Comparative phylotranscriptomics of four sympatric tetrigids provides implications for convergent evolution and morphological discordance

Abstract

Background

The classification of pygmy grasshoppers (Orthoptera: Tetrigidae) has historically relied on morphological traits that are prone to homoplasy, leading to persistent taxonomic instability, particularly at the Scelimeninae-Tetriginae subfamily interface. Here, we integrated high-throughput transcriptomic data from four sympatric species—Ergatettix serrifemora, Criotettix damingshanensis, Hedotettix latifemurus, and Hedotettix gracilis—with existing genomic resources, including the previously sequenced Gibbotettix parvipulvillus, to reconstruct a robust phylogenomic framework and investigate the genomic basis of ecological adaptation and phenotypic plasticity.

Results

Phylogenomic analysis based on 1,962 single-copy orthologous groups yielded a fully resolved topology that challenged traditional classifications. Gibbotettix parvipulvillus was robustly recovered within the Scelimeninae clade, identifying its spine-reduced morphology as a secondary adaptation rather than a diagnostic feature of Cladonotinae. Conversely, E. serrifemora was firmly placed within Tetriginae, despite its misleading morpholog. Divergence time estimation indicated that H. latifemurus and H. gracilis split approximately 15.87 million years ago (Mya), confirming their status as distinct species driven by putative gene family expansions related to neural behavior and structural morphogenesis, respectively. Furthermore, formal differential expression analysis of wing morphs revealed a conserved potential metabolic trade-off where the cAMP, calcium, cGMP-PKG, insulin, and endocytosis pathways were enriched.

Conclusions

Our study demonstrates that morphological convergence in Tetrigidae frequently masks true evolutionary relationships, necessitating a phylogenomic re-evaluation of subfamily boundaries. We provide the first molecular evidence linking wing loss to a potential shift from aerobic hypertrophy to anaerobic maintenance and stress management strategies. These findings offer new insights into the genomic architecture driving speciation and life-history trade-offs in Tetrigidae.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-026-12789-6.

Introduction

Pygmy grasshoppers (Orthoptera: Tetrigidae) are a distinct and evolutionarily ancient lineage of invertebrates that play essential roles in terrestrial ecosystems, particularly in humid microhabitats [1–3]. The Tetrigidae, characterized by their extended pronotum and reduced forewings, have long posed a challenge for taxonomists. The Tetrigidae possess a unique morphology, characterized by an extended pronotum and reduced forewings, which has historically complicated their taxonomy. The classification of this family is primarily based on morphological characters such as head morphology, the shape of the pronotum, the presence of spiky ventrolateral projections, and the dimensions of the femora [4]. However, recent advances in genomic technologies have begun to expose the limitations of these traditional markers. Morphological convergence, driven by environmental adaptation, often obscures true evolutionary relationships, leading to polyphyletic groupings within traditional subfamilies [5, 6]. As high-quality genomes become available—such as those for Eucriotettix oculatus [7], Tetrix japonica [8], and Gibbotettix parvipulvillus [2]—we now possess the “genomic backbone” necessary to re-evaluate these complex phylogenetic conflicts.

A prominent example of taxonomic uncertainty lies at the boundary between the subfamilies Tetriginae and Scelimeninae. Traditionally, Scelimeninae is defined by the presence of spiky ventrolateral projections or teeth on the pronotum and legs, while Tetriginae lacks these armaments. The genus Ergatettix Kirby 1914, typically characterized by a non-spinose morphology, has long been placed within Tetriginae. However, its systematic position remains contentious when compared with genera such as Criotettix, commonly regarded as belonging to Scelimeninae and exhibiting pronounced spinose structures [9, 10]. Whether the morphological similarity of Ergatettix to the Tetriginae is a result of common ancestry or a secondary loss of spines (reversal) due to habitat adaptation remains an open question that morphology alone cannot resolve.

Simultaneously, at the genus level, the validity of specific morphological traits for species delimitation requires rigorous testing. The genus Hedotettix Bolívar, 1887 serves as an excellent model for this investigation. This genus is known for its high polymorphism in pronotum length and wing form [11, 12]. Specifically, H. latifemurus (Zheng & Wei) and H. gracilis (Haan) are two closely related species primarily distinguished by the shape of the anterior margin of the pronotum—obtusely produced in H. gracilis and nearly truncate in H. latifemurus. While previous studies have focused on descriptions of new species or geographic records [11, 13], there is a lack of molecular evidence to confirm whether these variations in pronotal morphology represent true interspecific divergence or merely intraspecific plasticity. Validating the genetic distinctiveness of these two species is crucial for establishing reliable diagnostic characters for the genus.

In this study, we employed high-throughput RNA-sequencing (RNA-Seq) to obtain transcriptomic data for four representative species: E. serrifemora, C. damingshanensis, H. latifemurus, and H. gracilis. By integrating these transcriptomes with recently published genomic resources of Tetrigidae [1, 2, 7, 8], we constructed a robust phylogenomic framework. Our objectives were to resolve the phylogenetic placement of E. serrifemora, to test the hypothesis of its affinity; to assess the genetic distance between H. latifemurus and H. gracilis to verify the taxonomic value of pronotal morphology; and to discuss the implications of morphological convergence and trait plasticity in the evolution of pygmy grasshoppers. This study highlights the power of transcriptomics in resolving taxonomic enigmas where traditional morphology falls short.

Materials and methods

Sample collection and species identification

Adult specimens of four pygmy grasshoppers—E. serrifemora, C. damingshanensis, H. latifemurus, and H. gracilis—were collected in the field (Fig. 1). E. serrifemora was sampled from Qingming Mountain, Luocheng Mulao Autonomous County, Guangxi (latitude: 25.0047° N; longitude: 108.9089° E), C. damingshanensis was sampled from Daming Mountain, Shanglin County, Guangxi (latitude: 23.5050° N; longitude: 108.4375° E), H. latifemurus was sampled from Gantian Town, Leye County, Guangxi (latitude: 24.6058° N; longitude: 106.4714° E), H. gracilis was sampled from Jinzhong Mountain, Longlin Various Nationalities Autonomous County, Guangxi (latitude: 24.6733° N; longitude: 104.9089° E). Additionally, E. serrifemora inhabits bare soil and gravel areas, C. damingshanensis inhabits in broad-leaved forests, while H. latifemurus and H. gracilis inhabit low grassy vegetation. Specimens were identified by Deng using original literature [14–17], along with the Orthoptera Species File [18] (http://orthoptera.speciesfile.org/). Among these specimens, both long-winged morph and short-winged morph individuals of these species were collected and mixed. For each species and wing morph (long-wing and short-wing), three biological replicates were prepared, yielding a total of 24 samples.

Fig. 1.

Images of the four pygmy grasshopper species, both long-winged morph and short-winged morph were shown. A E. serrifemora. B C. damingshanensis. C H. latifemurus. D H. gracilis. Scale bars = 1 mm

RNA extraction, library preparation, and sequencing

Total RNA was extracted from whole adult specimens using the TRIzol Reagent (Invitrogen, USA) following the manufacturer’s protocol. RNA integrity was assessed using a NanoDrop 2000 (Thermo Fisher Scientific, USA) and Agilent 2100 Bioanalyzer (Agilent Technologies, USA); only samples with RNA Integrity Number (RIN) > 7.0 were used. RNA-seq libraries were constructed using the NEBNext Ultra II RNA Library Prep Kit (New England Biolabs, USA) according to the supplier’s instructions. The libraries were quantified using a Qubit 4 Fluorometer (Thermo Fisher Scientific, USA) and their size distribution assessed with an Agilent 2100 Bioanalyzer. Sequencing was performed by Shanghai Yaoen Biotechnology Co., Ltd. using the Illumina HiSeq 6000 platform with a paired-end 150 bp configuration.

Data preprocessing and de novo transcriptome assembly

Raw sequencing reads were quality-filtered and trimmed using Trimmomatic v0.39 [19] with the following parameters: ILLUMINACLIP: adapter. fa: 2:30:10, LEADING: 3, TRAILING: 3, SLIDINGWINDOW: 4: 15, and MINLEN: 36. Given the absence of high-quality reference genomes for these species, de novo transcriptome assembly was conducted independently for each species using Trinity v2.15.2 [20] with default settings. To identify potential protein-coding regions in the assembled transcripts, we employed TransDecoder (v5.5.0) to predict open reading frames (ORFs) and extract their corresponding peptide sequences, with a minimum protein length threshold of 100 amino acids and homology search against the Pfam database (v37.2) to improve prediction accuracy.

Functional annotation and orthology inference

Functional annotation of predicted proteins was conducted using BLASTp (E-value < 1e-5) against the NCBI Non-Redundant (NR), Swiss-Prot, and KOG databases. Gene Ontology (GO) terms and KEGG pathways were assigned using eggNOG-mapper v2.1.9 [21]. To infer orthologous relationships, the proteomes of the four newly sequenced species and the three genomic references were analyzed using OrthoFinder v2.5.4 [22]. All-vs-all BLASTp searches were performed, and orthologous groups (OGs) were clustered using the MCL algorithm. Single-copy orthologs shared by all seven species were extracted for phylogenomic analysis.

Statistical analysis

The amino acid sequences of the identified 1,962 single-copy orthologous genes were individually aligned using MAFFT v7.475 [23] (L-INS-i algorithm). Poorly aligned regions were trimmed using trimAl v1.4 [24] with the -automated1 heuristic. The curated alignments were concatenated into a supermatrix using PhyloSuite v1.2.2 [25]. A Maximum Likelihood (ML) phylogenetic tree was reconstructed using IQ-TREE v2.1.2 [26]. The best-fit substitution model for each partition was determined by ModelFinder [27], and nodal support was evaluated using 1,000 ultrafast bootstrap replicates (UFBoot2) [28]. To evaluate potential gene-tree discordance driven by incomplete lineage sorting (ILS), we complemented the concatenation approach with a coalescent-based species tree inference. Individual ML gene trees were inferred for each of the 1,962 orthologs using IQ-TREE, and the species tree was estimated under the multispecies coalescent model using ASTRAL-III v5.7.8 [29]. Gene concordance factors (gCF) and site concordance factors (sCF) were calculated using IQ-TREE to quantify genomic support across loci.

Divergence time estimation and gene family evolution

Divergence times were estimated using the MCMCtree program within the PAML v4.9 package [30]. The approximate likelihood method was used to calculate the gradient and Hessian matrix. We applied soft-bound fossil calibrations at the following nodes: The root of the tree (Divergence of Orthoptera) was constrained with soft bounds between 255 million years ago (Mya) and 299 Mya, following a Beta prior (2.55, 2.99), corresponding to the Permian-Carboniferous boundary. An upper bound of 131 Mya (< 1.31) was applied to the most recent common ancestor (MRCA) of the Tetrigidae ingroup, reflecting the Early Cretaceous radiation of the family. Minimum age constraints were applied to specific internal nodes based on reliable fossil evidence: a lower bound of 48 Mya (> 0.48) for the divergence of the Tetrix-Hedotettix clade, and a lower bound of 36 Mya (> 0.36) for the Scelimeninae clade (Criotettix, Eucriotettix, Gibbotettix, and Zhengitettix). Two independent MCMC chains were run for 1,000,000 generations, sampling every 1,000 generations, with a burn-in of 100,000. Convergence was assessed using Tracer v1.7 [31]. Gene family expansion and contraction analyses were performed using CAFE 5 [32] based on the ultrametric tree and the gene count matrix from OrthoFinder. A birth-death model with a single λ parameter was fitted, and gene families with a conditional p-value < 0.05 were considered to have undergone significant size changes. Because CAFE models gene family size evolution under a birth–death framework that assumes genomic locus counts, and de novo transcriptome assemblies may not fully satisfy this assumption owing to assembly fragmentation, isoform redundancy, and expression-level biases, we implemented several filtering steps to mitigate potential artifacts. Specifically, only orthogroups assigned by OrthoFinder under stringent all-versus-all homology criteria were retained, single-isoform representative sequences were selected during TransDecoder prediction (longest ORF per transcript cluster), and highly volatile gene families (copy number variance > 10× across species) were excluded prior to CAFE modeling. Despite these precautions, the resulting expansion and contraction estimates should be interpreted as preliminary transcriptomic proxies rather than definitive measures of genomic duplication or deletion events.

Morphological analysis and tanglegram construction

A morphological matrix comprising 92 discrete characters was compiled for all studied species. The complete morphological matrix, detailed character definitions, and coding criteria are provided in Supplementary Table S1 (Table S1). A morphological phylogeny was inferred using IQ-TREE with the MK + ASC model (correcting for ascertainment bias) and 1,000 bootstrap replicates. To visualize cytonuclear discordance, a tanglegram comparing the ML molecular tree and the morphological tree was generated using the cophylo function in the R package phytools [33]. Morphological disparity was further quantified via Principal Coordinate Analysis (PCoA) based on Gower’s distances. The homoplasy levels of individual characters were evaluated by calculating the Retention Index (RI) and Consistency Index (CI) using the phangorn package [34].

Wing morph-specific expression and pathway analysis

To identify conserved molecular mechanisms underlying wing dimorphism, we performed a formal differential expression analysis to avoid classification biases inherent to fixed TPM thresholds. Raw read counts obtained from transcriptomic quantifications were used as input for the DESeq2 package (v1.34.0) [35] in R. Size factors were applied to normalize library depth variations across replicates. Differentially expressed genes (DEGs) between long-winged (LW) and short-winged (SW) morphs were identified using a stringent statistical framework, setting the false discovery rate (FDR) < 0.05 (adjusted via the Benjamini-Hochberg procedure) and an absolute log2 fold change (|log2FC|) > 1. Functional enrichment of these significantly up- and down-regulated DEGs was performed using the clusterProfiler package [36] (p-adjust < 0.05). Key signaling pathways (FoxO, HIF-1, mTOR) were manually reconstructed based on KEGG mapper results to visualize the differential regulation between wing morphs.

Results

Transcriptome assembly and quality assessment

High-throughput RNA sequencing was performed for four Tetrigidae species: E. serrifemora, C. damingshanensis, H. latifemurus, and H. gracilis. A total of more than 6 Gb of raw data was obtained for each sample, ensuring sufficient coverage for downstream analyses. De novo assembly of the clean reads yielded high-quality transcriptomes for all species. The number of assembled transcripts ranged from 84,930 in H. latifemurus to 148,156 in C. damingshanensis. The assembly integrity was robust, with N50 values ranging from 1,935 bp (H. gracilis) to 2,847 bp (H. latifemurus), and the GC content of the transcripts remained consistent across species, ranging from 40.56% to 42.55%. Subsequent prediction of coding sequences (CDS) identified a total of 16,654, 30,091, 14,878, and 25,643 CDSs for E. serrifemora, C. damingshanensis, H. latifemurus, and H. gracilis, respectively. The N50 values of the predicted CDSs were 1,677 bp, 1,473 bp, 1,725 bp, and 1,386 bp, respectively. Detailed assembly and annotation statistics are summarized in Table 1.

Table 1.

Summary of transcriptome assembly and CDS prediction for the four Tetrigidae species

Species	E.serrifemora	C.damingshanensis	H. latifemurus	H. gracilis
Total Transcripts	92,201	148,156	84,930	136,245
Total Length (bp)	129,142,150	200,896,095	138,688,044	171,547,947
N50 Length (bp)	2,404	2,244	2,847	1,935
Mean GC Content (%)	40.56	42.15	40.72	42.55
Total CDS	16,654	30,091	14,878	25,643
Total Length (bp)	19,711,269	31,825,266	18,629,208	24,923,001
N50 Length (bp)	1,677	1,473	1,725	1,386

The predicted coding sequences were annotated against public databases to elucidate the biological functions of the assembled transcriptomes. A total of 47,764, 63,244, 42,032, and 57,972 sequences were successfully annotated for E. serrifemora, C. damingshanensis, H. latifemurus, and H. gracilis, respectively. GO classification was performed to characterize the gene functions at Level 2 (Fig. 2). The comparative distribution of GO terms within the “Biological Process” category is presented in Fig. 2. Across all four newly sequenced species, the distribution patterns were highly consistent. The most abundant categories were “cellular process”, “metabolic process”, and “biological regulation”, reflecting the fundamental biological activities essential for survival and development. Other significant categories included “response to stimulus” and “multicellular organismal process.”

Fig. 2.

Comparative GO classification of annotated coding sequences across six Tetrigidae species. Functional annotation was performed at GO Level 2. The bar chart displays the distribution of gene counts assigned to various GO terms

For comparative analysis, we included the genomic annotation data of two reference species, E. oculatus and T. japonica. The content and distribution patterns remain highly consistent, although the total abundance of assigned GO terms in these genomic datasets is lower than that in the four transcriptome-based datasets. This difference is expected, as de novo transcriptome assemblies often retain isoforms and alternatively spliced variants, resulting in a higher count of annotated sequences compared to the non-redundant gene sets typically derived from high-quality genome assemblies.

Subsequently, OGs were identified to characterize the genomic conservation and evolutionary relationships among the species. The distribution of shared gene families across the six Tetrigidae species is visualized (Fig. 3). A substantial number of orthogroups showed high conservation; notably, 7,082 core orthogroups were shared by all six species (represented by the central red polygon in Fig. 3). This large set of shared genes indicates a close evolutionary affinity among the sampled species and provides a robust dataset for downstream phylogenomic reconstruction. Additionally, specific overlaps between species pairs (e.g., within the genus Hedotettix) further reflect their varying degrees of genetic relatedness.

Fig. 3.

Venn diagram illustrating the intersection of OGs among the six Tetrigidae species. The analysis was performed using OrthoFinder based on predicted protein sequences

Phylogenomic architecture and morphological evolution

Based on the supermatrix of 1,962 single-copy OGs (955,144 amino acid sites), the phylogenomic analysis yielded a fully resolved ML tree with maximal statistical confidence (BS = 100 for all nodes; Fig. 4, left panel). The molecular phylogeny clearly delineated two major lineages. The first lineage corresponds to the Scelimeninae clade, recovering G. parvipulvillus—traditionally considered a member of Cladonotinae—nested deeply within Scelimeninae as the sister group to Z. transpicula. C. damingshanensis was robustly recovered as the sister taxon to E. oculatus within this clade. The second lineage comprises the Tetriginae species, and E. serrifemora was recovered at the base of the clade containing T. japonica and Hedotettix, providing strong molecular support for its long-established placement within Tetriginae.

Fig. 4.

Tanglegram contrasting the phylogenomic (left) and morphological (right) relationships of Tetrigidae species. Left: The phylogenomic tree was reconstructed using IQ-TREE based on a concatenated dataset of 1,962 single-copy orthologous genes. All nodes received 100% bootstrap support, providing a robust evolutionary backbone. Right: The morphological tree was inferred from 93 coded characters. Bootstrap support values are indicated at the nodes, showing generally low resolution. Lines: Connecting lines link the same species across the two trees, visualizing the extent of cytonuclear discordance

In sharp contrast, the phylogenetic tree inferred from 93 morphological characters displayed significant topological incongruence and weak nodal support (Fig. 4, right panel). The tanglegram highlights extensive conflict between morphological similarity and genetic relatedness. A striking discordance was observed for E. serrifemora and G. parvipulvillus: while they belong to distinct subfamilies in the molecular tree (Tetriginae and Scelimeninae, respectively), they clustered together in the morphological tree (BS = 53). This suggests strong morphological convergence or homoplasy between these two genera. Furthermore, the position of C. damingshanensis in the morphological analysis deviated significantly from its true evolutionary placement, appearing distant from its closest molecular relative, E. oculatus. These results underscore that morphological traits in Tetrigidae are highly prone to homoplasy, rendering them unreliable for resolving higher-level relationships without genomic evidence.

Then, we performed a PCoA based on Gower distances of discrete morphological characters to deconstruct this cytonuclear discordance (Fig. 5A). The morphospace visualization reveals that E. serrifemora clusters tightly with the core Tetriginae group (H. latifemurus, H. gracilis, and T. japonica) along the primary axis (PCoA 1, explaining 65% of variation), whereas G. parvipulvillus occupies a distinct region of the morphospace (PCoA 1 > 0.3). This result indicates that the global morphological profile of E. serrifemora is indeed consistent with its molecular position, and its erroneous grouping in the cladistic morphological tree likely resulted from the artificial weighting of a few homoplastic traits.

Fig. 5.

Analysis of morphological evolution and character utility in Tetrigidae. A Morphospace of the sampled species generated via PCoA based on Gower distances of 93 discrete morphological characters. The clustering of E. serrifemora with Hedotettix and Tetrix species supports their close phylogenetic relationship, contradicting traditional taxonomy. B Scatter plot of CI versus RI for all morphological characters. Points in the upper-right corner (red circle) represent characters with high phylogenetic signal (RI ≥ 0.8). C Lollipop plot ranking the top morphological characters by RI

Furthermore, the reliability of morphological traits was quantified by evaluating CI and RI for each character. The scatter plot of CI versus RI (Fig. 5B) demonstrates a broad distribution of homoplasy across the dataset, with many characters showing low phylogenetic signal (low RI), which explains the instability of the morphological tree. However, a subset of characters exhibits high phylogenetic signal (RI ≥ 0.8). Specifically, the character importance analysis (Fig. 5C) identified three characters (ID 25, 43, and 44) with perfect fit (RI = 1.0, CI = 1.0). These characters act as reliable synapomorphies supporting the molecular topology, distinguishing the Hedotettix-Ergatettix lineage from the Scelimeninae clade. These findings underscore that while morphological convergence obscures evolutionary history in Tetrigidae, specific diagnostic characters—when validated by genomic backbones—remain crucial for taxonomic delimitation.

Divergence time estimation, and gene family evolution

Based on the robust phylogenomic topology, we estimated the divergence times of Tetrigidae species using MCMCTree (Fig. 6A). The root of the phylogenetic tree was estimated at approximately 283.31 Mya, corresponding to the Permian period. A major cladogenetic event occurred during the Late Cretaceous (~ 87.53 Mya), marking the divergence between the Scelimeninae lineage (represented by Criotettix, Eucriotettix, Gibbotettix, and Zhengitettix) and the Tetriginae lineage. Within the Tetriginae clade, E. serrifemora diverged from the common ancestor of Tetrix and Hedotettix at approximately 74.30 Mya. The genus Hedotettix diversified more recently, with H. latifemurus and H. gracilis splitting around 15.87 Mya (Miocene), suggesting a relatively recent speciation event within a single genus.

Fig. 6.

Time-calibrated phylogenomic tree and concordance factor analysis. A Chronogram generated using MCMCTree based on the concatenated protein supermatrix. The axis at the top represents geological time (Mya). Black numbers above the nodes indicate the estimated divergence times (Mya). The light green bars represent the 95% confidence intervals (CI) for the divergence dates. The numbers on the branches indicate changes in gene family size inferred by CAFE. Red numbers (preceded by "+") denote the number of gene families that have undergone expansion, while green numbers (preceded by "−") denote contraction. B Scatter plot of gene concordance factor (gCF) versus site concordance factor (sCF) for all internal nodes. Points are colored by gCF support level: strong (≥80%, dark blue), moderate (50–80%, light blue), weak (30–50%, orange), and very weak (<30%, red). Node IDs correspond to branches in the species tree. Concordance factors were calculated by IQ-TREE

We further reconstructed the evolutionary dynamics of gene families (expansions and contractions) using CAFE (Fig. 6A). The analysis revealed dynamic genomic changes across the phylogeny. The most recent common ancestor (MRCA) of the sampled Tetrigidae species exhibited a trend of gene family contraction (+ 424 expansions vs. -2,678 contractions). However, distinct lineage-specific expansions were observed at the tips of the tree, potentially linked to environmental adaptations. Notably, C. damingshanensis showed a substantial expansion of 2,248 gene families, and H. gracilis exhibited 2,408 expanded families. In contrast, other lineages using genomic data, such as G. parvipulvillus and T. japonica, showed a relatively balanced or contraction-biased pattern. Indeed, the notably larger putative expansions observed in the transcriptome-based lineages (C. damingshanensis and H. gracilis) relative to the genome-based lineages (G. parvipulvillus and T. japonica) may partly reflect this methodological asymmetry rather than genuine biological differences in gene duplication rates. We therefore emphasize that these estimates should be treated as exploratory indicators of potential evolutionary trends rather than precise quantifications of genomic duplication events. Validation using even draft-quality genome assemblies would substantially improve the reliability of copy number inference for these species. Nevertheless, the broad functional trends identified through downstream GO enrichment of these putatively expanded families remain informative as hypotheses for future genomic investigation.

Furthermore, we complemented the concatenation analysis with a coalescent-based species tree. The ASTRAL species tree recovered an identical topology to the concatenated ML tree, confirming the robustness of the major phylogenomic relationships. Gene concordance factors (gCF) and site concordance factors (sCF), calculated using IQ-TREE, provided a locus-level quantification of phylogenomic support (Fig. 6B). The deepest bipartition separating the Scelimeninae and Tetriginae clades received near-unanimous support (gCF = 98.65%, sCF = 96.05%), indicating that virtually all gene trees and informative sites favor this split. Within the Tetriginae clade, the sister-group relationship of the two Hedotettix species (node 16: gCF = 67.34%, sCF = 75.12%) and the (Hedotettix + Tetrix) clade (node 15: gCF = 68.52%, sCF = 76.72%) received moderate-to-strong concordance, with gCF values substantially exceeding the sum of both discordance factors (gDF1 + gDF2), indicating genuine phylogenetic signal rather than stochastic noise. In contrast, several nodes within the Scelimeninae clade exhibited lower concordance. The placement of G. parvipulvillus as sister to Z. transpicula (node 18: gCF = 25.93%, sCF = 39.09%) and the broader Scelimeninae backbone (node 17: gCF = 33.50%, sCF = 44.32%) showed considerable gene-tree discordance, with a large proportion of discordant trees attributable to polyphyletic signal (gDFP = 48.82% and 35.86%, respectively). This pattern is consistent with rapid diversification and incomplete lineage sorting within the Scelimeninae radiation, though the short internal branch lengths at these nodes (0.0046 and 0.0103 substitutions per site) further corroborate a scenario of rapid successive speciation events.

Then, we performed GO enrichment analysis on the significantly expanded gene families identified in the four sequenced species to decipher the biological significance of these genomic changes. Filtering for highly significant terms (FDR < 0.01) at GO Level 3 within the Biological Process category revealed distinct functional profiles corresponding to divergent adaptive strategies (Fig. 7). The functional landscape of the expanded genes varied sharply among species. In C. damingshanensis, expanded families were significantly enriched in sensory and immune-related processes, such as “mechanosensory behavior”, “chemosensory behavior”, and “immune response”. This expansion likely facilitates survival in complex biotic environments by enhancing predator detection and pathogen defense. For E. serrifemora, the enrichment was predominantly concentrated in metabolic regulation and stress responses, including “NAD/NADH metabolic process”, “protein unfolding”, and “general adaptation syndrome”. These terms suggest a heightened physiological capacity to cope with environmental fluctuations or metabolic stress.

Fig. 7.

Functional enrichment of significantly expanded gene families across four Tetrigidae species. The heatmap illustrates the enrichment of GO terms (Biological Process, Level 3) associated with lineage-specific gene expansions. Only GO terms with a False Discovery Rate (FDR) < 0.01 were retained for visualization. Color Scale: The color gradient represents the row-scaled enrichment significance (Z-score), with red indicating higher enrichment levels and blue indicating lower levels

Within the genus Hedotettix, the two species exhibited striking functional divergence despite their close phylogenetic relationship. H. latifemurus showed unique enrichments in neural and behavioral pathways, such as ‘ensheathment of neurons’, ‘exploration behavior’, and ‘circadian rhythm’, implying an evolution towards complex behavioral plasticity. In contrast, H. gracilis—distinguished morphologically by an obtusely produced anterior pronotal margin—showed a massive investment in structural development. Its expanded genes were heavily enriched in ‘anatomical structure morphogenesis’, ‘muscle attachment’, and ‘intermediate filament-based process’. This molecular signature aligns with the morphological divergence of the species, suggesting that the expansion of structural gene families may underpin specific diagnostic traits, particularly the variation in pronotal shape, that differentiate it from H. latifemurus.

Conserved molecular mechanisms underlying wing dimorphism

Conserved transcriptomic differences between long-winged (LW) and short-winged (SW) morphs were found through the formal differential expression analysis using DESeq2 for each of the four species independently (FDR < 0.05, |log₂FC| > 1). A total of 191 KEGG pathways were enriched across all species. A Venn diagram analysis of these enriched pathways revealed that 18 pathways (9.42%) were shared among all four species, indicating a conserved molecular basis underlying wing dimorphism across divergent tetrigid lineages (Fig. 8A). An additional 65 pathways (34.03%) were shared by at least two species, while species-specific enrichments were also observed, with C. damingshanensis (28 pathways, 14.66%) and H. gracilis (15 pathways, 7.85%) exhibiting the largest sets of private enrichments.

Fig. 8.

Comparative KEGG pathway enrichment analysis of differentially expressed genes between long-winged and short-winged morphs across four Tetrigidae species. A Venn diagram showing the overlap of significantly enriched KEGG pathways among the four species. Numbers indicate the count of pathways in each intersection, with percentages relative to the total of 191 enriched pathways. A core set of 18 pathways (9.42%) was shared across all four species. B Heatmap displaying the number of DEGs assigned to each of the 18 shared KEGG pathways for each species. Color intensity reflects the number of DEGs per pathway

We categorized them into three tiers based on established literature on insect wing morphogenesis and scored them by their putative biological associations (Fig. 8B). Five pathways were classified as “core” wing development-associated pathways: cAMP signaling pathway, calcium signaling pathway, cGMP-PKG signaling pathway, insulin signaling pathway, and endocytosis. These pathways are integral to hormonal signal transduction (ecdysone and juvenile hormone via cAMP/cGMP-PKG), morphogen gradient formation (Wnt, Dpp, and Notch signaling via endocytosis), organ size regulation (insulin/TOR signaling), and cell proliferation during wing disc patterning (calcium signaling). All five pathways contained DEGs in every species examined, with the cAMP signaling pathway harboring the highest number of DEGs in C. damingshanensis (6 DEGs) and both H. latifemurus and H. gracilis (5 DEGs each). Five additional pathways—oxidative phosphorylation, neuroactive ligand-receptor interaction, pyruvate metabolism, purine metabolism, and lysosome—were classified as “supportive,” reflecting their roles in energy provisioning for rapidly proliferating wing tissues, nucleotide biosynthesis, and cellular remodeling during metamorphosis. Notably, oxidative phosphorylation was disproportionately represented in H. gracilis (11 DEGs), suggesting a particularly pronounced metabolic shift between wing morphs in this species. The remaining eight pathways showed weaker direct associations with wing development and likely reflect broader physiological differences between morphs.

Discussions

Resolving the “Scelimeninae-Tetriginae” paradox via phylotranscriptomics

Recently, several taxonomic units within the family Tetrigidae—across the subfamilies Cladonotinae, Metrodorinae, Scelimeninae, and Tetriginae—have been reclassified or split to establish new subfamilies [37]. However, such rearrangements, often based on limited morphological evidence and insufficient molecular phylogenetic signal, have led to controversies at higher taxonomic levels (e.g., genera and subfamilies) and, in some cases, to increased instability in classification systems. This situation largely arises from the lack of comprehensive molecular datasets, clearly recognizable genetic divergence and differentiation times, and stable morphological diagnostic traits. Therefore, the central challenge in the current classification of Tetrigidae lies in redefining the boundaries among subfamilies by integrating robust molecular phylogenomic data, morphological characteristics, and divergence-time estimation. The classification of Tetrigidae has historically been plagued by morphological homoplasy, particularly regarding the taxonomic boundary between Scelimeninae and Tetriginae [6, 38]. Notably, Subedi, et al. (2025) established a new subfamily, Criotettiginae, to accommodate Criotettix and Eucriotettix, primarily distinguished from Scelimeninae and Tetriginae by a combination of cephalic and pronotal characters [42]. However, our phylogenomic results do not support this taxonomic separation. Instead, both Criotettix and Eucriotettix are consistently recovered within the Scelimeninae clade, forming a well-supported lineage together with Zhengitettix (Fig. 4). Our phylogenomic reconstruction provides decisive evidence that challenges traditional diagnostic characters. The robust recovery of G. parvipulvillus within the Scelimeninae clade, despite its morphological resemblance to Cladonotinae, exposes the unreliability of relying solely on pronotal spines for subfamily delineation [39]. This finding aligns with the hypothesis that reduction or loss of spines may be a secondary adaptation to microhabitats where complex armaments confer a fitness cost, such as dense leaf litter [2, 5, 40–43]. E. serrifemora is definitively placed within Tetriginae at the base of the Tetrix + Hedotettix clade. The profound discordance visualized in our tanglegram (Fig. 4) demonstrates that morphological characters in pygmy grasshoppers are subject to intense convergent evolution, likely driven by similar ecological pressures acting on distantly related lineages [5, 40, 41, 44]. Notably, the coalescent-based ASTRAL analysis recovered an identical topology to the concatenation approach, and gene/site concordance factors confirmed that the key inter-subfamily split is supported by an overwhelming majority of individual gene histories (gCF = 98.65%; sCF = 96.05%). The lower concordance observed within the Scelimeninae clade (gCF = 25.93–33.50%) is consistent with rapid radiation and extensive ILS, yet the monophyly of the clade remains uncontested across all analyses. Consequently, we propose that future taxonomic revisions of Tetrigidae must prioritize phylogenomic backbones over labile morphological traits.

Genomic signatures of ecological adaptation

Beyond phylogeny, our study illuminates how genomic architecture shapes the ecological plasticity of tetrigids. The significant expansion of gene families in C. damingshanensis and E. serrifemora reveals distinct adaptive strategies. The enrichment of sensory and immune-related genes in C. damingshanensis correlates with its habitat in complex broad-leaved forests, where heightened chemosensory and mechanosensory capabilities are essential for predator avoidance and resource location [45]. In contrast, the expansion of metabolic and stress-response genes (e.g., “general adaptation syndrome”) in E. serrifemora reflects its adaptation to exposed, gravel-rich environments, which likely impose greater thermal and physiological stress [46, 47]. These lineage-specific transcriptomic enrichments and putative genomic expansions provide the molecular substrate for the “generalist” vs. “specialist” strategies observed in these taxa [48], suggesting that gene family turnover is a primary driver of niche diversification in Tetrigidae [49, 50].

Validating species boundaries in Hedotettix

The taxonomic validity of H. latifemurus and H. gracilis has been debated due to the potential for phenotypic plasticity to mimic interspecific variation [40]. Our study resolves this uncertainty by demonstrating a deep divergence time of approximately 15.87 Mya between these two lineages [5]. Furthermore, the functional differentiation of their expanded gene families mirrors their morphological distinction. H. gracilis, characterized by an obtusely produced anterior pronotal margin, exhibits a specific expansion of genes governing structural morphogenesis and muscle attachment. This suggests that its distinct pronotal architecture is not merely a plastic response to environmental cues, but a genetically fixed trait underpinned by the expansion of specific structural gene networks [51–53]. This integrative morpho-molecular evidence supports the retention of both taxa as valid biological species and highlights the utility of comparative transcriptomics in delimiting cryptic species complexes [54, 55].

Potential metabolic shifts underlying wing dimorphism

The identification of 18 conserved KEGG pathways enriched between LW and SW morphs across four phylogenetically diverse tetrigid species provides preliminary evidence for shared molecular underpinnings of wing dimorphism in Tetrigidae. Among these, the consistent enrichment of five core signaling pathways—cAMP, calcium, cGMP-PKG, insulin, and endocytosis—is notable, as these pathways collectively integrate hormonal regulation, morphogen-mediated patterning, and growth control during insect wing development [56–59]. The cAMP signaling pathway, which mediates the downstream effects of both ecdysone and juvenile hormone [60], contained DEGs in all four species, suggesting that hormonal signal transduction represents a conserved axis of morph differentiation.

Among the supportive pathways, the enrichment of oxidative phosphorylation—particularly prominent in H. gracilis (11 DEGs)—is consistent with the bioenergetic demands associated with flight muscle development and maintenance in LW morphs. This pattern, together with the enrichment of pyruvate metabolism across species, is compatible with the hypothesis that wing dimorphism involves a metabolic trade-off between aerobic capacity in LW morphs and alternative energy allocation strategies in SW morphs [61]. However, we emphasize that these inferences remain tentative given that our transcriptomic data derive from whole-body RNA extractions. In insects, flight-related metabolic reprogramming is primarily localized to thoracic flight muscles and associated tissues, and whole-body sampling inevitably integrates signals from multiple tissue types, potentially diluting or confounding tissue-specific expression patterns. The moderate number of DEGs per pathway (typically 1–11 per species) further suggests that the transcriptomic signal of wing morph differentiation, while statistically significant, is subtle at the whole-organism level.

Methodological considerations and limitations

While this study provides an integrated phylogenomic and transcriptomic framework for Tetrigidae, several methodological limitations must be acknowledged. It is important to acknowledge that our transcriptomic profiling was conducted using whole-body samples. Because flight capacity and morph differentiation in insects are tightly linked to tissue-specific regulation (e.g., flight muscles and endocrine glands), whole-body RNA extracts might dilute localized expression signals. Consequently, our findings regarding metabolic reprogramming and signaling pathway shifts should be interpreted as preliminary global trends. Future targeted studies utilizing tissue-specific RNA-seq or qPCR validation are warranted to corroborate these functional trade-offs.

A broader methodological consideration concerns the reliability of gene family evolution inferences drawn from transcriptomic data. The CAFE birth–death model was originally designed for genomic locus counts, and the application of this framework to de novo transcriptome assemblies introduces systematic uncertainties. Assembly fragmentation may artificially split single-copy genes into multiple orthogroup members, while expression-level biases mean that genes not transcribed under our sampling conditions remain undetected—potentially leading to both overestimation and underestimation of family sizes. We have taken several steps to mitigate these issues, including stringent orthogroup filtering and the inclusion of three genome-based reference species as internal benchmarks. Nonetheless, we explicitly acknowledge that the gene family expansion and contraction patterns reported here represent transcriptomic approximations, and the adaptive interpretations we propose should be regarded as working hypotheses rather than definitive conclusions. Future studies incorporating genome assemblies for these species will be essential to distinguish true gene duplications from transcriptomic artifacts and to rigorously quantify the genomic basis of ecological adaptation in Tetrigidae.

Conclusions

In summary, this study leverages comprehensive transcriptomic and genomic datasets to resolve long-standing taxonomic enigmas in Tetrigidae. We demonstrate that morphological convergence frequently masks true evolutionary relationships, necessitating a re-evaluation of the Scelimeninae and Tetriginae subfamilies. Furthermore, we identify specific gene family expansions and metabolic pathways that underpin ecological adaptation and wing polymorphism. These findings not only clarify the systematics of Ergatettix and Hedotettix but also provide a generalizable framework for understanding how genomic evolution drives phenotypic diversity in hemimetabolous insects.

Authors' contributions

W.A.D. and D.L.G. conceived and designed the study. W.A.D., B.W.Z., and Y.M.L. collected the samples. W.A.D. performed the morphological identification of the species. Y.M.L. and R.J.Z. performed the experiments, including RNA extraction and library preparation. D.L.G. and Y.M.L. performed the bioinformatic analyses and prepared all Figures. D.L.G. wrote the main manuscript text. W.A.D. supervised the project and critically revised the manuscript. All authors read and approved the final manuscript.

Funding

The project is supported by the Guangxi Natural Science Foundation under Grant No. 2023GXNSFDA026037, the Science & Technology Fundamental Resources Investigation Program of China (2023FY100200) and the National Natural Science Foundation of China (32360124; 32560123).

Data availability

The raw sequence data were deposited in NCBI’s SRA under the Accession Number: PRJNA1393755.

Declarations

Ethics approval and consent to participate

Ergatettix serrifemora, Criotettix damingshanensis, Hedotettix latifemurus, and Hedotettix gracilis are not regulated invertebrate species. The sample collection was carried out in strict accordance with the legal framework of China. The sampling sites were neither privately owned nor located within national nature reserves, and no conflicts of interest were involved. All samples were processed in accordance with the guiding principles specified in the Regulations for the Administration of Affairs Concerning Experimental Animals approved by the State Council of the People’s Republic of China, ensuring that no unnecessary harm was inflicted on the animals and that every effort was made to minimize their suffering. The experimental protocol was reviewed and approved by the Animal Care and Use Committee of Guangxi Normal University.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.