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Quality-Score Refinement of SSU rRNA Gene Pyrosequencing Differs Across Gene Region for Environmental Samples

Due to potential sequencing errors in pyrosequencing data, species richness and diversity indices of microbial systems can be miscalculated. The “traditional” sequence refinement method is not sufficient to account for overestimations (e.g., length, primer errors, ambiguous nucleotides). Recent in s...

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Detalles Bibliográficos
Autores principales: Bowen De León, Kara, Ramsay, Bradley D., Fields, Matthew W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer-Verlag 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3391548/
https://www.ncbi.nlm.nih.gov/pubmed/22476815
http://dx.doi.org/10.1007/s00248-012-0043-9
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author Bowen De León, Kara
Ramsay, Bradley D.
Fields, Matthew W.
author_facet Bowen De León, Kara
Ramsay, Bradley D.
Fields, Matthew W.
author_sort Bowen De León, Kara
collection PubMed
description Due to potential sequencing errors in pyrosequencing data, species richness and diversity indices of microbial systems can be miscalculated. The “traditional” sequence refinement method is not sufficient to account for overestimations (e.g., length, primer errors, ambiguous nucleotides). Recent in silico and single-organism studies have revealed the importance of sequence quality scores in the estimation of ecological indices; however, this is the first study to compare quality-score stringencies across four regions of the SSU rRNA gene sequence (V1V2, V3, V4, and V6) with actual environmental samples compared directly to corresponding clone libraries produced from the same primer sets. The nucleic acid sequences determined via pyrosequencing were subjected to varying quality-score cutoffs that ranged from 25 to 32, and at each quality-score cutoff, either 10 or 15 % of the nucleotides were allowed to be below the cutoff. When species richness estimates were compared for the tested samples, the cutoff values of Q27(15%), Q30(10%), and Q32(15%) for V1V2, V4, and V6, respectively, estimated similar values as obtained with clone libraries and Sanger sequencing. The most stringent Q tested (Q32(10%)) was not enough to account for species richness inflation of the V3 region pyrosequence data. Results indicated that quality-score assessment greatly improved estimates of ecological indices for environmental samples (species richness and α-diversity) and that the effect of quality-score filtering was region-dependent. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00248-012-0043-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-33915482012-07-25 Quality-Score Refinement of SSU rRNA Gene Pyrosequencing Differs Across Gene Region for Environmental Samples Bowen De León, Kara Ramsay, Bradley D. Fields, Matthew W. Microb Ecol Methods Due to potential sequencing errors in pyrosequencing data, species richness and diversity indices of microbial systems can be miscalculated. The “traditional” sequence refinement method is not sufficient to account for overestimations (e.g., length, primer errors, ambiguous nucleotides). Recent in silico and single-organism studies have revealed the importance of sequence quality scores in the estimation of ecological indices; however, this is the first study to compare quality-score stringencies across four regions of the SSU rRNA gene sequence (V1V2, V3, V4, and V6) with actual environmental samples compared directly to corresponding clone libraries produced from the same primer sets. The nucleic acid sequences determined via pyrosequencing were subjected to varying quality-score cutoffs that ranged from 25 to 32, and at each quality-score cutoff, either 10 or 15 % of the nucleotides were allowed to be below the cutoff. When species richness estimates were compared for the tested samples, the cutoff values of Q27(15%), Q30(10%), and Q32(15%) for V1V2, V4, and V6, respectively, estimated similar values as obtained with clone libraries and Sanger sequencing. The most stringent Q tested (Q32(10%)) was not enough to account for species richness inflation of the V3 region pyrosequence data. Results indicated that quality-score assessment greatly improved estimates of ecological indices for environmental samples (species richness and α-diversity) and that the effect of quality-score filtering was region-dependent. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00248-012-0043-9) contains supplementary material, which is available to authorized users. Springer-Verlag 2012-04-05 2012 /pmc/articles/PMC3391548/ /pubmed/22476815 http://dx.doi.org/10.1007/s00248-012-0043-9 Text en © The Author(s) 2012 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Methods
Bowen De León, Kara
Ramsay, Bradley D.
Fields, Matthew W.
Quality-Score Refinement of SSU rRNA Gene Pyrosequencing Differs Across Gene Region for Environmental Samples
title Quality-Score Refinement of SSU rRNA Gene Pyrosequencing Differs Across Gene Region for Environmental Samples
title_full Quality-Score Refinement of SSU rRNA Gene Pyrosequencing Differs Across Gene Region for Environmental Samples
title_fullStr Quality-Score Refinement of SSU rRNA Gene Pyrosequencing Differs Across Gene Region for Environmental Samples
title_full_unstemmed Quality-Score Refinement of SSU rRNA Gene Pyrosequencing Differs Across Gene Region for Environmental Samples
title_short Quality-Score Refinement of SSU rRNA Gene Pyrosequencing Differs Across Gene Region for Environmental Samples
title_sort quality-score refinement of ssu rrna gene pyrosequencing differs across gene region for environmental samples
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3391548/
https://www.ncbi.nlm.nih.gov/pubmed/22476815
http://dx.doi.org/10.1007/s00248-012-0043-9
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