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. 2026 Apr 2;16(4):e73342. doi: 10.1002/ece3.73342

Complete Chloroplast Genome of the Eria Sensu Lato Complex (Orchidaceae): Comparative Analysis and Phylogenetic Relationship

Xinyi Wu 1,2, Jian Li 1,2, Tingzhang Li 1,2, Fengxia Tang 1,2, Xiaojuan Duan 1,2, Wenhui Rao 1,2, Meina Wang 1,2,✉
PMCID: PMC13045314  PMID: 41939992

ABSTRACT

The Eria sensu lato (Eria s.l.) complex represents a highly diverse yet taxonomically challenging orchid lineage. To comprehensively elucidate its evolutionary history, we sequenced 14 complete chloroplast genomes and assembled a robust 18‐taxon dataset encompassing its major generic lineages. Comparative genomic analyses revealed that despite overall structural conservation with no rearrangements detected (genome sizes ranging from 150.9 to 159.7 kb), the complex exhibits a lineage‐specific, stepwise degradation of the NAD(P)H dehydrogenase (NDH) complex. This progressive gene loss, coupled with the physical contraction of inverted repeat (IR) boundaries, directly drives plastome miniaturization in specific taxa (e.g., Eria corneri and E. clausa ). To facilitate fine‐scale species delimitation, we identified seven hypervariable mutational hotspots, which successfully resolved the majority of interspecific relationships with a topology highly congruent to the whole‐plastome tree. Furthermore, selective pressure analysis via branch‐site models detected strong episodic positive selection acting on the ycf1 gene specifically within the Pinalia clade, highlighting potential eco‐physiological adaptations to dynamic epiphytic environments. Finally, phylogenomic reconstructions and divergence dating unveiled a topological incongruence suggesting rapid evolutionary radiation. This concentrated period of early divergence (9.97–5.53 Ma) coincides with Late Miocene paleoclimatic shifts, particularly the intensification of the Asian summer monsoon. Ultimately, this study significantly enriches the plastomic resources for the taxonomically difficult Eria s.l. complex, laying a valuable foundation for future evolutionary studies and systematic revisions.

Keywords: chloroplast genome, Eria s.l., Orchidaceae, phylogenetic analysis, positive selection, rapid radiation

We sequenced and assembled 18 complete chloroplast genomes representing the Eria sensu lato complex. Our comparative analyses unveiled stepwise NDH complex degradation, lineage‐specific positive selection on ycf1, and climate‐driven rapid radiation during the Late Miocene. These findings provide robust phylogenomic insights and novel molecular markers for the evolutionary history and conservation of this complex orchid group.

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1. Introduction

The Orchidaceae subtribe Eriinae encompasses a highly diverse and ecologically significant group of epiphytic and lithophytic orchids, widely distributed across tropical Asia. Historically, its most prominent member, the genus Eria Lindl., was treated as a massive and morphologically heterogeneous group, commonly referred to as the Eria sensu lato (Eria s.l.) complex. Comprising approximately 370 species globally, including 44 species distributed in China (Chen et al. 2009), this group suffered from a broad and poorly defined taxonomic scope (Chase et al. 2003). Extensive morphological variations and widespread convergences have rendered its internal taxonomy notoriously chaotic, leading early researchers to suspect its polyphyletic nature (Seidenfaden 1982; Ng 2002). Subsequent molecular studies utilizing traditional nuclear (ITS) and plastid markers (matK, trnL‐F) conclusively confirmed that Eria s.l. is highly polyphyletic. Consequently, it has been segregated into several morphologically distinct, monophyletic genera, including Pinalia, Cryptochilus, Dendrolirium, and Trichotosia (Ng et al. 2018). Despite these foundational taxonomic revisions, the deep‐level evolutionary relationships among these generic lineages—as well as the fine‐scale species boundaries within their recently diverged clades—remain ambiguous or weakly supported due to the limited informative sites provided by traditional few‐gene approaches. Consequently, there is a severe lack of comprehensive, genome‐scale phylogenetic studies dedicated to fully resolving the evolutionary history of this complex.

To overcome the limitations of conventional molecular markers, chloroplast (plastid) phylogenomics has emerged as a robust tool for resolving complex plant evolutionary histories. As highlighted in recent perspectives, while the utility of plastomes in resolving deep phylogenetic backbones is well established, much more remains to be explored at the species and population levels (Wang et al. 2024). At these fine‐scale taxonomic levels, whole‐plastome data provide unparalleled resolution for clarifying complex evolutionary relationships in hyper‐diverse orchid groups, such as Bulbophyllum and Cymbidium (Chen et al. 2024; Simpson et al. 2024). Furthermore, comparative plastomes analysis profoundly unveils lineage‐specific evolutionary dynamics, such as structural rearrangements, the recurrent loss of the ndh gene family, and adaptive evolution across varying ecological niches (Xue et al. 2023). Crucially, it also allows for the precise screening of hypervariable mutational hotspots. These tailored loci can be explicitly validated as highly sensitive DNA barcodes to trace maternal ancestry within complex groups (Dong et al. 2025) and resolve closely related species where traditional universal barcodes fail (Liu et al. 2023).

Despite its tremendous taxonomic complexity, the Eria s.l. complex remains largely unexplored at the plastome level. To address this critical knowledge gap, we sequenced and assembled the complete chloroplast genomes of 14 key Eriinae species sourced from China. These newly generated sequences were combined with previously published data to assemble a comprehensive 18‐taxon dataset encompassing all major generic lineages within the Eria s.l. complex. By leveraging this plastome‐scale data, our study aims to (1) characterize the genomic structure and investigate lineage‐specific gene loss events within Eria s.l.; (2) identify and in silico validate novel, hypervariable DNA barcodes tailored for this complex; (3) assess selective pressures to uncover signals of adaptive evolution linked to their epiphytic habitats; and (4) robustly reconstruct the phylogenetic backbone to elucidate the rapid radiation and evolutionary history of the Eria s.l. complex. Ultimately, this study provides a foundational phylogenomic framework for the future conservation, systematic revision, and evolutionary study of Eriinae.

2. Materials and Methods

2.1. Plant Materials and DNA Extraction

The plant samples used in this study were sourced from the National Orchid Conservation & Research Center of Shenzhen, with corresponding specimens stored in the herbarium of the same institution. Details of the samples, including 14 species newly sequenced for this research and 5 species obtained from the National Center for Biotechnology Information (NCBI), are provided in Table 1 (Table S1). Genomic DNA was extracted from leaf tissues using the Cetyltrimethylammonium bromide (CTAB) protocol (Doyle and Doyle 1987). To generate high‐quality sequence data, paired‐end sequencing (150 bp read length) was performed on an Illumina Novaseq X platform (Illumina, San Diego, CA, USA) at Novogene (Beijing, China), yielding approximately 8 Gb of raw data per species.

TABLE 1.

Complete chloroplast genome features of different Eria s.l. species.

Species Cp genome LSC IR SSC GC content (%) Number of Protein‐coding tRNA rRNA
Length (bp) Length (bp) Length (bp) Length (bp) Total LSC IR SSC Genes Genes Genes Genes
Cryptochilus roseus 159,479 87,113 26,917 18,532 37.0 34.7 43.1 30.0 131 85 38 8
Cryptochilus strictus 158,615 87,735 26,207 18,466 36.9 34.6 43.2 30.1 131 85 38 8
Dendrolirium lasiopetalum 158,740 88,062 26,213 18,252 37.0 34.7 43.2 30.3 131 85 38 8
Dendrolirium pachyphylla 159,715 87,232 26,983 18,517 37.1 34.8 43.1 30.1 131 85 38 8
Dendrolirium tomentosum 159,112 87,730 26,644 18,094 37.1 34.8 43.1 30.3 131 85 38 8
Eria corneri (MN477202) 150,956 85,316 25,437 16,323 37.3 34.9 43.5 30.0 127 81 38 8
Eria corneri 150,973 85,979 25,502 13,973 37.3 34.9 43.5 30.1 127 81 38 8
Eria coronaria 156,129 85,978 25,510 13,975 37.4 34.9 43.5 30.1 131 85 38 8
Eria javanica 156,807 84,475 26,942 17,770 37.3 35.0 43.1 30.5 131 85 38 8
Eria clausa 152,513 85,995 26,926 16,960 37.3 35.0 43.1 30.4 130 84 38 8
Pinalia acervata 159,286 87,211 26,808 18,459 37.0 34.7 43.0 30.1 131 85 38 8
Pinalia amica 158,566 86,807 26,655 18,449 37.1 34.8 43.1 30.1 131 85 38 8
Pinalia bipunctata 159,161 87,098 26,786 18,491 37.0 34.8 43.1 30.1 131 85 38 8
Pinalia obvia 159,466 87,333 26,826 18,481 36.9 34.7 43.1 30.1 131 85 38 8
Pinalia szetschuanica 158,737 87,150 26,540 18,507 37.0 34.7 43.2 30.1 131 85 38 8
Pinalia yunnanensis 158,486 86,486 26,759 18,482 37.0 34.7 43.1 30.1 131 85 38 8
Trichotosia pulvinata 159,201 87,246 26,929 18,097 37.1 34.8 43.1 30.5 131 85 38 8
Trichotosia velutina 159,105 87,346 26,796 18,167 37.1 34.8 43.1 30.4 131 85 38 8
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2.2. Chloroplast Genome Assembly and Annotation

Chloroplast genomes were assembled using GetOrganelle v1.7.5 (Jin et al. 2020) with the default parameters ‐R 15 ‐k 21,45,65,85,105 and the ‐F embplant_pt flag, utilizing Trichotosia velutina (OR544616) and Eria corneri (MN477202) as reference. Initial genome annotation was performed using the Plastid Genome Annotator (PGA) (Qu et al. 2019). To ensure the accuracy of start/stop codons and exon‐intron boundaries, the annotation results were manually inspected and corrected by comparing them with homologous genes from the reference species. Furthermore, tRNA genes were further verified using tRNAscan‐SE v2.0 (Lowe and Chan 2016) with default settings.

2.3. Comparative Analysis of Cp Genomes

The online tool CPJSdraw was uesd to examine and visualize the expansion and contraction of the LSC, SSC, IRa, and IRb boundaries in the chloroplast genomes of Eria s.l. species (Li, Guo, et al. 2023). To assess whole‐plastome sequence divergence and detect potential structural rearrangements (e.g., gene inversions or translocations), multiple sequence alignment of the chloroplast genomes of the 17 species was conducted using the mVISTA program (https://genome.lbl.gov/vista/mvista, accessed on 12 January 2026) in the Shuffle‐LAGAN mode, with the Pinalia obvia sequence serving as the reference (Brudno et al. 2003).

2.4. Repeat Sequence Analysis

Long repetitive sequences (LSRs), including forward, reverse, complement, and palindromic repeats, were detected using the REPuter program (https://bibiserv.cebitec.uni‐bielefeld.de/reputer, accessed on 10 February 2026), with a minimum repeat length of 30 bp and a Hamming distance of 3 (Kurtz et al. 2001). Simple sequence repeats (SSRs) were identified with the MISA‐web Perl script (Beier et al. 2017), applying minimum repeat unit thresholds of 10, 5, 4, 3, 3, and 3 for mono‐, di‐, tri‐, tetra‐, penta‐, and hexa‐motif microsatellites, respectively.

2.5. Nucleotide Diversity

To evaluate sequence divergence and identify mutational hotspots across the Eria s.l. plastomes, nucleotide diversity (Pi) analysis was conducted. The shared protein‐coding genes (CDS) and intergenic spacer (IGS) regions were extracted using the “Pi” subcommand in CPStools (Huang et al. 2024). Prior to the calculation of Pi values, sequences for each extracted region were independently aligned using MAFFT v7.505 (Katoh and Standley 2013). Following the alignment and calculation, regions exhibiting exceptionally high nucleotide diversity (Pi > 0.048) were selected as potential candidate DNA barcodes. The discriminatory power of these combined hypervariable loci was subsequently evaluated through phylogenetic reconstruction.

2.6. Gene Selective Pressure Analysis

To assess selective pressures on plastid CDS, we calculated the synonymous (Ks), non‐synonymous (Ka) substitution rates, and their ratio (Ka/Ks). First, 75 shared CDS were extracted from the annotated GenBank files using the python script get_annotated_regions_from_gb.py (available at https://github.com/Kinggerm/PersonalUtilities/). The sequences were aligned based on amino acid translations using MAFFT v7.505 and subsequently back‐translated to nucleotides with internal stop codons removed via Biopython (Cock et al. 2009). Pairwise Ka and Ks values were calculated using KaKs_Calculator v3.0 (Zhang 2022) under default settings, designating Pinalia amica as the reference species. Genes with undefined Ka/Ks ratios (Ks = 0) were excluded, retaining 42 genes. A Ka/Ks ratio > 1 indicates positive (adaptive) selection, while < 1 indicates purifying selection.

Furthermore, the branch‐site model in the codeml program of PAML v4.10.7 (Yang 2007) was used to detect episodic positive selection driving lineage divergence. Based on the reconstructed phylogeny, the five major generic lineages within Eria s.l. were successively designated as foreground branches. Likelihood Ratio Tests (LRTs) were performed comparing the alternative model (Model 2, NSsites = 2, fix_omega = 0) to the null model (Model 2, NSsites = 2, fix_omega = 1, omega = 1) (Zhang et al. 2005). Statistical significance was assessed using a Chi‐square distribution (df = 1).

2.7. Phylogenetic Analysis

To resolve the relationships among the 18 Eria s.l. species, four datasets were constructed: (1) complete chloroplast genomes; (2) 79 shared CDS; (3) 133 IGS regions; and (4) concatenated hypervariable regions. Sequences extracted via PhyloSuite (Zhang et al. 2020) were aligned using MAFFT v7.505 and trimmed with trimAl v1.2 (Capella‐Gutiérrez et al. 2009). Maximum Likelihood (ML) phylogenies for all four datasets were reconstructed using IQ‐TREE v1.6 (Nguyen et al. 2015). The optimal substitution model, TVM + F + R2, was automatically identified by ModelFinder according to the BIC (Kalyaanamoorthy et al. 2017). Node support was comprehensively assessed using a combination of the SH‐aLRT test (1000 replicates) and standard non‐parametric bootstrapping (1000 replicates). To corroborate the ML topology, Bayesian Inference (BI) was performed exclusively on the 79 CDS dataset using MrBayes v3.2 (Ronquist et al. 2012). Two independent MCMC runs of 50,000,000 generations were executed, sampling every 1000 generations until convergence, with a 25% burn‐in.

2.8. Divergence Time Estimation

To estimate species divergence times, an expanded 64‐taxon plastome dataset (Table S5) was analyzed. From this dataset, 67 shared CDS were extracted, aligned using MAFFT v7.505, and concatenated. A time‐calibrated BI phylogeny was first reconstructed using MrBayes v3.2 based on models determined by ModelTest‐NG (Darriba et al. 2020), utilizing two MCMC runs of 1000,000 generations and a 25% burn‐in. Based on this topology, molecular dating was performed using the Bayesian relaxed clock method in the mcmctree program (PAML v4.10.7). Two reliable orchid fossils constrained the crown clades of Dendrobium (23.2 Ma; Conran et al. 2009) and Goodyerinae (15.0 Ma). Secondary calibration priors were applied to the stem node of Orchidaceae/monocots (112.0 Ma; Ramírez et al. 2007) and the most recent common ancestor of all extant orchids (90.0 Ma; Givnish et al. 2015, 2016; Xiang et al. 2016).

3. Results

3.1. Chloroplast Genome Features

The chloroplast genomes of the 18 Eria s.l. species analyzed in this study exhibited a typical double‐stranded, circular, quadripartite structure. The genome sizes varied significantly, ranging from 150,956 bp in Eria corneri (MN477202) to 159,715 bp in Dendrolirium pachyphylla. The overall GC content of these genomes ranged from 36.9% to 37.4%. Most species contained 131 genes, including 85 CDS, 8 rRNA genes, and 38 tRNA genes. However, two species exhibited a reduced gene complement due to specific gene losses: Eria clausa contained 130 genes (with 84 CDS), while E. corneri displayed a more reduced plastome comprising only 127 genes (with 81 CDS). The lengths of the large single‐copy (LSC) and small single‐copy (SSC) regions showed interspecific variation, ranging from 84,475 to 88,062 bp and 13,973 to 18,532 bp, respectively. The IR regions were relatively conserved, with lengths ranging from 25,437 to 26,983 bp. The GC content within each region was as follows: 43.0%–43.5% in the IR regions, 30.0%–30.4% in the SSC region, and 34.6%–35.0% in the LSC region (Table 1).

In the 18 chloroplast genomes analyzed, all genes appeared as single copies in the LSC or SSC regions. However, 17 gene duplications were observed in the IR regions, including six tRNA genes and nine CDS. Across the entire plastome, three genes (ycf3, clpP, and rps12) each contained two introns, while the others possessed a single intron. The majority of variable sites were found in intergenic spacers, suggesting a higher evolutionary rate in these non‐coding regions compared to coding regions. Additionally, the IR regions exhibited a higher degree of conservation than the LSC and SSC regions across all species. These results suggest that the chloroplast genome structure and gene sequences are highly similar across these species, with no gene rearrangements detected. Notably, however, E. corneri and E. clausa showed significant sequence divergence and specific gene deletions in the SSC region corresponding to the NDH complex. Specifically, E. clausa exhibited an isolated deletion of the ndhF gene, whereas E. corneri displayed a more extensive loss, lacking the ndhA, ndhF, ndhG, and ndhI genes (Figure 1).

FIGURE 1.

FIGURE 1

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Comparison of 18 Eria s.l. chloroplast genomes using the mVISTA program, with the annotation of Pinalia obvia serving as the reference.

3.2. Contraction and Expansion of Inverted Repeats

In this study, the contractions and expansions of the IR regions were systematically analyzed by comparing the four distinct junctions (JLB, JSB, JSA, and JLA) across 17 orchid chloroplast genomes (Figure 2). Although the overall genomic structures are highly conserved, significant variations were observed in the distribution and distances of genes adjacent to these junctions. Two distinct patterns were identified at the LSC/IRb (JLB) boundary. In 14 of the analyzed species, the rpl22 gene spans across the junction. Conversely, in Pinalia acervata, Dendrolirium lasiopetalum, and Eria javanica, this gene is located entirely within the LSC region, positioned at a distance ranging from 5 to 214 bp away from the IRb boundary. The IRb/SSC (JSB) junction was relatively stable among these orchids; in the majority of the genomes, the ndhF gene spanned this boundary. A notable exception occurred in E. Corneri and E. clausa , where ndhF was completely absent at the junction. Furthermore, the SSC/IRa (JSA) and IRa/LSC (JLA) junctions exhibited high conservation across all evaluated genomes. The psbA gene was fully contained within the LSC region in all species, positioned at 110–330 bp from the IRa/LSC (JLA) boundary.

FIGURE 2.

FIGURE 2

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Comparison of the boundaries between the LSC, SSC, and IR regions among 17 Eria s.l. chloroplast genomes.

3.3. Repeat Sequence Analysis

A total of 614 LSRs were detected across the 17 Eria s.l. plastomes, comprising forward (F), reverse (R), complement (C), and palindromic (P) repeats (Figure 3). Palindromic (62.54%) and forward (32.57%) repeats were the most abundant, while reverse and complement repeats were rare. Dendrolirium pachyphylla contained the highest number of LSRs (73), whereas Pinalia yunnanensis possessed the fewest (22). Only four species (Cryptochilus strictus, Pinalia acervata, Pinalia obvia, and Pinalia szetschuanica) exhibited all four repeat types. Conversely, Pinalia amica, P. yunnanensis , Trichotosia pulvinata, and T. velutina completely lacked both reverse and complement repeats.

FIGURE 3.

FIGURE 3

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Frequency of four types of long repeats, Forward (F), Reverse (R), Complement (C), and Palindromic (P), in the chloroplast genomes of 17 Eria s.l. species.

A total of 1134 SSRs were identified, ranging from 57 in Pinalia bipunctata to 81 in T. velutina . Mononucleotide repeats were the most prevalent (66.4%), followed by dinucleotides (17.2%), with longer motifs (tri‐ to hexanucleotides) being progressively less common (Figure 4). Consistent with typical plastome compositions, these SSRs were overwhelmingly A/T‐rich. Regarding their genomic distribution, the majority of SSRs (61.29%) were concentrated in the IGS regions, compared to coding (22.40%) and intronic (16.31%) regions. Notably, our analysis revealed a unique lineage‐specific feature addressing the diversity of SSRs: E. corneri was the only species completely lacking both pentanucleotide and hexanucleotide repeats, a structural reduction that coincides with its miniaturized genome size.

FIGURE 4.

FIGURE 4

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Simple sequence repeats (SSRs) in the chloroplast genomes of 17 Eria s.l. species. (A) Number of different SSR motifs (mono‐, di‐, tri‐, tetra‐, penta‐, and hexa‐). (B) Frequency of SSRs in the intergenic regions (IGS), protein‐coding genes, and introns.

3.4. Nucleotide Diversity and DNA Barcoding Validation

To examine mutation hotspots within the 17 Eria s.l. chloroplast genomes, Pi values were calculated using CPStools for both shared single‐copy genes and intergenic regions (Figure 5, Table S2). The analysis showed higher divergence in the single‐copy regions (LSC and SSC) and greater conservation in the IR region. Furthermore, the Pi values was generally higher in intergenic regions than in coding regions. Among the genes studied, trnG‐GCC (0.08161), ycf1 (0.03068), rps15 (0.01975), rpl36 (0.01938), and rpl22 (0.01652) exhibited the highest Pi values. Based on a threshold of Pi > 0.048, a total of seven hypervariable regions were identified: one gene (trnG‐GCC, 0.08161) and six IGS regions (psaJ‐rpl33, 0.08222; psbT‐psbN, 0.06772; psbB‐psbT, 0.05634; trnL‐UAG‐ccsA, 0.05294; trnF‐GAA‐ndhJ, 0.04992; and petA‐psbJ, 0.04895).

FIGURE 5.

FIGURE 5

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Nucleotide diversity (Pi) across the complete chloroplast genomes of 17 Eria s.l. species. (A) Comparison of the nucleotide variability (PI) among CDS regions. (B) Comparison of the nucleotide variability among IGS regions.

Subsequently, to rigorously assess their utility for species resolution, a phylogenetic tree was reconstructed utilizing the concatenated sequences of these seven specific high‐Pi regions. Remarkably, the resulting topology was identical to those derived from the three comprehensive datasets (the complete chloroplast genomes, the 79 plastid CDS, and the 133 IGS regions), yielding robust branch support across the vast majority of internal nodes (Figure 7).

FIGURE 7.

FIGURE 7

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Phylogenetic trees of Eria s.l. species based on four datasets: (A) complete chloroplast genomes, (B) 79 shared protein‐coding sequences (CDS), (C) 133 intergenic spacer (IGS) regions, and (D) 7 highly variable region concatenation. Agrostophyllum callosum as the outgroup. Numbers at the nodes represent SH‐aLRT/ML bootstrap support values. For tree B, the third number represents the Bayesian posterior probability (PP).

3.5. Positive Selection Analysis

Comparative analysis of selective pressures among 17 Eria s.l. species revealed differential patterns of evolutionary constraint on plastid CDS. The ratio of non‐synonymous (Ka) to synonymous (Ks) substitution rates was calculated for 75 shared CDS across the analyzed species, using P. amica as the reference. The Ka/Ks ratios for most genes were substantially less than 1, with an overall average of 0.2520 (Figure 6, Table S3). However, specific genes exhibited notably elevated Ka/Ks values compared to the background average. Among all analyzed genes, ycf1 displayed the highest sequence divergence, with its maximum pairwise Ka/Ks ratio slightly exceeding 1 (1.0011). Other genes exhibiting relatively high, yet purifying, Ka/Ks values included accD (0.7588), clpP (0.6974), and matK (0.5055).

FIGURE 6.

FIGURE 6

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Ka/Ks ratio of 42 CDS of 17 Eria s.l. chloroplast genomes. The ratios were calculated using Pinalia amica as the reference species. The x‐axis displays the 42 analyzed CDS (genes with undefined Ka/Ks ratios due to Ks = 0 were excluded), and the y‐axis represents the 16 compared species.

To test whether adaptive evolution drove the divergence of key lineages, we used the branch‐site model in codeml to detect signals of positive selection. Based on the reconstructed phylogeny, the five genera investigated in this study were successively designated as foreground branches. Following LRTs on 75 CDS, the ycf1 gene was identified as having undergone episodic positive selection specifically on the Pinalia branch. A comparison of the alternative and null models revealed a significant increase in the log‐likelihood value for ycf1 (ln L 1 = −10583.60, ln L 0 = −10592.84), with an LRT statistic (2ΔlnL) of 18.48 (df = 1, p < 0.001) (Table S4).

3.6. Phylogenetic Analysis and Divergence Times

Phylogenetic analyses utilizing ML across four distinct datasets (A: complete chloroplast genomes; B: 79 shared CDS; C: 133 IGS regions; and D: concatenated seven highly variable regions), complemented by BI on the CDS dataset (B), yielded highly congruent topologies (Figure 7). The sampled Eria s.l. taxa formed a strongly supported monophyletic clade and were classified into five major generic clades. Within this complex, the genus Eria s.s. is positioned at the base of the tree, forming a sister group to the clade containing the other four genera. In these unconstrained phylogenies, Pinalia and Trichotosia form one clade (e.g., 100/100 support in Tree A), while Cryptochilus and Dendrolirium form another (e.g., 91.9/88 support in Tree A), with these two clades being sister groups.

Conversely, the time‐calibrated chronogram (Figure 8) inferred a slightly different, grade‐like topology for the generic divergence following the initial split of Eria. Divergence time estimation indicated that the stem age of the Eria s.l. clade was approximately 12.40 million years ago (Ma). The initial crown diversification commenced in the Late Miocene, with the genus Eria diverging from the ancestor of the remaining four genera at 9.97 Ma. Within the remaining clade, Cryptochilus diverged next at approximately 6.55 Ma. This was followed by the divergence of Dendrolirium at 6.34 Ma. The terminal split between the sister genera Pinalia and Trichotosia occurred near the Miocene–Pliocene boundary at 5.53 Ma. Finally, within the Pinalia lineage, crown diversification initiated around 4.03 Ma, with P. amica occupying the most basal position, while terminal species such as P. bipunctata , P. yunnanensis , and P. obvia diverged much more recently during the Pleistocene (c. 2.51–1.15 Ma).

FIGURE 8.

FIGURE 8

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Divergence time estimation of Eria s.l. and related taxa. The time‐calibrated phylogeny was inferred based on 67 CDS from 64 taxa. Numbers at the nodes indicate the estimated divergence times in millions of years ago (Ma).

4. Discussion

4.1. Chloroplast Genome Characteristics and NDH Loss

In this study, we report the complete chloroplast genomes of 14 Eria s.l. species for the first time and compare them with those of four previously published species. The chloroplast genomes of the 18 Eria s.l. species exhibited a highly conserved quadripartite structure, gene order, and overall GC content. The absence of major structural rearrangements or inversions, as evidenced by our comparative analyses, indicates a stable evolutionary history of the plastome macrostructure within this complex, which is consistent with patterns observed in most epidendroid orchids.

In higher plants, the chloroplast NAD(P)H dehydrogenase (NDH) complex mediates cyclic electron flow around photosystem I, which is essential for alleviating photo‐oxidative stress and maintaining photosynthetic efficiency (Shikanai 2016). A fully functional NDH complex comprises 11 plastid‐encoded subunits (ndhA–K). Our comparative genomic analysis revealed a fascinating intrageneric divergence in the retention of these ndh genes within the Eria genus. Most of the examined species, including E. coronaria and E. javanica , retain a complete and highly conserved set of all 11 plastid ndh genes. This indicates that the complete NDH pathway was functionally conserved in the common ancestor of the Eria complex. However, a remarkable pattern of lineage‐specific genomic reduction was observed within a distinct and well‐supported clade comprising E. corneri and E. clausa . While E. clausa exhibited only the isolated loss of the ndhF gene, its sister species, E. corneri, displayed much more severe degradation, lacking the ndhA, ndhF, ndhG, and ndhI genes. This substantial divergence within a single subclade provides compelling evidence for a stepwise degradation model of the NDH complex. Our findings align perfectly with the evolutionary trajectory recently revealed in Cymbidium, where the recurrent loss of ndhF at dynamic IR boundaries triggered progressive degradation and widespread pseudogenization of the entire NDH complex across independent lineages (Chen et al. 2025; Kim et al. 2015). We hypothesize that the initial structural disruption of ndhF occurred in the common ancestor of E. corneri and E. clausa .

Similar patterns of ndh gene loss have been widely observed in other genera within the Epidendroideae subfamily, such as Calanthe, Dendrobium, and Epidendrum (Chen et al. 2020; Xue et al. 2023; Zhao et al. 2023), implying that the NDH complex is not strictly essential for specific photosynthetic orchids. Sanderson et al. (2015) proposed that the inactivation of the ndh gene family might be strongly associated with an epiphytic lifestyle. To optimize photosynthesis under fluctuating canopy light environments, these epiphytes might rely on alternative physiological mechanisms, such as the PGR5/PGRL1‐dependent CEF pathway, to compensate for the loss of NDH function. Additionally, while some orchids have shown a transfer of ndh genes from the chloroplast to the mitochondrial (mt) or nuclear genome to maintain functionality, there is currently no definitive evidence directly linking this intracellular gene transfer to the initial loss of these genes in orchid chloroplast genomes (Lin et al. 2015). The rapid and progressive dismantling of the NDH complex in E. corneri and E. clausa thus highlights a dynamic genomic adaptation to their specific epiphytic niches.

4.2. Dynamics of IR Boundaries

Despite the overall structural stasis within the Eria s.l. complex, significant variations in genome size (ranging from 150,956 bp to 159,715 bp) were observed. Previous studies have shown that the contraction and expansion of IR boundaries are common events in plastid evolution, significantly influencing variations in plastid length and gene content across angiosperms (Raubeson et al. 2007). The size of the orchid plastome is also strongly related to changes in IR boundaries (Guo et al. 2021). Numerous studies have pointed out that instability at the IR/SSC junctions in orchids is strongly correlated with the loss of the ndhF gene (Kim et al. 2015; Niu et al. 2017).

In our study, only the LSC/IRb and IRb/SSC junctions exhibited two types among the 18 species across the four boundaries, while the other two (SSC/IRa and IRa/LSC) remained more conserved and stable (Figure 2). Notably, the variation in the JSB in E. corneri and E. clausa may be potentially linked to the absence of the ndhF gene, which likely contributes to the observed reduction in their chloroplast genome size compared to other Eria s.l. species. The connection between the ndh gene loss and genome size reduction has also been reported in the genera Chiloschista, Bulbophyllum, and Renanthera (Liu et al. 2023; Tao et al. 2023; Wu et al. 2024).

While the position of the boundaries, especially the expansion and contraction of the IR region, may provide insights into lineage evolution, our observations do not offer sufficient information to clarify the evolutionary relationships among taxa. Consequently, resolving the complex taxonomy of this group necessitates further sampling and more comprehensive comparisons relying on highly variable regions or whole‐plastome data.

4.3. Repeat Sequence Analysis

Repeat sequences, including SSRs and LSRs, are fundamental drivers of chloroplast genome rearrangement, sequence divergence, and mutation generation (Cavalier‐Smith 2002). In the examined Eria s.l. plastomes, palindromic and forward repeats were the most abundant LSRs (Figure 3). These large repeats are frequently associated with mutational hotspots and promote structural diversity in intergenic regions across orchid plastomes.

Regarding SSRs, the motifs identified in our study were highly A/T‐biased, consistent with observations in other plant plastomes (Jiang et al. 2022; Li, Wang, et al. 2023). While this compositional bias is a ubiquitous phenomenon attributed to the overall low GC content of plastomes, the genomic distribution of these repeats provides significant evolutionary insights. As Ellegren (2004) demonstrated, the distribution and variation of microsatellites within genomes directly reflect underlying selective pressures. In our analysis, we observed a highly non‐random distribution, with the vast majority of SSRs (61.29%) concentrated in the IGS regions, while their frequency was heavily suppressed in CDS (Figure 4). This distribution pattern strongly implies that stringent purifying selection acts to eliminate repeat expansions or contractions within coding regions to maintain reading frame integrity. Conversely, non‐coding regions experience relaxed purifying selection, permitting the accumulation of these mutational elements to drive sequence divergence (Liu et al. 2025).

A particularly noteworthy finding in our analysis is the absence of complex SSRs (pentanucleotide and hexanucleotide repeats) in E. corneri. As discussed previously, E. corneri possesses the smallest chloroplast genome among the sampled taxa, primarily due to the extensive degradation of the NDH complex and the contraction of its IR regions. The concurrent lack of complex, long‐motif SSRs in this species suggests a potential correlation between overall plastome miniaturization and a general suppression or loss of complex repetitive elements. A similar coupled reduction of genome size and repeat complexity has been documented in other highly specialized or reduced plastomes (Wicke et al. 2011). Ultimately, the abundant and variable repeat sequences identified in these Eria s.l. species represent an invaluable genomic resource, providing excellent candidate loci for developing highly polymorphic molecular markers for future population genetics and phylogeographic studies.

4.4. Phylogenetic Validation of Specific DNA Barcodes

Traditional universal DNA barcodes often fail to resolve the complex taxonomy of closely related Orchidaceae species, necessitating the identification of supplementary or lineage‐specific markers (Li et al. 2021). Through Pi analysis of the Eria s.l. plastomes, we identified seven hyper variable mutational hotspots (Pi > 0.048): one tRNA gene (trnG‐GCC) and six IGS (psaJ‐rpl33, psbT‐psbN, psbB‐psbT, trnL‐UAG‐ccsA, trnF‐GAA‐ndhJ, and petA‐psbJ). Notably, while the ycf1 gene is frequently utilized as a universal barcode in many plant lineages, it exhibited lower variability (Pi = 0.03068) than our identified top‐tier hotspots (Figure 5). The identification of these seven superior loci demonstrates the critical value of screening whole plastomes to discover lineage‐specific markers, particularly since standard universal barcodes frequently fail to provide adequate resolution in complex orchid groups (Li et al. 2021; Simpson et al. 2024).

By reconstructing a phylogenetic tree utilizing the concatenated alignment of these seven novel hotspots, we found that the resulting topology was identical to those derived from three comprehensive datasets: the complete chloroplast genomes, the 79 plastid CDS, and the 133 IGS regions (Figure 7). This highly stable topology also yielded robust bootstrap support across most internal nodes. Previous foundational studies have successfully clarified the broad generic boundaries and phylogenetic framework of the Eria s.l. complex using standard nuclear and plastid markers (Ng et al. 2018). However, such conventional loci frequently encounter limitations in resolving power when differentiating closely related terminal species. Our in silico validation demonstrates that the combination of these seven newly identified loci harbors a significantly denser phylogenetic signal. While future empirical studies involving population‐level PCR amplification will be necessary for ultimate field application (Hollingsworth et al. 2011), this specifically tailored multi‐locus barcode provides a highly sensitive and cost‐effective tool to complement traditional markers for fine‐scale species delimitation within this challenging group.

4.5. Adaptive Evolution of Plastid Protein‐Coding Genes

The evolutionary rate and selective pressure acting on CDS provide profound insights into the adaptive mechanisms of plant lineages. In our pairwise Ka/Ks analysis using P. amica as a reference, the overwhelming majority of the 79 plastid CDS exhibited Ka/Ks ratios substantially lower than 1 (overall average = 0.2520). This prevailing pattern indicates that strong purifying selection acts to maintain the functional conservatism of the chloroplast genome across the Eria s.l. complex, ensuring the stability of the essential photosynthetic apparatus (Weng et al. 2014). Nevertheless, specific genes exhibited notably elevated non‐synonymous substitution rates. For instance, the ycf1 gene displayed a relatively high evolutionary rate; however, Ka/Ks ratios strictly greater than 1 were only observed in specific pairwise comparisons (e.g., against C. strictus and Trichotosia species), while remaining below 1 in others (Figure 6, Table S3). While pairwise metrics provide a valuable overview of average selective pressures across entire genes and lineages, evolutionary adaptations can also be driven by episodic positive selection acting on specific amino acid sites within clades (Zhang et al. 2005). To further investigate these fine‐scale evolutionary dynamics, we additionally performed selection pressure analysis using the branch‐site model in PAML. By designating the distinct generic clades as foreground branches, we unequivocally identified a highly significant signal of positive selection (p < 0.001) acting exclusively on the ycf1 gene within the Pinalia lineage.

The ycf1 gene is widely recognized as one of the largest and most rapidly evolving genes within plant plastomes. Accumulating evidence indicates that ycf1 encodes the TIC214 protein, an indispensable core component of the translocon at the inner chloroplast envelope (TIC) complex. This complex fundamentally regulates the import of numerous nuclear‐encoded precursor proteins that are vital for plastid development, homeostasis, and stress responses (Kikuchi et al. 2013). The detection of strong episodic positive selection on the ycf1 gene specifically within the Pinalia lineage constitutes a compelling evolutionary footprint. Given the specific epiphytic or lithophytic ecological niches occupied by Pinalia species, adaptive mutations within the TIC214 translocon might have been favored to optimize the selective import of specific nuclear‐encoded functional proteins under fluctuating environmental stresses, such as intense canopy light or periodic drought (Fan et al. 2018). Consequently, the localized positive selection acting on ycf1 likely facilitated the successful evolutionary radiation and specific eco‐physiological adaptations of the Pinalia clade within the broader Eria s.l. complex.

4.6. Phylogenetic Relationships and the Rapid Radiation of the Eria s.l.

Our phylogenetic analyses strongly supported the monophyly of the Eria s.l. complex. Consistent with previous multi‐locus studies (Ng et al. 2018), Eria was identified as the basal diverging lineage (estimated at 9.97 Ma). While traditional markers often yielded unresolved, polytomy‐like backbones for the remaining clades (Ng et al. 2018), our plastome‐scale data recovered a highly supported topology for the five sampled genera (Figure 7). Across all evaluated datasets, ML analyses consistently recovered a sister relationship between Pinalia and Trichotosia (diverging at 5.53 Ma), as well as a clustering of Cryptochilus and Dendrolirium. Interestingly, the time‐calibrated chronogram inferred a successive divergence for the latter two genera rather than a sister relationship. This topological incongruence is likely attributed to their extremely narrow divergence window (Cryptochilus at c. 6.55 Ma, followed by Dendrolirium at 6.34 Ma). Such a short interval (c. 0.21 million years) suggests an episode of rapid evolutionary radiation, where lineages lack sufficient time to accumulate synapomorphies, frequently causing soft conflicts between unconstrained algorithms and molecular clock models (Whitfield and Lockhart 2007). While restricted taxon sampling might also partially influence these deep nodes (Zwickl and Hillis 2002), this rapid radiation hypothesis provides a robust evolutionary explanation.

This inferred Late Miocene radiation (9.97–5.53 Ma) coincides with major paleoclimatic events, particularly the intensification of the Asian summer monsoon and the Himalayan–Tibetan plateau uplift (Favre et al. 2015). These profound environmental shifts likely acted as catalysts for rapid diversification, a pattern similarly observed in other Asian epiphytic orchids like Cymbidium and Dendrobium (Givnish et al. 2015; Xue et al. 2023; Chen et al. 2024). At the infrageneric level, the Pinalia lineage underwent recent crown diversification starting around 4.03 Ma, with terminal taxa ( P. bipunctata , P. yunnanensis, and P. obvia) speciating during the Pleistocene (c. 2.51–1.15 Ma). This extremely recent divergence perfectly explains their considerable plastome conservation and low genetic divergence. Overall, our study demonstrates that the generic and infrageneric diversity within Eria s.l. was predominantly shaped by climate‐driven rapid radiation.

5. Conclusion

In this study, we sequenced and assembled the complete chloroplast genomes of 14 Eria s.l. species and performed a comprehensive comparative phylogenomic analysis across 18 representative taxa. Our analysis revealed a highly conserved chloroplast genome macrostructure across these species, characterized by high similarity in GC content, overall gene number, and gene order. We identified significant interspecific variations in genome size and inverted repeat (IR) boundaries, most notably characterized by the lineage‐specific, stepwise degradation of the NDH complex in taxa such as E. corneri and E. clausa . Furthermore, we found strong evidence of episodic positive selection in the ycf1 gene within the Pinalia clade, suggesting its adaptive role in plastid protein import mechanisms within dynamic epiphytic environments. Additionally, our phylogenomic reconstructions and divergence dating provided crucial insights into the backbone relationships of the complex, uncovering an episode of climate‐driven rapid evolutionary radiation during the Late Miocene. Leveraging nucleotide diversity, we identified seven hypervariable regions that hold promise as potential molecular markers for fine‐scale species identification within Eria s.l. These findings not only significantly enrich the existing chloroplast genome data for this taxonomically challenging group but also provide a robust foundational framework for understanding its complex evolutionary trajectory.

Author Contributions

Meina Wang: project administration (equal), writing – review and editing (equal). Xinyi Wu: data curation (equal), formal analysis (equal), writing – original draft (equal), writing – review and editing (equal). Jian Li: project administration (equal). Tingzhang Li: data curation (equal), formal analysis (equal). Fengxia Tang: resources (equal). Xiaojuan Duan: resources (equal). Wenhui Rao: resources (equal).

Funding

This work was supported by the Science, Technology and Innovation Commission of Shenzhen Municipality (Grant No. KCXFZ20211020164200001) and (Grant No. JCYJ20210324123013037).

Ethics Statement

The plant materials used in the study were collected with permission. The collection of plant materials and use complies with relevant institutional, national, and international guidelines and legislation. This article does not contain any studies with human participants or animals and does not involve any endangered or protected species.

Consent

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Table S1: Detailed information for the chloroplast genome sequences used in this study.

ECE3-16-e73342-s001.xlsx (10.4KB, xlsx)

Table S2a: Comparison of the nucleotide variability among genes regions of 17 Eria s.l. species.

Table S2b: Comparison of the nucleotide variability among IGS regions of 17 Eria s.l. species.

ECE3-16-e73342-s004.xlsx (16.8KB, xlsx)

Table S3: Pairwise non‐synonymous to synonymous substitution rate (Ka/Ks) ratios for 42 shared plastid CDS among Eria s.l. species. The Ka/Ks ratios were calculated using KaKs_Calculator under default settings, with Pinalia amica designated as the reference sequence.

ECE3-16-e73342-s002.xlsx (14.6KB, xlsx)

Table S4: Detection of episodic positive selection in 75 chloroplast CDS using the branch‐site model.

ECE3-16-e73342-s003.xlsx (12.9KB, xlsx)

Table S5: Species and accession information for the 50 plastomes used in phylogenetic analyses, retrieved from NCBI GenBank.

ECE3-16-e73342-s005.xlsx (14.4KB, xlsx)

Acknowledgements

The authors have nothing to report.

Data Availability Statement

The raw sequencing datasets generated and analyzed during the current study have been deposited in the Genome Sequence Archive (GSA) at the National Genomics Data Center (NGDC), China, under the BioProject accession number PRJCA059605. All data generated or analyzed are included within the article and the Tables S1–, S5.

References

  1. Beier, S. , Thiel T., Münch T., Scholz U., and Mascher M.. 2017. “MISA‐Web: A Web Server for Microsatellite Prediction.” Bioinformatics 33, no. 16: 2583–2585. 10.1093/bioinformatics/btx198. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Brudno, M. , Do C. B., Cooper G. M., et al. 2003. “LAGAN and Multi‐LAGAN: Efficient Tools for Large‐Scale Multiple Alignment of Genomic DNA.” Genome Research 13, no. 4: 721–731. 10.1101/gr.926603. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Capella‐Gutiérrez, S. , Silla‐Martínez J. M., and Gabaldón T.. 2009. “trimAl: A Tool for Automated Alignment Trimming in Large‐Scale Phylogenetic Analyses.” Bioinformatics 25, no. 15: 1972–1973. 10.1093/bioinformatics/btp348. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Cavalier‐Smith, T. 2002. “Chloroplast Evolution: Secondary Symbiogenesis and Multiple Losses.” Current Biology 12, no. 2: R62–R64. [DOI] [PubMed] [Google Scholar]
  5. Chase, M. W. , Cameron K. M., Barrett R. L., and Freudenstein J. V.. 2003. “DNA Data and Orchidaceae Systematics: A New Phylogenetic Classification.” In Orchid Conservation, edited by Dixon K. W., Kell S. P., Barrett R. L., and Cribb P. J., 69–89. Natural History Publications. [Google Scholar]
  6. Chen, H. Y. , Chen L. Q., Yao X., et al. 2025. “Comprehensive Species Sampling Reveals Pervasive Pseudogenization and Recurrent Complete Loss of Plastid Ndh Genes in the Genus Cymbidium (Orchidaceae).” BMC Plant Biology 26: 181. 10.1186/s12870-025-07945-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Chen, H. Y. , Zhang Z. R., Yao X., et al. 2024. “Plastid Phylogenomics Provides New Insights Into the Systematics, Diversification, and Biogeography of Cymbidium (Orchidaceae).” Plant Diversity 46, no. 4: 448–461. 10.1016/j.pld.2024.03.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Chen, X. Q. , Luo Y. B., and Wood J. J.. 2009. “Eria.” In Flora of China 25, edited by Chen X., Luo Y., and Jeffrey J. W., 343–346. Science Press. [Google Scholar]
  9. Chen, Y. , Zhong H., Zhu Y., et al. 2020. “Plastome Structure and Adaptive Evolution of Calanthe s.l. Species.” PeerJ 8: e10051. 10.7717/peerj.10051. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Cock, P. J. , Antao T., Chang J. T., et al. 2009. “Biopython: Freely Available Python Tools for Computational Molecular Biology and Bioinformatics.” Bioinformatics 25, no. 11: 1422–1423. 10.1093/bioinformatics/btp163. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Conran, J. G. , Bannister J. M., and Lee D. E.. 2009. “Earliest Orchid Macrofossils: Early Miocene Dendrobium and Earina (Orchidaceae: Epidendroideae) From New Zealand.” American Journal of Botany 96, no. 2: 466–474. 10.3732/ajb.0800269. [DOI] [PubMed] [Google Scholar]
  12. Darriba, D. , Posada D., Kozlov A. M., Stamatakis A., Morel B., and Flouri T.. 2020. “ModelTest‐NG: A New and Scalable Tool for the Selection of DNA and Protein Evolutionary Models.” Molecular Biology and Evolution 37, no. 1: 291–294. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Dong, Y. , Cao Q., Yu K., et al. 2025. “Chloroplast Phylogenomics Reveals the Maternal Ancestry of Cultivated Chrysanthemums.” Genomics Communications 2, no. 1: e019. 10.48130/gcomm-0025-0019. [DOI] [Google Scholar]
  14. Doyle, J. J. , and Doyle J. L.. 1987. “A Rapid DNA Isolation Procedure for Small Quantities of Fresh Leaf Tissue.” Phytochemical Bulletin 19: 11–15. [Google Scholar]
  15. Ellegren, H. 2004. “Microsatellites: Simple Sequences With Complex Evolution.” Nature Reviews Genetics 5, no. 6: 435–445. 10.1038/nrg1348. [DOI] [PubMed] [Google Scholar]
  16. Fan, W. B. , Wu Y., Yang J., Shahzad K., and Li Z. H.. 2018. “Comparative Chloroplast Genomics of Dipsacales Species: Insights Into Sequence Variation, Adaptive Evolution, and Phylogenetic Relationships.” Frontiers in Plant Science 9: 689. 10.3389/fpls.2018.00689. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Favre, A. , Päckert M., Pauls S. U., et al. 2015. “The Role of the Uplift of the Qinghai‐Tibetan Plateau for the Evolution of Tibetan Biotas.” Biological Reviews 90, no. 1: 236–253. 10.1111/brv.12107. [DOI] [PubMed] [Google Scholar]
  18. Givnish, T. J. , Spalink D., Ames M., et al. 2015. “Orchid Phylogenomics and Multiple Drivers of Their Extraordinary Diversification.” Proceedings of the Royal Society B: Biological Sciences 282, no. 1814: 20151553. 10.1098/rspb.2015.1553. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Givnish, T. J. , Zuluaga A., Marques I., et al. 2016. “Phylogenomics and Historical Biogeography of the Monocot Order Liliales: Out of Australia and Through Antarctica.” Cladistics 32, no. 6: 581–605. 10.1111/cla.12153. [DOI] [PubMed] [Google Scholar]
  20. Guo, Y. Y. , Yang J. X., Bai M. Z., Zhang G. Q., and Liu Z. J.. 2021. “The Chloroplast Genome Evolution of Venus Slipper (Paphiopedilum): IR Expansion, SSC Contraction, and Highly Rearranged SSC Regions.” BMC Plant Biology 21, no. 1: 248. 10.1186/s12870-021-03053-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Hollingsworth, P. M. , Graham S. W., and Little D. P.. 2011. “Choosing and Using a Plant DNA Barcode.” PLoS One 6, no. 5: e19254. 10.1371/journal.pone.0019254. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Huang, L. , Yu H., Wang Z., and Xu W.. 2024. “CPStools: A Package for Analyzing Chloroplast Genome Sequences.” iMetaOmics 1, no. 2: e25. 10.1002/imo2.25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Jiang, H. , Tian J., Yang J., et al. 2022. “Comparative and Phylogenetic Analyses of Six Kenya Polystachya (Orchidaceae) Species Based on the Complete Chloroplast Genome Sequences.” BMC Plant Biology 22, no. 1: 177. 10.1186/s12870-022-03529-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Jin, J. J. , Yu W. B., Yang J. B., et al. 2020. “GetOrganelle: A Fast and Versatile Toolkit for Accurate de Novo Assembly of Organelle Genomes.” Genome Biology 21, no. 1: 241. 10.1186/s13059-020-02154-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Kalyaanamoorthy, S. , Minh B. Q., Wong T. K., Von Haeseler A., and Jermiin L. S.. 2017. “ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates.” Nature Methods 14, no. 6: 587–589. 10.1038/nmeth.4285. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Katoh, K. , and Standley D. M.. 2013. “MAffT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability.” Molecular Biology and Evolution 30, no. 4: 772–780. 10.1093/molbev/mst010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Kikuchi, S. , Bédard J., Hirano M., et al. 2013. “Uncovering the Protein Translocon at the Chloroplast Inner Envelope Membrane.” Science 339, no. 6119: 571–574. 10.1126/science.1229262. [DOI] [PubMed] [Google Scholar]
  28. Kim, H. T. , Kim J. S., Moore M. J., et al. 2015. “Seven New Complete Plastome Sequences Reveal Rampant Independent Loss of the Ndh Gene Family Across Orchids and Associated Instability of the Inverted Repeat/Small Single‐Copy Region Boundaries.” PLoS One 10: e0142215. 10.1371/journal.pone.0142215. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Kurtz, S. , Choudhuri J. V., Ohlebusch E., Schleiermacher C., Stoye J., and Giegerich R.. 2001. “REPuter: The Manifold Applications of Repeat Analysis on a Genomic Scale.” Nucleic Acids Research 29, no. 22: 4633–4642. 10.1093/nar/29.22.4633. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Li, H. , Guo Q., Xu L., Gao H., Liu L., and Zhou X.. 2023. “CPJSdraw: Analysis and Visualization of Junction Sites of Chloroplast Genomes.” PeerJ 11: e15326. 10.7717/peerj.15326. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Li, H. , Xiao W., Tong T., et al. 2021. “The Specific DNA Barcodes Based on Chloroplast Genes for Species Identification of Orchidaceae Plants.” Scientific Reports 11, no. 1: 1424. 10.1038/s41598-021-81087-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Li, L. , Wang W., Zhang G., et al. 2023. “Comparative Analyses and Phylogenetic Relationships of Thirteen Pholidota Species (Orchidaceae) Inferred From Complete Chloroplast Genomes.” BMC Plant Biology 23, no. 1: 269. 10.1186/s12870-023-04233-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Lin, C. S. , Chen J. J. W., Huang Y. T., et al. 2015. “The Location and Translocation of Ndh Genes of Chloroplast Origin in the Orchidaceae Family.” Scientific Reports 5, no. 1: 9040. 10.1038/srep09040. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Liu, B. , Huang J., Wang Z., Li D., Yuan Z., and Yao Y.. 2025. “The Complete Chloroplast Genome of Encyclia tampensis (Orchidaceae): Structural Variation and Heterogeneous Evolutionary Dynamics in Epidendreae.” Genes 16, no. 12: 1418. 10.3390/genes16121418. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Liu, D. K. , Zhou C. Y., Tu X. D., et al. 2023. “Comparative and Phylogenetic Analysis of Chiloschista (Orchidaceae) Species and DNA Barcoding Investigation Based on Plastid Genomes.” BMC Genomics 24, no. 1: 749. 10.1186/s12864-023-09847-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Lowe, T. M. , and Chan P. P.. 2016. “tRNAscan‐SE on‐Line: Integrating Search and Context for Analysis of Transfer RNA Genes.” Nucleic Acids Research 44, no. W1: W54–W57. 10.1093/nar/gkw413. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Ng, Y. P. 2002. “Phylogenetic Relationships in Tribe Podochileae (Orchidaceae: Epidendroideae) Based on Combined Evidence From Molecular and Morphological Data.” Ph.D. thesis, University of London, UK.
  38. Ng, Y. P. , Schuiteman A., Pedersen H. Æ., et al. 2018. “Phylogenetics and Systematics of Eria and Related Genera (Orchidaceae: Podochileae).” Botanical Journal of the Linnean Society 186, no. 2: 179–201. 10.1093/botlinnean/box088. [DOI] [Google Scholar]
  39. Nguyen, L. T. , Schmidt H. A., von Haeseler A., and Minh B. Q.. 2015. “IQ‐TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum‐Likelihood Phylogenies.” Molecular Biology and Evolution 32, no. 1: 268–274. 10.1093/molbev/msu300. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Niu, Z. , Pan J., Zhu S., et al. 2017. “Comparative Analysis of the Complete Plastomes of Apostasia wallichii and Neuwiedia singapureana (Apostasioideae) Reveals Different Evolutionary Dynamics of IR/SSC Boundary Among Photosynthetic Orchids.” Frontiers in Plant Science 8: 1713. 10.3389/fpls.2017.01713. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Qu, X. J. , Moore M. J., Li D. Z., and Yi T. S.. 2019. “PGA: A Software Package for Rapid, Accurate, and Flexible Batch Annotation of Plastomes.” Plant Methods 15, no. 1: 50. 10.1186/s13007-019-0435-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Ramírez, S. R. , Gravendeel B., Singer R. B., Marshall C. R., and Pierce N. E.. 2007. “Dating the Origin of the Orchidaceae From a Fossil Orchid With Its Pollinator.” Nature 448, no. 7157: 1042–1045. 10.1038/nature06039. [DOI] [PubMed] [Google Scholar]
  43. Raubeson, L. A. , Peery R., Chumley T. W., et al. 2007. “Comparative Chloroplast Genomics: Analyses Including New Sequences From the Angiosperms Nuphar advena and Ranunculus macranthus .” BMC Genomics 8: 174. 10.1186/1471-2164-8-174. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Ronquist, F. , Teslenko M., Van Der Mark P., et al. 2012. “MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space.” Systematic Biology 61, no. 3: 539–542. 10.1093/sysbio/sys029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Sanderson, M. J. , Copetti D., Búrquez A., et al. 2015. “Exceptional Reduction of the Plastid Genome of Saguaro Cactus (Carnegiea gigantea, Cactaceae): Loss of the Ndh Gene Suite and Inverted Repeat.” American Journal of Botany 102, no. 7: 1115–1127. 10.3732/ajb.1500184. [DOI] [PubMed] [Google Scholar]
  46. Seidenfaden, G. 1982. “Orchid Genera in Thailand. X. Trichotosia Bl. and Eria Lindl.” Opera Botanica 62: 67–72. [Google Scholar]
  47. Shikanai, T. 2016. “Chloroplast NDH: A Different Enzyme With a Structure Similar to That of Respiratory NADH Dehydrogenase.” Biochimica et Biophysica Acta (BBA)‐Bioenergetics 1857, no. 7: 1015–1022. 10.1016/j.bbabio.2015.10.013. [DOI] [PubMed] [Google Scholar]
  48. Simpson, L. , Clements M. A., Orel H. K., Crayn D. M., and Nargar K.. 2024. “Plastid Phylogenomics Clarifies Broad‐Level Relationships in Bulbophyllum (Orchidaceae) and Provides Insights Into Range Evolution of Australasian Section Adelopetalum.” Frontiers in Plant Science 14: 1219354. 10.3389/fpls.2023.1219354. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Tao, L. , Duan H., Tao K., Luo Q. L., and Li L.. 2023. “Complete Chloroplast Genome Structural Characterization of Two Phalaenopsis (Orchidaceae) Species and Comparative Analysis With Their Alliance.” BMC Genomics 24: 359. 10.1186/s12864-023-09448-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Wang, J. , Kan S., Liao X., et al. 2024. “Plant Organellar Genomes: Much Done, Much More to Do.” Trends in Plant Science 29, no. 7: 754–769. 10.1016/j.tplants.2023.12.014. [DOI] [PubMed] [Google Scholar]
  51. Weng, M. L. , Blazier J. C., Govindu M., and Jansen R. K.. 2014. “Reconstruction of the Ancestral Plastid Genome in Geraniaceae Reveals a Correlation Between Genome Rearrangements, Repeats, and Nucleotide Substitution Rates.” Molecular Biology and Evolution 31, no. 3: 645–659. 10.1093/molbev/mst257. [DOI] [PubMed] [Google Scholar]
  52. Whitfield, J. B. , and Lockhart P. J.. 2007. “Deciphering Ancient Rapid Radiations.” Trends in Ecology & Evolution 22, no. 5: 258–265. 10.1016/j.tree.2007.01.012. [DOI] [PubMed] [Google Scholar]
  53. Wicke, S. , Schneeweiss G. M., dePamphilis C. W., Müller K. F., and Quandt D.. 2011. “The Evolution of the Plastid Chromosome in Land Plants: Gene Content, Gene Order, Gene Function.” Plant Molecular Biology 76, no. 3–5: 273–297. 10.1007/s11103-011-9762-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Wu, Y. , Zeng M. Y., Wang H. X., et al. 2024. “The Complete Chloroplast Genomes of Bulbophyllum (Orchidaceae) Species: Insight Into Genome Structure Divergence and Phylogenetic Analysis.” International Journal of Molecular Sciences 25, no. 5: 2665. 10.3390/ijms25052665. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Xiang, X. G. , Mi X. C., Zhou H. L., et al. 2016. “Biogeographical Diversification of Mainland Asian Dendrobium (Orchidaceae) and Its Implications for the Historical Dynamics of Evergreen Broad‐Leaved Forests.” Journal of Biogeography 43, no. 7: 1310–1323. 10.1111/jbi.12726. [DOI] [Google Scholar]
  56. Xue, Q. , Yang J., Yu W., et al. 2023. “The Climate Changes Promoted the Chloroplast Genomic Evolution of Dendrobium Orchids Among Multiple Photosynthetic Pathways.” BMC Plant Biology 23, no. 1: 189. 10.1186/s12870-023-04186-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Yang, Z. H. 2007. “PAML 4: Phylogenetic Analysis by Maximum Likelihood.” Molecular Biology and Evolution 24, no. 8: 1586–1591. [DOI] [PubMed] [Google Scholar]
  58. Zhang, D. , Gao F., Jakovli¢ I., et al. 2020. “PhyloSuite: An Integrated and Scalable Desktop Platform for Streamlined Molecular Sequence Data Management and Evolutionary Phylogenetics Studies.” Molecular Ecology Resources 20, no. 1: 348–355. 10.1111/1755-0998.13096. [DOI] [PubMed] [Google Scholar]
  59. Zhang, J. , Nielsen R., and Yang Z.. 2005. “Evaluation of an Improved Branch‐Site Likelihood Method for Detecting Positive Selection at the Molecular Level.” Molecular Biology and Evolution 22, no. 12: 2472–2479. 10.1093/molbev/msi237. [DOI] [PubMed] [Google Scholar]
  60. Zhang, Z. 2022. “KaKs_Calculator 3.0: Calculating Selective Pressure on Coding and Non‐Coding Sequences.” Genomics, Proteomics & Bioinformatics 20, no. 3: 536–540. 10.1016/j.gpb.2021.12.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Zhao, Z. , Zeng M. Y., Wu Y. W., et al. 2023. “Characterization and Comparative Analysis of the Complete Plastomes of Five Epidendrum (Epidendreae, Orchidaceae) Species.” International Journal of Molecular Sciences 24, no. 19: 14437. 10.3390/ijms241914437. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Zwickl, D. J. , and Hillis D. M.. 2002. “Increased Taxon Sampling Greatly Reduces Phylogenetic Error.” Systematic Biology 51, no. 4: 588–598. 10.1080/10635150290102339. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1: Detailed information for the chloroplast genome sequences used in this study.

ECE3-16-e73342-s001.xlsx (10.4KB, xlsx)

Table S2a: Comparison of the nucleotide variability among genes regions of 17 Eria s.l. species.

Table S2b: Comparison of the nucleotide variability among IGS regions of 17 Eria s.l. species.

ECE3-16-e73342-s004.xlsx (16.8KB, xlsx)

Table S3: Pairwise non‐synonymous to synonymous substitution rate (Ka/Ks) ratios for 42 shared plastid CDS among Eria s.l. species. The Ka/Ks ratios were calculated using KaKs_Calculator under default settings, with Pinalia amica designated as the reference sequence.

ECE3-16-e73342-s002.xlsx (14.6KB, xlsx)

Table S4: Detection of episodic positive selection in 75 chloroplast CDS using the branch‐site model.

ECE3-16-e73342-s003.xlsx (12.9KB, xlsx)

Table S5: Species and accession information for the 50 plastomes used in phylogenetic analyses, retrieved from NCBI GenBank.

ECE3-16-e73342-s005.xlsx (14.4KB, xlsx)

Data Availability Statement

The raw sequencing datasets generated and analyzed during the current study have been deposited in the Genome Sequence Archive (GSA) at the National Genomics Data Center (NGDC), China, under the BioProject accession number PRJCA059605. All data generated or analyzed are included within the article and the Tables S1–, S5.

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