Inferring the Clonal Structure of Viral Populations from Time Series Sequencing.
RNA virus populations will undergo processes of mutation and selection resulting in a mixed population of viral particles. High throughput sequencing of a viral population subsequently contains a mixed signal of the underlying clones. We would like to identify the underlying evolutionary structures....
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2015-11-01
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| Series: | PLoS Computational Biology |
| Online Access: | http://europepmc.org/articles/PMC4646700?pdf=render |
| _version_ | 1818940435754647552 |
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| author | Donatien F Chedom Pablo R Murcia Chris D Greenman |
| author_facet | Donatien F Chedom Pablo R Murcia Chris D Greenman |
| author_sort | Donatien F Chedom |
| collection | DOAJ |
| description | RNA virus populations will undergo processes of mutation and selection resulting in a mixed population of viral particles. High throughput sequencing of a viral population subsequently contains a mixed signal of the underlying clones. We would like to identify the underlying evolutionary structures. We utilize two sources of information to attempt this; within segment linkage information, and mutation prevalence. We demonstrate that clone haplotypes, their prevalence, and maximum parsimony reticulate evolutionary structures can be identified, although the solutions may not be unique, even for complete sets of information. This is applied to a chain of influenza infection, where we infer evolutionary structures, including reassortment, and demonstrate some of the difficulties of interpretation that arise from deep sequencing due to artifacts such as template switching during PCR amplification. |
| first_indexed | 2024-12-20T06:39:36Z |
| format | Article |
| id | doaj.art-089e93c351964aaca7a8ddf8b122f21a |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-20T06:39:36Z |
| publishDate | 2015-11-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-089e93c351964aaca7a8ddf8b122f21a2022-12-21T19:49:54ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582015-11-011111e100434410.1371/journal.pcbi.1004344Inferring the Clonal Structure of Viral Populations from Time Series Sequencing.Donatien F ChedomPablo R MurciaChris D GreenmanRNA virus populations will undergo processes of mutation and selection resulting in a mixed population of viral particles. High throughput sequencing of a viral population subsequently contains a mixed signal of the underlying clones. We would like to identify the underlying evolutionary structures. We utilize two sources of information to attempt this; within segment linkage information, and mutation prevalence. We demonstrate that clone haplotypes, their prevalence, and maximum parsimony reticulate evolutionary structures can be identified, although the solutions may not be unique, even for complete sets of information. This is applied to a chain of influenza infection, where we infer evolutionary structures, including reassortment, and demonstrate some of the difficulties of interpretation that arise from deep sequencing due to artifacts such as template switching during PCR amplification.http://europepmc.org/articles/PMC4646700?pdf=render |
| spellingShingle | Donatien F Chedom Pablo R Murcia Chris D Greenman Inferring the Clonal Structure of Viral Populations from Time Series Sequencing. PLoS Computational Biology |
| title | Inferring the Clonal Structure of Viral Populations from Time Series Sequencing. |
| title_full | Inferring the Clonal Structure of Viral Populations from Time Series Sequencing. |
| title_fullStr | Inferring the Clonal Structure of Viral Populations from Time Series Sequencing. |
| title_full_unstemmed | Inferring the Clonal Structure of Viral Populations from Time Series Sequencing. |
| title_short | Inferring the Clonal Structure of Viral Populations from Time Series Sequencing. |
| title_sort | inferring the clonal structure of viral populations from time series sequencing |
| url | http://europepmc.org/articles/PMC4646700?pdf=render |
| work_keys_str_mv | AT donatienfchedom inferringtheclonalstructureofviralpopulationsfromtimeseriessequencing AT pablormurcia inferringtheclonalstructureofviralpopulationsfromtimeseriessequencing AT chrisdgreenman inferringtheclonalstructureofviralpopulationsfromtimeseriessequencing |