Cargando…
Evaluation of different analysis pipelines for the detection of HIV-1 minority resistant variants
OBJECTIVE: Reliable detection of HIV minority resistant variants (MRVs) requires bioinformatics analysis with specific algorithms to obtain good quality alignments. The aim of this study was to analyze ultra-deep sequencing (UDS) data using different analysis pipelines. METHODS: HIV-1 protease, reve...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983569/ https://www.ncbi.nlm.nih.gov/pubmed/29856864 http://dx.doi.org/10.1371/journal.pone.0198334 |
_version_ | 1783328447390547968 |
---|---|
author | Perrier, Marine Désiré, Nathalie Storto, Alexandre Todesco, Eve Rodriguez, Christophe Bertine, Mélanie Le Hingrat, Quentin Visseaux, Benoit Calvez, Vincent Descamps, Diane Marcelin, Anne-Geneviève Charpentier, Charlotte |
author_facet | Perrier, Marine Désiré, Nathalie Storto, Alexandre Todesco, Eve Rodriguez, Christophe Bertine, Mélanie Le Hingrat, Quentin Visseaux, Benoit Calvez, Vincent Descamps, Diane Marcelin, Anne-Geneviève Charpentier, Charlotte |
author_sort | Perrier, Marine |
collection | PubMed |
description | OBJECTIVE: Reliable detection of HIV minority resistant variants (MRVs) requires bioinformatics analysis with specific algorithms to obtain good quality alignments. The aim of this study was to analyze ultra-deep sequencing (UDS) data using different analysis pipelines. METHODS: HIV-1 protease, reverse transcriptase (RT) and integrase sequences from antiretroviral-naïve patients were obtained using GS-Junior(®) (Roche) and MiSeq(®) (Illumina) platforms. MRVs were defined as variants harbouring resistance-mutation present at a frequency of 1%–20%. Reads were analyzed using different alignment algorithms: Amplicon Variant Analyzer(®), Geneious(®) compared to SmartGene(®) NGS HIV-1 module. RESULTS: 101 protease and 51 RT MRVs identified in 139 protease and 124 RT sequences generated with a GS-Junior(®) platform were analyzed using AVA(®) and SmartGene(®) software. The correlation coefficients for the MRVs were R(2) = 0.974 for protease and R(2) = 0.972 for RT. Discordances (n = 13 in protease and n = 15 in RT) mainly concerned low-level MRVs (i.e., with frequencies of 1%–2%, n = 18/28) and they were located in homopolymeric regions (n = 10/15). Geneious(®) and SmartGene(®) software were used to analyze 143 protease, 45 RT and 26 integrase MRVs identified in 172 protease, 69 RT, and 72 integrase sequences generated with a MiSeq(®) platform. The correlation coefficients for the MRVs were R(2) = 0.987 for protease, R(2) = 0.995 for RT and R(2) = 0.993 for integrase. Discordances (n = 9 in protease, n = 3 in RT, and n = 3 in integrase) mainly concerned low-level MRVs (n = 13/15). CONCLUSION: We found an excellent correlation between the various UDS analysis pipelines that we tested. However, our results indicate that specific attention should be paid to low-level MRVs, for which the use of two different analysis pipelines and visual inspection of sequences alignments might be beneficial. Thus, our results argue for use of a 2% threshold for MRV detection, rather than the 1% threshold, to minimize misalignments and time-consuming sight reading steps essential to ensure accurate results for MRV frequencies below 2%. |
format | Online Article Text |
id | pubmed-5983569 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-59835692018-06-16 Evaluation of different analysis pipelines for the detection of HIV-1 minority resistant variants Perrier, Marine Désiré, Nathalie Storto, Alexandre Todesco, Eve Rodriguez, Christophe Bertine, Mélanie Le Hingrat, Quentin Visseaux, Benoit Calvez, Vincent Descamps, Diane Marcelin, Anne-Geneviève Charpentier, Charlotte PLoS One Research Article OBJECTIVE: Reliable detection of HIV minority resistant variants (MRVs) requires bioinformatics analysis with specific algorithms to obtain good quality alignments. The aim of this study was to analyze ultra-deep sequencing (UDS) data using different analysis pipelines. METHODS: HIV-1 protease, reverse transcriptase (RT) and integrase sequences from antiretroviral-naïve patients were obtained using GS-Junior(®) (Roche) and MiSeq(®) (Illumina) platforms. MRVs were defined as variants harbouring resistance-mutation present at a frequency of 1%–20%. Reads were analyzed using different alignment algorithms: Amplicon Variant Analyzer(®), Geneious(®) compared to SmartGene(®) NGS HIV-1 module. RESULTS: 101 protease and 51 RT MRVs identified in 139 protease and 124 RT sequences generated with a GS-Junior(®) platform were analyzed using AVA(®) and SmartGene(®) software. The correlation coefficients for the MRVs were R(2) = 0.974 for protease and R(2) = 0.972 for RT. Discordances (n = 13 in protease and n = 15 in RT) mainly concerned low-level MRVs (i.e., with frequencies of 1%–2%, n = 18/28) and they were located in homopolymeric regions (n = 10/15). Geneious(®) and SmartGene(®) software were used to analyze 143 protease, 45 RT and 26 integrase MRVs identified in 172 protease, 69 RT, and 72 integrase sequences generated with a MiSeq(®) platform. The correlation coefficients for the MRVs were R(2) = 0.987 for protease, R(2) = 0.995 for RT and R(2) = 0.993 for integrase. Discordances (n = 9 in protease, n = 3 in RT, and n = 3 in integrase) mainly concerned low-level MRVs (n = 13/15). CONCLUSION: We found an excellent correlation between the various UDS analysis pipelines that we tested. However, our results indicate that specific attention should be paid to low-level MRVs, for which the use of two different analysis pipelines and visual inspection of sequences alignments might be beneficial. Thus, our results argue for use of a 2% threshold for MRV detection, rather than the 1% threshold, to minimize misalignments and time-consuming sight reading steps essential to ensure accurate results for MRV frequencies below 2%. Public Library of Science 2018-06-01 /pmc/articles/PMC5983569/ /pubmed/29856864 http://dx.doi.org/10.1371/journal.pone.0198334 Text en © 2018 Perrier et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Perrier, Marine Désiré, Nathalie Storto, Alexandre Todesco, Eve Rodriguez, Christophe Bertine, Mélanie Le Hingrat, Quentin Visseaux, Benoit Calvez, Vincent Descamps, Diane Marcelin, Anne-Geneviève Charpentier, Charlotte Evaluation of different analysis pipelines for the detection of HIV-1 minority resistant variants |
title | Evaluation of different analysis pipelines for the detection of HIV-1 minority resistant variants |
title_full | Evaluation of different analysis pipelines for the detection of HIV-1 minority resistant variants |
title_fullStr | Evaluation of different analysis pipelines for the detection of HIV-1 minority resistant variants |
title_full_unstemmed | Evaluation of different analysis pipelines for the detection of HIV-1 minority resistant variants |
title_short | Evaluation of different analysis pipelines for the detection of HIV-1 minority resistant variants |
title_sort | evaluation of different analysis pipelines for the detection of hiv-1 minority resistant variants |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983569/ https://www.ncbi.nlm.nih.gov/pubmed/29856864 http://dx.doi.org/10.1371/journal.pone.0198334 |
work_keys_str_mv | AT perriermarine evaluationofdifferentanalysispipelinesforthedetectionofhiv1minorityresistantvariants AT desirenathalie evaluationofdifferentanalysispipelinesforthedetectionofhiv1minorityresistantvariants AT stortoalexandre evaluationofdifferentanalysispipelinesforthedetectionofhiv1minorityresistantvariants AT todescoeve evaluationofdifferentanalysispipelinesforthedetectionofhiv1minorityresistantvariants AT rodriguezchristophe evaluationofdifferentanalysispipelinesforthedetectionofhiv1minorityresistantvariants AT bertinemelanie evaluationofdifferentanalysispipelinesforthedetectionofhiv1minorityresistantvariants AT lehingratquentin evaluationofdifferentanalysispipelinesforthedetectionofhiv1minorityresistantvariants AT visseauxbenoit evaluationofdifferentanalysispipelinesforthedetectionofhiv1minorityresistantvariants AT calvezvincent evaluationofdifferentanalysispipelinesforthedetectionofhiv1minorityresistantvariants AT descampsdiane evaluationofdifferentanalysispipelinesforthedetectionofhiv1minorityresistantvariants AT marcelinannegenevieve evaluationofdifferentanalysispipelinesforthedetectionofhiv1minorityresistantvariants AT charpentiercharlotte evaluationofdifferentanalysispipelinesforthedetectionofhiv1minorityresistantvariants |