocarpales and Laminariales.

https://doi.org/10.1371/journal.pone.0187104.s004

(PDF)

S5 Fig. Length in nucleotide of the mitochondrial cox2 gene in the different lineages of the Stramenopiles.

https://doi.org/10.1371/journal.pone.0187104.s005

(PDF)

S6 Fig. Plot of median nonsynonymous substitution rate (dN) of protein-coding genes encoded in the mitochondrial genome (in red) and the plastid genome (in green) with interquantile range (IQ).

https://doi.org/10.1371/journal.pone.0187104.s006

(PDF)

S1 Table. Blastp summary and unified proposed annotation.

Coccophora langsdorfii sequences were used as query for a blastp search against other brown algae plastid genomes.

https://doi.org/10.1371/journal.pone.0187104.s007

(PDF)

S2 Table. Summary of the accordance between the plastid encoded single gene trees topologies and the phylogeny of the Phaeophyceae.

TRUE indicates that the node is supported with above 50% Maximum Likelihood Bootstrap value. Underlined genes are more than 300 amino acids.

https://doi.org/10.1371/journal.pone.0187104.s008

(PDF)

S3 Table. Summary of the accordance between the mitochondria encoded single gene trees topologies and the phylogeny of the Phaeophyceae.

TRUE indicates that the node is supported with above 50% Maximum Likelihood Bootstrap value. Underlined genes are more than 300 amino acids.

https://doi.org/10.1371/journal.pone.0187104.s009

(PDF)

References

  1. 1. Oak JH. Fucales. In: Anon . editors. Algal flora of Korea. Volume 2, Number 2. Heterokontophyta: Phaeophyceae: Ishigeales, Dictyotales, Desmarestiales, Sphacelariales, Cutleriales, Ralfsiales, Laminariales. Incheon: National Institute of Biological Resources. 2010. pp. 111–172.
  2. 2. Yoshida T. Marine algae of Japan. 1st ed. Tokyo: Uchida Rokakuho Publishing Co., Ltd; 1998.
  3. 3. Titlyanov EA, Titlyanova TV, Belous OS. Useful marine plants of the Asia-Pacific Region countries. 1st ed. Vladivostok: Dalnauka; 2016.
  4. 4. Cho GY, Rousseau F, de Reviers B, Boo SM. Phylogenetic relationships within the Fucales (Phaeophyceae) assessed by the photosystem I coding psaA sequences. Phycologia. 2006;45: 512–519.
  5. 5. Cho SM, Lee SM, Ko YD, Mattio L, Boo SM. Molecular systematic reassessment of Sargassum (Fucales, Phaeophyceae) in Korea using four gene regions. Botanica Marina. 2012;55(5): 473–484.
  6. 6. Silberfeld T, Rousseau F, Reviers B de. An updated classification of brown algae (Ochrophyta, Phaeophyceae). Cryptogamie, Algologie. 2014;35: 117–156.
  7. 7. Status and distribution of endangered species. Ministry of Environment, Incheon: National Institute of Biological Resources. 2015. p. 344.
  8. 8. Brodie J, Andersen RA, Kawachi M, Millar AJK. Endangered algal species and how to protect them. Phycologia. 2009;48: 423–438.
  9. 9. Henry RJ. Evolution of DNA marker technology in plants. In: Henry RJ, editor. Molecular markers in plants. Ames, Iowa, USA: Wiley-Blackwell; 2013. pp 3–19.
  10. 10. Uwai S, Kogame K, Yoshida G, Kawai H, Ajisaka T. Geographical genetic structure and phylogeography of the Sargassum horneri / filicinum complex in Japan, based on the mitochondrial cox3 haplotype. Marine Biology. 2009;156: 901–911.
  11. 11. Uwai S, Nelson W, Neill K, Wang WD, Aguilar-Rosas LE, Boo SM, et al. Genetic diversity in Undaria pinnatifida (Laminariales, Phaeophyceae) deduced from mitochondria genes—origins and succession of introduced populations. Phycologia. 2006;45: 687–695.
  12. 12. Voisin M, Engel CR, Viard F. Differential shuffling of native genetic diversity across introduced regions in a brown alga: Aquaculture vs. maritime traffic effects. Proceedings of the National Academy of Sciences. 2005;102: 5432–5437. pmid:15802466
  13. 13. Sahu SK, Thangaraj M, Kathiresan K. DNA extraction protocol for plants with high levels of secondary metabolites and polysaccharides without using liquid nitrogen and phenol. ISRN Molecular Biology. 2012;2012: 1–6. pmid:27335662
  14. 14. Song HJ, Lee J, Graf L, Rho M, Qiu H, Bhattacharya D, et al. A novice’s guide to analyzing NGS-derived organelle and metagenome data. ALGAE. 2016;31: 137–154.
  15. 15. Chevreux B, Wetter T, and Suhai S. Genome sequence assembly using trace signals and additional sequence information. Computer Science and Biology: Proceedings of the German Conference on Bioinformatics (GCB). 1999; 99, pp. 45–56.
  16. 16. Altschul S. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research. 1997;25: 3389–3402. pmid:9254694
  17. 17. Kurtz S, Phillippy A, Delcher AL, Smoot M, Shumway M, Antonescu C, Salzberg SL. Versatile and open software for comparing large genomes. Genome Biology. 2004;5: R12. pmid:14759262
  18. 18. Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, et al. Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics. 2012;28: 1647–1649. pmid:22543367
  19. 19. Wyman SK, Jansen RK, Boore JL. Automatic annotation of organellar genomes with DOGMA. Bioinformatics. 2004;20: 3252–3255. pmid:15180927
  20. 20. Schattner P, Brooks AN, Lowe TM. The tRNAscan-SE, snoscan and snoGPS web servers for the detection of tRNAs and snoRNAs. Nucleic Acids Research. 2005;33: W686–W689. pmid:15980563
  21. 21. Lagesen K, Hallin P, Rodland EA, Staerfeldt H-H, Rognes T, Ussery DW. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Research. 2007;35: 3100–3108. pmid:17452365
  22. 22. Conant GC, Wolfe KH. GenomeVx: simple web-based creation of editable circular chromosome maps. Bioinformatics. 2008;24: 861–862. pmid:18227121
  23. 23. Darling AE, Mau B, Perna NT. progressiveMauve: Multiple Genome Alignment with Gene Gain, Loss and Rearrangement. PLoS ONE. 2010;5: e11147. pmid:20593022
  24. 24. Guy L, Roat Kultima J, Andersson SGE. genoPlotR: comparative gene and genome visualization in R. Bioinformatics. 2010;26: 2334–2335. pmid:20624783
  25. 25. Hilker R, Sickinger C, Pedersen CNS, Stoye J. UniMoG—a unifying framework for genomic distance calculation and sorting based on DCJ. Bioinformatics. 2012;28: 2509–2511. pmid:22815356
  26. 26. Alikhan N-F, Petty NK, Ben Zakour NL, Beatson SA. BLAST Ring Image Generator (BRIG): simple prokaryote genome comparisons. BMC Genomics. 2011;12: 402 pmid:21824423
  27. 27. Katoh K, Standley DM. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in performance and usability. Molecular Biology and Evolution. 2013;30: 772–780. pmid:23329690
  28. 28. Abascal F, Zardoya R, Telford MJ. TranslatorX: multiple alignment of nucleotide sequences guided by amino acid translations. Nucleic Acids Research. 2010;38: W7–W13. pmid:20435676
  29. 29. Vaidya G, Lohman DJ, Meier R. SequenceMatrix: concatenation software for the fast assembly of multi-gene datasets with character set and codon information. Cladistics. 2011;27: 171–180.
  30. 30. Nguyen L-T, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating Maximum-Likelihood phylogenies. Molecular Biology and Evolution. 2015;32: 268–274. pmid:25371430
  31. 31. Minh BQ, Nguyen MAT, von Haeseler A. Ultrafast approximation for phylogenetic bootstrap. Molecular Biology and Evolution. 2013;30: 1188–1195. pmid:23418397
  32. 32. Charif D, Lobry JR. SeqinR 1.0–2: a contributed package to the R project for statistical computing devoted to biological sequences retrieval and analysis. In: Bastolla U, Porto M, Roman HE Vendruscolo M, editors. Structural approaches to sequence evolution: Molecules, networks, populations. New York: Springer Verlag; 2007. pp. 207–232.
  33. 33. Stephens TG, Bhattacharya D, Ragan MA, Chan CX. PhySortR: a fast, flexible tool for sorting phylogenetic trees in R. PeerJ. 2016;4: e2038. pmid:27190724
  34. 34. Roy A, Kucukural A, Zhang Y. I-TASSER: a unified platform for automated protein structure and function prediction. Nature Protocols. 2010;5: 725–738. pmid:20360767
  35. 35. Yang J, Yan R, Roy A, Xu D, Poisson J, Zhang Y. The I-TASSER Suite: protein structure and function prediction. Nature Methods. 2014;12: 7–8. pmid:25549265
  36. 36. Zhang Y. I-TASSER server for protein 3D structure prediction. BMC Bioinformatics. 2008;9: 40. pmid:18215316
  37. 37. Wynne MJ, Andersen RA, Graf L, Yoon HS. Aureoscheda, a new genus of marine Pelagophyceae from the Bahamas, Caribbean Sea. Phycologia. 2014;53: 513–522.
  38. 38. Wicke S, Schneeweiss GM, dePamphilis CW, Müller KF, Quandt D. The evolution of the plastid chromosome in land plants: gene content, gene order, gene function. Plant Molecular Biology. 2011;76: 273–297. pmid:21424877
  39. 39. Janouškovec J, Liu S-L, Martone PT, Carré W, Leblanc C, Collén J, et al. Evolution of red algal plastid genomes: ancient architectures, introns, horizontal gene transfer, and taxonomic utility of plastid markers. PLoS ONE. 2013;8: e59001. pmid:23536846
  40. 40. Lee J, Cho CH, Park SI, Choi JW, Song HS, West JA, et al. Parallel evolution of highly conserved plastid genome architecture in red seaweeds and seed plants. BMC Biology. 2016;14: 75. pmid:27589960
  41. 41. Silberfeld T, Leigh JW, Verbruggen H, Cruaud C, de Reviers B, Rousseau F. A multi-locus time-calibrated phylogeny of the brown algae (Heterokonta, Ochrophyta, Phaeophyceae): Investigating the evolutionary nature of the “brown algal crown radiation.” Molecular Phylogenetics and Evolution. 2010;56: 659–674. pmid:20412862
  42. 42. Cho GY, Lee SH, Boo SM. A new brown algal order, Ishigeales (Phaeophyceae), established on the basis of plastid protein-coding rbcL, psaA, and psbA region comparisons. Journal of Phycology. 2004;40: 921–936.
  43. 43. Le Corguillé G, Pearson G, Valente M, Viegas C, Gschloessl B, Corre E, et al. Plastid genomes of two brown algae, Ectocarpus siliculosus and Fucus vesiculosus: further insights on the evolution of red-algal derived plastids. BMC Evolutionary Biology. 2009;9: 253. pmid:19835607
  44. 44. Liu F, Pang S. Chloroplast genome of Sargassum horneri (Sargassaceae, Phaeophyceae): comparative chloroplast genomics of brown algae. Journal of Applied Phycology. 2016;28: 1419–1426.
  45. 45. Yang JH, Graf L, Cho CH, Jeon BH, Kim JH, Yoon HS. Complete plastid genome of an ecologically important brown alga Sargassum thunbergii (Fucales, Phaeophyceae). Marine Genomics. 2016;28: 17–20. pmid:27012360
  46. 46. Zhang L, Wang X, Liu T, Wang H, Wang G, Chi S, et al. Complete plastid genome of the brown alga Costaria costata (Laminariales, Phaeophyceae). Escriva H, editor. PLOS ONE. 2015;10: e0140144. pmid:26444909
  47. 47. Wang X, Shao Z, Fu W, Yao J, Hu Q, Duan D. Chloroplast genome of one brown seaweed, Saccharina japonica (Laminariales, Phaeophyta): Its structural features and phylogenetic analyses with other photosynthetic plastids. Marine Genomics. 2013;10: 1–9. pmid:23305622
  48. 48. Zhang L, Wang X, Liu T, Wang G, Chi S, Liu C, et al. Complete plastid genome sequence of the brown alga Undaria pinnatifida. PLoS ONE. 2015;10: e0139366. pmid:26426800
  49. 49. Oudot-Le Secq M-PO-L, Goër SL, Stam WT, Olsen JL. Complete mitochondrial genomes of the three brown algae (Heterokonta: Phaeophyceae) Dictyota dichotoma, Fucus vesiculosus and Desmarestia viridis. Current Genetics. 2006;49: 47–58. pmid:16317568
  50. 50. Liu F, Pang S. Mitochondrial genome of Turbinaria ornata (Sargassaceae, Phaeophyceae): comparative mitogenomics of brown algae. Current Genetics. 2015;61: 621–631. pmid:25893565
  51. 51. Liu F, Pang S, Luo M. Complete mitochondrial genome of the brown alga Sargassum fusiforme (Sargassaceae, Phaeophyceae): genome architecture and taxonomic consideration. Mitochondrial DNA. 2016;27: 1158–1160. pmid:24989050
  52. 52. Liu F, Pang S, Chen W. Complete mitochondrial genome of the brown alga Sargassum hemiphyllum (Sargassaceae, Phaeophyceae): comparative analyses. Mitochondrial DNA. 2016;27: 1468–1470. pmid:25162799
  53. 53. Liu F, Pang S, Li X, Li J. Complete mitochondrial genome of the brown alga Sargassum horneri (Sargassaceae, Phaeophyceae): genome organization and phylogenetic analyses. Journal of Applied Phycology. 2015;27: 469–478.
  54. 54. Liu F, Pang S. Complete mitochondrial genome of the invasive brown alga Sargassum muticum (Sargassaceae, Phaeophyceae). Mitochondrial DNA. 2016;27: 1129–1130. pmid:24983154
  55. 55. Liu F, Pang S. Mitochondrial genome of Sargassum thunbergii: conservation and variability of mitogenomes within the subgenus Bactrophycus. Mitochondrial DNA. 2015; 1–3. pmid:25690051
  56. 56. Bi Y, Zhou Z. Complete mitochondrial genome of the brown alga Sargassum vachellianum (Sargassaceae, Phaeophyceae). Mitochondrial DNA. 2015; 1–2. pmid:26099977
  57. 57. Qu J-Q, Liu C, Wang X-M, Zhang Z-B, Chi S, Liu T. Complete mitochondrial genome of Costaria costata shows conservative evolution in Laminariales. Mitochondrial DNA. 2015;26: 919–920. pmid:24409887
  58. 58. Oudot-Le Secq M-P, Kloareg B, Loiseaux-De Goër S. The mitochondrial genome of the brown alga Laminaria digitata: a comparative analysis. European Journal of Phycology. 2002;37: 163–172.
  59. 59. Zhang J, Wang X, Liu C, Jin Y, Liu T. The complete mitochondrial genomes of two brown algae (Laminariales, Phaeophyceae) and phylogenetic analysis within Laminaria. Journal of Applied Phycology. 2013;25: 1247–1253.
  60. 60. Yotsukura N, Shimizu T, Katayama T, Druehl LD. Mitochondrial DNA sequence variation of four Saccharina species (Laminariales, Phaeophyceae) growing in Japan. Journal of Applied Phycology. 2010;22: 243–251.
  61. 61. Zhang J, Li N, Zhang Z, Liu T. Structure analysis of the complete mitochondrial genome in cultivation variety “Rongfu.” Journal of Ocean University of China. 2011;10: 351–356.
  62. 62. Wang S, Fan X, Guan Z, Xu D, Zhang X, Wang D, et al. Sequencing of complete mitochondrial genome of Saccharina latissima ye-C14. Mitochondrial DNA. 2015; 1–2. pmid:25629480
  63. 63. Li T-Y, Qu J-Q, Feng Y-J, Liu C, Chi S, Liu T. Complete mitochondrial genome of Undaria pinnatifida (Alariaceae, Laminariales, Phaeophyceae). Mitochondrial DNA. 2015;26: 953–954. pmid:24409911
  64. 64. Liu F, Pang S, Li J, Li X. Complete mitochondrial genome of the brown alga Colpomenia peregrina (Scytosiphonaceae, Phaeophyceae): genome characterization and comparative analyses. Mitochondrial DNA. 2014; 1–3. pmid:25208185
  65. 65. Cock JM, Sterck L, Rouzé P, Scornet D, Allen AE, Amoutzias G, et al. The Ectocarpus genome and the independent evolution of multicellularity in brown algae. Nature. 2010;465: 617–621. pmid:20520714
  66. 66. Liu F, Pang S. Mitochondrial phylogenomics reveals a close relationship between Petalonia fascia (Scytosiphonaceae, Phaeophyceae) and Ectocarpus siliculosus. Journal of Applied Phycology. 2015;27: 1021–1028.
  67. 67. Oudot-Le Secq M-P, Fontaine J-M, Rousvoal S, Kloareg B, Loiseaux-de Goër S. The complete sequence of a brown algal mitochondrial genome, the Ectocarpale Pylaiella littoralis (L.) Kjellm. Journal of Molecular Evolution. 2001;53: 80–88. pmid:11479679
  68. 68. Liu F, Pang S. Complete mitochondrial genome of the brown alga Scytosiphon lomentaria (Scytosiphonaceae, Phaeophyceae). Mitochondrial DNA. 2016;27: 1494–1496. pmid:25186060
  69. 69. Burger G, Zhu Y, Littlejohn TG, Greenwood SJ, Schnare MN, Lang BF, et al. Complete sequence of the mitochondrial genome of Tetrahymena pyriformis and comparison with Paramecium aurelia mitochondrial DNA. Journal of Molecular Biology. 2000;297: 365–380. pmid:10715207
  70. 70. de Graaf RM, van Alen TA, Dutilh BE, Kuiper JW, van Zoggel HJ, Huynh M, et al. The mitochondrial genomes of the ciliates Euplotes minuta and Euplotes crassus. BMC Genomics. 2009;10: 514. pmid:19895685
  71. 71. Funes S, Davidson E, Reyes-Prieto A, Magallón S, Herion P, King MP, et al. A green algal apicoplast ancestor. Science. 2002;298: 2155–2155. pmid:12481129
  72. 72. Waller RF, Keeling PJ. Alveolate and chlorophycean mitochondrial cox2 genes split twice independently. Gene. 2006;383: 33–37. pmid:16987614
  73. 73. Pérez-Martínez X, Antaramian A, Vázquez-Acevedo M, Funes S, Tolkunova E, d’Alayer J, et al. Subunit II of cytochrome c oxidase in chlamydomonad algae is a heterodimer encoded by two independent nuclear genes. Journal of Biological Chemistry. 2001;276: 11302–11309. pmid:11094061
  74. 74. Szafranski P. Evolutionarily recent, insertional fission of mitochondrial cox2 into complementary genes in bilaterian Metazoa. BMC Genomics. 2017;18. pmid:28359330
  75. 75. Gawryluk RM, Gray MW. A split and rearranged nuclear gene encoding the iron-sulfur subunit of mitochondrial succinate dehydrogenase in Euglenozoa. BMC Research Notes. 2009;2: 16. pmid:19192292
  76. 76. Adams KL, Ong HC, Palmer JD. Mitochondrial gene transfer in pieces: fission of the ribosomal protein gene rpl2 and partial or complete gene transfer to the nucleus. Molecular Biology and Evolution. 2001;18: 2289–2297. pmid:11719578
  77. 77. Kadenbach B, Stroh A, Hüther F-J, Reimann A, Steverding D. Evolutionary aspects of cytochrome c oxidase. Journal of Bioenergetics and Biomembranes. 1991;23: 321–334. pmid:1646800
  78. 78. Pecina P, Houstková H, Hansíková H, Zeman J, Houstek J. Genetic defects of cytochrome c oxidase assembly. Physiological Research. 2004;53 Suppl 1: S213–223.
  79. 79. Yang EC, Boo GH, Kim HJ, Cho SM, Boo SM, Andersen RA, et al. Supermatrix data highlight the phylogenetic relationships of photosynthetic Stramenopiles. Protist. 2012;163: 217–231. pmid:22001261
  80. 80. Smith DR. Mutation rates in plastid genomes: they are lower than you might think. Genome Biology and Evolution. 2015;7: 1227–1234. pmid:25869380
  81. 81. Yoon HS, Lee JY, Boo SM, Bhattacharya D. Phylogeny of Alariaceae, Laminariaceae, and Lessoniaceae (Phaeophyceae) based on plastid-encoded RuBisCo spacer and nuclear-encoded ITS sequence comparisons. Molecular Phylogenetics and Evolution. 2001;21: 231–243. pmid:11697918
  82. 82. Jackson C, Salomaki ED, Lane CE, Saunders GW. Kelp transcriptomes provide robust support for interfamilial relationships and revision of the little known Arthrothamnaceae (Laminariales). Journal of Phycology. 2017;53: 1–6. pmid:27704553