Single specimen genome assembly of Culicoides stellifer shows evidence of a non-retroviral endogenous viral element

Single specimen genome assembly of Culicoides stellifer shows evidence of a non-retroviral endogenous viral element | 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 Single specimen genome assembly of Culicoides stellifer shows evidence of a non-retroviral endogenous viral element Jessica Castellanos-Labarcena, Yoamel Milián-García, Tyler A. Elliott, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4623838/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Mar, 2025 Read the published version in BMC Genomics → Version 1 posted 11 You are reading this latest preprint version Abstract Background Advancing our knowledge of vector species genomes is a key step in our battle against the spread of diseases. Biting midges of the genus Culicoides are vectors of arboviruses that significantly affect livestock worldwide. Culicoides stellifer is a suspected vector with a wide range distribution in North America, for which cryptic diversity has been described. Results With just one specimen of C. stellifer , we assembled and annotated both a high-quality nuclear and a mitochondrial genome using the ultra-low input DNA PacBio protocol. The genome assembly is 119 Mb in length with a contig N50 value of 479.3 kb, contains 11% repeat sequences and 18,895 annotated protein-coding genes. To further elucidate the role of this species as a vector, we provide genomic evidence of a non-retroviral endogenous viral element integrated into the genome that corresponds to rhabdovirus nucleocapsid proteins, the same family as the Vesicular Stomatitis Virus. Conclusions This genomic information will pave the way for future investigations into this species's putative vector role. We also demonstrate the practicability of completing genomic studies in small dipterans using single specimens preserved in ethanol as well as introduce a workflow for data analysis that considers the challenges of insect genome assembly. Culicoides Vesicular Stomatitis Virus genome assembly vector arboviruses Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Culicoides biting midges (Diptera: Ceratopogonidae) are among the most important vectors of arboviruses pathogenic to livestock and wildlife. The genus is highly diverse, with 1,347 valid species [ 1 ], of which 151 are currently recognized in North America, occupying a broad geographical range [ 2 ]. Here, C. sonorensis and C. insignis are the only species with confirmed vector status and they are known to transmit bluetongue virus [BTV], vesicular stomatitis virus (VSV), and epizootic hemorrhagic disease virus [EHDV] [ 3 ]. Reports of increased rates of BTV and EHDV outside of the geographic range of both species suggest that there might be an expansion or shift in species distribution due to climate change, or other species not recognized as vectors could be involved [ 4 , 5 ]. One of such putative vector species is Culicoides stellifer (Coquillett, 1901), abundant and widely distributed in the United States of America (USA) and eastern Canada. Several field-collected individuals in the USA have been confirmed to carry arboviruses, but it has been challenging to complete vector competence assays [ 3 ]. C. stellifer has been closely associated with ungulate species, although host associations for many Neartic species are poorly understood [ 6 ]. Despite the serious threat to animal health these vectors represent and the significant economic losses outbreaks could cause, there is a lack of genomic studies of Culicoides , as well as little understanding of the systematics of the group [ 1 , 4 , 7 ]. The genome assembly of only two species is available in NCBI; C. sonorensis (GCA_900258525.3) [ 7 , 8 ] and C. brevitarsis (GCF_036172545.2). Partial or complete annotated mitogenomes, which are a valuable resource for studying the phylogenetics and systematics, are available for only four species ( C. arakawae , C. sonorensis, C. brevitarsis and C. biguttatus ) [ 9 ]. Genomic information is critical for understanding the unique evolutionary features of this group, phylogenetic relationships, vector competency for arboviruses, and cryptic diversity [ 3 , 7 , 9 ]. One of the main causes that only a limited amount of Culicoides genomes have been sequenced in is perhaps the difficulty to obtain sufficient quantities of high molecular weight DNA. Species are small, < 3 mm body length, which typically generates very low concentration DNA extracts from single specimens (< 1 ng/uL) [ 9 ]. Advances in long-read sequencing technologies that allow low amounts of input material and modifications to increase starting DNA concentration for library preparation have opened the door to generating high-quality genome assemblies for small arthropods [ 10 ]. Particularly, the PacBio HiFi ultra-low DNA input workflow starts with as low as 5 ng genomic DNA for whole-genome amplification and is recommended for genome sizes of up to 500 Mb. This workflow was used to generate a de novo genome assembly for Drosophila melanogaster [ 11 ] and two submillimeter Collembola species ( Desoria tigrina and Sminthurides aquaticus ) [ 12 ]. It allows sequencing the genome from a single, field-preserved specimen, generating medium-size fragments (10–25 kb) with high base accuracy (99.8%), which can be used to produce assemblies that are more contiguous and with a higher base accuracy. The expansion of Culicoides -borne pathogens in Eastern Canada, especially in Ontario, highlights the need to characterize potential vectors, viruses and hosts. C. stellifer is suspected to represent a species complex, with cryptic diversity reported for samples collected in Ontario [ 13 ]. In this study we present a high-quality genome assembly of a Culicoides stellifer specimen collected in Southern Ontario. In an attempt to provide more supporting evidence that this species may transmit one or more RNA viruses, we set out to query the genome for viral fragments, also known as non-retroviral endogenous viral elements (nrEVE) of BTV, EHDV, VSV and West Nile virus (WNV) viruses [ 14 , 15 , 16 ]. This phenomenon is known as virus-to-host horizontal gene transfer and is associated with persistent viral infection [ 17 ]. Given the complexity of Culicoides pathogens, crypticity, and unknown vector species, we developed a methodology and a bioinformatics pipeline to generate key genomic information for this group. This will significantly contribute to identifying new vector species, understanding the phylogenetic relationships of the group, and evolutionary processes involved in vector competence across Diptera. Methods Sample collection and genome sequencing . Culicoides stellifer specimens were collected at the Ontario Veterinary College Dairy Barn at the University of Guelph, Ontario, Canada, using miniature Centre for Disease Control (CDC) UV light traps (Bioquip, CA, USA). The specimens were identified using the dichotomous key for Culicoides of Ontario [ 5 ]. Five female individuals preserved in 95% ethanol were sent to the University of Delaware’s DNA Sequencing & Genotyping Center in Newark, DE, USA. As Culicoides species are less than 3 mm long and weigh < 1 mg, we decided to use the ultra-low DNA Input protocol from PacBio [ 11 ] to generate genomic data from a single specimen. Genomic DNA was extracted from each individual separately using the MagAttract HMW DNA kit (Qiagen). DNA quantification was completed using a Qubit Fluorimeter, and DNA fragment sizes were assessed by a Femto Pulse system (Agilent) for fragments of a length around 12–14 kb. The amount and quality of genomic DNA for only one individual was sufficient to move forward with library preparation. SMRTbell gDNA was constructed following the protocol “Preparing HiFi SMRT-bell libraries from Ultra-Low DNA input” using the SMRTbell Express Template Prep Kit 3.0 (Pacbio, 102-182-700). After a BluePippin size selection (Sage Science, PAC20KB) at 6 kb, the average library size was 10 kb measured on a Femto Pulse system Agilent). Sequencing was performed on a SMRT 8M cell on the Sequel IIe using the Sequel II Binding kit 2.2/Sequel II Sequencing kit 2.0 with a 30-hours movie. Preassembly Processing PacBio Hifi reads were first processed to trim PCR adapter sequences and to remove PCR duplicates. We used the lima for PCR adapter trimming and pbmarkdups for PCR duplicate removal, both available in pbbioconda ( https://github.com/PacificBiosciences/pbbioconda ). Properties of the genome, such as genome size, levels of heterozygosity and repeat content, were estimated by analysis of K -mer frequencies. We used Meryl v1.4.1, as implemented in Merqury v1.3 [ 18 ] and used the size of the Culicoides sonorensis genome as a reference [ 7 ] to estimate the k -mer size to use. Frequencies of k -mers ( K = 19) were counted using Meryl v1.4.1. With the k -mer histogram, we estimated the genome properties using GenomeScope v2.0 [ 19 ]. Mitogenome assembly and annotation For the assembly of the mitochondrial genome, we used MitoHiFi v3.2 [ 20 ], starting with the raw reads. The first assembled mitogenome was significantly larger than expected, so we decided to use only reads mapped to the reference genome ( Culicoides (Meijerehelea) arakawae Arakawa , 1910) and assembled the mitogenome using Pacific Biosciences’ Improved Phase Assembly (IPA, v1.8.0) HiFi Genome Assembler pipeline ( https://github.com/PacificBiosciences/pbipa ). We annotated the mitogenome using MITOS2 v2.1.8 as implemented in the Galaxy workbench [ 21 ]. Genome assembly Genome assembly was conducted after removing the mitochondrial genome reads. We used two assemblers, IPA v1.8.0 and Hifiasm v0.16.0 [ 22 ]. For Hifiasm, we used different similarity thresholds for duplicate haplotypes to be purged (-s parameter) following the author’s recommendations (s = 0.75, s = 0.55, and s = 0.35). The overall quality of these preliminary assemblies, especially continuity and completeness, was estimated using assembly-stats v17.02 (rjchallis/assembly-stats 17.02) and Benchmarking Universal Single-Copy Orthologs (BUSCO) v5.6.1 [ 23 ] with a Diptera database (diptera_odb10.gz). Given the high level of duplication of preliminary assemblies and the large size of genomes compared to the predicted value, we conducted a posteriori purging of duplicates using purge_dups [ 24 ]. The resulting assemblies showed similar characteristics in terms of contiguity and completeness; we selected the assembly generated with Hifiasm -s 0.35 for subsequent analyses as it has the largest N50 value. To further evaluate the quality of the assembly, we used Merqury v1.4.1 [ 18 ] to estimate base-level accuracy and completeness as well as BlobToolkit for contamination identification and isolation [ 25 ]. Genome annotation Repeat element annotation. We annotated transposable elements (TE), satellite DNA, simple and low-complexity repeats using Earl Grey v.4.1.1 [ 26 ]. Via Earl Grey, we used RepeatMasker v.4.1.6 [ 27 ] to identify and mask simple and low-complexity repeats, along with the Diptera subset of repeats from the growing, open source repeat reference library Dfam v.3.7 [ 28 ]. Once masked for these repeats, the genome was analyzed with RepeatModeler2 v.2.0.5 [ 29 ] for de novo repeat identification and classification. Earl Grey next employed a BLAST-extract-align-trim procedure on each repeat consensus sequence to refine their boundaries and improve the quality of the reference library, along with clustering of consensus sequences using CD-HIT to reduce redundancy [ 30 , 31 ]. Next, LTR_FINDER [ 32 , 33 ] was used to further detect any missing long terminal repeat (LTR) retrotransposons before combining all collected repeats and masking and annotating the genome once more with RepeatMasker. Finally, Earl Grey used RepeatCraft [ 34 ] to merge physically close or overlapping repeat fragments in the annotation which have the same classification. The library of generated consensus sequences was translated into open reading frames of at least 300 bp in all six frames using getorf [ 35 ], and these were queried against the Pfam v.35.0 [ 36 ] protein reference library using pfam_scan.pl to detect instances of host gene contamination in the repeat reference library. The output was manually inspected due to the small size of the reference library, and 22 consensus sequences were removed from the library. To provide additional evidence for the proper classification of TEs, the tool TEsorter v1.4.6 [ 37 ] was employed to extract open reading frames from all reference sequences, query them using hmmscan against compiled protein reference libraries of terminal inverted repeat (TIR) DNA transposons [ 38 ], long interspersed nuclear elements (LINE) [ 39 ] and LTR retrotransposons [ 40 ]. Due to the large proportion of unknown repeats, in terms of the number consensus sequences and percentage of total repeats annotated, all RepeatModeler2 consensus sequences of at least 100 bp and covering at least 10,000 in the assembly were manually inspected. For each consensus sequence, this involved one or more of the following steps recommended by Goubert et al. [ 41 ]: 1) use of TE_ManAnnot to extract blast hits for each consensus that were at least half the size of the consensus, along with enough flanking DNA to resolve the termini of the given consensus, 2) alignment of all hits using MAFFT v7.453 [ 42 ] to accommodate the high frequency of indels in repeats, 3) the removal of gaps in the alignment where 80% of the sequences featured a gap via T-COFFEE v13.46.0 [ 43 ], 4) the inspection of the alignment to confirm the consensus sequence did not need to be extended or adjusted, 5) the creation of a new consensus sequence when needed via cons in EMBOSS, and 6) the use of TE-Aid to visualize the size and number of hits of a given consensus, the divergence of hits from the consensus, the presence of repetitive structures within the consensus, and the presence of TE coding regions via blastp to the RepeatMasker RepeatPeps protein database. ● Gene prediction and functional annotation We completed the gene prediction on the soft-masked genome assembly using the BRAKER3 v3.0.8 pipeline [ 44 ], providing protein homology information as extrinsic evidence. We used the Arthropoda clade-partitioned file of OrthoDB 11 [ 45 ] as the source of reference protein sequences. We functionally annotated the predicted protein-coding genes using DIAMOND BLASTP [ 46 ], searching against the Swiss-Prot protein database ( https://www.uniprot.org/ ). We filtered the output for E-value 30%. The predicted genes were also mapped to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to classify functional categories using BlastKOALA ( https://www.kegg.jp/blastkoala/ ). Additionally, we ran InterProScan v5.67-99.0 [ 47 ] with all default settings and added the option of looking for the Gene Ontology (GO) annotation. Non-retroviral endogenous viral identification Nucleotide sequences for EHDV, VSV and WNV viruses were downloaded from GenBank, and the curated set of BTV sequences from BTV-GLUE [ 48 ]. Incomplete and artificial sequences were filtered out along with VSV and WNV viruses shorter than 10 000 bp by data processing in R v.4.3.2 [ 49 ], aided by tidyverse v2.0.0 [ 50 ], Biostrings v2.70.2 [ 51 ] and seqRFLP v1.0.1 ( https://github.com/helixcn/seqRFLP ). EHDV is a virus with a segmented genome, so each fragment was detected and sorted before multiple sequence alignments were built for each viral segment, or whole virus for the others, using MUSCLE [ 52 ] and default settings. A hidden Markov model (HMM) was generated for each alignment using hmmbuild in HMMER3 [ 53 ], and the C. stellifer , C. sonorensis (GCA_900258525.3) and C. brevitarsis (GCA_036172545.2) assemblies were queried against each of these models using nhmmer, along with the raw reads used in creating the C. stellifer assembly. Results Hifi sequencing with ultra-low DNA input workflow The ultra-low DNA input protocol includes a PCR amplification step to generate sufficient material for sequencing. This was a critical consideration when selecting this workflow to generate high-quality genomic information from a single C. stellifer specimen. PCR products ranged from 5-8 kb. These values suggest that the gDNA had some degree of fragmentation and that short fragments were preferentially amplified. Sequencing output resulted in 191,906 PacBio Hi-Fi reads with an average read length of ~ 13,000 bp. The genome size was estimated to be approximately 104 Mb, with a heterozygosity of 2.88% and 11.4% of repeat sequences (Figure 1). Figure 1: Genome properties based on raw data exploration. (A) GenomeScope results in linear coordinates on the PacBio Hifi sequencing dataset for one individual of Culicoides stellifer. The genome size (len) is predicted to be around 104 Mb, and 88.6% of the 19-mers are unique (aa), suggesting that the genome has around 11% repetitive content. Heterozygosity (ab), mean k-mer coverage for heterozygous bases (kcov), read error rate (err), the average rate of read duplications (dup), k-mer size used in the run (k:), and ploidy (p:) is also reported. The sequencing errors are identified by low-coverage K -mers. (B) Frequency histogram of the read length for the PacBio Hifi sequencing dataset for one individual of Culicoides stellifer . The dashed lines represent the mean value. Mitogenome Assembly Long-read sequencing technologies for mitochondrial genome assembly in Culicoides haven’t been explored before. We started by using the MitoHifi toolkit for mitochondrial assembly from Hifi data. When using raw data and assembled contigs with Hifiasm, the pipeline failed to correctly assemble the mitochondrial genome, as it generated a molecule much larger than expected (~ 50,000 bp). It is likely that the misassembly might be related to shorter reads, insufficient coverage, or the presence of nuclear-mitochondrial DNA (NUMTs). We selected 128 reads that mapped to a reference mitogenome ( C. arakawae ) and generated a de-novo assembly for C. stellifer’s mitochondrial genome using IPA assembler. This resulted in a 16,607 bp mitochondrial genome, which is within the range of mitogenome lengths previously reported for other species of the genus [9, 54]. Figure 2: Mitochondrial genome annotation for Culicoides stellifer. Protein-coding genes, rRNA, and tRNA are represented in green, brown and orange, respectively. The control region (D-loop) is marked in blue, and the intergenic spacers are marked in red. The annotation was completed using MITOS2 v2.1.8, and the figure was generated using Geneious prime v11:08. The annotation using MITOS2 identified 13 protein-coding genes (PCGs), 22 transfer RNAs (tRNA), and two ribosomal RNAs (rRNA). The assembly was circularized and overall it showed the same gene arrangement previously described for other species in the genus. PCGs sizes ranged from 152 (ATP8) to 1,732 bp (NAD5). Transfer RNA sizes ranged from 48 [tRNA F(gaa) to 72 bp [tRNA V(tac)], while rRNA lengths were 781 (rRNA S) and 1,284 bp (rRNA L). The estimated control region size was 1,842 bp. Additionally, 17 spacers were identified, ranging in size from 1 to 18 bp. Genome assembly We compared two long-read assembly tools (IPA and Hifiasm) and various levels of duplicate purging in Hifiasm (-s parameter). Overall, Hifiasm produced the best assemblies. All four initial assemblies resulted in primary genomes with a size >146 Mb and almost 30% of complete-duplicated genes reported by BUSCO. Different values of the similarity threshold for duplicate haplotigs (- s parameter) in the Hifiasm assemblies resulted in a slight decrease in the total number of contigs and an increase in the N50, producing overall similar values (Table 1). Purging duplicated regions with purge_dups reduced was successful in reducing the number of contigs by half, increased contiguity and significantly decreased the number of duplicated genes reported by BUSCO (Table 1). The 119 Mb size assembled genome is closer to the estimate of 105 Mb obtained from the k-mer analysis. In comparison to the other two available Culicoides genomes, our assembly displays good quality in terms of contiguity (N50 and L50) and completeness (Figure 3). The BUSCO scores of our assemblies (89.8 % complete (C) BUSCOs (including 2.0 % duplicated [D]), 1.5 % fragmented (F), and 8.6 % missing (M)) are very similar to those of the genome of C. brevitarsis, whose assembly includes three chromosomes and unplaced scaffolds. Our genome also is of significantly higher quality than that of C. sonorensis , as the latter involved pooling many individuals and was generated using short-read sequencing. As our final assembly, we selected the one with the highest N50 and the lowest number of duplicated BUSCOs without significantly decreasing the complete BUSCO score. The genome assembly (referred to as purged_s030) comprises 450 contigs, totalling 119,322,097 bp, contig N50 of 479,264 bp and L50 of 81 (Figure 3). We estimated a high base accuracy (QV=53.3) and 90% completeness based on the k-mer comparison between the assembly and those found in the PacBio raw reads. Table 1: Summary statistics of the Culicoides stellifer primary genome assemblies using HiFiasm with three levels of purge duplication and IPA. The only two other genomes of the Genus available in NCBI are included for comparison purposes. Genome Assembly C.stellifer HiFiasm -s 0.35 C.stellifer HiFiasm -s 0.35 purge_dups C.stellifer HiFiasm -s 0.55 purge_dups C.stellifer HiFiasm -s 0.75 purge_dups C.stellifer IPA C.stellifer IPA purge_dups C.sonorensis Velvet (GCA_900258525.3) C.brevitaris Raven; Polca (Masurca); Racon. Sequencing technology PacBio Hifi PacBio Hifi PacBio Hifi PacBio Hifi PacBio Hifi PacBio Hifi Illumina HiSeq Oxford Nanopore PromethION; Illumina NovaSeq Genome statistics Total length (Mb) 158 119 119 120 146 117 155.9 129.5 Number of contigs 810 450 451 463 730 600 3858 223 Number of scaffolds 0 0 0 0 0 0 0 149 Longest contig or scaffold (bp) 1,731,460 1,731,461 1,731,460 1,731,460 1,156,022 1,156,022 763,582 46,604,242 Mean contig or scaffold length (bp) 194,770 265,155 264,809 259,459 199,980 195,305 40,420 863,398 N50 356,049 479,265 459,312 458,458 289,321 306,443 109,184 3.5 Mb N90 84,987 132,711 132,524 113,333 104,260 98,560 NA NA L50 126 81 82 83 153 114 395 NA L90 476 261 265 269 479 368 NA NA GC content 30.8% 30.8% 30.8% 30.8% 30.8% 30.8% 28.3% 27.9% Total BUSCO for the genome assembly Complete BUSCO 2970 (90.4%) 2953 (89.9%) 2942 (89.8%) 2950 (89.8%) 2955 (89.9%) 2942 (89.6%) 89.5% 91.9% Complete single copy 2113 (64.3%) 2882 (87.7%) 2870 (87.4%) 2875 (87.5%) 1962 (59.7%) 2881 (87.7%) 63.0% 89.3% Complete duplicated 857 (26.1%) 71 (2.2%) 79 (2.4%) 75 (2.3%) 993 (30.2%) 61 (1.9%) 26.5% 2.6% Fragmented 50 (1.5%) 51 (1.6%) 53 (1.6%) 54 (1.6%) 54 (1.6%) 55 (1.7%) 4.4% 0.6% Missing 265 (8.1%) 281 (8.5%) 283 (8.6%) 281 (8.6%) 276 (8.5%) 288 (8.7%) 6.1% 7.5% *Table 1* Figure 3: Contig-level assembly of Culicoides stellifer. (A) Snail plot showing lengths of all contigs. The longest contig is represented in red, N50 in dark orange, and N90 in light orange. The outer ring shows the GC content of the genome. (B) Visualization of assembly contiguity showing contig sizes on the Y-axis for which x percent of the assembly consists of contigs of at least that size. The three assemblies of Culicoides stellife r with various levels of similarity purging are compared to the assembly of Culiocides sonorensis . Genome annotation Overall, the degree of repetitive content in the genome assembly of Culicoides stellifer was approximately 15 Mb of repetitive elements, representing 11 % of the genome assembly (Table 2). Initially, nearly half of all repeats were classified as unknown. Due to the small size of this reference library, it was decided to manually investigate the largest and most abundant consensus sequences as described in the Methods. Many of the unknown repeats were determined to be non-autonomous TIR DNA transposons, and in general, all DNA transposons were characterized by a lack of substantial coding regions for transposases. In an attempt to find autonomous elements, the repeat library output from a larger version of the assembly with less purged duplicates (HiFiasm -s 0.35) was inspected for novel consensus sequences, and these were added to the existing repeat library and the genome was re-annotated. In this new library, a total of 4 consensus sequences of DNA transposons (TcMar-Tc1, TcMar-Tigger, TcMar-ISRm11, hAT-Tip100) had partial coding regions, but none of these appear to be functional. Comparison and selective melding of the two libraries added new consensus sequences for four LTR retrotransposons with coding regions and well-resolved termini, as well as several LINE elements including an R2 consensus sequence. Retrotransposons make up a smaller fraction of the genome than DNA transposons, which stands in contrast to the pattern seen in the C. sonorensis genome [7]. Caution should be taken when comparing the repeats in these two genomes, as the methods differed and the repeat annotation in the C. sonorensis assembly was not as thorough as was done for C. stellifer . In general, the C. stellifer assembly has a lower repeat content than C. sonorensis ( ~11% vs 29.7%); however, when that repeat content is positively correlated with genome or assembly size [55], this is not surprising. Table 2: Summary of repeat elements annotated in the Culicoides stellifer assembly. The numbers of consensus sequences in parentheses represent those generated by RepeatModeler2. Repeat Superfamily Base pairs Consensus Sequences DNA transposon TIR Non-Autonomous 2,563,172 66 (59) hAT 496,695 9 (8) Tc1/Mariner 103,081 9 (3) piggyBac 55,206 1 (1) Other TIR 4,132 12 Total DNA 3,222,286 97 (71) Retrotransposon LTR Bel-Pao 202,125 41 (5) Ty1/Copia 100,586 20 (3) Ty3-like 87,488 54 (2) Unclassified LTR 48,094 2 (2) Total LTR 423,038 117 (12) LINE I 239,478 30 (5) Unclassified LINE 121,740 4 (4) CR1 91,715 26 (6) R2 48,480 1 (1) RTE 27,718 4 (3) Total LINE 529,131 65 (19) Total Retrotransposon 952,169 182 (31) Total TE 4,174,455 279 (102) Other Repeats Satellite/Simple/Low complexity 6,107,679 2976 (55) Unknown 5,434,496 216 (216) Total Repeats 15,716,630 3443 (373) *Table2* A breakdown of the contribution of different components of Earl Grey to the resultant repeat library is useful when considering repeat annotation in novel genomes (Table 3.). Dfam is a growing, open-source database of repeats, and its current subset of Dipteran repeats stems from species distantly related to C. stellifer , hence the limited contribution to the annotation. Rather than being an indictment of Dfam, this stresses the value of submitting consensus sequences to Dfam to increase its taxonomic scope and useability for new genomes. Table 3. Comparative statistics of repeat sequences detected by various sources and their annotation in the assembly. Repeat Source Consensus Sequences Mean Coverage/Consensus (bp) Total Coverage (bp) Dfam Diptera 181 1610 291,385 RepeatMasker 2891 966 2,792,913 RepeatModeler2 373 33,644 12,549,446 BRAKER2 predicted 18,895 proteins in the nuclear genome with 18,662 unique sequences. We annotated 10,524 proteins (55.7%) by searching against the Swiss-Prot protein sequence database. 7,283 genes were mapped to KEGG pathways using BlastKOALA (Table 4). Collectively, 7812 proteins were functionally annotated by InterProScan, of which 4057 were assigned a GO term. This resource provides complementary levels of protein annotation, including curated InterPro entries annotated with a unique name and GO terms. The following analyses were included in the output file: PANTHER, CATH-Gene3D, PROSITE Profiles, Pfam, SUPERFAMILY, SMART, FunFam, Conserved Domains Database (CDD), PRINTS, Hamap, PIRSF, NCBIfam and the Structure-Function Linkage Database (SFLD). These represent protein signature databases included in InterPro [56] that were scanned in an integrated way to predict protein functions and for which a match was found. Some of the results of these analyses are included in Table 4. We annotated more than 3,000 additional protein-coding genes for either the C. sonorensis (15,612) or the C. brevitarsis (11,137) genome, respectively. This indicates that our workflow recovered a more complete set of genes for this group. We ran BUSCO in protein mode on the predicted proteins using the diptera_odb10 lineage dataset, which resulted in 91.5% complete BUSCO, including 8.3% duplicated, 1.0% fragmented and 7.5% missing. These values are similar to the report of C. brevitarsis (GCF_036172545.1-RS_2024_03) except for the complete and duplicated genes for which we report a slightly higher value (2.6% for C. brevitarsis ). This difference is explained by the larger number of proteins predicted by BRAKER2 in our assembly compared to the annotation of C. brevitarsis using the NCBI Eukaryotic Genome Annotation Pipeline. Table 4: Functional annotation of Culicoides stellifer proteins. Genome annotation Number of elements Percentage Predicted protein-coding genes (BRAKER2) 18,895 Swiss Prot 10,524 55.7 KEGG (BlastKOALA) 7,342 38.9 Pfam 6,209 32.9 InterPro 6,807 36.0 GO 6,026 31.9 Non-retroviral integrated RNA virus fragment identification The genome query for integrated viral fragments yielded 38 hits, ranging from 44 bp (74.5% identity) to 322 bp (53.2% identity). Fourteen hits greater than 100 bp were queried against the non-redundant protein database in GenBank using blastx. While most of these returned no similar hits or only to RNA-binding domains of genes, a 322 bp fragment in the C. stellifer raw reads was found to be similar to VSV. Using blastn we confirmed the presence of this VSV-like fragment in the C. stellifer assembly (Figure 4) and in conjunction with the gene annotation data, showed that a full 1319 bp coding region for a nucleocapsid was present. A blastx search using this nucleocapsid sequence as a query returned many significant hits (93-98% query coverage, 28.33-38.23% amino acid identity, scores of 161-303, hit length of 1233-1377 bp) to rhabdovirus nucleocapsid proteins in GenBank. Figure 4: Representation of the non-retroviral endogenous viral element (nr-EVE) sequence found in the Culicoides stellifer assembly and the surrounding structural elements in that section of the genome. The sequence is shown aligned to other Rhabdoviruses sequences. Discussion Challenges for genomic studies in Culicoides Insect genomics faces challenges in obtaining sufficient high-molecular-weight DNA for high-quality genome assemblies of small-size species. Culicoides sizes range from 1 to 3 mm, which makes it very challenging to obtain high-quality genomic DNA. Here, we demonstrated the utility of the ultra-low DNA input PacBio protocol to sequence high-quality reference genomes from a single Culicoides individual collected in the field and preserved in ethanol. This opens the door to future biodiversity genomics projects for other small organisms at the millimetre scale. The evidence of some DNA degradation in the sample suggests that fresh frozen insects, or at least fresh-ethanol-preserved specimens kept at -25C, will be preferred for future projects. This is essential as the success of the ultra-low DNA input method depends on the quality of the DNA; particularly, the starting amount of biological material correlates with library complexity and is among the factors affecting PCR duplication rate [ 57 ]. Despite the limitations associated with PCR amplifications, such as low processivity in high-GC regions, the reduction in overall coverage due to PCR duplicate removal, and PCR-introduced errors, we recovered a high-quality genome assembly for Culicoides stellifer , with a more complete set of genes identified than in any previous assemblies. This might prove that this workflow can be highly efficient for small and not very complex genomes. The only other genome assembly with higher contiguity was generated using Oxford Nanopore data, which has known problems with base pair accuracy and the potential of sequence errors to confound assembly [ 58 ]. Assessing the effect of various levels of duplicate haplotigs purging in combination with two different assembly pipelines was important as insect genomes have high levels of heterozygosity [ 59 ]. The tool purge_dups allows the search and removal of false heterotype duplications, which are haplotype sequences that are relatively more divergent than other parts of the genome and are classified as separate genomic regions by the assembly algorithms [ 60 ]. The increased contiguity without affecting the overall BUSCO score demonstrates the importance of this step in the data analysis pipeline, as it is highly efficient in purging duplicated regions. Our assembly shows a lower amount of duplication compared to the assembly of C. sonorensis . The high level of duplication reported in the latter was likely the result of a misassembly due to heterozygosity in the sample. The authors of the study suggested that the high duplication level could have resulted from genetic variation among/within the sequenced genomes from the pool of individuals (375 males and 150 females) and the representation within the assembly of alternative alleles. Considerations for genome annotation The combination of EarlGrey and BRAKER2 for genome annotation resulted in a comprehensive description of the structural elements of the genome. EarlGrey is a pipeline that offers several advantages over other pipelines used for TE annotation. It is specifically designed to enhance TE consensus sequence length and integrity; during curation, almost no elements needed to be substantially adjusted, and RepeatCraft allows it to address issues related to artificial overlapping and fragmented annotations. The landscape of repetitive elements in the genome assembly of C. stellifer showed a significant amount of unknown repeats that are neither satellite DNA nor obvious TEs. A recent study examining 600 insect genomes found that a high percentage of repetitive sequences were not classified in most insect lineages (25%-85%). This is mainly associated with reference databases, which have biased representations that impact annotation, particularly affecting insect lineages that have been poorly sampled [ 61 ]. As well, for novel genomes it is important to evaluate the taxonomic composition of repeats used in the reference library. The sequencing technology is also an important factor in detecting TE elements. This study reported a 36% increase in the detection of repetitive elements (RE), especially LTRs, when the assembly was generated using long-read sequencing platforms. This highlights the significance of our study in demonstrating the feasibility of the ultra-low input protocol and providing a workflow for genome assembly and annotation of tiny hematophagous flies that serve as vectors of a variety of pathogens. By generating more genomes, we can contribute to insect RE databases and develop the field of RE description as part of biodiversity genomic studies. The finding of almost no autonomous DNA transposons suggests this genome may be heading to a DNA transposon extinction event in the absence of a horizontal transfer event into the genome, although it is possible that more of the genome remains to be assembled and low copy but autonomous DNA transposons remain in that fraction. Additionally, we may need to apply repeat detection to different assemblies to find lower copy repeats, but this seems challenging given that the few Culicoides genomes reported have all been generated with different sequencing technologies and various degrees of completeness and quality. In general, a hierarchical approach of combining repeat libraries from assemblies with different amounts of purged duplicates p may be useful if low copy repeats are of interest in any genome project. The most important part of a genome's structural annotation is the identification of protein-coding genes. We predicted a larger number of proteins in our assembly compared to previously reported genomes [ 7 ] ( C. brevitarsis genome assembly GCF_036172545.1-RS_2024_03), which can be explained by a higher-quality assembly and the use of software with higher accuracy and performance, such as BRAKER2. The lack of transcriptomic data for this species determined that we used clade-specific proteins from OrthoDB as extrinsic evidence to generate hint-guided ab initio gene predictions of protein-coding genes. Identification of the functional role of the proteins found a high percentage of homolog proteins in other organisms (~ 30%-55%), with the Swiss Pro database yielding the more comprehensive results. Genomic evidence of vector status The integration of viral genomes (or fragments) into the genomes of their hosts cannot only help us understand evolutionary history and relationships among host species but also offer insights into virus-host interaction [ 62 ]. In mosquito genomes, a large number of non-retroviral endogenous viral elements have been detected, and these have been associated with the vector capacity of the species [ 63 ]. For example, these can be associated with the production of small RNAs that unfold a response targeting incoming viral transcripts to modulate viral titre, acting as an exogenous antiviral agent that improves the efficiency of the host as an arbovirus vector. In dipterans, the integration of structural viral regions like the nucleoprotein, glycoprotein and matrix regions of the viruses has been more common than non-structural regions integration like the replicase [ 16 ]. The virus-midge interaction in Culicoides is a complex process that hasn’t been thoroughly studied [ 64 ]. Four integrated viral sequences have been reported in C. sonorensis , of which three were related to the family Phasmaviridae and one to the Chuviridae . The hit length ranged from 308 to 998 bp, and the pairwise identity ranged from 25.30–35.20% [ 16 ]. In dipterans, with the exception of the Aedes mosquito genome, in which more than 200 nrEVEs have been identified, a low number of integrated viral sequences have been described (0–1 in Drosophila melanogaster , 1 in Phlebotomus papatasi , 7 in ​​ Musca domestica , 5 in tephritid fruit flies, 1–3 in species of Culicidae and Anopheles ) [ 65 ]. In tephritid fruit flies, the most abundant nrEVEs reported are Rhabdoviridae -derived EVEs, and this was also found for mosquitos [ 65 ], [ 66 ]. Nevertheless, we consider that an in-depth analysis of nrEVEs in arbovirus vectors is needed and that generating high-quality genome assemblies will be key. In this study, we identified an nrEVE integrated into the genome of C. stellifer that corresponds to the rhabdovirus nucleocapsid proteins, including some matches to VSV. Vesicular stomatitis viruses belong to the family Rhabdoviridae. The genome of VSV has 11,161 nucleotides in length and encodes five major proteins, including the nucleocapsid or ribonucleoprotein. We focused on constructing a library just with the viruses for which Culicoides are known vectors with the goal of providing more supporting evidence that C. stellifer is a vector of arboviruses. The nrEVE identified is the footprint of a germline viral infection and was then transmitted to the offspring. This finding suggests a close and sustained relationship between rhabdo-like viruses with C. stellifer and could indicate that past and present distribution of VSV virus in North America could be linked to this host distribution. The quality of the host genome assembly influences the identification of nrEVEs and was most likely a determinant factor for not finding any arbovirus nrEVE in the genome of C. sonorensis . Assemblies based on short-read technology can mask highly repetitive regions where nrEVEs can be found [ 16 ]. Additionally, it is important to notice that viruses responsible for an existing nrEVE come from ancient viruses or might have undergone significant mutations over time. In that sense, viral query selection and filtering parameters are important parameters that need to be tuned in for the identification of nrEVEs [ 65 ]. Conclusions Insects account for the vast majority of eukaryotic biodiversity, and access to genomic resources remains limited for very small metazoans and megadiverse groups. For vector species, like the ones in the genus Culicoides , this information is critical for understanding the genetics of virus-host association and the evolution of vector competence in dipterans. Here we present the first annotated genome of Culicoides stellifer from a single specimen using PacBio long-reads. We put forward a workflow to approach data generation and analysis for genome assembly projects focused on small insects where the amount of gDNA is less than 1ng. This genome has been key in providing further evidence for the vector capacity of C. stellifer as we found a nrEVE from the nucleoprotein of a virus from the same family as VSV. The fairly expansive distribution of this species in North America and the potential of a range shift due to climate change requires further investigation as ungulate species in the northern latitudes could be at risk. Increasing the amount of genomic information will play a part in developing a multidisciplinary approach to understand virus-host interactions and manage viral pathogen transmission to livestock and wildlife. Declarations Data Availability This genome assembly has been deposited at DDBJ/ENA/GenBank under the accession JBDOCM000000000. The version described in this paper is version JBDOCM010000000. The annotated mitochondrial genome was deposited in GenBank under the accession PP873183. Code Availability *GitHub repository-under construction Author Contributions J.C.L, Y.M.G, and S.J.A conceived the project. J.C.L and Y.M.G collected the specimens. J.C.L, Y.M.G, and T.A.E. assembled, annotated, and analyzed the genome. T.A.E. analyzed and described the annotated repeat libraries and conducted the viral integration analysis. J.C.L. led the writing of the manuscript with assistance from Y.M.G, T.A.E., R.H., and D.S. All authors read and approved the final manuscript for submission. Competing Interests The authors declare that they have no competing interests. Funding Declaration This research was supported by the Arrell Food Institute Scholarship Program (J.C.L), a Discovery Grant from The Natural Sciences and Engineering Research Council of Canada (S.J.A), and the Food from Thought research program at the University of Guelph with funding from the Canada First Research Excellence Fund (S.J.A, D.S). Y.M.G was supported by Mitacs through the Mitacs Elevate Program. Acknowledgements We highly appreciate Kate Lindsay's support with the morphological identification of the specimens and taking the photographs. We thank Olga Shevchenko from the University of Delaware DNA Sequencing & Genotyping Center for assistance with data generation. We also thank Amanda Meuse, Elizabeth G. Mandeville, Toby Baril and Robert Gifford for valuable insights regarding genomic analysis and software troubleshooting. References Borkent A, Dominiak P. Catalog of the Biting Midges of the World (Diptera: Ceratopogonidae), Zootaxa , vol. 4787, no. 1, p. zootaxa.4787.1.1, Jun. 2020, 10.11646/zootaxa.4787.1.1 . Borkent A, Grogan WL Jr. Catalog of the New World biting midges north of Mexico (Diptera: Ceratopogonidae), Zootaxa , vol. 2273, no. 1, pp. 1-48-1–48, 2009. McGregor BL, Shults PT, McDermott EG. 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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-4623838","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":323451723,"identity":"c1ef293f-4172-4833-8da5-4f9b8c80ef1d","order_by":0,"name":"Jessica Castellanos-Labarcena","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYBACxgYwJcHDD+FbMBgQpeUAg42MJFQvYS1gcIAhzcbgALFamNsPP/78oeIwj/GN5MOveSok8swZmB9+wOuwnjQziQNnDvOY3UhLs+Y5I1Fs2cBmLIFXywwGM4aDbSAtOWbGvG0SiRsO8DAQ0ML++cPBf0CHzQBp+QfWwvwDvxYeA4mDDWlAMsf4MW8DWAsbflt6csokzhyz4ZE48yyNcc4xiWKDw2xmFvi0GLYf3/yhokbCnr89+fCHNzU2eQbHmx/fwKulAcEGuyeBgRmfeiCQR2IzfwBrGQWjYBSMglGABgCrjkrid91NGQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Guelph","correspondingAuthor":true,"prefix":"","firstName":"Jessica","middleName":"","lastName":"Castellanos-Labarcena","suffix":""},{"id":323451724,"identity":"eb5fd608-eab3-4580-8105-ff94db916891","order_by":1,"name":"Yoamel Milián-García","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Yoamel","middleName":"","lastName":"Milián-García","suffix":""},{"id":323451725,"identity":"375c42bf-ed95-4755-9262-b0e20fdbf8d3","order_by":2,"name":"Tyler A. Elliott","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Tyler","middleName":"A.","lastName":"Elliott","suffix":""},{"id":323451726,"identity":"ea928d17-9b71-40dd-836e-d0426457b29a","order_by":3,"name":"Dirk Steinke","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Dirk","middleName":"","lastName":"Steinke","suffix":""},{"id":323451727,"identity":"6bf295bb-5e0d-4b4b-9688-caf4fc49e51f","order_by":4,"name":"Robert Hanner","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"","lastName":"Hanner","suffix":""},{"id":323451728,"identity":"e28bc27d-d076-4024-9e2f-c78f0abe8fed","order_by":5,"name":"Sarah J. Adamowicz","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"J.","lastName":"Adamowicz","suffix":""}],"badges":[],"createdAt":"2024-06-23 04:53:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4623838/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4623838/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12864-025-11449-5","type":"published","date":"2025-03-14T15:58:14+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60394838,"identity":"c57a2f2d-098a-4efa-9653-dc33488accaa","added_by":"auto","created_at":"2024-07-16 09:40:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":907821,"visible":true,"origin":"","legend":"\u003cp\u003eGenome properties based on raw data exploration. (A) GenomeScope results in linear coordinates on the PacBio Hifi sequencing dataset for one individual of \u003cem\u003eCulicoides stellifer.\u003c/em\u003e The genome size (len) is predicted to be around 104 Mb, and 88.6% of the 19-mers are unique (aa), suggesting that the genome has around 11% repetitive content. Heterozygosity (ab), mean k-mer coverage for heterozygous bases (kcov), read error rate (err), the average rate of read duplications (dup), k-mer size used in the run (k:), and ploidy (p:) is also reported. The sequencing errors are identified by low-coverage \u003cem\u003eK\u003c/em\u003e-mers. (B) Frequency histogram of the read length for the PacBio Hifi sequencing dataset for one individual of \u003cem\u003eCulicoides stellifer\u003c/em\u003e. The dashed lines represent the mean value.\u003c/p\u003e","description":"","filename":"Figure1culicoides.png","url":"https://assets-eu.researchsquare.com/files/rs-4623838/v1/56449faf4c8cf1b9d2787b1e.png"},{"id":60395369,"identity":"12ef4141-7f6a-4220-b719-a66d31b11242","added_by":"auto","created_at":"2024-07-16 09:48:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":120371,"visible":true,"origin":"","legend":"\u003cp\u003eMitochondrial genome annotation for \u003cem\u003eCulicoides stellifer. \u003c/em\u003eProtein-coding genes, rRNA, and tRNA are represented in green, brown and orange, respectively. The control region (D-loop) is marked in blue, and the intergenic spacers are marked in red. The annotation was completed using MITOS2 v2.1.8, and the figure was generated using Geneious prime v11:08.\u003c/p\u003e","description":"","filename":"Figure2culicoides.png","url":"https://assets-eu.researchsquare.com/files/rs-4623838/v1/7316be3ef21cf35a0e24c7a0.png"},{"id":60394840,"identity":"8d5af725-7dfc-4d30-9178-aac97b456163","added_by":"auto","created_at":"2024-07-16 09:40:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1782078,"visible":true,"origin":"","legend":"\u003cp\u003eContig-level assembly of \u003cem\u003eCulicoides stellifer. \u003c/em\u003e(A) Snail plot showing lengths of all contigs. The longest contig is represented in red, N50 in dark orange, and N90 in light orange. The outer ring shows the GC content of the genome. (B) Visualization of assembly contiguity showing contig sizes on the Y-axis for which x percent of the assembly consists of contigs of at least that size. The three assemblies of \u003cem\u003eCulicoides stellife\u003c/em\u003er with various levels of similarity purging are compared to the assembly of \u003cem\u003eCuliocides sonorensis\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"Figure3culicoides.png","url":"https://assets-eu.researchsquare.com/files/rs-4623838/v1/83929fecf31626a4fed39802.png"},{"id":60394837,"identity":"e89369af-7831-4832-917b-0f935ab5d4ce","added_by":"auto","created_at":"2024-07-16 09:40:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1345824,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentation of the non-retroviral endogenous viral element (nr-EVE) sequence found in the \u003cem\u003eCulicoides stellifer\u003c/em\u003e assembly and the surrounding structural elements in that section of the genome. The sequence is shown aligned to other Rhabdoviruses sequences.\u003c/p\u003e","description":"","filename":"Figure4culicoides.png","url":"https://assets-eu.researchsquare.com/files/rs-4623838/v1/835ca5b3458ad14123b8206f.png"},{"id":78689019,"identity":"0dea5201-bd90-4a2a-b139-c32354eeb14c","added_by":"auto","created_at":"2025-03-17 16:10:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6803763,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4623838/v1/0239433a-3793-4012-b387-1fb3f4ef9587.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Single specimen genome assembly of Culicoides stellifer shows evidence of a non-retroviral endogenous viral element","fulltext":[{"header":"Background","content":"\u003cp\u003e \u003cem\u003eCulicoides\u003c/em\u003e biting midges (Diptera: Ceratopogonidae) are among the most important vectors of arboviruses pathogenic to livestock and wildlife. The genus is highly diverse, with 1,347 valid species [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], of which 151 are currently recognized in North America, occupying a broad geographical range [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Here, \u003cem\u003eC. sonorensis\u003c/em\u003e and \u003cem\u003eC. insignis\u003c/em\u003e are the only species with confirmed vector status and they are known to transmit bluetongue virus [BTV], vesicular stomatitis virus (VSV), and epizootic hemorrhagic disease virus [EHDV] [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Reports of increased rates of BTV and EHDV outside of the geographic range of both species suggest that there might be an expansion or shift in species distribution due to climate change, or other species not recognized as vectors could be involved [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. One of such putative vector species is \u003cem\u003eCulicoides stellifer\u003c/em\u003e (Coquillett, 1901), abundant and widely distributed in the United States of America (USA) and eastern Canada. Several field-collected individuals in the USA have been confirmed to carry arboviruses, but it has been challenging to complete vector competence assays [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. \u003cem\u003eC. stellifer\u003c/em\u003e has been closely associated with ungulate species, although host associations for many Neartic species are poorly understood [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the serious threat to animal health these vectors represent and the significant economic losses outbreaks could cause, there is a lack of genomic studies of \u003cem\u003eCulicoides\u003c/em\u003e, as well as little understanding of the systematics of the group [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The genome assembly of only two species is available in NCBI; \u003cem\u003eC. sonorensis\u003c/em\u003e (GCA_900258525.3) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and \u003cem\u003eC. brevitarsis\u003c/em\u003e (GCF_036172545.2). Partial or complete annotated mitogenomes, which are a valuable resource for studying the phylogenetics and systematics, are available for only four species (\u003cem\u003eC. arakawae\u003c/em\u003e, \u003cem\u003eC. sonorensis, C. brevitarsis\u003c/em\u003e and \u003cem\u003eC. biguttatus\u003c/em\u003e) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Genomic information is critical for understanding the unique evolutionary features of this group, phylogenetic relationships, vector competency for arboviruses, and cryptic diversity [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. One of the main causes that only a limited amount of \u003cem\u003eCulicoides\u003c/em\u003e genomes have been sequenced in is perhaps the difficulty to obtain sufficient quantities of high molecular weight DNA. Species are small, \u0026lt; 3 mm body length, which typically generates very low concentration DNA extracts from single specimens (\u0026lt;\u0026thinsp;1 ng/uL) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdvances in long-read sequencing technologies that allow low amounts of input material and modifications to increase starting DNA concentration for library preparation have opened the door to generating high-quality genome assemblies for small arthropods [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Particularly, the PacBio HiFi ultra-low DNA input workflow starts with as low as 5 ng genomic DNA for whole-genome amplification and is recommended for genome sizes of up to 500 Mb. This workflow was used to generate a \u003cem\u003ede novo\u003c/em\u003e genome assembly for \u003cem\u003eDrosophila melanogaster\u003c/em\u003e [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and two submillimeter Collembola species (\u003cem\u003eDesoria tigrina\u003c/em\u003e and \u003cem\u003eSminthurides aquaticus\u003c/em\u003e) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. It allows sequencing the genome from a single, field-preserved specimen, generating medium-size fragments (10\u0026ndash;25 kb) with high base accuracy (99.8%), which can be used to produce assemblies that are more contiguous and with a higher base accuracy.\u003c/p\u003e \u003cp\u003eThe expansion of \u003cem\u003eCulicoides\u003c/em\u003e-borne pathogens in Eastern Canada, especially in Ontario, highlights the need to characterize potential vectors, viruses and hosts. \u003cem\u003eC. stellifer\u003c/em\u003e is suspected to represent a species complex, with cryptic diversity reported for samples collected in Ontario [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In this study we present a high-quality genome assembly of a \u003cem\u003eCulicoides stellifer\u003c/em\u003e specimen collected in Southern Ontario. In an attempt to provide more supporting evidence that this species may transmit one or more RNA viruses, we set out to query the genome for viral fragments, also known as non-retroviral endogenous viral elements (nrEVE) of BTV, EHDV, VSV and West Nile virus (WNV) viruses [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This phenomenon is known as virus-to-host horizontal gene transfer and is associated with persistent viral infection [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Given the complexity of \u003cem\u003eCulicoides\u003c/em\u003e pathogens, crypticity, and unknown vector species, we developed a methodology and a bioinformatics pipeline to generate key genomic information for this group. This will significantly contribute to identifying new vector species, understanding the phylogenetic relationships of the group, and evolutionary processes involved in vector competence across Diptera.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003eSample collection and genome sequencing\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003eCulicoides stellifer\u003c/em\u003e specimens were collected at the Ontario Veterinary College Dairy Barn at the University of Guelph, Ontario, Canada, using miniature Centre for Disease Control (CDC) UV light traps (Bioquip, CA, USA). The specimens were identified using the dichotomous key for \u003cem\u003eCulicoides\u003c/em\u003e of Ontario [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Five female individuals preserved in 95% ethanol were sent to the University of Delaware\u0026rsquo;s DNA Sequencing \u0026amp; Genotyping Center in Newark, DE, USA. As \u003cem\u003eCulicoides\u003c/em\u003e species are less than 3 mm long and weigh\u0026thinsp;\u0026lt;\u0026thinsp;1 mg, we decided to use the ultra-low DNA Input protocol from PacBio [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] to generate genomic data from a single specimen. Genomic DNA was extracted from each individual separately using the MagAttract HMW DNA kit (Qiagen). DNA quantification was completed using a Qubit Fluorimeter, and DNA fragment sizes were assessed by a Femto Pulse system (Agilent) for fragments of a length around 12\u0026ndash;14 kb. The amount and quality of genomic DNA for only one individual was sufficient to move forward with library preparation.\u003c/p\u003e \u003cp\u003eSMRTbell gDNA was constructed following the protocol \u0026ldquo;Preparing HiFi SMRT-bell libraries from Ultra-Low DNA input\u0026rdquo; using the SMRTbell Express Template Prep Kit 3.0 (Pacbio, 102-182-700). After a BluePippin size selection (Sage Science, PAC20KB) at 6 kb, the average library size was 10 kb measured on a Femto Pulse system Agilent). Sequencing was performed on a SMRT 8M cell on the Sequel IIe using the Sequel II Binding kit 2.2/Sequel II Sequencing kit 2.0 with a 30-hours movie.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePreassembly Processing\u003c/h2\u003e \u003cp\u003ePacBio Hifi reads were first processed to trim PCR adapter sequences and to remove PCR duplicates. We used the \u003cem\u003elima\u003c/em\u003e for PCR adapter trimming and \u003cem\u003epbmarkdups\u003c/em\u003e for PCR duplicate removal, both available in \u003cem\u003epbbioconda\u003c/em\u003e (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/PacificBiosciences/pbbioconda\u003c/span\u003e\u003cspan address=\"https://github.com/PacificBiosciences/pbbioconda\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Properties of the genome, such as genome size, levels of heterozygosity and repeat content, were estimated by analysis of \u003cem\u003eK\u003c/em\u003e-mer frequencies. We used Meryl v1.4.1, as implemented in Merqury v1.3 [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and used the size of the \u003cem\u003eCulicoides sonorensis\u003c/em\u003e genome as a reference [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] to estimate the \u003cem\u003ek\u003c/em\u003e-mer size to use. Frequencies of \u003cem\u003ek\u003c/em\u003e-mers (\u003cem\u003eK\u003c/em\u003e\u0026thinsp;=\u0026thinsp;19) were counted using Meryl v1.4.1. With the \u003cem\u003ek\u003c/em\u003e-mer histogram, we estimated the genome properties using GenomeScope v2.0 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMitogenome assembly and annotation\u003c/h2\u003e \u003cp\u003eFor the assembly of the mitochondrial genome, we used MitoHiFi v3.2 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], starting with the raw reads. The first assembled mitogenome was significantly larger than expected, so we decided to use only reads mapped to the reference genome (\u003cem\u003eCulicoides (Meijerehelea) arakawae Arakawa\u003c/em\u003e, 1910) and assembled the mitogenome using Pacific Biosciences\u0026rsquo; Improved Phase Assembly (IPA, v1.8.0) HiFi Genome Assembler pipeline (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/PacificBiosciences/pbipa\u003c/span\u003e\u003cspan address=\"https://github.com/PacificBiosciences/pbipa\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e We annotated the mitogenome using MITOS2 v2.1.8 as implemented in the Galaxy workbench [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eGenome assembly\u003c/h2\u003e \u003cp\u003eGenome assembly was conducted after removing the mitochondrial genome reads. We used two assemblers, IPA v1.8.0 and Hifiasm v0.16.0 [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. For Hifiasm, we used different similarity thresholds for duplicate haplotypes to be purged (-s parameter) following the author\u0026rsquo;s recommendations (s\u0026thinsp;=\u0026thinsp;0.75, s\u0026thinsp;=\u0026thinsp;0.55, and s\u0026thinsp;=\u0026thinsp;0.35). The overall quality of these preliminary assemblies, especially continuity and completeness, was estimated using assembly-stats v17.02 (rjchallis/assembly-stats 17.02) and Benchmarking Universal Single-Copy Orthologs (BUSCO) v5.6.1 [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] with a Diptera database (diptera_odb10.gz). Given the high level of duplication of preliminary assemblies and the large size of genomes compared to the predicted value, we conducted \u003cem\u003ea posteriori\u003c/em\u003e purging of duplicates using \u003cem\u003epurge_dups\u003c/em\u003e [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The resulting assemblies showed similar characteristics in terms of contiguity and completeness; we selected the assembly generated with Hifiasm -s 0.35 for subsequent analyses as it has the largest N50 value. To further evaluate the quality of the assembly, we used Merqury v1.4.1 [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] to estimate base-level accuracy and completeness as well as BlobToolkit for contamination identification and isolation [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eGenome annotation\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRepeat element annotation.\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eWe annotated transposable elements (TE), satellite DNA, simple and low-complexity repeats using Earl Grey v.4.1.1 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Via Earl Grey, we used RepeatMasker v.4.1.6 [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] to identify and mask simple and low-complexity repeats, along with the Diptera subset of repeats from the growing, open source repeat reference library Dfam v.3.7 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Once masked for these repeats, the genome was analyzed with RepeatModeler2 v.2.0.5 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] for de novo repeat identification and classification. Earl Grey next employed a BLAST-extract-align-trim procedure on each repeat consensus sequence to refine their boundaries and improve the quality of the reference library, along with clustering of consensus sequences using CD-HIT to reduce redundancy [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Next, LTR_FINDER [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] was used to further detect any missing long terminal repeat (LTR) retrotransposons before combining all collected repeats and masking and annotating the genome once more with RepeatMasker. Finally, Earl Grey used RepeatCraft [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] to merge physically close or overlapping repeat fragments in the annotation which have the same classification. The library of generated consensus sequences was translated into open reading frames of at least 300 bp in all six frames using getorf [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], and these were queried against the Pfam v.35.0 [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] protein reference library using pfam_scan.pl to detect instances of host gene contamination in the repeat reference library. The output was manually inspected due to the small size of the reference library, and 22 consensus sequences were removed from the library.\u003c/p\u003e \u003cp\u003eTo provide additional evidence for the proper classification of TEs, the tool TEsorter v1.4.6 [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] was employed to extract open reading frames from all reference sequences, query them using hmmscan against compiled protein reference libraries of terminal inverted repeat (TIR) DNA transposons [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], long interspersed nuclear elements (LINE) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] and LTR retrotransposons [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Due to the large proportion of unknown repeats, in terms of the number consensus sequences and percentage of total repeats annotated, all RepeatModeler2 consensus sequences of at least 100 bp and covering at least 10,000 in the assembly were manually inspected. For each consensus sequence, this involved one or more of the following steps recommended by Goubert et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]: 1) use of TE_ManAnnot to extract blast hits for each consensus that were at least half the size of the consensus, along with enough flanking DNA to resolve the termini of the given consensus, 2) alignment of all hits using MAFFT v7.453 [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] to accommodate the high frequency of indels in repeats, 3) the removal of gaps in the alignment where 80% of the sequences featured a gap via T-COFFEE v13.46.0 [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], 4) the inspection of the alignment to confirm the consensus sequence did not need to be extended or adjusted, 5) the creation of a new consensus sequence when needed via cons in EMBOSS, and 6) the use of TE-Aid to visualize the size and number of hits of a given consensus, the divergence of hits from the consensus, the presence of repetitive structures within the consensus, and the presence of TE coding regions via blastp to the RepeatMasker RepeatPeps protein database.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e● Gene prediction and functional annotation\u003c/h2\u003e \u003cp\u003eWe completed the gene prediction on the soft-masked genome assembly using the BRAKER3 v3.0.8 pipeline [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], providing protein homology information as extrinsic evidence. We used the Arthropoda clade-partitioned file of OrthoDB 11 [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] as the source of reference protein sequences. We functionally annotated the predicted protein-coding genes using DIAMOND BLASTP [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], searching against the Swiss-Prot protein database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.uniprot.org/\u003c/span\u003e\u003cspan address=\"https://www.uniprot.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e We filtered the output for E-value\u0026thinsp;\u0026lt;\u0026thinsp;1e-10 and sequence identity\u0026thinsp;\u0026gt;\u0026thinsp;30%. The predicted genes were also mapped to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to classify functional categories using BlastKOALA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.kegg.jp/blastkoala/\u003c/span\u003e\u003cspan address=\"https://www.kegg.jp/blastkoala/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Additionally, we ran InterProScan v5.67-99.0 [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] with all default settings and added the option of looking for the Gene Ontology (GO) annotation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eNon-retroviral endogenous viral identification\u003c/h2\u003e \u003cp\u003eNucleotide sequences for EHDV, VSV and WNV viruses were downloaded from GenBank, and the curated set of BTV sequences from BTV-GLUE [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Incomplete and artificial sequences were filtered out along with VSV and WNV viruses shorter than 10 000 bp by data processing in R v.4.3.2 [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], aided by tidyverse v2.0.0 [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], Biostrings v2.70.2 [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] and seqRFLP v1.0.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/helixcn/seqRFLP\u003c/span\u003e\u003cspan address=\"https://github.com/helixcn/seqRFLP\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). EHDV is a virus with a segmented genome, so each fragment was detected and sorted before multiple sequence alignments were built for each viral segment, or whole virus for the others, using MUSCLE [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] and default settings. A hidden Markov model (HMM) was generated for each alignment using hmmbuild in HMMER3 [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], and the \u003cem\u003eC. stellifer\u003c/em\u003e, \u003cem\u003eC. sonorensis\u003c/em\u003e (GCA_900258525.3) and \u003cem\u003eC. brevitarsis\u003c/em\u003e (GCA_036172545.2) assemblies were queried against each of these models using nhmmer, along with the raw reads used in creating the \u003cem\u003eC. stellifer\u003c/em\u003e assembly.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eHifi sequencing with ultra-low DNA input workflow\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The ultra-low DNA input protocol includes a PCR amplification step to generate sufficient material for sequencing. This was a critical consideration when selecting this workflow to generate high-quality genomic information from a single \u003cem\u003eC. stellifer\u003c/em\u003e specimen. \u0026nbsp;PCR products ranged from 5-8 kb. These values suggest that the gDNA had some degree of fragmentation and that short fragments were preferentially amplified. Sequencing output resulted in 191,906 PacBio Hi-Fi reads with an average read length of ~ 13,000 bp. \u0026nbsp;The genome size was estimated to be approximately 104 Mb, with a heterozygosity of 2.88% and 11.4% of repeat sequences (Figure 1). \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1: Genome properties based on raw data exploration. (A) GenomeScope results in linear coordinates on the PacBio Hifi sequencing dataset for one individual of \u003cem\u003eCulicoides stellifer.\u003c/em\u003e The genome size (len) is predicted to be around 104 Mb, and 88.6% of the 19-mers are unique (aa), suggesting that the genome has around 11% repetitive content. Heterozygosity (ab), mean k-mer coverage for heterozygous bases (kcov), read error rate (err), the average rate of read duplications (dup), k-mer size used in the run (k:), and ploidy (p:) is also reported. The sequencing errors are identified by low-coverage \u003cem\u003eK\u003c/em\u003e-mers. (B) Frequency histogram of the read length for the PacBio Hifi sequencing dataset for one individual of \u003cem\u003eCulicoides stellifer\u003c/em\u003e. The dashed lines represent the mean value.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMitogenome Assembly\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLong-read sequencing technologies for mitochondrial genome assembly in \u003cem\u003eCulicoides\u003c/em\u003e haven\u0026rsquo;t been explored before. We started by using the MitoHifi toolkit for mitochondrial assembly from Hifi data. When using raw data and assembled contigs with Hifiasm, the pipeline failed to correctly assemble the mitochondrial genome, as it generated a molecule much larger than expected (~ 50,000 bp). It is likely that the misassembly might be related to shorter reads, insufficient \u0026nbsp;coverage, or the presence of nuclear-mitochondrial DNA (NUMTs). We selected 128 reads that mapped to a reference mitogenome (\u003cem\u003eC. arakawae\u003c/em\u003e) and generated a \u003cem\u003ede-novo\u003c/em\u003e assembly for \u003cem\u003eC. stellifer\u0026rsquo;s\u003c/em\u003e mitochondrial genome using IPA assembler. This resulted in a 16,607 bp mitochondrial genome, which is within the range of mitogenome lengths previously reported for other species of the genus [9, 54].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 2: Mitochondrial genome annotation for \u003cem\u003eCulicoides stellifer.\u0026nbsp;\u003c/em\u003eProtein-coding genes, rRNA, and tRNA are represented in green, brown and orange, respectively. The control region (D-loop) is marked in blue, and the intergenic spacers are marked in red. The annotation was completed using MITOS2 v2.1.8, and the figure was generated using Geneious prime v11:08.\u003c/p\u003e\n\u003cp\u003eThe annotation using MITOS2 identified 13 protein-coding genes (PCGs), 22 transfer RNAs \u0026nbsp;(tRNA), and two ribosomal RNAs (rRNA). The assembly was circularized and overall it showed the same gene arrangement previously described for other species in the genus. PCGs sizes ranged from 152 (ATP8) to 1,732 bp (NAD5). Transfer RNA sizes ranged from 48 [tRNA F(gaa) to 72 bp [tRNA V(tac)], while rRNA lengths were 781 (rRNA S) and 1,284 bp (rRNA L). The estimated control region size was 1,842 bp. Additionally, 17 spacers were identified, ranging in size from 1 to 18 bp.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenome assembly\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe compared two long-read assembly tools (IPA and Hifiasm) and various levels of duplicate purging in Hifiasm (-s parameter). Overall, Hifiasm produced the best assemblies. All four initial assemblies resulted in primary genomes with a size \u0026gt;146 Mb and almost 30% of complete-duplicated genes reported by BUSCO. Different values of the similarity threshold for duplicate haplotigs (- s parameter) in the Hifiasm assemblies resulted in a slight decrease in the total number of contigs and an increase in the N50, producing overall similar values (Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePurging duplicated regions with purge_dups reduced was successful in reducing the number of contigs by half, increased contiguity and significantly decreased the number of duplicated genes reported by BUSCO (Table 1). The 119 Mb size assembled genome is closer to the estimate of 105 Mb obtained from the k-mer analysis. In comparison to the other two available \u003cem\u003eCulicoides\u003c/em\u003e genomes, our assembly displays good quality in terms of contiguity (N50 and L50) and completeness (Figure 3). The BUSCO scores of our assemblies (89.8 % complete (C) BUSCOs (including 2.0 % duplicated [D]), 1.5 % fragmented (F), and 8.6 % missing (M)) are very similar to those of the genome of \u003cem\u003eC. brevitarsis,\u0026nbsp;\u003c/em\u003ewhose assembly includes three chromosomes and unplaced scaffolds. Our genome also is of significantly higher quality than that of \u003cem\u003eC. sonorensis\u003c/em\u003e, as the latter involved pooling many individuals and was generated using short-read sequencing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs our final assembly, we selected the one with the highest N50 and the lowest number of duplicated BUSCOs without significantly decreasing the complete BUSCO score. The genome assembly (referred to as purged_s030) comprises 450 contigs, totalling 119,322,097 bp, contig N50 of 479,264 bp and L50 of 81 (Figure 3). We estimated a high base accuracy (QV=53.3) and 90% completeness based on the k-mer comparison between the assembly and those found in the PacBio raw reads.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1: Summary statistics of the \u003cem\u003eCulicoides stellifer\u003c/em\u003e primary genome assemblies using HiFiasm with three levels of purge duplication and IPA. The only two other genomes of the Genus available in NCBI are included for comparison purposes.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"757\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenome Assembly\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eC.stellifer\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHiFiasm\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-s 0.35\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eC.stellifer\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHiFiasm\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-s 0.35\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003epurge_dups\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eC.stellifer\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHiFiasm\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-s 0.55\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003epurge_dups\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eC.stellifer\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHiFiasm\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-s 0.75\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003epurge_dups\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eC.stellifer\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eIPA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eC.stellifer\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eIPA\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003epurge_dups\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eC.sonorensis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eVelvet\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(GCA_900258525.3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eC.brevitaris\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRaven; Polca (Masurca); Racon.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSequencing technology\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003ePacBio Hifi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003ePacBio Hifi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003ePacBio Hifi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003ePacBio Hifi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003ePacBio Hifi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003ePacBio Hifi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003eIllumina HiSeq\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003eOxford Nanopore PromethION; Illumina NovaSeq\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"9\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenome statistics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal length (Mb)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e155.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e129.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of contigs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e463\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e730\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e3858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e223\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of scaffolds\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLongest contig or scaffold (bp)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e1,731,460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e1,731,461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e1,731,460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e1,731,460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e1,156,022\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e1,156,022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e763,582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e46,604,242\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean contig or scaffold length (bp)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e194,770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e265,155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e264,809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e259,459\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e199,980\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e195,305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e40,420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e863,398\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN50\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e356,049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e479,265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e459,312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e458,458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e289,321\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e306,443\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e109,184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e3.5 Mb\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e84,987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e132,711\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e132,524\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e113,333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e104,260\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e98,560\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eL50\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eL90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e476\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGC content\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e30.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e30.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e30.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e30.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e30.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e30.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e28.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e27.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"9\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal BUSCO for the genome assembly\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComplete BUSCO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e2970\u003c/p\u003e\n \u003cp\u003e(90.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e2953\u003c/p\u003e\n \u003cp\u003e(89.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e2942\u003c/p\u003e\n \u003cp\u003e(89.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e2950\u003c/p\u003e\n \u003cp\u003e(89.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e2955\u003c/p\u003e\n \u003cp\u003e(89.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e2942\u003c/p\u003e\n \u003cp\u003e(89.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e89.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e91.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComplete single copy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e2113\u003c/p\u003e\n \u003cp\u003e(64.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e2882\u003c/p\u003e\n \u003cp\u003e(87.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e2870\u003c/p\u003e\n \u003cp\u003e(87.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e2875\u003c/p\u003e\n \u003cp\u003e(87.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e1962\u003c/p\u003e\n \u003cp\u003e(59.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e2881\u003c/p\u003e\n \u003cp\u003e(87.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e63.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e89.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComplete duplicated\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e857\u003c/p\u003e\n \u003cp\u003e(26.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003cp\u003e(2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003cp\u003e(2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003cp\u003e(2.3%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e993\u003c/p\u003e\n \u003cp\u003e(30.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003cp\u003e(1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e26.5%\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e2.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFragmented\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003cp\u003e(1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003cp\u003e(1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003cp\u003e(1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003cp\u003e(1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003cp\u003e(1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003cp\u003e(1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e4.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e0.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMissing\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.64332892998679%\" valign=\"top\"\u003e\n \u003cp\u003e265\u003c/p\u003e\n \u003cp\u003e(8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e281\u003c/p\u003e\n \u003cp\u003e(8.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.624834874504623%\" valign=\"top\"\u003e\n \u003cp\u003e283\u003c/p\u003e\n \u003cp\u003e(8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e281\u003c/p\u003e\n \u003cp\u003e(8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.775429326287979%\" valign=\"top\"\u003e\n \u003cp\u003e276\u003c/p\u003e\n \u003cp\u003e(8.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.228533685601057%\" valign=\"top\"\u003e\n \u003cp\u003e288\u003c/p\u003e\n \u003cp\u003e(8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e6.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.756935270805812%\" valign=\"top\"\u003e\n \u003cp\u003e7.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Table 1* \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 3: Contig-level assembly of \u003cem\u003eCulicoides stellifer.\u0026nbsp;\u003c/em\u003e(A) Snail plot showing lengths of all contigs. The longest contig is represented in red, N50 in dark orange, and N90 in light orange. The outer ring shows the GC content of the genome. (B) Visualization of assembly contiguity showing contig sizes on the Y-axis for which x percent of the assembly consists of contigs of at least that size. The three assemblies of \u003cem\u003eCulicoides stellife\u003c/em\u003er with various levels of similarity purging are compared to the assembly of \u003cem\u003eCuliocides sonorensis\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenome annotation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall, the degree of repetitive content in the genome assembly of \u003cem\u003eCulicoides stellifer\u003c/em\u003e was \u0026nbsp; approximately 15 Mb of repetitive elements, representing 11 % of the genome assembly (Table 2). Initially, nearly half of all repeats were classified as unknown. Due to the small size of this reference library, it was decided to manually investigate the largest and most abundant consensus sequences as described in the Methods. Many of the unknown repeats were determined to be non-autonomous TIR DNA transposons, and in general, all DNA transposons were characterized by a lack of substantial coding regions for transposases. In an attempt to find autonomous elements, the repeat library output from a larger version of the assembly with less purged duplicates (HiFiasm -s 0.35) was inspected for novel consensus sequences, and these were added to the existing repeat library and the genome was re-annotated. In this new library, a total of 4 consensus sequences of DNA transposons (TcMar-Tc1, TcMar-Tigger, TcMar-ISRm11, hAT-Tip100) had partial coding regions, but none of these appear to be functional. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eComparison and selective melding of the two libraries added new consensus sequences for four LTR retrotransposons with coding regions and well-resolved termini, as well as several LINE elements including an R2 consensus sequence. Retrotransposons make up a smaller fraction of the genome than DNA transposons, which stands in contrast to the pattern seen in the \u003cem\u003eC. sonorensis\u003c/em\u003e genome [7]. Caution should be taken when comparing the repeats in these two genomes, as the methods differed and the repeat annotation in the \u003cem\u003eC. sonorensis\u003c/em\u003e assembly was not as thorough as was done for \u003cem\u003eC. stellifer\u003c/em\u003e. In general, the \u003cem\u003eC. stellifer\u003c/em\u003e assembly has a lower repeat content than \u003cem\u003eC. sonorensis\u003c/em\u003e ( ~11% vs 29.7%); however, when \u0026nbsp; that repeat content is positively correlated with genome or assembly size [55], this is not surprising.\u003c/p\u003e\n\u003cp\u003eTable 2: Summary of repeat elements annotated in the \u003cem\u003eCulicoides stellifer\u003c/em\u003e assembly. The numbers of consensus sequences in parentheses represent those generated by RepeatModeler2.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"547\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.53016453382084%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRepeat\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.497257769652652%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSuperfamily\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.270566727605118%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBase pairs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.70201096892139%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eConsensus Sequences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.53016453382084%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDNA transposon\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.497257769652652%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.270566727605118%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.70201096892139%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.53016453382084%\" rowspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eTIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.497257769652652%\" valign=\"top\"\u003e\n \u003cp\u003eNon-Autonomous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.270566727605118%\" valign=\"top\"\u003e\n \u003cp\u003e2,563,172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.70201096892139%\" valign=\"top\"\u003e\n \u003cp\u003e66 (59)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003ehAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e496,695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e9 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003eTc1/Mariner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e103,081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e9 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003epiggyBac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e55,206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003eOther TIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e4,132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cu\u003eTotal DNA\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e3,222,286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e97 (71)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.53016453382084%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRetrotransposon\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.497257769652652%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cu\u003e\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.270566727605118%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.70201096892139%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.53016453382084%\" rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eLTR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.497257769652652%\" valign=\"top\"\u003e\n \u003cp\u003eBel-Pao\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.270566727605118%\" valign=\"top\"\u003e\n \u003cp\u003e202,125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.70201096892139%\" valign=\"top\"\u003e\n \u003cp\u003e41 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003eTy1/Copia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e100,586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e20 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003eTy3-like\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e87,488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e54 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003eUnclassified LTR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e48,094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e2 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cu\u003eTotal LTR\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e423,038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e117 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.53016453382084%\" rowspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003eLINE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.497257769652652%\" valign=\"top\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.270566727605118%\" valign=\"top\"\u003e\n \u003cp\u003e239,478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.70201096892139%\" valign=\"top\"\u003e\n \u003cp\u003e30 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003eUnclassified LINE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e121,740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003eCR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e91,715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e26 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003eR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e48,480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003eRTE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e27,718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cu\u003eTotal LINE\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e529,131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e65 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.26315789473684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cu\u003eTotal Retrotransposon\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.42105263157895%\" valign=\"top\"\u003e\n \u003cp\u003e952,169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e182 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.53016453382084%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.497257769652652%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal TE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.270566727605118%\" valign=\"top\"\u003e\n \u003cp\u003e4,174,455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.70201096892139%\" valign=\"top\"\u003e\n \u003cp\u003e279 (102)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.53016453382084%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther Repeats\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.497257769652652%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.270566727605118%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.70201096892139%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.53016453382084%\" valign=\"top\"\u003e\n \u003cp\u003eSatellite/Simple/Low complexity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.497257769652652%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.270566727605118%\" valign=\"top\"\u003e\n \u003cp\u003e6,107,679\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.70201096892139%\" valign=\"top\"\u003e\n \u003cp\u003e2976 (55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.53016453382084%\" valign=\"top\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.497257769652652%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.270566727605118%\" valign=\"top\"\u003e\n \u003cp\u003e5,434,496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.70201096892139%\" valign=\"top\"\u003e\n \u003cp\u003e216 (216)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.53016453382084%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.497257769652652%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Repeats\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.270566727605118%\" valign=\"top\"\u003e\n \u003cp\u003e15,716,630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.70201096892139%\" valign=\"top\"\u003e\n \u003cp\u003e3443 (373)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;*Table2*\u003c/p\u003e\n\u003cp\u003eA breakdown of the contribution of different components of Earl Grey to the resultant repeat library is useful when considering repeat annotation in novel genomes (Table 3.). Dfam is a growing, open-source database of repeats, and its current subset of Dipteran repeats stems from species distantly related to \u003cem\u003eC. stellifer\u003c/em\u003e, hence the limited contribution to the annotation. Rather than being an indictment of Dfam, this stresses the value of submitting consensus sequences to Dfam to increase its taxonomic scope and useability for new genomes. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3. Comparative statistics of repeat sequences detected by various sources and their annotation in the assembly.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"711\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.39381153305204%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRepeat Source\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.347398030942333%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eConsensus Sequences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.05203938115331%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean Coverage/Consensus (bp)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.206751054852322%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Coverage (bp)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.39381153305204%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDfam Diptera\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.347398030942333%\" valign=\"top\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.05203938115331%\" valign=\"top\"\u003e\n \u003cp\u003e1610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.206751054852322%\" valign=\"top\"\u003e\n \u003cp\u003e291,385\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.39381153305204%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRepeatMasker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.347398030942333%\" valign=\"top\"\u003e\n \u003cp\u003e2891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.05203938115331%\" valign=\"top\"\u003e\n \u003cp\u003e966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.206751054852322%\" valign=\"top\"\u003e\n \u003cp\u003e2,792,913\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.39381153305204%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRepeatModeler2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.347398030942333%\" valign=\"top\"\u003e\n \u003cp\u003e373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.05203938115331%\" valign=\"top\"\u003e\n \u003cp\u003e33,644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.206751054852322%\" valign=\"top\"\u003e\n \u003cp\u003e12,549,446\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBRAKER2 predicted 18,895 proteins in the nuclear genome with 18,662 unique sequences. We annotated 10,524 proteins (55.7%) by searching against the Swiss-Prot protein sequence database. 7,283 genes were mapped to KEGG pathways using BlastKOALA (Table 4). Collectively, 7812 proteins were functionally annotated by InterProScan, of which 4057 were assigned a GO term. This resource provides complementary levels of protein annotation, including curated InterPro entries annotated with a unique name and GO terms. The following analyses were included in the output file: PANTHER, CATH-Gene3D, PROSITE Profiles, Pfam, SUPERFAMILY, SMART, FunFam, Conserved Domains Database (CDD), PRINTS, Hamap, PIRSF, NCBIfam and the Structure-Function Linkage Database (SFLD). These represent protein signature databases included in InterPro [56] that were scanned in an integrated way to predict protein functions and for which a match was found. Some of the results of these analyses are included in Table 4.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe annotated more than 3,000 additional protein-coding genes for either the \u003cem\u003eC. sonorensis\u003c/em\u003e (15,612) or the \u003cem\u003eC. brevitarsis\u003c/em\u003e (11,137) genome, respectively. This indicates that our workflow recovered a more complete set of genes for this group. We ran BUSCO in protein mode on the predicted proteins using the diptera_odb10 lineage dataset, which resulted in 91.5% complete BUSCO, including 8.3% duplicated, 1.0% fragmented and 7.5% missing. These values are similar to the report of \u003cem\u003eC. brevitarsis\u003c/em\u003e (GCF_036172545.1-RS_2024_03) except for the complete and duplicated genes for which we report a slightly higher value (2.6% for \u003cem\u003eC. brevitarsis\u003c/em\u003e). This difference is explained by the larger number of proteins predicted by BRAKER2 in our assembly compared to the annotation of \u003cem\u003eC. brevitarsis\u003c/em\u003e using the NCBI Eukaryotic Genome Annotation Pipeline.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4: Functional annotation of \u003cem\u003eCulicoides stellifer\u003c/em\u003e proteins.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenome annotation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of elements\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredicted protein-coding genes (BRAKER2)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e18,895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSwiss Prot\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e10,524\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e55.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eKEGG (BlastKOALA)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e7,342\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e38.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePfam\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e6,209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e32.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterPro\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e6,807\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e36.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e6,026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e31.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Non-retroviral integrated RNA virus fragment identification\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe genome query for integrated viral fragments yielded 38 hits, ranging from 44 bp (74.5% identity) to 322 bp (53.2% identity). Fourteen hits greater than 100 bp were queried against the non-redundant protein database in GenBank using blastx. While most of these returned no similar hits or only to RNA-binding domains of genes, a 322 bp fragment in the \u003cem\u003eC. stellifer\u0026nbsp;\u003c/em\u003eraw reads was found to be similar to VSV. Using blastn we confirmed the presence of this VSV-like fragment in the \u003cem\u003eC. stellifer\u003c/em\u003e assembly (Figure 4) and in conjunction with the gene annotation data, showed that a full 1319 bp coding region for a nucleocapsid was present. A blastx search using this nucleocapsid sequence as a query returned many significant hits (93-98% query coverage, 28.33-38.23% amino acid identity, scores of 161-303, hit length of 1233-1377 bp) to rhabdovirus nucleocapsid proteins in GenBank.\u003c/p\u003e\n\u003cp\u003eFigure 4: Representation of the non-retroviral endogenous viral element (nr-EVE) sequence found in the \u003cem\u003eCulicoides stellifer\u003c/em\u003e assembly and the surrounding structural elements in that section of the genome. The sequence is shown aligned to other Rhabdoviruses sequences.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cb\u003eChallenges for genomic studies in\u003c/b\u003e \u003cb\u003eCulicoides\u003c/b\u003e\u003c/p\u003e \u003cp\u003eInsect genomics faces challenges in obtaining sufficient high-molecular-weight DNA for high-quality genome assemblies of small-size species. \u003cem\u003eCulicoides\u003c/em\u003e sizes range from 1 to 3 mm, which makes it very challenging to obtain high-quality genomic DNA. Here, we demonstrated the utility of the ultra-low DNA input PacBio protocol to sequence high-quality reference genomes from a single \u003cem\u003eCulicoides\u003c/em\u003e individual collected in the field and preserved in ethanol. This opens the door to future biodiversity genomics projects for other small organisms at the millimetre scale. The evidence of some DNA degradation in the sample suggests that fresh frozen insects, or at least fresh-ethanol-preserved specimens kept at -25C, will be preferred for future projects. This is essential as the success of the ultra-low DNA input method depends on the quality of the DNA; particularly, the starting amount of biological material correlates with library complexity and is among the factors affecting PCR duplication rate [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the limitations associated with PCR amplifications, such as low processivity in high-GC regions, the reduction in overall coverage due to PCR duplicate removal, and PCR-introduced errors, we recovered a high-quality genome assembly for \u003cem\u003eCulicoides stellifer\u003c/em\u003e, with a more complete set of genes identified than in any previous assemblies. This might prove that this workflow can be highly efficient for small and not very complex genomes. The only other genome assembly with higher contiguity was generated using Oxford Nanopore data, which has known problems with base pair accuracy and the potential of sequence errors to confound assembly [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAssessing the effect of various levels of duplicate haplotigs purging in combination with two different assembly pipelines was important as insect genomes have high levels of heterozygosity [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. The tool purge_dups allows the search and removal of false heterotype duplications, which are haplotype sequences that are relatively more divergent than other parts of the genome and are classified as separate genomic regions by the assembly algorithms [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. The increased contiguity without affecting the overall BUSCO score demonstrates the importance of this step in the data analysis pipeline, as it is highly efficient in purging duplicated regions. Our assembly shows a lower amount of duplication compared to the assembly of \u003cem\u003eC. sonorensis\u003c/em\u003e. The high level of duplication reported in the latter was likely the result of a misassembly due to heterozygosity in the sample. The authors of the study suggested that the high duplication level could have resulted from genetic variation among/within the sequenced genomes from the pool of individuals (375 males and 150 females) and the representation within the assembly of alternative alleles.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eConsiderations for genome annotation\u003c/h2\u003e \u003cp\u003eThe combination of EarlGrey and BRAKER2 for genome annotation resulted in a comprehensive description of the structural elements of the genome. EarlGrey is a pipeline that offers several advantages over other pipelines used for TE annotation. It is specifically designed to enhance TE consensus sequence length and integrity; during curation, almost no elements needed to be substantially adjusted, and RepeatCraft allows it to address issues related to artificial overlapping and fragmented annotations. The landscape of repetitive elements in the genome assembly of \u003cem\u003eC. stellifer\u003c/em\u003e showed a significant amount of unknown repeats that are neither satellite DNA nor obvious TEs. A recent study examining 600 insect genomes found that a high percentage of repetitive sequences were not classified in most insect lineages (25%-85%). This is mainly associated with reference databases, which have biased representations that impact annotation, particularly affecting insect lineages that have been poorly sampled [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. As well, for novel genomes it is important to evaluate the taxonomic composition of repeats used in the reference library. The sequencing technology is also an important factor in detecting TE elements. This study reported a 36% increase in the detection of repetitive elements (RE), especially LTRs, when the assembly was generated using long-read sequencing platforms. This highlights the significance of our study in demonstrating the feasibility of the ultra-low input protocol and providing a workflow for genome assembly and annotation of tiny hematophagous flies that serve as vectors of a variety of pathogens. By generating more genomes, we can contribute to insect RE databases and develop the field of RE description as part of biodiversity genomic studies.\u003c/p\u003e \u003cp\u003eThe finding of almost no autonomous DNA transposons suggests this genome may be heading to a DNA transposon extinction event in the absence of a horizontal transfer event into the genome, although it is possible that more of the genome remains to be assembled and low copy but autonomous DNA transposons remain in that fraction. Additionally, we may need to apply repeat detection to different assemblies to find lower copy repeats, but this seems challenging given that the few \u003cem\u003eCulicoides\u003c/em\u003e genomes reported have all been generated with different sequencing technologies and various degrees of completeness and quality. In general, a hierarchical approach of combining repeat libraries from assemblies with different amounts of purged duplicates p may be useful if low copy repeats are of interest in any genome project.\u003c/p\u003e \u003cp\u003eThe most important part of a genome's structural annotation is the identification of protein-coding genes. We predicted a larger number of proteins in our assembly compared to previously reported genomes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] (\u003cem\u003eC. brevitarsis\u003c/em\u003e genome assembly GCF_036172545.1-RS_2024_03), which can be explained by a higher-quality assembly and the use of software with higher accuracy and performance, such as BRAKER2. The lack of transcriptomic data for this species determined that we used clade-specific proteins from OrthoDB as extrinsic evidence to generate hint-guided ab initio gene predictions of protein-coding genes. Identification of the functional role of the proteins found a high percentage of homolog proteins in other organisms (~\u0026thinsp;30%-55%), with the Swiss Pro database yielding the more comprehensive results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eGenomic evidence of vector status\u003c/h2\u003e \u003cp\u003eThe integration of viral genomes (or fragments) into the genomes of their hosts cannot only help us understand evolutionary history and relationships among host species but also offer insights into virus-host interaction [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. In mosquito genomes, a large number of non-retroviral endogenous viral elements have been detected, and these have been associated with the vector capacity of the species [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. For example, these can be associated with the production of small RNAs that unfold a response targeting incoming viral transcripts to modulate viral titre, acting as an exogenous antiviral agent that improves the efficiency of the host as an arbovirus vector. In dipterans, the integration of structural viral regions like the nucleoprotein, glycoprotein and matrix regions of the viruses has been more common than non-structural regions integration like the replicase [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe virus-midge interaction in \u003cem\u003eCulicoides\u003c/em\u003e is a complex process that hasn\u0026rsquo;t been thoroughly studied [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Four integrated viral sequences have been reported in \u003cem\u003eC. sonorensis\u003c/em\u003e, of which three were related to the family \u003cem\u003ePhasmaviridae\u003c/em\u003e and one to the \u003cem\u003eChuviridae\u003c/em\u003e. The hit length ranged from 308 to 998 bp, and the pairwise identity ranged from 25.30\u0026ndash;35.20% [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In dipterans, with the exception of the \u003cem\u003eAedes\u003c/em\u003e mosquito genome, in which more than 200 nrEVEs have been identified, a low number of integrated viral sequences have been described (0\u0026ndash;1 in \u003cem\u003eDrosophila melanogaster\u003c/em\u003e, 1 in \u003cem\u003ePhlebotomus papatasi\u003c/em\u003e, 7 in ​​\u003cem\u003eMusca domestica\u003c/em\u003e, 5 in tephritid fruit flies, 1\u0026ndash;3 in species of \u003cem\u003eCulicidae\u003c/em\u003e and \u003cem\u003eAnopheles\u003c/em\u003e) [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. In tephritid fruit flies, the most abundant nrEVEs reported are \u003cem\u003eRhabdoviridae\u003c/em\u003e-derived EVEs, and this was also found for mosquitos [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e], [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Nevertheless, we consider that an in-depth analysis of nrEVEs in arbovirus vectors is needed and that generating high-quality genome assemblies will be key.\u003c/p\u003e \u003cp\u003eIn this study, we identified an nrEVE integrated into the genome of \u003cem\u003eC. stellifer\u003c/em\u003e that corresponds to the rhabdovirus nucleocapsid proteins, including some matches to VSV. Vesicular stomatitis viruses belong to the family Rhabdoviridae. The genome of VSV has 11,161 nucleotides in length and encodes five major proteins, including the nucleocapsid or ribonucleoprotein. We focused on constructing a library just with the viruses for which \u003cem\u003eCulicoides\u003c/em\u003e are known vectors with the goal of providing more supporting evidence that \u003cem\u003eC. stellifer\u003c/em\u003e is a vector of arboviruses. The nrEVE identified is the footprint of a germline viral infection and was then transmitted to the offspring. This finding suggests a close and sustained relationship between rhabdo-like viruses with \u003cem\u003eC. stellifer\u003c/em\u003e and could indicate that past and present distribution of VSV virus in North America could be linked to this host distribution.\u003c/p\u003e \u003cp\u003eThe quality of the host genome assembly influences the identification of nrEVEs and was most likely a determinant factor for not finding any arbovirus nrEVE in the genome of \u003cem\u003eC. sonorensis\u003c/em\u003e. Assemblies based on short-read technology can mask highly repetitive regions where nrEVEs can be found [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Additionally, it is important to notice that viruses responsible for an existing nrEVE come from ancient viruses or might have undergone significant mutations over time. In that sense, viral query selection and filtering parameters are important parameters that need to be tuned in for the identification of nrEVEs [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eInsects account for the vast majority of eukaryotic biodiversity, and access to genomic resources remains limited for very small metazoans and megadiverse groups. For vector species, like the ones in the genus \u003cem\u003eCulicoides\u003c/em\u003e, this information is critical for understanding the genetics of virus-host association and the evolution of vector competence in dipterans. Here we present the first annotated genome of \u003cem\u003eCulicoides stellifer\u003c/em\u003e from a single specimen using PacBio long-reads. We put forward a workflow to approach data generation and analysis for genome assembly projects focused on small insects where the amount of gDNA is less than 1ng. This genome has been key in providing further evidence for the vector capacity of \u003cem\u003eC. stellifer\u003c/em\u003e as we found a nrEVE from the nucleoprotein of a virus from the same family as VSV. The fairly expansive distribution of this species in North America and the potential of a range shift due to climate change requires further investigation as ungulate species in the northern latitudes could be at risk. Increasing the amount of genomic information will play a part in developing a multidisciplinary approach to understand virus-host interactions and manage viral pathogen transmission to livestock and wildlife.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis genome assembly has been deposited at DDBJ/ENA/GenBank under the accession JBDOCM000000000. The version described in this paper is version JBDOCM010000000.\u003c/p\u003e\n\u003cp\u003eThe annotated mitochondrial genome was deposited in GenBank under the accession PP873183.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e*GitHub repository-under construction\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.C.L, Y.M.G, and S.J.A conceived the project. J.C.L and Y.M.G collected the specimens. J.C.L, Y.M.G, and T.A.E. assembled, annotated, and analyzed the genome. T.A.E. analyzed and described the annotated repeat libraries and conducted the viral integration analysis. J.C.L. led the writing of the manuscript with assistance from Y.M.G, T.A.E., R.H., and D.S. All authors read and approved the final manuscript for submission.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Arrell Food Institute Scholarship Program (J.C.L), a Discovery Grant from The Natural Sciences and Engineering Research Council of Canada (S.J.A), and the Food from Thought research program at the University of Guelph with funding from the Canada First Research Excellence Fund (S.J.A, D.S). Y.M.G was supported by Mitacs through the Mitacs Elevate Program.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe highly appreciate Kate Lindsay\u0026apos;s support with the morphological identification of the specimens and taking the photographs. We thank Olga Shevchenko from the University of Delaware DNA Sequencing \u0026amp; Genotyping Center for assistance with data generation. We also thank Amanda Meuse, Elizabeth G. Mandeville, Toby Baril and Robert Gifford for valuable insights regarding genomic analysis and software troubleshooting.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBorkent A, Dominiak P. Catalog of the Biting Midges of the World (Diptera: Ceratopogonidae), \u003cem\u003eZootaxa\u003c/em\u003e, vol. 4787, no. 1, p. zootaxa.4787.1.1, Jun. 2020, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.11646/zootaxa.4787.1.1\u003c/span\u003e\u003cspan address=\"10.11646/zootaxa.4787.1.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorkent A, Grogan WL Jr. Catalog of the New World biting midges north of Mexico (Diptera: Ceratopogonidae), \u003cem\u003eZootaxa\u003c/em\u003e, vol. 2273, no. 1, pp. 1-48-1\u0026ndash;48, 2009.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcGregor BL, Shults PT, McDermott EG. A Review of the Vector Status of North American Culicoides (Diptera: Ceratopogonidae) for Bluetongue Virus, Epizootic Hemorrhagic Disease Virus, and Other Arboviruses of Concern. 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Jul. 2017;18(1):512. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12864-017-3903-3\u003c/span\u003e\u003cspan address=\"10.1186/s12864-017-3903-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Culicoides, Vesicular Stomatitis Virus, genome assembly, vector, arboviruses","lastPublishedDoi":"10.21203/rs.3.rs-4623838/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4623838/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAdvancing our knowledge of vector species genomes is a key step in our battle against the spread of diseases. Biting midges of the genus \u003cem\u003eCulicoides\u003c/em\u003e are vectors of arboviruses that significantly affect livestock worldwide. \u003cem\u003eCulicoides stellifer\u003c/em\u003e is a suspected vector with a wide range distribution in North America, for which cryptic diversity has been described.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWith just one specimen of \u003cem\u003eC. stellifer\u003c/em\u003e, we assembled and annotated both a high-quality nuclear and a mitochondrial genome using the ultra-low input DNA PacBio protocol. The genome assembly is 119 Mb in length with a contig N50 value of 479.3 kb, contains 11% repeat sequences and 18,895 annotated protein-coding genes. To further elucidate the role of this species as a vector, we provide genomic evidence of a non-retroviral endogenous viral element integrated into the genome that corresponds to rhabdovirus nucleocapsid proteins, the same family as the Vesicular Stomatitis Virus.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis genomic information will pave the way for future investigations into this species's putative vector role. We also demonstrate the practicability of completing genomic studies in small dipterans using single specimens preserved in ethanol as well as introduce a workflow for data analysis that considers the challenges of insect genome assembly.\u003c/p\u003e","manuscriptTitle":"Single specimen genome assembly of Culicoides stellifer shows evidence of a non-retroviral endogenous viral element","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-16 09:40:30","doi":"10.21203/rs.3.rs-4623838/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-30T06:25:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-29T22:33:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-26T09:01:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"111109512388434374476567918703315877305","date":"2024-07-25T23:18:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"90825385166441531300704476863908580069","date":"2024-07-25T08:07:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"338050478217746318348279894585889979668","date":"2024-07-25T01:18:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-26T08:16:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-26T07:52:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-25T04:07:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-25T04:05:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2024-06-23T04:39:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dbb0dddc-8795-4331-ac33-fe42700461f8","owner":[],"postedDate":"July 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-17T16:04:00+00:00","versionOfRecord":{"articleIdentity":"rs-4623838","link":"https://doi.org/10.1186/s12864-025-11449-5","journal":{"identity":"bmc-genomics","isVorOnly":false,"title":"BMC Genomics"},"publishedOn":"2025-03-14 15:58:14","publishedOnDateReadable":"March 14th, 2025"},"versionCreatedAt":"2024-07-16 09:40:30","video":"","vorDoi":"10.1186/s12864-025-11449-5","vorDoiUrl":"https://doi.org/10.1186/s12864-025-11449-5","workflowStages":[]},"version":"v1","identity":"rs-4623838","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4623838","identity":"rs-4623838","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}