Genomic factors shape carbon and nitrogen metabolic niche breadth across Saccharomycotina yeasts.

Organisms exhibit extensive variation in ecological niche breadth, from very narrow (specialists) to very broad (generalists). Two general paradigms have been proposed to explain this variation: (i) trade-offs between performance efficiency and breadth and (ii) the joint influence of extrinsic (environmental) and intrinsic (genomic) factors. We assembled genomic, metabolic, and ecological data from nearly all known species of the ancient fungal subphylum Saccharomycotina (1154 yeast strains from 1051 species), grown in 24 different environmental conditions, to examine niche breadth evolution. We found that large differences in the breadth of carbon utilization traits between yeasts stem from intrinsic differences in genes encoding specific metabolic pathways, but we found limited evidence for trade-offs. These comprehensive data argue that intrinsic factors shape niche breadth variation in microbes.

Giants among Cnidaria: Large Nuclear Genomes and Rearranged Mitochondrial Genomes in Siphonophores.

Siphonophores (Cnidaria: Hydrozoa) are abundant predators found throughout the ocean and are important constituents of the global zooplankton community. They range in length from a few centimeters to tens of meters. They are gelatinous, fragile, and difficult to collect, so many aspects of the biology of these roughly 200 species remain poorly understood. To survey siphonophore genome diversity, we performed Illumina sequencing of 32 species sampled broadly across the phylogeny. Sequencing depth was sufficient to estimate nuclear genome size from k-mer spectra in six specimens, ranging from 0.7 to 2.3 Gb, with heterozygosity estimates between 0.69% and 2.32%. Incremental k-mer counting indicates k-mer peaks can be absent with nearly 20× read coverage, suggesting minimum genome sizes range from 1.4 to 5.6 Gb in the 25 samples without peaks in the k-mer spectra. This work confirms most siphonophore nuclear genomes are large relative to the genomes of other cnidarians, but also identifies several with reduced size that are tractable targets for future siphonophore nuclear genome assembly projects. We also assembled complete mitochondrial genomes for 33 specimens from these new data, indicating a conserved gene order shared among nonsiphonophore hydrozoans, Cystonectae, and some Physonectae, revealing the ancestral mitochondrial gene order of siphonophores. Our results also suggest extensive rearrangement of mitochondrial genomes within other Physonectae and in Calycophorae. Though siphonophores comprise a small fraction of cnidarian species, this survey greatly expands our understanding of cnidarian genome diversity. This study further illustrates both the importance of deep phylogenetic sampling and the utility of k-mer-based genome skimming in understanding the genomic diversity of a clade.

Enhancing neural encoding models for naturalistic perception with a multi-level integration of deep neural networks and cortical networks.

Cognitive neuroscience aims to develop computational models that can accurately predict and explain neural responses to sensory inputs in the cortex. Recent studies attempt to leverage the representation power of deep neural networks (DNNs) to predict the brain response and suggest a correspondence between artificial and biological neural networks in their feature representations. However, typical voxel-wise encoding models tend to rely on specific networks designed for computer vision tasks, leading to suboptimal brain-wide correspondence during cognitive tasks. To address this challenge, this work proposes a novel approach that upgrades voxel-wise encoding models through multi-level integration of features from DNNs and information from brain networks. Our approach combines DNN feature-level ensemble learning and brain atlas-level model integration, resulting in significant improvements in predicting whole-brain neural activity during naturalistic video perception. Furthermore, this multi-level integration framework enables a deeper understanding of the brain's neural representation mechanism, accurately predicting the neural response to complex visual concepts. We demonstrate that neural encoding models can be optimized by leveraging a framework that integrates both data-driven approaches and theoretical insights into the functional structure of the cortical networks.

Cryptic diversity begets challenges and opportunities in biodiversity research.

How many species of life are there on Earth? This is a question that we want to know but cannot yet answer. Some scholars speculate that the number of species may reach 2.2 billion when considering cryptic diversity and that each morphology-based insect species may contain an average of 3.1 cryptic species. With nearly two million described species, such high estimates of cryptic diversity would suggest that cryptic species are widespread. The development of molecular species delimitation has led to the discovery of a large number of cryptic species, and cryptic biodiversity has gradually entered our field of vision and attracted more attention. This paper introduces the concept of cryptic species, how they evolve, and methods by which they may be discovered and confirmed, and provides theoretical and methodological guidance for the study of hidden species. A workflow of how to confirm cryptic species is provided. In addition, the importance and reliability of multi-evidence-based integrated taxonomy are reaffirmed as a way to better standardize decision-making processes. Special focus on cryptic diversity and increased funding for taxonomy is needed to ensure that cryptic species in hyperdiverse groups are discoverable and described. An increased focus on cryptic species in the future will naturally arise as more difficult groups are studied, and thereby, we may finally better understand the rules governing the evolution and maintenance of cryptic biodiversity.

Quantification of Hypsarrhythmia in Infantile Spasmatic EEG: A Large Cohort Study.

Infantile spasms (IS) is a neurological disorder causing mental and/or developmental retardation in many infants. Hypsarrhythmia is a typical symptom in the electroencephalography (EEG) signals with IS. Long-term EEG/video monitoring is most frequently employed in clinical practice for IS diagnosis, from which manual screening of hypsarrhythmia is time consuming and lack of sufficient reliability. This study aims to identify potential biomarkers for automatic IS diagnosis by quantitative analysis of the EEG signals. A large cohort of 101 IS patients and 155 healthy controls (HC) were involved. Typical hypsarrhythmia and non-hypsarrhythmia EEG signals were annotated, and normal EEG were randomly picked from the HC. Root mean square (RMS), teager energy (TE), mean frequency, sample entropy (SamEn), multi-channel SamEn, multi-scale SamEn, and nonlinear correlation coefficient were computed in each sub-band of the three EEG signals, and then compared using either a one-way ANOVA or a Kruskal-Wallis test (based on their distribution) and the receiver operating characteristic (ROC) curves. The effects of infant age on these features were also investigated. For most of the employed features, significant ( ) differences were observed between hypsarrhythmia EEG and non-hypsarrhythmia EEG or HC, which seem to increase with increased infant age. RMS and TE produce the best classification in the delta and theta bands, while entropy features yields the best performance in the gamma band. Our study suggests RMS and TE (delta and theta bands) and entropy features (gamma band) to be promising biomarkers for automatic detection of hypsarrhythmia in long-term EEG monitoring. The findings of our study indicate the feasibility of automated IS diagnosis using artificial intelligence.

Multiple Origins of Bioluminescence in Beetles and Evolution of Luciferase Function.

Bioluminescence in beetles has long fascinated biologists, with diverse applications in biotechnology. To date, however, our understanding of its evolutionary origin and functional variation mechanisms remains poor. To address these questions, we obtained high-quality reference genomes of luminous and nonluminous beetles in 6 Elateroidea families. We then reconstructed a robust phylogenetic relationship for all luminous families and related nonluminous families. Comparative genomic analyses and biochemical functional experiments suggested that gene evolution within Elateroidea played a crucial role in the origin of bioluminescence, with multiple parallel origins observed in the luminous beetle families. While most luciferase-like proteins exhibited a conserved nonluminous amino acid pattern (TLA346 to 348) in the luciferin-binding sites, luciferases in the different luminous beetle families showed divergent luminous patterns at these sites (TSA/CCA/CSA/LVA). Comparisons of the structural and enzymatic properties of ancestral, extant, and site-directed mutant luciferases further reinforced the important role of these sites in the trade-off between acyl-CoA synthetase and luciferase activities. Furthermore, the evolution of bioluminescent color demonstrated a tendency toward hypsochromic shifts and variations among the luminous families. Taken together, our results revealed multiple parallel origins of bioluminescence and functional divergence within the beetle bioluminescent system.

Neural control of lexical tone production in human laryngeal motor cortex.

In tonal languages, which are spoken by nearly one-third of the world's population, speakers precisely control the tension of vocal folds in the larynx to modulate pitch in order to distinguish words with completely different meanings. The specific pitch trajectories for a given tonal language are called lexical tones. Here, we used high-density direct cortical recordings to determine the neural basis of lexical tone production in native Mandarin-speaking participants. We found that instead of a tone category-selective coding, local populations in the bilateral laryngeal motor cortex (LMC) encode articulatory kinematic information to generate the pitch dynamics of lexical tones. Using a computational model of tone production, we discovered two distinct patterns of population activity in LMC commanding pitch rising and lowering. Finally, we showed that direct electrocortical stimulation of different local populations in LMC evoked pitch rising and lowering during tone production, respectively. Together, these results reveal the neural basis of vocal pitch control of lexical tones in tonal languages.

Dissecting neural computations in the human auditory pathway using deep neural networks for speech.

The human auditory system extracts rich linguistic abstractions from speech signals. Traditional approaches to understanding this complex process have used linear feature-encoding models, with limited success. Artificial neural networks excel in speech recognition tasks and offer promising computational models of speech processing. We used speech representations in state-of-the-art deep neural network (DNN) models to investigate neural coding from the auditory nerve to the speech cortex. Representations in hierarchical layers of the DNN correlated well with the neural activity throughout the ascending auditory system. Unsupervised speech models performed at least as well as other purely supervised or fine-tuned models. Deeper DNN layers were better correlated with the neural activity in the higher-order auditory cortex, with computations aligned with phonemic and syllabic structures in speech. Accordingly, DNN models trained on either English or Mandarin predicted cortical responses in native speakers of each language. These results reveal convergence between DNN model representations and the biological auditory pathway, offering new approaches for modeling neural coding in the auditory cortex.

Extensive intragenomic variation in the internal transcribed spacer region of fungi.

Fungi are among the most biodiverse organisms in the world. Accurate species identification is imperative for studies on fungal ecology and evolution. The internal transcribed spacer (ITS) rDNA region has been widely accepted as the universal barcode for fungi. However, several recent studies have uncovered intragenomic sequence variation within the ITS in multiple fungal species. Here, we mined the genome of 2414 fungal species to determine the prevalence of intragenomic variation and found that the genomes of 641 species, about one-quarter of the 2414 species examined, contained multiple ITS copies. Of those 641 species, 419 (∼65%) contained variation among copies revealing that intragenomic variation is common in fungi. We proceeded to show how these copies could result in the erroneous description of hundreds of fungal species and skew studies evaluating environmental DNA (eDNA) especially when making diversity estimates. Additionally, many genomes were found to be contaminated, especially those of unculturable fungi.

Genomic and ecological factors shaping specialism and generalism across an entire subphylum.

Organisms exhibit extensive variation in ecological niche breadth, from very narrow (specialists) to very broad (generalists). Paradigms proposed to explain this variation either invoke trade-offs between performance efficiency and breadth or underlying intrinsic or extrinsic factors. We assembled genomic (1,154 yeast strains from 1,049 species), metabolic (quantitative measures of growth of 843 species in 24 conditions), and ecological (environmental ontology of 1,088 species) data from nearly all known species of the ancient fungal subphylum Saccharomycotina to examine niche breadth evolution. We found large interspecific differences in carbon breadth stem from intrinsic differences in genes encoding specific metabolic pathways but no evidence of trade-offs and a limited role of extrinsic ecological factors. These comprehensive data argue that intrinsic factors driving microbial niche breadth variation.

Evolutionary origin, population diversity, and diagnostics for a cryptic hybrid pathogen.

Cryptic fungal pathogens pose significant identification and disease management challenges due to their morphological resemblance to known pathogenic species while harboring genetic and (often) infectionrelevant trait differences. The cryptic fungal pathogen Aspergillus latus, an allodiploid hybrid originating from Aspergillus spinulosporus and an unknown close relative of Aspergillus quadrilineatus within section Nidulantes, remains poorly understood. The absence of accurate diagnostics for A. latus has led to misidentifications, hindering epidemiological studies and the design of effective treatment plans. We conducted an in-depth investigation of the genomes and phenotypes of 44 globally distributed isolates (41 clinical isolates and three type strains) from Aspergillus section Nidulantes. We found that 21 clinical isolates were A. latus; notably, standard methods of pathogen identification misidentified all A. latus isolates. The remaining isolates were identified as A. spinulosporus (8), A. quadrilineatus (1), or A. nidulans (11). Phylogenomic analyses shed light on the origin of A. latus, indicating one or two hybridization events gave rise to the species during the Miocene, approximately 15.4 to 8.8 million years ago. Characterizing the A. latus pangenome uncovered substantial genetic diversity within gene families and biosynthetic gene clusters. Transcriptomic analysis revealed that both parental genomes are actively expressed in nearly equal proportions and respond to environmental stimuli. Further investigation into infection-relevant chemical and physiological traits, including drug resistance profiles, growth under oxidative stress conditions, and secondary metabolite biosynthesis, highlight distinct phenotypic profiles of the hybrid A. latus compared to its parental and closely related species. Leveraging our comprehensive genomic and phenotypic analyses, we propose five genomic and phenotypic markers as diagnostics for A. latus species identification. These findings provide valuable insights into the evolutionary origin, genomic outcome, and phenotypic implications of hybridization in a cryptic fungal pathogen, thus enhancing our understanding of the underlying processes contributing to fungal pathogenesis. Furthermore, our study underscores the effectiveness of extensive genomic and phenotypic analyses as a promising approach for developing diagnostics applicable to future investigations of cryptic and emerging pathogens.

Latent neural dynamics encode temporal context in speech.

Direct neural recordings from human auditory cortex have demonstrated encoding for acoustic-phonetic features of consonants and vowels. Neural responses also encode distinct acoustic amplitude cues related to timing, such as those that occur at the onset of a sentence after a silent period or the onset of the vowel in each syllable. Here, we used a group reduced rank regression model to show that distributed cortical responses support a low-dimensional latent state representation of temporal context in speech. The timing cues each capture more unique variance than all other phonetic features and exhibit rotational or cyclical dynamics in latent space from activity that is widespread over the superior temporal gyrus. We propose that these spatially distributed timing signals could serve to provide temporal context for, and possibly bind across time, the concurrent processing of individual phonetic features, to compose higher-order phonological (e.g. word-level) representations.

Decoding and synthesizing tonal language speech from brain activity.

Recent studies have shown that the feasibility of speech brain-computer interfaces (BCIs) as a clinically valid treatment in helping nontonal language patients with communication disorders restore their speech ability. However, tonal language speech BCI is challenging because additional precise control of laryngeal movements to produce lexical tones is required. Thus, the model should emphasize the features from the tonal-related cortex. Here, we designed a modularized multistream neural network that directly synthesizes tonal language speech from intracranial recordings. The network decoded lexical tones and base syllables independently via parallel streams of neural network modules inspired by neuroscience findings. The speech was synthesized by combining tonal syllable labels with nondiscriminant speech neural activity. Compared to commonly used baseline models, our proposed models achieved higher performance with modest training data and computational costs. These findings raise a potential strategy for approaching tonal language speech restoration.

Incongruence in the phylogenomics era.

Genome-scale data and the development of novel statistical phylogenetic approaches have greatly aided the reconstruction of a broad sketch of the tree of life and resolved many of its branches. However, incongruence - the inference of conflicting evolutionary histories - remains pervasive in phylogenomic data, hampering our ability to reconstruct and interpret the tree of life. Biological factors, such as incomplete lineage sorting, horizontal gene transfer, hybridization, introgression, recombination and convergent molecular evolution, can lead to gene phylogenies that differ from the species tree. In addition, analytical factors, including stochastic, systematic and treatment errors, can drive incongruence. Here, we review these factors, discuss methodological advances to identify and handle incongruence, and highlight avenues for future research.

The Transcriptional Repressor PerR Senses Sulfane Sulfur by Cysteine Persulfidation at the Structural Zn2+ Site in Synechococcus sp. PCC7002.

Cyanobacteria can perform both anoxygenic and oxygenic photosynthesis, a characteristic which ensured that these organisms were crucial in the evolution of the early Earth and the biosphere. Reactive oxygen species (ROS) produced in oxygenic photosynthesis and reactive sulfur species (RSS) produced in anoxygenic photosynthesis are closely related to intracellular redox equilibrium. ROS comprise superoxide anion (O2●-), hydrogen peroxide (H2O2), and hydroxyl radicals (●OH). RSS comprise H2S and sulfane sulfur (persulfide, polysulfide, and S8). Although the sensing mechanism for ROS in cyanobacteria has been explored, that of RSS has not been elucidated. Here, we studied the function of the transcriptional repressor PerR in RSS sensing in Synechococcus sp. PCC7002 (PCC7002). PerR was previously reported to sense ROS; however, our results revealed that it also participated in RSS sensing. PerR repressed the expression of prxI and downregulated the tolerance of PCC7002 to polysulfide (H2Sn). The reporter system indicated that PerR sensed H2Sn. Cys121 of the Cys4:Zn2+ site, which contains four cysteines (Cys121, Cys124, Cys160, and Cys163) bound to one zinc atom, could be modified by H2Sn to Cys121-SSH, as a result of which the zinc atom was released from the site. Moreover, Cys19 could also be modified by polysulfide to Cys19-SSH. Thus, our results reveal that PerR, a representative of the Cys4 zinc finger proteins, senses H2Sn. Our findings provide a new perspective to explore the adaptation strategy of cyanobacteria in Proterozoic and contemporary sulfurization oceans.

A comparative analysis of mitochondrial ORFs provides new insights on expansion of mitochondrial genome size in Arcidae.

BACKGROUND: Arcidae, comprising about 260 species of ark shells, is an ecologically and economically important lineage of bivalve mollusks. Interestingly, mitochondrial genomes of several Arcidae species are 2-3 times larger than those of most bilaterians, and are among the largest bilaterian mitochondrial genomes reported to date. The large mitochondrial genome size is mainly due to expansion of unassigned regions (regions that are functionally unassigned). Previous work on unassigned regions of Arcidae mtDNA genomes has focused on nucleotide-level analyses to observe sequence characteristics, however the origin of expansion remains unclear. RESULTS: We assembled six new mitogenomes and sequenced six transcriptomes of Scapharca broughtonii to identify conserved functional ORFs that are transcribed in unassigned regions. Sixteen lineage-specific ORFs with different copy numbers were identified from seven Arcidae species, and 11 of 16 ORFs were expressed and likely biologically active. Unassigned regions of 32 Arcidae mitogenomes were compared to verify the presence of these novel mitochondrial ORFs and their distribution. Strikingly, multiple structural analyses and functional prediction suggested that these additional mtDNA-encoded proteins have potential functional significance. In addition, our results also revealed that the ORFs have a strong connection to the expansion of Arcidae mitochondrial genomes and their large-scale duplication play an important role in multiple expansion events. We discussed the possible origin of ORFs and hypothesized that these ORFs may originate from duplication of mitochondrial genes. CONCLUSIONS: The presence of lineage-specific mitochondrial ORFs with transcriptional activity and potential functional significance supports novel features for Arcidae mitochondrial genomes. Given our observation and analyses, these ORFs may be products of mitochondrial gene duplication. These findings shed light on the origin and function of novel mitochondrial genes in bivalves and provide new insights into evolution of mitochondrial genome size in metazoans.

Contrasting modes of macro and microsynteny evolution in a eukaryotic subphylum.

Examination of the changes in order and arrangement of homologous genes is key for understanding the mechanisms of genome evolution in eukaryotes. Previous comparisons between eukaryotic genomes have revealed considerable conservation across species that diverged hundreds of millions of years ago (e.g., vertebrates,1,2,3 bilaterian animals,4,5 and filamentous fungi6). However, understanding how genome organization evolves within and between eukaryotic major lineages remains underexplored. We analyzed high-quality genomes of 120 representative budding yeast species (subphylum Saccharomycotina) spanning ∼400 million years of eukaryotic evolution to examine how their genome organization evolved and to compare it with the evolution of animal and plant genome organization.7 We found that the decay of both macrosynteny (the conservation of homologous chromosomes) and microsynteny (the conservation of local gene content and order) was strongly associated with evolutionary divergence across budding yeast major clades. However, although macrosynteny decayed very fast, within ∼100 million years, the microsynteny of many genes-especially genes in metabolic clusters (e.g., in the GAL gene cluster8)-was much more deeply conserved both within major clades and across the subphylum. We further found that when genomes with similar evolutionary divergence times were compared, budding yeasts had lower macrosynteny conservation than animals and filamentous fungi but higher conservation than angiosperms. In contrast, budding yeasts had levels of microsynteny conservation on par with mammals, whereas angiosperms exhibited very low conservation. Our results provide new insight into the tempo and mode of the evolution of gene and genome organization across an entire eukaryotic subphylum.

OrthoSNAP: A tree splitting and pruning algorithm for retrieving single-copy orthologs from gene family trees.

Molecular evolution studies, such as phylogenomic studies and genome-wide surveys of selection, often rely on gene families of single-copy orthologs (SC-OGs). Large gene families with multiple homologs in 1 or more species-a phenomenon observed among several important families of genes such as transporters and transcription factors-are often ignored because identifying and retrieving SC-OGs nested within them is challenging. To address this issue and increase the number of markers used in molecular evolution studies, we developed OrthoSNAP, a software that uses a phylogenetic framework to simultaneously split gene families into SC-OGs and prune species-specific inparalogs. We term SC-OGs identified by OrthoSNAP as SNAP-OGs because they are identified using a splitting and pruning procedure analogous to snapping branches on a tree. From 415,129 orthologous groups of genes inferred across 7 eukaryotic phylogenomic datasets, we identified 9,821 SC-OGs; using OrthoSNAP on the remaining 405,308 orthologous groups of genes, we identified an additional 10,704 SNAP-OGs. Comparison of SNAP-OGs and SC-OGs revealed that their phylogenetic information content was similar, even in complex datasets that contain a whole-genome duplication, complex patterns of duplication and loss, transcriptome data where each gene typically has multiple transcripts, and contentious branches in the tree of life. OrthoSNAP is useful for increasing the number of markers used in molecular evolution data matrices, a critical step for robustly inferring and exploring the tree of life.

Synechococcus sp. PCC7002 Uses Peroxiredoxin to Cope with Reactive Sulfur Species Stress.

Cyanobacteria are a widely distributed group of microorganisms in the ocean, and they often need to cope with the stress of reactive sulfur species, such as sulfide and sulfane sulfur. Sulfane sulfur refers to the various forms of zero-valent sulfur, including persulfide, polysulfide, and element sulfur (S8). Although sulfane sulfur participates in signaling transduction and resistance to reactive oxygen species in cyanobacteria, it is toxic at high concentrations and induces sulfur stress, which has similar effects to oxidative stress. In this study, we report that Synechococcus sp. PCC7002 uses peroxiredoxin to cope with the stress of cellular sulfane sulfur. Synechococcus sp. PCC7002 contains six peroxiredoxins, and all were induced by S8. Peroxiredoxin I (PrxI) reduced S8 to H2S by forming a disulfide bond between residues Cys53 and Cys153 of the enzyme. A partial deletion strain of Synechococcus sp. PCC7002 with decreased copy numbers of the prxI gene was more sensitive to S8 than was the wild type. Thus, peroxiredoxin is involved in maintaining the homeostasis of cellular sulfane sulfur in cyanobacteria. Given that peroxiredoxin evolved before the occurrence of O2 on Earth, its original function could have been to cope with reactive sulfur species stress, and that function has been preserved. IMPORTANCE Cyanobacteria are the earliest microorganisms that perform oxygenic photosynthesis, which has played a key role in the evolution of life on Earth, and they are the most important primary producers in the modern oceans. The cyanobacterium Synechococcus sp. PCC7002 uses peroxiredoxin to reduce high levels of sulfane sulfur. That function is possibly the original role of peroxiredoxin, as the enzyme evolved before the appearance of O2 on Earth. The preservation of the reduction of sulfane sulfur by peroxiredoxin5-type peroxiredoxins may offer cyanobacteria an advantage in the complex environment of the modern oceans.

Contrasting modes of mitochondrial genome evolution in sister taxa of wood-eating marine bivalves (Teredinidae and Xylophagaidae).

The bivalve families Teredinidae and Xylophagaidae include voracious consumers of wood in shallow and deep-water marine environments, respectively. The taxa are sister clades whose members consume wood as food with the aid of intracellular cellulolytic endosymbionts housed in their gills. This combination of adaptations is found in no other group of animals and was likely present in the common ancestor of both families. Despite these commonalities, the two families have followed dramatically different evolutionary paths with respect to anatomy, life history and distribution. Here we present 42 new mitochondrial genome sequences from Teredinidae and Xylophagaidae and show that distinct trajectories have also occurred in the evolution and organization of their mitochondrial genomes. Teredinidae display significantly greater rates of amino acid substitution but absolute conservation of protein-coding gene order, whereas Xylophagaidae display significantly less amino acid change but have undergone numerous and diverse changes in genome organization since their divergence from a common ancestor. As with many bivalves, these mitochondrial genomes encode two ribosomal RNAs, 12 protein coding genes, and 22 tRNAs; atp8 was not detected. We further show that their phylogeny, as inferred from amino acid sequences of 12 concatenated mitochondrial protein-coding genes, is largely congruent with those inferred from their nuclear genomes based on 18S and 28S ribosomal RNA sequences. Our results provide a robust phylogenetic framework to explore the tempo and mode of mitochondrial genome evolution and offer directions for future phylogenetic and taxonomic studies of wood-boring bivalves.