Conifer-feeding bark beetles are important herbivores and decomposers in forest ecosystems. These species have evolved specializations to complete their life cycle in nutritionally poor wooden substrates and some can overwhelm tree defences and kill enormous numbers of trees during population outbreaks. The Eurasian spruce bark beetle (Ips typographus) is one tree-killing species; during a recent epidemic it destroyed >100 million m3 of spruce in a single year. We report a 236 Mb, highly contiguous I. typographus genome assembly using PacBio long-read sequencing. The final phased assembly had a contig N50 of 6.65 Mb in 272 contigs and was predicted to contain 23,923 protein-coding genes. Comparative genomic analysis including 11 additional coleopterans revealed expanded gene families associated with plant cell wall degradation, including pectinases, aspartyl proteases, and glycosyl hydrolases. This first whole-genome sequence from the genus Ips provides timely resources to address important questions about the evolutionary biology of the true weevils (Curculionidae), one of the most species-rich animal families. This resource will also allow for improved studies of functional genomics of both fundamental and applied value. In forests of today, increasingly stressed by global warming, this draft genome may ultimately assist in developing novel pest control strategies to mitigate outbreaks.
Article
A Highly Contiguous Genome Assembly of a Major Forest Pest, the Eurasian Spruce Bark Beetle Ips Typographus
https://doi.org/10.21203/rs.3.rs-182683/v1
This work is licensed under a CC BY 4.0 License
Journal Publication
published 09 Sep, 2021
Version 1
posted 12 Feb, 2021
You are reading this latest preprint version
Coleoptera
Curculionidae
Scolytinae
bark beetle
long-read sequencing
RNA-Seq
genome
de novo assembly
Ips
Conifer-feeding bark beetles (Coleoptera; Curculionidae; Scolytinae) are keystone species in forest ecosystems, contributing to wood decomposition and nutrient recycling through direct feeding and the action of beetle-associated microbiota 1. However, a few so-called aggressive species can also kill large numbers of healthy trees through pheromone-coordinated mass-attacks once their populations surpass a critical threshold density, quickly transforming entire forest landscapes at tremendous economic and ecological costs 2, 3. Since abiotic factors are important drivers for beetle population growth 4, outbreaks of aggressive species are expected to increase in frequency and severity due to climate change 5, 6. Beetle population growth is promoted by increasing temperatures that reduce both winter mortality and developmental time, allowing for the production of additional generations per year. Furthermore, the resistance of conifer trees to beetle attack is compromised during heat and drought stress 7.
The Eurasian spruce bark beetle (Ips typographus [L.]) is the most serious pest of Norway spruce (Picea abies [L.] Karst) and other spruce species in the beetle’s range, currently causing unprecedented forest destruction across the Palearctic region (Fig. 1). In Europe, I. typographus killed between 2 and 14 million m3 spruce annually from 1970 to 2010 8, but during the hot and dry summer of 2019, it killed more than 110 million m3 9. Beetle mass-attacks on trees are coordinated by an aggregation pheromone made up of cis-verbenol and 2-methyl-3-buten-2-ol. The pheromone is produced by males as they initiate boring in suitable host trees and attracts large numbers of both sexes 10. The pheromone component cis-verbenol is produced from the spruce monoterpene (−)-4S-α-pinene 11, whereas 2-methyl-3-buten-2-ol is produced de novo by the beetles 12. Pheromone attraction is modulated by other compounds produced by con- and heterospecific beetles as well as by host and non-host trees, highlighting the importance of chemosensation in this bark beetle 13, 14, 15. Due to the beetle´s economic and ecological importance, studies have started to address the molecular biology and function of chemosensation in I. typographus, but genetic resources are scarce and have thus far been limited to transcriptomic data 16, 17.
Tree-killing bark beetles like I. typographus thrive on the inner bark (Fig. 1a-d), one of the most nutritionally poor and recalcitrant organic substrates on earth 18. Abundant carbon-rich bio-polymers present in bark and adjoining sapwood, such as lignin, hemicellulose and cellulose may not be available to bark beetles as nutrients until prior degradation by fungi and other microbes 19. Bark beetles, including I. typographus, are associated with a holobiont of diverse microbiota, including gut endo-symbionts 20, 21, yeasts 22, and ecto-symbionts such as ophiostomatoid fungi that the beetles inoculate into attacked trees 23. Once established in the tree, these fungi may serve as food for developing beetles, metabolise conifer chemical defences, and accelerate tree death 24, 25, 26.
Although beetles (Coleoptera) constitute the largest order of the Metazoa, only 11 Coleoptera genomes have been published, of which only two belong to members of the 6,000 species strong Scolytinae subfamily (the mountain pine beetle, Dendroctonus ponderosae Hopkins, 27 and the coffee berry borer, Hypothenemus hampei Ferrari 28). Sequencing of additional Scolytinae genomes would enable comparative genomic studies and shed light on taxon-specific ecological adaptations in this highly specialized and important insect group. The main aim of this study was to assemble and annotate a high-quality genome of I. typographus. Secondly, we performed a comparative genomic analysis with 20 other metazoan genomes, specifically investigating Ips- and bark beetle-specific gene family expansions. We expect that our high-quality assembly of the I. typographus genome will be an important resource for forthcoming fundamental and applied studies on this important insect that endangers entire forest landscapes (Fig. 1e).
2.1 Insect rearing and nucleic acid extraction
To reduce heterozygosity in the beetles before sequencing, we ran 10 generations of sibling mating. The first mating pairs were taken from a laboratory-reared population of I. typographus originating from Lardal, SW Norway. The continuous culture was kept at the Swedish University of Agricultural Sciences in Alnarp, Sweden on local, freshly cut Norway spruce, following the procedures described in Anderbrant, Schlyter 29. Sexes were separated by pronotum hair density 30 and each mating pair had a 28 × 12–14 cm (length × diameter) spruce bolt providing food ad libitum 29. For each new sibling mating generation, we used siblings from offspring from one or occasionally two bolts (strictly separated), ensuring strict sibling mating. To reduce the risk of breeding failure, the 10 successful sibling mating generations were undertaken by using at least 10 spruce bolts per generation, with little or no observed inbreeding depression effects on fecundity or body mass over time. High molecular weight (HMW) DNA was extracted from around 100 individuals from this 10× inbred population to be used for high-throughput sequencing. Beetles were frozen in liquid nitrogen and pulverised using a pre-chilled mini-mortar and pestle. The resulting powder was transferred with a pre-chilled spatula to a microfuge tube containing lysis buffer and ball bearings. The sample was further homogenised using a Qiagen TissueLyzer by shaking for 1 min at 50 Hz. The optimal method for isolation of good quality HMW DNA from I. typographus was using the Qiagen Genomic Tip 100/G kit following the manufacturers’ instructions, except for a prolonged incubation time at 50°C overnight with gentle agitation using a modified lysis buffer (20 mM EDTA, 100 mM NaCl, 1% Triton® X-100, 500 mM Guanidine-HCl, 10 mM Tris, pH 7.9) replacing the standard Qiagen G2 buffer, and with the addition of Proteinase K to 0.8 mg/ml. This was supplemented with the addition of DNase-free RNase A (20 µg/ml) treatment and incubation for 30 min at 37°C, followed by centrifugation for 20 min at 12,000× g to pellet insoluble debris. The clarified lysate was then transferred to the QBT buffer-equilibrated Genomic Tip to proceed with the standard protocol.
2.2 Genome sequencing, assembly and evaluation
DNA samples were transported to the sequencing facility at the Uppsala Genome Center, Science for Life Laboratory, Uppsala University, Sweden for library preparation and sequencing on the PacBio RS II platform (Pacific Biosciences). Primary assembly of the PacBio long reads was performed using FALCON-kit v1.3.0 software and haplotype phasing was achieved using FALCON-unzip v1.2.0 with default settings 31. Contigs from the final assembly were aligned against each other using MUMmer 32 and redundant contigs removed. The completeness of the genome was assessed using metrics derived from read alignment and searches of single-copy orthologs. The Benchmarking Universal Single-Copy Orthologs (BUSCO v3.0.2) 33 tool was used to search the genome assembly against the insecta_odb9 database of 1,658 genes. In order to obtain an understanding of the chromosomal structure of long contigs, telomeric motifs were identified using the script FindTelomeres.py (https://github.com/JanaSperschneider/FindTelomeres). Genome size estimation was performed via k-mer counting with Jellyfish v2.3.0 34 using GenomeScope 2.0 35 from a genome survey of 364 million 150 bp Illumina reads equivalent to approximately 230-fold coverage.
2.3 Genome annotation
A custom repeat library was produced from the genome assembly using RepeatModeler v1.0.11 (http://www.repeatmasker.org/RepeatModeler/). This custom library, together with the Repbase library, was used with RepeatMasker v4.0.8 (http://www.repeatmasker.org/) to soft mask the assembly prior to annotation. RNA-Seq data from multiple beetle life stages and tissues (Supplementary Table 1) were aligned to the genome assembly using HiSat2 v2.1.0 36 and annotated using StringTie v1.3.3 37. The alignment features were passed to BRAKER2 38 as hints for training an AUGUSTUS model using GeneMark-ET. The transcriptome assembly from the above RNA-Seq data was used together with the published protein sequences from the genomes of three species of Coleoptera namely, D. ponderosae (Scolytinae), Anoplophora glabripennis Motschulsky (Cerambycidae), Tribolium castaneum Herbst (Tenebrionidae), and also the protein sequences from a further eight high-quality genomes, including Drosophila melanogaster Meigen (Diptera) and Homo sapiens Linné, as evidence for homology-based gene prediction using MAKER3 39, as outlined in Supplementary Fig. 1. Because transcriptome data is prone to misassembly and chimaeras it was only used for evidence and not for prediction. Protein sequences identified from the BUSCO searches were passed to the MAKER3 pipeline for training SNAP 40 along with the BRAKER2 trained AUGUSTUS model for ab initio predictions, using the HiSat2 RNA-Seq alignments as transcript-based evidence. Gene model predictions were retained if they were greater than 33 amino acids in length and were supported by at least one form of supporting evidence of either (i) a BLASTp match (E-value < 10− 10) to the non-redundant protein GenBank database, (ii) coverage by RNA-Seq data alignment, or (iii) containing a hit to the Pfam database. Several iterations of MAKER3 were performed to improve upon the prediction in subsequent runs.
2.4 Comparative genomics and phylogenomics
In order to identify expansions of gene families within the I. typographus genome, we searched the protein-coding sequences for Pfam 41 domains to assign gene function. We used HMMER v3.1 42 (hmmscan) to search the Pfam A database (release 32.0) for 13,841 different domains of 20 different species of Metazoa. Counts of each domain were collated for each species and domains that occurred multiple times in a protein sequence were counted only once. A Fisher’s exact test was then conducted iteratively using R, comparing the number of counts in Pfam families found in an individual genome, normalised by the total gene count for that species, against the background, which we defined as the average of the counts in the remaining species. Multiple testing corrections were done using the FDR method in R for all calculated p-values. A Pfam domain was considered expanded in I. typographus if it showed a corrected p-value < 0.05.
Protein sequences from I. typographus, D. ponderosae, T. castaneum, H. hampei and A. glabripennis were compared for orthology using all-against-all alignments (E-value of 10− 5) and clustered using OrthoVenn2 43 with an inflation value of 1.5. Phylogenetic inference from orthologous genes was undertaken by comparing the I. typographus gene set with the protein-coding sequences from 11 other species of Coleoptera (Supplementary Table 2) using OrthoFinder v2.4.0 44. Orthologous gene groups were used to build a rooted species tree that was visualised using FigTree v1.4.4 https://github.com/rambaut/figtree/releases. Presence of genes associated with detoxification and pesticide resistance in sequenced species of Coleoptera were identified based on Pfam domains contained within their respective protein sequences.
2.5 Transcriptome assembly and quantification of gene expression
Transcriptome libraries from different I. typographus life stages and tissue types (larval stages 1–3, pupae, adult beetle, male head, female head, callow male gut and fat body, callow female gut and fat body) were prepared at the Czech University of Life Sciences, Prague (Supplementary Table 1). Whole larvae, pupae and adult I. typographus were sampled along with discrete tissues that were dissected from adults and pooled under sterile conditions for RNA extraction. Total RNA was purified using the PureLink™ RNA Kit from Ambion (Invitrogen) following the manufacturer’s protocol. The integrity of the purified total RNA was checked using agarose gel electrophoresis and the 2100 Bioanalyzer system (Agilent Technologies, Inc). Total RNA samples with an integrity number (RIN) > 7 were selected for sequencing. Total RNA was quantified using a Qubit 2.0 Fluorometer (Thermo Fisher Scientific) with an RNA HS Assay Kit (Invitrogen) before sending for sequencing at Novogene, China, using the Illumina platform to generate a minimum of 30 million 150 bp paired-end reads per sample. Five biological replicates for each sample type were sequenced. Raw reads were processed using Trimmomatic v 45 and assembled using Trinity v2.8.2 46 with the default parameters except for --normalize_max_read_cov 100 --min_kmer_cov 3 --min_glue 3 -KMER_SIZE 23. Expression levels were measured by aligning quality-processed RNA-Seq reads to the genome assembly using HiSat2 v2.1.0. Aligned reads were sorted with SAMtools v1.5 47 and counts reported as transcripts per one million mapped reads (TPM) using StringTie v1.3.3. TPM values visualised in heatmaps were transformed to log2 (TPM + 1) and normalised across tissues using the scale function in R.
3.1 Genome sequencing, assembly and completeness assessment
A highly inbred line of I. typographus was successfully produced via full-sib mating for 10 generations. Whole-genome sequencing yielded over 4.5 million subreads totalling more than 50 gigabases of sequence equivalent to 211-fold coverage. The subread N50 was 19.3 kb with a mean read length of 12.4 kb. Estimation of genome size using a kmer-counting approach suggested a total haploid size of 221.9 Mb (Fig. 2), comparable with the mountain pine beetle (D. ponderosae) genome assembly of 204 Mb 27. The final, phased genome sequence was 236 Mb in total length and comprised 272 contigs with an N50 of 6.65 Mb; the longest contig being 16.9 Mb in size (Table 1). Seventy-eight percent of the genome assembly was contained in 36 contigs that were greater than 1 Mb in size (Supplementary Table 3). The five largest contigs were all greater than 10 Mb in length.
TABLE 1. Assembly statistics of the Ips typographus genome and comparisons with two other Coleoptera species, Dendroctonus ponderosae and Tribolium castaneum.
|
Statistic |
Ityp1.0 (this study) |
DendPond_male_1.01 |
Tcas5.22 |
|
Genome size (Mb) |
236.82 |
252.85 |
165.93 |
|
Number of contigs |
272 |
8,188 |
2,081 |
|
Contig N50 (Mb) |
6.65 |
0.63 |
15.27 |
|
Contig L50 |
12 |
87 |
5 |
|
Max. contig length (Mb) |
16.86 |
4.16 |
31.38 |
|
Min. contig length (kb) |
20.29 |
1.00 |
0.25 |
|
GC (%) |
35.21 |
35.91 |
33.86 |
|
BUSCO Completeness (insecta_odb9) |
98.6% |
95.4% |
99.3% |
|
Complete and single-copy |
1,535 (92.6%) |
1,489 (89.8%) |
1,643 (99.1%) |
|
Complete and duplicated |
99 (6%) |
93 (5.6%) |
4 (0.2%) |
|
Fragmented |
15 (0.9%) |
49 (3.0%) |
8 (0.5%) |
|
Missing |
9 (0.5%) |
27 (1.6%) |
3 (0.2%) |
|
RNA-Seq alignment rate (% total) |
93.56 |
- |
- |
|
RNA-Seq alignment rate (% concordantly exactly 1 time) |
83.73 |
- |
- |
Note: Comparison genomes downloaded from GenBank; 1Dendroctonus ponderosae GCA_000355655.1; 2Tribolium castaneum GCA_000002335.3.
Telomeric motifs are regions of repetitive sequences of DNA that indicate the ends of chromosomes. These motifs were identified at the ends of eight different contigs (five forward strands, three reverse strands). Telomeric motifs were located at one end of the five largest contigs (Supplementary Table 4) suggesting that each of these largest contigs start or finish at the end of a chromosome. The overall GC content was 33.21%. Approximately 28.2% of the genome contained repetitive sequence when masked using a custom library. This was slightly higher than in D. ponderosae (between 17% and 23%) 27, though lower than in T. castaneum (42%) 48. Analysis of completeness of the draft genome using the BUSCO tool revealed that 1,649 (99.5%) of the 1,658 genes in the insecta_odb9 database could be identified as present either partial or complete. Only nine genes (0.5%) were considered missing from the assembly. The I. typographus assembly statistics were of a quality comparable with the release of the enhanced T. castaneum genome sequence 49 and were considerably higher than most other Coleoptera genomes published to date. Thus, our evaluation indicates that the de novo assembly of the I. typographus genome is of high quality. Comparisons of contig sizes with other species and the presence of multiple telomeres suggest some of the largest contigs contained in this assembly may be approaching chromosome scale.
3.2 Genome annotation
Our approach to annotate the I. typographus genome exploited extensive transcriptomic resources and numerous publicly available protein sequences using ab initio and homology-based predictors. The final set of models consisted of 23,923 protein-coding genes (Table 2) with the majority (> 77%) assigned an annotation edit distance (AED) score of 0.5 or less (Supplementary Fig. 3). At least 84% (20,094) of the gene models were supported by alignments to our RNA-Seq read data. Searches of the annotated predicted protein sequences using BUSCOs from the insecta_odb9 libraries identified 1,584 (95.5%) of the 1,658 protein sequences in the Insecta dataset, with only 38 (2.3%) sequences missing (Supplementary Fig. 4). Comparing the outcome of BUSCO searches with the published Scolytinae (D. ponderosae and H. hampei) gene models, the I. typographus predictions had similar levels of completeness as these and were also comparable with the higher-quality coleopteran genome assemblies, such as the two other wood-feeding beetles (Agrilus planipennis and Anoplophora glabripennis; Supplementary Fig. 4). Moreover, read alignment of RNA-Seq data to annotated regions of the draft genome resulted in an average of 83.7% of reads mapping concordantly in pairs to the gene space. An overall average of 93.6% mapped reads indicates that the majority of transcripts captured in our RNA-Seq data can be found and are intact in the I. typographus gene set. Of the 23,923 predicted protein sequences, 59% contained Pfam domains. The number of gene models for I. typographus was considerably higher than that reported for D. ponderosae (13,088) 27, though comparable with the annotation of A. glabripennis 50 and H. hampei 28 with 22,035 and 19,222 predicted protein-coding genes, respectively. Taken together, these statistics suggest the production of a comprehensive set of gene models for I. typographus.
TABLE 2. Statistics of the predicted gene models from the Ips typographus draft assembly (Ityp1.0).
|
Statistic |
Ityp1.0 |
|
Number of genes |
23,923 |
|
Total gene length (bp) |
132,911,182 |
|
Longest gene (bp) |
318,767 |
|
Average gene length (bp) |
5,556 |
|
Average exon length (bp) |
324 |
|
Average intron length (bp) |
957 |
|
% of genome covered by genes |
56 |
|
Average exons per gene |
5 |
|
Average introns per gene |
4 |
|
Number containing Pfam domains |
14,145 |
3.3 Orthology and comparative analysis with other Coleopteran genomes
Comparison of orthologous genes shared among three beetle species closely related to I. typographus showed a core set of 6,991 shared gene clusters and a unique set of 811 clusters that were specific to I. typographus (Fig. 3a). Gene ontology enrichment analysis of these Ips-specific gene clusters revealed nine enriched categories, including DNA and RNA binding, regulation, and signalling (Supplementary Table 5). A total of 22 gene families were significantly expanded in I. typographus when compared with the 11 other published coleopteran genomes and a selection of other model invertebrates. A selection (17) of these expanded gene families are shown in Fig. 3b. The limited number of significantly expanded gene families discovered in I. typographus in this analysis reflects the comprehensive array of beetle species included in the dataset. Using this comprehensive approach, we were able to highlight gene families that appear distinctly relevant to the ecology of I. typographus and/or conifer-feeding bark beetles. A phylogenetic tree inferred from orthologous gene families shows the phylogenetic position of I. typographus relative to the other coleopterans included in this study (Fig. 3c).
Feeding on the stem bark of trees necessitates the ability to metabolize plant cell walls using endogenous enzymes or relying on the actions of associated microbiota. Notably, genes containing domains associated with plant cell wall degrading enzymes (PCWDEs) were significantly expanded in the I. typographus genome. Large expansions of PCWDEs were previously reported in the bark beetle D. ponderosae and the polyphagous cerambycid wood-borer A. glabripennis 27, 50. In particular, three families of glycosyl hydrolase (GH) enzymes were expanded in the conifer-feeding bark beetles I. typographus and D. ponderosae (Fig. 3b). Genes containing the Pfam domain GH48 (PF02011) were most abundant in these species, possessing eight (I. typographus) and six (D. ponderosae) proteins containing this domain. GH48 enzymes are reducing end-acting cellobiohydrolases and have been identified in several polyphagous insect species, but chiefly among the two Coleopteran superfamilies Chrysomeloidea and Curculionoidea 51. A detailed phylogenetic analysis of the Coleoptera and their GH gene repertoire has been reported previously 52. The most abundant expression of these genes in I. typographus occurred predominantly in the fat body, with some genes being specifically expressed during different larval stages, but none in pupae (Fig. 4a). This finding is surprising since these genes typically are highly expressed in guts, and further experiments are needed to investigate functional roles of these proteins in the fat body. GH enzymes are also commonly found in bacteria and more rarely in fungi 53 and their presence in insects is thought to be the result of horizontal gene transfer events from bacteria 51, 52, 54, 55. Fungal symbionts assist I. typographus in colonising spruce trees and may play essential roles in beetle nutrition and weakening host tree defences 25, 26. GH48 enzymes are thought to assist in the degradation of fungal chitin 56, which may be important for I. typographus as laboratory bioassays have shown a strong feeding preference of immature adults for media colonized by symbiotic fungi 25. Three separate tandem duplication events appear to have occurred in I. typographus since the establishment of GH48 genes in the Curculionoidea, seen as three pairs of genes occurring adjacent to each other in the genome (sequentially numbered gene models are found adjacently in the genome). Phylogenetic analysis of all the GH48 domain-containing genes in the 11 species of Coleoptera analysed in this study highlights that the eight genes from I. typographus share the highest similarity with those from the other Scolytinae species D. ponderosae and H. hampei (Fig. 4b).
The I. typographus genome contains 33 aspartyl protease (PF13650) domain-containing genes. Although these genes are also expanded in the wood-borer A. glabripennis, this is more than any of the other species included in this study, and clearly distinguishes I. typographus from D. ponderosae that has only a single gene containing this domain. Aspartyl protease is a digestive protease and has been implicated in proteolytic digestion in insects 57. Both pectinesterase (PF01095) and polysaccharide lyase (PF14683) gene families were found enriched in the three bark beetles. GH28 genes were also expanded in the bark beetles, but also in the wood borers A. glabripennis and especially the emerald ash borer, Agrilus planipennis (Buprestidae). These gene families are known to be involved in the degradation of pectin, which is a major component of primary plant cell walls. In several beetle species (D. ponderosae, H. hampei, A. glabripennis, and L. decemlineata) there is evidence suggesting a fungal origin of the GH28 genes 58, and references therein. Expansions of genes involved in cell wall degradation may extend the capacity of these species to digest their recalcitrant host plants efficiently.
Searches of protein families within 12 species of Coleoptera revealed differences in the repertoire of genes important for detoxification and pesticide resistance. Interestingly, comparison between I. typographus and D. ponderosae revealed many similarities in gene family abundance (Table 3). However, these two conifer-infesting bark beetles did not display an enrichment for gene families involved in xenobiotic metabolism when compared to other agriculturally important Coleopterans. In particular, the number of cytochrome P450 genes in the I. typographus genome (86 genes) is lower than in all the other species included in our analysis, except for H. hampei (67 genes). However, the number of P450 genes in D. ponderosae is only marginally higher (93 genes), and many of these genes were shown to form species-specific expansions mainly within the CYP6 and CYP9 subfamilies 27. Hence, it is possible that Scolytinae specialists on conifers detoxify host defences (such as abundant conifer monoterpenes and phenolics) using a smaller, but specialized, repertoire of P450 enzymes, as compared to generalist beetles feeding on diverse angiosperms. Conifers in the pine family (Pinaceae) are rich in preformed terpenes and conifer specialists might therefore be expected to have numerous P450s to detoxify these. However, I. typographus seems to be less tolerant to terpenes than Dendroctonus spp 59. This may appear paradoxical considering its lifestyle, but I. typographus may have a strategy of quickly reducing the levels of tree defences by mass-attack and assistance from fungal symbionts 60. Correspondingly, Norway spruce trees have less preformed defences and rely more on capability for induced response for their resistance against bark beetle attacks 61.
TABLE 3. Comparison of protein families associated with detoxification and pesticide resistance between Ips typographus and 11 other Coleoptera species. The number of proteins containing the specific Pfam domain for each family is given.
Note: Atum, Aethina tumida; Apla, Agrilus planipennis; Agla, Anoplophora glabripennis; Cmac, Callosobruchus maculatus; Dpon, Dendroctonus ponderosae; Dvir, Diabrotica virgifera; Hham, Hypothenemus hampei; Ityp, Ips typographus; Ldec, Leptinotarsa decemlineata; Nves, Nicrophorus vespilloides; Otau, Onthophagus taurus; Tcas, Tribolium
Colour codes: dark green, Conifer feeders; light green Angiosperm feeders; no colour, non-herbivores.We assembled and annotated the genome of the Eurasian spruce bark beetle Ips typographus, an important pest of spruce across the Palearctic. This highly contiguous, phased assembly comprises 236 Mb of sequence in 272 contigs with an N50 of 6.65 Mb and contains 23,923 annotated genes. Our analyses of this assembly suggest gene family expansions of primarily plant cell wall degrading enzymes, of which aspartyl protease domain-containing genes stand out as particularly expanded. P450 enzyme-encoding genes involved in hormone synthesis and catabolism of toxins are reduced in numbers. This first whole-genome sequence from the genus Ips provides timely resources for population genetic studies and studies addressing important questions about the evolutionary biology and ecology of the true weevils. The genome is also expected to facilitate both fundamental and applied studies of functional genomics, as well as gene knockdown/knockout experiments. The essential odorant receptors are one example of a gene family that could be targeted to limit outbreaks, since interfering with the beetles’ odour-guided host and mate finding behaviours likely will reduce their reproductive success 17, 62. Hence, this genomic resource may serve as a basis for improved and innovative management of an increasing threat to stressed trees in the Anthropocene.
ACKNOWLEDGEMENTS
The authors would like to acknowledge the support of the National Genomics Infrastructure (NGI) / Uppsala Genome Center and UPPMAX for providing assistance in massive parallel sequencing and computational infrastructure. Work performed at NGI / Uppsala Genome Center has been funded by RFI / VR and Science for Life Laboratory, Sweden. Dr Jan Bílý (Czech University of Life Sciences, Prague) is acknowledged for technical support during RNA samples preparation for tissue transcriptome study. Infrastructural support and salary for A.R., E.G-W., and F.S. were obtained from project EXTEMIT-K CZ.02.1.01/0.0/0.0/15_003/0000433 financed by OP RDE at Czech University of Life Sciences, Prague. M.N.A. was funded by the Swedish Research Council FORMAS (grants #217-2014-689 and #2018-01444). C.L. acknowledges support from the Swedish Research Council VR (#2017-03804). P.K. was funded by the Research Council of Norway (grant #249958/F20).
CONFLICT OF INTEREST
The authors declare no competing interests.
AUTHOR CONTRIBUTIONS
D.P. performed the genome annotation, all bioinformatic analyses and wrote the manuscript, with M.N.A contributing to the initial draft. M.N.A. and F.S. conceived, initiated, and designed the study with E.G-W. and P.K., F.S. performed the sib-mating process with A.C., H.V. performed DNA extraction, C.L. provided resources for the bioinformatics, A.R. and E.G-W. undertook tissue transcriptome sequencing for genome annotation. All authors commented on, improved and approved the final manuscript.
DATA AVAILABILITY STATEMENT
This Whole Genome Shotgun project has been deposited at DDBJ/ENA/GenBank under the accession JADDUH000000000. The version described in this paper is version JADDUH010000000. All sequence data relating to this study are available under the BioProject accession numbers PRJNA671615 and PRJNA679450.
ORCID
0000-0001-9807-8524 Martin N. Andersson
0000-0002-1244-0308 Fredrik Schlyter
0000-0003-3237-3525 Amit Roy
0000-0001-6323-7791 Daniel Powell
0000-0002-7205-0715 Paal Krokene
0000-0002-7752-5871 Amrita Chakraborty
- Edmonds RL, Eglitis A. The role of the Douglas-fir beetle and wood borers in the decomposition of and nutrient release from Douglas-fir logs. Canadian Journal of Forest Research 19, 853-859 (1989).
- Hlásny T, et al. Living with bark beetles: impacts, outlook and management options. In: From Science to Policy 8). European Forest Institute (2019).
- Raffa KF, Andersson MN, Schlyter F. Host selection by bark beetles: Playing the odds in a high‐stakes game. In: Advances in Insect Physiology (eds Blomquist G, Tittinger C). Elsevier Ltd. (2016).
- Biedermann PHW, et al. Bark beetle population dynamics in the Anthropocene: Challenges and solutions. Trends in Ecology & Evolution 34, 914-924 (2019).
- Kurz WA, et al. Mountain pine beetle and forest carbon feedback to climate change. Nature 452, 987-990 (2008).
- Marini L, et al. Climate drivers of bark beetle outbreak dynamics in Norway spruce forests. Ecography 40, 1426-1435 (2017).
- Allen CD, et al. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. Forest Ecology and Management 259, 660-684 (2010).
- Seidl R, Schelhaas M-J, Rammer W, Verkerk PJ. Increasing forest disturbances in Europe and their impact on carbon storage. Nature climate change 4, 806-810 (2014).
- Ebner G. Significantly more damaged wood in 2019.) (2020).
- Schlyter F, Birgersson G, Byers JA, Löfqvist J, Bergström G. Field response of spruce bark beetle, Ips typographus, to aggregation pheromone candidates. Journal of Chemical Ecology 13, 701-716 (1987).
- Lindström M, Norin T, Birgersson G, Schlyter F. Variation of enantiomeric composition of a-pinene in Norway spruce, Picea abies, and its influence on production of verbenol isomers by Ips typographus in the field. Journal of Chemical Ecology 15, 541-548 (1989).
- Lanne B, Ivarsson P, Johnsson P, Bergström G, Wassgren A-B. Biosynthesis of 2-methyl-3-buten-2-ol, a pheromone component of Ips typographus (Coleoptera: Scolytidae). Insect Biochemistry 19, 163-167 (1989).
- Andersson MN, Larsson MC, Blazenec M, Jakus R, Zhang Q-H, Schlyter F. Peripheral modulation of pheromone response by inhibitory host compound in a beetle. Journal of Experimental Biology 213, 3332-3339 (2010).
- Schlyter F, Birgersson G, Leufvén A. Inhibition of attraction to aggregation pheromone by verbenone and ipsenol: Density regulation mechanisms in bark beetle Ips typographus. Journal of Chemical Ecology 15, 2263-2277 (1989).
- Zhang Q-H, Schlyter F. Olfactory recognition and behavioural avoidance of angiosperm nonhost volatiles by conifer-inhabiting bark beetles. Agricultural and Forest Entomology 6, 1-20 (2004).
- Andersson MN, et al. Antennal transcriptome analysis of the chemosensory gene families in the tree killing bark beetles, Ips typographus and Dendroctonus ponderosae (Coleoptera: Curculionidae: Scolytinae). BMC Genomics 14, 198 (2013).
- Yuvaraj JK, et al. Putative ligand binding sites of two functionally characterized bark beetle odorant receptors. (bioRxiv) BMC Biology revised 2020-12-21, accepted 202-12-21, (2021).
- Filipiak M, Weiner J. Nutritional dynamics during the development of xylophagous beetles related to changes in the stoichiometry of 11 elements. Physiological Entomology 42, 73-84 (2017).
- Kirk TK, Cowling EB. Biological decomposition of solid wood. In: The Chemistry of Solid Wood (ed Rowell R). ACS Publications. https://pubs.acs.org/doi/abs/10.1021/ba-1984-0207.ch012 (1984).
- Chakraborty A, Ashraf MZ, Modlinger R, Synek J, Schlyter F, Roy A. Unravelling the gut bacteriome of Ips (Coleoptera: Curculionidae: Scolytinae): Identifying core bacterial assemblage and their ecological relevance. Scientific reports 10, 1-17 (2020a).
- Chakraborty A, Modlinger R, Ashraf MZ, Synek J, Schlyter F, Roy A. Core mycobiome and their ecological relevance in the gut of five Ips bark beetles (Coleoptera: Curculionidae: Scolytinae). Frontiers in Microbiology 11, 2134 (2020b).
- Davis TS. The ecology of yeasts in the bark beetle holobiont: A century of research revisited. Microbial ecology 69, 723-732 (2015).
- Kirisits T. Fungal associates of european bark beetles with special emphasis on the ophiostomatoid fungi. In: Bark and Wood Boring Insects in Living Trees in Europe, a Synthesis (eds Lieutier F, Day KR, A. B, Grégoire J-C, Evans HF). Springer Netherlands (2007).
- Christiansen E. Ceratocystis polonica inoculated in Norway spruce: Blue‐staining in relation to inoculum density, resinosis and tree growth. European Journal of Forest Pathology 15, 160-167 (1985).
- Kandasamy D, Gershenzon J, Andersson MN, Hammerbacher A. Volatile organic compounds influence the interaction of the Eurasian spruce bark beetle (Ips typographus) with its fungal symbionts. ISME Journal 13, 1788-1800 (2019).
- Zhao T, Kandasamy D, Krokene P, Chen J, Gershenzon J, Hammerbacher A. Fungal associates of the tree-killing bark beetle, Ips typographus, vary in virulence, ability to degrade conifer phenolics and influence bark beetle tunneling behavior. Fungal Ecology 38, 71-79 (2019).
- Keeling CI, et al. Draft genome of the mountain pine beetle, Dendroctonus ponderosae Hopkins, a major forest pest. Genome Biology 14, R27 (2013).
- Vega FE, et al. Draft genome of the most devastating insect pest of coffee worldwide: The coffee berry borer, Hypothenemus hampei. Scientific Reports 5, 1-17 (2015).
- Anderbrant O, Schlyter F, Birgersson G. Intraspecific competition affecting parents and offspring in the bark beetle Ips typographus. Oikos 45, 89-98 (1985).
- Schlyter F, Cederholm I. Separation of the sexes of living spruce bark beetles, Ips typographus (L.), (Coleoptera: Scolytidae). Journal of Applied Entomology 92, 42-47 (1981).
- Chin CS, et al. Phased diploid genome assembly with single-molecule real-time sequencing. Nature Methods 13, 1050-1054 (2016).
- Kurtz S, et al. Versatile and open software for comparing large genomes. Genome biology 5, (2004).
- Simão FA, Waterhouse RM, Ioannidis P, Kriventseva EV, Zdobnov EM. BUSCO: Assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210-3212 (2015).
- Marçais G, Kingsford C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27, 764-770 (2011).
- Ranallo-Benavidez TR, Jaron KS, Schatz MC. GenomeScope 2.0 and Smudgeplot for reference-free profiling of polyploid genomes. Nature Communications 11, (2020).
- Kim D, Langmead B, Salzberg SL. HISAT: A fast spliced aligner with low memory requirements. Nature Methods 12, 357-360 (2015).
- Pertea M, Pertea GM, Antonescu CM, Chang T-C, Mendell JT, Salzberg SL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nature Biotechnology 33, 290-295 (2015).
- Hoff KJ, Lange S, Lomsadze A, Borodovsky M, Stanke M. BRAKER1: Unsupervised RNA-Seq-based genome annotation with GeneMark-ET and AUGUSTUS. Bioinformatics 32, 767-769 (2015).
- Holt C, Yandell M. MAKER2 : An annotation pipeline and genome-database management tool for second-generation genome projects. BMC Bioinformatics 12, 491-491 (2011).
- Korf I. Gene finding in novel genomes. BMC Bioinformatics 5, 59 (2004).
- Finn RD, et al. Pfam: the protein families database. Nucleic acids research 42, D222-230 (2014).
- Potter SC, Luciani A, Eddy SR, Park Y, Lopez R, Finn RD. HMMER web server: 2018 update. Nucleic Acids Research 46, W200-W204 (2018).
- Xu L, et al. OrthoVenn2: A web server for whole-genome comparison and annotation of orthologous clusters across multiple species. Nucleic Acids Research 47, W52-W58 (2019).
- Emms DM, Kelly S. OrthoFinder: Phylogenetic orthology inference for comparative genomics. Genome Biology 20, 238-238 (2019).
- Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114-2120 (2014).
- Haas BJ, et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nature Protocols 8, 1494-1512 (2013).
- Li H, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078-2079 (2009).
- Wang S, Lorenzen MD, Beeman RW, Brown SJ. Analysis of repetitive DNA distribution patterns in the Tribolium castaneum Genome Biology 9, 1-14 (2008).
- Herndon N, et al. Enhanced genome assembly and a new official gene set for Tribolium castaneum. BMC Genomics 21, 47-47 (2020).
- McKenna DD, et al. Genome of the Asian longhorned beetle (Anoplophora glabripennis), a globally significant invasive species, reveals key functional and evolutionary innovations at the beetle–plant interface. Genome Biology 17, 227-227 (2016).
- Eyun SI, et al. Molecular evolution of glycoside hydrolase genes in the western corn rootworm (Diabrotica virgifera virgifera). PLoS ONE 9, (2014).
- McKenna DD, et al. The evolution and genomic basis of beetle diversity. Proceedings of the National Academy of Sciences USA 116, 24729-24737 (2019).
- Berger E, Zhang D, Zverlov VV, Schwarz WH. Two noncellulosomal cellulases of Clostridium thermocellum, Cel9I and Cel48Y, hydrolyse crystalline cellulose synergistically. FEMS Microbiology Letters 268, 194-201 (2007).
- Chu C-C, et al. Patterns of differential gene expression in adult rotation-resistant and wild-type western corn rootworm digestive tracts. Evolutionary Applications 8, 692-704 (2015).
- Pauchet Y, Heckel DG. The genome of the mustard leaf beetle encodes two active xylanases originally acquired from bacteria through horizontal gene transfer. Proceedings of the Royal Society B: Biological Sciences 280, (2013).
- Fujita K, Shimomura K, Yamamoto K-i, Yamashita T, Suzuki K. A chitinase structurally related to the glycoside hydrolase family 48 is indispensable for the hormonally induced diapause termination in a beetle. Biochemical and Biophysical Research Communications 345, 502-507 (2006).
- Santamaría ME, et al. Digestive proteases in bodies and faeces of the two-spotted spider mite, Tetranychus urticae. Journal of Insect Physiology 78, 69-77 (2015).
- Schoville SD, et al. A model species for agricultural pest genomics: the genome of the Colorado potato beetle, Leptinotarsa decemlineata (Coleoptera: Chrysomelidae). Scientific reports 8, 1-18 (2018).
- Everaerts C, Grégoire J-C, Merlin J. The toxicity of Norway spruce monoterpenes to two bark beetle species and their associates. In: Mechanisms of Woody Plant Defenses Against Insects (eds Mattson WJ, Levieux J, Bernard-Dagan C). Springer (1988).
- Franceschi VR, Krokene P, Christiansen E, Krekling T. Anatomical and chemical defenses of conifer bark against bark beetles and other pests. New phytologist 167, 353-376 (2005).
- Schiebe C, et al. Inducibility of chemical defences in Norway spruce bark is correlated with unsuccessful mass attacks by the spruce bark beetle. Oecologia 170, 183-198 (2012).
- Andersson MN, Newcomb RD. Pest control compounds targeting insect chemoreceptors: Another silent spring? Frontiers in Ecology and Evolution 5, 5 (2017).
There is NO Competing Interest.
- IpsgenomeSupplMaterialFinalComm.Biol.docx
Supplementary Material