Abstract
Prior to this study, complete mitochondrial genomes from Order Thysanoptera were restricted to a single family, the Thripidae, resulting in a biased view of their evolution. Here we present the sequences for the mitochondrial genomes of four additional thrips species, adding three extra families and an additional subfamily, thus greatly improving taxonomic coverage. Thrips mitochondrial genomes are marked by high rates of gene rearrangement, duplications of the control region and tRNA mutations. Derived features of mitochondrial tRNAs in thrips include gene duplications, anticodon mutations, loss of secondary structures and high gene translocation rates. Duplicated control regions are found in the Aeolothripidae and the ‘core’ Thripinae clade but do not appear to promote gene rearrangement as previously proposed. Phylogenetic analysis of thrips mitochondrial sequence data supports the monophyly of two suborders, a sister-group relationship between Stenurothripidae and Thripidae, and suggests a novel set of relationships between thripid genera. Ancestral state reconstructions indicate that genome rearrangements are common, with just eight gene blocks conserved between any thrips species and the ancestral insect mitochondrial genome. Conversely, 71 derived rearrangements are shared between at least two species, and 24 of these are unambiguous synapomorphies for clades identified by phylogenetic analysis. While the reconstructed sequence of genome rearrangements among the protein-coding and ribosomal RNA genes could be inferred across the phylogeny, direct inference of phylogeny from rearrangement data in MLGO resulted in a highly discordant set of relationships inconsistent with both sequence-based phylogenies and previous morphological analysis. Given the demonstrated rates of genomic evolution within thrips, extensive sampling is needed to fully understand these phenomena across the order.
Subject terms: Phylogenetics, Next-generation sequencing
Introduction
Complete mitochondrial genomes have been shown to be useful for phylogenetic and evolutionary studies at various taxonomic scales, as they provide more phylogenetic information than individual genes alone1–4. The mitochondrial genome of metazoans is typically a circular molecule 14–19 kilobases (kb) in length, that contains a conserved set of 37 genes: 13 protein-coding genes (PCGs), ATPase subunits 6 and 8 (atp6 and atp8), Cytochrome oxidase subunits 1 to 3 (cox1-cox3), cytochrome b (cob), NADH dehydrogenase subunits 1–6 and 4 L (nad1-6 and nad4L); the small and large subunit rRNAs (rrnL and rrnS), 22 transfer RNA (tRNA) genes, and a non-coding control region (CR) which contains initiation sites for transcription and replication1,5. In addition to sequence variation, metazoan mitochondrial genomes also exhibit variation in a number of features, such as length, tRNA secondary structure, gene order, and the number and internal structure of control regions6–8. These features can provide evidence for evolutionary relationships among taxa at high and/or low taxonomic levels beyond that provided by analysis of mitochondrial sequence data alone9–11.
The thrips, Order Thysanoptera, are a small order of insects, with 6154 described species12. The order is currently divided into two suborders, Terebrantia and Tubulifera, and nine families13. Despite the modest diversity of the group, the eight published thrips mitochondrial genomes are all from members of the suborder Terebrantia; a single unpublished genome from Tubulifera (GenBank Accession No. KP198620). Even within Terebrantia, information is available for just three of the four subfamilies within a single family, Thripidae: Thripinae (Anaphothrips obscurus14, Frankliniella intonsa15, F. occidentalis16, Scirtothrips dorsalis17, Thrips imaginis18, and T. palmi19), Dendrothripinae (Dendrothrips minowai20), and Sericothripinae (Neohydatothrips samayunkur21).
Multiple classification hypothesis have been proposed for Thysanoptera13,22–24, each of which conflicts with studies of thrips phylogenetic relationships. The most widely followed classification of order Thysanoptera recognises two suborders and 13 families (nine extant and four extinct families)13. Bhatti elevated Thysanoptera to a superorder with Terebrantia and Tubulifera as orders, and proposed 40 families based on highly conserved structures in the body architecture24, including elevating the subfamilies Dendrothripinae, Panchaetothripinae, Sericothripinae, Franklinothripinae to family level. In the only major study of thrips phylogenetics, Buckman et al. (2013) used multiple molecular markers to test the relationships within thrips, particularly of families and subfamilies25. Their data supported the monophyly of Tubulifera and Terebrantia and of the families Phlaeothripidae, Aeolothripidae, Melanthripidae and Thripidae. However, relationships between the four thripid subfamilies, Dendrothripinae, Sericothripinae, Panchaetothripinae, and Thripinae, were unclear. The two largest subfamilies, Phlaeothripinae and Thripinae, were paraphyletic and require further study to understand their internal relationships. Mitochondrial genome data from Thysanoptera are analysed there in order to further clarify the phylogenetic relationships of the order.
In the present study, four mitochondrial genomes representing three additional thrips families plus the fourth thripid subfamily (Panchaeotothripinae) were sequenced, annotated and compared to the other available thrips genomes. We analysed the main features of the newly generated genomes, including nucleotide composition, secondary structure of tRNAs and control region. To determine relationships within Thysanoptera, analyses with sequence-based and genome rearrangement phylogenetic inference methods were used.
Materials and Methods
Ethics statement
Thrips specimens were collected in the field by the beating method. All species used in this study are common on agricultural and horticultural crops and are not listed in “List of Protected Animals in India”. Thus, no prior permission was required for their collection.
Sample collection and DNA extraction
Specimens of Franklinothrips vespiformis (from general vegetation), G. uzeli (from banyan tree, Ficus benghalensis), H. indicus (from date palm, Phoenix sp.) and R. cruentatus (from pomegranate, Punica granatum) were collected from Odisha State, India. Specimens were preserved in absolute alcohol and stored at −80 °C at the Centre for DNA Taxonomy, Molecular Systematics Division, Zoological Survey of India, Kolkata. Morphological identification of all the specimens was done by the author (K.T.) with the help of available taxonomic keys26–30. The DNeasy DNA Extraction kit (QIAGEN) was used for the extraction of the genomic DNA following the manufacturer’s standard protocol. DNA Quantity was estimated by using a Qubit fluorometer with the dsDNA high-sensitivity kit (Invitrogen) and by agarose gel (0.8%) electrophoresis.
Mitochondrial genome sequencing, assembly, annotation
Whole genomic DNA was sequenced using the Illumina NextSeq500 (2 × 150 base paired-end reads) (Illumina, USA) platform. Paired-end libraries were constructed using the TruSeq DNA Library Preparation kit according to standard protocols. Libraries were pooled, cleaned with Highprep magnetic beads (Magbio) and then sequenced on a Nextseq 500, using 2 × 150 chemistry at the Genotypic Technology Pvt. Ltd. Bangalore, India (http://www.genotypic.co.in/). The approximately 25 million raw reads were trimmed to remove the low quality reads by using NGS-Toolkit31. Trimmed reads were filtered using the Burrows-Wheeler Alignment (BWA) tool32 and then assembled in SPAdes 3.9.033 using default parameters and the Scirtothrips dorsalis EA mitochondrial genome as a reference. Aligned reads were used for de novo mitochondrial genome assembly. The annotation of the assembled genome was performed using the MITOS web-server34 (http://mitos.bioinf.uni-leipzig.de/index.py) to estimate the location of protein coding (PCGs), transfer RNA (tRNAs), and ribosomal RNA genes (rRNAs). Gene boundaries for PCGs and rRNAs were confirmed manually using BLASTn, BLASTp and ORF Finder (as implemented at NCBI35 (https://www.ncbi.nlm.nih.gov/orffinder/). Initiation and termination codons were confirmed in MEGAX36 using the published mitochondrial genome sequences of other thrips as references. The secondary structures of tRNAs were predicted by using MITOS, tRNAscan-SE37 (http://lowelab.ucsc.edu/tRNAscan-SE/), and ARWEN 1.238. In addition to annotating the four thrips species sequenced here, the mitochondrial genome of Haplothrips aculeatus (GenBank KP198620) was re-annotated to identify genes missing from the GenBank record for this species.
Genome visualization, and comparative analysis
The circular genome maps for all four species were predicted by the CGView online server (http://stothard.afns.ualberta.ca/cgview_server/) with default parameters (Fig. 1, Table 1). Differences between tRNA isotypes in thrips species were assessed by p- and maximum composite likelihood distances for each pairwise-comparison using MEGAX36. Base mismatches occurring at the boundaries between DHU or TΨC arms and in loop regions were not considered for tRNA distances due to length variation in these areas. The secondary structures within control regions (CRs) were predicted by mfold39 (unafold.rna.albany.edu/?q = mfold) using default parameters. Homology between CR copies in thrips species with multiple CRs were determined with a ClustalW40 sequence alignment implemented in MEGAX. Tandem repeats within CR were identified with Tandem Repeats Finder41 (https://tandem.bu.edu/trf/trf.html).
Table 1.
Sub-order | Family | Subfamily | Species | Accession No. | Size (bp) | Reference |
---|---|---|---|---|---|---|
Terebrantia | Aeolothripidae | Franklinothrips vespiformis | MN072395 | 16,224 | This Study | |
Stenurothripidae | Holarthothrips indicus | MN072397 | 15,243 | This Study | ||
Thripidae | Dendrothripinae | Dendrothrips minowai | MF582634 | 14,631 | Chen SC, et al.20 | |
Panchaetothripinae | Rhiphiphorothrips cruentatus | MN072396 | 15,143 | This Study | ||
Sericothripinae | Neohydatothrips samayunkur | MF991901 | 15,295 | Kumar et al.36 | ||
Thripinae | Thrips palmi | MF991901 | 15,333 | Chakraborty et al.19 | ||
Anaphothrips obscurus | KY498001 | 14,890 | Liu et al. 2017 | |||
Scirtothrips dorsalis EA | KM349826 | 15,343 | Dickey et al.17 | |||
Scirtothrips dorsalis SA | KM349827 & KM349828 | 15,204 | Dickey et al.17 | |||
Frankliniella intonsa | JQ917403 | 15,215 | Yan et al.15 | |||
Frankliniella occidentalis | JN835456 | 14,889 | Yan et al.16 | |||
Thrips imaginis | AF335993 | 15,407 | Shao et al. 2001 | |||
Tubulifera | Phlaeothripidae | Phlaeothripinae | Gynaikothrips uzeli | MK940484 | 14,002 | This Study |
Haplothrips aculeatus | KP198620 | 14,616 | Unpublished |
Data set preparation, model selection and phylogenetic analysis
Phylogenetic analysis was conducted on the PCGs from the 10 thrips mitochondrial genomes, the four species newly sequenced here and a representative of the Hemiptera (Alloerhunchus bakeri)42 as an outgroup. This outgroup was chosen as Hemiptera are generally considered to be the sister group of thrips43. Sequences for each PCG were aligned individually with codon-based multiple alignments using MAFFT as implemented in the TranslatorX44. Given that initial alignments resulted in some ‘gappy’ and potentially poorly aligned regions, masking of ambiguously aligned sites was performed using GBlocks45 (as implemented in TranslatorX) using default setting. Ambiguously aligned sites were removed from the protein alignment before back-translation to nucleotides. The dataset of all PCGs were concatenated using SequenceMatrix v1.7.84546. To assess the impact of high substitution rates and potentially poorly aligned regions within genes, four data sets were constructed: (1) all 13 PCGs, all codon positions, 12334 bp; (2) all 13 PCGs, third codon position excluded, 8124 bp.: (3) all 13 PCGs, all codon positions, masked with GBlock,s 8421 bp; (4) all 13 PCGs, third codon position exluded, masked with GBlocks, 5614 bp. To find the best substitution models, PartitionFinder version 2.1.147 was used with the ‘greedy’ algorithm and the following predefined partitions: codon positions for each PCG (39 partitions for datasets 1 and 3, 26 for datasets 2 and 4) (Supplementary Table S1). The CIPRES Science Gateway v.3.148 (www.phylo.org/sub_sections/portal/) portal was used to infer both Bayesian (BI) and maximum likelihood (ML) phylogenies for each of the 4 datasets. BI analyses were conducted with Mr.Bayes ver. 3.249 with two MCMC runs each with four chains (three heated and one cold) run for 500,000 generations, with tree sampling every 100 generations and a burn-in of 25%. The ML analysis was performed using IQ tree ver.1.6.1050,51 with 1000 replicates of ultrafast likelihood bootstrap to obtain a consensus tree. Phylogenetic trees were visualized and edited using FigTree ver 1.4.252 (http://tree.bio.ed.ac.uk/software/figtree/).
Gene order analysis and ancestral state estimation
Three methods were applied to estimate gene arrangement history in Thysanoptera: (1) mapping of ancestral and shared derived boundaries; (2) common interval analysis; and (3) maximum likelihood analysis of gene order. The vast majority of insect mitochondrial genomes sequenced to date share an identical gene order, the inferred ancestral insect mitochondrial genome1, which is most parsimoniously inferred to have been present in the common ancestors of many insect orders including the sister-group of thrips, Hemiptera53. While mitochondrial genome rearrangements have been found in some hemipteran species, in each instance these are confined to derived clades representing disparate groups. All mitochondrial gene rearrangements observed in thrips, thus occurred at some point after the common ancestor of Thysanoptera + Hemiptera, and the evolutionary pattern of these rearrangements is inferred relative to this ancestor who retained the inferred ancestral insect mitochondrial genome1.
Gene boundary mapping was conducted by pairwise comparison of each thrips genome to the inferred ancestral insect mitochondrial genome1 to determine the retention of ancestral and derived gene boundaries following Yoshizawa et al.54 (Supplementary Table S2). The longest series of shared gene-boundaries between any two species were identified as ‘gene blocks’ and species with only a portion of the gene block (i.e. 1 or more of its gene boundaries) identified as possessing a ‘modified gene block’. Shared ancestral and derived gene boundaries/blocks were mapped onto the BI tree inferred from dataset 1.
Common interval analysis was conducted using CREx55 for pairwise comparisons and TreeREx56 for inference of ancestral genome states. Pairwise comparisons using CREx were performed for each of the four newly sequenced thrips genomes against the inferred ancestral insect mitochondrial genome to determine the minimum number of genome rearrangement events separating each thrips species from the ancestral state. CREx considers four types of rearrangement events: transpositions, inversions (gene inverted but not transposed), inverse transpositions (gene both inverted and transposed) and tandem-duplication/random loss (TDRL) involving the duplication and rearrangement of multiple genes within a single gene block.
By comparing genome common intervals over a fixed phylogenetic tree, TreeREx56 infers genome states for the common ancestor at each node in that tree, and allows the order of genome rearrangements in evolutionary time to be inferred. TreeREx utilises the same common interval algorithm as CREx and the same set of rearrangement events (transpositions, inversions, inverse transpositions, TDRL). TreeREx analysis was performed with default settings: strong consistency method applied (-s); weak consistency method applied (-w); parsimonious weak consistency method applied (-W); obtain alternative bp scenario for prime nodes (-o); maximum number of inversions (−m = 0), +TDRL scenarios considered.
As both CREx and TreeREx are incapable of handling genomes without fixed gene sets, both missing data and the duplication of genes as observed in thrips violates the algorithm and require work arounds. Genes that were apparently missing (one tRNA), were omitted from pairwise CREx analyses for the species in which they were not detected (Supplementary Table S3). TreeREx analyses of all thrips taxa were conducted using just the relative order of the major genes (PCGs, rRNAs, primary CR) because some species were missing tRNA genes and others had duplicate copies of tRNAs (Supplementary Table S4). Preliminary analyses eliminating both missing and duplicated genes from all species but retaining all other tRNAs indicated such high rates of tRNA rearrangement that any phylogenetic patterns in the remaining genes could not be identified. Treating tRNA rearrangements as ‘noise’ in such reconstructions has been previously applied to identify ancestral genome arrangements for each of the bilaterian superphyla34, and is an efficient way to account for the differences in rearrangement rate between classes of mitochondrial genes. This approach was taken here.
MLGO (maximum likelihood analysis of gene order)57 is an algorithm for directly inferring phylogeny based on gene order data, and is not limited to a common gene set across taxa in the way that CREx/TreeREx is. Complete gene order data, including duplicated and excluding missing genes only from those taxa in which they were undetected were used to infer a phylogeny of thrips (Supplementary Table S5). The MLGO phylogeny was compared against those generated from sequence data alone (datasets 1–4, both BI and ML analyses) to determine the direct phylogenetic signal from gene-order data alone.
Results
Genome structure, organization and composition
We sequenced complete mitochondrial genomes of F. vespiformis (16,224 bp long), H. indicus (15,243 bp), R. cruentatus (15,143 bp) and G. uzeli (14,002 bp) (Fig. 1, Supplementary Table S6). All four species had at least the canonical 37 genes found in most Metazoa, except G. uzeli in which tRNA isoleucine (trnI) was not detected. One control region (CR) was detected in H. indicus, R. cruentatus and G. uzeli while two were found in F. vespiformis.
Most of the genes in F. vespiformis, H. indicus, and R. cruentatus were encoded on the majority strand except three PCGs (nad5, nad4, nad4L) and three tRNAs (trnC, trnH and trnP). Although the majority of genes in G. uzeli were also encoded by the majority strand, a slightly larger number were encoded on the minority strand, four PCGs (nad5, nad4, nad4L, nad2), fifteen tRNAs (trnL1, trnH, trnS2, trnC, trnR, trnA, trnY, trnG, trnD, trnL2, trnW, trnM, trnK, trnP, trnV) and both ribosomal RNAs (rrnS, rrnL). All four genomes were AT rich (F. vespifomis: 75.35%, H. indicus: 74.89%, R. cruentatus: 76.58%, and G. uzeli: 82.15%) as has been observed in other thrips and almost all insect mitochondrial genomes (Supplementary Table S7).
Transfer RNAs
All fourteen of the thrips mitochondrial genomes that we examined had the 22 tRNAs found in the ancestral insect mitochondrial genome except for G. uzeli, in which trnI was not detected. Duplicated tRNAs were detected in H. aculeatus (trnM) and in T. imaginis (trnS1, trnE). In H. aculeatus, the second copy of trnM (located between trnV and trnL2) is an exact duplicate of the first copy (65 bp, between trnK and trnV) with same anticodon (CAT), so it is difficult to predict which copy, or both, is functional. In T. imaginis, the first copy of trnS1 (between trnD and trnL1) is 55 bp long whereas the second copy (between CR2 and trnP) is 69 bp and 33.3% similar to the first copy; both have an NCT anticodon. Previous analysis suggested that the trnS1 copy that lies between trnD and trnL1 is more similar to copies of this gene in other thrips species than is the second copy (between CR2 and trnP)18. In T. imaginis, the first copy of trnE (between trnN and CR2) is 64 bp whereas the second copy (between trnD and trnL1) is 29 bp and is 45.3% similar to the first copy; the first copy is clearly the functional one as the second copy lacks an anticodon arm.
A comparison of tRNA secondary structure and nucleotide substitutions across thrips mitochondrial genomes that we examined are provided (Supplementary Figs. S1 and S2). In most thrips sequenced to date tRNAs have the typical cloverleaf secondary structure with a few exceptions. The DHU stem and loop are absent from trnS1 in all thrips species except H. indicus, H. aculaetus, F. intonsa, and F. occidentalis; from trnV in all species except F. vespiformis, G. uzeli, H. indicus, H. aculaetus, and D. minowai; and from trnN in A. obscurus. The TΨC stem and loop is absent from trnL2 in G. uzeli, from trnT in N. samayunkur and T. palmi, and from trnR in N. samayunkur. Lack of the DHU stem-loop in trnS1 is nearly ubiquitous in insect mitochondrial genomes, however the absence of this or other stem-loops from other tRNA isotypes is extremely uncommon58. Finally, there is a consistent difference in anti-codon sequence for trnA between the thrips suborders: GCT in Terebrantia versus GCA in Tubulifera. Anticodon loop mutations, even in the ‘wobble’ nucleotide are comparatively uncommon in insects generally.
Calculations of the p-distance (pDis), maximum- likelihood distance (MLdis) and base difference (BDps) showed that the trnE is the most conserved tRNA (BDps = 6.363, MLdis = 0.293 ± 0.18 and pDis = 0.163 ± 0.07), whereas trnD is the most variable (BDps = 19.04, MLdis = 0.592 ± 0.24 and pDis = 0.359 ± 0.09). trnI was not analysed for substitution patterns as it was not detected in G. uzeli (Supplementary Table S8).
Control regions
The control region is typically the largest non-coding region in the mitochondrial genome, and is heavily biased to A + T nucleotides. The CRs of thrips vary in number, size, and location within the genome across the 13 species sequenced to date due to duplications and gene rearrangements. Three control regions are observed in the F. intonsa, F. occidentalis, and S. dorsalis SA, two in F. vespiformis, N. samayunkur, S. dorsalis EA, T. imaginis, and T. palmi, while the remaining 6 thrips species have only one control region (Figs. 2 and 3). Conserved motifs (including a poly T-stretch at the 5′ end, TA(A)n-like stretch, hairpin loop structures, TATA motif, and G(A)nT motif) within the CR have been identified as initiation sites for replication and transcription6,59–61. These conserved motifs are also detected in thrips, however the arrangement of motifs differs between species.
Previous studies have shown a conserved location of at least one CR between atp6 and nad5, as it was found in all species from the family Thripidae except Neohydatothrips (variable sets of tRNAs are also found between the CR and atp6 in different species, but atp6 is the closest major upstream major gene)14. This CR was thus proposed to be the original location for Thysanoptera as a whole, despite the absence of data from families other than Thripidae, and that this region was homologous between species that had multiple CRs. However, with our expanded sampling it is clear that this conserved position for the CR is confined to Thripidae + Stenurothripidae, whereas CR location differs in Aeolothripidae (between cytb and rrnS), and in each of the two Phlaeothripidae examined between rrnL and nad2 (in Gynaikothrips) and between rrnL and atp6 (in Haplothrips). The position of both CRs within Neohydatothrips, between nad4L and nad6, appears to be secondarily derived, differing as it does from all other thripids sampled to date.
Five thrips species (F. vespiformis, N. samayunkur, S. dorsalis EA, T. imaginis, and T. palmi) have two CRs (Figs. 2 and 3). Sequence similarity between CRs varies widely across species from as low as 10.03% in F. vespiformis to 99% in T. imaginis. Species with higher similarity between CRs correspondingly have higher similarity in the makeup of their CR motifs, i.e. T. imaginis CR motifs are almost identical, while N. samayunkur (44.2% similar) CRs share some features: two tandem repeats of 6 base pairs, 192 bp A + T rich and T-stretch region following with TATA motif, 18 bp hairpin loop flanking with G(A)nT.
A further three thrips species (F. intonsa, F. occidentalis, and S. dorsalis SA) possess three putative CRs (Fig. 3). The CR1 of F. intonsa (between atp6 and nad5, the putative ancestral location in Thripidae) has 54% sequence similarity with CR2 and 50% to CR3, whereas CR2 and CR3 show 91.15% sequence similarity to each other. Each of the three F. intonsa CRs share an 18 bp poly T-stretch, an 18 bp hairpin loop structure, the GAAT motif, whereas three 23 bp long tandem repeats (TRs) are present in CR1 and CR3. F. occidentalis has three CRs in the same genomic locations as its congener F. intonsa, and has a similar pattern of sequence similarity: CR1 is 89.15% similar to CR2 and 86.32% to CR3, while CR2 and CR3 show 98.92% sequence similarity to each other. The three CRs in F. occidentalis also share poly T-stretches (20 bp), hairpin loops (31 bp), A + T rich region (21 bp) and GAAAT motifs, while two of them (CR1 and CR2) share TRs of 17 bp. While the South Asia isolate of Scirothrips dorsalis has three mitochondrial CRs, comparisons are complicated by the fact that this isolate has a multipartite genome, with two CRs on the larger chromosome (representing 93% of genome length, 35/37 genes), and a third on the second, smaller chromosome (representing the remaining 7% and 2/37 genes)14. The CR1 of S. dorsalis SA (again between atp6 and nad5) was 51.74% similar to CR2 and 34.88% to CR3, while CR2 and CR3 showed 49.1% sequence similarity to each other. The two CRs on the larger chromosome (CR1 and CR2) possess a 77 bp A + T rich region, TATA motif, two classes of 3 bp TRs (GAA and GTA), 26 bp poly T-stretch, and a 45 bp hairpin loop structure without the GAT motif. In contrast, CR3 possess all the conserved CR motifs plus two TRs of 27 bp each.
Phylogenetic relationships
We generated eight phylogenetic trees based on four datasets and two inference methods (BI and ML). The topology most commonly recovered across this study is represented by analysis BI-1 (Fig. 4), and variation between analyses is reported below. The suborders Tubulifera and Terebrantia were recovered as monophyletic in all analyses. In six analyses (BI-1 to 4 and ML-1 and ML-3) Stenurothripidae is sister to Thripidae, whereas, in analyses ML-2 and ML-4 (datasets which exclude third codon positions) Aeolothripidae is sister to Stenurothripidae but with low bootstrap support. Thripidae is monophyletic in all analyses, with the subfamily Panchaetothripinae sister to the remaining three subfamilies (Dendrothripinae, Sericothripinae and Panchaetothripinae) in all analyses (Supplementary Figs. S3–S6). Dendrothripinae was sister to part of the Thripinae (Anaphothrips) in the majority of analyses (BI-1, 2, 4, ML-1, 2), but was sister to a clade composed of Thripinae and Sericothripinae species in analyses BI-3, ML-3 and ML-4 trees. The subfamily Sericothripinae always grouped with Scirtothrips, rendering Thripinae paraphyletic in all trees. The genera Frankliniella, Thrips and Scirtothrips were monophyletic in all analyses, however relationships between Thripinae genera varied between analyses: Frankliniella + Thrips (BI-1, 2, 4 and ML-3, 4) versus Frankliniella + (Neohydatothrips + Scirtothrips) (BI-3, ML-1, 2). Genus level relationships appear quite sensitive to inclusion/exclusion decisions regarding potentially high variability sites (both third codon positions and GBlocks masking) and had low nodal support.
Mapping shared gene orders
Linearised gene order maps for 14 thrips mitochondrial genomes plus the inferred ancestral insect gene order are given in Fig. 5. Eight conserved gene blocks (labelled A-H) that have been retained from the ancestral insect in at least one thrips species are mapped on the gene orders (Supplementary Table S2). These ancestral gene blocks consist of between 2 and 7 genes (1–6 gene boundaries) and 150–4000 bp of the genome. Gene blocks that are partly conserved (either due to loss of a portion of the genes or the translocation of other genes into the middle of the gene block) are also noted. Gene block A (cox1-trnL2-cox2) is conserved in H. indicus, R. cruentatus, D. minowai, A. obscurus, and partially present in most of the remaining Thripidae species (nad3 is inserted in Frankliniella, Scirtothrips and T. imaginis). Gene block B (atp8-atp6) is retained in all thrips species except N. samayunkur where atp8 gene has been inverted. Block C (trnR-trnN) is conserved only in H. indicus and R. cruentatus, and partially present in T. imaginis (trnT is inserted between trnR-trnN). Block D (trnN-trnS1-trnE) is conserved in Phlaeothripidae, while a shuffled version of this gene block (trnN-trnE-trnS1) occurs in species of Frankliniella. In contrast, trnS1 is translocated from gene block D in Scirtothrips species and N. samayunkur. Block E (nad5-trnH-nad4-nad4L-trnT-trnP-nad6) is conserved in H. indicus, R. cruentatus and F. vespiformis. Other thrips species have either portions of this gene block (nad5 to nad4L in 8 species) or minor variations due to translocation of tRNAs or CRs into this gene block (3 species). In Phlaeothripidae, block E is split into two gene blocks (nad5-trnH) and (nad4-nad4L-trnT). Block F (nad6-cytb) is found only in G. uzeli. Block G (rrnL-trnV) is conserved in all Terebrantia species except N. samayunkur. Block H (nad2-trnW) is similarly conserved in Terebrantia except F. vespiformis. The phylogenetic distribution of the ancestral gene blocks is shown on Fig. 6.
Four hundred and three derived gene boundaries are found in the 14 available mitochondrial genomes of thrips. Of these, 71 are shared, derived gene boundaries (numbered 1 to 71 in Fig. 5) present in at least two species and a further 90 unique boundaries found in a single species were identified. The gene order of H. indicus (Stenurothripidae) is identical to that of R. cruentatus (Thripidae) sharing 25 derived gene boundaries. Four of these 25 gene boundries (57, 60, 62, 63) are exclusive to these two species, while six (55, 56, 58, 59, 64, 65) are shared with F. vespiformis and one (61) is shared with tubuliferans.
Out of the 71 derived gene boundries, 47 are either homoplastic or secondarily lost in some of the taxa descended from the node and remaining 24 are unambiguously synapomorphies. Hence, 24 shared derived gene boundaries were mapped onto the phylogenetic tree inferred from the BI-1 dataset (Fig. 6). Derived gene boundary 17 (trnW-nad1) is a synapomorphy for all terebrantians except Aeolothripidae, consistent with the majority of the phylogenetic analyses (BI-1 to 4, ML-1, 3). Gene boundaries 6, 7 and 16 (trnG-trnK, trnK-cox3, and trnY-nad2) are synapomorphies for the family Thripidae exclusive of subfamily Panchaetothripinae. Gene boundaries 52 and 53 (nad4L-trnL1 and nad6-trnP) are synapomorphic for the A. obscurus and D. minowai clade, again consistent with the majority of phylogenetic analyses (BI-1, 2, 4, ML-1, 2). Gene boundary 1 (cox1-nad3) is a synapomorphy for the clade composed of ‘thripinae’ i.e. all genera other than Anaphothrips. Gene boundary 37 (trnS1-trnL1) is synapomorphic for the clade Frankliniella plus Thrips. Gene boundary 10 (trnL1-trnT) is a synapomorphy for Neohydatothrips + Scirtothrips. Gene boundaries 47, 48, and 49 (trnP-trnY, atp6-trnN and trnL1-nad5) are synapomorphies for the genus Frankliniella whereas boundaries 35, 40, 41, and 43 (cox2-trnG, atp6-trnQ, trnQ-trnS2, rrnL-cox1) are synapomorphies for Thrips. Gene boundary 9 (trnI-trnL1) and 11 (trnP-trnN) are synapomorhies for Scirtothrips again consistent with the majority of phylogenetic analyses (BI-1, 2, 4, ML-1, 2). The species of Tubulifera have six (66 to 71) synapomorphic gene boundaries (cox-trnQ, trnQ-cox2, trnG-trnD, trnK-trnM, trnR-cytb, nad1-cox1).
Common-interval analysis of gene order with CREX
Gene rearrangements in F. vespiformis
Two alternative scenarios, each with seven rearrangement events were inferred: transposition of trnI, inversion of two gene blocks three major genes (nad1, trnL1, rrnS, trnV, rrnL and trnF) and four TDRL events. In total, six PCGs (nad3, cytb, nad2, nad1, atp8, atp6) were rearranged relative to their position in the ancestral genome. Most tRNAs were in derived positions, and a second CR separates the genes trnL2 and cox2 which are otherwise a conserved gene boundary (part of block A) (Supplementary Fig. S7).
Gene rearrangements in H. indicus, and R. cruentatus
The gene order of R. cruentatus is identical to that of H. indicus despite these two taxa belonging to different families. Again, two alternative scenarios each with seven events were inferred, including the same transposition and inversions as in F. vespiformis with a different set of 4 TDRL events. Most of the major genes and tRNAs are rearranged relative to the ancestral genome (Supplementary Fig. S7).
Gene rearrangements in G. uzeli
Two alternative scenarios, each consisting of 12 inversions and 5 TDRL events were inferred. Twelve of the 15 major genes are in the same relative positions as in the ancestral gene order (nad4/nad4L and rrnL/rrnS have been shuffled in gene order, while nad1 is between nad2 and cox1). Two major genes (nad1 and nad2), and ten tRNAs (trnF, trnS2, trnR, trnA, trnD, trnG, trnL2, trnW, trnM, trnK) have been inverted (Supplementary Fig. S8).
Reconstructing genome evolution across the thrips phylogeny
Due to very high rates of tRNA rearrangement (see preceding section), the relative gene order of the major genes (PCGs and rRNAs) were used to infer the gene order of the common ancestors at each node in the phylogeny (Supplementary Table S4). Replicate analyses were run in TreeREx of the tree inferred from the BI-1 and ML-3 datasets as these represented the most topologically divergent phylogenetic trees recovered from sequence data. The differences between these two topologies, however, did not involve taxa whose relative gene orders differed. For instance, different resolutions of the relationships between the genera Frankliniella, Thrips, Neohydatothrips and Scirtothrips are uninformative with respect to gene order, as each of these gene all share the same arrangement of their major genes.
Large-scale genome rearrangement through TDRL events that duplicated most of the genome were inferred to have occurred between the common ancestor of Thysanoptera and the ancestral insect gene order (Fig. 7A, Supplementary Table S9). Subsequent, similarly large-scale TDRL events were inferred between the common ancestor of Thysanoptera and the Tubulifera, and between the common ancestor of Terebrantia and Franklinothrips. Modest rearrangements (e.g., transposition) of nad3 in the common ancestor of the clade composed of Frankliniella, Thrips, Neohydatothrips and Scirtothrips, and in some terminal taxa e.g. Neohydatothrips and Scirtothrips dorsalis SA, were found in the more derived portions of the tree.
Genome order analysis
Inferring thysanoptera phylogeny directly from gene-order
The MLGO phylogeny is based on the complete gene-order data including duplicated genes, and excluding missing/unannotated genes on a species-by-species basis as appropriate depending on their original genome annotations. The MLGO topology is highly discordant with all the phylogenies inferred from sequence datasets (both BI and ML analysis, and all 4 datasets) (Supplementary Table S6, Fig. 7B). In the MLGO phylogeny Tubulifera renders Terebrantia paraphyletic, as a clade composed of Aeolothripidae, Stenurothripidae and subfamily Panchaeothripinae was found to be sister to Tubulifera. Relationships within the remaining Thripidae were both inconsistent with previous taxonomic classifications (i.e. Thripinae was paraphyletic) and with the sequence-based phylogeny. While the clade Anaphothrips + Dendrothrips and genus-level monophyly of Thrips, Frankliniella and Scirtothrips was supported by both gene-order and sequence based phylogenies, relationships between the groups varied greatly between the data types. Broadly speaking the MLGO phylogeny appears to group taxa by the extent of gene rearrangements rather than shared gene orders. For instance, the clade of Tubulifera, Aeolothripidae, Stenurothripidae and Panchaeothripinae includes all the taxa with the most divergent thrips mitochondrial genomes, whereas the other clade composed of Thripidae (excluding Panchaeothripinae) have broadly similar gene orders (c.f. Fig. 7A).
Discussion
The additional mitochondrial genomes sequenced from thrips for this study greatly extend our understanding of their evolution within Thysanoptera. All but one of the previously available genomes, and all published analyses of thrips mitochondrial genomes, have been confined to the family Thripidae, the second-most speciose thrips family and which includes the most agricultural pest species12. In expanding the taxonomic scale of available thrips mitochondrial genomes (three additional families, one additional thripid subfamily) we have greatly expanded our understanding of the evolutionary dynamics of the mitochondrial genome within the order and have enhanced our knowledge of the thrips phylogeny.
Evolution of mitochondrial genome architectures in thrips
The additional species sequenced in the present study demonstrate the absence of a predictable taxonomic scale for the evolution of mitochondrial gene order and genome architecture in Thysanoptera. Gene order is identical between members of two different families (Stenurothripidae and Panchaeothripinae), yet differs between congeneric species (e.g. T. imaginis vs. T. palmi and F. intonsa vs. F. occidentalis). Similarly, some derived mitochondrial genome structures are conserved across large clades within thrips, while other derived architectures differ between populations within a single species. For example, multiple CRs, which are otherwise rare within insects1, are found in all members of the clade comprising most of the thripine genera plus Neohydatothrips, whereas genome fragmentation varies between populations of Scirtothrips dorsalis17. The taxonomic scale of derived mitochondrial genomic features observed in thrips thus cannot be assumed based on limited sampling. For example, our additional sampling revealed that genomic features previously ascribed to the order Thysanoptera, such as multiple CRs being typical for the order16,20, are rather only features of the family Thripidae. Although we are able to identify new trends in mitochondrial genomic evolution in thrips, and refine our understanding of other trends on the basis of extra sampling, considerable additional study is required to verify these proposals.
Expanded sampling supports earlier proposals that tRNAs are subject to higher rates of evolutionary change than are observed in either the PCGs or the rRNAs, including gene duplication, loss, secondary structure variation, anti-codon mutations and rearrangements. Duplicated tRNAs have now been identified from multiple, distantly related thrips species, including representatives of both suborders (Haplothrips in Tubulifera and Thrips imaginis in Terebrantia). These duplicated tRNAs include both examples where duplicate tRNAs are sequence identical (trnM in Haplothrips) and ones which show significant sequence divergence (trnS1 and trnE in T. imaginis). Across insects, sequence identical tRNA duplications are more common, typically in the form of tandem-repeats (e.g. in Hymenoptera62). However, the example in Haplothrips is not a tandem-repeat (trnV separates the two copies). Both sequence-identical and diverged duplicate copies of genes are predicted intermediary products of the tandem-duplication/random-loss (TDRL) model of gene rearrangements (being present between the duplication step and later complete loss of one of the gene copies)63, however they are rarely observed in insects relative to completed rearrangements1. Indeed, within thrips multiple, almost complete genome length, TDRL events were inferred from the CREx analysis, with 90 derived gene-boundaries (most of which involve tRNA rearrangements) found by comparative genome mapping, yet duplicated tRNAs were found in just two species. This suggests that even in genomically ‘active’ groups such as thrips, TDRL events must resolve quite rapidly in evolutionary time for us to observe so few species with intermediate TDRL products such as duplicate genes. Similar conclusions have been drawn from analyses of Hymenoptera, another insect order with rapid rates of tRNA rearrangement64.
Similarly, expanded taxonomic sampling sheds further light on the phenomena of multiple control regions (CRs) in thrips. Multiple CRs are a rare feature within insect mitochondrial genomes with the majority of examples coming from taxa with fragmented genomes such as lice65, where each chromosome has one CR. Multiple CRs within a single mitochondrial chromosome, as in thrips, are very rare in insects or other arthropods (e.g. ticks66) but somewhat more commonin vertebrates, especially birds67. Previous authors have proposed that the presence of multiple CRs in thrips may increase the rate of gene rearrangement18. The expanded sampling in the present study suggests that this is not the case. Within Thripidae, there is a limited degree of rearrangement between species with a single CR (Rhipiphorothrips, Anaphothrips and Dendrothrips) and those in the main ‘Thripinae’ clade (including Sericothripinae but excluding Anaphothrips), all of whose members have multiple CRs (several tRNA genes and the synapomorphic translocation of nad3 to between cox1 and cox2 in the later clade). Conversely, there are few rearrangements between congeneric species which both possess multiple CRs (e.g. Thrips and Frankliniella), while in Scirtothrips while the two studied population possesses a duplicate CR in different locations in the mitochondrial genome, they differ by no other gene rearrangements17. Taken together these features suggest that the interaction between CR duplication and gene rearrangement is not causal. At best CR duplication is likely part of large TDRL events (such as that which translocated nad3 in the main ‘Thripinae’ clade), not a genomic feature which could drive ongoing rearrangement once introduced into a genome18. Thrips species with multiple CRs vary widely in the degree of sequence conservation between CR copies, from very high sequence identities between CRs in Thrips and Frankliniella spp. (>90%) to as low as 10% identity in Franklinothrips. Concerted evolution, via gene conversion or selection, has been proposed as the process by which high sequence identity is maintained between duplicate CR regions68,69. Given the variation between thrips species in the apparent fidelity of concerted evolution between duplicate CR regions, this group could be a useful model system for examining these phenomena in mitochondrial genomes.
Phylogeny of the thysanoptera
Phylogenetic inference using PCGs demonstrated significant resolving power of this data source for deep-level questions within the order Thysanoptera. Results were largely insensitive to data noise (in the form of third codon positions, or the inconsistently aligned sites masked by GBlocks) and to inference method (ML vs BI) at the levels of family interrelationships and between thripid subfamilies. Genus-level relationships within the non-monophyletic Thripinae, however, were much more variable between datasets suggesting sensitivity to data noise at these levels. This is comparable to many other insect orders in that deep-level (e.g. families/superfamily) relationships are seemingly robust to analytical decisions such as taxon selection, data inclusion/exclusion or alignment method, while shallow-level relationships show differing degrees of sensitivity64,70–74. The root cause of these sensitivities cannot be determined at this time, as the ‘true’ phylogeny of thrips is not yet known to compare individual analyses against. In those insect orders for which robust, independent estimates of ordinal phylogeny exist, there is inconsistency as to whether including potentially noisy regions of the mitochondrial genome (such as third codon positions) results in greater or lesser congruence between the mitochondrial topology and the nuclear and/or morphological ones. For example, Diptera71 and Hymenoptera72 trees appear to be less accurate when third codon positions are included, while topological accuracy in Isoptera is improved74,75, and in other orders such as Psocoptera54 and Lepidoptera76 topology is the same regardless of their inclusion or exclusion. Integration of mitochondrial genomic data with ongoing efforts to understand thrips evolution from morphological77,78 and nuclear genomic79 perspectives will help to highlight potential sources of bias in mitochondrial genomes as a data source.
The thrips phylogeny inferred using sequence data for mitochondrial PCGs for 14 species compares well with previous multi-locus phylogenies at the level of family, but is quite incompatible at the level of subfamily or genus. Buckman et al.25 analyzed five genes (including one mitochondrial gene), and in two of their three analyses (ML and BI), found the same consensus interfamily relationships as found here from the majority of datasets (i.e. Fig. 4). The position of Stenurothripidae differs in the minority result from both the present study (Thripidae + (Stenurothripidae + Aeolothripidae), found here in the ML2 and ML4 datasets (Supplementary Figs. S5 and S6), versus Stenurotrhipidae + (Thripidae + Aeolothripidae) in Buckman et al.’s25 Maximum Parsimony analysis. Despite finding the same consensus topology as here (i.e. Aeolothripidae + (Stenurothripidae + Thripidae), nodal support in Buckman et al.26 was generally low for interfamily nodes, with only their Bayesian analysis finding statistically significant support. In contrast, support for interfamily nodes in the present study are generally high (100% bootstrap support or 1.0 posterior probabilities), except for the node grouping Stenurothripidae with Thripidae. Both studies include a single representative of this family, a Holarthrothrips spp. in both cases, and while this family is quite small (just 6 species globally12), this instability in family resolution suggests that additional targeted sampling of the Stenurothripidae would be valuable in definitively resolving interfamily relationships within Thysanoptera.
In contrast, subfamily and genus-level relationships within the Thripidae are widely inconsistent across/among the present mitochondrial-genome based analyses, multi-locus analysis25 and morphology-based phylogeny of Thripidae78. Both our consensus topology (Fig. 4) and the alternative resolutions within Thripidae found in a minority of datasets differed significantly from these previous studies. The most striking difference is our consistent finding of Panchaetothripinae as the sister of the remaining Thripidae in all datasets and analyses. In contrast, both the multi-locus and morphological analyses resulted Panchaetothripinae to be nested well within Thripinae in a quite derived position within their respective trees25,78. Although the panchaetothripine representative used here, Rhipiphorothrips, was not amongst the taxa used in multi-locus analysis25, both it and all the taxa in the later study were included in morphology based analysis78 which found strong support for the monophyly of the subfamily. Mound & Morris (2007)80 found equivocal support for the placement of Panchaetothripinae (sister to the rest of the family in some analyses, derived within Thripidae in others), but more recent papers have been consistent in finding a derived position for the subfamily. The present study marks the first strong molecular evidence for the placement as sister to the rest of Thripidae. The sister group relationship between Thrips and Frankliniella (supported here by analyses BI-1, 2, 4 and ML-3, 4) is supported by morphology tree78, but was strongly rejected by the multi-locus study25, with the two genera consistently placed in different major clades within Thripidae. Morphological analyses suggest that the two genera are not particularly closely related, and the sister-grouping in the present study is likely due to the greatly reduced taxon sampling relative to Zhang et al.78. Considerable additional sampling is needed to resolve the relationship of these two genera which include the bulk of pest thrips species. The only consistent relationship found between the three studies is the sister-grouping of Neohydatothrips and Scirtothrips which has been suggested previously based on morphological similarities81, and was further supported in a recent morphological phylogeny of the Scirtothrips genus-group77. Overall, the variation in genus-level relationships found between studies that differ in taxon selection and data source, points to the difficulty in definitively resolving relationships within the Thripidae. Given the size of this family (300 genera and over 2100 species), its importance as pests, and our understanding of the evolution of feeding behaviours in thrips78, considerable additional thripid sampling is needed, as the use of exemplar taxa as surrogates for monophyletic higher-level groups (e.g. subfamilies or genus-groups) will be problematic.
Genome rearrangements in thrips
The current study provides additional evidence that Thysanoptera is an insect order with heightened rates of mitochondrial genome rearrangement, consistent with Cameron’s hypothesis that haplodiploidy is a predisposing factor to genome rearrangements1. The four newly sequenced thrips species display three novel gene orders relative to other thrips, including the first instance of a gene order conserved over deeper evolutionary history, between representatives of the families Stenurothripidae and Thripidae (Holarthrothrips and Rhipiphorothrips respectively). Previous studies had shown that mitochondrial gene order varied between even different species of the genus14,18, so conserved gene orders over this scale was unexpected. The majority of genes in all thrips sequenced to date are rearranged relative to the inferred ancestral insect mitochondrial genome with only 14 of the 37 gene boundaries conserved in any of the thrips species, and the majority of the conserved gene blocks (Fig. 6) lost in some or all taxa. Indeed, of the eight conserved gene blocks identified, only block B (atp8-atp6) comes close to being universally conserved within thrips, being present in all species except Neohydatothrips (where atp8 is inverted but not translocated). Conversely, through mapping derived gene boundaries we were able to identify several that are synapomorphic for major clades within thrips and that provide supporting evidence for the consensus topology (Fig. 4). For example, trnW-nad1 (derived boundary #17) is synapomorphic for Stenurothripidae + Thripidae, a relationship which received equivocal support in prior molecular phylogenies of the order (Buckman et al., 2013), and which was sensitive to the inclusion of third codon positions in the current study. Similarly, three derived boundaries, trnG-trnK (#6), trnK-cox3 (#7), and trnY-nad2 (#16), were synapomorphic for the monophyly of Thripidae excluding Panchaetothripinae, another relationship which was not supported in prior molecular25 or morphological analyses78. Tubulifera is supported by seven derived gene boundaries (Fig. 5; #61 is homoplastic, 66–71 are synapomorphic), including two derived gene blocks, nad1-cox1-trnQ-cox2 and trnG-trnD-rrnS, despite otherwise quite dissimilar gene arrangements (c.f. Fig. 5). Although gene rearrangements in thrips are relatively noisy (i.e., 90 unique derived gene boundaries vs 71 shared vs 24 apparently synapomorphic ones), they do provide additional evidence for clade monophyly and can complement sequence-based analyses, thus increasing our confidence in clades which are not consistently recovered between different studies or for which nodal support is weak.
As in other insect orders, the majority of rearrangements involve tRNAs (Fig. 5) adding further evidence for the selective neutrality of tRNA position within the mitochondrial genome64. As a consequence of the scale of tRNA positional differences between thrips mitochondrial genomes, CREx inference of the evolutionary events underlying these genome rearrangements consistently inferred multiple TDRL events encompassing duplications of major portions of the genome (Supplementary Figs. S7 and S8). This software has similarly inferred high numbers of large-scale TDRLs in other insect groups with high rates of tRNA rearrangement such as Psocoptera54 and Hymenoptera7, suggesting that it algorithmically favours TDRL events over other inferred classes of gene rearrangements. Noise from tRNA rearrangements (there are likely multiple tRNA rearrangements along each branch, analogous to the ‘multiple-hits’ problem with third-codon positions82), combined with the presence of duplicated tRNAs in some species and the absence of a tRNA gene from Gynaikothrips, made the inference of ancestral genomes for key clades within thrips computationally intractable with TreeREx (which has the same core algorithm as CREx). By limiting our ancestral genome analysis to just the major genes (PCGs and rRNAs) we were, however, able to reconstruct rearrangement of these larger, less ‘mobile’ genes. Removing tRNAs from ancestral genome reconstruction has been useful in understanding the major genome evolutionary events within Metazoa34, as their higher relative rates of rearrangement obscured the fundamentally conserved nature of gene arrangement across taxa as deep as superphyla. tRNA removal is similarly effective in thrips, allowing the identification of major rearrangements in the common ancestors of major clades such as Terebrantia, Stenurothripidae + Thripidae and ‘core’ Thripinae (including Neohydatothrips).
Direct use of gene arrangement data in phylogenetic inference using MLGO proved unsuccessful likely due of the extremely high rates of tRNA rearrangements in thrips as discussed above. The overall topology differed significantly from all the trees produced in the present study, and from previous molecular phylogenies of the order25,78, most notably in the non-monophyly of Terebrantia and Thripidae. Even considering gene-rearrangement data in isolation, clades that were supported by unambiguously synapomorphic rearrangements, including Scirtothrips + Neohydatothrips, Stenurothripidae + Thripidae and Thripidae excluding Panchaetothripidae, were not recovered by the MLGO analysis. Examination of novel gene boundaries (Fig. 5) clearly shows that there are large numbers of derived gene-boundaries that are either homoplastic or have been secondarily lost in one or more thrips lineages (47 of 71 derived boundaries). These, plus the high number of unique gene boundaries (90 found in just once in thrips), suggest that MLGO may be vulnerable to ‘long-branch’ type effects83. The two main clades that were inferred, Thripidae (except Rhipiphorothrips) in one and the remaining thrips species in the other, roughly correspond to the scale of total rearrangements (higher in the first clade), rather than adequately modelling phylogenetically informative versus uninformative rearrangements. Indeed, the only two thrips species to share identical gene orders (Holarthrothrips and Rhipiphorothrips) are strongly grouped as a clade, despite every other line of phylogenetic evidence suggesting that they are distantly related (morphology, multilocus and mitochondrial genome phylogenies). Properly modelling symplesiomorphic gene arrangements (as the absence of rearrangements between these species can be regarded) will likely always prove challenging given the overall low total number of characters provided by the mitochondrial genome (only 37 genes plus CR). Further exploration of MLGO and other methods of direct phylogenetic inference from gene-order data, however, will improve our understanding of how these methods work with empirical data. Further data from thrips would contribute to those explorations, especially for testing utility at finer taxonomic scales such as within families or subfamilies.
Supplementary information
Acknowledgements
The authors are thankful to the Director of Zoological Survey of India (ZSI), Ministry of Environment, Forests and Climate Change (MoEFCC), Govt. of India for providing necessary permissions and facilities. This work was financially supported by Zoological Survey of India (ZSI) in-house project, ‘National Faunal Genome Resources (NFGR)’ to V.K. and K.C. This study was supported by SERB funded project “Delimiting Species Boundaries in Pest and Vector thrips. (Thysanoptera: Thripidae) from India” to V.K. and K.T. and MoEFCC funded AICOPTAX Project “Taxonomic studies on the Tubulifera (Insecta: Thysanoptera) of India” to V.K. This work is a part of the Ph. D thesis of the RC.
Author contributions
Conceptualization: Kaomud Tyagi, Vikas Kumar; Data curation: Rajasree Chakraborty, Kaomud Tyagi; Formal analysis: Kaomud Tyagi, Vikas Kumar, Rajasree Chakraborty; Funding acquisition: Kailash Chandra, Vikas Kumar; Investigation: Kaomud Tyagi, Vikas Kumar; Methodology: Kaomud Tyagi, Vikas Kumar, Stephen L. Cameron, Rajasree Chakraborty; Project administration: Kailash Chandra, Vikas Kumar; Resources: Kailash Chandra, Vikas Kumar; Software: Kaomud Tyagi, Vikas Kumar, Rajasree Chakraborty, Andrew D. Sweet; Supervision: Vikas Kumar, Stephen L. Cameron, Kailash Chandra; Validation: Kaomud Tyagi, Vikas Kumar; Visualization: Vikas Kumar, Kaomud Tyagi; Writing: Kaomud Tyagi, Vikas Kumar, Stephen L. Cameron.
Data availability
Annotated mitochondrial genome assemblies are deposited in NCBI GenBank under the following accession numbers: F. vespiformis (MN072395), H. indicus (MN072397), R. cruentatus (MN072396), G. uzeli (MK940484).
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
is available for this paper at 10.1038/s41598-020-57705-4.
References
- 1.Cameron SL. Insect mitochondrial genomics: implications for evolution and phylogeny. Ann. Rev. Entomol. 2014;59:95–117. doi: 10.1146/annurev-ento-011613-162007. [DOI] [PubMed] [Google Scholar]
- 2.Li T, et al. A Mitochondrial Genome of Rhyparochromidae (Hemiptera: Heteroptera) and a Comparative Analysis of Related Mitochondrial Genomes. Sci. Rep. 2016;6:35175. doi: 10.1038/srep35175. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Song F, et al. Capturing the phylogeny of Holometabola with mitochondrial genome data and Bayesian Site-Heterogeneous Mixture Models. Genome Biol. Evol. 2016;8:1411–1426. doi: 10.1093/gbe/evw086. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Singh D, et al. The mitochondrial genome of Muga silkworm (Antheraea assamensis) and its comparative analysis with other lepidopteran insects. PLoS One. 2017;12:e0188077. doi: 10.1371/journal.pone.0188077. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Wolstenholme DR. Animal mitochondrial DNA: structure and evolution. Int. Rev. Cytol. 1992;141:173–216. doi: 10.1016/S0074-7696(08)62066-5. [DOI] [PubMed] [Google Scholar]
- 6.Cameron SL, Johnson KP, Whiting MF. The mitochondrial genome of the screamer louse Bothriometopus (Phthiraptera: Ischnocera): effects of extensive gene rearrangements on the evolution of the genome. J. Mol. Evol. 2007;65:589–604. doi: 10.1007/s00239-007-9042-8. [DOI] [PubMed] [Google Scholar]
- 7.Chen L, et al. Extensive gene rearrangements in the mitochondrial genomes of two egg parasitoids Trichogramma japonicum and Trichogramma ostriniae (Hymenoptera: Chalcidoidea: Trichogrammatidae) Sci. Rep. 2018;8:7034. doi: 10.1038/s41598-018-25338-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Ye F, Lan X, Zhu WB, You P. Mitochondrial genomes of praying mantises (Dictyoptera Mantodea): rearrangement duplication and reassignment of tRNA genes. Sci. Rep. 2016;6:25634. doi: 10.1038/srep25634. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Clary DO, Wolstenholme DR. The mitochondrial DNA molecular of Drosophila yakuba: nucleotide sequence gene organization and genetic code. J. Mol. Evol. 1985;22:252–271. doi: 10.1007/BF02099755. [DOI] [PubMed] [Google Scholar]
- 10.Boore JL, Lavrov DV, Brown WM. Gene translocation links insects and crustaceans. Nature. 1998;392:667–668. doi: 10.1038/33577. [DOI] [PubMed] [Google Scholar]
- 11.Dowton M, Castro LR, Austin AD. Mitochondrial gene rearrangements as phylogenetic characters in the invertebrates: The examination of genome “morphology”. Invertebr. Syst. 2002;16:345–356. doi: 10.1071/IS02003. [DOI] [Google Scholar]
- 12.ThripsWiki, ThripsWiki - providing information on the World’s thrips. Available from, http://thrips.info/wiki/. (Accessed 15 October 2018).
- 13.Mound LA, Heming BS, Palmer JM. Phylogenetic relationships between the families of recent Thysanoptera. Zool. J. Linn. Soc. London. 1980;69:111–141. doi: 10.1111/j.1096-3642.1980.tb01934.x. [DOI] [Google Scholar]
- 14.Hangrui L, et al. Novel insights into mitochondrial gene rearrangement in thrips (Insecta: Thysanoptera) from the grass thrips Anaphothrips obscurus. Sci. Rep. 2017;7:4284. doi: 10.1038/s41598-017-04617-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Yan D, et al. The mitochondrial genome of Frankliniella intonsa: insights into the evolution of mitochondrial genomes at lower taxonomic levels in Thysanoptera. Genomics. 2014;104:306–312. doi: 10.1016/j.ygeno.2014.08.003. [DOI] [PubMed] [Google Scholar]
- 16.Yan D, et al. The complete mitochondrial genome sequence of the western flower thrips Frankliniella occidentalis (Thysanoptera: Thripidae) contains triplicate putative control regions. Gene. 2012;506:117–124. doi: 10.1016/j.gene.2012.06.022. [DOI] [PubMed] [Google Scholar]
- 17.Dickey AM, et al. A novel mitochondrial genome architecture in thrips (Insecta: Thysanoptera): extreme size asymmetry among chromosomes and possible recent control region duplication. BMC Genomics. 2015;16:439. doi: 10.1186/s12864-015-1672-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Shao R, Barker SC. The highly rearranged mitochondrial genome of the plague thrips Thrips imaginis (Insecta: Thysanoptera): convergence of two novel gene boundaries and an extraordinary arrangement of rRNA genes. Mol. Biol. Evol. 2003;20:362–370. doi: 10.1093/molbev/msg045. [DOI] [PubMed] [Google Scholar]
- 19.Chakraborty R, et al. The complete mitochondrial genome of Melon thrips Thrips palmi (Thripinae): comparative analysis. PLoS One. 2018;13:e0199404. doi: 10.1371/journal.pone.0199404. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Chen SC, et al. The complete mitochondrial genome of the stick tea thrips Dendrothrips minowai (Thysanoptera: Thripidae) Mitochondrial DNA Part B. 2018;1:58–59. doi: 10.1080/23802359.2017.1419099. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Kumar V, et al. The first complete mitochondrial genome of marigold pest thrips Neohydatothrips samayunkur (Sericothripinae) and comparative analysis. Sci. Rep. 2019;9:151. doi: 10.1038/s41598-018-36379-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Bhatti JS. The orders Terebrantia and Tubulifera of the superorder Thysanoptera (Insecta), A Critical Appraisal. Zoology. Journal of Pure and Applied Zoology) 1988;1:167–240. [Google Scholar]
- 23.Bhatti JS. The Order Tubulifera (Insecta): Its characters and classification into families, Zoology. Journal of Pure and Applied Zoology) 1992;3:127–162. [Google Scholar]
- 24.Bhatti JS. The classification of Terebrantia (Insecta) into families. Orient. Ins. 2006;40:339–375. doi: 10.1080/00305316.2006.10417487. [DOI] [Google Scholar]
- 25.Buckman RS, Mound LA, Whiting MF. Phylogeny of thrips (Insecta: Thysanoptera) based on five molecular loci. Syst. Entomol. 2013;38:123–133. doi: 10.1111/j.1365-3113.2012.00650.x. [DOI] [Google Scholar]
- 26.Wilson TH. A monograph of the subfamily Panchaetothripinae (Thysanoptera: Thripidae) Memoirs of the American Entomological Institute. 1975;23:1–354. [Google Scholar]
- 27.Bhatti JS, Ananthakrishnan TN. Studies in some Indian Thysanoptera. Entomon. 1978;3:229–238. [Google Scholar]
- 28.Ananthakrishnan TN, Sen S. Taxonomy of Indian Thysanoptera. Zoological Survey of India (Handbook Series) 1980;1:1–234. [Google Scholar]
- 29.Bhatti JS. A new species of Holarthrothrips from Iraq with notes on host plants and key to species along with clarification of the position of this genus among Thysanoptera. Zoology (Journal of Pure and Applied Zoology) 1986;1:1–33. [Google Scholar]
- 30.Mound LA, Reynaud P. Franklinothrips; a pantropical Thysanoptera genus of ant-mimicking obligate predators (Aeolothripidae) Zootaxa. 2005;864:1–16. doi: 10.11646/zootaxa.864.1.1. [DOI] [Google Scholar]
- 31.Patel RK, Jain M. NGS QC Toolkit: A toolkit for quality control of next generation sequencing data. PLoS One. 2012;7:e30619. doi: 10.1371/journal.pone.0030619. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25:1754–1760. doi: 10.1093/bioinformatics/btp324. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Bankevich A, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 2012;19:455–477. doi: 10.1089/cmb.2012.0021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Bernt M, et al. MITOS: Improved de novo metazoan mitochondrial genome annotation. Mol. Phylogenet. Evol. 2013;69:352–364. doi: 10.1016/j.ympev.2013.05.002. [DOI] [PubMed] [Google Scholar]
- 35.Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. GenBank. Nucleic. Acids. Res. 2005;33:D34–D38. doi: 10.1093/nar/gki063. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: Molecular Evolutionary Genetics Analysis across computing platforms. Mol. Biol. Evol. 2018;35:1547–1549. doi: 10.1093/molbev/msy096. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic. Acids. Res. 1997;25:955–964. doi: 10.1093/nar/25.5.955. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Laslett D, Canbäck B. ARWEN a program to detect tRNA genes in metazoan mitochondrial nucleotide sequences. Bioinformatics. 2008;24:172–175. doi: 10.1093/bioinformatics/btm573. [DOI] [PubMed] [Google Scholar]
- 39.Zuker M. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic. Acids. Res. 2003;31:3406–3415. doi: 10.1093/nar/gkg595. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Thompson, J. D., Gibson, T. J., & Higgins, D. G. Multiple Sequence Alignment Using ClustalW and ClustalX. Current Protocols in Bioinformatics 2.3.1–2.3.22. pmid: 18792934 354 (2002). [DOI] [PubMed]
- 41.Benson. G. Tandem repeats finder: A program to analyze DNA sequences. Nucleic. Acids. Res. 1999;27:573–580. doi: 10.1093/nar/27.2.573. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Li H, et al. The complete mitochondrial genome of the damsel bug Alloeorhynchus bakeri (Hemiptera: Nabidae) Int. J. Biol. Sci. 2012;8:93–107. doi: 10.7150/ijbs.8.93. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Johnson KP, et al. Phylogenomics and the evolution of hemipteroid insects. Proc. Natl. Acad. Sci. USA. 2018;115:12775–12780. doi: 10.1073/pnas.1815820115. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Abascal F, Zardoya R, Telford MJ. TranslatorX: multiple alignment of nucleotide sequences guided by amino acid translations. Nucleic Acids Res. 2010;38:W7–W13. doi: 10.1093/nar/gkq291. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol. Biol. Evol. 2000;17:540–552. doi: 10.1093/oxfordjournals.molbev.a026334. [DOI] [PubMed] [Google Scholar]
- 46.Vaidya, G, Lohman, D. J. & Meier, R. SequenceMatrix: concatenation software for the fast assembly of multi-gene datasets with character set and codon information. Cladistics. 27, 171–180 (2011). [DOI] [PubMed]
- 47.Lanfear R, Frandsen PB, Wright AM, Senfeld T, Calcott B. PartitionFinder 2: new methods for selecting partitioned models of evolution for molecular and morphological phylogenetic analyses. Mol. Biol. Evol. 2017;34:772–773. doi: 10.1093/molbev/msw260. [DOI] [PubMed] [Google Scholar]
- 48.Miller, M. A., Pfeiffer, W., & Schwartz, T. “Creating the CIPRES Science Gateway for inference of large phylogenetic trees” in Proceedings of the Gateway Computing Environments Workshop (GCE) 14 Nov. 2010 New Orleans LA pp 1–8 (2010).
- 49.Ronquist F, et al. MRBAYES 3.2: Efficient Bayesian phylogenetic inference and model selection across a large model space. Syst. Biol. 2012;61:539–542. doi: 10.1093/sysbio/sys029. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Nguyen LT, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum likelihood phylogenies. Mol. Biol. Evol. 2015;32:268–274. doi: 10.1093/molbev/msu300. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Hoang DT, Chernomor O, von Haeseler A, Minh BQ, Vinh LS. UFBoot2: Improving the ultrafast bootstrap approximation. Mol. Biol. Evol. 2017;35:512–528. doi: 10.1093/molbev/msx281. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Rambaut, A. FigTree. Version 1.4.2 Institute of Evolutionary Biology, University of Edinburgh, Edinburgh (2014).
- 53.Wang Y, Chen J, Jiang LY, Qiao GX. Hemipteran Mitochondrial Genomes: Features, Structures. Int. J. Mol. Sci. 2015;16:12382–12404. doi: 10.3390/ijms160612382. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Yoshizawa K, et al. Mitochondrial phylogenomics and genome rearrangements in the barklice (Insecta: Psocodea) Mol. Phylogenet. Evol. 2018;119:118–127. doi: 10.1016/j.ympev.2017.10.014. [DOI] [PubMed] [Google Scholar]
- 55.Bernt M, et al. CREx: Inferring Genomic Rearrangements Based on Common Intervals. Bioinformatics. 2007;23:2957–2958. doi: 10.1093/bioinformatics/btm468. [DOI] [PubMed] [Google Scholar]
- 56.Bernt, M., Merkle, D. & Middendorf, M. An Algorithm for Inferring Mitochondrial Genome Rearrangements in a Phylogenetic Tree. Comparative Genomics International Workshop, RECOMB-CG 2008, 5267 Lecture Notes in Bioinformatics (LNBI), 143–157 (2008).
- 57.Hu F, Lin Y, Tang J. MLGO: phylogeny reconstruction and ancestral inference from gene-order data. BMC Bioinformatics. 2014;15:354. doi: 10.1186/s12859-014-0354-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Cameron SL. How to sequence and annotate insect mitochondrial genomes for systematic and comparative genomics research. Syst. Entomol. 2014;39:400–411. doi: 10.1111/syen.12071. [DOI] [Google Scholar]
- 59.Zhang DX, Hewitt GM. Insect mitochondrial control region: a review of its structure evolution and usefulness in evolutionary studies. Biochem. Syst. Ecol. 1997;25:99–120. doi: 10.1016/S0305-1978(96)00042-7. [DOI] [Google Scholar]
- 60.Hassanin A, Leger N, Deutsch J. Evidence for multiple reversals of asymmetric mutational constraints during the evolution of the mitochondrial genome of Metazoa and consequences for phylogenetic inferences. Syst. Biol. 2005;54:277–298. doi: 10.1080/10635150590947843. [DOI] [PubMed] [Google Scholar]
- 61.Hassanin A. Phylogeny of Arthropoda inferred from mitochondrial sequences: strategies for limiting the misleading effects of multiple changes in pattern and rates of substitution. Mol. Phylogenet. Evol. 2006;38:100–116. doi: 10.1016/j.ympev.2005.09.012. [DOI] [PubMed] [Google Scholar]
- 62.Cameron SL, et al. Mitochondrial genome organization and phylogeny of two vespid wasps. Genome. 2008;51:800–808. doi: 10.1139/G08-066. [DOI] [PubMed] [Google Scholar]
- 63.Boore Jeffrey L. Comparative Genomics. Dordrecht: Springer Netherlands; 2000. The Duplication/Random Loss Model for Gene Rearrangement Exemplified by Mitochondrial Genomes of Deuterostome Animals; pp. 133–147. [Google Scholar]
- 64.Dowton M, Cameron SL, Dowavic JI, Austin AD, Whiting MF. Characterisation of 67 mitochondrial gene rearrangements in the Hymenoptera suggests that mitochondrial tRNA gene position is selectively neutral. Mol. Phylogenet. Evol. 2009;26:1607–1617. doi: 10.1093/molbev/msp072. [DOI] [PubMed] [Google Scholar]
- 65.Song F, et al. Mitochondrial Genome Fragmentation Unites the Parasitic Lice of Eutherian Mammals. Syst. Biol. 2019;68:430–44. doi: 10.1093/sysbio/syy062. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Shao R, Barker SC, Mitani H, Aoki Y, Fukunaga M. Evolution of Duplicate Control Regions in the Mitochondrial Genomes of Metazoa: A Case Study with Australasian Ixodes Ticks. Mol. Phylogenet. Evol. 2004;22:620–629. doi: 10.1093/molbev/msi047. [DOI] [PubMed] [Google Scholar]
- 67.Schirtzinger EE, et al. Multiple independent origins of mitochondrial control region duplications in the order Psittaciformes. Mol. Phylogenet. Evol. 2012;64:342–356. doi: 10.1016/j.ympev.2012.04.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Kumazawa Y, Ota H, Nishida M, Ozawa T. Gene rearrangements in snake mitochondrial genomes: highly concerted evolution of control-region-like sequences duplicated and inserted into a tRNA gene cluster. Mol. Biol. Evol. 1996;13:1242–1254. doi: 10.1093/oxfordjournals.molbev.a025690. [DOI] [PubMed] [Google Scholar]
- 69.Eberhard JR, Wright TF. Rearrangement and evolution of mitochondrial genomes in parrots. Mol. Phy. Evol. 2016;94:34–36. doi: 10.1016/j.ympev.2015.08.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70.Dowton M, Cameron SL, Austin AD, Whiting MF. Phylogenetic approaches for the analysis of mitochondrial genome sequence data in the Hymenoptera – a lineage with both rapidly and slowly evolving mitochondrial genomes. Mol. Phylogenet. Evol. 2009;52:512–519. doi: 10.1016/j.ympev.2009.04.001. [DOI] [PubMed] [Google Scholar]
- 71.Ding SM, et al. The phylogeny and evolutionary timescale of Muscoidea (Diptera: Brachycera: Calyptratae) inferred from mitochondrial genomes. PLoS One. 2015;10:e0134170. doi: 10.1371/journal.pone.0134170. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72.Mao M, Gibson T, Dowton M. Higher-level phylogeny of the Hymenoptera inferred from mitochondrial genomes. Mol. Phylogenet. Evol. 2015;84:34–43. doi: 10.1016/j.ympev.2014.12.009. [DOI] [PubMed] [Google Scholar]
- 73.Li XK, et al. Mitochondrial genomes provide insights into the phylogeny of Lauxanioidea (Diptera: Cyclorrhapha) Int. J. Mol. Sci. 2017;18:773. doi: 10.3390/ijms18040773. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 74.Cameron SL, Lo N, Bourguignon T, Svenson GJ, Evans TA. A mitochondrial genome phylogeny of termites (Insecta: Termitoidae): Robust support for interfamilial relationships and molecular synapomorphies define major clades. Mol. Phylogenet. Evol. 2012;65:163–173. doi: 10.1016/j.ympev.2012.05.034. [DOI] [PubMed] [Google Scholar]
- 75.Bourguignon T, et al. Mitochondrial Phylogenomics Resolves the Global Spread of Higher Termites Ecosystem Engineers of the Tropics. Mol. Biol. Evol. 2016;34:589–597. doi: 10.1093/molbev/msw253. [DOI] [PubMed] [Google Scholar]
- 76.Yang XX, Cameron SL, Lees DC, Xue DY, Han HX. A mitochondrial genome phylogeny of owlet moths (Lepidoptera: Noctuoidea) and examination of the utility of mitochondrial genomes for lepidopteran phylogenetics. Mol. Phylogenet. Evol. 2015;85:230–237. doi: 10.1016/j.ympev.2015.02.005. [DOI] [PubMed] [Google Scholar]
- 77.Zhang S, Mound LA, Feng J. Phylogenetic relationships among Scirtothrips species and related genera (Thysanoptera Thripidae) based on morphology. Zool. Anz. 2019;280:1–13. doi: 10.1016/j.jcz.2019.02.004. [DOI] [Google Scholar]
- 78.Zhang S, Mound LA, Feng J. Morphological phylogeny of Thripidae (Thysanoptera: Terebrantia) Invertebr. Syst. 2019;33:671–696. [Google Scholar]
- 79.Zhang Z, et al. De novo transcriptome sequencing in Frankliniella occidentalis to identify genes involved in plant virus transmission and insecticide resistance. Genomics. 2013;101:296–305. doi: 10.1016/j.ygeno.2013.02.005. [DOI] [PubMed] [Google Scholar]
- 80.Mound LA, Morris DC. The insect Order Thysanoptera: classification versus systematics. Zootaxa. 2007;1668:395–411. doi: 10.11646/zootaxa.1668.1.21. [DOI] [Google Scholar]
- 81.Lima EFB, Mound LA. Systematic relationships of the Thripidae subfamily Sericothripinae (Insect: Thysanoptera) Zool. Anz. 2016;263:24–32. doi: 10.1016/j.jcz.2016.03.001. [DOI] [Google Scholar]
- 82.Smith JM, Smith NH. Synonymous Nucleotide Divergence: What Is “saturation. Genetics. 1996;142:1033–1036. doi: 10.1093/genetics/142.3.1033. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83.Bergsten J. A review of long-branch attraction. Cladistics. 2005;21:163–193. doi: 10.1111/j.1096-0031.2005.00059.x. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Annotated mitochondrial genome assemblies are deposited in NCBI GenBank under the following accession numbers: F. vespiformis (MN072395), H. indicus (MN072397), R. cruentatus (MN072396), G. uzeli (MK940484).