Literature DB >> 29802418

Necessary Sequencing Depth and Clustering Method to Obtain Relatively Stable Diversity Patterns in Studying Fish Gut Microbiota.

Fanshu Xiao1, Yuhe Yu2, Jinjin Li3, Philippe Juneau4, Qingyun Yan5.   

Abstract

The 16S rRNA gene is one of the most commonly used molecular markers for estimating bacterial diversity during the past decades. However, there is no consistency about the sequencing depth (from thousand to millions of sequences per sample), and the clustering methods used to generate OTUs may also be different among studies. These inconsistent premises make effective comparisons among studies difficult or unreliable. This study aims to examine the necessary sequencing depth and clustering method that would be needed to ensure a stable diversity patterns for studying fish gut microbiota. A total number of 42 samples dataset of Siniperca chuatsi (carnivorous fish) gut microbiota were used to test how the sequencing depth and clustering may affect the alpha and beta diversity patterns of fish intestinal microbiota. Interestingly, we found that the sequencing depth (resampling 1000-11,000 per sample) and the clustering methods (UPARSE and UCLUST) did not bias the estimates of the diversity patterns during the fish development from larva to adult. Although we should acknowledge that a suitable sequencing depth may differ case by case, our finding indicates that a shallow sequencing such as 1000 sequences per sample may be also enough to reflect the general diversity patterns of fish gut microbiota. However, we have shown in the present study that strict pre-processing of the original sequences is required to ensure reliable results. This study provides evidences to help making a strong scientific choice of the sequencing depth and clustering method for future studies on fish gut microbiota patterns, but at the same time reducing as much as possible the costs related to the analysis.

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Year:  2018        PMID: 29802418     DOI: 10.1007/s00284-018-1516-y

Source DB:  PubMed          Journal:  Curr Microbiol        ISSN: 0343-8651            Impact factor:   2.188


  24 in total

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2.  UPARSE: highly accurate OTU sequences from microbial amplicon reads.

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3.  Assembling large genomes with single-molecule sequencing and locality-sensitive hashing.

Authors:  Konstantin Berlin; Sergey Koren; Chen-Shan Chin; James P Drake; Jane M Landolin; Adam M Phillippy
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4.  Cross-biome metagenomic analyses of soil microbial communities and their functional attributes.

Authors:  Noah Fierer; Jonathan W Leff; Byron J Adams; Uffe N Nielsen; Scott Thomas Bates; Christian L Lauber; Sarah Owens; Jack A Gilbert; Diana H Wall; J Gregory Caporaso
Journal:  Proc Natl Acad Sci U S A       Date:  2012-12-10       Impact factor: 11.205

5.  Accuracy of protist diversity assessments: morphology compared with cloning and direct pyrosequencing of 18S rRNA genes and ITS regions using the conspicuous tintinnid ciliates as a case study.

Authors:  Charles Bachy; John R Dolan; Purificación López-García; Philippe Deschamps; David Moreira
Journal:  ISME J       Date:  2012-10-04       Impact factor: 10.302

6.  Robust estimation of microbial diversity in theory and in practice.

Authors:  Bart Haegeman; Jérôme Hamelin; John Moriarty; Peter Neal; Jonathan Dushoff; Joshua S Weitz
Journal:  ISME J       Date:  2013-02-14       Impact factor: 10.302

7.  Unraveling the outcome of 16S rDNA-based taxonomy analysis through mock data and simulations.

Authors:  Ali May; Sanne Abeln; Wim Crielaard; Jaap Heringa; Bernd W Brandt
Journal:  Bioinformatics       Date:  2014-02-10       Impact factor: 6.937

8.  Phasing amplicon sequencing on Illumina Miseq for robust environmental microbial community analysis.

Authors:  Liyou Wu; Chongqing Wen; Yujia Qin; Huaqun Yin; Qichao Tu; Joy D Van Nostrand; Tong Yuan; Menting Yuan; Ye Deng; Jizhong Zhou
Journal:  BMC Microbiol       Date:  2015-06-19       Impact factor: 3.605

9.  Individuals' diet diversity influences gut microbial diversity in two freshwater fish (threespine stickleback and Eurasian perch).

Authors:  Daniel I Bolnick; Lisa K Snowberg; Philipp E Hirsch; Christian L Lauber; Rob Knight; J Gregory Caporaso; Richard Svanbäck
Journal:  Ecol Lett       Date:  2014-05-22       Impact factor: 9.492

Review 10.  The sequence of sequencers: The history of sequencing DNA.

Authors:  James M Heather; Benjamin Chain
Journal:  Genomics       Date:  2015-11-10       Impact factor: 5.736

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