Nitrate reduction to ammonium: a phylogenetic, physiological, and genetic aspects in Prokaryotes and eukaryotes.

The microbe-mediated conversion of nitrate (NO3-) to ammonium (NH4+) in the nitrogen cycle has strong implications for soil health and crop productivity. The role of prokaryotes, eukaryotes and their phylogeny, physiology, and genetic regulations are essential for understanding the ecological significance of this empirical process. Several prokaryotes (bacteria and archaea), and a few eukaryotes (fungi and algae) are reported as NO3- reducers under certain conditions. This process involves enzymatic reactions which has been catalysed by nitrate reductases, nitrite reductases, and NH4+-assimilating enzymes. Earlier reports emphasised that single-cell prokaryotic or eukaryotic organisms are responsible for this process, which portrayed a prominent gap. Therefore, this study revisits the similarities and uniqueness of mechanism behind NO3- -reduction to NH4+ in both prokaryotes and eukaryotes. Moreover, phylogenetic, physiological, and genetic regulation also shed light on the evolutionary connections between two systems which could help us to better explain the NO3--reduction mechanisms over time. Reports also revealed that certain transcription factors like NtrC/NtrB and Nit2 have shown a major role in coordinating the expression of NO3- assimilation genes in response to NO3- availability. Overall, this review provides a comprehensive information about the complex fermentative and respiratory dissimilatory nitrate reduction to ammonium (DNRA) processes. Uncovering the complexity of this process across various organisms may further give insight into sustainable nitrogen management practices and might contribute to addressing global environmental challenges.

Diverse patterns of correspondence between protist metabarcodes and protist metagenome-assembled genomes.

Two common approaches to study the composition of environmental protist communities are metabarcoding and metagenomics. Raw metabarcoding data are usually processed into Operational Taxonomic Units (OTUs) or amplicon sequence variants (ASVs) through clustering or denoising approaches, respectively. Analogous approaches are used to assemble metagenomic reads into metagenome-assembled genomes (MAGs). Understanding the correspondence between the data produced by these two approaches can help to integrate information between the datasets and to explain how metabarcoding OTUs and MAGs are related with the underlying biological entities they are hypothesised to represent. MAGs do not contain the commonly used barcoding loci, therefore sequence homology approaches cannot be used to match OTUs and MAGs. We made an attempt to match V9 metabarcoding OTUs from the 18S rRNA gene (V9 OTUs) and MAGs from the Tara Oceans expedition based on the correspondence of their relative abundances across the same set of samples. We evaluated several metrics for detecting correspondence between features in these two datasets and developed controls to filter artefacts of data structure and processing. After selecting the best-performing metrics, ranking the V9 OTU/MAG matches by their proportionality/correlation coefficients and applying a set of selection criteria, we identified candidate matches between V9 OTUs and MAGs. In some cases, V9 OTUs and MAGs could be matched with a one-to-one correspondence, implying that they likely represent the same underlying biological entity. More generally, matches we observed could be classified into 4 scenarios: one V9 OTU matches many MAGs; many V9 OTUs match many MAGs; many V9 OTUs match one MAG; one V9 OTU matches one MAG. Notably, we found some instances in which different OTU-MAG matches from the same taxonomic group were not classified in the same scenario, with all four scenarios possible even within the same taxonomic group, illustrating that factors beyond taxonomic lineage influence the relationship between OTUs and MAGs. Overall, each scenario produces a different interpretation of V9 OTUs, MAGs and how they compare in terms of the genomic and ecological diversity they represent.

18S rDNA sequence-structure phylogeny of the eukaryotes simultaneously inferred from sequences and their individual secondary structures.

OBJECTIVE: The eukaryotic tree of life has been subject of numerous studies ever since the nineteenth century, with more supergroups and their sister relations being decoded in the last years. In this study, we reconstructed the phylogeny of eukaryotes using complete 18S rDNA sequences and their individual secondary structures simultaneously. After the sequence-structure data was encoded, it was automatically aligned and analyzed using sequence-only as well as sequence-structure approaches. We present overall neighbor-joining trees of 211 eukaryotes as well as the respective profile neighbor-joining trees, which helped to resolve the basal branching pattern. A manually chosen subset was further inspected using neighbor-joining, maximum parsimony, and maximum likelihood analyses. Additionally, the 75 and 100 percent consensus structures of the subset were predicted. RESULTS: All sequence-structure approaches show improvements compared to the respective sequence-only approaches: the average bootstrap support per node of the sequence-structure profile neighbor-joining analyses with 90.3, was higher than the average bootstrap support of the sequence-only profile neighbor-joining analysis with 73.9. Also, the subset analyses using sequence-structure data were better supported. Furthermore, more subgroups of the supergroups were recovered as monophyletic and sister group relations were much more comparable to results as obtained by multi-marker analyses.

Dynamic evolution of the mTHF gene family associated with primary metabolism across life.

BACKGROUND: The folate cycle of one-carbon (C1) metabolism, which plays a central role in the biosynthesis of nucleotides and amino acids, demonstrates the significance of metabolic adaptation. We investigated the evolutionary history of the methylenetetrahydrofolate dehydrogenase (mTHF) gene family, one of the main drivers of the folate cycle, across life. RESULTS: Through comparative genomic and phylogenetic analyses, we found that several lineages of Archaea lacked domains vital for folate cycle function such as the mTHF catalytic and NAD(P)-binding domains of FolD. Within eukaryotes, the mTHF gene family diversified rapidly. For example, several duplications have been observed in lineages including the Amoebozoa, Opisthokonta, and Viridiplantae. In a common ancestor of Opisthokonta, FolD and FTHFS underwent fusion giving rise to the gene MTHFD1, possessing the domains of both genes. CONCLUSIONS: Our evolutionary reconstruction of the mTHF gene family associated with a primary metabolic pathway reveals dynamic evolution, including gene birth-and-death, gene fusion, and potential horizontal gene transfer events and/or amino acid convergence.

Connecting Species-Specific Extents of Genome Reduction in Mitochondria and Plastids.

Mitochondria and plastids have both dramatically reduced their genomes since the endosymbiotic events that created them. The similarities and differences in the evolution of the two organelle genome types have been the target of discussion and investigation for decades. Ongoing work has suggested that similar mechanisms may modulate the reductive evolution of the two organelles in a given species, but quantitative data and statistical analyses exploring this picture remain limited outside of some specific cases like parasitism. Here, we use cross-eukaryote organelle genome data to explore evidence for coevolution of mitochondrial and plastid genome reduction. Controlling for differences between clades and pseudoreplication due to relatedness, we find that extents of mtDNA and ptDNA gene retention are related to each other across taxa, in a generally positive correlation that appears to differ quantitatively across eukaryotes, for example, between algal and nonalgal species. We find limited evidence for coevolution of specific mtDNA and ptDNA gene pairs, suggesting that the similarities between the two organelle types may be due mainly to independent responses to consistent evolutionary drivers.

The NCBI Comparative Genome Viewer (CGV) is an interactive visualization tool for the analysis of whole-genome eukaryotic alignments.

We report a new visualization tool for analysis of whole-genome assembly-assembly alignments, the Comparative Genome Viewer (CGV) (https://ncbi.nlm.nih.gov/genome/cgv/). CGV visualizes pairwise same-species and cross-species alignments provided by National Center for Biotechnology Information (NCBI) using assembly alignment algorithms developed by us and others. Researchers can examine large structural differences spanning chromosomes, such as inversions or translocations. Users can also navigate to regions of interest, where they can detect and analyze smaller-scale deletions and rearrangements within specific chromosome or gene regions. RefSeq or user-provided gene annotation is displayed where available. CGV currently provides approximately 800 alignments from over 350 animal, plant, and fungal species. CGV and related NCBI viewers are undergoing active development to further meet needs of the research community in comparative genome visualization.

Macroalgal eukaryotic microbiome composition indicates novel phylogenetic diversity and broad host spectrum of oomycete pathogens.

Seaweeds are important components of marine ecosystems with emerging potential in aquaculture and as sources of biofuel, food products and pharmacological compounds. However, an increasingly recognised threat to natural and industrial seaweed populations is infection with parasitic single-celled eukaryotes from the relatively understudied oomycete lineage. Here we examine the eukaryomes of diverse brown, red and green marine macroalgae collected from polar (Baffin Island), cold-temperate (Falkland Islands) and tropical (Ascension Island) locations, with a focus on oomycete and closely related diatom taxa. Using 18S rRNA gene amplicon sequencing, we show unexpected genetic and taxonomic diversity of the eukaryomes, a strong broad-brush association between eukaryome composition and geographic location, and some evidence of association between eukaryome structure and macroalgal phylogenetic relationships (phylosymbiosis). However, the oomycete fraction of the eukaryome showed disparate patterns of diversity and structure, highlighting much weaker association with geography and no evidence of phylosymbiosis. We present several novel haplotypes of the most common oomycete Eurychasma dicksonii and report for the first time a cosmopolitan distribution and absence of host specificity of this important pathogen. This indicates rich diversity in macroalgal oomycete pathogens and highlights that these pathogens may be generalist and highly adaptable to diverse environmental conditions.

Dating Ammonia-Oxidizing Bacteria with Abundant Eukaryotic Fossils.

Evolution of a complete nitrogen (N) cycle relies on the onset of ammonia oxidation, which aerobically converts ammonia to nitrogen oxides. However, accurate estimation of the antiquity of ammonia-oxidizing bacteria (AOB) remains challenging because AOB-specific fossils are absent and bacterial fossils amenable to calibrate molecular clocks are rare. Leveraging the ancient endosymbiosis of mitochondria and plastid, as well as using state-of-the-art Bayesian sequential dating approach, we obtained a timeline of AOB evolution calibrated largely by eukaryotic fossils. We show that the first AOB evolved in marine Gammaproteobacteria (Gamma-AOB) and emerged between 2.1 and 1.9 billion years ago (Ga), thus postdating the Great Oxidation Event (GOE; 2.4 to 2.32 Ga). To reconcile the sedimentary N isotopic signatures of ammonia oxidation occurring near the GOE, we propose that ammonia oxidation likely occurred at the common ancestor of Gamma-AOB and Gammaproteobacterial methanotrophs, or the actinobacterial/verrucomicrobial methanotrophs which are known to have ammonia oxidation activities. It is also likely that nitrite was transported from the terrestrial habitats where ammonia oxidation by archaea took place. Further, we show that the Gamma-AOB predated the anaerobic ammonia-oxidizing (anammox) bacteria, implying that the emergence of anammox was constrained by the availability of dedicated ammonia oxidizers which produce nitrite to fuel anammox. Our work supports a new hypothesis that N redox cycle involving nitrogen oxides evolved rather late in the ocean.

Ribosome decision graphs for the representation of eukaryotic RNA translation complexity.

The application of ribosome profiling has revealed an unexpected abundance of translation in addition to that responsible for the synthesis of previously annotated protein-coding regions. Multiple short sequences have been found to be translated within single RNA molecules, within both annotated protein-coding and noncoding regions. The biological significance of this translation is a matter of intensive investigation. However, current schematic or annotation-based representations of mRNA translation generally do not account for the apparent multitude of translated regions within the same molecules. They also do not take into account the stochasticity of the process that allows alternative translations of the same RNA molecules by different ribosomes. There is a need for formal representations of mRNA complexity that would enable the analysis of quantitative information on translation and more accurate models for predicting the phenotypic effects of genetic variants affecting translation. To address this, we developed a conceptually novel abstraction that we term ribosome decision graphs (RDGs). RDGs represent translation as multiple ribosome paths through untranslated and translated mRNA segments. We termed the latter "translons." Nondeterministic events, such as initiation, reinitiation, selenocysteine insertion, or ribosomal frameshifting, are then represented as branching points. This representation allows for an adequate representation of eukaryotic translation complexity and focuses on locations critical for translation regulation. We show how RDGs can be used for depicting translated regions and for analyzing genetic variation and quantitative genome-wide data on translation for characterization of regulatory modulators of translation.

Natural history of eukaryotic DNA viruses with double jelly-roll major capsid proteins.

The phylum Preplasmiviricota (kingdom Bamfordvirae, realm Varidnaviria) is a broad assemblage of diverse viruses with comparatively short double-stranded DNA genomes (<50 kbp) that produce icosahedral capsids built from double jelly-roll major capsid proteins. Preplasmiviricots infect hosts from all cellular domains, testifying to their ancient origin, and, in particular, are associated with six of the seven supergroups of eukaryotes. Preplasmiviricots comprise four major groups of viruses, namely, polintons, polinton-like viruses (PLVs), virophages, and adenovirids. We used protein structure modeling and analysis to show that protein-primed DNA polymerases (pPolBs) of polintons, virophages, and cytoplasmic linear plasmids encompass an N-terminal domain homologous to the terminal proteins (TPs) of prokaryotic PRD1-like tectivirids and eukaryotic adenovirids that are involved in protein-primed replication initiation, followed by a viral ovarian tumor-like cysteine deubiquitinylase (vOTU) domain. The vOTU domain is likely responsible for the cleavage of the TP from the large pPolB polypeptide and is inactivated in adenovirids, in which TP is a separate protein. Many PLVs and transpovirons encode a distinct derivative of polinton-like pPolB that retains the TP, vOTU, and pPolB polymerization palm domains but lacks the exonuclease domain and instead contains a superfamily 1 helicase domain. Analysis of the presence/absence and inactivation of the vOTU domains and replacement of pPolB with other DNA polymerases in eukaryotic preplasmiviricots enabled us to outline a complete scenario for their origin and evolution.

DeepReg: a deep learning hybrid model for predicting transcription factors in eukaryotic and prokaryotic genomes.

Deep learning models (DLMs) have gained importance in predicting, detecting, translating, and classifying a diversity of inputs. In bioinformatics, DLMs have been used to predict protein structures, transcription factor-binding sites, and promoters. In this work, we propose a hybrid model to identify transcription factors (TFs) among prokaryotic and eukaryotic protein sequences, named Deep Regulation (DeepReg) model. Two architectures were used in the DL model: a convolutional neural network (CNN), and a bidirectional long-short-term memory (BiLSTM). DeepReg reached a precision of 0.99, a recall of 0.97, and an F1-score of 0.98. The quality of our predictions, the bias-variance trade-off approach, and the characterization of new TF predictions were evaluated and compared against those produced by DeepTFactor, as well as against experimental data from three model organisms. Predictions based on our DLM tended to exhibit less variance and bias than those from DeepTFactor, thus increasing reliability and decreasing overfitting.

Advances in the mechanisms and applications of RNA silencing in crop protection.

RNA silencing (or RNA interference, RNAi) is a conserved mechanism for regulating gene expression in eukaryotes, which plays vital roles in plant development and response to biotic and abiotic stresses. The discovery of trans-kingdom RNAi and interspecies RNAi provides a theoretical basis for exploiting RNAi-based crop protection strategies. Here, we summarize the canonical RNAi mechanisms in plants and review representative studies associated with plant-pathogen interactions. Meanwhile, we also elaborate upon the principles of host-induced gene silencing, spray-induced gene silencing and microbe-induced gene silencing, and discuss their applications in crop protection, thereby providing help to establish novel RNAi-based crop protection strategies.

Blessing or curse: how the epigenetic resolution of host-transposable element conflicts shapes their evolutionary dynamics.

Transposable elements (TEs) are selfish genetic elements whose antagonistic interactions with hosts represent a common genetic conflict in eukaryotes. To resolve this conflict, hosts have widely adopted epigenetic silencing that deposits repressive marks at TEs. However, this mechanism is imperfect and fails to fully halt TE replication. Furthermore, TE epigenetic silencing can inadvertently spread repressive marks to adjacent functional sequences, a phenomenon considered a 'curse' of this conflict resolution. Here, we used forward simulations to explore how TE epigenetic silencing and its harmful side effects shape the evolutionary dynamics of TEs and their hosts. Our findings reveal that epigenetic silencing allows TEs and their hosts to stably coexist under a wide range of conditions, because the underlying molecular mechanisms give rise to copy-number dependency of the strength of TE silencing. Interestingly, contrary to intuitive expectations that TE epigenetic silencing should evolve to be as strong as possible, we found a selective benefit for modifier alleles that weaken TE silencing under biologically feasible conditions. These results reveal that the dual nature of TE epigenetic silencing, with both positive and negative effects, complicates its evolutionary trajectory and makes it challenging to determine whether TE epigenetic silencing is a 'blessing' or a 'curse'.

Unraveling the impact of climatic warming and wetting on eukaryotic microbial diversity and assembly mechanisms: A 10-year case study in Lake Bosten, NW China.

Over the last six decades, northwest China has undergone a significant climatic shift from "warm-dry" to "warm-wet", profoundly impacting the structures and functions of lake ecosystem across the region. However, the influences of this climatic transition on the diversity patterns, co-occurrence network, and assembly processes of eukaryotic microbial communities in lake ecosystem, along with the underlying mechanisms, remain largely unexplored. To bridge this knowledge gap, our study focused on Lake Bosten, the largest inland freshwater body in China, conducting a comprehensive analysis. Firstly, we examined the dynamics of key water quality parameters in the lake based on long-term monitoring data (1992-2022). Subsequently, we collected 93 water samples spanning two distinctive periods: low water level (WL) and high total dissolved solids (TDS) (PerWLTDS; 2010-2011; attributed to "warm-dry" climate), and high WL and low TDS (PerTDSWL; 2021-2022; associated with "warm-wet" climate). Eukaryotic microorganisms were further investigated using 18S rRNA gene sequencing and various statistical methods. Our findings revealed that climatic warming and wetting significantly increased eukaryotic microbial α-diversity (all Wilcox. test: P<0.05), while simultaneously reducing ß-diversity (all Wilcox. test: P<0.001) and network complexity. Through the two sampling periods, assembly mechanisms of eukaryotic microorganisms were predominantly influenced by dispersal limitation (DL) and drift (DR) within stochastic processes, alongside homogeneous selection (HoS) within deterministic processes. WL played a mediating role in eukaryotic microbial DL and HoS processes in the PerTDSWL, whereas water quality and α-diversity influenced the DL process in the PerWLTDS. Collectively, these results underscore the direct and indirect impacts of "warm-wet" conditions on the eukaryotic microorganisms within Lake Bosten. This study provides valuable insights into the evolutionary dynamics of lake ecosystems under such climatic conditions and aids in predicting the ecological ramifications of global climatic changes.

Planktonic eukaryotes in the Chesapeake Bay: contrasting responses of abundant and rare taxa to estuarine gradients.

Phytoplankton are important drivers of aquatic ecosystem function and environmental health. Their community compositions and distributions are directly impacted by environmental processes and human activities, including in the largest estuary in North America, the Chesapeake Bay. It is crucial to uncover how planktonic eukaryotes play fundamental roles as primary producers and trophic links and sustain estuarine ecosystems. In this study, we investigated the detailed community structure and spatiotemporal variations of planktonic eukaryotes in the Chesapeake Bay across space and time for three consecutive years. A clear seasonal and spatial shift of total, abundant, and rare planktonic eukaryotes was evident, and the pattern recurred interannually. Multiple harmful algal species have been identified in the Bay with varied distribution patterns, such as Karlodinium, Heterosigma akashiwo, Protoperidinium sp., etc. Compared to abundant taxa, rare subcommunities were more sensitive to environmental disturbance in terms of richness, diversity, and distribution. The combined effects of temporal variation (13.3%), nutrient availability (10.0%), and spatial gradients (8.8%) structured the distribution of eukaryotic microbial communities in the Bay. Similar spatiotemporal patterns between planktonic prokaryotes and eukaryotes suggest common mechanisms of adjustment, replacement, and species interaction for planktonic microbiomes under strong estuarine gradients. To our best knowledge, this work represents the first systematic study on planktonic eukaryotes in the Bay. A comprehensive view of the distribution of planktonic microbiomes and their interactions with environmental processes is critical in understanding the underlying microbial mechanisms involved in maintaining the stability, function, and environmental health of estuarine ecosystems. IMPORTANCE: Deep sequencing analysis of planktonic eukaryotes in the Chesapeake Bay reveals high community diversity with many newly recognized phytoplankton taxa. The Chesapeake Bay planktonic eukaryotes show distinct seasonal and spatial variability, with recurring annual patterns of total, abundant, and rare groups. Rare taxa mainly contribute to eukaryotic diversity compared to abundant groups, and they are more sensitive to spatiotemporal variations and environmental filtering. Temporal variations, nutrient availability, and spatial gradients significantly affect the distribution of eukaryotic microbial communities. Similar spatiotemporal patterns in prokaryotes and eukaryotes suggest common mechanisms of adjustment, substitution, and species interactions in planktonic microbiomes under strong estuarine gradients. Interannually recurring patterns demonstrate that diverse eukaryotic taxa have well adapted to the estuarine environment with a long residence time. Further investigations of how human activities impact estuarine planktonic eukaryotes are critical in understanding their essential ecosystem roles and in maintaining environmental safety and public health.

IPEV: identification of prokaryotic and eukaryotic virus-derived sequences in virome using deep learning.

BACKGROUND: The virome obtained through virus-like particle enrichment contains a mixture of prokaryotic and eukaryotic virus-derived fragments. Accurate identification and classification of these elements are crucial to understanding their roles and functions in microbial communities. However, the rapid mutation rates of viral genomes pose challenges in developing high-performance tools for classification, potentially limiting downstream analyses. FINDINGS: We present IPEV, a novel method to distinguish prokaryotic and eukaryotic viruses in viromes, with a 2-dimensional convolutional neural network combining trinucleotide pair relative distance and frequency. Cross-validation assessments of IPEV demonstrate its state-of-the-art precision, significantly improving the F1-score by approximately 22% on an independent test set compared to existing methods when query viruses share less than 30% sequence similarity with known viruses. Furthermore, IPEV outperforms other methods in accuracy on marine and gut virome samples based on annotations by sequence alignments. IPEV reduces runtime by at most 1,225 times compared to existing methods under the same computing configuration. We also utilized IPEV to analyze longitudinal samples and found that the gut virome exhibits a higher degree of temporal stability than previously observed in persistent personal viromes, providing novel insights into the resilience of the gut virome in individuals. CONCLUSIONS: IPEV is a high-performance, user-friendly tool that assists biologists in identifying and classifying prokaryotic and eukaryotic viruses within viromes. The tool is available at https://github.com/basehc/IPEV.

How do bacterial endosymbionts work with so few genes?

The move from a free-living environment to a long-term residence inside a host eukaryotic cell has profound effects on bacterial function. While endosymbioses are found in many eukaryotes, from protists to plants to animals, the bacteria that form these host-beneficial relationships are even more diverse. Endosymbiont genomes can become radically smaller than their free-living relatives, and their few remaining genes show extreme compositional biases. The details of how these reduced and divergent gene sets work, and how they interact with their host cell, remain mysterious. This Unsolved Mystery reviews how genome reduction alters endosymbiont biology and highlights a "tipping point" where the loss of the ability to build a cell envelope coincides with a marked erosion of translation-related genes.

How mitochondrial cristae illuminate the important role of oxygen during eukaryogenesis.

Inner membranes of mitochondria are extensively folded, forming cristae. The observed overall correlation between efficient eukaryotic ATP generation and the area of internal mitochondrial inner membranes both in unicellular organisms and metazoan tissues seems to explain why they evolved. However, the crucial use of molecular oxygen (O2) as final acceptor of the electron transport chain is still not sufficiently appreciated. O2 was an essential prerequisite for cristae development during early eukaryogenesis and could be the factor allowing cristae retention upon loss of mitochondrial ATP generation. Here I analyze illuminating bacterial and unicellular eukaryotic examples. I also discuss formative influences of intracellular O2 consumption on the evolution of the last eukaryotic common ancestor (LECA). These considerations bring about an explanation for the many genes coming from other organisms than the archaeon and bacterium merging at the start of eukaryogenesis.

Phylogenomic position of eupelagonemids, abundant, and diverse deep-ocean heterotrophs.

Eupelagonemids, formerly known as Deep Sea Pelagic Diplonemids I (DSPD I), are among the most abundant and diverse heterotrophic protists in the deep ocean, but little else is known about their ecology, evolution, or biology in general. Originally recognized solely as a large clade of environmental ribosomal subunit RNA gene sequences (SSU rRNA), branching with a smaller sister group DSPD II, they were postulated to be diplonemids, a poorly studied branch of Euglenozoa. Although new diplonemids have been cultivated and studied in depth in recent years, the lack of cultured eupelagonemids has limited data to a handful of light micrographs, partial SSU rRNA gene sequences, a small number of genes from single amplified genomes, and only a single formal described species, Eupelagonema oceanica. To determine exactly where this clade goes in the tree of eukaryotes and begin to address the overall absence of biological information about this apparently ecologically important group, we conducted single-cell transcriptomics from two eupelagonemid cells. A SSU rRNA gene phylogeny shows that these two cells represent distinct subclades within eupelagonemids, each different from E. oceanica. Phylogenomic analysis based on a 125-gene matrix contrasts with the findings based on ecological survey data and shows eupelagonemids branch sister to the diplonemid subgroup Hemistasiidae.

Cip1, a CDK regulator, determines heterothallic mating or homothallic selfing in a protist.

Mating type (sex) plays a crucial role in regulating sexual reproduction in most extant eukaryotes. One of the functions of mating types is ensuring self-incompatibility to some extent, thereby promoting genetic diversity. However, heterothallic mating is not always the best mating strategy. For example, in low-density populations or specific environments, such as parasitic ones, species may need to increase the ratio of potential mating partners. Consequently, many species allow homothallic selfing (i.e., self-fertility or intraclonal mating). Throughout the extensive evolutionary history of species, changes in environmental conditions have influenced mating strategies back and forth. However, the mechanisms through which mating-type recognition regulates sexual reproduction and the dynamics of mating strategy throughout evolution remain poorly understood. In this study, we show that the Cip1 protein is responsible for coupling sexual reproduction initiation to mating-type recognition in the protozoal eukaryote Tetrahymena thermophila. Deletion of the Cip1 protein leads to the loss of the selfing-avoidance function of mating-type recognition, resulting in selfing without mating-type recognition. Further experiments revealed that Cip1 is a regulatory subunit of the Cdk19-Cyc9 complex, which controls the initiation of sexual reproduction. These results reveal a mechanism that regulates the choice between mating and selfing. This mechanism also contributes to the debate about the ancestral state of sexual reproduction.