- Research article
- Open Access
Comparative genomics of the miniature wasp and pest control agent Trichogramma pretiosum
- Amelia R. I. Lindsey1, 2Email author,
- Yogeshwar D. Kelkar3,
- Xin Wu4,
- Dan Sun4,
- Ellen O. Martinson3, 5,
- Zhichao Yan3, 6,
- Paul F. Rugman-Jones1,
- Daniel S. T. Hughes7,
- Shwetha C. Murali7,
- Jiaxin Qu7,
- Shannon Dugan7,
- Sandra L. Lee7,
- Hsu Chao7,
- Huyen Dinh7,
- Yi Han7,
- Harsha Vardhan Doddapaneni7,
- Kim C. Worley7,
- Donna M. Muzny7,
- Gongyin Ye6,
- Richard A. Gibbs7,
- Stephen Richards7,
- Soojin V. Yi4,
- Richard Stouthamer†1Email author and
- John H. Werren†3Email author
© Lindsey et al. 2018
- Received: 15 February 2018
- Accepted: 20 April 2018
- Published: 18 May 2018
Trichogrammatids are minute parasitoid wasps that develop within other insect eggs. They are less than half a millimeter long, smaller than some protozoans. The Trichogrammatidae are one of the earliest branching families of Chalcidoidea: a diverse superfamily of approximately half a million species of parasitoid wasps, proposed to have evolved from a miniaturized ancestor. Trichogramma are frequently used in agriculture, released as biological control agents against major moth and butterfly pests. Additionally, Trichogramma are well known for their symbiotic bacteria that induce asexual reproduction in infected females. Knowledge of the genome sequence of Trichogramma is a major step towards further understanding its biology and potential applications in pest control.
We report the 195-Mb genome sequence of Trichogramma pretiosum and uncover signatures of miniaturization and adaptation in Trichogramma and related parasitoids. Comparative analyses reveal relatively rapid evolution of proteins involved in ribosome biogenesis and function, transcriptional regulation, and ploidy regulation. Chalcids also show loss or especially rapid evolution of 285 gene clusters conserved in other Hymenoptera, including many that are involved in signal transduction and embryonic development. Comparisons between sexual and asexual lineages of Trichogramma pretiosum reveal that there is no strong evidence for genome degradation (e.g., gene loss) in the asexual lineage, although it does contain a lower repeat content than the sexual lineage. Trichogramma shows particularly rapid genome evolution compared to other hymenopterans. We speculate these changes reflect adaptations to miniaturization, and to life as a specialized egg parasitoid.
The genomes of Trichogramma and related parasitoids are a valuable resource for future studies of these diverse and economically important insects, including explorations of parasitoid biology, symbiosis, asexuality, biological control, and the evolution of miniaturization. Understanding the molecular determinants of parasitism can also inform mass rearing of Trichogramma and other parasitoids for biological control.
- Comparative genomics
- Biological control
Trichogramma (Hymenoptera: Trichogrammatidae) wasps are minute polyphagous egg parasitoids used globally for controlling a variety of agricultural insect pests . They are some of the smallest known insects (smaller than the largest protozoans), with adults measuring only tenths of millimeters in length. The family Trichogrammatidae is one of the earliest branching families of the superfamily Chalcidoidea [2, 3] (henceforth referred to as chalcids). This puts Trichogramma in a position to help us more broadly study the evolution of chalcid parasitoids, a diverse and ecologically important insect group. Additionally, many species of Trichogramma contain mixtures of sexual and asexual populations, and in many, asexual reproduction is induced by the endosymbiont Wolbachia [4, 5]. Therefore, Trichogramma is an excellent group to use for investigations of the evolution, ecology, and mechanisms of asexual reproduction.
The transition to a parasitic lifestyle is often associated with reductions in genome size and complexity and the rapid evolution of particular protein families involved in host-parasite interactions [6–9]. Chalcidoidea is a derived group of hymenopteran parasitoids, estimated to contain at least half a million species [10, 11]. The superfamily has undergone rapid speciation since its emergence in the late Jurassic period . Evidence points to the chalcid ancestor being a miniaturized egg parasitoid, with subsequent diversification of the superfamily resulting in lineages that evolved even more miniaturized forms (such as trichogrammatids and mymarids) and those that reverted to a larger body size but maintained many features of the miniaturized ancestor, such as highly reduced wing venation . Miniaturization in insects is associated with a suite of changes, including reduction of the exo- and endoskeleton, compaction of chromatin and reduction of cell size in the nervous system, changes in allometry such as relative head and brain size, and even the loss of organs normally required for respiration and circulation in larger insects [13–17]. It is likely that these major alterations in development and morphology will be reflected in the genome of chalcids, even for those taxa that subsequently increased in size following the adaptive radiation that resulted in their amazing abundance and diversity [2, 3, 12].
Trichogramma are found worldwide with about 180 described species in the genus [18–20], many of which are morphologically indistinguishable from each other and exhibit complex patterns of reproductive compatibility [21–24]. Trichogrammatids have a wide host range and can parasitize insect eggs of several orders . Their size varies depending on the size of the host egg and the number of eggs laid within a host, but the adult wasps are often 0.3–0.4 mm long, with body lengths under 0.2 mm not uncommon [25, 26]. The same genetic line of Trichogramma can produce wasps anywhere from less than 0.2 mm to greater than 0.5 mm long, indicating just how plastic their body size is . This plasticity in size is also seen at the level of the cell: aminergic neuron somata in Trichogramma evanescens range from 1.7 μm in small adults to 4.4 μm in genetically identical large adults . As a result of their small size, Trichogramma have a number of unique morphological features in addition to the aforementioned changes often associated with miniaturization. Trichogramma have the smallest known insect ommatidia (a component of the eye) , a large relative volume of the central nervous system, some of the largest relative measurements of encephalization found in animals (with the brain size being larger than expected for the body size and thus metabolically expensive), and a loss of larval circulatory and respiratory organs [13, 14, 16]. These reductions and simplifications make it challenging to identify them to species based on morphology.
Many populations of Trichogramma are asexual due to infection with parthenogenesis-inducing Wolbachia symbionts [4, 28, 29], and in some cases they have evolved irreversible asexuality due to the loss of sexual function, such as the ability to fertilize eggs [30, 31]. Like all other Hymenoptera, Trichogramma are haplodiploid, where males develop from haploid eggs, and females develop from diploid eggs. In Trichogramma infected with Wolbachia, diploidy is obtained through failed chromatid segregation during the first mitotic division of the egg , resulting in female offspring from unfertilized eggs, rather than from fertilization. The molecular mechanism of this failed chromatid segregation is unknown. Additionally, while diploidization is essential for producing females from unfertilized eggs, it is not sufficient. Diploid male and intersex individuals are produced in appreciable quantities, implicating the importance of epigenetic patterning for complete parthenogenesis induction [33–35], a phenomenon also described for other species of parasitoid wasps infected with parthenogenesis-inducing Wolbachia .
We present the genome sequence of one such asexual, Wolbachia-infected line of Trichogramma pretiosum and a sexual strain of the same species. We use comparative genomics to identify unique features of Trichogramma and chalcid wasp genomes. The asexual Trichogramma pretiosum genome is compared to that of the conspecific sexual line to investigate which features of the reference genome are found across the species and are not unique to the transition to asexuality. Additionally, we sequenced the methylome of the asexual Trichogramma pretiosum line to lay the foundation for future work on the epigenetic effects of parthenogenesis induction. The Trichogramma pretiosum genome provides a foundation for further studies in biological control, host-microbe interactions, and the evolution of parasitism, asexuality, and miniaturization.
Genome statistics and completeness
Genome assembly statistics for an asexual line of Trichogramma pretiosum
Total length of scaffolds
Total ungapped length
Species used in comparative analyses
European honey bee
~ 10 mm 
~ 7 mm 
~ 3 mm 
~ 1 mm 
Braconid parasitoid wasp
~ 4 mm 
~ 2 mm 
Parasitic wood wasp
~ 11 mm 
~ 0.3 mm 
Using the results from OrthoMCL clustering, we estimated the number of genes in the single-copy core clusters, variable-copy number core clusters, dispensable genome clusters (present in two to seven species), species-specific clusters, and singleton genes for each taxon (Fig. 2b). The core, single-copy set of orthologs was 1311 clusters for Hymenoptera (yellow bars in Fig. 2b) and 3492 gene clusters for the chalcids, 100 of which were unique to the chalcid clade. When copy number was not considered, the core gene set of all the hymenopteran species was composed of 5204 gene clusters, with 6382 clusters for chalcids, 159 of which were unique to chalcids. Chalcid-specific gene family clusters were overrepresented for 12 Gene Ontology (GO) terms, including functions related to cellular organization as well as perception of and response to stimuli, which may relate to the evolution of smaller size and potentially host-seeking behaviors (see Additional file 2: Table S13).
There were 285 gene clusters not detected in any of the chalcids (Trichogramma, Nasonia, Ceratosolen, and Copidosoma) but found in all the other hymenopterans. These gene families are significantly overrepresented for 12 GO terms, eight of them related to signal transduction (see Additional file 2: Table S13). The missing (or especially divergent) chalcid genes include those for key proteins and transcription factors relating to the control of development, embryo segmentation, and dorsal-ventral patterning including putative homologs of sog (a growth factor), krueppel-1 (a mediator of juvenile hormone signaling), knirps (involved in segmentation), protein winged eye (determination of imaginal disc identity), and a homeobox-like protein. Several of these genes had already been identified as missing in Nasonia but important for dorsal-ventral patterning in Drosophila . These include enhancer of split, trithorax, a centaurin-like protein, and F-box and leucine-rich repeat protein 7 . All extant lineages of chalcids have maintained features of ancestral miniaturization (e.g., highly reduced wing venation) , and they are likely to show genomic signatures of this ancestral state. Indeed, developmental studies of Nasonia embryos revealed novel genetic and molecular developmental networks , consistent with idea of a novel developmental plan ancestral to Chalcidoidea . Our data suggest that these may be a feature of chalcid evolution more broadly, and that these shared chalcid-unique and missing gene families may underlie the adaptive radiation of wasps in the superfamily.
Species-specific and missing enes in Trichogramma pretiosum
Total numbers of species-specific genes and missing genes for each genome
Missing gene familiesb,c
We investigated whether or not the apparent 4203 Trichogramma pretiosum “species-specific genes” were truly species-specific or divergent enough to fall below the clustering threshold for orthology detection. Indeed, blastp results show that even with a stringent e-value threshold of 1e-10 and the requirement that the Trichogramma pretiosum gene cover at least 50% of the length of the protein in another genome, more than half (55%, n = 2320) of the species-specific genes are recovered in the other hymenopteran species (Fig. 2d). With an e-value threshold of 1e-5 and no length requirement, 74% (n = 3113) of the “species-specific” Trichogramma pretiosum genes are recovered in other hymenopterans, indicating that most of these genes are not truly species-specific, but likely rapidly evolving such that they fall below the original orthology detection threshold. Trichogramma proteins did not cluster with the other hymenopteran proteins in the OrthoMCL analysis because of either (1) having identities lower than 70% as compared to the other hymenopteran proteins (the identify threshold used in clustering) or (2) not clustering tightly enough with the homologs (the inflation parameter). These recovered genes that were significantly diverged from their hymenopteran homologs represent a quarter (24%) of the entire set of Trichogramma pretiosum coding sequences. While it is well established that there is a tradeoff between the ability to detect divergent orthologs and incorrectly clustering out-paralogs in orthology analyses , it is notable that such a large proportion of the Trichogramma coding sequences failed to cluster with other hymenopteran proteins. Furthermore, it is interesting that the proteins in this category are related to DNA packaging, nucleosome assembly, and chromatin (see Additional file 3: Table S14): a possible connection to the unique chromatin compaction seen in minute insects like Trichogramma [13, 14]. After correcting for the identification of 3113 “species-specific” Trichogramma proteins in other hymenopteran genomes, only 1090 of the Trichogramma proteins retain their species-specific status. These “true” species-specific genes are overrepresented for a number of GO terms including metabolic processes, the regulation of transcription, and signaling (see Additional file 3: Table S14).
We also assessed the status of the large number (n = 403) of apparent Trichogramma-specific “missing genes” (Table 3). We investigated whether or not they were truly absent, or if they were divergent or pseudogenized. Nasonia vitripennis representatives for each of these gene families were used to tblastn search for these “missing genes” in the genome sequence of Trichogramma pretiosum. Using an e-value cutoff of 1e-10, 355 of these genes were recovered in Trichogramma. Furthermore, 311 out of the 355 recovered apparent “missing genes” are hits to annotated genes. It appears that most of these are not missing, but instead were not initially assigned to gene families because of rapid evolution relative to that of the outgroups. Cross-referencing these 311 genes with the list of Trichogramma singletons revealed that 254 of the “missing genes” had been assigned singleton status, thus inflating our counts both for missing genes and singleton genes. Adjusted counts of lineage-specific and missing genes are shown in parentheses in Table 3. However, note that manual curation of lineage-specific and missing genes was not performed for the other species. Regardless, Trichogramma pretiosum appears to be an outlier with regard to the numbers of proteins that fail to cluster with the other hymenopteran proteins, while the chalcids as a group are characterized by a separate set of missing or especially divergent genes.
Gene family expansions and contractions
The numbers of gene families that have significantly expanded or contracted along branches in the phylogeny are represented in Fig. 2c. As expected based on the number of genes in species-specific clusters and in the core genome, Nasonia vitripennis and Apis mellifera had the highest numbers of significantly expanded gene families (306 and 161 families, respectively). There is a clear trend of increased numbers of gene family contractions in Chalcidoidea, both on the branch leading to Chalcidoidea and along each lineage within Chalcidoidea. There are very few lineage-specific contractions in the branches leading to Microplitis demolitor and Orussus abietinus, implying that these contractions are a unique feature of chalcid evolution and not necessarily associated with parasitic wasps in general. While the chalcids do show higher numbers of contracting gene families, there is still a significant amount of species-specific gene family expansion that has occurred. The only branches of the phylogeny that experienced more contractions than expansions were those leading to the Chalcidoidea (expansions = 4, contractions = 20) and to Trichogramma pretiosum (expansions = 26, contractions = 41). Nasonia vitripennis and Trichogramma pretiosum had the highest number of unique genes (Table 3), but Trichogramma pretiosum had relatively few significantly expanding gene families due to its species-specific genes primarily being singletons as opposed to occurring in species-specific clusters.
Protein evolution in Trichogramma
Phylogenetic reconstruction of the Hymenoptera (Fig. 1, based on 107 single-copy protein-coding genes) revealed an especially long branch leading to Trichogramma pretiosum. We looked across a larger set of single-copy orthologs to determine whether or not Trichogramma proteins are evolving faster in particular functional categories, or if sequences are evolving faster across the genome. To do so, we defined a set of core genes (n = 3180) that were present as single-copy genes in Apis mellifera, Nasonia vitripennis, and Trichogramma pretiosum for use in a series of comparative analyses, using Apis as the outgroup. Tajima’s relative rate tests followed by overrepresentation analyses and correction for multiple comparisons revealed a suite of GO terms associated with more rapidly evolving genes. Masking low-quality regions of the alignments had little effect on the GO terms overrepresented, but as expected, decreased the total number of genes found to have significantly different rates of evolution. Without masking the alignments, 1023 genes had evidence for elevated rates of protein evolution: 832 in Trichogramma and 191 in Nasonia. After masking the alignments, 590 genes showed elevated rates of protein evolution: 441 in Trichogramma and 149 in Nasonia. Thus, Trichogramma appears to be characterized by an enriched set of rapidly evolving genes.
In contrast to Nasonia, which has no overrepresented GO terms in its more rapidly evolving gene set, Trichogramma shows clear GO term enrichments. In Trichogramma, 30 GO terms were overrepresented, with 23 of them overrepresented in both masked and unmasked versions of the analyses (see Additional file 4: Table S15). Significantly overrepresented GO terms include those relating to signaling and regulatory processes, specifically regulation of nucleotide metabolism and transcription. By concatenating the alignments and performing the same relative rate test, we find that the Trichogramma branch is indeed significantly longer overall (p < 0.0001). This lends further support to the rapid evolution along the Trichogramma branch. Although the causes of this remain unclear, we speculate that it could have to do with the short generation time of these wasps (approximately 10 days per generation in the laboratory), the unusual feeding ecology (both larvae and adults primarily utilize the eggs of moths and butterflies), and/or the consequences of adaptation to the very small size of insects in this lineage.
Protein evolution across Hymenoptera and Chalcidoidea
Numbers of chalcid proteins with 1st–4th longest branch lengths
Numbers of hymenopteran proteins with 1st–7th longest branch lengths
Proteins that had the longest branch from the chalcid ancestor to Trichogramma were significantly enriched for 19 GO terms, including nucleotide metabolic processes, transcription, and the regulation of gene expression (see Additional file 5: Table S16). There was no significant enrichment of any GO terms in the set of proteins where the branch to Trichogramma was the shortest of the orthologous group. Neither Nasonia nor Copidosoma had GO term enrichments for proteins in which these species represented either the longest or shortest branch. In contrast, orthologous groups in which the longest branch led to Ceratosolen, the fig wasp, were significantly overrepresented for mitochondrial functions such as ATP production and oxidation-reduction processes (see Additional file 5: Table S16). Lastly, proteins with 1st place assigned to Apis were overrepresented for GO terms associated with organic acid metabolism, likely a feature of adaptation to processing nectar and pollen.
Protein branch lengths significantly correlated between genomes (Spearman’s rank: p < 0.0001), confirming that more rapidly evolving proteins in one genome were likely to be rapidly evolving in other genomes [51, 52]. To determine which proteins had faster or slower rates of evolution across chalcids as a whole and in Trichogramma specifically, we first ordered and ranked the set of proteins (from 1 to 1311) within each chalcid species by their “chalcid-to-species” branch length: the within-genome rank. Within-genome ranks were significantly correlated between genomes (Spearman’s rank: p < 0.0001). Then, we assigned ranks to proteins based on their distance from the chalcid ancestor to the hymenopteran ancestor, i.e., the base rank. By comparing the median within-chalcid species rank to the base rank, we identified proteins for which the rank changed after the divergence from the chalcid ancestor (Fig. 3c). For example, a protein with a base rank of 10 (indicating a relatively short distance from the chalcid ancestor to the hymenopteran ancestor compared to other proteins) and a median within-chalcid rank of 1000 (indicating a relatively long branch from the chalcid ancestor to the species, compared to other proteins) would receive a score of + 990. To avoid overrepresentation among any protein category based on basal evolutionary rates, proteins were binned into groups of 100 based on the base rank (Fig. 3c). For example, bin “1–100” contains the 100 proteins with the shortest chalcid-to-Hymenoptera ancestor distances, and within each bin we selected the proteins with the largest discrepancy (top 10% and bottom 10%) in rank between the chalcid median rank and the base rank (Fig. 3c). We then used the same method to look specifically for Trichogramma genes with unusually ranked proteins, this time comparing the within-Trichogramma rank of the protein to the base rank of the protein (Fig. 3d). Lastly, to identify proteins evolving differently in Trichogramma relative to the other chalcids, we compared the within-Trichogramma rankings to the median rank of the other chalcids (Copidosoma, Ceratosolen, and Nasonia) instead of the base rank (Fig. 3e). The results of these three different comparisons were “fast” and “slow” proteins in each of the three categories: (1) chalcids to the base (Fig. 3c), (2) Trichogramma to the base (Fig. 3d), and (3) Trichogramma to the other chalcids (Fig. 3e). For each of these lists of proteins, we looked for overrepresented GO terms. Protein and GO term lists for each category are provided in Additional file 6: Table S17.
For proteins more rapidly evolving in chalcids, there was significant overrepresentation of GO terms associated with ribosomes and programmed cell death. Manual annotation revealed that the fastest evolving proteins in chalcids (relative to the base rank) are enriched for genes with inferred functions in cell size, proliferation, and ploidy. It is noteworthy that cell ploidy level and endoduplication can also affect cell size . Examples include Nuak family SNF1 kinase (5th fastest, involved in cell ploidy), LTV1 (6th, in cell size and endoduplication), Zinc Finger FYVE protein 6 (7th, in cell adhesion), Transcription Factor AR1 (13th, in cell proliferation and apoptosis), and escargot-like (23rd, in maintenance of diploidy). We therefore argue that rapid evolution of these proteins could be involved in the proposed miniaturization of the chalcid ancestor . There were no overrepresented GO terms for “slow” chalcid proteins. These findings suggest that ribosome structure and cell ploidy regulation could be a fruitful topic for study in chalcids.
Fast Trichogramma proteins (as compared to the base and to other chalcids) were again overrepresented for GO terms related to gene expression, nucleotide metabolism, and transcriptional processes. Manual annotation of the fastest evolving Trichogramma proteins relative to other chalcids (based on rank change) indicate genes involved in head structure and cell proliferation, including goosecoid homeobox (5th fastest), ETS-related transcription factor Elf-5 (6th, expressed in epithelial cells), forkhead domain containing gene crocodile-like (7th), the pair-rule and bristle formation gene hairy (9th), and transmembrane protein 45B (11th, implicated in cell proliferation). Relatively slow evolving Trichogramma proteins (compared to the base rate) were overrepresented for processes associated with actin and cytoskeleton organization. In contrast, slow Trichogramma proteins, as compared to other chalcids, were overrepresented for mitochondrial-interacting GO terms: oxidation-reduction, generation of precursor metabolites and energy, oxidative phosphorylation, and electron transport chain. This is especially interesting, as these are categories of genes that had previously been identified as more rapidly evolving in other parasitoids, such as Nasonia . In the Nasonia complex, nuclear-mitochondrial incompatibilities figure prominently in reproductive isolation between closely related species [38, 54, 55] and show accelerated rates of mitochondrial evolution . In contrast, Trichogramma spp. have unusual and difficult-to-predict patterns of intra- and interspecific reproductive compatibilities [21–24], which may be explained by the relatively slower evolution of nuclear genes interacting with mitochondria.
Lastly, we looked at the overlap of the “fast” proteins in all three categories (Fig. 3f). The 71 proteins that are unique to the “chalcid-to-base” only category include a suite of ribosomal biogenesis and ribosomal proteins, suggesting extensive evolution of the ribosomal complex and transcriptional machinery specific to the origin of chalcids. There are only nine proteins in the Trichogramma-to-base only category, but they include four proteins associated with polymerase I, II, or III. The 32 proteins present in the overlap of all three categories include several proteins related to maintenance or determination of ploidy and cell cycle regulation, potentially relating to cell size , so the evolution of these genes may be relevant to the evolution of miniaturization in the chalcid ancestor and further size reductions in Trichogramma. In sum, we find strong evidence for a rapid rate of protein evolution in Trichogramma pretiosum, and more generally in chalcids, that is particularly evident in categories relating to the regulation of gene expression and transcription, development, and ploidy. These may be involved in selection for size miniaturization and adaptation to a life as a tiny, quickly developing egg parasitoid.
Comparison to a sexual Trichogramma pretiosum
The reference asexual line of Trichogramma pretiosum represents a relatively recent transition to asexuality. Sexual function has been lost to the point where Wolbachia is essential for maintenance of the colony, but females are able to mate and fertilize eggs at a low level . Nevertheless, we wanted to determine whether or not features of the Trichogramma pretiosum reference genome were representative of the Trichogramma pretiosum clade as a whole, or the fact that the sequenced line is asexual, and may have undergone gene loss or divergence due to asexuality. We therefore assembled a short insert draft genome (using paired-end 250-bp reads) for a sexually reproducing line of Trichogramma pretiosum, “CA-29,” which is naturally uninfected with Wolbachia (see Additional file 1: Section S4) [19, 57–68]. The sexual line is derived from a population in California, whereas the asexual line is from a population in Peru. We obtained approximately 70× coverage of the CA-29 Trichogramma draft genome, resulting in a de novo assembly of 189,939,323 bp into 40,567 contigs. Clearly the quality of this assembly is inferior to the reference asexual line. Nevertheless, it can be used to address some key questions, such as whether or not features of the reference genome are a result of the transition to asexuality or are conserved features of Trichogramma pretiosum independent of reproductive type.
Depending on circumstances, models predict either an increase or decrease in the abundance of repetitive DNA as a consequence of the transition to asexual reproduction [69–73]. We therefore compared the repetitive elements present in the sexual and asexual Trichogramma genomes using k-mer-based approaches (see Additional file 1: Section S6) [41–44, 74]. The size of the sexual genome as predicted by k-mer frequencies was 193.9 mega base pairs (Mbp), with a repetitive fraction of 26.2%. This indicates that there was no significant reduction in the size or repeat content of the asexual genome (195 Mbp and 30.3%, respectively), as compared to the sexual one. However, within that total repetitive fraction the sexual and asexual genomes had different proportions of the types of repetitive elements. We constructed repeat libraries containing transposons and tandem repeats and mapped genomic reads back to these sequences to estimate their abundance in both genomes. The sexual genome had a significantly higher percentage of reads mapping to transposons and tandem repeats, as compared to the asexual genome (~ 12% and ~ 8%, respectively, chi-squared statistic: p < 0.001), and had a greater abundance of some specific transposon-like elements and tandem arrays (see Additional file 1: Tables S11 and S12). Therefore, the asexual genome appears to have a lower abundance of repetitive DNA relative to the sexual genome, in contrast to some predictions for recently evolved asexual genomes.
We next looked for the presence of what had originally been annotated as “missing genes” in the asexual reference genome. Of the 355 “missing Trichogramma genes” that were recovered through species-specific blast searches, 348 were also recovered in the sexual genome, indicating that the pattern of “missing genes” (which are actually rapidly evolving genes) is not a result of the transition to asexuality. Therefore, we conclude that the apparent gene loss in Trichogramma pretiosum was not due to unusual gene losses or divergence in the asexual lineage, but reflects primarily rapid protein evolution in the Trichogramma pretiosum clade.
We looked for overrepresented functional categories within groups of genes containing different types of variants between the sexual and asexual lines. The most highly diverged genes, as measured by genes in the top 5% of missense mutations per amino acid site, were overrepresented for GO terms also overrepresented in the asexual Trichogramma pretiosum singleton gene set (see Additional file 7: Table S18), many of which we went on to show are not actually lineage-specific. More than half of the GO terms overrepresented in the diverged gene category were related to nucleotide metabolism or nitrogen metabolism, and may reflect the egg-feeding ecology of the wasps or the metabolically expensive large brain size in Trichogramma. We hypothesized that these rapidly diverging genes were more likely to be categorized as singletons in the comparative analyses. Indeed, a significant portion (51.8%) of the genes undergoing rapid divergence between the sexual and asexual lineages were defined as singletons (p < 0.0001), which again is in agreement with the idea that Trichogramma singletons may have a longer evolutionary history of divergence that prevented orthology detection in our analyses. We show that the functional categories diverging between the two Trichogramma pretiosum lines are also represented in the singleton gene categories, rapidly evolving gene categories (as determined by Tajima’s relative rate test and comparisons to other Hymenoptera), or both (Fig. 4b). Genes with frameshift mutations between the sexual and asexual lines were overrepresented for seven GO terms, five of which were also overrepresented in the divergent category (see Additional file 7: Table S18).
We then quantified dS and dN between the sexual and asexual lines. These measurements also cannot be assigned to the respective lineage without a more closely related outgroup (due to nucleotide substitution saturation). For the single-copy core genes previously used for Tajima’s relative rate testing (n = 3180), dS between the sexual and asexual genomes was 0.013 +/− 0.0003. When all Trichogramma coding sequences were considered, dS was 0.014 +/− 0.0002. Genes with dN/dS greater than 1 (n = 357) were overrepresented for a suite of GO terms (see Additional file 7: Table S18) that again overlap with the GO terms overrepresented in other analyses of rapid evolution and divergence: the regulation of transcriptional processes and nucleotide metabolism. The estimates of dS between the sexual and asexual lines (~ 0.014) are similar to estimates of dS between some sibling species of Nasonia , and thus represent a high level of divergence for an intraspecific comparison. While it is possible that there are cryptic species within the Trichogramma pretiosum clade, it is notable that these two lines readily produce heterozygous (F1) and recombinant (F2) offspring without any apparent hybrid breakdown , despite their divergence and geographically distant origins (California and Peru). There is appreciable interspecific hybrid incompatibility within the Nasonia clade, and the genes with elevated dN/dS in those comparisons are overrepresented for mitochondrial-interacting genes and are involved in hybrid breakdown [75, 76]. In contrast, mitochondrial gene ontologies are not overrepresented in the rapidly evolving Trichogramma gene sets, but were identified as slower evolving in Trichogramma compared to the other chalcids (Fig. 3d), which may explain the hybrid compatibility despite the higher levels of nuclear genome divergence.
We next compared rates of protein evolution with the core set of conserved hymenopteran orthologs, using Nasonia as the outgroup. While we did not have a closely related outgroup that allowed us to compare evolution of the sexual and asexual genomes at the nucleotide level, using Tajima’s relative rate test allowed us to determine whether or not the divergence between sexual and asexual lineages is a result of more amino acid changes on one branch than the other. There were no proteins with significantly elevated rates of evolution in one branch over the other, indicating that both the sexual and asexual lines are diverging from the common ancestor at similar rates. Thus, divergence between the sexual and asexual lines, and from the rest of Hymenoptera, cannot be attributed to their different reproductive modes but is a feature of the Trichogramma clade more generally.
Methylation in the Trichogramma pretiosum genome
We experimentally validated methylation patterns in the genome with whole genome bisulfite sequencing and found that gene methylation density mirrors gene CpG O/E density (Fig. 6b). There is a strong negative correlation between gene coding DNA sequence (CDS) CpG O/E and gene fractional methylation, especially for genes above a threshold of 0.01 fractional methylation. For methylated genes (> 0.01 gene body fractional methylation), we confirmed methylation bias towards the 5′ prime end and enrichment of CpG methylation in exons compared to introns (Fig. 6c). This pattern is absent in unmethylated genes and mirrors similar patterns observed in other hymenopterans such as Nasonia vitripennis and Apis mellifera [82, 83].
Conservation of methylation
Methylation status of gene body methylation across 3180 single-copy orthologs
Number of orthologsa
Conserved methylation status
T. pretiosum lineage-specific gain of methylation
T. pretiosum lineage-specific loss of methylation
Conserved methylation status
Trichogramma have been extensively studied as biological control agents, for their relationship with parthenogenesis-inducing Wolbachia symbionts, and for their minute size. We obtained a high-quality reference genome for an asexual line of Trichogramma pretiosum and found that approximately a third of all the coding sequences have signatures of rapid evolution compared to other hymenopteran species, either through rate testing, protein branch lengths, or the discovery of more divergent orthologs that initially failed to cluster with other hymenopteran proteins. Comparisons at different phylogenetic distances (intraorder and intraspecific) revealed that rapidly evolving Trichogramma genes were overrepresented for a number of functional categories, largely nucleic acid metabolism and transcriptional regulation. Genome-wide comparisons to a sexual line of Trichogramma pretiosum reveal that the signatures of rapid evolution and apparent gene loss are not due to the transition to asexuality. Genes originally identified as missing were recovered at the same frequency in both the sexual and asexual genomes, indicating no difference due to reproductive mode. Most “missing genes” and “species-specific genes” are neither missing nor species-specific, but are divergent enough that orthology was not detected. Furthermore, we identified no proteins that had a significantly elevated rate of evolution in either the sexual or asexual lineage as compared to Nasonia, indicating that they are diverging from their common ancestor at similar rates.
Gene family contractions were more common in chalcids compared to the other hymenopterans, and from this study we detect many chalcid-specific gene family gains and losses that may underlie the rapid adaptive radiation of the chalcid superfamily, or the evolution of a miniaturized ancestor. The most notable of these are the loss of conserved genes involved in signaling, embryonic development, and patterning. In parallel, we identified genes that are more rapidly evolving in chalcids that may also be associated with the evolution of a miniaturized chalcid ancestor. These include functions relating to cell size, cell proliferation, and ploidy.
Trichogramma pretiosum has a functional methylation toolkit, and has characteristic patterns of CpG depletion and methylation throughout the genome. The pattern of methylation is phylogenetically conserved across Hymenoptera, with five prime exons consistently being the targets of methylation, and methylation occurring in conserved core genes. Epigenetic patterning likely plays a critical role in sex determination and may be mediated by Trichogramma’s relationship with Wolbachia [33–35]. Indeed, Wolbachia has been shown to affect methylation in other insect hosts [89, 90]. Mechanistic investigation into how Wolbachia may sculpt methylation patterns is a promising direction for understanding host-symbiont interactions in this system.
The Trichogramma pretiosum genomes provide the framework for more detailed studies on the basis of symbiont-mediated parthenogenesis, sex determination, and the constraints of parasitism. A deeper understanding of genome adaptations specific to the Trichogramma clade versus those associated with sexual-asexual transitions will emerge from additional genome sequencing. The Trichogramma system is rich in multiple examples of sexual-asexual transitions resulting in polymorphic and fixed asexual populations of differing divergence for these future studies [5, 19, 30, 91].
Trichogramma pretiosum is one of 30 arthropod species sequenced as a part of the pilot project for the i5K 5000 arthropod genomes project at the Baylor College of Medicine Human Genome Sequencing Center (HGSC). We sequenced the genome of an irreversibly asexual line of Trichogramma pretiosum using an Illumina-ALLPATHS-LG sequencing and assembly strategy. In brief, we generated paired-end 100-bp sequences for libraries of nominal insert sizes 180 bp, 500 bp, 1 kb, 3 kb, and 8 kb, assembled with ALLPATHS-LG (v35218)  and further scaffolded and gap-filled using in-house tools Atlas-Link (v.1.0) and Atlas gap-fill (v.2.2) (https://www.hgsc.bcm.edu/software/). The genome was annotated with a Maker 2.0 annotation pipeline tuned specifically for arthropods , using RNA-seq libraries to identify exon-intron boundaries. For specific methodological details about biological samples, libraries, sequencing, and annotation, see Additional file 1: Section S1 [5, 29, 30, 58, 59, 92–99].
We reconstructed a phylogeny of 21 hymenopteran species from transcriptomic or genomic data, using 107 single-copy protein-coding genes with RAxML version 8.2.8 , and rooted on Athalia rosae. This phylogeny was pruned to eight species for which we performed in-depth genomic comparisons (Table 1). It was essential to construct a more complete phylogeny of Hymenoptera, followed by pruning, in order to avoid long branch length attraction, which otherwise resulted in phylogenetic relationships not supported by other phylogenetic studies of Hymenoptera [2, 3, 46, 47, 101]. Protein-coding sequences from these genomes were clustered into families of orthologous genes using OrthoMCL . GO terms were mapped to the coding sequences from all genomes using Blast2GO . To obtain GO terms for each gene family delineated by OrthoMCL, all GO terms represented by at least 40% of the members within a gene family were recorded, as was done in the work of Grbic et al. . We used CAFE v3.1  to identify significantly expanding and contracting gene families across Hymenoptera. For more specific comparative and statistical methods, see Additional file 1: Sections S2.1–S2.4 [38–40, 45–48, 79, 102–113].
Protein rate evolution: Tajima’s relative rate tests
Protein rate evolution tests were performed with Tajima’s relative rate test , using the R package pegas , on amino acid alignments of single-copy orthologs, comparing Trichogramma pretiosum to Nasonia vitripennis, using Apis mellifera as an outgroup. Alignments were created with MAFFT v7.271 , and rate testing was performed on two versions of the alignments: those masked of especially divergent regions with Gblocks [107, 116], and full-length alignments of the same orthologs. BiNGO  was used to identify significantly overrepresented GO terms in all analyses. For more specific comparative and statistical methods, see Additional file 1: Section S2.5 [106, 107, 111, 114–116].
Protein rate evolution: phylogenetic comparisons
In addition to the pairwise comparisons between Trichogramma and Nasonia proteins (n = 3180), we compared rates of protein evolution across all species in our hymenopteran phylogeny for each protein in the single-copy core hymenopteran genome (n = 1311 proteins). Based on the previously constructed species tree, branch lengths of the alignments masked by Gblocks were estimated with RAxML version 8.2.11 , using the same parameters as those used for construction of the species tree. Branch lengths were extracted using Newick Utilities version 1.6 . Raw distances from each chalcid species to the chalcid root and from each hymenopteran species to the hymenopteran root were ordered in R v3.4.1 , so as to identify the protein with the longest branch length within each orthologous group. For each chalcid, we normalized branch lengths by dividing the “species-to-chalcid root distance” by the distance from the chalcid root to the hymenopteran root. This normalization better allowed for comparisons between proteins, accounting for the background rate of evolution (as determined by the distance from the chalcid root to the hymenopteran root). Additionally, we ranked all 1311 proteins by their raw branch lengths—within each chalcid genome using the “species-to-chalcid root distance” and separately by the “chalcid root-to-hymenopteran root” distance. GO term analyses were performed as described in Additional file 1: Section S2. Where indicated in the results, chi-squared analyses were performed with the fifer package in R v3.3.2, using the chisq.post.hoc function .
Methylation in Trichogramma pretiosum
We collected previously described DNMT protein sequences and identified putative DNMTs in Trichogramma pretiosum. Clustal Omega  was used to align the sequences, and Molecular Evoutionary Genetics Analysis (MEGA)  was used to construct a maximum likelihood tree. Computational predictions of methylation in the Trichogramma pretiosum genome were performed using the nucleotide composition method (CpG O/E method): CpG observed/expected and GpC observed/expected were calculated for CDS . Methylation patterns were experimentally validated via whole genome bisulfite sequencing. See Additional file 1: Section S3 [38, 120–125] for additional details on methylation analyses and sequencing.
We compared total exon and intron lengths per gene across Trichogramma pretiosum, Apis mellifera, and Nasonia vitripennis. Additionally, we compared intron and exon lengths for the genes that are single copy, as determined by our OrthoMCL analyses, in the three genomes. One-way ANOVA followed by Tukey’s honest significant difference (HSD) test was used to determine significant differences between lineages for intron and exon lengths.
Comparisons to sexual Trichogramma pretiosum
Trichogramma pretiosum contains both sexual and asexual forms; populations can either be a mixture of types or fixed for either sexual or asexual forms [5, 19, 30, 91]. For an initial comparison of sexual and asexual strains, we performed whole genome shotgun sequencing for a sexual line of Trichogramma pretiosum, CA-29, a previously described inbred line . In contrast to the reference asexual line from Peru, CA-29 originates from Irvine, California, where populations of Trichogramma pretiosum are completely sexual and have not been collected with Wolbachia infections . Critically, these two lines (Insectary and CA-29) are compatible and have no obvious reductions in fitness in either the F1 or F2 generation . We generated 27,480,751 paired-end, 250-bp reads, amounting to ~ 70× coverage of a 195-Mbp genome. We performed an assembly with MaSuRCA , aligned the CA-29 draft genome to the reference asexual i5k genome and called differences with NUCmer , and identified functional consequences of SNPs and indels with SnpEff . Additional details are provided in Additional file 1: Section S4 [19, 57–68].
We thank Bob Schmitz for help with the whole genome bisulfite sequencing. We thank Hans Smid, Eric A. Smith, and three anonymous reviewers for feedback on earlier drafts of the manuscript. We thank the staff at the Baylor College of Medicine HGSC for their contributions, and we acknowledge Monica Poelchau and Christopher Childers for their contributions to the i5k workspace.
This work was supported by the National Human Genome Research Institute (U54 HG003273 to RAG); the National Science Foundation (DEB 1501227 to ARIL, DEB 1257053 and IOS 1456233 to JHW, and MCB 1615664 to SVY); the United States Department of Agriculture (NIFA 194617 to RS and NIFA 2016-67011-24778 to ARIL); and Robert and Peggy van den Bosch Memorial Scholarships to ARIL. None of the funding bodies had any role in the design of the study; collection, analysis, and interpretation of data; or in writing of the manuscript.
Availability of data and materials
The Trichogramma pretiosum Whole Genome Shotgun project has been deposited at the DNA Data Bank of Japan (DDBJ)/European Molecular Biology Laboratory (EMBL)/GenBank under accession number JARR00000000. The version described in this paper is version JARR00000000.1. See Additional file 1: Section S1 for a complete listing of accession numbers for individual libraries. All associated sequences are contained within the National Center for Biotechnology Information (NCBI) BioProject PRJNA168121. Trichogramma pretiosum colonies Insectary and CA-29 are available upon request, and specimens have been vouchered at the University of California Riverside Entomology Research Museum (UCRC_ENT 00496290 and UCRC_ENT 00496294, respectively).
JHW, RS, and SR conceived the project and directed its management, assisted by ARIL. PFRJ reared the Trichogramma lines and extracted DNA and RNA for sequencing, assembly, and annotation at the HGSC by DSTH, SCM, JQ, SD, SLL, HC, HD, YH, HVD, KCW, DMM, and RAG. EOM generated the hymenopteran phylogeny, and YDK performed orthology assignments and repetitive element analysis. DS and SVY performed computational methylation predictions, and XW and SVY analyzed the Bis-Seq and comparative methylation data and analyzed intron and exon sizes. ZY, GY, JHW, and ARIL analyzed the core hymenopteran protein branch lengths and ranks. ARIL analyzed the orthology data generated by YDK, including rate testing, gene family expansions and contractions, and missing gene searches; performed the sexual genome comparisons including rearing, DNA extractions, sequencing, assembly, and comparisons to the reference; searched for immunity genes; performed all GO term analyses; and wrote the first draft of the manuscript after coordinating the contributions of methods and figures from all authors. ARIL, JHW, RS, PFRJ, YDK, ZY, EOM, XW, SVY, and SR edited the manuscript. All authors read and approved the final manuscript.
Ethics approval and consent to participate
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- Knutson A: The Trichogramma manual: a guide to the use of Trichogramma for biological control with special reference to augmentative releases for control of bollworm and budworm in cotton: Texas Agricultural Extension Service, the Texas A&M University System; 1998.Google Scholar
- Heraty JM, Burks RA, Cruaud A, Gibson GAP, Liljeblad J, Munro J, Rasplus JY, Delvare G, Jansta P, Gumovsky A, et al. A phylogenetic analysis of the megadiverse Chalcidoidea (Hymenoptera). Cladistics. 2013;29(5):466–542.View ArticleGoogle Scholar
- Munro JB, Heraty JM, Burks RA, Hawks D, Mottern J, Cruaud A, Rasplus JY, Jansta P. A molecular phylogeny of the Chalcidoidea (Hymenoptera). PLoS One. 2011;6(11):e27023.PubMedPubMed CentralView ArticleGoogle Scholar
- Stouthamer R, Breeuwer JAJ, Luck RF, Werren JH. Molecular identification of microorganisms associated with parthenogenesis. Nature. 1993;361(6407):66–8.PubMedView ArticleGoogle Scholar
- Stouthamer R, Luck RF, Hamilton WD. Antibiotics cause parthenogenetic Trichogramma (Hymenoptera, Trichogrammatidae) to revert to sex. Proc Natl Acad Sci. 1990;87(7):2424–7.PubMedPubMed CentralView ArticleGoogle Scholar
- Sundberg LR, Pulkkinen K. Genome size evolution in macroparasites. Int J Parasitol. 2015;45(5):285–8.PubMedView ArticleGoogle Scholar
- Tellier A, Moreno-Gámez S, Stephan W. Speed of adaptation and genomic footprints of host-parasite coevolution under arms race and trench warfare dynamics. Evolution. 2014;68(8):2211–24.PubMedGoogle Scholar
- Poulin R: Evolutionary ecology of parasites. Princeton: Princeton University Press; 2011.Google Scholar
- Johnston J, Ross L, Beani L, Hughes D, Kathirithamby J. Tiny genomes and endoreduplication in Strepsiptera. Insect Mol Biol. 2004;13(6):581–5.PubMedView ArticleGoogle Scholar
- Heraty J. Parasitoid biodiversity and insect pest management. In: Foottit B, Adler P, editors. Parasitoid biodiversity and insect pest management. Hague: Springer-Verlag; 2009. p. 445–62.View ArticleGoogle Scholar
- Heraty J, Gates M. "Diversity of Chalcidoidea (Hymenoptera) at El Edén Ecological Reserve, Mexico." The Lowland Maya Area: Three Millennia at the Human-Wildland Interface. 2003. p. 277.Google Scholar
- Peters RS, Niehuis O, Gunkel S, Bläser M, Mayer C, Podsiadlowski L, Kozlov A, Donath A, van Noort S, Liu S, et al. Transcriptome sequence-based phylogeny of chalcidoid wasps (Hymenoptera: Chalcidoidea) reveals a history of rapid radiations, convergence, and evolutionary success. Mol Phylogen Evol. 2018;120:286–96.View ArticleGoogle Scholar
- Polilov A. Features of the structure of hymenoptera associated with miniaturization: 2. Anatomy of Trichogramma evanescens (Hymenoptera, Trichogrammatidae). Entomol Rev. 2016;96(4):419–31.View ArticleGoogle Scholar
- Polilov AA. Small is beautiful: features of the smallest insects and limits to miniaturization. Annu Rev Entomol. 2015;60:103–21.PubMedView ArticleGoogle Scholar
- Polilov AA. The smallest insects evolve anucleate neurons. Arthropod Struct Dev. 2012;41(1):29–34.PubMedGoogle Scholar
- Van Der Woude E, Smid HM, Chittka L, Huigens ME. Breaking Haller's rule: brain-body size isometry in a minute parasitic wasp. Brain Behav Evol. 2013;81(2):86–92.PubMedView ArticleGoogle Scholar
- Fischer S, Mueller CH, Meyer-Rochow VB. How small can small be: the compound eye of the parasitoid wasp Trichogramma evanescens (Westwood, 1833)(Hymenoptera, Hexapoda), an insect of 0.3-to 0.4-mm total body size. Vis Neurosci. 2011;28(4):295–308.PubMedView ArticleGoogle Scholar
- Pinto JD, Stouthamer R. Systematics of the Trichogrammatidae with emphasis on Trichogramma. In: Wajnberg E, Hassan SA, editors. Trichogramma and other egg parasitoids. London: CAB; 1994. p. 1–36.Google Scholar
- Pinto JD: Systematics of the North American species of Trichogramma Westwood (Hymenoptera: Trichogrammatidae). Washington, DC: The Entomological Society of Washington; 1998.Google Scholar
- Pinto JD. A review of the New World genera of Trichogrammatidae (Hymenoptera). J Hymenoptera Res. 2006;15(1):38–163.Google Scholar
- Li ZX, Zheng L, Shen ZR. Using internally transcribed spacer 2 sequences to re-examine the taxonomic status of several cryptic species of Trichogramma (Hymenoptera : Trichogrammatidae). Eur J Entomol. 2004;101(3):347–58.View ArticleGoogle Scholar
- Stouthamer R, Jochemsen P, Platner GR, Pinto JD. Crossing incompatibility between Trichogramma minutum and T. platneri (Hymenoptera: Trichogrammatidae): implications for application in biological control. Environ Entomol. 2000;29(4):832–7.View ArticleGoogle Scholar
- Pinto JD, Stouthamer R, Platner GR. A new cryptic species of Trichogramma (Hymenoptera: Trichogrammatidae) from the Mojave Desert of California as determined by morphological, reproductive and molecular data. Proc Entomol Soc Wash. 1997;99(2):238–47.Google Scholar
- Pinto JD, Stouthamer R, Platner GR, Oatman ER. Variation in reproductive compatibility in Trichogramma and its taxonomic significance (Hymenoptera: Trichogrammatidae). Ann Entomol Soc Am. 1991;84(1):37–46.View ArticleGoogle Scholar
- Bai B, Luck RF, Forster L, Stephens B, Janssen JM. The effect of host size on quality attributes of the egg parasitoid, Trichogramma pretiosum. Entomol Exp Appl. 1992;64(1):37–48.View ArticleGoogle Scholar
- Greenberg S, Nordlund DA, Wu Z. Influence of rearing host on adult size and ovipositional behavior of mass produced female Trichogramma minutum Riley and Trichogramma pretiosum Riley (Hymenoptera: Trichogrammatidae). Biol Control. 1998;11(1):43–8.View ArticleGoogle Scholar
- van der Woude E, Smid HM. Effects of isometric brain-body size scaling on the complexity of monoaminergic neurons in a minute parasitic wasp. Brain Behav Evol. 2017;89(3):185–94.PubMedPubMed CentralView ArticleGoogle Scholar
- Schilthuizen M, Stouthamer R. Horizontal transmission of parthenogenesis-inducing microbes in Trichogramma wasps. Proc R Soc Lond B. 1997;264(1380):361–6.View ArticleGoogle Scholar
- Stouthamer R, Werren JH. Microbes associated with parthenogenesis in wasps of the genus Trichogramma. J Invertebr Pathol. 1993;61(1):6–9.View ArticleGoogle Scholar
- Russell JE, Stouthamer R. The genetics and evolution of obligate reproductive parasitism in Trichogramma pretiosum infected with parthenogenesis-inducing Wolbachia. Heredity. 2011;106(1):58–67.PubMedView ArticleGoogle Scholar
- Stouthamer R, Russell JE, Vavre F, Nunney L. Intragenomic conflict in populations infected by parthenogenesis inducing Wolbachia ends with irreversible loss of sexual reproduction. BMC Evol Biol. 2010;10:12.View ArticleGoogle Scholar
- Stouthamer R, Kazmer DJ. Cytogenetics of microbe-associated parthenogenesis and its consequences for gene flow in Trichogramma wasps. Heredity. 1994;73:317–27.View ArticleGoogle Scholar
- Tulgetske GM, Stouthamer R. Characterization of intersex production in Trichogramma kaykai infected with parthenogenesis-inducing Wolbachia. Naturwissenschaften. 2012;99(2):143–52.PubMedView ArticleGoogle Scholar
- Tulgetske GM. Investigations into the mechanisms of Wolbachia induced parthenogenesis and sex determination in the parasitoid wasp, Trichogramma: Ph.D. Dissertation. Riverside: University of California; 2010.Google Scholar
- Lindsey ARI, Stouthamer R. Penetrance of symbiont-mediated parthenogenesis is driven by reproductive rate in a parasitoid wasp. PeerJ. 2017;5:e3505.PubMedPubMed CentralView ArticleGoogle Scholar
- Ma WJ, Pannebakker BA, van de Zande L, Schwander T, Wertheim B, Beukeboom LW. Diploid males support a two-step mechanism of endosymbiont-induced thelytoky in a parasitoid wasp. BMC Evol Biol. 2015;15:84.PubMedPubMed CentralView ArticleGoogle Scholar
- van Vugt J, de Nooijer S, Stouthamer R, de Jong H. NOR activity and repeat sequences of the paternal sex ratio chromosome of the parasitoid wasp Trichogramma kaykai. Chromosoma. 2005;114(6):410–9.PubMedView ArticleGoogle Scholar
- Werren JH, Richards S, Desjardins CA, Niehuis O, Gadau J, Colbourne JK, Beukeboom LW, Desplan C, Elsik CG, Grimmelikhuijzen CJP, et al. Functional and evolutionary insights from the genomes of three parasitoid Nasonia species. Science. 2010;327(5963):343–8.PubMedView ArticleGoogle Scholar
- Rago A, Gilbert DG, Choi JH, Sackton TB, Wang X, Kelkar YD, Werren JH, Colbourne JK. OGS2: genome re-annotation of the jewel wasp Nasonia vitripennis. BMC Genomics. 2016;17:678.PubMedPubMed CentralView ArticleGoogle Scholar
- Lindsey ARI, Werren JH, Richards S, Stouthamer R. Comparative genomics of a parthenogenesis-inducing Wolbachia symbiont. G3 (Bethesda). 2016;6(7):2113–23.View ArticleGoogle Scholar
- Zytnicki M, Akhunov E, Quesneville H. Tedna: a transposable element de novo assembler. Bioinformatics. 2014;30(18):2656–8.PubMedView ArticleGoogle Scholar
- Kohany O, Gentles AJ, Hankus L, Jurka J. Annotation, submission and screening of repetitive elements in Repbase: RepbaseSubmitter and Censor. BMC Bioinformatics. 2006;7(1):474.PubMedPubMed CentralView ArticleGoogle Scholar
- Li H: Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv preprint arXiv:13033997. 2013.Google Scholar
- Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, Subgroup GPDP. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25(16):2078–9.PubMedPubMed CentralView ArticleGoogle Scholar
- Sackton TB, Werren JH, Clark AG. Characterizing the infection-induced transcriptome of Nasonia vitripennis reveals a preponderance of taxonomically-restricted immune genes. PLoS One. 2013;8(12):e83984.PubMedPubMed CentralView ArticleGoogle Scholar
- Klopfstein S, Vilhelmsen L, Heraty JM, Sharkey M, Ronquist F. The Hymenopteran tree of life: evidence from protein-coding genes and objectively aligned ribosomal data. PLoS One. 2013;8(8):e69344.PubMedPubMed CentralView ArticleGoogle Scholar
- Heraty J, Ronquist F, Carpenter JM, Hawks D, Schulmeister S, Dowling AP, Murray D, Munro J, Wheeler WC, Schiff N, et al. Evolution of the hymenopteran megaradiation. Mol Phylogen Evol. 2011;60(1):73–88.View ArticleGoogle Scholar
- Li L, Stoeckert CJ, Roos DS. OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res. 2003;13(9):2178–89.PubMedPubMed CentralView ArticleGoogle Scholar
- Pers D, Buchta T, Özüak O, Wolff S, Pietsch JM, Memon MB, Roth S, Lynch JA. Global analysis of dorsoventral patterning in the wasp Nasonia reveals extensive incorporation of novelty in a regulatory network. BMC Biol. 2016;14(1):63.PubMedPubMed CentralView ArticleGoogle Scholar
- Kuzniar A, van Ham RC, Pongor S, Leunissen JA. The quest for orthologs: finding the corresponding gene across genomes. Trends Genet. 2008;24(11):539–51.PubMedView ArticleGoogle Scholar
- Tourasse NJ, Li W-H. Selective constraints, amino acid composition, and the rate of protein evolution. Mol Biol Evol. 2000;17(4):656–64.PubMedView ArticleGoogle Scholar
- Pál C, Papp B, Lercher MJ. An integrated view of protein evolution. Nat Rev Genet. 2006;7(5):337–48.PubMedView ArticleGoogle Scholar
- Amodeo AA, Skotheim JM. Cell-size control. Cold Spring Harb Perspect Biol. 2016;8(4):a019083.PubMedPubMed CentralView ArticleGoogle Scholar
- Breeuwer JA, Werren JH. Hybrid breakdown between two haplodiploid species: the role of nuclear and cytoplasmic genes. Evolution. 1995;49(4):705–17.PubMedView ArticleGoogle Scholar
- Ellison C, Niehuis O, Gadau J. Hybrid breakdown and mitochondrial dysfunction in hybrids of Nasonia parasitoid wasps. J Evol Biol. 2008;21(6):1844–51.PubMedView ArticleGoogle Scholar
- Oliveira DC, Raychoudhury R, Lavrov DV, Werren JH. Rapidly evolving mitochondrial genome and directional selection in mitochondrial genes in the parasitic wasp Nasonia (Hymenoptera: Pteromalidae). Mol Biol Evol. 2008;25(10):2167–80.PubMedPubMed CentralView ArticleGoogle Scholar
- Lindsey ARI, Stouthamer R. The effects of outbreeding on a parasitoid wasp fixed for infection with a parthenogenesis-inducing Wolbachia symbiont. Heredity. 2017;119(6):411–7.PubMedView ArticleGoogle Scholar
- Stouthamer R, Hu JG, van Kan F, Platner GR, Pinto JD. The utility of internally transcribed spacer 2 DNA sequences of the nuclear ribosomal gene for distinguishing sibling species of Trichogramma. BioControl. 1999;43(4):421–40.View ArticleGoogle Scholar
- Werren JH, Windsor DM. Wolbachia infection frequencies in insects: evidence of a global equilibrium? Proc R Soc Lond B. 2000;267(1450):1277–85.View ArticleGoogle Scholar
- Zimin AV, Marcais G, Puiu D, Roberts M, Salzberg SL, Yorke JA. The MaSuRCA genome assembler. Bioinformatics. 2013;29(21):2669–77.PubMedPubMed CentralView ArticleGoogle Scholar
- Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, He G, Chen Y, Pan Q, Liu Y, et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience. 2012;1:18.PubMedPubMed CentralView ArticleGoogle Scholar
- Kurtz S, Phillippy A, Delcher AL, Smoot M, Shumway M, Antonescu C, Salzberg SL. Versatile and open software for comparing large genomes. Genome Biol. 2004;5(2):1.View ArticleGoogle Scholar
- Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, Land SJ, Lu X, Ruden DM. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly. 2012;6(2):80–92.PubMedPubMed CentralView ArticleGoogle Scholar
- Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, Handsaker RE, Lunter G, Marth GT, Sherry ST. The variant call format and VCFtools. Bioinformatics. 2011;27(15):2156–8.PubMedPubMed CentralView ArticleGoogle Scholar
- McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20(9):1297–303.PubMedPubMed CentralView ArticleGoogle Scholar
- Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, Pimentel H, Salzberg SL, Rinn JL, Pachter L. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc. 2012;7(3):562–78.PubMedPubMed CentralView ArticleGoogle Scholar
- Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32(5):1792–7.PubMedPubMed CentralView ArticleGoogle Scholar
- Yang Z, Nielsen R. Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models. Mol Biol Evol. 2000;17(1):32–43.PubMedView ArticleGoogle Scholar
- Dolgin ES, Charlesworth B. The fate of transposable elements in asexual populations. Genetics. 2006;174(2):817–27.PubMedPubMed CentralView ArticleGoogle Scholar
- Bast J, Schaefer I, Schwander T, Maraun M, Scheu S, Kraaijeveld K. No accumulation of transposable elements in asexual arthropods. Mol Biol Evol. 2016;33(3):697–706.PubMedView ArticleGoogle Scholar
- Kraaijeveld K, Zwanenburg B, Hubert B, Vieira C, de Pater S, van Alphen JJM, den Dunnen JT, de Knijff P. Transposon proliferation in an asexual parasitoid. Mol Ecol. 2012;21(16):3898–906.PubMedView ArticleGoogle Scholar
- Nuzhdin SV, Petrov DA. Transposable elements in clonal lineages: lethal hangover from sex. Biol J Linn Soc. 2003;79(1):33–41.View ArticleGoogle Scholar
- Werren JH. Selfish genetic elements, genetic conflict, and evolutionary innovation. Proc Natl Acad Sci. 2011;108(Supplement 2):10863–70.PubMedPubMed CentralView ArticleGoogle Scholar
- Benson G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 1999;27(2):573–80.PubMedPubMed CentralView ArticleGoogle Scholar
- Burton RS, Barreto FS. A disproportionate role for mtDNA in Dobzhansky-Muller incompatibilities? Mol Ecol. 2012;21(20):4942–57.PubMedView ArticleGoogle Scholar
- Burton RS, Pereira RJ, Barreto FS. Cytonuclear genomic interactions and hybrid breakdown. Annu Rev Ecol Evol Syst. 2013;44(1):281–302.View ArticleGoogle Scholar
- Glastad K, Hunt B, Yi S, Goodisman M. DNA methylation in insects: on the brink of the epigenomic era. Insect Mol Biol. 2011;20(5):553–65.PubMedView ArticleGoogle Scholar
- Coulondre C, Miller JH, Farabaugh PJ, Gilbert W. Molecular basis of base substitution hotspots in Escherichia coli. Nature. 1978;274(5673):775–80.PubMedView ArticleGoogle Scholar
- Consortium HGS. Insights into social insects from the genome of the honeybee Apis mellifera. Nature. 2006;443(7114):931.View ArticleGoogle Scholar
- Zeng J, Yi SV. DNA methylation and genome evolution in honeybee: gene length, expression, functional enrichment covary with the evolutionary signature of DNA methylation. Genome Biol Evol. 2010;2:770–80.PubMedPubMed CentralView ArticleGoogle Scholar
- Wallberg A, Glémin S, Webster MT. Extreme recombination frequencies shape genome variation and evolution in the honeybee, Apis mellifera. PLoS Genet. 2015;11(4):e1005189.PubMedPubMed CentralView ArticleGoogle Scholar
- Wang X, Wheeler D, Avery A, Rago A, Choi J-H, Colbourne JK, Clark AG, Werren JH. Function and evolution of DNA methylation in Nasonia vitripennis. PLoS Genet. 2013;9(10):e1003872.PubMedPubMed CentralView ArticleGoogle Scholar
- Hunt BG, Glastad KM, Soojin VY, Goodisman MA. The function of intragenic DNA methylation: insights from insect epigenomes. Integr Comp Biol. 2013;53(2):319–28.PubMedView ArticleGoogle Scholar
- Sarda S, Zeng J, Hunt BG, Yi SV. The evolution of invertebrate gene body methylation. Mol Biol Evol. 2012;29(8):1907–16.PubMedView ArticleGoogle Scholar
- Keller TE, Han P, Yi SV. Evolutionary transition of promoter and gene body DNA methylation across invertebrate-vertebrate boundary. Mol Biol Evol. 2016;33(4):1019–28.PubMedView ArticleGoogle Scholar
- Vinogradov AE. Intron–genome size relationship on a large evolutionary scale. J Mol Evol. 1999;49(3):376–84.PubMedView ArticleGoogle Scholar
- Jeffares DC, Mourier T, Penny D. The biology of intron gain and loss. Trends Genet. 2006;22(1):16–22.PubMedView ArticleGoogle Scholar
- Hanrahan SJ, Johnston JS. New genome size estimates of 134 species of arthropods. Chromosom Res. 2011;19(6):809–23.View ArticleGoogle Scholar
- Ye YXH, Woolfit M, Huttley GA, Rances E, Caragata EP, Popovici J, O'Neill SL, McGraw EA. Infection with a virulent strain of Wolbachia disrupts genome wide-patterns of cytosine methylation in the mosquito Aedes aegypti. PLoS One. 2013;8(6):e66482.PubMedPubMed CentralView ArticleGoogle Scholar
- Negri H, Franchini A, Gonella E, Daffonchio D, Mazzoglio PJ, Mandrioli M, Alma A. Unravelling the Wolbachia evolutionary role: the reprogramming of the host genomic imprinting. Proc R Soc Lond B. 2009;276(1666):2485–91.View ArticleGoogle Scholar
- Almeida R, Stouthamer R. ITS-2 sequences-based identification of Trichogramma species in South America. Braz J Biol. 2015;75(4):974–82.PubMedView ArticleGoogle Scholar
- Gnerre S, Maccallum I, Przybylski D, Ribeiro FJ, Burton JN, Walker BJ, Sharpe T, Hall G, Shea TP, Sykes S, et al. High-quality draft assemblies of mammalian genomes from massively parallel sequence data. Proc Natl Acad Sci. 2011;108(4):1513–8.PubMedView ArticleGoogle Scholar
- Holt C, Yandell M. MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects. BMC Bioinformatics. 2011;12(1):491.PubMedPubMed CentralView ArticleGoogle Scholar
- Jeong G, Stouthamer R. Quantification of Wolbachia copy number in Trichogramma eggs (Hymenoptera: Trichogrammatidae): lysozyme treatment significantly improves total gene yield from the Gram-negative bacterium. Entomol Res. 2009;39(1):66–9.View ArticleGoogle Scholar
- Pintureau B, Grenier S, Boléat B, Lassablière F, Heddi A, Khatchadourian C. Dynamics of Wolbachia populations in transfected lines of Trichogramma. J Invertebr Pathol. 2000;76(1):20–5.PubMedView ArticleGoogle Scholar
- Parra G, Bradnam K, Korf I. CEGMA: a pipeline to accurately annotate core genes in eukaryotic genomes. Bioinformatics. 2007;23(9):1061–7.PubMedView ArticleGoogle Scholar
- Stanke M, Diekhans M, Baertsch R, Haussler D. Using native and syntenically mapped cDNA alignments to improve de novo gene finding. Bioinformatics. 2008;24(5):637–44.PubMedView ArticleGoogle Scholar
- Korf I. Gene finding in novel genomes. BMC Bioinformatics. 2004;5(1):59.PubMedPubMed CentralView ArticleGoogle Scholar
- Simão FA, Waterhouse RM, Ioannidis P, Kriventseva EV, Zdobnov EM. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics. 2015;31(19):3210–2.PubMedView ArticleGoogle Scholar
- Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014;30(9):1312–3.PubMedPubMed CentralView ArticleGoogle Scholar
- Owen AK, George J, Pinto JD, Heraty JM. A molecular phylogeny of the Trichogrammatidae (Hymenoptera: Chalcidoidea), with an evaluation of the utility of their male genitalia for higher level classification. Syst Entomol. 2007;32(2):227–51.View ArticleGoogle Scholar
- Conesa A, Gotz S, Garcia-Gomez JM, Terol J, Talon M, Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005;21(18):3674–6.PubMedView ArticleGoogle Scholar
- Grbic M, Van Leeuwen T, Clark RM, Rombauts S, Rouze P, Grbic V, Osborne EJ, Dermauw W, Ngoc PC, Ortego F, et al. The genome of Tetranychus urticae reveals herbivorous pest adaptations. Nature. 2011;479(7374):487–92.PubMedPubMed CentralView ArticleGoogle Scholar
- De Bie T, Cristianini N, Demuth JP, Hahn MW. CAFE: a computational tool for the study of gene family evolution. Bioinformatics. 2006;22(10):1269–71.PubMedView ArticleGoogle Scholar
- Xiao J-H, Yue Z, Jia L-Y, Yang X-H, Niu L-H, Wang Z, Zhang P, Sun B-F, He S-M, Li Z, et al. Obligate mutualism within a host drives the extreme specialization of a fig wasp genome. Genome Biol. 2013;14(12):R141.PubMedPubMed CentralView ArticleGoogle Scholar
- Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30(4):772–80.PubMedPubMed CentralView ArticleGoogle Scholar
- Talavera G, Castresana J. Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. Syst Biol. 2007;56(4):564–77.PubMedView ArticleGoogle Scholar
- Wheeler D, Redding AJ, Werren JH. Characterization of an ancient Lepidopteran lateral gene transfer. PLoS One. 2013;8(3):e59262.PubMedPubMed CentralView ArticleGoogle Scholar
- Burke GR, Walden KK, Whitfield JB, Robertson HM, Strand MR. Widespread genome reorganization of an obligate virus mutualist. PLoS Genet. 2014;10(9):e1004660.PubMedPubMed CentralView ArticleGoogle Scholar
- Martinson EO, Kelkar YD, Chang C-H, Werren JH. The evolution of venom by co-option of single-copy genes. Curr Biol. 2017;27(13):2007–2013.e2008.PubMedView ArticleGoogle Scholar
- Maere S, Heymans K, Kuiper M. BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics. 2005;21(16):3448–9.PubMedView ArticleGoogle Scholar
- Paradis E, Claude J, Strimmer K. APE: Analyses of Phylogenetics and Evolution in R language. Bioinformatics. 2004;20(2):289–90.PubMedView ArticleGoogle Scholar
- Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997;25(17):3389–402.PubMedPubMed CentralView ArticleGoogle Scholar
- Tajima F. Simple methods for testing the molecular evolutionary clock hypothesis. Genetics. 1993;135(2):599–607.PubMedPubMed CentralGoogle Scholar
- Paradis E. pegas: an R package for population genetics with an integrated-modular approach. Bioinformatics. 2010;26(3):419–20.PubMedView ArticleGoogle Scholar
- Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol. 2000;17(4):540–52.PubMedView ArticleGoogle Scholar
- Junier T, Zdobnov EM. The Newick Utilities: high-throughput phylogenetic tree processing in the UNIX shell. Bioinformatics. 2010;26(13):1669–70.PubMedPubMed CentralView ArticleGoogle Scholar
- R Core Team. R: a language and environment for statistical computing. In: R Foundation for Statistical Computing. Vienna: http://www.R-project.org; 2014.
- Fife D: fifer: a collection of miscellaneous functions. R package version 1.0. 2014.Google Scholar
- Sievers F, Wilm A, Dineen D, Gibson TJ, Karplus K, Li W, Lopez R, McWilliam H, Remmert M, Soding J, et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol. 2011;7:539.PubMedPubMed CentralView ArticleGoogle Scholar
- Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Mol Biol Evol. 2013;30(12):2725–9.PubMedPubMed CentralView ArticleGoogle Scholar
- Elango N, Yi SV. DNA methylation and structural and functional bimodality of vertebrate promoters. Mol Biol Evol. 2008;25(8):1602–8.PubMedView ArticleGoogle Scholar
- Urich MA, Nery JR, Lister R, Schmitz RJ, Ecker JR. MethylC-seq library preparation for base-resolution whole-genome bisulfite sequencing. Nat Protoc. 2015;10(3):475–83.PubMedPubMed CentralView ArticleGoogle Scholar
- Krueger F, Andrews SR. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics. 2011;27(11):1571–2.PubMedPubMed CentralView ArticleGoogle Scholar
- Galbraith DA, Yang X, Niño EL, Yi S, Grozinger C. Parallel epigenomic and transcriptomic responses to viral infection in honey bees (Apis mellifera). PLoS Path. 2015;11(3):e1004713.View ArticleGoogle Scholar
- Ruttner F. Geographical variability and classification. In: Rinderer TE, editor. Bee genetics and breeding. London: Academic Press; 1986. p. 23–56.View ArticleGoogle Scholar
- Oishi K, Sawa M, Hatakeyama M, Kageyama Y. Genetics and biology of the sawfly, Athalia rosae (Hymenoptera). Genetica. 1993;88(2):119–27.PubMedView ArticleGoogle Scholar
- Noyes J. Copidosoma truncatellum (Dalman) and C. floridanum (Ashmead)(Hymenoptera, Encyrtidae), two frequently misidentified polyembryonic parasitoids of caterpillars (Lepidoptera). Syst Entomol. 1988;13(2):197–204.View ArticleGoogle Scholar
- Hafez M. Notes on the introduction and biology of Microplitis demolitor Wilk. Bull Soc Ent d'Egypte. 1951;37:107–21.Google Scholar
- Rivers DB, Denlinger DL. Fecundity and development of the ectoparasitic wasp Nasonia vitripennis are dependent on host quality. Entomol Exp Appl. 1995;76(1):15–24.View ArticleGoogle Scholar
- Vilhelmsen L. The old wasp and the tree: fossils, phylogeny and biogeography in the Orussidae (Insecta, Hymenoptera). Biol J Linn Soc. 2004;82(2):139–60.View ArticleGoogle Scholar