Russian version English version
About the Journal
Editorial Board
Instructions for Authors
Information for Readers and Authors
Current Issue
Archive
Contact Us
Search

Send manuscript
 


Volume 18   Issue 2   Year 2023
References

  1. Zhang L., Chen F.X., Zeng Z., Xu M., Sun F., Yang L., Bi X., Lin Y., Gao Y.J., Hao H.X. et al. Advances in Metagenomics and Its Application in Environmental Microorganisms. Front. Microbiol. 2021;12:1–15. doi: 10.3389/fmicb.2021.766364
  2. Roux S., Matthijnssens J., Dutilh B.E. Metagenomics in Virology. In: Encyclopedia of Virology. Ed. Bamford D.H., Zuckerman M. Cambridge: Academic Press. 2020. P. 133–140. doi: 10.1016/B978-0-12-809633-8.20957-6
  3. Sommers P., Chatterjee A., Varsani A., Trubl G. Integrating Viral Metagenomics into an Ecological Framework. Annu. Rev. Virol. 2021;8:133–158. doi: 10.1146/annurev-virology-010421-053015
  4. Santiago-Rodriguez T.M., Hollister E.B. Potential Applications of Human Viral Metagenomics and Reference Materials: Considerations for Current and Future Viruses. Appl. Environ. Microbiol. 2020;86(22):1–12. doi: 10.1128/AEM.01794-20
  5. Santiago-Rodriguez T.M., Hollister E.B. Unraveling the viral dark matter through viral metagenomics. Front. Immunol. 2022;13:1–13. doi: 10.3389/fimmu.2022.1005107
  6. Leinonen R., Sugawara H., Shumway M. The sequence read archive. Nucleic Acids Res. 2011;39:2010–2012. doi: 10.1093/nar/gkq1019
  7. Shi M., Lin X.D., Tian J.H., Chen L.J., Chen X., Li C.X., Qin X.C., Li J., Cao J.P., Eden J.S. et al. Redefining the invertebrate RNA virosphere. Nature. 2016;540(7634):539–543. doi: 10.1038/nature20167
  8. Zhang Y.Y., Chen Y., Wei X., Cui J. Viromes in marine ecosystems reveal remarkable invertebrate RNA virus diversity. Sci. China Life Sci. 2022;65(2):426–437. doi: 10.1007/s11427-020-1936-2
  9. Thomas T., Gilbert J., Meyer F. Metagenomics - a guide from sampling to data analysis. Microb. Inform. Exp. 2012;2(1):3. doi: 10.1186/2042-5783-2-3
  10. Nooij S., Schmitz D., Vennema H., Kroneman A., Koopmans M.P.G. Overview of virus metagenomic classification methods and their biological applications. Front. Microbiol. 2018;9:749. doi: 10.3389/fmicb.2018.00749
  11. Sutton T.D.S., Clooney A.G., Ryan F.J., Ross R.P., Hill C. Choice of assembly software has a critical impact on virome characterisation. Microbiome. 2019;7(1):1–15. doi: 10.1186/s40168-019-0626-5
  12. Hiltemann S., Rasche H., Gladman S., Hotz H.R., Larivière D., Blankenberg D., Jagtap P.D., Wollmann T., Bretaudeau A., Goué N. et al. Galaxy Training: A powerful framework for teaching! PLoS Comput. Biol. 2023;19(1):1–18. doi: 10.1371/journal.pcbi.1010752
  13. Skewes-Cox P., Sharpton T.J., Pollard K.S., DeRisi J.L. Profile hidden Markov models for the detection of viruses within metagenomic sequence data. PLoS One. 2014;9(8):e105067. doi: 10.1371/journal.pone.0105067
  14. Ren J., Song K., Deng C., Ahlgren N.A., Fuhrman J.A., Li Y., Xie X., Poplin R., Sun F. Identifying viruses from metagenomic data using deep learning. Quant. Biol. 2020;8(1):64–77. doi: 10.1007/s40484-019-0187-4
  15. Reyes A.P., Alves J.M., Durham A.M., Gruber A. Use of profile hidden Markov models in viral discovery: current insights. Adv. Genomics Genet. 2017;7:29–45. doi: 10.2147/AGG.S136574
  16. Butina T.V., Bukin Y.S., Petrushin I.S., Tupikin A.E., Kabilov M.R., Belikov S.I. Extended evaluation of viral diversity in Lake Baikal through metagenomics. Microorganisms. 2021;9(4):1–31. doi: 10.3390/microorganisms9040760
  17. Butina T.V., Petrushin I.S., Khanaev I.V., Bukin Y.S. Metagenomic Assessment of DNA Viral Diversity in Freshwater Sponges, Baikalospongia bacillifera. Microorganisms. 2022;10(2):480. doi: 10.3390/microorganisms10020480
  18. Butina T.V., Khanaev I.V., Petrushin I.S., Bondaryuk A.N., Maikova O.O., Bukin Y.S. The RNA Viruses in Samples of Endemic Lake Baikal Sponges. Diversity. 2023;15(7):1–20. doi: 10.3390/microorganisms10020480
  19. Bolger A.M., Lohse M., Usadel B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–2120. doi: 10.1093/bioinformatics/btu170
  20. Nurk S., Meleshko D., Korobeynikov A., Pevzner P.A. MetaSPAdes: A new versatile metagenomic assembler. Genome Res. 2017;27(5):824–834. doi: 10.1101/gr.213959.116
  21. Guo J., Bolduc B., Zayed A.A., Varsani A., Dominguez-Huerta G., Delmont T.O., Pratama A.A., Gazitúa M.C., Vik D., Sullivan M.B. et al. VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses. Microbiome. 2021;9(1):1–13. doi: 10.1186/s40168-020-00990-y
  22. Nayfach S., Camargo A.P., Schulz F., Eloe-Fadrosh E., Roux S., Kyrpides N.C. CheckV assesses the quality and completeness of metagenome-assembled viral genomes. Nat. Biotechnol. 2021;39(5):578–585. doi: 10.1038/s41587-020-00774-7
  23. Buchfink B., Xie C., Huson D.H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods. 2014;12(1):59–60. doi: 10.1038/nmeth.3176
  24. Wheeler T.J., Clements J., Eddy S.R., Hubley R., Jones T.A., Jurka J., Smit A.F.A., Finn R.D. Dfam: A database of repetitive DNA based on profile hidden Markov models. Nucleic Acids Res. 2013;41:70–82. doi: 10.1093/nar/gks1265
  25. Dfam release 3.7 (January 2023). https://www.dfam.org/ (accessed 02.11.2023).
  26. O’Leary N.A., Wright M.W., Brister J.R., Ciufo S., Haddad D., McVeigh R., Rajput B., Robbertse B., Smith-White B., Ako-Adjei D. et al. Reference sequence (RefSeq) database at NCBI: Current status, taxonomic expansion, and functional annotation. Nucleic Acids Res. 2016;44:D733–D745. doi: 10.1093/nar/gkv1189
  27. Langmead B., Salzberg S.L. Fast gapped-read alignment with Bowtie 2. Nat. Methods. 2012;9(4):357–359. doi: 10.1038/nmeth.1923
  28. Danecek P., Bonfield J.K., Liddle J., Marshall J., Ohan V., Pollard M.O., Whitwham A., Keane T., McCarthy S.A., Davies R.M. Twelve years of SAMtools and BCFtools. Gigascience. 2021;10(2):1–4. doi: 10.1093/gigascience/giab008
  29. Oksanen J. Package ‘vegan’. https://github.com/vegandevs/vegan (accessed 03.11.2023).
  30. Li D., Liu C.M., Luo R., Sadakane K., Lam T.W. MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015;31(10):1674–1676. doi: 10.1093/bioinformatics/btv033
  31. Peng Y., Leung H.C.M., Yiu S.M., Chin F.Y.L. IDBA-UD: A de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics. 2012;28(11):1420–1428. doi: 10.1093/bioinformatics/bts174
  32. Yang C., Chowdhury D., Zhang Z., Cheung W.K., Lu A., Bian Z., Zhang L. A review of computational tools for generating metagenome-assembled genomes from metagenomic sequencing data. Comput. Struct. Biotechnol. J. 2021;19:6301–6314. doi: 10.1016/j.csbj.2021.11.028
  33. Petrovskii S., Petrovskaya N. Computational ecology as an emerging science. Interface Focus. 2012;2(2):241–254. doi: 10.1098/rsfs.2011.0083
  34. Kieft K., Zhou Z., Anantharaman K. VIBRANT: Automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences. Microbiome. 2020;8:1–23. doi: 10.1186/s40168-020-00867-0
  35. Moya A., Elena S.F., Bracho A., Miralles R., Barrio E. The evolution of RNA viruses: A population genetics view. Proc. Natl. Acad. Sci. U.S.A. 2000;24(13):6967–6973. doi: 10.1073/pnas.97.13.6967
  36. Bondaryuk A.N., Kulakova N.V., Belykh O.I., Bukin Y.S. Dates and Rates of Tick-Borne Encephalitis Virus–The Slowest Changing Tick-Borne Flavivirus. Int. J. Mol. Sci. 2023;24(3):2921. doi: 10.3390/ijms24032921
  37. Kang D.D., Froula J., Egan R., Wang Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ. 2015;3:e1165. doi: 10.7717/peerj.1165
  38. Wu Y.W., Simmons B.A., Singer S.W. MaxBin 2.0: An automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics. 2016;32(4):605–607. doi: 10.1093/bioinformatics/btv638
  39. Tamames J., Puente-Sánchez F. SqueezeMeta, a highly portable, fully automatic metagenomic analysis pipeline. Front Microbiol. 2019;9:3349. doi: 10.3389/fmicb.2018.03349
  40. Rosario K., Breitbart M. Exploring the viral world through metagenomics. Curr. Opin. Virol. 2011;1(4):289–297. doi: 10.1016/j.coviro.2011.06.004
  41. Gudenkauf B.M., Hewson I. Comparative metagenomics of viral assemblages inhabiting four phyla of marine invertebrates. Front. Mar. Sci. 2016;3:1–12. doi: 10.3389/fmars.2016.00023
  42. Waldron F.M., Stone G.N., Obbard D.J. Metagenomic sequencing suggests a diversity of RNA interference-like responses to viruses across multicellular eukaryotes. PLoS Genet. 2018;14(7):e1007533. doi: 10.1371/journal.pgen.1007533
  43. Bai G.H., Lin S.C., Hsu Y.H., Chen S.Y. The Human Virome: Viral Metagenomics, Relations with Human Diseases, and Therapeutic Applications. Viruses. 2022;14:278. doi: 10.3390/v14020278
  44. Richard J.C., Blevins E., Dunn C.D., Leis E.M., Goldberg T.L. Viruses of Freshwater Mussels during Mass Mortality Events in Oregon and Washington, USA. Viruses. 2023;15(8):1–18. doi: 10.3390/v15081719
  45. Li W., Godzik A. Cd-hit: A fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics. 2006;22(13):1658–1659. doi: 10.1093/bioinformatics/btl158
Table of Contents
Original Article
Bukin Yu.S., Bondaryuk A.N., Butina T.V. Performance Analysis of Cross-Assembly of Metatranscriptomic Datasets in Viral Community Studies. Ìàthematical biology and bioinformatics. 2023;18(2):418-433. doi: 10.17537/2023.18.418
(published in Russian)

Abstract (rus.)
Abstract (eng.)
Full text (rus., pdf)
References

 
  Copyright IMPB RAS © 2005-2025