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Overview of Sequence Analysis Methods in COVID-19 Infections

Yıl 2022, Cilt: 8 Sayı: 1, 6 - 17, 21.03.2022
https://doi.org/10.30934/kusbed.1052257

Öz

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) was identified as the agent of COVID-19, and genomic data was first shared by China on January 10, 2020. Since then, tremendous effort has been devoted to sequencing the viral genome from samples collected around the world. In the recent past, next-generation sequencing (NGS) strategies have been used successfully to trace the origins, understand the evolution of infectious agents, to investigate the chains of the spread of epidemics, to facilitate the development of effective and rapid molecular diagnostic tests, and to contribute to the research of treatments and vaccines. Recent advances in technology and science have allowed the genomes of SARS-CoV-2, the agent of COVID-19, to be sequenced within hours or days after a case is identified. In this way, for the first time, the public health and epidemic size of a pandemic can be monitored in real-time. The early sharing of SARS-CoV-2 genome sequences has allowed the rapid development of molecular diagnostic tests, contributing to global preparedness and the design of countermeasures. Rapid, large-scale sequencing of the virus genome is essential in understanding the dynamics of viral outbreaks and assessing the effectiveness of control measures. SARS-CoV-2 gene sequencing can be used in many different areas, including improved diagnosis, development of countermeasures, and investigation of disease epidemiology. The development of effective and rapid sequencing methods to fully identify the genomic sequence of the etiologic agent of COVID-19 has been fundamental to the design of diagnostic molecular tests and the determination of effective measures and strategies to reduce the spread of the pandemic. Different approaches and sequencing methods can be applied to SARS-CoV-2 genomes, as evidenced by the number of sequences available. However, each technology and sequencing approach has its advantages and limitations. In this review, current platforms and methodological approaches for sequencing SARS-CoV-2 genomes will be discussed.

Kaynakça

  • European Centre for Disease Prevention and Control. (2021). Sequencing of SARS-CoV-2: first update (Technical Guidance).ECDC:Stockholm. https://www.ecdc.europa.eu/en/ publications-data/sequencing-sars-cov-2. Published September 2021. Accessed September 10, 2021.
  • Chiara M, D'Erchia AM, Gissi C, et al. Next generation sequencing of SARS-CoV-2 genomes: challenges, applications and opportunities. Brief Bioinform. 2021;22(2):616-630. doi: 10.1093/bib/bbaa297
  • GISAID. hCoV-19 Reference Sequence. www.gisaid.org. Published October 2021. Accessed October 17, 2021.
  • GISAID. Genomic epidemiology of novel coronavirus - Global subsampling. https://nextstrain.org/ncov. Published October 2021. Accessed October 17, 2021.
  • Rambaut A, Holmes EC, O'Toole Á, et al. A dynamic nomenclature proposal for SARS-CoV-2 lineages to assist genomic epidemiology. Nat Microbiol. 2020;5:1403-1407. doi: 10.1038/s41564-020-0770-5
  • World Health Organization. (‎2021)‎. Genomic sequencing of SARS-CoV-2: a guide to implementation for maximum impact on public health, 8 January 2021. World Health Organization. https://apps.who.int/iris/handle/10665/338480. Published October 2021. Accessed October 10, 2021.
  • Li C, Zhao C, Bao J, Tang B, Wang Y, Gu B. Laboratory diagnosis of coronavirus disease-2019 (COVID-19). Clin Chim Acta. 2020;510:35-46. doi: 10.1016/j.cca.2020.06.045
  • Greninger AL, Chen EC, Sittler T, et al. A metagenomic analysis of pandemic influenza A (2009 H1N1) infection in patients from North America. PLoS One. 2010;5(10):e13381. doi: 10.1371/journal.pone.0013381
  • Carter LJ, Garner LV, Smoot JW, et al. Assay Techniques and Test Development for COVID-19 Diagnosis. ACS Cent Sci. 2020;6(5):591-605. doi: 10.1021/acscentsci.0c00501
  • ARTIC NETWORK. (2020). SARS-CoV-2. https://artic.network/ncov-2019. Published October 2021. Accessed October 12, 2021.
  • Kim D, Lee JY, Yang JS, Kim JW, Kim VN, Chang H. The Architecture of SARS-CoV-2 Transcriptome. Cell. 2020;181(4):914-921. doi: 10.1016/j.cell.2020.04.011
  • Chan JF, Yuan S, Kok KH, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395(10223):514-523. doi: 10.1016/S0140-6736(20)30154-9
  • Lewandowski K, Xu Y, Pullan ST, et al. Metagenomic Nanopore Sequencing of Influenza Virus Direct from Clinical Respiratory Samples. J Clin Microbiol. 2019;58(1):e00963-19. doi: 10.1128/JCM.00963-19
  • Kafetzopoulou LE, Efthymiadis K, Lewandowski K, et al. Assessment of metagenomic Nanopore and Illumina sequencing for recovering whole genome sequences of chikungunya and dengue viruses directly from clinical samples. Euro Surveill. 2018(10);23:1800228. doi: 10.2807/1560-7917.ES.2018.23.50.1800228
  • Lam TTY, Jia N, Zhang YW, et al. Identifying SARS-CoV-2-related coronaviruses in Malayan pangolins. Nature. 2020;583:282-285. doi: 10.1038/s41586-020-2169-0
  • Zhang H, Ai JW, Yang W, et al. Metatranscriptomic Characterization of Coronavirus Disease 2019 Identified a Host Transcriptional Classifier Associated With Immune Signaling. Clin Infect Dis. 2021;73(3):376-385. doi: 10.1093/cid/ciaa663
  • Butler DJ, Mozsary C, Meydan C, et al. Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions. bioRxiv Preprint. 2020 Update in: Nat Commun. 2021:12:1660. doi: 10.1101/2020.04.20.048066
  • Xiao M, Liu X, Ji J, et al. Multiple approaches for massively parallel sequencing of SARS-CoV-2 genomes directly from clinical samples. Genome Med. 2020;12(1):57. doi: 10.1186/s13073-020-00751-4
  • Meredith LW, Hamilton WL, Warne B, et al. Rapid implementation of SARS-CoV-2 sequencing to investigate cases of health-care associated COVID-19: a prospective genomic surveillance study. Lancet Infect Dis. 2020;20(11):1263-1271. doi: 10.1016/S1473-3099(20)30562-4
  • Albert TJ, Molla MN, Muzny DM, et al. Direct selection of human genomic loci by microarray hybridization. Nat Methods. 2007;4(11):903-905. doi: 10.1038/nmeth1111
  • Maurano MT, Ramaswami S, Zappile P, et al. Sequencing identifies multiple early introductions of SARS-CoV-2 to the New York City region. Genome Res. 2020;30(12):1781-1788. doi: 10.1101/gr.266676.120
  • Amarasinghe SL, Su S, Dong X, Zappia L, Ritchie ME, Gouil Q. Opportunities and challenges in long-read sequencing data analysis. Genome biology. 2020;21(1):1-16. doi: 10.1186/s13059-020-1935-5
  • Karsch-Mizrachi I, Takagi T, Cochrane G. Sequence Database Collaboration IN. The international nucleotide sequence database collaboration. Nucleic acids research. 2016; 44(D1):48-50. doi: 10.1093/nar/gkx1097
  • Mailman MD, Feolo M, Jin Y, et al. The NCBI dbGaP database of genotypes and phenotypes. Nat Genet. 2007;39(10):1181-1186. doi: 10.1038/ng1007-1181
  • Chiara M, Horner DS, Gissi C, Pesole G. Comparative Genomics Reveals Early Emergence and Biased Spatiotemporal Distribution of SARS-CoV-2. Mol Biol Evol. 2021;38(6):2547-2565. doi: 10.1093/molbev/msab049
  • Boni MF, Lemey P, Jiang X, et al. Evolutionary origins of the SARS-CoV-2 sarbecovirus lineage responsible for the COVID-19 pandemic. Nat Microbiol. 2020;5(11):1408-1417. doi: 10.1038/s41564-020-0771-4
  • Shu Y, McCauley J. GISAID: Global initiative on sharing all influenza data - from vision to reality. Euro Surveill. 2017;22(13):30494. doi: 10.2807/1560-7917.ES.2017.22.13.30494
  • Kosakovsky Pond SL, Poon AFY, Velazquez R, et al. HyPhy 2.5-A Customizable Platform for Evolutionary Hypothesis Testing Using Phylogenies. Mol Biol Evol. 2020;37(1):295-299. doi: 10.1093/molbev/msz197
  • Di Giorgio S, Martignano F, Torcia MG, Mattiuz G, Conticello SG. Evidence for host-dependent RNA editing in the transcriptome of SARS-CoV-2. Sci Adv. 2020;6(25):eabb5813. doi: 10.1126/sciadv.abb5813
  • Picardi E, Mansi L, Pesole G. A-to-I RNA editing in SARS-COV-2: real or artifact? BioRxiv: Prepr Serv Biol. 2020. doi: 10.1101/2020.07.27.223172.
  • Pachetti M, Marini B, Benedetti F, et al. Emerging SARS-CoV-2 mutation hot spots include a novel RNA-dependent-RNA polymerase variant. J Transl Med. 2020;18(1):179. doi: 10.1186/s12967-020-02344-6

COVID-19 Enfeksiyonlarında Dizi Analizi Yöntemlerine Genel Bakış

Yıl 2022, Cilt: 8 Sayı: 1, 6 - 17, 21.03.2022
https://doi.org/10.30934/kusbed.1052257

Öz

Şiddetli akut solunum sendromu koronavirüs 2 (SARS-CoV-2), koronavirüs hastalığı 2019'un (COVID-19) etkeni olarak tanımlandı ve genomik veriler ilk olarak 10 Ocak 2020'de Çin tarafından paylaşıldı. O tarihten itibaren, dünya genelinde toplanan örneklerden viral genomu dizilemek için çok büyük çaba harcandı. Yakın geçmişte, kökenleri izlemek ve bulaşıcı ajanların evrimini anlamak, salgınların yayılma zincirlerini araştırmak, hem etkili ve hızlı moleküler tanı testlerinin geliştirilmesini kolaylaştırmak hem de tedavi ve aşıların araştırılmasına katkıda bulunmak için, yeni nesil dizileme (NGS) stratejileri, başarıyla kullanılmıştır. Teknoloji ve bilimdeki son gelişmeler, COVID-19'un etkeni olan ağır akut solunum sendromu koronavirüsü-2'nin (SARS-CoV-2) genomlarının, bir vakanın tanımlanmasından sonraki saatler veya günler içinde dizilenmesine olanak sağlamıştır. Bu sayede, ilk kez, bir pandeminin halk sağlığı ve epidemi boyutu gerçek zamanlı olarak izlenebilmektedir. SARS-CoV-2 genom dizilerinin erken paylaşımı, moleküler tanı testlerinin hızla geliştirilmesine olanak sağlayarak, küresel hazırlığa ve karşı önlemlerin tasarımına katkıda bulunmuştur. Hızlı, büyük ölçekli virüs genom dizilimi, viral salgınların dinamiklerini anlama ve kontrol önlemlerinin etkinliğini değerlendirmede oldukça önemlidir. SARS-CoV-2 gen dizilimi, gelişmiş tanılar, karşı önlemlerin geliştirilmesi ve hastalık epidemiyolojisinin araştırılması dahil olmak üzere birçok farklı alanda kullanılabilir. COVID-19'un etiyolojik ajanının genomik dizisini tam olarak tanımlamak için etkili ve hızlı dizileme yöntemlerinin geliştirilmesi, tanısal moleküler testlerin tasarımı ve pandemi yayılımını azaltmada etkili önlemlerin alınması ve stratejilerin belirlenmesinde temel olmuştur. Mevcut dizilerin sayısından anlaşıldığı gibi, SARS-CoV-2 genomlarına, farklı yaklaşımlar ve dizileme yöntemleri uygulanabilir. Bununla birlikte, her teknoloji ve dizileme yaklaşımının kendi avantajları ve sınırlamaları vardır. Bu derlemede, SARS-CoV-2 genomlarının dizilenmesi için şu andaki mevcut platformlar ve metodolojik yaklaşımlardan bahsedilecektir.

Kaynakça

  • European Centre for Disease Prevention and Control. (2021). Sequencing of SARS-CoV-2: first update (Technical Guidance).ECDC:Stockholm. https://www.ecdc.europa.eu/en/ publications-data/sequencing-sars-cov-2. Published September 2021. Accessed September 10, 2021.
  • Chiara M, D'Erchia AM, Gissi C, et al. Next generation sequencing of SARS-CoV-2 genomes: challenges, applications and opportunities. Brief Bioinform. 2021;22(2):616-630. doi: 10.1093/bib/bbaa297
  • GISAID. hCoV-19 Reference Sequence. www.gisaid.org. Published October 2021. Accessed October 17, 2021.
  • GISAID. Genomic epidemiology of novel coronavirus - Global subsampling. https://nextstrain.org/ncov. Published October 2021. Accessed October 17, 2021.
  • Rambaut A, Holmes EC, O'Toole Á, et al. A dynamic nomenclature proposal for SARS-CoV-2 lineages to assist genomic epidemiology. Nat Microbiol. 2020;5:1403-1407. doi: 10.1038/s41564-020-0770-5
  • World Health Organization. (‎2021)‎. Genomic sequencing of SARS-CoV-2: a guide to implementation for maximum impact on public health, 8 January 2021. World Health Organization. https://apps.who.int/iris/handle/10665/338480. Published October 2021. Accessed October 10, 2021.
  • Li C, Zhao C, Bao J, Tang B, Wang Y, Gu B. Laboratory diagnosis of coronavirus disease-2019 (COVID-19). Clin Chim Acta. 2020;510:35-46. doi: 10.1016/j.cca.2020.06.045
  • Greninger AL, Chen EC, Sittler T, et al. A metagenomic analysis of pandemic influenza A (2009 H1N1) infection in patients from North America. PLoS One. 2010;5(10):e13381. doi: 10.1371/journal.pone.0013381
  • Carter LJ, Garner LV, Smoot JW, et al. Assay Techniques and Test Development for COVID-19 Diagnosis. ACS Cent Sci. 2020;6(5):591-605. doi: 10.1021/acscentsci.0c00501
  • ARTIC NETWORK. (2020). SARS-CoV-2. https://artic.network/ncov-2019. Published October 2021. Accessed October 12, 2021.
  • Kim D, Lee JY, Yang JS, Kim JW, Kim VN, Chang H. The Architecture of SARS-CoV-2 Transcriptome. Cell. 2020;181(4):914-921. doi: 10.1016/j.cell.2020.04.011
  • Chan JF, Yuan S, Kok KH, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395(10223):514-523. doi: 10.1016/S0140-6736(20)30154-9
  • Lewandowski K, Xu Y, Pullan ST, et al. Metagenomic Nanopore Sequencing of Influenza Virus Direct from Clinical Respiratory Samples. J Clin Microbiol. 2019;58(1):e00963-19. doi: 10.1128/JCM.00963-19
  • Kafetzopoulou LE, Efthymiadis K, Lewandowski K, et al. Assessment of metagenomic Nanopore and Illumina sequencing for recovering whole genome sequences of chikungunya and dengue viruses directly from clinical samples. Euro Surveill. 2018(10);23:1800228. doi: 10.2807/1560-7917.ES.2018.23.50.1800228
  • Lam TTY, Jia N, Zhang YW, et al. Identifying SARS-CoV-2-related coronaviruses in Malayan pangolins. Nature. 2020;583:282-285. doi: 10.1038/s41586-020-2169-0
  • Zhang H, Ai JW, Yang W, et al. Metatranscriptomic Characterization of Coronavirus Disease 2019 Identified a Host Transcriptional Classifier Associated With Immune Signaling. Clin Infect Dis. 2021;73(3):376-385. doi: 10.1093/cid/ciaa663
  • Butler DJ, Mozsary C, Meydan C, et al. Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions. bioRxiv Preprint. 2020 Update in: Nat Commun. 2021:12:1660. doi: 10.1101/2020.04.20.048066
  • Xiao M, Liu X, Ji J, et al. Multiple approaches for massively parallel sequencing of SARS-CoV-2 genomes directly from clinical samples. Genome Med. 2020;12(1):57. doi: 10.1186/s13073-020-00751-4
  • Meredith LW, Hamilton WL, Warne B, et al. Rapid implementation of SARS-CoV-2 sequencing to investigate cases of health-care associated COVID-19: a prospective genomic surveillance study. Lancet Infect Dis. 2020;20(11):1263-1271. doi: 10.1016/S1473-3099(20)30562-4
  • Albert TJ, Molla MN, Muzny DM, et al. Direct selection of human genomic loci by microarray hybridization. Nat Methods. 2007;4(11):903-905. doi: 10.1038/nmeth1111
  • Maurano MT, Ramaswami S, Zappile P, et al. Sequencing identifies multiple early introductions of SARS-CoV-2 to the New York City region. Genome Res. 2020;30(12):1781-1788. doi: 10.1101/gr.266676.120
  • Amarasinghe SL, Su S, Dong X, Zappia L, Ritchie ME, Gouil Q. Opportunities and challenges in long-read sequencing data analysis. Genome biology. 2020;21(1):1-16. doi: 10.1186/s13059-020-1935-5
  • Karsch-Mizrachi I, Takagi T, Cochrane G. Sequence Database Collaboration IN. The international nucleotide sequence database collaboration. Nucleic acids research. 2016; 44(D1):48-50. doi: 10.1093/nar/gkx1097
  • Mailman MD, Feolo M, Jin Y, et al. The NCBI dbGaP database of genotypes and phenotypes. Nat Genet. 2007;39(10):1181-1186. doi: 10.1038/ng1007-1181
  • Chiara M, Horner DS, Gissi C, Pesole G. Comparative Genomics Reveals Early Emergence and Biased Spatiotemporal Distribution of SARS-CoV-2. Mol Biol Evol. 2021;38(6):2547-2565. doi: 10.1093/molbev/msab049
  • Boni MF, Lemey P, Jiang X, et al. Evolutionary origins of the SARS-CoV-2 sarbecovirus lineage responsible for the COVID-19 pandemic. Nat Microbiol. 2020;5(11):1408-1417. doi: 10.1038/s41564-020-0771-4
  • Shu Y, McCauley J. GISAID: Global initiative on sharing all influenza data - from vision to reality. Euro Surveill. 2017;22(13):30494. doi: 10.2807/1560-7917.ES.2017.22.13.30494
  • Kosakovsky Pond SL, Poon AFY, Velazquez R, et al. HyPhy 2.5-A Customizable Platform for Evolutionary Hypothesis Testing Using Phylogenies. Mol Biol Evol. 2020;37(1):295-299. doi: 10.1093/molbev/msz197
  • Di Giorgio S, Martignano F, Torcia MG, Mattiuz G, Conticello SG. Evidence for host-dependent RNA editing in the transcriptome of SARS-CoV-2. Sci Adv. 2020;6(25):eabb5813. doi: 10.1126/sciadv.abb5813
  • Picardi E, Mansi L, Pesole G. A-to-I RNA editing in SARS-COV-2: real or artifact? BioRxiv: Prepr Serv Biol. 2020. doi: 10.1101/2020.07.27.223172.
  • Pachetti M, Marini B, Benedetti F, et al. Emerging SARS-CoV-2 mutation hot spots include a novel RNA-dependent-RNA polymerase variant. J Transl Med. 2020;18(1):179. doi: 10.1186/s12967-020-02344-6
Toplam 31 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Klinik Tıp Bilimleri
Bölüm Derleme
Yazarlar

Ferhat Gürkan Aslan 0000-0001-8394-1962

Elmas Pınar Kahraman Kılbaş 0000-0003-1348-625X

Mustafa Altındiş 0000-0003-0411-9669

Yayımlanma Tarihi 21 Mart 2022
Gönderilme Tarihi 2 Ocak 2022
Kabul Tarihi 14 Şubat 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 8 Sayı: 1

Kaynak Göster

APA Aslan, F. G., Kahraman Kılbaş, E. P., & Altındiş, M. (2022). COVID-19 Enfeksiyonlarında Dizi Analizi Yöntemlerine Genel Bakış. Kocaeli Üniversitesi Sağlık Bilimleri Dergisi, 8(1), 6-17. https://doi.org/10.30934/kusbed.1052257
AMA Aslan FG, Kahraman Kılbaş EP, Altındiş M. COVID-19 Enfeksiyonlarında Dizi Analizi Yöntemlerine Genel Bakış. KOU Sag Bil Derg. Mart 2022;8(1):6-17. doi:10.30934/kusbed.1052257
Chicago Aslan, Ferhat Gürkan, Elmas Pınar Kahraman Kılbaş, ve Mustafa Altındiş. “COVID-19 Enfeksiyonlarında Dizi Analizi Yöntemlerine Genel Bakış”. Kocaeli Üniversitesi Sağlık Bilimleri Dergisi 8, sy. 1 (Mart 2022): 6-17. https://doi.org/10.30934/kusbed.1052257.
EndNote Aslan FG, Kahraman Kılbaş EP, Altındiş M (01 Mart 2022) COVID-19 Enfeksiyonlarında Dizi Analizi Yöntemlerine Genel Bakış. Kocaeli Üniversitesi Sağlık Bilimleri Dergisi 8 1 6–17.
IEEE F. G. Aslan, E. P. Kahraman Kılbaş, ve M. Altındiş, “COVID-19 Enfeksiyonlarında Dizi Analizi Yöntemlerine Genel Bakış”, KOU Sag Bil Derg, c. 8, sy. 1, ss. 6–17, 2022, doi: 10.30934/kusbed.1052257.
ISNAD Aslan, Ferhat Gürkan vd. “COVID-19 Enfeksiyonlarında Dizi Analizi Yöntemlerine Genel Bakış”. Kocaeli Üniversitesi Sağlık Bilimleri Dergisi 8/1 (Mart 2022), 6-17. https://doi.org/10.30934/kusbed.1052257.
JAMA Aslan FG, Kahraman Kılbaş EP, Altındiş M. COVID-19 Enfeksiyonlarında Dizi Analizi Yöntemlerine Genel Bakış. KOU Sag Bil Derg. 2022;8:6–17.
MLA Aslan, Ferhat Gürkan vd. “COVID-19 Enfeksiyonlarında Dizi Analizi Yöntemlerine Genel Bakış”. Kocaeli Üniversitesi Sağlık Bilimleri Dergisi, c. 8, sy. 1, 2022, ss. 6-17, doi:10.30934/kusbed.1052257.
Vancouver Aslan FG, Kahraman Kılbaş EP, Altındiş M. COVID-19 Enfeksiyonlarında Dizi Analizi Yöntemlerine Genel Bakış. KOU Sag Bil Derg. 2022;8(1):6-17.