High quality de novo long read genome assembly and annotation of resistance protein families for saw toothed grain beetle

High quality de novo long read genome assembly and annotation of resistance protein families for saw toothed grain beetle | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article High quality de novo long read genome assembly and annotation of resistance protein families for saw toothed grain beetle Hatim Almansouri This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5784528/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Saw-toothed grain beetle ( Oryzaephilus surinamensis ) negatively impacts food products, which are considered as common insect pests in several countries. This study reports 159 Mb high quality long reads de novo genome assembly of O. surinamensis using PacBio-Sequel sequencing technology. The genome was assembled into 3043 contigs with the largest contigs 2.35 Mb and N50 length of 0.177 Mb, L50 171 contigs, 255.8X coverage, GC content of 29.69%, 54,156 microsatellite sequences and BUSCO evaluation revealed 98.6%. Genome annotation identified 11,227 genes and predicted 34,082 protein-coding genes (93.6% Busco score), of which 32,173 (94.39%) were annotated by Pfam database. The annotation of protein families identified important genes for pesticide and Enironmental resistance. Furthermore, Wolbachia endosymbiotic identified with 1.93 Mb genome size and 2060 predicted genes while Candidatus Shikimatogenerans Silvanidophilus endosymbiotic identified with 1.92 Mb genome size and 1223 predicted genes. This study provides a new reference genome and comprehensive resource for O. surinamensis and highlights important genes and pathways that influence agriculture. Oryzaephilus surinamensis PacBio-Sequel sequencing endosymbionts comparative orthologous analysis pest genomics Introduction Order Coleoptera is the largest of all insect orders, with more than 340,00 species; however, relatively few genomes have been sequenced and assembled compared with those in other orders, such as Hymenoptera and Diptera (Thomas et al., 2020 ; Mayhew, 2002). Coleoptera belongs to the Silvanidae family, which includes O. surinamensis , a common pest of stored products in Canada, the United States, Britain, Australia, Asia, Africa, and South America (Sinha and Watters, 1985). It can infest various food products, such as neem seed kernels, dates, rice, wheat, raisins, and stored products, thus having negative impacts on food quality and safety (Sinha and Watters, 1985) (Govindaraj J et al., 2014). Moreover, O. surinamensis can easily survive and grow in several types of food products, thereby raising the need to improve the management of these invasive pest insects. Several pest management methods are available for controlling invasive insects. Long-term pest management using insecticides can induce insecticide resistance (Lorini et al., 2007 ). In most insects, insecticide resistance and the detoxification of plant chemical components are related to the activity of P450 and glutathione S-transferase genes (Hazzouri et al., 2020 ). These genes are responsible for detoxification and insecticide resistance in several insects such as O. surinamensis and Rhynchophorus ferrugineus (Boyer et al., 2012 ) (Hazzouri et al., 2020 ). Specifically, O. surinamensis is one of the major stored-product insect pests that is resistant to common pesticides, such as fenitrothion, pirimiphos-methyl, and chlorpyrifos methyl, and has the ability to detoxify natural insecticides such as essential oils (Boyer et al., 2012 ) In addition, behavioral changes linked to resistance were observed when treated with high insecticide concentrations (Boyer et al., 2012 ). Thus, endosymbionts have the potential to control insect pests. Kingan et al. ( 2019 ) suggested the disruption of bacterial symbiont transmission from females to offspring to potentially control invasive insects. Similarly, Wolbachia bacterial endosymbionts have been found in 66% of insect species, such as O. surinamensis (Kiefer et al., 2022 ), Callosobruchus chinensis (Kondo et al., 2002 ), Drosophila melanogaster , and Culex quinquefasciatus (Glaser et al., 2010). It exhibits active reproductive manipulation rules in the host, O. surinamensis , leading to a strong female bias (Kiefer et al., 2022 ). C. silvanidophilus is another endosymbiont found in O. surinamensis that plays an important role as a precursor of aromatic amino acids for the synthesis of the host cuticle via the shikimate pathway (Kiefer et al., 2022 ). These studies have suggested that endosymbionts of O. surinamensis can be a control factor limiting the invasive insect pest O. surinamensis . This study provides a comprehensive genomic and functional annotation resource that supports the development of effective pest management strategies for O. surinamensis . It is providing a baseline for understanding the genomic and protein annotations of O. surinamensis , which are highly contiguous, complete, and less fragmented. In addition, metabolic pathways and protein functional annotations were analyzed to identify genes that play important roles in the control of the insect pest O. surinamensis . This raises concerns about potential detoxification and insecticide resistance genes in O. surinamensis that could affect pest management. Method and materials DNA extraction and sequencing O. surinamensis adults were obtained from stored dates located in Jeddah, Kingdom of Saudi Arabia. Sample of 70 individual were frozen at − 80°C until the time of DNA extraction. The protocol of Qiagen Genomic 20 tip protocol (Qiagen, Hilden, Germany) used for DNA extraction. The frozen individuals were ground to a fine powder in liquid nitrogen using a mortar and pestle and collected in a 2-mL tube. The powdered sample was mixed with G2 buffer and RNase A (100 mg/µl) as suggested in protocol.io (Tom Harrop, 2018 ). This was followed by incubation with a thermomixer for 30 min at 37°C and 700 rpm agitation. Subsequently, 60 µl of Qiagen Proteinase K (19133, Qiagen, Hilden, Germany) was added and samples were incubated at 50°C and 400 rpm agitation for 2 h. Following centrifugation for 20 min at room temperature, the supernatant was purified using genomic 20 tip columns according to the manufacturer's recommendations. The DNA concentration was determined using the Qubit dsDNA HS Assay Kit (Q33230, Waltham, MA, USA) and a NanoDrop 8000 (Thermo Fisher), and the integrity of gDNA was visualized with a gDNA 165 kb kit (FP-1002-0275) by running a Femto Pulse (Agilent, Santa Clara, USA). The library was prepared using 150 ng of gDNA and CLR SMRT cells were prepared using the SMRT Cell Express Template Prep Kit 2.0 (Pacific Biosciences, Menlo Park, CA, USA, 100-938-900), following the CLR low-input protocol by PacBio. Final SMRTcells were annealed with v4 and polymerase with Sequel Binding Kit 2.1 and Internal Control Kit 1.0 (Pacific Biosciences, 101-429-300), SMRT Cell 1M v2 (Pacific Biosciences, 101-008-000), and sequenced for 10-h movies with 2 h pre-extension time. Raw read quality Full genome sequencing was performed and raw reads of O. surinamensis SRR22318063 were checked, processed, and polished using PacBio SMRTlink V7.0. The LongQC quality control tool (Fukasawa et al., 2019) was used with -x pb-sequel and default settings to check the raw read quality and the presence of changes in read length, GC content, and per-read coverage plots. Endosymbiont analysis Endosymbiont raw reads of Wolbachia SRR24786162 and S. silvanidophilus SRR25179365 were extracted from O. surinamensis SRR22318063 using minimap2 v2.25 (Li, 2018 ) with -ax asm20 alignment option between raw reads O. surinamensis SRR22318063 from this study and NCBI obtained assembly GCF_018200315.1 S. silvanidophilus and GCA_002907405.1 Wolbachia then confirmed the extraction by Bold Identification v0.0.27 (Yang et al., 2020 ) and MLST v2.11 (Jolley and Maiden, 2010) and assign the genome statistics by Quast v5.0.2 (Gurevich et al., 2013 ). Endosymbiont genome assembly was performed using the Canu v1.9 assembler in default settings (Koren et al., 2017 ). Genome and protein annotations were performed using Prodigal (Hyatt et al., 2010 ) and genome quality was assessed using BUSCO v5.2.2 with the Insecta database odb10 and CheckM2 v1.0.2 (Chklovski et al., 2023 ) for genome completeness and contamination and then annotated by BLAST + and hmmscan searches against protein databases and HAMAP HMMs library using Prokka v1.14.6 (Seemann T, 2014 ). Moreover, orthologous between Wolbachia PRJNA975352 and other strains of Wolbachia was examined using Orthofinder v2.3.12 (Emms and Kelly, 2015 ). The phylogenetic tree was visualized using Fig Tree version 1.4.0 (Rambaut, 2006). Genome assembly and annotation The genome assembly of de novo O. surinamensis was performed using Canu v1.9 assembler (Koren et al., 2017 ). Haplotigs and overlaps were removed from the assembled genome using PurgeDups v1.0.1 (Guan et al., 2020 ). In addition, the quality assessment of the genome assembly was examined using QUAST-LG v5.0.2 (Gurevich et al., 2013 ), whereas the completeness of the genome assembly of O. surinamensis was assessed using BUSCO v5.2.2 with the Insecta database odb10 (Simao et al., 2015 ). GlimmerHMM (Majoros et al., 2004 ) used with default settings to predict genes while Augustus v3.4.0 (Stanke et al., 2006 ) used to predict proteins of O. surinamensis . Completeness of the predicted protein of O. surinamensis was assessed using BUSCO v5.2.2 with the Insecta database odb10 (Simao et al., 2015 ). O. surinamensis GCA004796505.1 obtained from NCBI and genome assembly was examined using QUAST v5.0.2. Simple sequence repeat identification MISA (Beier et al., 2017 ) was used to characterize the different types of SSRs sequences using default settings. The frequency of SSRs was identified based on the percentage of the total number of SSRs per megabase of insect genome size. The percentage SSRs density was calculated by dividing the identified SSRs sequences by the total size of the examined sequences. Functional and metabolic pathway annotation The assembled unigenes were aligned against NCBI-NR and UniProtKB/Swiss-Prot with an E-value of 10 − 5 accessed June 2022. Genes were identified based on the best hits against known sequences. Metabolic pathways were annotated using several protein databases, including KOfam, Pfam, eggNOG, and NCBI protein family models (NPFM). Furthermore, functional annotation and metabolic pathways were predicted by the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, gene ontology (GO), cluster of orthologous groups (COG), and eukaryotic orthologous groups (KOG) with a BLASTX E-value of 10 − 5 , accessed in Jun 2022. Metabolic pathways and functional annotations were searched against NOG, NCBI, Pfam, Kofam, and TCDB, using Mantis (Jones et al., 2014 ). PFAM-A annotation HmmSearch (Sun et al., 2007) used to search Pfam databases (Finn RD et al., 2014) (Bateman et al., 2004 ) for homologous protein sequences with predicted protein of O. surinamensis by using hidden Markov models (HMMs). HmmSearch used with default setting and E-value of 10 − 5 to identify protein families overall and specifically highlighted detoxification and resistance proteins families. Results and Discussion Raw read quality A total of 10 Gb of PacBio raw reads and 41 Gb of total bases were generated, with an N50 read length of 5961 bp and a mean read length of 4128 bp. The quality of raw reads was examined using the quality control tool LongQC (Fukasawa et al., 2019). Several changes in the read length, GC content, and per-read coverage plots were assumed to be endosymbiont reads (Supplementary material 01). Wolbachia endosymbiont SRR24786162 and S. silvanidophilus endosymbiont PRJNA988171 were detected and excluded for further analyses. Endosymbiont analysis The genome assembly of the Wolbachia endosymbiont revealed a 1.93 Mb genome size in 15 contigs with N50 531 Kb and 21,112.4X coverage. It was predicted to have 2060 genes, 2106 CDS, 3 rRNA genes, and 34% GC. Additionally, five conserved genes were identified (gatB, coxA, hcpA, ftsZ, and fbpA) (Supplementary material 02). Similarly, Mavingui et al. ( 2012 ) reported a Wolbachia genome size of 1.24 Mb with an average GC content of 33.7%. The quality of the genome assembly was assessed by BUSCO to be 82.2%, which is comparable to the different strains of Wolbachia (Supplementary material 03). CheckM2 v1.0.2 (Chklovski et al., 2023 ) showed completeness of 99.31% and 10.74% contamination. Wolbachia PRJNA975352 has 2118 proteins with 1988 orthologs in 1142 orthogroups belonging to different strains of Wolbachia , as published by Kiefer et al. ( 2022 ) (Supplementary material 04 and 05). Based on this, the phylogenetic tree grouped the Wolbachia strains into two branches based on orthologs. The first branch of the phylogenetic tree contained Wolbachia strains related to group A, B, E and D. Wolbachia endosymbiont PRJNA975352 strain wOS shows less genetic differences with Wolbachia strain related to group B with high orthologs. Conversely, the second branch contains Wolbachia strains related to group C and F that shows higher genetic differences with strain from the first branch (Supplementary material 06). These findings are consistent with the phylogenetic tree reported by Kiefer et al. ( 2022 ). S. silvanidophilus PRJNA988171 extracted from the host raw reads O. surinamensis SRR22318063. The genome assembly of S. silvanidophilus exhibited a genome size of 1.92 Mb in 393 contigs with N50 6 Kb with a total coverage of 21,264X. It was predicted to have 1223 genes, 1081 CDS and 38% GC. Due to the difficulties in sequencing the host DNA with endosymbiont, BUSCO analysis showed 41 fragmented genes, 58 missing genes, 22 complete and single copy genes and 3 duplicated genes. The quality results with CheckM2 v1.0.2 (Chklovski et al., 2023 ) showed a completeness of 9.88% and 1.8% contamination. Similarly, a study by Kiefer et al. ( 2021 ) detected S. silvanidophilus endosymbionts in O. surinamensis with genome size of 0.30 Mb, 16.2% GC, 299 genes with a BUSCO score of 11 fragmented genes, 45 missing genes, and 68 complete and single copies. Genome assembly, annotation, and prediction Full genome sequencing was performed on O. surinamensis PRJNA992804 isolates from food stores in the Jeddah region of Saudi Arabia. The genome assembly of O. surinamensis comprised 3043 contigs with genome coverage of 255.8X and the total length of the genome was estimated to be 159 Mb. The read N50 was contig length was 0.17 Mb with L50 171 contigs and the average length of contigs was 52.3 Kb with largest contigs 2.35 Mb (Table 1 ). The GC content was 29.6%, and the number of mismatches, N’s per 100 kb was 0. The genome annotation of O. surinamensis had a mean gene length of 4410.52 bp, mean exon length of 203.40 bp, and mean intron length of 1067.12 bp, where 97.53% of the genome contigs were above 10 kb in length. The BUSCO score indicated the genome quality assessment 98.6% with 1347 out of 1367 marker genes covered by the Insecta database 10, where complete and single copy was (89.17%) 1219, complete and duplicate (9.4%) 129, and fragmented genes (0.29%) 4, and 16 genes (1.17%) were missing (Simao et al., 2015 ). Genome annotation of O. surinamensis predicted 11,227 genes with 31,187 coding sequences (CDS) that had an average length of 279 bp (8194 CDS had > 300 bp whereas 1453 CDS had > 1 Kb) and a total length of 8.7 Mb for all CDS. A total of 11,584 messenger RNA (mRNA) with an average length of 1492 bp were present (9281 mRNA > 300 bp whereas 5200 mRNA > 1 kb). Besides, 131 ribosomal RNA were detected with average length 596.82 bp, 5S rRNA was 97 with average length 101.97 bp, 5.8S rRNA was 16 with average length 149.62 bp, and 28S rRNA was 18 with average length 3661 bp. Furthermore, O. surinamensis had 34,082 predicted protein-coding genes with an average length of 2666 amino acids using Augustus v3.4.0 (Stanke et al., 2006 ). the quality of the predicted proteins evaluated using BUSCO in protein mode with the Insecta database 10 of BUSCO, which indicated completeness at 93.6%, with the lowest duplicated 6.8% for O. surinamensis. The choice of library preparation method can influence sequence quality, genome assembly, and further annotation and analysis (Haendiges et al., 2021 ). Therefore, the genome was assembled using PacBio reads resulting in a more contiguous, complete and better genome size than the assembled genome of O. surinamensis GCA004796505.1, which was sequenced using MiSeq Illumina. It had a smaller genome assembly size of 104 Mb, with 11,890 contigs, a GC ratio of 29.2%, 23.86 mismatches (N’s) per 100 Kbp and 24,810 bp total number of uncalled bases (N’s). This lower estimated genome assembly is inconsistent with the findings of this study, as well as those of Sharaf et al. ( 2010 ), who used flow cytometry to estimate the genome size of O. surinamensis around 151.5 Mb and 154.1 Mb. In addition, O. surinamensis GCA004796505.1 had lower predicted genes 10,580 and 26,231 CDS compared to this study. Simple sequence repeat identification In this study, simple sequence repeats (SSRs) identified, also known as microsatellites, in the genome of O. surinamensis. It has 54,156 identified SSRs with 0.034 SSRs density, 339.81 SSRs frequency in 159.37 Mb genome size (Table 2). Different types of SSRs were observed in gradual decrease however, mononucleotide SSRs were the dominant, which is consistent with the findings for the Batocera horsfieldi beetle (Peng et al., 2021). Also, mono-and trinucleotides were more abundant than other types of SSRs, which was also observed in the mosquito species (Wang et al., 2019 ) and 6 plant species (Zhao et al., 2015 ). Specifically, dinucleotide SSRs were more abundant than trinucleotides, which was also observed in the study by Fan and Chu ( 2007 ) and in the Batocera horsfieldi beetle (Peng et al., 2021). Functional and metabolic pathway annotation This study provides the first molecular resource that highlights the metabolic and functional annotation of saw-toothed grain beetles. The putative functions of 11,227 unigenes were identified by alignment using DIAMOND and BLASTX with a cut-off E-value of 10 − 5 (Buchfink et al., 2000). Functional annotation using NCBI-NR, KOG, and UniProtKB/Swiss-Prot showed that the percentage of identical matches was less than 60%, which was lower than expected. This may be due to the lack of species related to the Silvanidae family or those closely related to O. surinamensis in these databases (Supplementary material 07, 08, and 09). Metabolic pathways were annotated using several protein databases, including KOfam, Pfam, eggNOG, and NCBI protein family models (NPFM). Generally, O. surinamensis had the highest number of queries identified proteins observed in the Pfam-A database that shows the highest identified proteins 32,173 among other protein databases with average reference protein length of 157.8 amino acids, whereas an average query protein length was 722.1 amino acids. Overall, the average identified reference proteins were less than 800 amino acids, whereas Pfam-A and NCBI had the lowest, which may contain novel sequences with extremely few protein sequences matching because of the lower number of species related to the Silvanidae family or closely related to O. surinamensis in the NR database (Table 3 ). For example, NCBI has the reference protein TIGR03150 with a length of 407 amino acids. The protein is KAS-II, and FabF is involved in the condensation step of fatty acid biosynthesis with a query protein length of 2070 amino acids. COG annotation COG is standard database for identifying orthologous gene functions using 25 functional classifications. The conserved regions in the genes support the classification based on homologous relationships. Generally, the cluster of orthologous gene function analysis of O. surinamensis classified (21.08%) 7186 of 34,082 genes into the COG functional category. Single transduction mechanisms, general function prediction, translation, ribosomal structure and biogenesis, post-translational modifications, protein turnover, and chaperones showed the highest findings in COG annotation (Supplementary material 10). KEGG pathway analysis The metabolic pathway annotation results were interpreted as 394 KEGG modules that showed 22 KEGG metabolic pathways that mapped the annotated genes to the KEGG database. A total of 22 KEGG pathways were detected, with a total of 3322 unigenes for O. surinamensis . The KEGG pathway distribution showed that O. surinamensis had the highest number of annotated general metabolic pathways (858 unigenes), followed by carbohydrate metabolism (354), amino acid metabolism (278), and biosynthesis of secondary metabolites (272). Among the 3322 unigenes, 490 were mapped to 5 biosynthesis pathways: biosynthesis of secondary metabolites, amino acids, nucleotide sugars, cofactors, and other secondary metabolites. For example, the biosynthesis of secondary metabolites was the highest, with 272 unigenes, whereas the lowest was 26 unigenes for the biosynthesis of nucleotide sugars (Supplementary material 11). Gene ontology analysis It is a comprehensive and large source of information on the functions of genes in several species within the Tree of Life. A total of 42,769 GO terms were assigned to 1499 genes with 5977 hits for O. surinamensis . Most GO terms were assigned to biological process with 2119 hits, followed by molecular function (1278 hits), protein class (1170 hits), cellular components (869 hits), and GO pathway categories (541 hits) (Supplementary material 12 and 13). The highest number of terms in the cellular components category was cellular anatomy, with 770 genes. The molecular function category contained a large number of genes for catalytic activity and binding (633 and 374, respectively). The biological process category had a large number of genes involved in cellular, metabolic, and biological regulation (695, 446, and 321, respectively). The protein class category contained a high number of genes (462) encoding metabolite interconversion enzymes. The GO pathway category showed a large number of genes (37 and 29) involved in the pentose phosphate pathway and threonine biosynthesis, respectively. In addition, this study presents the first molecular resources that provide metabolic and functional annotations for saw-toothed grain beetles. These findings have GO annotated 13.35% (1499 genes) of the total 11,227 genes from O. surinamensis , which is consistent with the percentage of annotated GO genes in the study by Kumar et al. (2020), who assigned GO annotation to 10,534 of 87,451 (12.04%) genes from the coconut rhinoceros beetle Oryctes rhinoceros L PRJNA486419. Based on these results, most annotation databases had a limited number of species related to the Silvanidae family or were closely related to O. surinamensis . PFAM-A annotation of O. surinamensis resistance protein families Several protein families are common between O. surinamensis and other insects, such as Rhynchophorus ferrugineus and palm weevils (Hazzouri et al., 2020 ). The PFAM annotation of O. surinamensis revealed 5108 (39,898 occurrences) protein families. P450 cytochromes, Glutathione S-Transferase-N and ABC transporters were the most abundant among the eight common protein families associated with detoxification and pesticide resistance (Table 4). For instance, P450 cytochromes (PF00067) are large family of enzymes that involved in xenobiotic detoxification and degradation of endogenous molecules (Keeling et al., 2013). Generally, beetles and weevils detoxify plant chemical components using genes encoding detoxifying enzymes, such as P450 and Glutathione S-transferases (Hazzouri et al., 2020 ). This study indicated 158 P450 cytochromes identified for O. surinamensis , which is higher than the P450 found in R. ferruiius , D. ponderosae , and D. melanogaster that have 120, 85, and 86, respectively (Hazzouri et al., 2020 ; Keeling et al., 2013). Table 4: Protein families of pesticide resistance for O. surinamensis PRJNA992804. Annotation of protein family related to resistance to environment stress The odorant protein families (PF01395 and PF01161) support insects in detecting pheromones and odorants and have been identified in O. surinamensis in 19 PBP/GOBP families (Table 5 ). This allows the insect to locate infected palm trees using released volatiles in the air as well as aggregate pheromones released by males to coordinate attacks on trees (Hazzouri et al., 2020 ). Besides, heat shock proteins (HSPs; PF00011, PF00012, and PF00183) are of three types—HSP20, HSP70 and HSP 90. The annotation detected 28 HSP in O. surinamensis , including 15 HSP70, 8 HSP20, and 5 HSP90 (Table 5 ). In contrast, the number of HSP in O. surinamensis was lower than that in the desert beetle Microdera punctipennis , which has 72 HSP that are important for adaptation and survival in extreme desert environments (Lu X et al., 2014 ). Pest management control This study provides genomic and proteomic annotations to support the development of pest management strategies for O. surinamensis . P450 enzymes play crucial roles in the detoxification of plant chemical compounds. Oil compounds from Laurus nobilis have demonstrated potential for the control of invasive pests, such as R. dominica and T. castaneum (Jemaa et al., 2012). Although the toxic activity of 158 P450 enzymes was identified for O. surinamensis , Laurus nobilis was efficient against major stored-product insect pests (Jemaa et al., 2012). Another approach involves the management of O. surinamensis using pheromones and odorants (Table 3 ). Similar strategies have been successful in controlling insect pest of R. ferrugineus (Antony et al., 2016 ) and the apple insect pest Cydia pomonella (Balasko et al., 2020 ). Additionally, O. surinamensis may require longer time to eliminate compared to other species when using aeration method to cool stored grains at temperatures between 13°C and 20°C (David and ramanyam, 2006). Furthermore, disrupting the transmission of bacterial symbionts from female insects to their offspring holds promise as a strategy to control invasive insect pests, such as Lycorma delicatula (Kingan et al., 2019 ). Based on this, the endosymbionts of O. surinamensis have the potential to become controlling factors that limit the invasive insect pests of O. surinamensis . It exhibits active reproductive manipulation rules in its host, O. surinamensis , which leads to a strong female bias (Kiefer et al., 2022 ). In addition, S. silvanidophilus is another endosymbiont found in O. surinamensis , which can be a growth control factor for O. surinamensis , as it plays an important role in providing aromatic amino acid precursors for cuticle synthesis in the host via the shikimate pathway (Kiefer et al., 2022 ). In addition, most insect pests, such as Cephalonomia tarsalis have natural parasitoids and predators that mainly attack O. surinamensis larvae (David and Ramanyam, 2006). However, the use of biological control agents such as C. tarsalis may lead to an increase in the predator population or the movement of predators to other areas. Further research is recommended because current pest management strategies for O. surinamensis are inefficient. Conclusions This study provided assembled and annotated genome of the O. surinamensis using PacBio long read technology. The raw reads obtained from genomic sequencing were de novo assembled into a high-quality genome, which can serve as a valuable mapping reference for future genetic studies on the saw-toothed grain beetle and closely related species. Interestingly, it has been identified two crucial bacterial endosymbionts within O. surinamensis that hold promise for insect pest management strategies. Comprehensive analyses yielded additional annotation information about O. surinamensis , highlighting several areas relevant to pest control and management. Specifically, this study highlighted detoxification genes, heat shock genes, odorant receptor genes and other significant insecticide resistance genes in the saw-toothed grain beetle. The data presented in this study contribute to the discovery of essential candidate genes for pest control and provide a foundational resource for future investigations into this invasive insect pest species. Moreover, it is recommended to employ advanced sequencing technologies, including both next-generation and third-generation methodologies, to conduct a comprehensive analysis of the insect's transcriptome. Declarations Data availability The raw reads and genome assemblies of O. surinamensis have been submitted to NCBI under the accession number SRR22318063 and PRJNA992804, respectively. Endosymbiont bacteria Wolbachia and S. silvanidophilus data related to this study are available under accession PRJNA975352 and PRJNA988171. Supplementary material and other relative data are available from Zenodo https://zenodo.org/records/14466150. Acknowledgments Special thanks to the management of KAUST Core Labs as well as to Bioscience Core Lab and Supercomputing Core Lab for providing support for computing resources. Thanks to Ming Sin Cheung, Patrick Alexander Putra, Karen Carty and Nagarajan Kathiresan for the support. In fond memory of our talented colleague Kamel Jabbari. Funding This was funded by King Abdullah University of Science and Technology. Conflict of interests The author declares no conflict of interest. References Antony B, Soffan A, Jakše J, Abdelazim MM, Aldosari SA, Aldawood AS, Pain A (2016) Identification of the genes involved in odorant reception and detection in the palm weevil Rhynchophorus ferrugineus, an important quarantine pest, by antennal transcriptome analysis. BMC Genomics 17:69 Balasko M, Bazok R, Mikac K, Lemic D, Zivkovic I (2020) Pest management challenges and control practice in codling moth. 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J Comput Biol 7:203–214 Zhao H, Yang L, Peng Z, Sun H, Yue X, Lou Y, Dong L, Wang L, Gao Z (2015) Developing genome-wide microsatellite markers of bamboo and their applications on molecular marker assisted taxonomy for accessions in the genus Phyllostachys. Sci Rep 5:8018 Tables Tables 1 to 5 are available in the Supplementary Files section. Supplementary Materials Supplementary Materials are not available with this version. Additional Declarations The authors declare no competing interests. Supplementary Files Tables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5784528","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":399123295,"identity":"77a8cf56-ee18-40a1-82d0-20a4f34a5434","order_by":0,"name":"Hatim Almansouri","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIie3OMUvEMBTA8RcOnISuPUTuKyQUKnLV+yothWbJcGMHhzfd6trJz5BJcOsZuC7BrpEulQ4uDgVXEVvvhlOi5+iQPwSSkB8vAC7XP4yWAOXeMaK73eQXMvlCspEQPET2U38gVb2+N3A7O/PU5iRf1oFX8OcW8nmCnmptZKFTUAIadldk2VTTJvSNYAiaJ+hn1EZouSVEmuNwirSJwAiCZKUGAnZSd59kIWs9kodoZvgTkveBeFVvJWY7JZGlGEkZUhMzJDgQEPYppqNK0CaVJkvPkaYB0y+siDc8WPliaf9Y0r2KvLmQtVo/4tslu6l42/dX89Nrr5I2soPfL+JhHf383uVyuVwH+gDOlWw3H/xHvgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-9477-4477","institution":"King Abdullah University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Hatim","middleName":"","lastName":"Almansouri","suffix":""}],"badges":[],"createdAt":"2025-01-08 00:00:56","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-5784528/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5784528/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73407225,"identity":"31825e0f-2ef4-47d4-9043-5d15564aab2b","added_by":"auto","created_at":"2025-01-09 15:34:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":721913,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5784528/v1/3e0801c1-3511-401d-a25b-f4aff5187beb.pdf"},{"id":73406882,"identity":"137a0693-014c-4d92-894c-7c4e8ab552db","added_by":"auto","created_at":"2025-01-09 15:26:16","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":561148,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-5784528/v1/f8f338376c7ac3c8f0c23a65.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eHigh quality de novo long read genome assembly and annotation of resistance protein families for saw toothed grain beetle\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOrder Coleoptera is the largest of all insect orders, with more than 340,00 species; however, relatively few genomes have been sequenced and assembled compared with those in other orders, such as Hymenoptera and Diptera (Thomas et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mayhew, 2002). Coleoptera belongs to the Silvanidae family, which includes \u003cem\u003eO. surinamensis\u003c/em\u003e, a common pest of stored products in Canada, the United States, Britain, Australia, Asia, Africa, and South America (Sinha and Watters, 1985). It can infest various food products, such as neem seed kernels, dates, rice, wheat, raisins, and stored products, thus having negative impacts on food quality and safety (Sinha and Watters, 1985) (Govindaraj J et al., 2014). Moreover, \u003cem\u003eO. surinamensis\u003c/em\u003e can easily survive and grow in several types of food products, thereby raising the need to improve the management of these invasive pest insects.\u003c/p\u003e \u003cp\u003eSeveral pest management methods are available for controlling invasive insects. Long-term pest management using insecticides can induce insecticide resistance (Lorini et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). In most insects, insecticide resistance and the detoxification of plant chemical components are related to the activity of P450 and glutathione S-transferase genes (Hazzouri et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These genes are responsible for detoxification and insecticide resistance in several insects such as \u003cem\u003eO. surinamensis\u003c/em\u003e and \u003cem\u003eRhynchophorus ferrugineus\u003c/em\u003e (Boyer et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) (Hazzouri et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Specifically, \u003cem\u003eO. surinamensis\u003c/em\u003e is one of the major stored-product insect pests that is resistant to common pesticides, such as fenitrothion, pirimiphos-methyl, and chlorpyrifos methyl, and has the ability to detoxify natural insecticides such as essential oils (Boyer et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) In addition, behavioral changes linked to resistance were observed when treated with high insecticide concentrations (Boyer et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThus, endosymbionts have the potential to control insect pests. Kingan et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) suggested the disruption of bacterial symbiont transmission from females to offspring to potentially control invasive insects. Similarly, \u003cem\u003eWolbachia\u003c/em\u003e bacterial endosymbionts have been found in 66% of insect species, such as \u003cem\u003eO. surinamensis\u003c/em\u003e (Kiefer et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), \u003cem\u003eCallosobruchus chinensis\u003c/em\u003e (Kondo et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), \u003cem\u003eDrosophila melanogaster\u003c/em\u003e, and \u003cem\u003eCulex quinquefasciatus\u003c/em\u003e (Glaser et al., 2010). It exhibits active reproductive manipulation rules in the host, \u003cem\u003eO. surinamensis\u003c/em\u003e, leading to a strong female bias (Kiefer et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). \u003cem\u003eC. silvanidophilus\u003c/em\u003e is another endosymbiont found in \u003cem\u003eO. surinamensis\u003c/em\u003e that plays an important role as a precursor of aromatic amino acids for the synthesis of the host cuticle via the shikimate pathway (Kiefer et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These studies have suggested that endosymbionts of \u003cem\u003eO. surinamensis\u003c/em\u003e can be a control factor limiting the invasive insect pest \u003cem\u003eO. surinamensis\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eThis study provides a comprehensive genomic and functional annotation resource that supports the development of effective pest management strategies for \u003cem\u003eO. surinamensis\u003c/em\u003e. It is providing a baseline for understanding the genomic and protein annotations of \u003cem\u003eO. surinamensis\u003c/em\u003e, which are highly contiguous, complete, and less fragmented. In addition, metabolic pathways and protein functional annotations were analyzed to identify genes that play important roles in the control of the insect pest \u003cem\u003eO. surinamensis\u003c/em\u003e. This raises concerns about potential detoxification and insecticide resistance genes in \u003cem\u003eO. surinamensis\u003c/em\u003e that could affect pest management.\u003c/p\u003e"},{"header":"Method and materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDNA extraction and sequencing\u003c/h2\u003e \u003cp\u003e \u003cem\u003eO. surinamensis\u003c/em\u003e adults were obtained from stored dates located in Jeddah, Kingdom of Saudi Arabia. Sample of 70 individual were frozen at \u0026minus;\u0026thinsp;80\u0026deg;C until the time of DNA extraction. The protocol of Qiagen Genomic 20 tip protocol (Qiagen, Hilden, Germany) used for DNA extraction. The frozen individuals were ground to a fine powder in liquid nitrogen using a mortar and pestle and collected in a 2-mL tube. The powdered sample was mixed with G2 buffer and RNase A (100 mg/\u0026micro;l) as suggested in protocol.io (Tom Harrop, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This was followed by incubation with a thermomixer for 30 min at 37\u0026deg;C and 700 rpm agitation. Subsequently, 60 \u0026micro;l of Qiagen Proteinase K (19133, Qiagen, Hilden, Germany) was added and samples were incubated at 50\u0026deg;C and 400 rpm agitation for 2 h. Following centrifugation for 20 min at room temperature, the supernatant was purified using genomic 20 tip columns according to the manufacturer's recommendations. The DNA concentration was determined using the Qubit dsDNA HS Assay Kit (Q33230, Waltham, MA, USA) and a NanoDrop 8000 (Thermo Fisher), and the integrity of gDNA was visualized with a gDNA 165 kb kit (FP-1002-0275) by running a Femto Pulse (Agilent, Santa Clara, USA). The library was prepared using 150 ng of gDNA and CLR SMRT cells were prepared using the SMRT Cell Express Template Prep Kit 2.0 (Pacific Biosciences, Menlo Park, CA, USA, 100-938-900), following the CLR low-input protocol by PacBio. Final SMRTcells were annealed with v4 and polymerase with Sequel Binding Kit 2.1 and Internal Control Kit 1.0 (Pacific Biosciences, 101-429-300), SMRT Cell 1M v2 (Pacific Biosciences, 101-008-000), and sequenced for 10-h movies with 2 h pre-extension time.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRaw read quality\u003c/h3\u003e\n\u003cp\u003eFull genome sequencing was performed and raw reads of \u003cem\u003eO. surinamensis\u003c/em\u003e SRR22318063 were checked, processed, and polished using PacBio SMRTlink V7.0. The LongQC quality control tool (Fukasawa et al., 2019) was used with -x pb-sequel and default settings to check the raw read quality and the presence of changes in read length, GC content, and per-read coverage plots.\u003c/p\u003e\n\u003ch3\u003eEndosymbiont analysis\u003c/h3\u003e\n\u003cp\u003eEndosymbiont raw reads of \u003cem\u003eWolbachia\u003c/em\u003e SRR24786162 and \u003cem\u003eS. silvanidophilus\u003c/em\u003e SRR25179365 were extracted from \u003cem\u003eO. surinamensis\u003c/em\u003e SRR22318063 using minimap2 v2.25 (Li, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) with -ax asm20 alignment option between raw reads \u003cem\u003eO. surinamensis\u003c/em\u003e SRR22318063 from this study and NCBI obtained assembly GCF_018200315.1 \u003cem\u003eS. silvanidophilus\u003c/em\u003e and GCA_002907405.1 \u003cem\u003eWolbachia\u003c/em\u003e then confirmed the extraction by Bold Identification v0.0.27 (Yang et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and MLST v2.11 (Jolley and Maiden, 2010) and assign the genome statistics by Quast v5.0.2 (Gurevich et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Endosymbiont genome assembly was performed using the Canu v1.9 assembler in default settings (Koren et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Genome and protein annotations were performed using Prodigal (Hyatt et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and genome quality was assessed using BUSCO v5.2.2 with the Insecta database odb10 and CheckM2 v1.0.2 (Chklovski et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) for genome completeness and contamination and then annotated by BLAST\u0026thinsp;+\u0026thinsp;and hmmscan searches against protein databases and HAMAP HMMs library using Prokka v1.14.6 (Seemann T, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Moreover, orthologous between \u003cem\u003eWolbachia\u003c/em\u003e PRJNA975352 and other strains of \u003cem\u003eWolbachia\u003c/em\u003e was examined using Orthofinder v2.3.12 (Emms and Kelly, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The phylogenetic tree was visualized using Fig Tree version 1.4.0 (Rambaut, 2006).\u003c/p\u003e\n\u003ch3\u003eGenome assembly and annotation\u003c/h3\u003e\n\u003cp\u003eThe genome assembly of de novo \u003cem\u003eO. surinamensis\u003c/em\u003e was performed using Canu v1.9 assembler (Koren et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Haplotigs and overlaps were removed from the assembled genome using PurgeDups v1.0.1 (Guan et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In addition, the quality assessment of the genome assembly was examined using QUAST-LG v5.0.2 (Gurevich et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), whereas the completeness of the genome assembly of \u003cem\u003eO. surinamensis\u003c/em\u003e was assessed using BUSCO v5.2.2 with the Insecta database odb10 (Simao et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). GlimmerHMM (Majoros et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) used with default settings to predict genes while Augustus v3.4.0 (Stanke et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) used to predict proteins of \u003cem\u003eO. surinamensis\u003c/em\u003e. Completeness of the predicted protein of \u003cem\u003eO. surinamensis\u003c/em\u003e was assessed using BUSCO v5.2.2 with the Insecta database odb10 (Simao et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). \u003cem\u003eO. surinamensis\u003c/em\u003e GCA004796505.1 obtained from NCBI and genome assembly was examined using QUAST v5.0.2.\u003c/p\u003e\n\u003ch3\u003eSimple sequence repeat identification\u003c/h3\u003e\n\u003cp\u003eMISA (Beier et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) was used to characterize the different types of SSRs sequences using default settings. The frequency of SSRs was identified based on the percentage of the total number of SSRs per megabase of insect genome size. The percentage SSRs density was calculated by dividing the identified SSRs sequences by the total size of the examined sequences.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eFunctional and metabolic pathway annotation\u003c/h2\u003e \u003cp\u003eThe assembled unigenes were aligned against NCBI-NR and UniProtKB/Swiss-Prot with an E-value of 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e accessed June 2022. Genes were identified based on the best hits against known sequences. Metabolic pathways were annotated using several protein databases, including KOfam, Pfam, eggNOG, and NCBI protein family models (NPFM).\u003c/p\u003e \u003cp\u003eFurthermore, functional annotation and metabolic pathways were predicted by the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, gene ontology (GO), cluster of orthologous groups (COG), and eukaryotic orthologous groups (KOG) with a BLASTX E-value of 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e, accessed in Jun 2022. Metabolic pathways and functional annotations were searched against NOG, NCBI, Pfam, Kofam, and TCDB, using Mantis (Jones et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePFAM-A annotation\u003c/h3\u003e\n\u003cp\u003eHmmSearch (Sun et al., 2007) used to search Pfam databases (Finn RD et al., 2014) (Bateman et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) for homologous protein sequences with predicted protein of \u003cem\u003eO. surinamensis\u003c/em\u003e by using hidden Markov models (HMMs). HmmSearch used with default setting and E-value of 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e to identify protein families overall and specifically highlighted detoxification and resistance proteins families.\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eRaw read quality\u003c/h2\u003e\n \u003cp\u003eA total of 10 Gb of PacBio raw reads and 41 Gb of total bases were generated, with an N50 read length of 5961 bp and a mean read length of 4128 bp. The quality of raw reads was examined using the quality control tool LongQC (Fukasawa et al., 2019). Several changes in the read length, GC content, and per-read coverage plots were assumed to be endosymbiont reads (Supplementary material 01). \u003cem\u003eWolbachia\u003c/em\u003e endosymbiont SRR24786162 and \u003cem\u003eS. silvanidophilus\u003c/em\u003e endosymbiont PRJNA988171 were detected and excluded for further analyses.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eEndosymbiont analysis\u003c/h2\u003e\n \u003cp\u003eThe genome assembly of the \u003cem\u003eWolbachia\u003c/em\u003e endosymbiont revealed a 1.93 Mb genome size in 15 contigs with N50 531 Kb and 21,112.4X coverage. It was predicted to have 2060 genes, 2106 CDS, 3 rRNA genes, and 34% GC. Additionally, five conserved genes were identified (gatB, coxA, hcpA, ftsZ, and fbpA) (Supplementary material 02). Similarly, Mavingui et al. (\u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e) reported a \u003cem\u003eWolbachia\u003c/em\u003e genome size of 1.24 Mb with an average GC content of 33.7%. The quality of the genome assembly was assessed by BUSCO to be 82.2%, which is comparable to the different strains of \u003cem\u003eWolbachia\u003c/em\u003e (Supplementary material 03). CheckM2 v1.0.2 (Chklovski et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e) showed completeness of 99.31% and 10.74% contamination.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e PRJNA975352 has 2118 proteins with 1988 orthologs in 1142 orthogroups belonging to different strains of \u003cem\u003eWolbachia\u003c/em\u003e, as published by Kiefer et al. (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e) (Supplementary material 04 and 05). Based on this, the phylogenetic tree grouped the \u003cem\u003eWolbachia\u003c/em\u003e strains into two branches based on orthologs. The first branch of the phylogenetic tree contained \u003cem\u003eWolbachia\u003c/em\u003e strains related to group A, B, E and D. \u003cem\u003eWolbachia\u003c/em\u003e endosymbiont PRJNA975352 strain wOS shows less genetic differences with \u003cem\u003eWolbachia\u003c/em\u003e strain related to group B with high orthologs. Conversely, the second branch contains \u003cem\u003eWolbachia\u003c/em\u003e strains related to group C and F that shows higher genetic differences with strain from the first branch (Supplementary material 06). These findings are consistent with the phylogenetic tree reported by Kiefer et al. (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eS. silvanidophilus\u003c/em\u003e PRJNA988171 extracted from the host raw reads \u003cem\u003eO. surinamensis\u003c/em\u003e SRR22318063. The genome assembly of \u003cem\u003eS. silvanidophilus\u003c/em\u003e exhibited a genome size of 1.92 Mb in 393 contigs with N50 6 Kb with a total coverage of 21,264X. It was predicted to have 1223 genes, 1081 CDS and 38% GC. Due to the difficulties in sequencing the host DNA with endosymbiont, BUSCO analysis showed 41 fragmented genes, 58 missing genes, 22 complete and single copy genes and 3 duplicated genes. The quality results with CheckM2 v1.0.2 (Chklovski et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e) showed a completeness of 9.88% and 1.8% contamination. Similarly, a study by Kiefer et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) detected \u003cem\u003eS. silvanidophilus\u003c/em\u003e endosymbionts in \u003cem\u003eO. surinamensis\u003c/em\u003e with genome size of 0.30 Mb, 16.2% GC, 299 genes with a BUSCO score of 11 fragmented genes, 45 missing genes, and 68 complete and single copies.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eGenome assembly, annotation, and prediction\u003c/h2\u003e\n \u003cp\u003eFull genome sequencing was performed on \u003cem\u003eO. surinamensis\u003c/em\u003e PRJNA992804 isolates from food stores in the Jeddah region of Saudi Arabia. The genome assembly of \u003cem\u003eO. surinamensis\u003c/em\u003e comprised 3043 contigs with genome coverage of 255.8X and the total length of the genome was estimated to be 159 Mb. The read N50 was contig length was 0.17 Mb with L50 171 contigs and the average length of contigs was 52.3 Kb with largest contigs 2.35 Mb (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The GC content was 29.6%, and the number of mismatches, N\u0026rsquo;s per 100 kb was 0. The genome annotation of \u003cem\u003eO. surinamensis\u003c/em\u003e had a mean gene length of 4410.52 bp, mean exon length of 203.40 bp, and mean intron length of 1067.12 bp, where 97.53% of the genome contigs were above 10 kb in length. The BUSCO score indicated the genome quality assessment 98.6% with 1347 out of 1367 marker genes covered by the Insecta database 10, where complete and single copy was (89.17%) 1219, complete and duplicate (9.4%) 129, and fragmented genes (0.29%) 4, and 16 genes (1.17%) were missing (Simao et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eGenome annotation of \u003cem\u003eO. surinamensis\u003c/em\u003e predicted 11,227 genes with 31,187 coding sequences (CDS) that had an average length of 279 bp (8194 CDS had\u0026thinsp;\u0026gt;\u0026thinsp;300 bp whereas 1453 CDS had\u0026thinsp;\u0026gt;\u0026thinsp;1 Kb) and a total length of 8.7 Mb for all CDS. A total of 11,584 messenger RNA (mRNA) with an average length of 1492 bp were present (9281 mRNA\u0026thinsp;\u0026gt;\u0026thinsp;300 bp whereas 5200 mRNA\u0026thinsp;\u0026gt;\u0026thinsp;1 kb). Besides, 131 ribosomal RNA were detected with average length 596.82 bp, 5S rRNA was 97 with average length 101.97 bp, 5.8S rRNA was 16 with average length 149.62 bp, and 28S rRNA was 18 with average length 3661 bp. Furthermore, \u003cem\u003eO. surinamensis\u003c/em\u003e had 34,082 predicted protein-coding genes with an average length of 2666 amino acids using Augustus v3.4.0 (Stanke et al., \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e). the quality of the predicted proteins evaluated using BUSCO in protein mode with the Insecta database 10 of BUSCO, which indicated completeness at 93.6%, with the lowest duplicated 6.8% for \u003cem\u003eO. surinamensis.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThe choice of library preparation method can influence sequence quality, genome assembly, and further annotation and analysis (Haendiges et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, the genome was assembled using PacBio reads resulting in a more contiguous, complete and better genome size than the assembled genome of \u003cem\u003eO. surinamensis\u003c/em\u003e GCA004796505.1, which was sequenced using MiSeq Illumina. It had a smaller genome assembly size of 104 Mb, with 11,890 contigs, a GC ratio of 29.2%, 23.86 mismatches (N\u0026rsquo;s) per 100 Kbp and 24,810 bp total number of uncalled bases (N\u0026rsquo;s). This lower estimated genome assembly is inconsistent with the findings of this study, as well as those of Sharaf et al. (\u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e), who used flow cytometry to estimate the genome size of \u003cem\u003eO. surinamensis\u003c/em\u003e around 151.5 Mb and 154.1 Mb. In addition, \u003cem\u003eO. surinamensis\u003c/em\u003e GCA004796505.1 had lower predicted genes 10,580 and 26,231 CDS compared to this study.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eSimple sequence repeat identification\u003c/h2\u003e\n \u003cp\u003eIn this study, simple sequence repeats (SSRs) identified, also known as microsatellites, in the genome of \u003cem\u003eO. surinamensis.\u003c/em\u003e It has 54,156 identified SSRs with 0.034 SSRs density, 339.81 SSRs frequency in 159.37 Mb genome size (Table 2). Different types of SSRs were observed in gradual decrease however, mononucleotide SSRs were the dominant, which is consistent with the findings for the \u003cem\u003eBatocera horsfieldi\u003c/em\u003e beetle (Peng et al., 2021). Also, mono-and trinucleotides were more abundant than other types of SSRs, which was also observed in the mosquito species (Wang et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e) and 6 plant species (Zhao et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). Specifically, dinucleotide SSRs were more abundant than trinucleotides, which was also observed in the study by Fan and Chu (\u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e) and in the \u003cem\u003eBatocera horsfieldi\u003c/em\u003e beetle (Peng et al., 2021).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFunctional and metabolic pathway annotation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThis study provides the first molecular resource that highlights the metabolic and functional annotation of saw-toothed grain beetles. The putative functions of 11,227 unigenes were identified by alignment using DIAMOND and BLASTX with a cut-off E-value of 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e (Buchfink et al., 2000). Functional annotation using NCBI-NR, KOG, and UniProtKB/Swiss-Prot showed that the percentage of identical matches was less than 60%, which was lower than expected. This may be due to the lack of species related to the Silvanidae family or those closely related to \u003cem\u003eO. surinamensis\u003c/em\u003e in these databases (Supplementary material 07, 08, and 09).\u003c/p\u003e\n \u003cp\u003eMetabolic pathways were annotated using several protein databases, including KOfam, Pfam, eggNOG, and NCBI protein family models (NPFM). Generally, \u003cem\u003eO. surinamensis\u003c/em\u003e had the highest number of queries identified proteins observed in the Pfam-A database that shows the highest identified proteins 32,173 among other protein databases with average reference protein length of 157.8 amino acids, whereas an average query protein length was 722.1 amino acids. Overall, the average identified reference proteins were less than 800 amino acids, whereas Pfam-A and NCBI had the lowest, which may contain novel sequences with extremely few protein sequences matching because of the lower number of species related to the Silvanidae family or closely related to \u003cem\u003eO. surinamensis\u003c/em\u003e in the NR database (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). For example, NCBI has the reference protein TIGR03150 with a length of 407 amino acids. The protein is KAS-II, and FabF is involved in the condensation step of fatty acid biosynthesis with a query protein length of 2070 amino acids.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eCOG annotation\u003c/h2\u003e\n \u003cp\u003eCOG is standard database for identifying orthologous gene functions using 25 functional classifications. The conserved regions in the genes support the classification based on homologous relationships. Generally, the cluster of orthologous gene function analysis of \u003cem\u003eO. surinamensis\u003c/em\u003e classified (21.08%) 7186 of 34,082 genes into the COG functional category. Single transduction mechanisms, general function prediction, translation, ribosomal structure and biogenesis, post-translational modifications, protein turnover, and chaperones showed the highest findings in COG annotation (Supplementary material 10).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eKEGG pathway analysis\u003c/h2\u003e\n \u003cp\u003eThe metabolic pathway annotation results were interpreted as 394 KEGG modules that showed 22 KEGG metabolic pathways that mapped the annotated genes to the KEGG database. A total of 22 KEGG pathways were detected, with a total of 3322 unigenes for \u003cem\u003eO. surinamensis\u003c/em\u003e. The KEGG pathway distribution showed that \u003cem\u003eO. surinamensis\u003c/em\u003e had the highest number of annotated general metabolic pathways (858 unigenes), followed by carbohydrate metabolism (354), amino acid metabolism (278), and biosynthesis of secondary metabolites (272). Among the 3322 unigenes, 490 were mapped to 5 biosynthesis pathways: biosynthesis of secondary metabolites, amino acids, nucleotide sugars, cofactors, and other secondary metabolites. For example, the biosynthesis of secondary metabolites was the highest, with 272 unigenes, whereas the lowest was 26 unigenes for the biosynthesis of nucleotide sugars (Supplementary material 11).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003eGene ontology analysis\u003c/h2\u003e\n \u003cp\u003eIt is a comprehensive and large source of information on the functions of genes in several species within the Tree of Life. A total of 42,769 GO terms were assigned to 1499 genes with 5977 hits for \u003cem\u003eO. surinamensis\u003c/em\u003e. Most GO terms were assigned to biological process with 2119 hits, followed by molecular function (1278 hits), protein class (1170 hits), cellular components (869 hits), and GO pathway categories (541 hits) (Supplementary material 12 and 13). The highest number of terms in the cellular components category was cellular anatomy, with 770 genes. The molecular function category contained a large number of genes for catalytic activity and binding (633 and 374, respectively). The biological process category had a large number of genes involved in cellular, metabolic, and biological regulation (695, 446, and 321, respectively). The protein class category contained a high number of genes (462) encoding metabolite interconversion enzymes. The GO pathway category showed a large number of genes (37 and 29) involved in the pentose phosphate pathway and threonine biosynthesis, respectively. In addition, this study presents the first molecular resources that provide metabolic and functional annotations for saw-toothed grain beetles. These findings have GO annotated 13.35% (1499 genes) of the total 11,227 genes from \u003cem\u003eO. surinamensis\u003c/em\u003e, which is consistent with the percentage of annotated GO genes in the study by Kumar et al. (2020), who assigned GO annotation to 10,534 of 87,451 (12.04%) genes from the coconut rhinoceros beetle \u003cem\u003eOryctes rhinoceros\u003c/em\u003e L PRJNA486419. Based on these results, most annotation databases had a limited number of species related to the Silvanidae family or were closely related to \u003cem\u003eO. surinamensis\u003c/em\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePFAM-A annotation of\u003c/strong\u003e \u003cstrong\u003eO. surinamensis\u003c/strong\u003e \u003cstrong\u003eresistance protein families\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eSeveral protein families are common between \u003cem\u003eO. surinamensis\u003c/em\u003e and other insects, such as \u003cem\u003eRhynchophorus ferrugineus\u003c/em\u003e and palm weevils (Hazzouri et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). The PFAM annotation of \u003cem\u003eO. surinamensis\u003c/em\u003e revealed 5108 (39,898 occurrences) protein families. P450 cytochromes, Glutathione S-Transferase-N and ABC transporters were the most abundant among the eight common protein families associated with detoxification and pesticide resistance (Table 4). For instance, P450 cytochromes (PF00067) are large family of enzymes that involved in xenobiotic detoxification and degradation of endogenous molecules (Keeling et al., 2013). Generally, beetles and weevils detoxify plant chemical components using genes encoding detoxifying enzymes, such as P450 and Glutathione S-transferases (Hazzouri et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). This study indicated 158 P450 cytochromes identified for \u003cem\u003eO. surinamensis\u003c/em\u003e, which is higher than the P450 found in \u003cem\u003eR. ferruiius\u003c/em\u003e, \u003cem\u003eD. ponderosae\u003c/em\u003e, and \u003cem\u003eD. melanogaster\u003c/em\u003e that have 120, 85, and 86, respectively (Hazzouri et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Keeling et al., 2013).\u003c/p\u003e\n \u003cp\u003eTable 4: Protein families of pesticide resistance for \u003cem\u003eO. surinamensis\u003c/em\u003e PRJNA992804.\u003cstrong\u003eAnnotation of protein family related to resistance to environment stress\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe odorant protein families (PF01395 and PF01161) support insects in detecting pheromones and odorants and have been identified in \u003cem\u003eO. surinamensis\u003c/em\u003e in 19 PBP/GOBP families (Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). This allows the insect to locate infected palm trees using released volatiles in the air as well as aggregate pheromones released by males to coordinate attacks on trees (Hazzouri et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Besides, heat shock proteins (HSPs; PF00011, PF00012, and PF00183) are of three types\u0026mdash;HSP20, HSP70 and HSP 90. The annotation detected 28 HSP in \u003cem\u003eO. surinamensis\u003c/em\u003e, including 15 HSP70, 8 HSP20, and 5 HSP90 (Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). In contrast, the number of HSP in \u003cem\u003eO. surinamensis\u003c/em\u003e was lower than that in the desert beetle \u003cem\u003eMicrodera punctipennis\u003c/em\u003e, which has 72 HSP that are important for adaptation and survival in extreme desert environments (Lu X et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003ePest management control\u003c/h2\u003e\n \u003cp\u003eThis study provides genomic and proteomic annotations to support the development of pest management strategies for \u003cem\u003eO. surinamensis\u003c/em\u003e. P450 enzymes play crucial roles in the detoxification of plant chemical compounds. Oil compounds from \u003cem\u003eLaurus nobilis\u003c/em\u003e have demonstrated potential for the control of invasive pests, such as \u003cem\u003eR. dominica\u003c/em\u003e and \u003cem\u003eT. castaneum\u003c/em\u003e (Jemaa et al., 2012). Although the toxic activity of 158 P450 enzymes was identified for \u003cem\u003eO. surinamensis\u003c/em\u003e, \u003cem\u003eLaurus nobilis\u003c/em\u003e was efficient against major stored-product insect pests (Jemaa et al., 2012). Another approach involves the management of \u003cem\u003eO. surinamensis\u003c/em\u003e using pheromones and odorants (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Similar strategies have been successful in controlling insect pest of \u003cem\u003eR. ferrugineus\u003c/em\u003e (Antony et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) and the apple insect pest \u003cem\u003eCydia pomonella\u003c/em\u003e (Balasko et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Additionally, \u003cem\u003eO. surinamensis\u003c/em\u003e may require longer time to eliminate compared to other species when using aeration method to cool stored grains at temperatures between 13\u0026deg;C and 20\u0026deg;C (David and ramanyam, 2006).\u003c/p\u003e\n \u003cp\u003eFurthermore, disrupting the transmission of bacterial symbionts from female insects to their offspring holds promise as a strategy to control invasive insect pests, such as \u003cem\u003eLycorma delicatula\u003c/em\u003e (Kingan et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Based on this, the endosymbionts of \u003cem\u003eO. surinamensis\u003c/em\u003e have the potential to become controlling factors that limit the invasive insect pests of \u003cem\u003eO. surinamensis\u003c/em\u003e. It exhibits active reproductive manipulation rules in its host, \u003cem\u003eO. surinamensis\u003c/em\u003e, which leads to a strong female bias (Kiefer et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). In addition, \u003cem\u003eS. silvanidophilus\u003c/em\u003e is another endosymbiont found in \u003cem\u003eO. surinamensis\u003c/em\u003e, which can be a growth control factor for \u003cem\u003eO. surinamensis\u003c/em\u003e, as it plays an important role in providing aromatic amino acid precursors for cuticle synthesis in the host via the shikimate pathway (Kiefer et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). In addition, most insect pests, such as \u003cem\u003eCephalonomia tarsalis\u003c/em\u003e have natural parasitoids and predators that mainly attack \u003cem\u003eO. surinamensis\u003c/em\u003e larvae (David and Ramanyam, 2006). However, the use of biological control agents such as \u003cem\u003eC. tarsalis\u003c/em\u003e may lead to an increase in the predator population or the movement of predators to other areas. Further research is recommended because current pest management strategies for \u003cem\u003eO. surinamensis\u003c/em\u003e are inefficient.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study provided assembled and annotated genome of the \u003cem\u003eO. surinamensis\u003c/em\u003e using PacBio long read technology. The raw reads obtained from genomic sequencing were de novo assembled into a high-quality genome, which can serve as a valuable mapping reference for future genetic studies on the saw-toothed grain beetle and closely related species. Interestingly, it has been identified two crucial bacterial endosymbionts within \u003cem\u003eO. surinamensis\u003c/em\u003e that hold promise for insect pest management strategies. Comprehensive analyses yielded additional annotation information about \u003cem\u003eO. surinamensis\u003c/em\u003e, highlighting several areas relevant to pest control and management. Specifically, this study highlighted detoxification genes, heat shock genes, odorant receptor genes and other significant insecticide resistance genes in the saw-toothed grain beetle. The data presented in this study contribute to the discovery of essential candidate genes for pest control and provide a foundational resource for future investigations into this invasive insect pest species. Moreover, it is recommended to employ advanced sequencing technologies, including both next-generation and third-generation methodologies, to conduct a comprehensive analysis of the insect's transcriptome.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw reads and genome assemblies of \u003cem\u003eO. surinamensis\u003c/em\u003e have been submitted to NCBI under the accession number SRR22318063 and PRJNA992804, respectively. Endosymbiont bacteria \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eS. silvanidophilus\u003c/em\u003e data related to this study are available under accession PRJNA975352 and PRJNA988171. Supplementary material and other relative data are available from Zenodo https://zenodo.org/records/14466150.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSpecial thanks to the management of KAUST Core Labs as well as to Bioscience Core Lab and Supercomputing Core Lab for providing support for computing resources. Thanks to Ming Sin Cheung, Patrick \u0026nbsp; Alexander Putra, Karen Carty and Nagarajan Kathiresan for the support. In fond memory of our talented colleague Kamel Jabbari.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis was funded by King Abdullah University of Science and Technology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAntony B, Soffan A, Jakše J, Abdelazim MM, Aldosari SA, Aldawood AS, Pain A (2016) Identification of the genes involved in odorant reception and detection in the palm weevil Rhynchophorus ferrugineus, an important quarantine pest, by antennal transcriptome analysis. BMC Genomics 17:69\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBalasko M, Bazok R, Mikac K, Lemic D, Zivkovic I (2020) Pest management challenges and control practice in codling moth. 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Sci Rep 5:8018\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 5 are available in the Supplementary Files section.\u003c/p\u003e"},{"header":"Supplementary Materials","content":"\u003cp\u003eSupplementary Materials are not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"ba6b0342-9244-4200-9f89-975f6ec2e6db","identifier":"10.13039/501100004052","name":"King Abdullah University of Science and Technology","awardNumber":"1","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"King Abdullah University of Science and Technology","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Oryzaephilus surinamensis, PacBio-Sequel sequencing, endosymbionts, comparative orthologous analysis, pest genomics","lastPublishedDoi":"10.21203/rs.3.rs-5784528/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5784528/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSaw-toothed grain beetle (\u003cem\u003eOryzaephilus surinamensis\u003c/em\u003e) negatively impacts food products, which are considered as common insect pests in several countries. This study reports 159 Mb high quality long reads de novo genome assembly of \u003cem\u003eO. surinamensis\u003c/em\u003e using PacBio-Sequel sequencing technology. The genome was assembled into 3043 contigs with the largest contigs 2.35 Mb and N50 length of 0.177 Mb, L50 171 contigs, 255.8X coverage, GC content of 29.69%, 54,156 microsatellite sequences and BUSCO evaluation revealed 98.6%. Genome annotation identified 11,227 genes and predicted 34,082 protein-coding genes (93.6% Busco score), of which 32,173 (94.39%) were annotated by Pfam database. The annotation of protein families identified important genes for pesticide and Enironmental resistance. Furthermore, \u003cem\u003eWolbachia\u003c/em\u003e endosymbiotic identified with 1.93 Mb genome size and 2060 predicted genes while \u003cem\u003eCandidatus Shikimatogenerans Silvanidophilus\u003c/em\u003e endosymbiotic identified with 1.92 Mb genome size and 1223 predicted genes. This study provides a new reference genome and comprehensive resource for \u003cem\u003eO. surinamensis\u003c/em\u003e and highlights important genes and pathways that influence agriculture.\u003c/p\u003e","manuscriptTitle":"High quality de novo long read genome assembly and annotation of resistance protein families for saw toothed grain beetle","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-09 15:18:11","doi":"10.21203/rs.3.rs-5784528/v1","editorialEvents":[{"type":"communityComments","content":1}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5e8ed5ce-eb77-448d-a896-5f88d442d14d","owner":[],"postedDate":"January 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-09T15:18:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-09 15:18:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5784528","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5784528","identity":"rs-5784528","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}