Yuanning Li

Wood constitutes the largest reservoir of biogenic carbon on Earth, yet remarkably few animals can exploit it. While terrestrial wood-feeders like termites rely on highly diverse gut microbiomes, xylotrophic marine bivalves have evolved a fundamentally different approach: a spatially segregated system where intracellular gill symbionts produce enzymes that act remotely within a nearly sterile cecum. However, the genetic and evolutionary basis of this unique symbiosis remains largely elusive. Here, we integrate hologenomics, transcriptomics, and biochemistry of a shallow-water shipworm (Teredo navalis) and a deep-sea borer (Xyloredo sp.). We find that despite diverging approximately 147 million years ago and occupying drastically different habitats, these bivalves maintain a strictly conserved ancestral karyotype and a shared genomic architecture for wood digestion. Our models reveal a clear host-symbiont division of labor. The host genome is specialized for lignin modification and targeted enzyme transport, whereas a highly streamlined symbiont community is responsible for core polysaccharide degradation. Central to this minimalist strategy is a lineage-specific GH5-GH6 dual-catalytic enzyme. By sharing amino acids across proximal binding pockets, this fusion protein unites endo- and exo-cellulase activities, enabling highly synergistic cellulose cleavage without the need for complex microbial communities. Ultimately, our comparative analysis with terrestrial models demonstrates that these marine invertebrates achieve efficient biomass degradation not through microbial expansion, but through extreme functional streamlining and molecular innovation, offering a distinct evolutionary paradigm for marine carbon cycling.

A balanced immune response is required to limit the microbes without causing damage to the host. The forkhead box O (FoxO)-mediated immunity plays a pivotal role in maintaining microbiota homeostasis by regulating the expression of antimicrobial effectors in non-infected arthropods. However, the mechanism by which FoxO activity is appropriately coordinated remains unclear. In this study, we elucidated a feedback loop that coordinates FoxO-mediated antibacterial response using shrimp as a model. In this feedback loop, the commensal hemolymph microbiota maintains basal activation of FoxO, which determines the expression of antimicrobial effectors, platelet-derived growth factor/vascular endothelial growth factor (PDGF/VEGF)-related factor 1 (Pvf1) and PDGF/VEGF-related receptor 4 (Pvr4). This ligand-receptor system enhances phosphatidylinositol 3-kinase (PI3K)-protein kinase B (PKB/Akt) activity, limiting the excessive activation of FoxO and expression of antimicrobial effectors. This feedback loop is essential for maintaining the equilibrium of the microbiota, and its strength increases following a pathogenic infection, reducing the incidence of infection-induced mortality and tissue damage. This study revealed a microbiota-initiated feedback loop that balances FoxO-mediated antibacterial immunity for the establishment of microbiota homeostasis, and provides new insights into the functional diversification of PDGF/VEGF signaling.

RNA-binding proteins (RBPs) play critical roles in the regulation of gene expression. Recent studies have begun to detail the RNA recognition mechanisms of diverse RBPs. However, given the array of RBPs studied so far, it is implausible to experimentally profile RBP-binding peaks for hundreds of RBPs in multiple non-model organisms. Here, we introduce MuSIC ( Mu lti- S pecies RBP–RNA I nteractions using C onservation), a deep learning-based framework for predicting cross-species RBP–RNA interactions by leveraging label smoothing and evolutionary conservation of RBPs across 11 phylogenetically diverse species ranging from human to yeast. MuSIC outperforms state-of-the-art computational methods, and achieves highly accurate prediction of RBP-binding peaks across species. The prediction confidence is higher in the metazoan species, partially reflecting differences in RBP conservation patterns. Finally, the effects of homologous genetic variants on RBP binding can be computationally quantified across species, followed by experimental validations. The target transcripts with disrupted binding events are enriched in the ubiquitination-associated pathways. To summarize, MuSIC provides a useful computational framework for predicting RBP–RNA interactions cross-species and quantifying the effects of genetic variants on RBP binding, offering insights into the RBP-mediated regulatory mechanisms implicated in human diseases.

Gene gains and losses are a major driver of genome evolution; their precise characterization can provide insights into the origin and diversification of major lineages. Here, we examined gene family evolution of 1154 genomes from nearly all known species in the medically and technologically important yeast subphylum Saccharomycotina. We found that yeast gene family evolution differs from that of plants, animals, and filamentous ascomycetes, and is characterized by smaller overall gene numbers yet larger gene family sizes for a given gene number. Faster-evolving lineages (FELs) in yeasts experienced significantly higher rates of gene losses—commensurate with a narrowing of metabolic niche breadth—but higher speciation rates than their slower-evolving sister lineages (SELs). Gene families most often lost are those involved in mRNA splicing, carbohydrate metabolism, and cell division and are likely associated with intron loss, metabolic breadth, and non-canonical cell cycle processes. Our results highlight the significant role of gene family contractions in the evolution of yeast metabolism, genome function, and speciation, and suggest that gene family evolutionary trajectories have differed markedly across major eukaryotic lineages.

Crabs encompass the infra-orders Brachyura and Anomura, collectively constitute the clade Meiura within order Decapoda. Despite their considerable diversity, genomic resources for crabs remain scarce, hindering our understanding of their phylogeny and genetic mechanisms underlying such unique traits as carcinization. To address these questions, here we sequenced genomes of 10 crab species covering all currently controversial taxonomies at section level. Our whole-genome phylogenetic results support Raninoida is closer to Eubrachyura rather than Dromiacea, challenging the traditional classifications. Notably, the freshwater crab subsection Potamoida, represented by S. planum, is found to be more closely related to subsection Thoracotremata than to Heterotremata as previously suggested, indicating that crab classification based solely on morphology may be misleading. Our results also clarify that the family Gecarcinidae should be classified into Thoracotremata, contrary to previous placements in Heterotremata. Comparative genomic analyses identified lineage-specific families related to crab traits, including ionotropic glutamate receptors, neurotransmitters, and energy metabolism. Additionally, transcriptomic studies of Chinese mitten crab larval stages suggest that some lineage-specific genes such as ghrA, and TCB2, may account for the prominent carcinization in brachyurans. This study not only significantly expands the genomic repository for crabs, but also provides insights into the phylogeny and trait evolution of crabs.

Crustacea is a species-rich subphylum of Arthropoda that contains mostly aquatic species. Here, we established a comprehensive genomic database dedicated to the Crustacea. CRUSTADB represents a significant advancement in crustacean genomics, integrating an extensive array of genomic resources. The database encompasses 33 latest genomes, providing a foundational resource for genetic and genomic studies within this clade. Additionally, it includes an impressive 789 Gb of resequencing data across 10 species within the order Decapoda, 297 transcriptomes from 28 diverse species, and 312 mitochondrial genomes, offering a broad spectrum of genetic information. CRUSTADB is not merely a repository of genomic data; it also offers a suite of user-friendly tools designed for multifaceted integrative and comparative analyses. These tools enable users to visually browse the genomes and access a wide range of detailed information, including genome assembly statistics, genomic variations, gene annotations, expression profiles, gene family dynamics, and mitochondrial genomic data. Thus, CRUSTADB will facilitate a comprehensive understanding of crustacean genomics, serving as an invaluable resource for researchers in the field. CRUSTADB can be accessed at http://crustacean_ysfri.qnlm.ac/#/home.

Cryptic fungal pathogens pose disease management challenges due to their morphological resemblance to known pathogens. Here, we investigated the genomes and phenotypes of 53 globally distributed isolates of Aspergillus section Nidulantes fungi and found 30 clinical isolates—including four isolated from COVID-19 patients—were A. latus, a cryptic pathogen that originated via allodiploid hybridization. Notably, all A. latus isolates were misidentified. A. latus hybrids likely originated via a single hybridization event during the Miocene and harbor substantial genetic diversity. Transcriptome profiling of a clinical isolate revealed that both parental subgenomes are actively expressed and respond to environmental stimuli. Characterizing infection-relevant traits—such as drug resistance and growth under oxidative stress—revealed distinct phenotypic profiles among A. latus hybrids compared to parental and closely related species. Moreover, we identified four features that could aid A. latus taxonomic identification. Together, these findings deepen our understanding of the origin of cryptic pathogens.

Ancient divergences within Opisthokonta—a major lineage that includes organisms in the kingdoms Animalia, Fungi, and their unicellular relatives—remain contentious. To assess progress toward a genome-scale Opisthokonta phylogeny, we conducted the most taxon rich phylogenomic analysis using sets of genes inferred with different orthology inference methods and established the geological timeline of Opisthokonta diversification. We also conducted sensitivity analysis by subsampling genes or taxa from the full data matrix based on filtering criteria previously shown to improve phylogenomic inference. We found that approximately 85% of internal branches were congruent across data matrices and the approaches used. Notably, the use of different orthology inference methods was a substantial contributor to the observed incongruence: analyses using the same set of orthologs showed high congruence of 97% to 98%, whereas different sets of orthologs resulted in somewhat lower congruence (87% to 91%). Examination of unicellular Holozoa relationships suggests that the instability observed across varying gene sets may stem from weak phylogenetic signals. Our results provide a comprehensive Opisthokonta phylogenomic framework that will be useful for illuminating ancient evolutionary episodes concerning the origin and diversification of the 2 major eukaryotic kingdoms and emphasize the importance of investigating effects of orthology inference on phylogenetic analyses to resolve ancient divergences.

Maximum likelihood (ML) phylogenetic inference is widely used in phylogenomics. As heuristic searches most likely find suboptimal trees, it is recommended to conduct multiple (e.g., 10) tree searches in phylogenetic analyses. However, beyond its positive role, how and to what extent multiple tree searches aid ML phylogenetic inference remains poorly explored. Here, we found that a random starting tree was not as effective as the BioNJ and parsimony starting trees in inferring the ML gene tree and that RAxML-NG and PhyML were less sensitive to different starting trees than IQ-TREE. We then examined the effect of the number of tree searches on ML tree inference with IQ-TREE and RAxML-NG, by running 100 tree searches on 19,414 gene alignments from 15 animal, plant, and fungal phylogenomic datasets. We found that the number of tree searches substantially impacted the recovery of the best-of-100 ML gene tree topology among 100 searches for a given ML program. In addition, all of the concatenation-based trees were topologically identical if the number of tree searches was ≥10. Quartet-based ASTRAL trees inferred from 1 to 80 tree searches differed topologically from those inferred from 100 tree searches for 6/15 phylogenomic datasets. Finally, our simulations showed that gene alignments with lower difficulty scores had a higher chance of finding the best-of-100 gene tree topology and were more likely to yield the correct trees.

Gene gains and losses are a major driver of genome evolution; their precise characterization can provide insights into the origin and diversification of major lineages. Here, we examined gene family evolution of 1,154 genomes from nearly all known species in the medically and technologically important yeast subphylum Saccharomycotina. We found that yeast gene family and genome evolution are distinct from plants, animals, and filamentous ascomycetes and are characterized by small genome sizes and smaller gene numbers but larger gene family sizes. Faster-evolving lineages (FELs) in yeasts experienced significantly higher rates of gene losses—commensurate with a narrowing of metabolic niche breadth—but higher speciation rates than their slower-evolving sister lineages (SELs). Gene families most often lost are those involved in mRNA splicing, carbohydrate metabolism, and cell division and are likely associated with intron loss, metabolic breadth, and non-canonical cell cycle processes. Our results highlight the significant role of gene family contractions in the evolution of yeast metabolism, genome function, and speciation, and suggest that gene family evolutionary trajectories have differed markedly across major eukaryotic lineages.