Next Generation Sequencing in Big Data

Autor: Chinmayee C, Amrita Nischal, C R Manjunath | Soumya K N, A huge revolution has taken place in the area of Genomic science. Sequencing of millions of DNA strands in parallel and also getting a higher throughput reduces the need to implement fragment cloning methods, where extra copies of genes are produced. The methodology of sequencing a large number of DNA strands in parallel is known as Next Generation Sequencing technique. An overview of how different sequencing methods work is described. Selection of two sequencing methods, Sanger Sequencing method and Next generation sequencing method and analysis of the parameters used in both these techniques. A Comparative study of these two methods is carried out accordingly. An overview of when to use Sanger sequencing and when to use Next generation sequencing is described. Increase in the amount of genomic data has given rise to challenges like sharing, integrating and analyzing the genetic data. Therefore, application of one of the big data techniques known as Map Reduce model is used to sequence the genetic data. A flow chart of how genetic is processed using MapReduce model is also present. Next Generation Sequencing for analysis of huge amount of genetic data is very useful but it has few limitations such as scaling and efficiency. Fortunately recent researches have proven that these demerits of Next Generation Sequencing can be easily overcome by implementing big data methodologies. Chinmayee C | Amrita Nischal | C R Manjunath | Soumya K N \\'Next Generation Sequencing in Big Data\\' Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: https://www.ijtsrd.com/papers/ijtsrd12975.pdf, Bioinformatics, Next Generation Sequencing

A huge revolution has taken place in the area of Genomic science. Sequencing of millions of DNA strands in parallel and also getting a higher throughput reduces the need to implement fragment cloning methods, where extra copies of genes are produced.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2659::8ec53fa0c25e585e58a454a12c331f12
https://zenodo.org/record/3581804

Genetic Characterization of Enterovirus A71 Circulating in Africa

Autor: Ousmane Kebe, Michael R. Wiley, Javier Martin, Maël Bessaud, Francis Delpeyroux, Maria Dolores Fernandez-Garcia, Serge Alain Sadeuh-Mba, Manasi Majumdar, Gustavo Palacios, Romain Volle, Ionela Gouandjika-Vasilache, Anavaj Sakuntabhai, Etienne Simon-Loriere, Marie-Line Joffret, Kader Ndiaye

Publikováno v: Emerging Infectious Diseases, Vol 24, Iss 4, Pp 754-757 (2018)
Emerging Infectious Diseases
Emerging Infectious Diseases, Centers for Disease Control and Prevention, 2018, 24 (4), pp.754-757. ⟨10.3201/eid2404.171783⟩
Emerging Infectious Diseases, 2018, 24 (4), pp.754-757. ⟨10.3201/eid2404.171783⟩

International audience; We analyzed whole-genome sequences of 8 enterovirus A71 isolates (EV-A71). We confirm the circulation of geno-group C and the new genogroup E in West Africa. Our analysis demonstrates wide geographic circulation and describes

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8da7d7feedd688f1aacf018fe49ac034
https://wwwnc.cdc.gov/eid/article/24/4/17-1783_article

High-throughput droplet-based analysis of influenza A virus genetic reassortment by single-virus RNA sequencing

Autor: Kuang-Yu Chen, Jayaprakash Karuppusamy, Mary B. O’Neill, Vaitea Opuu, Mathieu Bahin, Sophie Foulon, Pablo Ibanez, Lluis Quintana-Murci, Tatsuhiko Ozawa, Sylvie van der Werf, Philippe Nghe, Nadia Naffakh, Andrew Griffiths, Catherine Isel

Publikováno v: Proceedings of the National Academy of Sciences of the United States of America
Proceedings of the National Academy of Sciences of the United States of America, 2023, 120 (6), pp.e2211098120. ⟨10.1073/pnas.2211098120⟩

International audience; The segmented RNA genome of influenza A viruses (IAVs) enables viral evolution through genetic reassortment after multiple IAVs coinfect the same cell, leading to viruses harboring combinations of eight genomic segments from d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e1a6151b328050a32ee6cb40589637fd
https://doi.org/10.1073/pnas.2211098120

Rel-Dependent Immune and Central Nervous System Mechanisms Control Viral Replication and Inflammation during Mouse Herpes Simplex Encephalitis

Autor: Robert Sladek, Benoît Charbonneau, Nila Wu, Mathieu Mancini, Grégory Caignard, Angela Pearson, Anne Dumaine, Salman T. Qureshi, Steve Gerondakis, Silvia M. Vidal, Gabriel André Leiva-Torres

Publikováno v: Journal of Immunology
Journal of Immunology, Publisher : Baltimore : Williams & Wilkins, c1950-. Latest Publisher : Bethesda, MD : American Association of Immunologists, 2019, 202 (5), pp.1479-1493. ⟨10.4049/jimmunol.1800063⟩

Herpes simplex encephalitis (HSE), caused by HSV type 1 (HSV-1) infection, is an acute neuroinflammatory condition of the CNS and remains the most common type of sporadic viral encephalitis worldwide. Studies in humans have shown that susceptibility

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a37f7ddca27e633c977e52f8ed14873e
https://doi.org/10.4049/jimmunol.1800063

2,6-Diaminopurine as a highly potent corrector of UGA nonsense mutations

Autor: Catherine Leroy, Séverine Amand, Anthony Mouray, David Tulasne, Andreas E. Kulozik, Christine Bailly, Thierry Chassat, Carole Trzaska, David Hannebique, Eric Adriaenssens, Jean-Michel Saliou, Elisabeth Werkmeister, Pierre-Arthur Moreau, Eric Westhof, Evelyne Duvernois-Berthet, Yuri Motorin, Romain Guilbert, Marie-Christine Copin, Virginie Marchand, Sylvie Rebuffat, Fabrice Lejeune, Hana Benhabiles

Publikováno v: Nature Communications
Nature Communications, Nature Publishing Group, 2020, 11 (1), pp.1509. ⟨10.1038/s41467-020-15140-z⟩
Nature Communications, Vol 11, Iss 1, Pp 1-12 (2020)
Nature Communications, Nature Publishing Group, 2020, 11 (1), ⟨10.1038/s41467-020-15140-z⟩
Nature Communications, 2020, 11 (1), pp.1509. ⟨10.1038/s41467-020-15140-z⟩

Nonsense mutations cause about 10% of genetic disease cases, and no treatments are available. Nonsense mutations can be corrected by molecules with nonsense mutation readthrough activity. An extract of the mushroom Lepista inversa has recently shown

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::18c43dcc029ea3821fec01525a179f50
http://europepmc.org/articles/PMC7083880