Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Genomics
  4. Volume 26, Issue 2
  5. Article
Volume 26, Issue 2
  • ISSN: 1389-2029
  • E-ISSN: 1875-5488

Abstract

Background

The blackish cicada () exhibits unique characteristics and is one of the model cicadas found in the Korean Peninsula. It is a species of southern origin, prefers high temperatures, and is listed as a climate-sensitive indicator species in South Korea. Therefore, this species can be utilized to study the impact of climate change on the genetic diversity and structure of populations. However, research on the genome of is limited.

Methods

We sequenced the genome of an individual collected from South Korea and constructed a draft genome. Additionally, we collected ten specimens from each of the five regions in South Korea and identified single nucleotide variants (SNVs) for population genetic analysis. The sequencing library was constructed using the MGIEasy DNA Library Prep Kit and sequenced using the MGISEQ-2000 platform with 150-bp paired-end reads.

Results

The draft genome of was approximately 5.0 Gb or 5.2 Gb, making it one of the largest genomes among insects. Population genetic analysis, which was conducted on four populations in South Korea, including both previously distributed and newly expanded regions, showed that Jeju Island, a remote southern island with the highest average temperature, formed an independent genetic group. However, there were no notable genetic differences among the inland populations selected based on varying average temperatures, indicating that the current population genetic composition on the Korean Peninsula is more reflective of biogeographic history rather than climate-induced genetic structures. Additionally, we unexpectedly observed that most individuals of collected in a specific locality were infected with microbes not commonly found in insects, necessitating further research on the pathogens within .

Conclusion

This study introduces the draft genome of , a climate-sensitive indicator species in South Korea. Population analysis results indicate that the current genetic structure of is driven by biogeographic history rather than just climate. The prevalence of widespread pathogen infections raises concerns about their impact on . Considering the scarcity of publicly available genomic resources related to the family Cicadidae, this draft genome and population data of are expected to serve as a valuable resource for various studies utilizing cicada genomes.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/cg/10.2174/0113892029314148240820082402
2024-08-27
2025-05-12

  • From This Site

    /content/journals/cg/10.2174/0113892029314148240820082402
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. SanbornA.F. Catalogue of the Cicadoidea (Hemiptera: Auchenorrhyncha).Amsterdam, NetherlandsElsevier2013
     [Google Scholar]
  2. LoganD.P. RoweC.A. MaherB.J. Life history of chorus cicada, an endemic pest of kiwifruit (Cicadidae: Homoptera).N. Z. Entomol.20143729610610.1080/00779962.2014.897302
     [Google Scholar]
  3. SimonC. CooleyJ.R. KarbanR. SotaT. Advances in the evolution and ecology of 13-and 17-year periodical cicadas.Annu. Rev. Entomol.202267145748210.1146/annurev‑ento‑072121‑06110834623904
     [Google Scholar]
  4. FukudaH. TakegawaY. TaketoA. Comparison of mitochondrial DNA sequences among Japanese cicadas, with special reference to three Tibicenine species.Memoirs Fukui Univ. Technol.2006361163170
     [Google Scholar]
  5. XieX. GuoH. LiuJ. WangJ. LiH. DengZ. Edible and Medicinal Progress of Cryptotympana atrata (Fabricius) in China.Nutrients20231519426610.3390/nu1519426637836550
     [Google Scholar]
  6. LeeY.J. HayashiM. Taxonomic review of Cicadidae (Hemiptera, Auchenorrhyncha) from Taiwan, part 1. Platypleurini, Tibicenini, Polyneurini, and Dundubiini (Dundubiina).Insecta Koreana2003202149185
     [Google Scholar]
  7. HayashiM. A revision of the Genus Cryptotympana (Homoptera, Cicadidae) part II.Bull. Kitakyushu Mus. Nat. Hist198771109
     [Google Scholar]
  8. KimT.E. OhS.Y. ChangE. JangY. Host availability hypothesis: Complex interactions with abiotic factors and predators may best explain population densities of cicada species.Anim. Cells Syst.201418214315310.1080/19768354.2014.906501
     [Google Scholar]
  9. LeeH.Y. OhS.Y. JangY. Morphometrics of the final instar exuviae of five cicada species occurring in urban areas of central Korea.J. Asia Pac. Entomol.201215462763010.1016/j.aspen.2012.07.004
     [Google Scholar]
  10. National Institute of Biological ResourcesList of 100 climatesensitive biological indicator species and 30 candidate species.2017Available From: https://species.nibr.go.kr/home/mainHome.do?cont_link=011Ab&subMenu=011017&contCd=011017
  11. KiK.S. GimJ. YoonK.S. LeeJ.Y. Effects of tropical night and light pollution on cicadas calls in urban areas.Korean J. Environ. Ecol.201630472472910.13047/KJEE.2016.30.4.724
     [Google Scholar]
  12. GuJ.H. LeeJ.W. LeeW.S. ChoiK.H. SeoC.Y. ParkH.K. KimS.S. HanJ.S. Sound quality characteristics of the cicada singing noise in urban areas.Transac. Korean Soc. Noise Vibr. Eng.201222982582910.5050/KSNVE.2012.22.9.825
     [Google Scholar]
  13. TavassolyI. GoldfarbJ. IyengarR. Systems biology primer: The basic methods and approaches.Essays Biochem.201862448750010.1042/EBC2018000330287586
     [Google Scholar]
  14. RichardsonM.F. WeinertL.A. WelchJ.J. LinheiroR.S. MagwireM.M. JigginsF.M. BergmanC.M. Population genomics of the Wolbachia endosymbiont in Drosophila melanogaster. PLoS Genet.2012812e100312910.1371/journal.pgen.100312923284297
     [Google Scholar]
  15. HerewardJ.P. CaiX. MatiasA.M.A. WalterG.H. XuC. WangY. Migration dynamics of an important rice pest: The brown planthopper ( Nilaparvata lugens ) across Asia—Insights from population genomics.Evol. Appl.20201392449245910.1111/eva.1304733005233
     [Google Scholar]
  16. KimS.W. KimM.J. KimS.R. ParkJ.S. KimK.Y. KimK.H. KwakW. KimI. Whole-genome sequences of 37 breeding line Bombyx mori strains and their phenotypes established since 1960s.Sci. Data20229118910.1038/s41597‑022‑01289‑335474080
     [Google Scholar]
  17. LiY. YaoJ. SangH. WangQ. SuL. ZhaoX. XiaZ. WangF. WangK. LouD. WangG. WaterhouseR.M. WangH. LuoS. SunC. Pan-genome analysis highlights the role of structural variation in the evolution and environmental adaptation of Asian honeybees.Mol. Ecol. Resour.2024242e1390510.1111/1755‑0998.1390537996991
     [Google Scholar]
  18. LiQ. JiA. ShenH. HanQ. QinG. The forewing of a black cicadaCryptotympana atrata (Hemiptera, Homoptera: Cicadidae): Microscopic structures and mechanical properties.Microsc. Res. Tech.20228593153316410.1002/jemt.2417335656939
     [Google Scholar]
  19. BolgerA.M. LohseM. UsadelB. Trimmomatic: A flexible trimmer for Illumina sequence data.Bioinformatics201430152114212010.1093/bioinformatics/btu17024695404
     [Google Scholar]
  20. MarcaisG. KingsfordC. Jellyfish: A fast k-mer counter.Tutorialis e Manuais2012118
     [Google Scholar]
  21. LiD. LiuC.M. LuoR. SadakaneK. LamT.W. MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph.Bioinformatics201531101674167610.1093/bioinformatics/btv03325609793
     [Google Scholar]
  22. ManniM. BerkeleyM.R. SeppeyM. SimãoF.A. ZdobnovE.M. BUSCO update: Novel and streamlined workflows along with broader and deeper phylogenetic coverage for scoring of eukaryotic, prokaryotic, and viral genomes.Mol. Biol. Evol.202138104647465410.1093/molbev/msab19934320186
     [Google Scholar]
  23. SmitA.F.A. HubleyR. GreenP. RepeatMasker.2004Available From: http://www.repeatmasker.org
  24. FlynnJ.M. HubleyR. GoubertC. RosenJ. ClarkA.G. FeschotteC. SmitA.F. RepeatModeler2 for automated genomic discovery of transposable element families.Proc. Natl. Acad. Sci. USA2020117179451945710.1073/pnas.192104611732300014
     [Google Scholar]
  25. BaoZ. EddyS.R. Automated de novo identification of repeat sequence families in sequenced genomes.Genome Res.20021281269127610.1101/gr.8850212176934
     [Google Scholar]
  26. PriceA.L. JonesN.C. PevznerP.A. De novo identification of repeat families in large genomes.Bioinformatics200521Suppl. 1i351i35810.1093/bioinformatics/bti101815961478
     [Google Scholar]
  27. BensonG. Tandem repeats finder: A program to analyze DNA sequences.Nucleic Acids Res.199927257358010.1093/nar/27.2.5739862982
     [Google Scholar]
  28. HubleyR. FinnR.D. ClementsJ. EddyS.R. JonesT.A. BaoW. SmitA.F.A. WheelerT.J. The Dfam database of repetitive DNA families.Nucleic Acids Res.201644D1D81D8910.1093/nar/gkv127226612867
     [Google Scholar]
  29. KimD. PaggiJ.M. ParkC. BennettC. SalzbergS.L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype.Nat. Biotechnol.201937890791510.1038/s41587‑019‑0201‑431375807
     [Google Scholar]
  30. BrůnaT. HoffK.J. LomsadzeA. StankeM. BorodovskyM. BRAKER2: Automatic eukaryotic genome annotation with GeneMark-EP+ and AUGUSTUS supported by a protein database.NAR Genom. Bioinform.202131lqaa10810.1093/nargab/lqaa10833575650
     [Google Scholar]
  31. BuchfinkB. XieC. HusonD.H. Fast and sensitive protein alignment using DIAMOND.Nat. Methods2015121596010.1038/nmeth.317625402007
     [Google Scholar]
  32. PruittK.D. TatusovaT. MaglottD.R. NCBI reference sequences (RefSeq): A curated non-redundant sequence database of genomes, transcripts and proteins.Nucleic Acids Res.200735DatabaseSuppl. 1D61D6510.1093/nar/gkl84217130148
     [Google Scholar]
  33. BoutetE. LieberherrD. TognolliM. SchneiderM. BansalP. BridgeA.J. PouxS. BougueleretL. XenariosI. UniProtKB/swiss-prot, the manually annotated section of the uniprot knowledgebase: How to use the entry view.Plant Bioinformatics. EdwardsD. New York, USAHumana2016235410.1007/978‑1‑4939‑3167‑5_2
     [Google Scholar]
  34. FlyBase ConsortiumThe FlyBase database of the Drosophila genome projects and community literature.Nucleic Acids Res.200331117217510.1093/nar/gkg09412519974
     [Google Scholar]
  35. VasimuddinM. MisraS. LiH. AluruS. Efficient architecture-aware acceleration of BWA-MEM for multicore systems.2019 IEEE international parallel and distributed processing symposium.Rio de Janeiro, BrazilIPDPS201931432410.1109/IPDPS.2019.00041
     [Google Scholar]
  36. LiH. HandsakerB. WysokerA. FennellT. RuanJ. HomerN. MarthG. AbecasisG. DurbinR. The Sequence Alignment/Map format and SAMtools.Bioinformatics200925162078207910.1093/bioinformatics/btp35219505943
     [Google Scholar]
  37. DanecekP. AutonA. AbecasisG. AlbersC.A. BanksE. DePristoM.A. HandsakerR.E. LunterG. MarthG.T. SherryS.T. McVeanG. DurbinR. The variant call format and VCFtools.Bioinformatics201127152156215810.1093/bioinformatics/btr33021653522
     [Google Scholar]
  38. CingolaniP. PlattsA. WangL.L. CoonM. NguyenT. WangL. LandS.J. LuX. RudenD.M. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff.Fly (Austin)201262809210.4161/fly.1969522728672
     [Google Scholar]
  39. RajA. StephensM. PritchardJ.K. fastSTRUCTURE: Variational inference of population structure in large SNP data sets.Genetics2014197257358910.1534/genetics.114.16435024700103
     [Google Scholar]
  40. PritchardJ.K. StephensM. DonnellyP. Inference of population structure using multilocus genotype data.Genetics2000155294595910.1093/genetics/155.2.94510835412
     [Google Scholar]
  41. Blanco-MíguezA. BeghiniF. CumboF. McIverL.J. ThompsonK.N. ZolfoM. ManghiP. DuboisL. HuangK.D. ThomasA.M. NickolsW.A. PiccinnoG. PiperniE. PunčochářM. Valles-ColomerM. TettA. GiordanoF. DaviesR. WolfJ. BerryS.E. SpectorT.D. FranzosaE.A. PasolliE. AsnicarF. HuttenhowerC. SegataN. Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4.Nat. Biotechnol.202341111633164410.1038/s41587‑023‑01688‑w36823356
     [Google Scholar]
  42. GodakovaS.A. Sevast’yanovaG.A. SemenovaS.K. Structure and distribution of the retrotransposon Bov-B LINE.Mol. Gen. Mikrobiol. Virusol.201634191210.18821/0208‑0613‑2016‑34‑1‑9‑1227183715
     [Google Scholar]
  43. SparksM.E. HebertF.O. JohnstonJ.S. HamelinR.C. CussonM. LevesqueR.C. Gundersen-RindalD.E. Sequencing, assembly and annotation of the whole-insect genome of Lymantria dispar dispar, the European gypsy moth.G3-Genes Genomes Genet.2021118jkab150
     [Google Scholar]
  44. KimS.R. KwakW. KimH. Caetano-AnollesK. KimK.Y. KimS.B. ChoiK.H. KimS.W. HwangJ.S. KimM. KimI. GooT.W. ParkS.W. Genome sequence of the Japanese oak silk moth, Antheraea yamamai: The first draft genome in the family Saturniidae.Gigascience20187111110.1093/gigascience/gix11329186418
     [Google Scholar]
  45. McCutcheonJ.P. BoydB.M. DaleC. The life of an insect endosymbiont from the cradle to the grave.Curr. Biol.20192911R485R49510.1016/j.cub.2019.03.03231163163
     [Google Scholar]
  46. GilR. LatorreA. MoyaA. Bacterial endosymbionts of insects: Insights from comparative genomics.Environ. Microbiol.20046111109112210.1111/j.1462‑2920.2004.00691.x15479245
     [Google Scholar]
  47. KikuchiY. Endosymbiotic bacteria in insects: Their diversity and culturability.Microbes Environ.200924319520410.1264/jsme2.ME09140S21566374
     [Google Scholar]
  48. CampbellM.A. ŁukasikP. MeyerM.C. BucknerM. SimonC. VelosoC. MichalikA. McCutcheonJ.P. Changes in endosymbiont complexity drive host-level compensatory adaptations in cicadas.MBio201896e02104-1810.1128/mBio.02104‑1830425149
     [Google Scholar]
  49. CampbellM.A. Van LeuvenJ.T. MeisterR.C. CareyK.M. SimonC. McCutcheonJ.P. Genome expansion via lineage splitting and genome reduction in the cicada endosymbiont Hodgkinia.Proc. Natl. Acad. Sci. USA201511233101921019910.1073/pnas.142138611226286984
     [Google Scholar]
  50. PelegA.Y. SeifertH. PatersonD.L. Acinetobacter baumannii: Emergence of a successful pathogen.Clin. Microbiol. Rev.200821353858210.1128/CMR.00058‑0718625687
     [Google Scholar]
  51. MortensenB.L. SkaarE.P. The contribution of nutrient metal acquisition and metabolism to Acinetobacter baumannii survival within the host.Front. Cell. Infect. Microbiol.201339510.3389/fcimb.2013.0009524377089
     [Google Scholar]
  52. HarikrishnanR. BalasundaramC. Modern trends in Aeromonas hydrophila disease management with fish.Rev. Fish. Sci.200513428132010.1080/10641260500320845
     [Google Scholar]
  53. QinY. LinG. ChenW. HuangB. HuangW. YanQ. Flagellar motility contributes to the invasion and survival of Aeromonas hydrophila in Anguilla japonica macrophages.Fish Shellfish Immunol.201439227327910.1016/j.fsi.2014.05.01624859591
     [Google Scholar]
  54. SharmaD. SharmaP. SoniP. First case report of Providencia Rettgeri neonatal sepsis.BMC Res. Notes201710153610.1186/s13104‑017‑2866‑429084590
     [Google Scholar]
  55. JacksonT.J. WangH. NugentM.J. GriffinC.T. BurnellA.M. DowdsB.C. Isolation of insect pathogenic bacteria, Providencia rettgeri, from Heterorhabditis spp.J. Appl. Microbiol.1995783237244
     [Google Scholar]
  56. SioziosS. Nadal JimenezP. AzagiT. SprongH. FrostC.L. ParrattS.R. TaylorG. BrettellL. LiewK.C. CroftL. KingK.C. BrockhurstM.A. HypšaV. NovakovaE. DarbyA.C. HurstG.D. Genome dynamics across the evolutionary transition to endosymbiosis.bioRxiv202310.1101/2023.05.02.539033
     [Google Scholar]
  57. CasadevallA. PirofskiL. Host-pathogen interactions: Redefining the basic concepts of virulence and pathogenicity.Infect. Immun.19996783703371310.1128/IAI.67.8.3703‑3713.199910417127
     [Google Scholar]
/content/journals/cg/10.2174/0113892029314148240820082402
Loading
Whole Genome Sequences of Cryptotympana atrata Fabricius, 1775 (Hemiptera: Cicadidae) in the Korean Peninsula: Insights into Population Structure with Novel Pathogenic Or Symbiotic Candidates
Curr. Genomics 26, 118 (2025); https://doi.org/10.2174/0113892029314148240820082402
/content/journals/cg/10.2174/0113892029314148240820082402
/content/journals/cg/10.2174/0113892029314148240820082402
Loading

Data & Media loading...


  • Article Type:     Research Article
Keyword(s): Blackish cicada; climate-sensitive indicator species; Cryptotympana atrata; genetic population; hemiptera; whole genome

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test