Skip to main content
Download PDF

Plastome structure, phylogenomics, and divergence times of tribe Cinnamomeae (Lauraceae)

BMC Genomics volume 23, Article number: 642 (2022) Cite this article

Abstract

Background

Tribe Cinnamomeae is a species-rich and ecologically important group in tropical and subtropical forests. Previous studies explored its phylogenetic relationships and historical biogeography using limited loci, which might result in biased molecular dating due to insufficient parsimony-informative sites. Thus, 15 plastomes were newly sequenced and combined with published plastomes to study plastome structural variations, gene evolution, phylogenetic relationships, and divergence times of this tribe.

Results

Among the 15 newly generated plastomes, 14 ranged from 152,551 bp to 152,847 bp, and the remaining one (Cinnamomum chartophyllum XTBGLQM0164) was 158,657 bp. The inverted repeat (IR) regions of XTBGLQM0164 contained complete ycf2, trnICAU, rpl32, and rpl2. Four hypervariable plastid loci (ycf1, ycf2, ndhF-rpl32-trnLUAG, and petA-psbJ) were identified as candidate DNA barcodes. Divergence times based on a few loci were primarily determined by prior age constraints rather than by DNA data. In contrast, molecular dating using complete plastid protein-coding genes (PCGs) was determined by DNA data rather than by prior age constraints. Dating analyses using PCGs showed that Cinnamomum sect. Camphora diverged from C. sect. Cinnamomum in the late Oligocene (27.47 Ma).

Conclusions

This study reports the first case of drastic IR expansion in tribe Cinnamomeae, and indicates that plastomes have sufficient parsimony-informative sites for molecular dating. Besides, the dating analyses provide preliminary insights into the divergence time within tribe Cinnamomeae and can facilitate future studies on its historical biogeography.

Peer Review reports

Background

Tribe Cinnamomeae (Lauraceae), named by Baillon in 1870, includes Cinnamomum, Phoebe, Machilus, Alseodaphne, Persea, Nothaphoebe, Apollonias, Hufelandia, Nesodaphne, Haasia, Beilschmiedia, Aiouea, and Potameia [1]. Kostermans [2] reclassified Lauraceae and placed Ocotea, Cinnamomum, Actinodaphne, Sassafras, Umbellularia, Dicypellium, Aiouea, Aniba, Endlicheria, Licaria, Urbanodendron, Systemonodaphne, and Phyllostemonodaphne in tribe Cinnamomeae based on inflorescence traits and cupule structures. However, tribe Cinnamomeae was dismantled by van der Werff and Richter [3], and genera of this tribe were placed in tribe Perseeae and tribe Laureae according to inflorescence traits and wood and bark anatomical structures. Many other studies also used different character combinations and even chemical constituents to revise this tribe and its related groups [4,5,6] and drew distinct conclusions attributed to convergent or parallel evolution of morphologies in Lauraceae and the fact that different biologists assigned different weights to morphologies in taxonomy [7, 8]. The difficulties in morphology-based taxonomy and the development of molecular phylogenetics have promoted the transition from traditional to phylogeny-based classification of Lauraceae [9].

In the past decades, evolutionary biologists have made much progress in the phylogenetics of tribe Cinnamomeae, but the relationships within the tribe have not been fully resolved. The phylogenetic tree based on matK indicated the monophyly of the Cryptocarya group, the Chlorocardium-Mezilaurus clade, and the Persea group [10]. However, the relationships of tribes Cinnamomeae and Laureae remained unresolved due to insufficient informative sites. The phylogenetic tree based on ITS showed that tribes Cinnamomeae and Laureae were monophyletic, and Sassafras and Umbellularia should be excluded from tribe Laureae and placed in tribe Cinnamomeae [11]. However, phylogenetic relationships within tribes were unclear. Huang et al. [12] comprehensively sampled the Cinnamomum group, reconstructed the tree of tribe Cinnamomeae using ITS + LEAFY + RPB2, and found that Aiouea was sister to Cinnamomum sect. Cinnamomum + Kuloa. Unfortunately, Sassafras and the Ocotea complex in the New World were not included. Penagos Zuluaga et al. [13] used restriction site-associated DNA sequencing (RAD-seq) data and constructed a highly resolved maximum likelihood (ML) tree of Aiouea and the Ocotea complex, but the other clades of tribe Cinnamomeae were not sampled. Plastid phylogenomics showed that Nectandra + Ocotea were sisters to all the other clades of tribe Cinnamomeae [14, 15], which was in conflict with the nuclear-loci-based tree of Huang et al. [12]. Phylogenetic conflicts between plastid and nuclear data are common in plants and typically accepted as a result of uniparental (plastid) inheritance versus biparental (nuclear) inheritance [16, 17].

Tribe Cinnamomeae consists of shrubs or trees and is the most species-rich tribe of Lauraceae with more than 1000 species [6]. Most species are distributed in the tropical rainforests and subtropical evergreen broad-leaved forests of Asia and the Americas, with a small number in Oceania and Africa [6]. Ecological prominence and wide and disjunctive distributions make this tribe an ideal target for studying historical biogeography. Divergence time estimation is the foundation for biogeographic studies. However, several studies used few loci and neglected the potential impact of limited informative sites on divergence time estimations (e.g., [12, 18, 19]). Brandley et al. [20] suggested that divergence times were primarily determined by prior age constraints rather than DNA data when informative sites were insufficient. Divergence times of the Cinnamomum group were estimated using only three nuclear loci that contained limited informative sites [12], and therefore, they need reinvestigation.

In general, the complete plastid genomes (plastomes) contain more informative sites than several nuclear or plastid loci; therefore, plastome phylogenomics can better resolve the phylogenetic relationships of plants. With the rapid development of next-generation sequencing, plastomes became cost-effective and have been widely used to explore plant evolution [21]. To date, 48 plastomes representing 29 species of tribe Cinnamomeae have been reported in GenBank and Lauraceae Chloroplast Genome Database (LCGDB; https://lcgdb.wordpress.com/) (accessed on 20 March 2022), which accounts for only ca. 2.3% of the total species diversity. Hence, we report 15 newly sequenced plastomes of tribe Cinnamomeae and combine them with published plastomes (Table S1), aiming to: (1) explore plastome structural variations, (2) identify hypervariable regions as promising DNA barcodes for future study, (3) assess the influence of limited parsimony-informative (Pi) sites on divergence time estimation, and (4) reestimate the divergence time using plastomes.

Materials and methods

Sampling, DNA extraction, and sequencing

In this study, 15 samples were used for DNA sequencing. These samples represented 14 species from two sections (sect. Camphora and sect. Cinnamomum) in the genus Cinnamomum. Materials were collected from living plants in the field and botanical gardens. Plants were identified and deposited as voucher specimens in the herbarium of the South China Botanical Garden, Chinese Academy of Sciences (IBSC) (Table S2). The cetyltrimethylammonium bromide (CTAB) method [22] was used to extract genomic DNA of each sample from silica gel-dried leaf tissues. The DNA concentration was measured with the Qubit 3.0 Fluorometer dsDNA HS Assay Kit (Invitrogen, Carlsbad, CA, USA), and DNA fragment size distribution was assessed using 1% agarose gel electrophoresis. The library with an insert size of 270 bp was constructed at the Beijing Genomics Institute (BGI; Shenzhen, China). Paired-end reads of 150 bp were sequenced by genome skimming with the HiSeq X Ten system (Illumina Inc., San Diego, CA, USA).

Plastome assembly and annotation

Low-quality reads and adaptors were removed using Trimmomatic v0.36 [23], and FastQC [24] was used to assess data quality. About 2 Gb clean reads were obtained for each sample. The plastomes were assembled using NOVOPlasty v2.7.2 [25] and GetOrganelle v1.7.5.3 [26]. To ensure that the plastomes were correctly assembled, the clean reads were mapped to plastomes using Burrows-Wheeler Aligner v0.7.17-r1188 [27] and SAMtools v1.9 [28], and the results were manually checked in the Geneious v9.1.3 [29]. The plastomes were annotated using the GeSeq–Annotation of Organellar Genomes program (https://chlorobox.mpimp-golm.mpg.de/geseq.html) [30]. Thereafter, the start and stop codon positions of protein-coding genes (PCGs) were checked and adjusted in Geneious. Raw reads and newly generated plastomes were submitted to GenBank (accession numbers shown in Table S2). Plastome maps were drawn using the online program OrganellarGenomeDRAW tool (OGDRAW; https://chlorobox.mpimp-golm.mpg.de/OGDraw.html) [31].

Comparative genomic analyses and hypervariable regions

For the 15 newly sequenced plastomes, rearrangement and inversion were detected with Mauve v1.1.1 [32] in Geneious. The expansion and contraction of boundaries between inverted repeat (IRa and IRb) regions and single copy (LSC and SSC) regions were identified using IRscope v0.1 [33]. To validate the IR boundary variation, primers were designed in Geneious, and polymerase chain reaction (PCR) and gel electrophoresis experiments were performed.

To detect variable regions across tribe Cinnamomeae, a 39-plastome dataset was created comprising 30 species of Cinnamomum, one species of Nectandra, seven species of Ocotea, and one species of Sassafras (Table S1). Genome variability was assessed using mVISTA [34] under Shuffle-LAGAN mode, with Cinnamomum osmophloeum (GenBank accession number: MT384386) randomly selected as a reference. The 39 plastomes were aligned using MAFFT [35] with default settings and nucleotide diversity (Pi) was calculated in DnaSP v5 [36], with window length and step size set as 1000 and 250 bp, respectively. Variations in Pi across sites were plotted using ggplot2 [37] in R v4.0.4 [38].

Repeat sequence identification

For the 39-plastome dataset, three types of repetitive sequences, including dispersed repeats, simple sequence repeats (SSRs), and tandem repeats, were examined. For dispersed repeats (including forward, reverse, complement, and palindromic repeats), the REPuter online program (https://bibiserv.cebitec.uni-bielefeld.de/reputer) was used with default settings: maximum computed repeats = 50 and minimal repeat size = 8 [39]. To determine SSRs, the MIcroSAtellite identification tool (MISA v2.1) [40] was used with default settings: the minimum number of repetitions for mono-, di-, tri-, tetra-, penta-, and hexanucleotides was 10, 6, 5, 5, 5, and 5, respectively. To detect tandem repeats, Tandem Repeats Finder v4.09 [41] was used with the following criteria: matching weight = 2, mismatching penalty = 7, indel penalty = 7, minimum alignment score = 80, maximum period size = 500, match probability = 80, and indel probability = 10.

Phylogenetic analyses

Three concatenated sequence matrices were prepared for phylogenetic analyses: (1) complete plastomes with one IR removed to reduce redundancy (CP-c); (2) protein-coding genes (PCG-c); and (3) non-protein-coding genes (NPCG-c), including intergenic regions, tRNAs, rRNAs, and introns. Because gaps can influence tree topology [42, 43], sites with more than 50% gap percentage were trimmed using ClipKIT [44]. The three matrices consisted of 11 plastomes from tribe Laureae as outgroups, and 43 plastomes from tribe Cinnamomeae, representing 30 species of Cinnamomum, one species of Nectandra, seven species of Ocotea, and one species of Sassafras (Table S1). All loci were extracted using the Python script PersonalUtilities (https://github.com/Kinggerm/PersonalUtilities) and were aligned using MAFFT with default settings. The alignments were manually checked in Geneious and were concatenated using AMAS v1.0 [45]. Alignment lengths, number of variable sites, number of parsimony-informative sites, and GC content of CP-c, PCG-c, and NPCG-c were summarized using AMAS [45]. The best-scoring ML tree was searched in RAxML v8.2.11 [46] with the GTRGAMMA model and 1000 bootstrap replicates, and by specifying the rapid bootstrapping strategy (‘-f a’ option).

Selective pressure analyses

To detect genes under positive selection, selective pressure analyses were performed on extracted PCGs using CODEML in PAML 4.9j [47] following the protocol of Xiao et al. [48]. The PCG-c ML tree was used as input, with bootstrap values and branch length removed using MEGA X [49]. Site-specific model comparisons (M3 vs. M0, M2a vs. M1a, M8 vs. M7) were invoked to identify positively selected sites [50], and the likelihood ratio test (LRT) was performed in R. Nucleotide sites with Bayes empirical bayes (BEB) value > 0.95 and p value < 0.05 were considered positively selected.

Effect of uninformative loci on molecular dating

To assess the effect of uninformative loci on divergence time estimation, two molecular dating analyses were conducted in BEAST v2.6.3 [51]. First, three nuclear loci (ITS, LEAFY, RPB2; Huang et al. [12]) were downloaded from GenBank (Table S3). These loci were aligned using MAFFT, and the alignments were concatenated into a matrix using AMAS. The best-fitted substitution model (GTR + I + G4) was determined in ModelTest-NG [52] according to the Akaike information criterion (AIC). The GAMMA distribution model (G4) accounts for rate heterogeneity among sites and works sufficiently well for most datasets [51]. Two secondary calibration points (stem and crown ages of the Cinnamomum group) and one fossil calibration point (stem age of Alseodaphne) with normal distributions were used for prior age constraints following Huang et al. [12]. Subsequently, molecular dating analysis (hereafter: full analysis) was performed for 100,000,000 generations, sampling every 10,000 generations. Second, “Sample From Prior” was selected and other parameters were kept unchanged in BEAUTi, generating a new configuration file for another molecular dating analysis without DNA data (hereafter: prior-only analysis).

After completing the two dating analyses, the distributions and mean of posterior age of the splitting time of Aiouea and C. sect. Cinnamomum + Kuloa were compared. If the distributions and mean of divergence time estimated from DNA data (full analysis) were similar to the prior-only analysis, then the estimated times were concluded to only (or mainly) be influenced by prior age constraints rather than by DNA data.

Molecular dating using PCGs

To estimate divergence times within tribe Cinnamomeae, newly sequenced plastomes were combined with published plastomes from GenBank and LCGDB, generating a 100-plastome dataset. This dataset represented 39 species of tribe Cinnamomeae, 12 species of tribe Laureae, 17 species of tribe Perseeae, three species of tribe Caryodaphnopsideae, three species of tribe Neocinnamomeae, 17 species of tribe Cryptocaryeae of Lauraceae, two species of Hernandiaceae, and three species of Calycanthaceae (Table S1).

The best-fitted model (GTR + I + G4) was selected for the PCGs dataset in ModelTest-NG according to AIC. The uncorrelated relaxed log-normal molecular clock allows sequence evolutionary rate to vary among different parts of a phylogeny [16], and also accounts for uncertainties in phylogenetic relationships and fossil calibrations [17], thus was used in this study. Yule model was specified for the speciation process. GAMMA distribution was set for the prior of birthrate, and the exponential distribution was assigned for the prior of ucldMean and ucldStdev. The BEAST analysis was run for 400,000,000 Markov chain Monte Carlo (MCMC) generations with the sampling frequency of 40,000.

Because fossils attributed to Cinnamomum are unreliable [12], four macrofossils of the outgroups were used for node calibrations. First, Virginianthus calycanthoides Friis et al. is a well-preserved fossil flower from the early to middle Albian of Cretaceous [53], and the fossil can be used to calibrate the crown age of Laurales [54]. Here, a log-normal distribution was set for the crown node of Laurales with offset, mean, and standard deviation as 107.1, 0.5, and 0.6, respectively. Second, Potomacanthus lobatus von Balthazar et al. is a charcoalified fossil flower described from the early to middle Albian of Cretaceous, and this fossil was used to calibrate the stem node of Lauraceae with a log-normal distribution and offset of 106.8, mean of 0.5, and standard deviation of 0.6, following Kondraskov et al. [55]. Third, Neusenia tetrasporangiata Eklund is a flower bud fossil described from the Santonian/Campanian (ca. 83 ma) of Cretaceous, and it shows a close relationship to extant Neocinnamomum based on its psilate pollen [56, 57]. This fossil was used to calibrate the crown node of the Neocinnamomum-Caryodaphnopsis-core Lauraceae clade by specifying a log normal distribution with an offset of 83, a mean of 1, and a standard deviation of 1.1. Fourth, Machilus maomingensis Tang et al. is a leaf fossil described from the late or middle Eocene, and it exhibits a close similarity to extant Machilus based on leaf architecture and cuticle [58]. This fossil was used to calibrate the stem node of Machilus, assigning a log-normal distribution with an offset of 33.7, a mean of 1, and a standard deviation of 0.85. To ensure that the estimated times were determined by DNA data rather than by prior age constraints, an additional BEAST analysis was performed by specifying “Sample From Prior” with 100,000,000 MCMC generations and sampling frequency of 10,000, while the other parameters were unchanged.

Tracer v1.7.1 [59] was to confirm the convergence of parameters (ESS ≥ 200). After discarding the first 20% of posterior trees as burn-in, TreeAnnotator in BEAST v2.6.3 was used to generate the maximum clade credibility tree [51].

Results

Plastome features

All 15 newly sequenced plastomes shared a typical quadripartite structure—LSC, SSC, IRa, and IRb. The genome size of Cinnamomum chartophyllum XTBGLQM0164 was 158,657 bp, substantially larger than the other 14 Cinnamomum plastomes ranging from 152,551 bp (C. cassia D053) to 152,847 bp (C. austrosinense) (Table 1). The size of the IR region of C. chartophyllum was 25,974 bp, approximately 5000 bp larger than the other 14 samples (20,060–20,132 bp). The size of the SC region of C. chartophyllum XTBGLQM0164 was smaller than the other 14 samples. All 15 plastomes had 79 unique PCGs, 30 unique tRNAs, and four unique rRNAs. However, the C. chartophyllum XTBGLQM0164 plastome had 85 PCGs, 37 tRNAs, and eight rRNAs, and the other 14 plastomes had only 82 PCGs, 36 tRNAs, and eight rRNAs (Tables 1 and S4). The GC content of the 15 plastomes ranged from 39.1 to 39.2%.

Table 1 Summary of the 15 newly sequenced plastomes of tribe Cinnamomeae
Full size table

IR expansion and contraction, and genome rearrangement

Cinnamomum chartophyllum harbored double complete trnICAU, rpl32, rpl2, and ycf2 in the IR regions, showing significant IR expansion (Figs. 1 and S1). To ensure that the expansion was not caused by sequencing or assembly errors, two pairs of primers were designed in Geneious, targeting rpl2 exon2, trnHGUG, and their intergenic region (Table S5). C. cassia D053 and C. longepaniculatum wh020 were selected as a comparison for PCR and gel electrophoresis experiments. The experimental result showed that the targeting region existed in C. chartophyllum (Fig. S2), but not in the other species, suggesting significant IR expansion in the C. chartophyllum plastome. Besides, according to the Mauve analysis, no rearrangement and inversion were detected in the 15 plastomes (Fig. S3).

Fig. 1
figure 1

Gene maps of newly sequenced plastomes and Cinnamomum chartophyllum MW421301. Genes related to inverted repeat (IR) expansion are colored in red (ycf2, trnLCAU, rpl23, and rpl2 of Cinnamomum chartophyllum XTBGLQM0164)

Full size image

Hypervariable regions

Genome variability analysis using mVISTA showed that sequence divergence within tribe Cinnamomeae was mostly located in the intergenic regions and two PCGs, ycf1 and ycf2 (Fig. S4). According to the nucleotide diversity analysis, four loci with higher Pi values were ycf1, ycf2, ndhF-rpl32-trnLUAG, and petA-psbJ (Fig. 2). Besides, three universal barcoding loci (trnH-psbA, matK, and rbcL) are shown in Fig. 2. The Pi values of trnH-psbA, matK, and rbcL were substantially lower than the four hypervariable loci.

Fig. 2
figure 2

The variation of nucleotide diversity across 39 plastomes of tribe Cinnamomeae. Four hypervariable loci (ycf1, ndhF-rpl32-trnLUAG, ycf2, and petA-psbJ) and three standard DNA barcodes (trnH-psbA, matK, and rbcL) are indicated

Full size image

Characterization of repetitive sequences

A total of 1950 dispersed repeats were detected for the 39 species, of which forward, palindromic, and reverse repeats constituted the majority (95.18%), and complement repeats constituted the minority (4.82%) (Table S6). The number of forward repeats (716) was higher than palindromic (568) or reverse (572) repeats. The lengths of dispersed repeats were similar within Cinnamomum and Sassafras (18–87 bp), but were smaller than Nectandra and Ocotea (18–275 bp). A total of 2640 SSRs were identified across the 39 species, of which 2374 were A/T monomers, 57 were G/C monomers, and 209 were AT/TA/GA/TC dimers. No trimers, tetramers, hexamers, and pentamers were found. The number of tandem repeats was similar among the 39 species (4–9). However, the lengths of tandem repeats of Cinnamomum and Sassafras were 18–39 bp, smaller than Nectandra and Ocotea (19–99 bp).

Phylogenetic analyses

The alignment lengths, number of variable sites, number of parsimony-informative sites, and GC content of PCG-c, NPCG-c, and CP-c are shown in Table 2. Because the phylogenetic relationships within tribe Cinnamomeae were largely congruent based on the three matrices (Figs. 3, S5, and S6), only the PCG-c ML tree has been present in the main text. As shown in Fig. 3, tribe Cinnamomeae consisted of three major clades—I, II, and III. Nectandra and Ocotea (clade I) were sister to Sassafras and Cinnamomum (clade II). In clade II, nine of the 12 species from Cinnamomum sect. Camphora formed a monophyletic group and were sister to Sassafras. In clade III, the other three species (C. chartophyllum, C. camphora, and C. tenuipile) of sect. Camphora were nested within 18 species from sect. Cinnamomum.

Table 2 Summary of the three matrices used in maximum likelihood analyses
Full size table
Fig. 3
figure 3

Phylogenetic tree inferred from maximum likelihood analysis based on concatenated protein-coding genes (PCG-c). Outgroups are pruned; bootstrap values = 100% are indicated as asterisks (*) above branches; newly sequenced samples are red-colored

Full size image

Selective pressure analyses

According to the site-specific model comparisons and LRT tests, 19 genes contained 57 positively selected sites. Of these genes, ycf1 harbored 18 sites, with nine in rbcL, seven in ycf2, and 1–3 in each of the other 16 genes (accD, ndhA, ndhF, ndhJ, petD, psaA, psbC, psaB, psbB, rpl2, rpl16, rpoC2, rpoB, rps12, rps2, and ycf4; Table S7).

Effect of uninformative loci on molecular dating

According to BEAST analysis based on three nuclear loci (full analysis), clade H2 (Aiouea) separated from clade H3 (Kuloa + C. sect. Cinnamomum) at 49.98 Ma (95% highest posterior density (HPD) = 40.71–59.54 Ma) (Fig. 4a and b). BEAST analysis without DNA (prior-only analysis) showed that the divergence time of clades H2 and H3 was 45.35 Ma (95% HPD = 33.58–57.50 Ma) (Fig. 4b). The posterior distributions largely overlapped (Fig. 4b), and the means were similar (49.98 vs. 45.35), suggesting that the dating results of the full analysis were mainly determined by prior age constraints, rather than by the three nuclear loci data.

Fig. 4
figure 4

Divergence time estimation using ITS, LEAFY, and RPB2. a Molecular dating with DNA data (full analysis). The numbers near nodes are divergence times; the blue node bars indicate 95% highest posterior distributions; the three red circles at nodes indicate calibration points; species-rich clades are collapsed. b The posterior distributions of the divergence time of clades H1 and H2 in the full analysis and prior-only analysis (divergence time estimation without DNA data). Prior-only analysis and full analysis are colored in red and blue, respectively

Full size image

Divergence times within tribe Cinnamomeae based on PCGs

According to BEAST analysis based on PCGs (full analysis), tribe Cinnamomeae originated at 44.79 Ma (95% HPD = 34.02–54.64 Ma) and diverged at 34.31 Ma (95% HPD = 23.44–46.05 Ma) (Fig. 5a). Clade II separated from clade III at 27.47 Ma (95% HPD = 17.08–38.34 Ma) (Fig. 5b). BEAST analysis without PCGs (prior-only analysis) showed that the divergence time of clades II and III was 58.23 Ma (95% HPD = 39.81–75.16 Ma) (Fig. 5b). The posterior distributions did not overlap, and the means were substantially different (Fig. 5b), suggesting that the dating results of the full analysis were determined by PCGs, not by prior age constraints.

Fig. 5
figure 5

Divergence time estimation using plastid protein-coding genes (PCGs). a Molecular dating with DNA data (full analysis). The blue node bars indicate 95% highest posterior distributions; the four red pentacles indicate fossil calibration points. b The posterior distributions of the divergence time of clades II and III in the full analysis and prior-only analysis (divergence time estimation without DNA data). Prior-only analysis and full analysis are colored in blue and green, respectively

Full size image

Discussion

Plastome structure variation and evolution

Fourteen of the 15 newly sequenced plastomes of Cinnamomum were conservative in overall structure, genome size, GC content, and gene order and content (Fig. 1; Tables 1 and S4), which were congruent with published plastomes from tribe Cinnamomeae [14, 60, 61]. One exception was the plastome of Cinnamomum chartophyllum XTBGLQM0164, which had a larger genome size compared with another published plastome of this species (MW421301, 152,722 bp) and the other 14 newly sequenced plastomes (Table 1; Fig. 1). Its larger size was caused by IR expansion, resulting in double complete trnICAU, rpl32, rpl2, and ycf2 in the IR regions (Figs. 1 and S1), which is the first case in tribe Cinnamomeae. Infrageneric IR expansion was relatively common in angiosperms, for example, IR of Plantago (Plantaginaceae) ranged from 24,955 bp to 38,644 bp [62], Pelargonium (Geraniaceae) from 38,036 bp to 87,724 bp [63], Euphorbia (Euphorbiaceae) from 26,434 bp to 43,573 bp [64], and Caryodaphnopsis (Lauraceae) from 20,036 bp to 25,601 bp [61]. As for intraspecific IR expansion, a double-strand break followed by strand invasion and recombination can result in intraspecific length polymorphism and was proposed to explain large and small IR expansions [65,66,67], which may be responsible for the IR expansion of C. chartophyllum XTBGLQM0164.

Abundant repetitive sequences were detected across the 39 species of tribe Cinnamomeae (Table S6). For SSRs, poly-A/T constituted the majority and poly-G/C were rare in this study, which were also found in other plants, such as Euphorbia [64], Zygophyllum [68], and Swertia [69]. Long repeat sequences play critical roles in plastome variation and rearrangements [65, 70]. Although abundant long repeats (dispersed and tandem repeats) were detected, no rearrangements were observed in the Mauve analysis (Fig. S3). Interestingly, the maximum lengths of long repeat sequences were substantially higher in Nectandra and Ocotea than in Cinnamomum and Sassafras (Table S6), which may reflect the distinct evolutionary histories of the two lineages of tribe Cinnamomeae. The newly identified SSRs, tandem repeats, and dispersed repeats can facilitate population genetics and evolutionary studies of tribe Cinnamomeae in the future.

Plastids are bioenergetic organelles responsible for photosynthesis and numerous metabolic processes. Positive selection of plastid genes is common and has been used to explain the adaptive evolution of plants [69, 71,72,73]. In this study, the site models indicated that positive selection acted on sites of roughly one-fifth of all plastid PCGs (19 of 79; Table S7). Of these genes, ycf1, ycf2, and rbcL contained more positively selected sites than the other genes. ycf1 and ycf2 are the two largest open reading frames of higher plants and encode products essential to cell survival [74]. ycf2 was also reported to participate in encoding the 2-MD heteromeric AAA-ATPase complex, which associates with the TIC complex and functions as an import motor [75]. rbcL is a photosynthesis-related gene that encodes the large subunit of RubisCO and has been shown to undergo positive selection in all lineages of green plants [76]. For example, the positive selection in rbcL of Schiedea was suggested to promote the colonization of new habitats [77]. Therefore, the data generated in this study can facilitate future works that determine more specific details about how positive selection could have played a role in adaptations to new environments.

Candidate DNA barcodes

DNA barcode is a standard region of nucleotide sequence used for species identification [78]. Three plastid loci (rbcL, matK, and trnH-psbA) and a nuclear-ribosomal DNA region (ITS2) were selected as standard barcodes [79] and were widely used in community ecology, biodiversity conservation, and evolutionary biology [80,81,82]. However, these standard barcodes always displayed low phylogenetic resolutions in recently diversified taxa [10, 83]; therefore, developing new DNA barcodes is necessary. This study showed that ycf1, ycf2, petA-psbJ, and ndhF-rpl32-trnLUAG were more informative than the standard barcodes (rbcL, matK, and trnH-psbA), which were largely in line with Trofimov et al. [14]. ycf1 was indicated to be the most variable loci and showed better phylogenetic resolutions than standard DNA barcodes in land plants [84]. ycf2, petA-psbJ, and ndhF-rpl32-trnLUAG were not always hypervariable among different taxa [54, 64, 85], suggesting that the three loci were taxa-specific barcodes. Given the limited sampling in this study, more species with multiple samples of tribe Cinnamomeae should be included in future work to evaluate the discriminative power of ycf2, petA-psbJ, and ndhF-rpl32-trnLUAG.

Phylogenetic relationships and divergence time of tribe Cinnamomeae

According to the PCG-c ML tree (Fig. 3), Cinnamomum and two of its sections were not monophyletic, which was consistent with Huang et al. [12]. Cinnamomum camphora, C. chartophyllum, and C. tenuipile were positioned in C. sect. Camphora based on ITS + LEAFY + RPB2 [12], however, they were grouped with C. sect. Cinnamomum based on plastomes. The three species nested within different sections based on plastomes and nuclear loci, and originated long after the occurrence of the most recent common ancestor of Cinnamomum; therefore, their conflicting positions were unlikely to be caused by incomplete lineage sorting (ILS), which commonly occurred in a short period [86,87,88]. Thus, hybridization or introgression may be responsible for this case. Furthermore, the sister relationship of clades I and III was supported by ITS + LEAFY + RPB2 [12]. In contrast, clade I was sister to clades II and III in this study. The contrasting cytonuclear discordance may be caused by ancient hybridization, introgression, or ILS, which are common in plants [16, 89, 90].

Divergence time estimation is the basis of historical biogeography, and inaccurate divergence time estimation can bias the understanding of plant evolution. By the full analysis and prior-only analysis comparison, the divergence times of tribe Cinnamomeae based on three nuclear loci were largely affected by prior age constraints (Fig. 4b) and thus were not accurate. Many branch support values of Huang et al. [12] were low, suggesting that the three nuclear loci had insufficient parsimony-informative sites and could have biased the molecular dating analysis [20]. In contrast, the PCGs results were not affected by the prior age constraints (Fig. 5b). According to the results, tribe Cinnamomeae originated around 44.79 Ma, about 10 Ma younger than the estimation from Huang et al. [12], and the divergence time of the two sections of Cinnamomum was 27.47 Ma, about 24 Ma younger than the estimation from Huang et al. [12]. Therefore, the biogeographic inference of Huang et al. [12] needs to be reinvestigated. For example, Kuloa is distributed in Central Africa and sister to C. sect. Cinnamomum [12, 91]. Its divergence from C. sect. Cinnamomum should be later than the divergence of C. sect. Cinnamomum and C. sect. Camphora, 27.47 Ma (Fig. 5a), which was long after the breakup of boreotropical flora in the late Eocene [92, 93]. Therefore, the Africa–Asia disjunction of tribe Cinnamomeae was more likely caused by long-distance dispersal rather than by the breakup of boreotropical flora. Despite the new findings in this study, more species and a large number of nuclear loci are needed to further elucidate the phylogenetic relationships and infer a more reasonable historical biogeography of tribe Cinnamomeae.

Conclusions

In this study, 15 plastomes representing 14 species of tribe Cinnamomeae were newly sequenced. Comparative analyses showed that plastomes of tribe Cinnamomeae were highly similar in terms of the overall structure, long repeat sequences, and SSRs. Drastic expansion of the IR regions was detected in Cinnamomum chartophyllum XTBGLQM0164, which is the first case in tribe Cinnamomeae. ycf1, ycf2, ndhF-rpl32-trnLUAG, and petA-psbJ were hypervariable and can be used as candidate DNA barcodes for this tribe. Divergence time estimation using plastomes was not affected by prior age constraints. Cinnamomum sect. Camphora separated from C. sect. Cinnamomum at 27.47 Ma, long after the breakup of boreotropical flora, suggesting that long-distance dispersal may play an important role in shaping the disjunctive distribution of tribe Cinnamomeae. Overall, the obtained plastome resources can facilitate population genetics, phylogenetics, and biogeographic studies of tribe Cinnamomeae in the future.

Availability of data and materials

The newly sequenced 15 plastomes of tribe Cinnamomeae were submitted to the Science Data Bank (https://doi.org/10.57760/sciencedb.01896) and GenBank (accession numbers shown in Table S2). All raw reads were submitted to sequence read archive of NCBI under bioproject PRJNA843587 (SRA accession numbers shown in Table S2). The accession numbers of the other plastomes downloaded from GenBank and LCGDB were shown in Table S1.

Abbreviations

AIC:

Akaike information criterion

BEB:

Bayes empirical bayes

BGI:

Beijing Genomics Institute

CP:

Complete plastome

CTAB:

Cetyltrimethylammonium bromide

ESS:

Effective sample size

HPD:

Highest posterior density

ILS:

Incomplete lineage sorting

IR:

Inverted repeat

LCGDB:

Lauraceae Chloroplast Genome Database

LRT:

Likelihood ratio test

LSC:

Large single copy

MCMC:

Markov chain Monte Carlo

ML:

Maximum likelihood

NPCG:

Non-protein-coding gene

OGDRAW:

OrganellarGenomeDRAW

PCG:

Protein-coding gene

PCR:

Polymerase chain reaction

Pi:

Parsimony-informative

RAD-seq:

Restriction site-associated DNA sequencing

SSC:

Small single copy

SSR:

Simple sequence repeat

References

  1. Baillon H. Histoire des Plantes, vol. 2. Paris: Librairie Hachette; 1870.

    Google Scholar 

  2. Kostermans AJGH. Lauraceae. Reinwardtia. 1957;4:193–256.

    Google Scholar 

  3. van der Werff H, Richter HG. Toward an improved classification of Lauraceae. Ann Mo Bot Gard. 1996;83:409–18.

    Article  Google Scholar 

  4. Gottlieb OR. Chemosystematics of the lauraceae. Phytochemistry. 1972;11(5):1537–70.

    Article  CAS  Google Scholar 

  5. Hutchinson J. The genera of flowering plants (Dicotyledonae), vol. 1. Oxford: Clarendon Press; 1964.

    Google Scholar 

  6. Rohwer JG. Lauraceae. In: Kubitzki K, Rohwer JG, Bittrich V, editors. Flowering plants · Dicotyledons. The families and genera of vascular plants, vol. 2. Berlin Heidelberg: Springer-Verlag; 1993. p. 366–90.

    Chapter  Google Scholar 

  7. Li J, Conran JG, Christophel DC, Li Z-M, Li L, Li H-W. Phylogenetic relationships of the Litsea complex and core Laureae (Lauraceae) using ITS and ETS sequences and morphology. Ann Mo Bot Gard. 2008;95(4):580–600.

    Article  Google Scholar 

  8. van der Merwe M, Crayn DM, Ford AJ, Weston PH, Rossetto M. Evolution of Australian Cryptocarya (Lauraceae) based on nuclear and plastid phylogenetic trees: evidence of recent landscape-level disjunctions. Aust Syst Bot. 2016;29(2):157–66.

    Article  Google Scholar 

  9. Tian Y, Zhou J, Zhang Y, Wang S, Wang Y, Liu H, et al. Research Progress in plant molecular systematics of Lauraceae. Biology. 2021;10(5):391.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Rohwer JG. Toward a phylogenetic classification of the Lauraceae: evidence from matK sequences. Syst Bot. 2000;25(1):60–71.

    Article  Google Scholar 

  11. Chanderbali AS, van der Werff H, Renner SS. Phylogeny and historical biogeography of Lauraceae: evidence from the chloroplast and nuclear genomes. Ann Mo Bot Gard. 2001;88(1):104–34.

    Article  Google Scholar 

  12. Huang J-F, Li L, van der Werff H, Li H-W, Rohwer JG, Crayn DM, et al. Origins and evolution of cinnamon and camphor: a phylogenetic and historical biogeographical analysis of the Cinnamomum group (Lauraceae). Mol Phylogenet Evol. 2016;96:33–44.

    Article  CAS  PubMed  Google Scholar 

  13. Penagos Zuluaga JC, van der Werff H, Park B, Eaton DAR, Comita LS, Queenborough SA, et al. Resolved phylogenetic relationships in the Ocotea complex (Supraocotea) facilitate phylogenetic classification and studies of character evolution. Am J Bot. 2021;108(4):664–79.

    Article  PubMed  Google Scholar 

  14. Trofimov D, Cadar D, Schmidt-Chanasit J, Rodrigues de Moraes PL, Rohwer JG. A comparative analysis of complete chloroplast genomes of seven Ocotea species (Lauraceae) confirms low sequence divergence within the Ocotea complex. Sci Rep. 2022;12(1):1120.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Song Y, Yu WB, Tan YH, Jin JJ, Wang B, Yang JB, et al. Plastid phylogenomics improve phylogenetic resolution in the Lauraceae. J Syst Evol. 2020;58(4):423–39.

    Article  Google Scholar 

  16. Rieseberg LH, Soltis D. Phylogenetic consequences of cytoplasmic gene flow in plants. Evol Trend Plant. 1991;5:65–84.

    Google Scholar 

  17. Hansen AK, Escobar LK, Gilbert LE, Jansen RK. Paternal, maternal, and biparental inheritance of the chloroplast genome in Passiflora (Passifloraceae): implications for phylogenetic studies. Am J Bot. 2007;94(1):42–6.

    Article  CAS  PubMed  Google Scholar 

  18. Zhang J-Q, Meng S-Y, Allen GA, Wen J, Rao G-Y. Rapid radiation and dispersal out of the Qinghai-Tibetan plateau of an alpine plant lineage Rhodiola (Crassulaceae). Mol Phylogenet Evol. 2014;77:147–58.

    Article  PubMed  Google Scholar 

  19. Friesen N, German DA, Hurka H, Herden T, Oyuntsetseg B, Neuffer B. Dated phylogenies and historical biogeography of Dontostemon and Clausia (Brassicaceae) mirror the palaeogeographical history of the Eurasian steppe. J Biogeogr. 2016;43(4):738–49.

    Article  Google Scholar 

  20. Brandley MC, Wang Y, Guo X, Montes de Oca AN, Fería-Ortíz M, Hikida T, et al. Accommodating heterogenous rates of evolution in molecular divergence dating methods: an example using intercontinental dispersal of Plestiodon (Eumeces) lizards. Syst Biol. 2011;60(1):3–15.

    Article  CAS  PubMed  Google Scholar 

  21. Gitzendanner MA, Soltis PS, Yi T-S, Li D-Z, Soltis DE. Plastome phylogenetics: 30 years of inferences into plant evolution. In: Chaw S-M, Jansen RK, editors. Advances in botanical ResearchPlant diversity, vol. 85. London: Academic Press; 2018. p. 293–313.

    Google Scholar 

  22. Doyle JJ, Doyle JL. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem Bull. 1987;19:11–5.

    Google Scholar 

  23. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Andrews S. FastQC: a quality control tool for high throughput sequence data. 2010. http://www.bioinformatics.babraham.ac.uk/projects/fastqc. Accessed 15 Oct 2021.

    Google Scholar 

  25. Dierckxsens N, Mardulyn P, Smits G. NOVOPlasty: de novo assembly of organelle genomes from whole genome data. Nucleic Acids Res. 2016;45(4):e18–e.

    PubMed Central  Google Scholar 

  26. Jin J-J, Yu W-B, Yang J-B, Song Y, dePamphilis CW, Yi T-S, et al. GetOrganelle: a fast and versatile toolkit for accurate de novo assembly of organelle genomes. Genome Biol. 2020;21(1):241.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Li H, Durbin R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics. 2010;26(5):589–95.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25(16):2078–9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, et al. Geneious basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics. 2012;28(12):1647–9.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Tillich M, Lehwark P, Pellizzer T, Ulbricht-Jones ES, Fischer A, Bock R, et al. GeSeq - versatile and accurate annotation of organelle genomes. Nucleic Acids Res. 2017;45(W1):W6–W11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Lohse M, Drechsel O, Kahlau S, Bock R. OrganellarGenomeDRAW—a suite of tools for generating physical maps of plastid and mitochondrial genomes and visualizing expression data sets. Nucleic Acids Res. 2013;41(W1):W575–W81.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Darling AC, Mau B, Blattner FR, Perna NT. Mauve: multiple alignment of conserved genomic sequence with rearrangements. Genome Res. 2004;14(7):1394–403.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Amiryousefi A, Hyvönen J, Poczai P. IRscope: an online program to visualize the junction sites of chloroplast genomes. Bioinformatics. 2018;34(17):3030–1.

    Article  CAS  PubMed  Google Scholar 

  34. Frazer KA, Pachter L, Poliakov A, Rubin EM, Dubchak I. VISTA: computational tools for comparative genomics. Nucleic Acids Res. 2004;32(suppl_2):W273–W9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30(4):772–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Librado P, Rozas J. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics. 2009;25(11):1451–2.

    Article  CAS  PubMed  Google Scholar 

  37. Wickham H. ggplot2: elegant graphics for data analysis. New York: Springer-Verlag; 2016.

    Book  Google Scholar 

  38. R Core Team. R: The R Project for Statistical Computing. 2021. https://www.r-project.org. Accessed 15 Dec 2021.

  39. Kurtz S, Choudhuri JV, Ohlebusch E, Schleiermacher C, Stoye J, Giegerich R. REPuter: the manifold applications of repeat analysis on a genomic scale. Nucleic Acids Res. 2001;29(22):4633–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Beier S, Thiel T, Münch T, Scholz U, Mascher M. MISA-web: a wFrontiers in plant Scienceeb server for microsatellite prediction. Bioinformatics. 2017;33(16):2583–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Benson G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 1999;27(2):573–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Duvall MR, Burke SV, Clark DC. Plastome phylogenomics of Poaceae: alternate topologies depend on alignment gaps. Bot J Linn Soc. 2020;192(1):9–20.

    Article  Google Scholar 

  43. Orton LM, Barbera P, Nissenbaum MP, Peterson PM, Quintanar A, Soreng RJ, et al. A 313 plastome phylogenomic analysis of Pooideae: exploring relationships among the largest subfamily of grasses. Mol Phylogenet Evol. 2021;159:107110.

    Article  PubMed  Google Scholar 

  44. Steenwyk JL, Buida TJ III, Li Y, Shen X-X, Rokas A. ClipKIT: a multiple sequence alignment trimming software for accurate phylogenomic inference. PLoS Biol. 2020;18(12):e3001007.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Borowiec ML. AMAS: a fast tool for alignment manipulation and computing of summary statistics. PeerJ. 2016;4:e1660.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014;30(9):1312–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Yang Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol. 2007;24(8):1586–91.

    Article  CAS  PubMed  Google Scholar 

  48. Xiao T-W, Xu Y, Jin L, Liu T-J, Yan H-F, Ge X-J. Conflicting phylogenetic signals in plastomes of the tribe Laureae (Lauraceae). PeerJ. 2020;8:e10155.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol. 2018;35(6):1547–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Yang Z, Nielsen R. Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages. Mol Biol Evol. 2002;19(6):908–17.

    Article  CAS  PubMed  Google Scholar 

  51. Bouckaert R, Heled J, Kühnert D, Vaughan T, Wu C-H, Xie D, et al. BEAST 2: a software platform for bayesian evolutionary analysis. PLoS Comp Biol. 2014;10(4):e1003537.

    Article  CAS  Google Scholar 

  52. Darriba D, Posada D, Kozlov AM, Stamatakis A, Morel B, Flouri T, et al. ModelTest-NG: a new and scalable tool for the selection of DNA and protein evolutionary models. Mol Biol Evol. 2020;37(1):291–4.

    Article  CAS  PubMed  Google Scholar 

  53. Friis EM, Eklund H, Pedersen KR, Crane PR. Virginianthus calycanthoides gen. Et sp. nov.-a Calycanthaceous flower from the Potomac group (early cretaceous) of eastern North America. Int J Plant Sci. 1994;155(6):772–85.

    Article  Google Scholar 

  54. Li H, Liu B, Davis CC, Yang Y. Plastome phylogenomics, systematics, and divergence time estimation of the Beilschmiedia group (Lauraceae). Mol Phylogenet Evol. 2020;151:106901.

    Article  PubMed  Google Scholar 

  55. Kondraskov P, Schütz N, Schüßler C, de Sequeira MM, Guerra AS, Caujapé-Castells J, et al. Biogeography of Mediterranean hotspot biodiversity: re-evaluating the 'Tertiary Relict' hypothesis of Macaronesian Laurel forests. PLoS One. 2015;10(7):e0132091.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Eklund H. Lauraceous flowers from the late cretaceous of North Carolina, U.S.A. Bot J Linn Soc. 2000;132(4):397–428.

    Article  Google Scholar 

  57. Atkinson BA, Stockey RA, Rothwell GW, Mindell RA, Bolton MJ. Lauraceous flowers from the Eocene of Vancouver Island: Tinaflora beardiae gen. Et sp. nov. (Lauraceae). Int J Plant Sci. 2015;176(6):567–85.

    Article  Google Scholar 

  58. Tang B, Han M, Xu Q, Jin J. Leaf cuticle microstructure of Machilus maomingensis sp. nov. (Lauraceae) from the Eocene of the Maoming basin, South China. Acta Geol Sin - Engl. 2016;90(5):1561–71.

    Article  Google Scholar 

  59. Rambaut A, Drummond AJ, Xie D, Baele G, Suchard MA. Posterior summarization in bayesian phylogenetics using tracer 1.7. Syst Biol. 2018;67(5):901–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Chen C, Zheng Y, Liu S, Zhong Y, Wu Y, Li J, et al. The complete chloroplast genome of Cinnamomum camphora and its comparison with related Lauraceae species. PeerJ. 2017;5:e3820.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Song Y, Yu WB, Tan Y, Liu B, Yao X, Jin J, et al. Evolutionary comparisons of the chloroplast genome in Lauraceae and insights into loss events in the Magnoliids. Genome Biol Evol. 2017;9(9):2354–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Mower JP, Guo W, Partha R, Fan W, Levsen N, Wolff K, et al. Plastomes from tribe Plantagineae (Plantaginaceae) reveal infrageneric structural synapormorphies and localized hypermutation for Plantago and functional loss of ndh genes from Littorella. Mol Phylogenet Evol. 2021;162:107217.

    Article  PubMed  Google Scholar 

  63. Weng M-L, Ruhlman TA, Jansen RK. Expansion of inverted repeat does not decrease substitution rates in Pelargonium plastid genomes. New Phytol. 2017;214(2):842–51.

    Article  CAS  PubMed  Google Scholar 

  64. Wei N, Pérez-Escobar OA, Musili PM, Huang W-C, Yang J-B, Hu A-Q, et al. Plastome evolution in the Hyperdiverse genus Euphorbia (Euphorbiaceae) using Phylogenomic and comparative analyses: large-scale expansion and contraction of the inverted repeat region. Front Plant Sci. 2021;12:712064.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Lee C, Choi IS, Cardoso D, de Lima HC, de Queiroz LP, Wojciechowski MF, et al. The chicken or the egg? Plastome evolution and an independent loss of the inverted repeat in papilionoid legumes. Plant J. 2021;107(3):861–75.

    Article  CAS  PubMed  Google Scholar 

  66. Goulding SE, Wolfe KH, Olmstead RG, Morden CW. Ebb and flow of the chloroplast inverted repeat. Mol Gen Genet MGG. 1996;252(1):195–206.

    Article  CAS  PubMed  Google Scholar 

  67. Wang R-J, Cheng C-L, Chang C-C, Wu C-L, Su T-M, Chaw S-M. Dynamics and evolution of the inverted repeat-large single copy junctions in the chloroplast genomes of monocots. BMC Evol Biol. 2008;8(1):36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Zhang L, Wang S, Su C, Harris A, Zhao L, Su N, et al. Comparative chloroplast genomics and phylogenetic analysis of Zygophyllum (Zygophyllaceae) of China. Front Plant Sci. 2021;12:723622.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Cao Q, Gao Q, Ma X, Zhang F, Xing R, Chi X, et al. Plastome structure, phylogenomics and evolution of plastid genes in Swertia (Gentianaceae) in the Qing-Tibetan plateau. BMC Plant Biol. 2022;22(1):195.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Weng M-L, Blazier JC, Govindu M, Jansen RK. Reconstruction of the ancestral plastid genome in Geraniaceae reveals a correlation between genome rearrangements, repeats, and nucleotide substitution rates. Mol Biol Evol. 2014;31(3):645–59.

    Article  CAS  PubMed  Google Scholar 

  71. Yang Q, Fu G-F, Wu Z-Q, Li L, Zhao J-L, Li Q-J. Chloroplast genome evolution in four Montane Zingiberaceae taxa in China. Front Plant Sci. 2022;12:774482.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Gui L, Jiang S, Xie D, Yu L, Huang Y, Zhang Z, et al. Analysis of complete chloroplast genomes of Curcuma and the contribution to phylogeny and adaptive evolution. Gene. 2020;732:144355.

    Article  CAS  PubMed  Google Scholar 

  73. Piot A, Hackel J, Christin P-A, Besnard G. One-third of the plastid genes evolved under positive selection in PACMAD grasses. Planta. 2018;247(1):255–66.

    Article  CAS  PubMed  Google Scholar 

  74. Drescher A, Ruf S, Calsa T Jr, Carrer H, Bock R. The two largest chloroplast genome-encoded open reading frames of higher plants are essential genes. Plant J. 2000;22(2):97–104.

    Article  CAS  PubMed  Google Scholar 

  75. Kikuchi S, Asakura Y, Imai M, Nakahira Y, Kotani Y, Hashiguchi Y, et al. A Ycf2-FtsHi Heteromeric AAA-ATPase complex is required for chloroplast protein import. Plant Cell. 2018;30(11):2677–703.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Kapralov MV, Filatov DA. Widespread positive selection in the photosynthetic Rubisco enzyme. BMC Evol Biol. 2007;7(1):73.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  77. Kapralov MV, Filatov DA. Molecular adaptation during adaptive radiation in the Hawaiian endemic genus Schiedea. PLoS One. 2006;1(1):e8.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  78. CBOL Plant Working Group, Hollingsworth Peter M, Forrest Laura L, Spouge John L, Hajibabaei M, Ratnasingham S, et al. A DNA barcode for land plants. Proc Natl Acad Sci U S A. 2009;106(31):12794–7.

    Article  PubMed Central  Google Scholar 

  79. Kress WJ. Plant DNA barcodes: applications today and in the future. J Syst Evol. 2017;55(4):291–307.

    Article  Google Scholar 

  80. Lu L-M, Mao L-F, Yang T, Ye J-F, Liu B, Li H-L, et al. Evolutionary history of the angiosperm flora of China. Nature. 2018;554(7691):234–8.

    Article  CAS  PubMed  Google Scholar 

  81. Kress WJ, García-Robledo C, Uriarte M, Erickson DL. DNA barcodes for ecology, evolution, and conservation. Trends Ecol Evol. 2015;30(1):25–35.

    Article  PubMed  Google Scholar 

  82. Li X-Q, Xiang X-G, Zhang Q, Jabbour F, Ortiz RC, Erst AS, et al. Immigration dynamics of tropical and subtropical Southeast Asian limestone karst floras. Proc Royal Soc B. 1966;2022(289):20211308.

    Google Scholar 

  83. Starr JR, Naczi RFC, Chouinard BN. Plant DNA barcodes and species resolution in sedges (Carex, Cyperaceae). Mol Ecol Resour. 2009;9(s1):151–63.

    Article  CAS  PubMed  Google Scholar 

  84. Dong W, Xu C, Li C, Sun J, Zuo Y, Shi S, et al. ycf1, the most promising plastid DNA barcode of land plants. Sci Rep. 2015;5(1):8348.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Liu C, Chen H-H, Tang L-Z, Khine PK, Han L-H, Song Y, et al. Plastid genome evolution of a monophyletic group in the subtribe lauriineae (Laureae, Lauraceae). Plant Divers. 2021. https://doi.org/10.1016/j.pld.2021.11.009.

  86. Whitfield JB, Lockhart PJ. Deciphering ancient rapid radiations. Trends Ecol Evol. 2007;22(5):258–65.

    Article  PubMed  Google Scholar 

  87. Suh A, Smeds L, Ellegren H. The dynamics of incomplete lineage sorting across the ancient adaptive radiation of Neoavian birds. PLoS Biol. 2015;13(8):e1002224.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  88. Yu Y, Than C, Degnan JH, Nakhleh L. Coalescent histories on phylogenetic networks and detection of hybridization despite incomplete lineage sorting. Syst Biol. 2011;60(2):138–49.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Rose JP, Toledo CAP, Lemmon EM, Lemmon AR, Sytsma KJ. Out of sight, out of mind: widespread nuclear and plastid-nuclear discordance in the flowering plant genus Polemonium (Polemoniaceae) suggests widespread historical gene flow despite limited nuclear signal. Syst Biol. 2021;70(1):162–80.

    Article  CAS  PubMed  Google Scholar 

  90. Zhou B-F, Yuan S, Crowl AA, Liang Y-Y, Shi Y, Chen X-Y, et al. Phylogenomic analyses highlight innovation and introgression in the continental radiations of Fagaceae across the northern hemisphere. Nat Commun. 2022;13(1):1320.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Trofimov D, Rohwer JG. Towards a phylogenetic classification of the Ocotea complex (Lauraceae): an analysis with emphasis on the Old World taxa and description of the new genus Kuloa. Bot J Linn Soc. 2020;192(3):510–35.

    Article  Google Scholar 

  92. Tiffney BH. Perspectives on the origin of the floristic similarity between eastern Asia and eastern North America. J Arnold Arboretum. 1985;66:73–94.

    Article  Google Scholar 

  93. Wolfe JA. Some aspects of plant geography of the northern hemisphere during the late cretaceous and tertiary. Ann Mo Bot Gard. 1975;62:264–79.

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank Bu-Hang Li, Feng-Lin Chen, Qi-Ming Mei, Qiao-Ming Li, Ting Li, and Yong Xu for their assistance in sample collection, Yu-Ying Zhou for DNA extraction, and Dimitar Dimitrov for his helpful suggestions on data analysis. The authors would like to thank TopEdit (www.topeditsci.com) for linguistic assistance during preparation of this manuscript.

Funding

The project was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences, Grant No. XDB31000000.

Author information

Authors and Affiliations

  1. Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China

    Tian-Wen Xiao & Xue-Jun Ge

  2. Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences, Guangzhou, China

    Xue-Jun Ge

Authors
  1. Tian-Wen Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xue-Jun Ge
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization, TWX and XJG; data analysis, TWX; writing—original draft preparation, TWX; writing—review and editing, XJG and TWX. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Xue-Jun Ge.

Ethics declarations

Ethics approval and consent to participate

No specific permits were required for the samples in this study. Material collection and molecular experiments were carried on in compliance with the relevant laws of China.

Consent for publication

Not applicable.

Competing interests

The authors declare that there are no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Table S1.

The plastomes used in different analyses of this study. Table S2. Collection information and accession numbers of the 15 samples of tribe Cinnamomeae. Table S3. The GenBank accession numbers of ITS, RPB2, and LEAFY. Table S4. Gene content of the 15 newly generated plastomes. Table S5. The sequences of primers. Table S6. Number of dispersed repeats, SSRs, and tandem repeats of the 39 species of tribe Cinnamomeae. Table S7.p value of the likelihood ratio tests and positively selected codon sites.

Additional file 2: Fig. S1.

Comparison of the SC/IR junctions among the 15 newly generated plastomes of tribe Cinnamomeae. JLA, LSC/IRa boundary; JSA, SSC/IRa boundary; JSB, SSC/IRb boundary; JLB, LSC/IRb boundary. Fig. S2. Map of the gel electrophoresis experiments. XTBG, Cinnamomum chartophyllum; D053, C. cassia; wh020, C. longepaniculatum. Fig. S3. Structural alignment of the 15 newly generated plastomes of tribe Cinnamomeae inferred from Mauve. Fig. S4. Visualized alignments of 39 plastomes of tribe Cinnamomeae using mVISTA. The vertical scale indicates percentage of identity ranging from 50 to 100%. Exons are colored in dark blue, non-coding sequences (CNS) are colored in red, tRNA and rRNA genes (UTR) are colored in green. Fig. S5. Phylogenetic tree inferred from maximum likelihood analysis using concatenated complete plastomes with one IR removed (CP-c). Bootstrap values are indicated above branches. Fig. S6. Phylogenetic tree inferred from maximum likelihood analysis using concatenated non-protein-coding genes (NPCG-c). Bootstrap values are indicated above branches.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Xiao, TW., Ge, XJ. Plastome structure, phylogenomics, and divergence times of tribe Cinnamomeae (Lauraceae). BMC Genomics 23, 642 (2022). https://doi.org/10.1186/s12864-022-08855-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12864-022-08855-4

Keywords

  • Lauraceae
  • Plastome
  • Hypervariable region
  • Divergence time estimation

BMC Genomics

ISSN: 1471-2164

Contact us