Phylogenetic Network Research Articles

Phylogenetic network classes through the lens of expanding covers

It was recently shown that a large class of phylogenetic networks, the ‘labellable’ networks, is in bijection with the set of ‘expanding’ covers of finite sets. In this paper, we show how several prominent classes of phylogenetic networks can be characterised purely in terms of properties of their associated covers. These classes include the tree-based, tree-child, orchard, tree-sibling, and normal networks. In the opposite direction, we give an example of how a restriction on the set of expanding covers can define a new class of networks, which we call ‘spinal’ phylogenetic networks.

Two microbes assisting Miscanthus floridulus in remediating multi-metal(loid)s-contaminated soil.

Miscanthus has good tolerance to multi-metal(loid)s and has received increasing attention in remediated studies of metal(loid)s-contaminated soil. In this study, we conducted phytoextraction techniques to investigate the synergic effects of remediation of multi-metal(loid)s-contaminated soil by Miscanthus floridulus (Lab.) and two plant growth-promoting bacteria (PGPB), TS8 and MR2, affiliated to Enterobacteriaceae. The results exhibited a decrease of arsenic (15.27-21.50%), cadmium (8.64-15.52%), plumbum (5.92-12.76%), and zinc (12.84-24.20%) except for copper contents in the soil in bacterial inoculation groups, indicating that MR2 and TS8 could enhance the remediation of metal(loid)s. Moreover, increased fresh/dry weight and height indicated that inoculated bacteria could promote Miscanthus growth. Although the activities of antioxidant enzymes and the content of chlorophyll in the overground tissues showed no significant increase or even decrease, the activities of antioxidant enzymes in the underground tissues and soil were elevated by 48.95-354.17%, available P by 19.07-23.02%, and available K by 15.34-17.79% (p < 0.05). Bacterial inoculants could also decrease the soil pH. High-throughput sequencing analysis showed that the bacterial inoculant affected the rhizosphere bacterial community and reduced community diversity, but the relative abundance of some PGPB was found to increase. Phylogenetic molecular ecological networks indicated that bacterial inoculants reduced interactions between rhizosphere bacteria and thereby led to a simpler network structure but increased the proportion of positive-correlation links and enhanced the metabiosis and symbiosis of those bacteria. Spearman's test showed that OTUs affiliated with Enterobacteriaceae and soil nutrients were critical for metal(loid) remediation and Miscanthus growth. The results of this study provide a basis for the synergic remediation of multi-metal(loid)s-contaminated soils by Miscanthus and PGPB and provide a reference for the subsequent regulation of Miscanthus remediation efficiency by the other PGPB or critical bacteria.

Extended Lissamphibia: a tale of character non-independence, analytical parameters and islands of trees

The age, content and inter-order relationships of crown Lissamphibia remain a debated topic in vertebrate systematics. Recent phylogenetic analyses of fossil amphibians were used to propose an extended Lissamphibia, with Anura and Caudata nested in Dissorophoidea and with Gymnophiona nested in Stereospondyli, but this hypothesis was not supported by subsequent studies on updated matrices. In a parsimony context, the extended Lissamphibia hypothesis was shown to result from the effects of large island bias on the majority-rule consensus, which masked the presence of topologies supporting the restricted Lissamphibia hypothesis, with all extant orders nested in Dissorophoidea or in Stereospondyli. Re-analysing this dataset, taking into account the presence of inapplicable and polymorphic character states and revising the scores for logically non-independent characters, shows that the phylogenies inferred from the morphological data matrix used to propose the extended Lissamphibia hypothesis are not robust to changes in analytical parameters and that great care should be taken when analysing fossil amphibian datasets. With the set of most parsimonious trees inferred from the unrevised matrix used to propose the extended Lissamphibia hypothesis, I also demonstrate that the phenomenon of large island bias extends to phylogenetic networks, but not to topology-based tests of taxonomic instability that do not rely on split-frequencies.

Computing the Bounds of the Number of Reticulations in a Tree-Child Network That Displays a Set of Trees.

Phylogenetic network is an evolutionary model that uses a rooted directed acyclic graph (instead of a tree) to model an evolutionary history of species in which reticulate events (e.g., hybrid speciation or horizontal gene transfer) occurred. Tree-child network is a kind of phylogenetic network with structural constraints. Existing approaches for tree-child network reconstruction can be slow for large data. In this study, we present several computational approaches for bounding from below the number of reticulations in a tree-child network that displays a given set of rooted binary phylogenetic trees. In addition, we also present some theoretical results on bounding from above the number of reticulations. Through simulation, we demonstrate that the new lower bounds on the reticulation number for tree-child networks can practically be computed for large tree data. The bounds can provide estimates of reticulation for relatively large data.

Asymmetric Cluster-Based Measures for Comparative Phylogenetics.

Phylogenetic inference and reconstruction methods generate hypotheses on evolutionary history. Competing inference methods are frequently used, and the evaluation of the generated hypotheses is achieved using tree comparison costs. The Robinson-Foulds (RF) distance is a widely used cost to compare the topology of two trees, but this cost is sensitive to tree error and can overestimate tree differences. To overcome this limitation, a refined version of the RF distance called the Cluster Affinity (CA) distance was introduced. However, CA distances are symmetric and cannot compare different types of trees. These asymmetric comparisons occur when gene trees are compared with species trees, when disparate datasets are integrated into a supertree, or when tree comparison measures are used to infer a phylogenetic network. In this study, we introduce a relaxation of the original Affinity distance to compare heterogeneous trees called the asymmetric CA cost. We also develop a biologically interpretable cost, the Cluster Support cost that normalizes by cluster size across gene trees. The characteristics of these costs are similar to the symmetric CA cost. We describe efficient algorithms, derive the exact diameters, and use these to standardize the cost to be applicable in practice. These costs provide objective, fine-scale, and biologically interpretable values that can assess differences and similarities between phylogenetic trees.

Exploring the Distribution of Phylogenetic Networks Generated Under a Birth-Death-Hybridization Process

Gene-flow processes such as hybridization and introgression play important roles in shaping diversity across the tree of life. Recent studies extending birth-death models have made it possible to investigate patterns of reticulation in a macroevolutionary context. These models allow for different macroevolutionary patterns of gene flow events that can either add, maintain, or remove lineages—with the gene flow itself possibly being dependent on the relatedness between species—thus creating complex diversification scenarios. Further, many reticulate phylogenetic inference methods assume specific reticulation structures or phylogenies belonging to certain network classes. However, the distributions of phylogenetic networks under reticulate birth-death processes are poorly characterized, and it is unknown whether they violate common methodological assumptions. We use simulation techniques to explore phylogenetic network space under a birth-death-hybridization process where the hybridization rate can have a linear dependence on genetic distance. Specifically, we measured the number of lineages through time and role of hybridization in diversification along with the proportion of phylogenetic networks that belong to commonly used network classes (e.g., tree-child, tree-based, or level-1 networks). We find that the growth of phylogenetic networks and class membership are largely affected by assumptions about macroevolutionary patterns of gene flow. In accordance with previous studies, a lower proportion of networks belonged to these classes based on type and density of reticulate events. However, under a birth-death-hybridization process, these factors form an antagonistic relationship; the type of reticulation events that cause high membership proportions also lead to the highest reticulation density, consequently lowering the overall proportion of phylogenies in some classes. Further, we observed that genetic distance–dependent gene flow and incomplete sampling increase the proportion of class membership, primarily due to having fewer reticulate events. Our results can inform studies if their biological expectations of gene flow are associated with evolutionary histories that satisfy the assumptions of current methodology and aid in finding phylogenetic classes that are relevant for methods development.

Indole signaling enhances biofilm formation and quorum sensing in sequencing biofilm batch reactors

Indole is a heterocyclic organic compound that acts as a signaling molecule to regulate biofilm formation (BF) by microorganisms. However, the potential roles of indole in BF among microbial communities in wastewater treatment systems remain unknown. In this study, the effects of indole signaling on BF and quorum sensing (QS) of the complex microbial communities in sequencing batch biofilm reactors were systematically explored. The results showed that indole at 200 mg/L increased BF along with concentrations of homoserine lactones. High-throughput sequencing revealed the underlying mechanism of notable differences in the BF capacity of microbial communities between the indole-treated and control groups. The indole-related metabolic and QS functions of the genera in the biofilm were annotated based on the QS-related protein database and previous studies. Relative abundance analysis showed that the QS-related genera, such as Acinetobacter, that produce indole oxygenase were significantly enriched in the indole-treatment group. In addition, bioinformatics analyses revealed that indole at 200 mg/L enhanced BF, QS, and protein efflux. Based on a phylogenetic molecular ecological network, QS was positively correlated to indole treatment of Burkholderia, suggesting that indole promotes QS and BF. This study provides new insights into the effects of indole signaling on BF of microbes and sheds light on its potential regulatory mechanism in wastewater treatment plants.

Molecular characterization of recombinant LSDV isolates from 2022 outbreak in Indonesia through phylogenetic networks and whole-genome SNP-based analysis

Lumpy skin disease (LSD) is a transboundary viral disease of cattle and water buffaloes caused by the LSD virus, leading to high morbidity, low mortality, and a significant economic impact. Initially endemic to Africa only, LSD has spread to the Middle East, Europe, and Asia in the past decade. The most effective control strategy for LSD is the vaccination of cattle with live-attenuated LSDV vaccines. Consequently, the emergence of two groups of LSDV strains in Asian countries, one closely related to the ancient Kenyan LSDV isolates and the second made of recombinant viruses with a backbone of Neethling-vaccine and field isolates, emphasized the need for constant molecular surveillance. This current study investigated the first outbreak of LSD in Indonesia in 2022. Molecular characterization of the isolate circulating in the country based on selected LSDV-marker genes: RPO30, GPCR, EEV glycoprotein gene, and B22R, as well as whole genome analysis using several analytical tools, indicated the Indonesia LSDV isolate as a recombinant of LSDV_Neethling_vaccine_LW_1959 and LSDV_NI-2490. The analysis clustered the Indonesia_LSDV with the previously reported LSDV recombinants circulating in East and Southeast Asia, but different from the recombinant viruses in Russia and the field isolates in South-Asian countries. Additionally, this study has demonstrated alternative accurate ways of LSDV whole genome analysis and clustering of isolates, including the recombinants, instead of whole-genome phylogenetic tree analysis. These data will strengthen our understanding of the pathogens’ origin, the extent of their spread, and determination of suitable control measures required.

Divergence and reticulation in the Mexican white oaks: ecological and phylogenomic evidence on species limits and phylogenetic networks in the Quercus laeta complex (Fagaceae).

Introgressive hybridization poses a challenge to taxonomic and phylogenetic understanding of taxa, particularly when there are high numbers of co-occurring, intercrossable species. The genus Quercus exemplifies this situation. Oaks are highly diverse in sympatry and cross freely, creating syngameons of interfertile species. Although a well-resolved, dated phylogeny is available for the American oak clade, evolutionary relationships within many of the more recently derived clades remain to be defined, particularly for the young and exceptionally diverse Mexican white oak clade. Here, we adopted an approach bridging micro- and macroevolutionary scales to resolve evolutionary relationships in a rapidly diversifying clade endemic to Mexico. Ecological data and sequences of 155 low-copy nuclear genes were used to identify distinct lineages within the Quercus laeta complex. Concatenated and coalescent approaches were used to assess the phylogenetic placement of these lineages relative to the Mexican white oak clade. Phylogenetic network methods were applied to evaluate the timing and genomic significance of recent or historical introgression among lineages. The Q. laeta complex comprises six well-supported lineages, each restricted geographically and with mostly divergent climatic niches. Species trees corroborated that the different lineages are more closely related to other species of Mexican white oaks than to each other, suggesting that this complex is polyphyletic. Phylogenetic networks estimated events of ancient introgression that involved the ancestors of three present-day Q. laeta lineages. The Q. laeta complex is a morphologically and ecologically related group of species rather than a clade. Currently, oak phylogenetics is at a turning point, at which it is necessary to integrate phylogenetics and ecology in broad regional samples to figure out species boundaries. Our study illuminates one of the more complicated of the Mexican white oak groups and lays groundwork for further taxonomic study.

Increased geographic sampling suggests incomplete lineage sorting and recent introgression between Pyrrhosoma nymphula (Sulzer, 1776) and P. elisabethae Schmidt, 1948 in the Western Palearctic

We analysed COI and ITS sequences from a total of 69 European Pyrrhosoma nymphula (Sulzer, 1776) and three P. elisabethae Schmidt, 1948 to explore species boundaries and phylogeographic patterns in their Western Palearctic distributions. We found that phylogenetic and haplotype network analyses support previous results that the widespread P. nymphula and the endangered P. elisabethae are distinct species, and that P. nymphula in North Africa are distinct from P. nymphula in Europe. However, our results also suggest that neither diversification is complete as we found evidence for introgression of mitochondrial DNA between P. elisabethae and eastern Europe P. nymphula, as well as possible incomplete lineage sorting. Finally, our results indicate that while P. nymphu­la likely recolonized most of Europe from an Iberian Peninsula refugium following the Weichsel Glaciation, separate refugia possibly existed in North Africa, southern Italy, and for P. elisabethae in the southwestern Balkan.

Hierarchical-taxonomy-aware and attentional convolutional neural networks for acoustic identification of bird species: A phylogenetic perspective

The study of bird populations is crucial for biodiversity research and conservation. Deep artificial neural networks have revolutionized bird acoustic recognition; however, most methods overlook inherent relationships among bird populations, resulting in the loss of biological information. To address this limitation, we propose the Phylogenetic Perspective Neural Network (PPNN), which incorporates hierarchical multilevel labels for each bird. PPNN uses a hierarchical semantic embedding framework to capture feature information at different levels. Attention mechanisms are employed to extract and select common and distinguishing features, thereby improving classification accuracy. We also propose a path correction strategy to rectify inconsistent predictions. Experimental results on bird acoustic datasets demonstrate that PPNN outperforms current methods, achieving classification accuracies of 90.450%, 91.883%, and 89.950% on the Lishui-Zhejiang Birdsdata (100 species), BirdCLEF2018-Small (150 species), and BirdCLEF2018-Large (500 species) datasets respectively, with the lowest hierarchical distance of a mistake across all datasets. Our proposed method is applicable to any bird acoustic dataset and presents significant advantages as the number of categories increases.

Anomalous networks under the multispecies coalescent: theory and prevalence.

Reticulations in a phylogenetic network represent processes such as gene flow, admixture, recombination and hybrid speciation. Extending definitions from the tree setting, an anomalous network is one in which some unrooted tree topology displayed in the network appears in gene trees with a lower frequency than a tree not displayed in the network. We investigate anomalous networks under the Network Multispecies Coalescent Model with possible correlated inheritance at reticulations. Focusing on subsets of 4 taxa, we describe a new algorithm to calculate quartet concordance factors on networks of any level, faster than previous algorithms because of its focus on 4 taxa. We then study topological properties required for a 4-taxon network to be anomalous, uncovering the key role of [Formula: see text]-cycles: cycles of 3 edges parent to a sister group of 2 taxa. Under the model of common inheritance, that is, when each gene tree coalesces within a species tree displayed in the network, we prove that 4-taxon networks are never anomalous. Under independent and various levels of correlated inheritance, we use simulations under realistic parameters to quantify the prevalence of anomalous 4-taxon networks, finding that truly anomalous networks are rare. At the same time, however, we find a significant fraction of networks close enough to the anomaly zone to appear anomalous, when considering the quartet concordance factors observed from a few hundred genes. These apparent anomalies may challenge network inference methods.

Predicting horizontal gene transfers with perfect transfer networks

BackgroundHorizontal gene transfer inference approaches are usually based on gene sequences: parametric methods search for patterns that deviate from a particular genomic signature, while phylogenetic methods use sequences to reconstruct the gene and species trees. However, it is well-known that sequences have difficulty identifying ancient transfers since mutations have enough time to erase all evidence of such events. In this work, we ask whether character-based methods can predict gene transfers. Their advantage over sequences is that homologous genes can have low DNA similarity, but still have retained enough important common motifs that allow them to have common character traits, for instance the same functional or expression profile. A phylogeny that has two separate clades that acquired the same character independently might indicate the presence of a transfer even in the absence of sequence similarity.Our contributionsWe introduce perfect transfer networks, which are phylogenetic networks that can explain the character diversity of a set of taxa under the assumption that characters have unique births, and that once a character is gained it is rarely lost. Examples of such traits include transposable elements, biochemical markers and emergence of organelles, just to name a few. We study the differences between our model and two similar models: perfect phylogenetic networks and ancestral recombination networks. Our goals are to initiate a study on the structural and algorithmic properties of perfect transfer networks. We then show that in polynomial time, one can decide whether a given network is a valid explanation for a set of taxa, and show how, for a given tree, one can add transfer edges to it so that it explains a set of taxa. We finally provide lower and upper bounds on the number of transfers required to explain a set of taxa, in the worst case.

Homoplastic versus xenoplastic evolution: exploring the emergence of key intrinsic and extrinsic traits in the montane genus Soldanella (Primulaceae).

Specific ecological conditions in the high mountain environment exert a selective pressure that often leads to convergent trait evolution. Reticulations induced by incomplete lineage sorting and introgression can lead to discordant trait patterns among gene and species trees (hemiplasy/xenoplasy), providing a false illusion that the traits under study are homoplastic. Using phylogenetic species networks, we explored the effect of gene exchange on trait evolution in Soldanella, a genus profoundly influenced by historical introgression. At least three features evolved independently multiple times: the single-flowered dwarf phenotype, dysploid cytotype, and ecological generalism. The present analyses also indicated that the recurring occurrence of stoloniferous growth might have been prompted by an introgression event between an ancestral lineage and a still extant species, although its emergence via convergent evolution cannot be completely ruled out. Phylogenetic regression suggested that the independent evolution of larger genomes in snowbells is most likely a result of the interplay between hybridization events of dysploid and euploid taxa and hostile environments at the range margins of the genus. The emergence of key intrinsic and extrinsic traits in snowbells has been significantly impacted not only by convergent evolution but also by historical and recent introgression events.

Abundant incongruence in a clade endemic to a biodiversity hotspot: Phylogenetics of the scrub mint clade (Lamiaceae)

The Scrub Mint clade(Lamiaceae) provides a unique system for investigating the evolutionary processes driving diversification in the North American Coastal Plain from both a systematic and biogeographic context. The clade comprisesDicerandra, Conradina, Piloblephis, Stachydeoma, and four species of the broadly defined genus Clinopodium(Mentheae; Lamiaceae), almost all of which are endemic to the North American Eastern Coastal Plain. Most species of this clade are threatened or endangered and restricted to sandhill or a mosaic of scrub habitats. We analyzed relationships in this clade to understand the evolution of the group and identify evolutionary mechanisms acting on the clade, with important implications for conservation. We used a target-capture method to sequence and analyze 238 nuclear loci across all species of scrub mints, reconstructed the phylogeny, and calculated gene tree concordance, gene tree estimation error, and reticulation indices for every node in the tree using ML methods. Phylogenetic networks were used to determine reticulation events. Our nuclear phylogenetic estimates were consistent with previous results, while greatly increasing the robustness of taxon sampling. The phylogeny resolved the full relationship between Dicerandra and Conradina and the less-studied members of the clade (Piloblephis, Stachydeoma, Clinopodium spp.). We found hotspots of gene tree discordance and reticulation throughout the tree, especially in perennial Dicerandra. Several instances of reticulation events were uncovered between annual and perennial Dicerandra, and within the Conradina + allies clade. Incomplete lineage sorting also likely contributed to phylogenetic discordance. These results clarify phylogenetic relationships in the clade and provide insight on important evolutionary drivers in the clade, such as hybridization. General relationships in the group were confirmed, while the large amount of gene tree discordance is likely due to reticulation across the phylogeny.

Phylogenomic analysis expands the known repertoire of single-stranded DNA viruses in benthic zones of the South Indian Ocean.

Single-stranded (ss) DNA viruses are ubiquitous and constitute some of the most diverse entities on Earth. Most studies have focused on ssDNA viruses from terrestrial environments resulting in a significant deficit in benthic ecosystems including aphotic zones of the South Indian Ocean (SIO). Here, we assess the diversity and phylogeny of ssDNA in deep waters of the SIO using a combination of established viral taxonomy tools and a Hidden Markov Model based approach. Replication initiator protein-associated (Rep) phylogenetic reconstruction and sequence similarity networks were used to show that the SIO hosts divergent and as yet unknown circular Rep-encoding ssDNA viruses. Several sequences appear to represent entirely novel families, expanding the repertoire of known ssDNA viruses. Results suggest that a small proportion of these viruses may be circular genetic elements, which may strongly influence the diversity of both eukaryotes and prokaryotes in the SIO. Taken together, our data show that the SIO harbours a diverse assortment of previously unknown ssDNA viruses. Due to their potential to infect a variety of hosts, these viruses may be crucial for marine nutrient recycling through their influence of the biological carbon pump.

Ultrafast learning of four-node hybridization cycles in phylogenetic networks using algebraic invariants.

The abundance of gene flow in the Tree of Life challenges the notion that evolution can be represented with a fully bifurcating process which cannot capture important biological realities like hybridization, introgression, or horizontal gene transfer. Coalescent-based network methods are increasingly popular, yet not scalable for big data, because they need to perform a heuristic search in the space of networks as well as numerical optimization that can be NP-hard. Here, we introduce a novel method to reconstruct phylogenetic networks based on algebraic invariants. While there is a long tradition of using algebraic invariants in phylogenetics, our work is the first to define phylogenetic invariants on concordance factors (frequencies of four-taxon splits in the input gene trees) to identify level-1 phylogenetic networks under the multispecies coalescent model. Our novel hybrid detection methodology is optimization-free as it only requires the evaluation of polynomial equations, and as such, it bypasses the traversal of network space, yielding a computational speed at least 10 times faster than the fastest-to-date network methods. We illustrate our method's performance on simulated and real data from the genus Canis. We present an open-source publicly available Julia package PhyloDiamond.jl available at https://github.com/solislemuslab/PhyloDiamond.jl with broad applicability within the evolutionary community.

PM-CNN: microbiome status recognition and disease detection model based on phylogeny and multi-path neural network.

The human microbiome, found throughout various body parts, plays a crucial role in health dynamics and disease development. Recent research has highlighted microbiome disparities between patients with different diseases and healthy individuals, suggesting the microbiome's potential in recognizing health states. Traditionally, microbiome-based status classification relies on pre-trained machine learning (ML) models. However, most ML methods overlook microbial relationships, limiting model performance. To address this gap, we propose PM-CNN (Phylogenetic Multi-path Convolutional Neural Network), a novel phylogeny-based neural network model for multi-status classification and disease detection using microbiome data. PM-CNN organizes microbes based on their phylogenetic relationships and extracts features using a multi-path convolutional neural network. An ensemble learning method then fuses these features to make accurate classification decisions. We applied PM-CNN to human microbiome data for status and disease detection, demonstrating its significant superiority over existing ML models. These results provide a robust foundation for microbiome-based state recognition and disease prediction in future research and applications. PM-CNN software is available at https://github.com/qdu-bioinfo/PM_CNN.

Spatiotemporal Distribution of PRRSV-1 Clades in Hungary with a Focus on the Era of Disease Eradication.

Porcine reproductive and respiratory syndrome (PRRS) is the cause of the most severe economic losses in the pig industry worldwide. PRRSV is extremely diverse in Europe, which poses a significant challenge to disease control within a country or any region. With the combination of phylogenetic reconstruction and network analysis, we aimed to uncover the major routes of the dispersal of PRRSV clades within Hungary. In brief, by analyzing >2600 ORF5 sequences, we identified at least 12 clades (including 6 clades within lineage 1 and 3 clades within lineage 3) common in parts of Western Europe (including Denmark, Germany and the Netherlands) and identified 2 novel clades (designated X1 and X2). Of interest, some genetic clades unique to other central European countries, such as the Czech Republic and Poland, were not identified. The pattern of PRRSV clade distribution is consistent with the route of the pig trade among countries, showing that most of the identified clades were introduced from Western Europe when fatteners were transported to Hungary. As a result of rigorous implementation of the national eradication program, the swine population was declared officially free from PRRSV. This map of viral diversity and clade distribution will serve as valuable baseline information for the maintenance of PRRSV-free status in the post-eradication era.

Phylogenomic analyses and chromosome ploidy identification reveal multiple cryptic species in Allium sikkimense complex (Amaryllidaceae).

Polyploidization is a process that typically leads to instantaneous reproductive isolation and has, therefore, been considered as one of the major evolutionary forces in the species-rich Hengduan Mountains (HM), yet this topic remains poorly studied in the region. Allium sikkimense and its relatives (about eight species) compose a natural diploid-polyploid complex with the highest diversity in the HM and adjacent areas. A combination of nuclear ribosomal DNA (nrDNA), plastome, transcriptome, and ploidy identification through chromosome counting and flow cytometry is employed to reconstruct the phylogenetic relationships in this complex and to investigate the frequency and the evolutionary significance of polyploidy in the complex. The plastome failed to resolve the phylogenetic relationships of the different species in the A. sikkimense complex, and the phylogenetic tree based on nrDNA also has limited resolution. However, our study reveals a well-resolved phylogenetic framework for species in the A. sikkimense complex using more than 1,000 orthologous genes from the transcriptome data. Previously recognized morphospecies A. sikkimense are non-monophyletic and comprise at least two independently evolved lineages (i.e., cryptic species), each forming a clade with different diploid species in this complex. The embedded pattern of octoploid A. jichouense and tetraploid A. sp. nov. within different polyploid samples of A. sikkimense supports a possible scenario of budding speciation (via niche divergence). Furthermore, our results reveal that co-occurring species in the A. sikkimense complex usually have different ploidy levels, suggesting that polyploidy is an important process for reproductive isolation of sympatric Allium species. Phylogenetic network analyses suggested that the phylogenetic relationships of the A. sikkimense complex, allowing for reticulation events, always fit the dataset better than a simple bifurcating tree. In addition, the included or exserted filaments, which have long been used to delimit species, are highly unreliable taxonomically due to their extensive parallel and convergent evolution.