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Can Abundance of Protists Be Inferred from Sequence Data: A Case Study of Foraminifera

Protists are key players in microbial communities, yet our understanding of their role in ecosystem functioning is seriously impeded by difficulties in identification of protistan species and their quantification. Current microscopy-based methods used for determining the abundance of protists are te...

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Autores principales: Weber, Alexandra A-T., Pawlowski, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3576339/
https://www.ncbi.nlm.nih.gov/pubmed/23431390
http://dx.doi.org/10.1371/journal.pone.0056739
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author Weber, Alexandra A-T.
Pawlowski, Jan
author_facet Weber, Alexandra A-T.
Pawlowski, Jan
author_sort Weber, Alexandra A-T.
collection PubMed
description Protists are key players in microbial communities, yet our understanding of their role in ecosystem functioning is seriously impeded by difficulties in identification of protistan species and their quantification. Current microscopy-based methods used for determining the abundance of protists are tedious and often show a low taxonomic resolution. Recent development of next-generation sequencing technologies offered a very powerful tool for studying the richness of protistan communities. Still, the relationship between abundance of species and number of sequences remains subjected to various technical and biological biases. Here, we test the impact of some of these biological biases on sequence abundance of SSU rRNA gene in foraminifera. First, we quantified the rDNA copy number and rRNA expression level of three species of foraminifera by qPCR. Then, we prepared five mock communities with these species, two in equal proportions and three with one species ten times more abundant. The libraries of rDNA and cDNA of the mock communities were constructed, Sanger sequenced and the sequence abundance was calculated. The initial species proportions were compared to the raw sequence proportions as well as to the sequence abundance normalized by rDNA copy number and rRNA expression level per species. Our results showed that without normalization, all sequence data differed significantly from the initial proportions. After normalization, the congruence between the number of sequences and number of specimens was much better. We conclude that without normalization, species abundance determination based on sequence data was not possible because of the effect of biological biases. Nevertheless, by taking into account the variation of rDNA copy number and rRNA expression level we were able to infer species abundance, suggesting that our approach can be successful in controlled conditions.
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spelling pubmed-35763392013-02-21 Can Abundance of Protists Be Inferred from Sequence Data: A Case Study of Foraminifera Weber, Alexandra A-T. Pawlowski, Jan PLoS One Research Article Protists are key players in microbial communities, yet our understanding of their role in ecosystem functioning is seriously impeded by difficulties in identification of protistan species and their quantification. Current microscopy-based methods used for determining the abundance of protists are tedious and often show a low taxonomic resolution. Recent development of next-generation sequencing technologies offered a very powerful tool for studying the richness of protistan communities. Still, the relationship between abundance of species and number of sequences remains subjected to various technical and biological biases. Here, we test the impact of some of these biological biases on sequence abundance of SSU rRNA gene in foraminifera. First, we quantified the rDNA copy number and rRNA expression level of three species of foraminifera by qPCR. Then, we prepared five mock communities with these species, two in equal proportions and three with one species ten times more abundant. The libraries of rDNA and cDNA of the mock communities were constructed, Sanger sequenced and the sequence abundance was calculated. The initial species proportions were compared to the raw sequence proportions as well as to the sequence abundance normalized by rDNA copy number and rRNA expression level per species. Our results showed that without normalization, all sequence data differed significantly from the initial proportions. After normalization, the congruence between the number of sequences and number of specimens was much better. We conclude that without normalization, species abundance determination based on sequence data was not possible because of the effect of biological biases. Nevertheless, by taking into account the variation of rDNA copy number and rRNA expression level we were able to infer species abundance, suggesting that our approach can be successful in controlled conditions. Public Library of Science 2013-02-19 /pmc/articles/PMC3576339/ /pubmed/23431390 http://dx.doi.org/10.1371/journal.pone.0056739 Text en © 2013 Weber, Pawlowski http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Weber, Alexandra A-T.
Pawlowski, Jan
Can Abundance of Protists Be Inferred from Sequence Data: A Case Study of Foraminifera
title Can Abundance of Protists Be Inferred from Sequence Data: A Case Study of Foraminifera
title_full Can Abundance of Protists Be Inferred from Sequence Data: A Case Study of Foraminifera
title_fullStr Can Abundance of Protists Be Inferred from Sequence Data: A Case Study of Foraminifera
title_full_unstemmed Can Abundance of Protists Be Inferred from Sequence Data: A Case Study of Foraminifera
title_short Can Abundance of Protists Be Inferred from Sequence Data: A Case Study of Foraminifera
title_sort can abundance of protists be inferred from sequence data: a case study of foraminifera
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3576339/
https://www.ncbi.nlm.nih.gov/pubmed/23431390
http://dx.doi.org/10.1371/journal.pone.0056739
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