Application of Next-Generation Sequencing (NGS) Techniques for Selected Companion Animals
Abstract
:Simple Summary
Abstract
1. Introduction
2. Physiological Investigations
2.1. Reproduction Research
2.2. Microbiology
3. Metabolic Processes in Animals
4. Veterinary Genetic
5. Veterinary Parasitology
6. Infectious Diseases in Animals
7. Veterinary Immunology
8. Veterinary Oncology
9. Treatment Planning
10. Advantages and Disadvantages of NGS
11. Future Perspectives for Sequencing
12. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Aranaz, A. Significance and Integration of Molecular Diagnostics in the Framework of Veterinary Practice. Methods Mol. Biol. 2015, 1247, 19–30. [Google Scholar] [CrossRef]
- Bell, J. The Polymerase Chain Reaction. Immunol. Today 1989, 10, 351–355. [Google Scholar] [CrossRef] [PubMed]
- Sanger, F.; Coulson, A.R. A Rapid Method for Determining Sequences in DNA by Primed Synthesis with DNA Polymerase. J. Mol. Biol. 1975, 94, 441–448. [Google Scholar] [CrossRef] [PubMed]
- Gupta, N.; Verma, V.K. Next-Generation Sequencing and Its Application: Empowering in Public Health Beyond Reality. In Microbial Technology for the Welfare of Society; Springer: Singapore, 2019; Volume 17, pp. 313–341. [Google Scholar] [CrossRef]
- Ronaghi, M. Pyrosequencing Sheds Light on DNA Sequencing. Genome Res. 2001, 11, 3–11. [Google Scholar] [CrossRef]
- Qin, D. Next-Generation Sequencing and Its Clinical Application. Cancer Biol. Med. 2019, 16, 4–10. [Google Scholar] [CrossRef] [PubMed]
- Hu, T.; Chitnis, N.; Monos, D.; Dinh, A. Next-Generation Sequencing Technologies: An Overview. Hum. Immunol. 2021, 82, 801–811. [Google Scholar] [CrossRef] [PubMed]
- Khodakov, D.; Wang, C.; Zhang, D.Y. Diagnostics Based on Nucleic Acid Sequence Variant Profiling: PCR, Hybridization, and NGS Approaches. Adv. Drug Deliv. Rev. 2016, 105, 3–19. [Google Scholar] [CrossRef] [PubMed]
- Deneke, C.; Rentzsch, R.; Renard, B.Y. PaPrBaG: A Machine Learning Approach for the Detection of Novel Pathogens from NGS Data. Sci. Rep. 2017, 7, 39194. [Google Scholar] [CrossRef]
- Stathopoulou, K.M.; Georgakopoulos, S.; Tasoulis, S.; Plagianakos, V.P. Investigating the Overlap of Machine Learning Algorithms in the Final Results of RNA-Seq Analysis on Gene Expression Estimation. Health Inf. Sci. Syst. 2024, 12, 14. [Google Scholar] [CrossRef] [PubMed]
- De La Fuente, G.; Belanche, A.; Girwood, S.E.; Pinloche, E.; Wilkinson, T.; Newbold, C.J. Pros and Cons of Ion-Torrent Next Generation Sequencing versus Terminal Restriction Fragment Length Polymorphism T-RFLP for Studying the Rumen Bacterial Community. PLoS ONE 2014, 9, e101435. [Google Scholar] [CrossRef] [PubMed]
- Pearman, W.S.; Freed, N.E.; Silander, O.K. Testing the Advantages and Disadvantages of Short- and Long-Read Eukaryotic Metagenomics Using Simulated Reads. BMC Bioinform. 2020, 21, 220. [Google Scholar] [CrossRef] [PubMed]
- Petersen, L.M.; Martin, I.W.; Moschetti, W.E.; Kershaw, C.M.; Tsongalis, G.J. Third-Generation Sequencing in the Clinical Laboratory: Exploring the Advantages and Challenges of Nanopore Sequencing. J. Clin. Microbiol. 2019, 58, e01315-19. [Google Scholar] [CrossRef] [PubMed]
- Amarasinghe, S.L.; Su, S.; Dong, X.; Zappia, L.; Ritchie, M.E.; Gouil, Q. Opportunities and Challenges in Long-Read Sequencing Data Analysis. Genome Biol. 2020, 21, 30. [Google Scholar] [CrossRef] [PubMed]
- Zinsstag, J.; Schelling, E.; Crump, L.; Whittaker, M.; Tanner, M.; Stephen, C. One Health: The Theory and Practice of Integrated Health Approaches; CABI: Wallingford, UK, 2021. [Google Scholar] [CrossRef]
- Gullapalli, R.R.; Desai, K.V.; Santana-Santos, L.; Kant, J.A.; Becich, M.J. Next Generation Sequencing in Clinical Medicine: Challenges and Lessons for Pathology and Biomedical Informatics. J. Pathol. Inform. 2012, 3, 40. [Google Scholar] [CrossRef] [PubMed]
- Elangovan, A.; Jeyaseelan, T. Medical Imaging Modalities: A Survey. In Proceedings of the 1st International Conference on Emerging Trends in Engineering, Technology and Science, ICETETS 2016, Pudukkottai, India, 24–26 February 2016. [Google Scholar] [CrossRef]
- Luppa, P.B.; Müller, C.; Schlichtiger, A.; Schlebusch, H. Point-of-Care Testing (POCT): Current Techniques and Future Perspectives. TrAC Trends Anal. Chem. 2011, 30, 887–898. [Google Scholar] [CrossRef] [PubMed]
- Dodet, B.; Heseltine, E.; Saliou, P. Rotaviruses in Human and Veterinary Medicine. Trends Microbiol. 1997, 5, 176–178. [Google Scholar] [CrossRef] [PubMed]
- Hull, N.C.; Schumaker, B.A. Comparisons of Brucellosis between Human and Veterinary Medicine. Infect. Ecol. Epidemiol. 2018, 8, 1500846. [Google Scholar] [CrossRef] [PubMed]
- Van Borm, S.; Belák, S.; Freimanis, G.; Fusaro, A.; Granberg, F.; Höper, D.; King, D.P.; Monne, I.; Orton, R.; Rosseel, T. Next-Generation Sequencing in Veterinary Medicine: How Can the Massive Amount of Information Arising from High-Throughput Technologies Improve Diagnosis, Control, and Management of Infectious Diseases? Methods Mol. Biol. 2014, 1247, 415–436. [Google Scholar] [CrossRef] [PubMed]
- Dunisławska, A.; Łachmańska, J.; Sławińska, A.; Siwek, M. Next Generation Sequencing in Animal Science-a Review. Anim. Sci. Pap. Rep. 2017, 35, 205–224. [Google Scholar]
- Belák, S.; Karlsson, O.E.; Blomström, A.L.; Berg, M.; Granberg, F. New Viruses in Veterinary Medicine, Detected by Metagenomic Approaches. Vet. Microbiol. 2013, 165, 95–101. [Google Scholar] [CrossRef]
- Garza, D.R.; Dutilh, B.E. From Cultured to Uncultured Genome Sequences: Metagenomics and Modeling Microbial Ecosystems. Cell. Mol. Life Sci. 2015, 72, 4287–4308. [Google Scholar] [CrossRef] [PubMed]
- Arizmendi, A.; Rudd Garces, G.; Crespi, J.A.; Olivera, L.H.; Barrientos, L.S.; Peral García, P.; Giovambattista, G. Analysis of Doberman Pinscher and Toy Poodle Samples with Targeted Next-Generation Sequencing. Gene 2023, 853, 147069. [Google Scholar] [CrossRef] [PubMed]
- Viluma, A.; Sayyab, S.; Mikko, S.; Andersson, G.; Bergström, T.F. Evaluation of Whole-Genome Sequencing of Four Chinese Crested Dogs for Variant Detection Using the Ion Proton System. Canine Genet. Epidemiol. 2015, 2, 16. [Google Scholar] [CrossRef] [PubMed]
- Sugasawa, T.; Matsumoto, Y.; Fang, H.; Takemasa, T.; Komine, R.; Tamai, S.; Gu, W.; Tanaka, K.; Kanki, Y.; Takahashi, Y. Establishing a Sequencing Method for the Whole Mitochondrial DNA of Domestic Dogs. Animals 2023, 13, 2332. [Google Scholar] [CrossRef] [PubMed]
- Goldstein, D.S. How Does Homeostasis Happen? Integrative Physiological, Systems Biological, and Evolutionary Perspectives. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019, 316, R301–R317. [Google Scholar] [CrossRef] [PubMed]
- Frese, K.S.; Katus, H.A.; Meder, B. Next-Generation Sequencing: From Understanding Biology to Personalized Medicine. Biology 2013, 2, 378–398. [Google Scholar] [CrossRef] [PubMed]
- Nowak, M.; Rehrauer, H.; Ay, S.S.; Findik, M.; Boos, A.; Kautz, E.; Kowalewski, M.P. Gene Expression Profiling of the Canine Placenta during Normal and Antigestagen-Induced Luteolysis. Gen. Comp. Endocrinol. 2019, 282, 113194. [Google Scholar] [CrossRef] [PubMed]
- Kukurba, K.R.; Montgomery, S.B. RNA Sequencing and Analysis. Cold Spring Harb. Protoc. 2015, 2015, 951–969. [Google Scholar] [CrossRef]
- Harvey, R.G.; Duclos, D.; Krumbeck, J.; Tang, S. Quantification of the Bacterial Flora and Its Major Constituents on the Abdominal Skin of Clinically Healthy Dogs. Am. J. Vet. Res. 2023, 84, 1–6. [Google Scholar] [CrossRef] [PubMed]
- Bergeron, C.C.; Costa, M.C.; de Souza, L.B.; Sauvé, F. Description of the Bacterial Microbiota of Anal Sacs in Healthy Dogs. Can. J. Vet. Res. 2021, 85, 12–17. [Google Scholar] [PubMed]
- Banks, K.C.; Giuliano, E.A.; Busi, S.B.; Reinero, C.R.; Ericsson, A.C. Evaluation of Healthy Canine Conjunctival, Periocular Haired Skin, and Nasal Microbiota Compared to Conjunctival Culture. Front. Vet. Sci. 2020, 7, 558. [Google Scholar] [CrossRef] [PubMed]
- Apostolopoulos, N.; Glaeser, S.P.; Bagwe, R.; Janssen, S.; Mayer, U.; Ewers, C.; Kämpfer, P.; Neiger, R.; Thom, N. Description and Comparison of the Skin and Ear Canal Microbiota of Non-Allergic and Allergic German Shepherd Dogs Using next Generation Sequencing. PLoS ONE 2021, 16, e0250695. [Google Scholar] [CrossRef] [PubMed]
- Meason-Smith, C.; Diesel, A.; Patterson, A.P.; Older, C.E.; Johnson, T.J.; Mansell, J.M.; Suchodolski, J.S.; Rodrigues Hoffmann, A. Characterization of the Cutaneous Mycobiota in Healthy and Allergic Cats Using next Generation Sequencing. Vet. Dermatol. 2017, 28, 71. [Google Scholar] [CrossRef] [PubMed]
- Arai, T. The Development of Animal Nutrition and Metabolism and the Challenges of Our Time. Front. Vet. Sci. 2014, 1, 23. [Google Scholar] [CrossRef]
- Allen, M.J. Biochemical Markers of Bone Metabolism in Animals: Uses and Limitations. Vet. Clin. Pathol. 2003, 32, 101–113. [Google Scholar] [CrossRef] [PubMed]
- Jiang, Y.; Xiong, X.; Danska, J.; Parkinson, J. Metatranscriptomic Analysis of Diverse Microbial Communities Reveals Core Metabolic Pathways and Microbiomespecific Functionality. Microbiome 2016, 4, 2. [Google Scholar] [CrossRef] [PubMed]
- Wallis, N.; Raffan, E. The Genetic Basis of Obesity and Related Metabolic Diseases in Humans and Companion Animals. Genes 2020, 11, 1378. [Google Scholar] [CrossRef]
- Grzemski, A.; Stachowiak, M.; Flisikowski, K.; Mankowska, M.; Krzeminska, P.; Gogulski, M.; Aleksiewicz, R.; Szydlowski, M.; Switonski, M.; Nowacka-Woszuk, J. FTO and IRX3 Genes Are Not Promising Markers for Obesity in Labrador Retriever Dogs. Ann. Anim. Sci. 2019, 19, 343–357. [Google Scholar] [CrossRef]
- Eritja, À.; Caus, M.; Belmonte, T.; de Gonzalo-Calvo, D.; García-Carrasco, A.; Martinez, A.; Martínez, M.; Bozic, M. MicroRNA Expression Profile in Obesity-Induced Kidney Disease Driven by High-Fat Diet in Mice. Nutrients 2024, 16, 691. [Google Scholar] [CrossRef] [PubMed]
- Rodney, A.R.; Buckley, R.M.; Fulton, R.S.; Fronick, C.; Richmond, T.; Helps, C.R.; Pantke, P.; Trent, D.J.; Vernau, K.M.; Munday, J.S.; et al. A Domestic Cat Whole Exome Sequencing Resource for Trait Discovery. Sci. Rep. 2021, 11, 7159. [Google Scholar] [CrossRef]
- Di Loria, A.; Ferravante, C.; D’Agostino, Y.; Giurato, G.; Tursi, M.; Grego, E.; Perego, M.; Weisz, A.; Ciaramella, P.; Santilli, R. Gene-Expression Profiling of Endomyocardial Biopsies from Dogs with Dilated Cardiomyopathy Phenotype. J. Vet. Cardiol. 2024, 52, 78–89. [Google Scholar] [CrossRef] [PubMed]
- Uno, Y.; Yamato, O.; Yamazaki, H. Transcript Abundance of Hepatic Drug-Metabolizing Enzymes in Two Dog Breeds Compared with 14 Species Including Humans. Drug Metab. Pharmacokinet. 2024, 55, 101002. [Google Scholar] [CrossRef] [PubMed]
- Yokoyama, J.S.; Lam, E.T.; Ruhe, A.L.; Erdman, C.A.; Robertson, K.R.; Webb, A.A.; Williams, D.C.; Chang, M.L.; Hytönen, M.K.; Lohi, H.; et al. Variation in Genes Related to Cochlear Biology Is Strongly Associated with Adult-Onset Deafness in Border Collies. PLoS Genet. 2012, 8. [Google Scholar] [CrossRef] [PubMed]
- Sayyab, S.; Viluma, A.; Bergvall, K.; Brunberg, E.; Jagannathan, V.; Leeb, T.; Andersson, G.; Bergström, T.F. Whole-Genome Sequencing of a Canine Family Trio Reveals a FAM83G Variant Associated with Hereditary Footpad Hyperkeratosis. G3 2016, 6, 521–527. [Google Scholar] [CrossRef] [PubMed]
- Wang, X.; Liang, Y.; Zhao, J.; Li, Y.; Gou, S.; Zheng, M.; Zhou, J.; Zhang, Q.; Mi, J.; Lai, L. Generation of Permanent Neonatal Diabetes Mellitus Dogs with Glucokinase Point Mutations through Base Editing. Cell Discov. 2021, 7, 92. [Google Scholar] [CrossRef]
- Ye, F.; Samuels, D.C.; Clark, T.; Guo, Y. High-Throughput Sequencing in Mitochondrial DNA Research. Mitochondrion 2014, 17, 157–163. [Google Scholar] [CrossRef] [PubMed]
- Lyons, L.A.; Creighton, E.K.; Alhaddad, H.; Beale, H.C.; Grahn, R.A.; Rah, H.C.; Maggs, D.J.; Helps, C.R.; Gandolfi, B. Whole Genome Sequencing in Cats, Identifies New Models for Blindness in AIPL1 and Somite Segmentation in HES7. BMC Genom. 2016, 17, 265. [Google Scholar] [CrossRef] [PubMed]
- Yuan, J.; Kitchener, A.C.; Lackey, L.B.; Sun, T.; Jiangzuo, Q.; Tuohetahong, Y.; Zhao, L.; Yang, P.; Wang, G.; Huang, C.; et al. The Genome of the Black-Footed Cat: Revealing a Rich Natural History and Urgent Conservation Priorities for Small Felids. Proc. Natl. Acad. Sci. USA 2024, 121, e2310763120. [Google Scholar] [CrossRef]
- Buckley, R.M.; Davis, B.W.; Brashear, W.A.; Farias, F.H.G.; Kuroki, K.; Graves, T.; Hillier, L.W.; Kremitzki, M.; Li, G.; Middleton, R.; et al. A New Domestic Cat Genome Assembly Based on Long Sequence Reads Empowers Feline Genomic Medicine and Identifies a Novel Gene for Dwarfism. bioRxiv 2020. [Google Scholar] [CrossRef]
- Giani, A.M.; Gallo, G.R.; Gianfranceschi, L.; Formenti, G. Long Walk to Genomics: History and Current Approaches to Genome Sequencing and Assembly. Comput. Struct. Biotechnol. J. 2020, 18, 9–19. [Google Scholar] [CrossRef] [PubMed]
- Liu, Y.; Xu, J.; Chen, M.; Wang, C.; Li, S. A Unified STR Profiling System across Multiple Species with Whole Genome Sequencing Data. BMC Bioinform. 2019, 20, 671. [Google Scholar] [CrossRef] [PubMed]
- Lojkić, M.; Raič, I.; Karadjole, T.; Bačić, G.; Butković, I.; Prvanović Babić, N.; Špoljarić, B.; Getz, I.; Folnožić, I.; Šavorić, J.; et al. Dual Sire Insemination in Dogs. Vet. Stanica 2023, 54, 29–37. [Google Scholar] [CrossRef]
- Holden, C. Canine Genome Project. Science 1990, 248, 1184. [Google Scholar] [CrossRef] [PubMed]
- Ostrander, E.A.; Wayne, R.K. The Canine Genome. Genome Res. 2005, 15, 1706–1716. [Google Scholar] [CrossRef] [PubMed]
- O’Brien, S.J.; Menotti-Raymond, M.; Murphy, W.J.; Yuhki, N. The Feline Genome Project. Annu. Rev. Genet. 2002, 36, 657–686. [Google Scholar] [CrossRef] [PubMed]
- Nicholas, F.; Tammen, I.; Hub, S.I. Online Mendelian Inheritance in Animals (OMIA); University of Sydney: Sydney, Australia, 1995. [Google Scholar] [CrossRef]
- Wu, X.; Den Boer, E.R.; Vos-Loohuis, M.; van Steenbeek, F.G.; Monroe, G.R.; Nijman, I.J.; Leegwater, P.A.J.; Fieten, H. Investigation of Genetic Modifiers of Copper Toxicosis in Labrador Retrievers. Life 2020, 10, 266. [Google Scholar] [CrossRef] [PubMed]
- Ballesteros, N.; Castañeda, S.; Muñoz, M.; Flórez, A.; Pinilla, J.C.; Ramírez, J.D. The First Report of Dirofilaria Repens Infection in Dogs from Colombia. Parasitol. Res. 2023, 122, 2445–2450. [Google Scholar] [CrossRef] [PubMed]
- Valkiunas, G.; Iezhova, T.A.; Križanauskiene, A.; Palinauskas, V.; Sehgal, R.N.M.; Bensch, S. A Comparative Analysis of Microscopy and PCR-Based Detection Methods for Blood Parasites. J. Parasitol. 2008, 94, 1395–1401. [Google Scholar] [CrossRef] [PubMed]
- Inácio, S.V.; Gomes, J.F.; Falcão, A.X.; Suzuki, C.T.N.; Nagata, W.B.; Loiola, S.H.N.; Dos Santos, B.M.; Soares, F.A.; Rosa, S.L.; Baptista, C.B.; et al. Automated Diagnosis of Canine Gastrointestinal Parasites Using Image Analysis. Pathogens 2020, 9, 139. [Google Scholar] [CrossRef] [PubMed]
- Simonato, G.; Frangipane di Regalbono, A.; Cassini, R.; Traversa, D.; Beraldo, P.; Tessarin, C.; Pietrobelli, M. Copromicroscopic and Molecular Investigations on Intestinal Parasites in Kenneled Dogs. Parasitol. Res. 2015, 114, 1963–1970. [Google Scholar] [CrossRef] [PubMed]
- Dumoulin, A. False Positives in Infectious Serology: A Rare Issue That Should Not Be Ignored. Rev. Med. Suisse 2023, 19, 1830–1834. [Google Scholar] [CrossRef] [PubMed]
- Lesniak, I.; Franz, M.; Heckmann, I.; Greenwood, A.D.; Hofer, H.; Krone, O. Surrogate Hosts: Hunting Dogs and Recolonizing Grey Wolves Share Their Endoparasites. Int. J. Parasitol. Parasites Wildl. 2017, 6, 278–286. [Google Scholar] [CrossRef] [PubMed]
- Castillo-Castañeda, A.C.; Patiño, L.H.; Zuñiga, M.F.; Cantillo-Barraza, O.; Ayala, M.S.; Segura, M.; Bautista, J.; Urbano, P.; Jaimes-Dueñez, J.; Ramírez, J.D. An Overview of the Trypanosomatid (Kinetoplastida: Trypanosomatidae) Parasites Infecting Several Mammal Species in Colombia. Parasites Vectors 2022, 15, 471. [Google Scholar] [CrossRef] [PubMed]
- Huggins, L.G.; Atapattu, U.; Young, N.D.; Traub, R.J.; Colella, V. Development and Validation of a Long-Read Metabarcoding Platform for the Detection of Filarial Worm Pathogens of Animals and Humans. BMC Microbiol. 2024, 24, 28. [Google Scholar] [CrossRef]
- Lagier, J.C.; Edouard, S.; Pagnier, I.; Mediannikov, O.; Drancourt, M.; Raoult, D. Current and Past Strategies for Bacterial Culture in Clinical Microbiology. Clin. Microbiol. Rev. 2015, 28, 208–236. [Google Scholar] [CrossRef] [PubMed]
- Yang, S.; Rothman, R.E. PCR-Based Diagnostics for Infectious Diseases: Uses, Limitations, and Future Applications in Acute-Care Settings. Lancet Infect. Dis. 2004, 4, 337–348. [Google Scholar] [CrossRef] [PubMed]
- Haselbeck, A.H.; Im, J.; Prifti, K.; Marks, F.; Holm, M.; Zellweger, R.M. Serology as a Tool to Assess Infectious Disease Landscapes and Guide Public Health Policy. Pathogens 2022, 11, 732. [Google Scholar] [CrossRef] [PubMed]
- Gwinn, M.; Maccannell, D.; Armstrong, G.L. Next Generation Sequencing of Infectious Pathogens. JAMA 2019, 321, 893–894. [Google Scholar] [CrossRef] [PubMed]
- Van, S.; Sciensano, B.; Granberg, F.; Colling, A. Next-Generation Sequencing Workflows in Veterinary Infection Biology: Towards Validation and Quality Assurance. Rev. Sci. Tech. 2016, 35, 67–81. [Google Scholar] [CrossRef] [PubMed]
- Li, M.; Yan, K.; Jia, P.; Wei, E.; Wang, H. Metagenomic Next-Generation Sequencing May Assist Diagnosis of Cat-Scratch Disease. Front. Cell. Infect. Microbiol. 2022, 12, 946849. [Google Scholar] [CrossRef]
- Granberg, F.; Bálint, Á.; Belák, S. Novel Technologies Applied to the Nucleotide Sequencing and Comparative Sequence Analysis of the Genomes of Infectious Agents in Veterinary Medicine. Rev. Sci. Tech. 2016, 35, 25–42. [Google Scholar] [CrossRef] [PubMed]
- Charles, R.A.; Pow-Brown, P.; Gordon-Dillon, A.; Blake, L.; Nicholls, S.; Brown-Jordan, A.; Caruth, J.; Sant, C.; Pargass, I.; Basu, A.; et al. Completing the Puzzle: A Cluster of Hunting Dogs with Tick-Borne Illness from a Fishing Community in Tobago, West Indies. Pathogens 2024, 13, 161. [Google Scholar] [CrossRef] [PubMed]
- Intirach, J.; Lv, X.; Sutthanont, N.; Cai, B.; Champakaew, D.; Chen, T.; Han, Q.; Lv, Z. Molecular and Next-Generation Sequencing Analysis of Tick-Borne Pathogens of Rhipicephalus Ticks (Acari: Ixodidae) in Cattle and Dogs. Acta Trop. 2024, 252, 107138. [Google Scholar] [CrossRef] [PubMed]
- Davitt, C.; Huggins, L.G.; Pfeffer, M.; Batchimeg, L.; Jones, M.; Battur, B.; Wiethoelter, A.K.; Traub, R. Next-Generation Sequencing Metabarcoding Assays Reveal Diverse Bacterial Vector-Borne Pathogens of Mongolian Dogs. Curr. Res. Parasitol. Vector-Borne Dis. 2024, 5, 100173. [Google Scholar] [CrossRef] [PubMed]
- Condon, E.; Grecco, S.; Marandino, A.; Aldaz, J.; Enciso, J.; Alfaro, L.; Bucafusco, D.; Pérez, R.; Panzera, Y. Development of an Accurate and Rapid Method for Whole Genome Characterization of Canine Parvovirus. J. Virol. Methods 2024, 325, 114870. [Google Scholar] [CrossRef] [PubMed]
- Lanszki, Z.; Tóth, G.E.; Schütz, É.; Zeghbib, S.; Rusvai, M.; Jakab, F.; Kemenesi, G. Complete Genomic Sequencing of Canine Distemper Virus with Nanopore Technology during an Epizootic Event. Sci. Rep. 2022, 12, 4116. [Google Scholar] [CrossRef] [PubMed]
- Lanszki, Z.; Lanszki, J.; Tóth, G.E.; Zeghbib, S.; Jakab, F.; Kemenesi, G. Retrospective Detection and Complete Genomic Sequencing of Canine Morbillivirus in Eurasian Otter (Lutra lutra) Using Nanopore Technology. Viruses 2022, 14, 1433. [Google Scholar] [CrossRef] [PubMed]
- Sakamoto, H.; Ito, G.; Goto-Koshino, Y.; Sakamoto, M.; Nishimura, R.; Momoi, Y. Detection of Domestic Cat Hepadnavirus by Next-Generation Sequencing and epidemiological Survey in Japan. J. Vet. Med. Sci. 2023, 85, 642–646. [Google Scholar] [CrossRef] [PubMed]
- Momoi, Y.; Matsuu, A. Detection of Severe Fever with Thrombocytopenia Syndrome Virus and Other Viruses in Cats via Unbiased Next-Generation Sequencing. J. Veter. Diagn. Investig. 2020, 33, 279–282. [Google Scholar] [CrossRef] [PubMed]
- Boros, Á.; Albert, M.; Urbán, P.; Herczeg, R.; Gáspár, G.; Balázs, B.; Cságola, A.; Pankovics, P.; Gyenesei, A.; Reuter, G. Unusual “Asian-Origin” 2c to 2b Point Mutant Canine Parvovirus (Parvoviridae) and Canine Astrovirus (Astroviridae) Co-Infection Detected in Vaccinated Dogs with an Outbreak of Severe Haemorrhagic Gastroenteritis with High Mortality Rate in Hungary. Vet. Res. Commun. 2022, 46, 1355–1361. [Google Scholar] [CrossRef] [PubMed]
- Choga, W.T.; Letsholo, S.L.; Marobela-Raborokgwe, C.; Gobe, I.; Mazwiduma, M.; Maruapula, D.; Rukwava, J.; Binta, M.G.; Zuze, B.J.L.; Koopile, L.; et al. Near-Complete Genome of SARS-CoV-2 Delta Variant of Concern Identified in a Symptomatic Dog (Canis lupus familiaris) in Botswana. Vet. Med. Sci. 2023, 9, 1465–1472. [Google Scholar] [CrossRef] [PubMed]
- Kuhlmeier, E.; Chan, T.; Agüí, C.V.; Willi, B.; Wolfensberger, A.; Beisel, C.; Topolsky, I.; Beerenwinkel, N.; Stadler, T.; Jones, S.; et al. Detection and Molecular Characterization of the SARS-CoV-2 Delta Variant and the Specific Immune Response in Companion Animals in Switzerland. Viruses 2023, 15, 245. [Google Scholar] [CrossRef] [PubMed]
- Kattoor, J.J.; Mlalazi-Oyinloye, M.; Nemser, S.M.; Wilkes, R.P. Development of a Targeted NGS Assay for the Detection of Respiratory Pathogens Including SARS-CoV-2 in Felines. Pathogens 2024, 13, 335. [Google Scholar] [CrossRef] [PubMed]
- Padilla-Blanco, M.; Vega, S.; Enjuanes, L.; Morey, A.; Lorenzo, T.; Marín, C.; Ivorra, C.; Maiques, E.; Rubio, V.; Rubio-Guerri, C. Detection of SARS-CoV-2 in a Dog with Hemorrhagic Diarrhea. BMC Vet. Res. 2022, 18, 370. [Google Scholar] [CrossRef] [PubMed]
- Gershwin, L.J. Autoimmune Diseases in Small Animals. Vet. Clin. N. Am.—Small Anim. Pract. 2010, 40, 439–457. [Google Scholar] [CrossRef] [PubMed]
- Ji, Y.; Yang, Y.; Wu, Z. Programming of Metabolic and Autoimmune Diseases in Canine and Feline: Linkage to the Gut Microbiome. Microb. Pathog. 2023, 185, 106436. [Google Scholar] [CrossRef] [PubMed]
- MacNeill, A.L.; Dandrieux, J.; Lubas, G.; Seelig, D.; Szladovits, B. The Utility of Diagnostic Tests for Immune-Mediated Hemolytic Anemia. Vet. Clin. Pathol. 2019, 48 (Suppl. S1), 7–16. [Google Scholar] [CrossRef] [PubMed]
- Wyatt, E.K.; Schmidt, V.; Legnani, S. Canine Cutaneous Lupus Erythematosus with Prominent Interdigital Lesions in Two Greyhounds. Vet. Dermatol. 2024, 35, 242–246. [Google Scholar] [CrossRef] [PubMed]
- Hwang, M.H.; Darzentas, N.; Bienzle, D.; Moore, P.F.; Morrison, J.; Keller, S.M. Characterization of the Canine Immunoglobulin Heavy Chain Repertoire by next Generation Sequencing. Vet. Immunol. Immunopathol. 2018, 202, 181–190. [Google Scholar] [CrossRef] [PubMed]
- Oh, J.H.; Cho, J.Y. Comparative Oncology: Overcoming Human Cancer through Companion Animal Studies. Exp. Mol. Med. 2023, 55, 725–734. [Google Scholar] [CrossRef] [PubMed]
- Wilk, S.S.; Michalak, K.; Owczarek, E.P.; Winiarczyk, S.; Zabielska-Koczywąs, K.A. Proteomic Analyses Reveal the Role of Alpha-2-Macroglobulin in Canine Osteosarcoma Cell Migration. Int. J. Mol. Sci. 2024, 25, 3989. [Google Scholar] [CrossRef] [PubMed]
- Sakthikumar, S.; Warrier, M.; Whitley, D.; Facista, S.; Adkins, J.; Aman, S.; Tsinajinnie, D.; Duran, N.; Siravegna, G.; Ahmed, Z.; et al. Genomic Analysis across 53 Canine Cancer Types Reveals Novel Mutations and High Clinical Actionability Potential. Vet. Comp. Oncol. 2024, 22, 30–41. [Google Scholar] [CrossRef]
- Flory, A.; Kruglyak, K.M.; Tynan, J.A.; McLennan, L.M.; Rafalko, J.M.; Fiaux, P.C.; Hernandez, G.E.; Marass, F.; Nakashe, P.; Ruiz-Perez, C.A.; et al. Clinical Validation of a Next-Generation Sequencing-Based Multi-Cancer Early Detection “Liquid Biopsy” Blood Test in over 1,000 Dogs Using an Independent Testing Set: The CANcer Detection in Dogs (CANDiD) Study. PLoS ONE 2022, 17, e0266623. [Google Scholar] [CrossRef] [PubMed]
- McCleary-Wheeler, A.L.; Fiaux, P.C.; Flesner, B.K.; Ruiz-Perez, C.A.; McLennan, L.M.; Tynan, J.A.; Hicks, S.C.; Rafalko, J.M.; Grosu, D.S.; Chibuk, J.; et al. Next-Generation Sequencing-Based Liquid Biopsy May Be Used for Detection of Residual Disease and Cancer Recurrence Monitoring in Dogs. Am. J. Vet. Res. 2024, 85, 1–8. [Google Scholar] [CrossRef] [PubMed]
- Ventola, C.L. The Antibiotic Resistance Crisis: Part 1: Causes and Threats. Pharm. Ther. 2015, 40, 277–283. [Google Scholar]
- Harada, K.; Miyamoto, T.; Sugiyama, M.; Asai, T. First Report of a BlaNDM-5-Carrying Escherichia Coli Sequence Type 12 Isolated from a Dog with Pyometra in Japan. J. Infect. Chemother. 2024, in press. [Google Scholar] [CrossRef] [PubMed]
- Kasprzak, J.; Westphalen, C.B.; Frey, S.; Schmitt, Y.; Heinemann, V.; Fey, T.; Nasseh, D. Supporting the Decision to Perform Molecular Profiling for Cancer Patients Based on Routinely Collected Data through the Use of Machine Learning. Clin. Exp. Med. 2024, 24, 73. [Google Scholar] [CrossRef] [PubMed]
- Fibi-Smetana, S.; Inglis, C.; Schuster, D.; Eberle, N.; Granados-Soler, J.L.; Liu, W.; Krohn, S.; Junghanss, C.; Nolte, I.; Taher, L.; et al. The TiHoCL Panel for Canine Lymphoma: A Feasibility Study Integrating Functional Genomics and Network Biology Approaches for Comparative Oncology Targeted NGS Panel Design. Front. Vet. Sci. 2023, 10, 1301536. [Google Scholar] [CrossRef] [PubMed]
- Murrell, A.; Rakyan, V.K.; Beck, S. From Genome to Epigenome. Hum. Mol. Genet. 2005, 14, R3–R10. [Google Scholar] [CrossRef] [PubMed]
- Kumar, K.R.; Cowley, M.J.; Davis, R.L. Next-Generation Sequencing and Emerging Technologies. Semin. Thromb. Hemost. 2019, 45, 661–673. [Google Scholar] [CrossRef] [PubMed]
- Díaz, L.; Zambrano, E.; Flores, M.E.; Contreras, M.; Crispín, J.C.; Alemán, G.; Bravo, C.; Armenta, A.; Valdés, V.J.; Tovar, A.; et al. Ethical Considerations in Animal Research: The Principle of 3R’s. Rev. Investig. Clin. 2020, 73, 199–209. [Google Scholar] [CrossRef] [PubMed]
- Thompson, P.B. Genetically Modified Animals: Ethical Issues. J. Anim. Sci. 1993, 71, 51–56. [Google Scholar] [CrossRef] [PubMed]
- Martinez-Martin, N.; Magnus, D. Privacy and Ethical Challenges in Next-Generation Sequencing. Expert. Rev. Precis. Med. Drug Dev. 2019, 4, 95–104. [Google Scholar] [CrossRef] [PubMed]
- Xiao, T.; Zhou, W. The Third Generation Sequencing: The Advanced Approach to Genetic Diseases. Transl. Pediatr. 2020, 9, 163–173. [Google Scholar] [CrossRef] [PubMed]
- Eid, J.; Fehr, A.; Gray, J.; Luong, K.; Lyle, J.; Otto, G.; Peluso, P.; Rank, D.; Baybayan, P.; Bettman, B.; et al. Real-Time DNA Sequencing from Single Polymerase Molecules. Science 2009, 323, 133–138. [Google Scholar] [CrossRef] [PubMed]
- Lee, H.; Gurtowski, J.; Yoo, S.; Nattestad, M.; Marcus, S.; Goodwin, S.; McCombie, W.R.; Schatz, M.C. Third-Generation Sequencing and the Future of Genomics. bioRxiv 2016. preprint. [Google Scholar] [CrossRef]
- Schadt, E.E.; Turner, S.; Kasarskis, A. A Window into Third-Generation Sequencing. Hum. Mol. Genet. 2010, 19, R227–R240. [Google Scholar] [CrossRef]
- Loit, K.; Adamson, K.; Bahram, M.; Puusepp, R.; Anslan, S.; Kiiker, R.; Drenkhan, R.; Tedersood, L. Relative Performance of MinION (Oxford Nanopore Technologies) versus Sequel (Pacific Biosciences) Thirdgeneration Sequencing Instruments in Identification of Agricultural and Forest Fungal Pathogens. Appl. Environ. Microbiol. 2019, 85, e01368-19. [Google Scholar] [CrossRef] [PubMed]
- Lamb, H.J.; Hayes, B.J.; Nguyen, L.T.; Ross, E.M. The Future of Livestock Management: A Review of Real-Time Portable Sequencing Applied to Livestock. Genes 2020, 11, 1478. [Google Scholar] [CrossRef] [PubMed]
- Jain, M.; Olsen, H.E.; Paten, B.; Akeson, M. The Oxford Nanopore MinION: Delivery of Nanopore Sequencing to the Genomics Community. Genome Biol. 2016, 17, 239. [Google Scholar] [CrossRef] [PubMed]
- Meslier, V.; Quinquis, B.; Da Silva, K.; Plaza Oñate, F.; Pons, N.; Roume, H.; Podar, M.; Almeida, M. Benchmarking Second and Third-Generation Sequencing Platforms for Microbial Metagenomics. Sci. Data 2022, 9, 694. [Google Scholar] [CrossRef] [PubMed]
- Ardui, S.; Ameur, A.; Vermeesch, J.R.; Hestand, M.S. Single Molecule Real-Time (SMRT) Sequencing Comes of Age: Applications and Utilities for Medical Diagnostics. Nucleic Acids Res. 2018, 46, 2159–2168. [Google Scholar] [CrossRef] [PubMed]
- Punetha, J.; Hoffman, E.P. Short Read (Next-Gen) Sequencing: A Tutorial with Cardiomyopathy Diagnostics as an Exemplar. Circ. Cardiovasc. Genet. 2013, 6, 427–434. [Google Scholar] [CrossRef]
- Magi, A.; Giusti, B.; Tattini, L. Characterization of MinION Nanopore Data for Resequencing Analyses. Brief. Bioinform. 2017, 18, 940–953. [Google Scholar] [CrossRef] [PubMed]
- Athanasopoulou, K.; Boti, M.A.; Adamopoulos, P.G.; Skourou, P.C.; Scorilas, A. Third-Generation Sequencing: The Spearhead towards the Radical Transformation of Modern Genomics. Life 2021, 12, 30. [Google Scholar] [CrossRef] [PubMed]
- Cheng, C.; Xiao, P. Evaluation of the Correctable Decoding Sequencing as a New Powerful Strategy for DNA Sequencing. Life Sci. Alliance 2022, 5, e202101294. [Google Scholar] [CrossRef] [PubMed]
- Tan, O.; Shrestha, R.; Cunich, M.; Schofield, D.J. Application of Next-Generation Sequencing to Improve Cancer Management: A Review of the Clinical Effectiveness and Cost-Effectiveness. Clin. Genet. 2018, 93, 533–544. [Google Scholar] [CrossRef] [PubMed]
- Cuber, P.; Chooneea, D.; Geeves, C.; Salatino, S.; Creedy, T.J.; Griffin, C.; Sivess, L.; Barnes, I.; Price, B.; Misra, R. Comparing the Accuracy and Efficiency of Third Generation Sequencing Technologies, Oxford Nanopore Technologies, and Pacific Biosciences, for DNA Barcode Sequencing Applications. Ecol. Genet. Genom. 2023, 28, 100181. [Google Scholar] [CrossRef]
Type of Sequencing | Advantages | Disadvantages |
---|---|---|
Illumina Sequencing | High throughput, short read lengths, and low error rates make it ideal for applications requiring deep coverage and precise variant detection. It is cost-effective and widely accessible, with a broad range of library preparation kits available for various applications [4]. | Limited read lengths, typically up to a few hundred base pairs, may pose challenges for de novo assembly and analysis of repetitive regions. PCR amplification during library preparation can introduce bias and errors, particularly in low-input samples [4]. |
Ion Torrent Sequencing | Offers rapid turnaround times and simple workflow, with no need for fluorescence labeling or imaging. It is suitable for targeted sequencing, amplicon sequencing, and small-genome sequencing [11]. | Error rates are higher compared to other NGS platforms, particularly in homopolymeric regions. The detection of insertions and deletions (indels) can be challenging, leading to decreased accuracy in variant calling [11]. |
Pacific Biosciences (PacBio) Sequencing | Provides long read lengths, spanning thousands to tens of thousands of base pairs, facilitating de novo assembly, resolving complex genomic regions, and detecting structural variations with high precision. It also enables direct observation of epigenetic modifications, such as DNA methylation [12]. | Higher error rates, particularly in the form of indels, limit the accuracy. Lower throughput and higher per-base costs may be prohibitive for large-scale projects requiring deep sequencing coverage [12] |
Oxford Nanopore Sequencing: | Offers real-time sequencing, long read lengths, and portability, making it suitable for field applications, rapid diagnostics, and real-time monitoring of DNA synthesis. It does not require PCR amplification, allowing for direct sequencing of native DNA and RNA molecules [13]. | Error rates can be relatively high, particularly in homopolymeric regions, although continuous improvements in base-calling algorithms are addressing this limitation. Additionally, the current cost per base is higher compared to other NGS platforms [13]. |
Long-Range Sequencing | Enables the detection of structural variations, haplotype phasing, and genome scaffolding by spanning large genomic distances. They complement short-read sequencing technologies and facilitate the assembly of complex genomes [14]. | Limited to structural variant detection and genome scaffolding, long-range sequencing methods typically have lower throughput and higher costs compared to short-read sequencing platforms. Additionally, they may require additional library preparation steps and specialized instrumentation [14]. |
Platform | MinIon | Sequel | Sanger |
---|---|---|---|
Long-read sequencing | Offers long-read sequencing capabilities with read lengths ranging from thousands to tens of thousands of bases [112,114,115]. | Provides longer average read lengths, often exceeding 10,000 bases [115,116]. | Typically produces relatively short read lengths, ranging from several hundred to a few thousand bases [117]. |
Throughput | It has lower throughput than Sequel, processing a fewer number of reads per run. Its rapid sequencing turnaround time and low upfront cost can compensate for this limitation in certain applications [112]. | Offers the highest throughput, generating a larger number of reads per run compared [112]. | Relatively low-throughput and time-consuming, especially for projects requiring large-scale sequencing [6]. |
Error rates | Higher than Sequel [118] | Lower than MinIon [119] | Is considered the gold standard for accuracy, it has lower error rates compared to third-generation sequencing platforms [120]. |
Cost-effectiveness | Offers a lower than Sequel upfront cost and reduced instrument footprint. However, the cost per base can be relatively high due to consumable expenses [119]. | Requires a higher than MinIon initial investment but may offer better cost-effectiveness in projects requiring large-scale sequencing due to its higher throughput and lower cost per base [121]. | It is more cost-effective for targeted sequencing of individual genes or small genomic regions. However, for projects requiring whole-genome or whole-exome sequencing, the cost per base can become prohibitive [121]. |
Applicability: | Well-suited for rapid, real-time sequencing applications, field studies, and point-of-care diagnostics due to its portability and quick turnaround time [113,122]. | Particularly advantageous for comprehensive genome analysis, including de novo assembly, structural variant detection, and long-range haplotyping, owing to its high throughput and long-read capabilities [122]. | Widely used in clinical diagnostics for confirming genetic variants identified through other sequencing methods. It plays a crucial role in verifying pathogenic mutations, identifying rare variants, and assessing genetic heterogeneity in patients with inherited disorders or cancer [102]. |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Domrazek, K.; Jurka, P. Application of Next-Generation Sequencing (NGS) Techniques for Selected Companion Animals. Animals 2024, 14, 1578. https://doi.org/10.3390/ani14111578
Domrazek K, Jurka P. Application of Next-Generation Sequencing (NGS) Techniques for Selected Companion Animals. Animals. 2024; 14(11):1578. https://doi.org/10.3390/ani14111578
Chicago/Turabian StyleDomrazek, Kinga, and Piotr Jurka. 2024. "Application of Next-Generation Sequencing (NGS) Techniques for Selected Companion Animals" Animals 14, no. 11: 1578. https://doi.org/10.3390/ani14111578
APA StyleDomrazek, K., & Jurka, P. (2024). Application of Next-Generation Sequencing (NGS) Techniques for Selected Companion Animals. Animals, 14(11), 1578. https://doi.org/10.3390/ani14111578