Evidence map›Paper›PMID 23431390›Full record

ArticlePloS one2013

Can abundance of protists be inferred from sequence data: a case study of foraminifera.

Alexandra A-T Weber, Jan Pawlowski

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In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

50 citing papers in PubMed.

  1. Review
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  6. Fungal diversity present in ornithogenic soils of extreme equatorial Atlantic São Pedro and São Paulo archipelago using DNA metabarcoding.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2025
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  7. Article
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  11. Cryptic fungal diversity revealed by DNA metabarcoding in historic wooden structures at Whalers Bay, Deception Island, maritime Antarctic.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2023
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  15. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Alexandra A-T WeberDepartment of Genetic and Evolution, University of Geneva, Sciences III, Genève, Switzerland.
Jan Pawlowski

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

BiomassCulture TechniquesDNA, ComplementaryDNA, ProtozoanDNA, RibosomalForaminiferaGenes, ProtozoanHigh-Throughput Nucleotide SequencingPolymorphism, Restriction Fragment LengthRibosome Subunits, SmallSequence Analysis, DNAWater MicrobiologyDNA, ComplementaryDNA, ProtozoanDNA, Ribosomal

Identifiers

PMID23431390
PMCPMC3576339

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.