QIIME allows analysis of high-throughput community sequencing data

Caporaso, J. Gregory; Kuczynski, Justin; Stombaugh, Jesse; Bittinger, Kyle; Bushman, Frederic D.; Costello, Elizabeth K.; Fierer, Noah; Peña, Antonio González; Goodrich, Julia K.; Gordon, Jeffrey I.; Huttley, Gavin A.; Kelley, Scott T.; Knights, Dan; Koenig, Jeremy E.; Ley, Ruth E.; Lozupone, Catherine; McDonald, Daniel; Muegge, Brian D.; Pirrung, Meg; Reeder, Jens; Sevinsky, Joel; Turnbaugh, Peter J.; Walters, William A.; Widmann, Jeremy; Yatsunenko, Tanya; Zaneveld, Jesse; Knight, Rob

doi:10.1038/nmeth.f.303

Cited by 30,732 publications

(22,913 citation statements)

References 6 publications

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“…Differentiation among collection months for each metabarcoding marker was compared using Bray–Curtis distance based on a rarefied OTU table and visualized using principle coordinate analysis plots generated with QIIME v1.8.0 (beta_diversity_through_plots.py, Caporaso et al., 2010), with strength and significance of groupings assessed using the Adonis method (compare_categories.py, 999 permutations). The taxa or OTUs contributing to the difference between months were identified using SIMPER analysis based on the fourth‐root‐transformed OTU tables and morphology‐based counts with the vegan package (Oksanen et al., 2015) in R version 3.2.1 (R Core Team 2015).…”

Section: Methodsmentioning

confidence: 99%

Effect of marker choice and thermal cycling protocol on zooplankton DNA metabarcoding studies

Clarke

Beard

Swadling

et al. 2017

Ecology and Evolution

169

193

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DNA metabarcoding is a promising approach for rapidly surveying biodiversity and is likely to become an important tool for measuring ecosystem responses to environmental change. Metabarcoding markers need sufficient taxonomic coverage to detect groups of interest, sufficient sequence divergence to resolve species, and will ideally indicate relative abundance of taxa present. We characterized zooplankton assemblages with three different metabarcoding markers (nuclear 18S rDNA, mitochondrial COI, and mitochondrial 16S rDNA) to compare their performance in terms of taxonomic coverage, taxonomic resolution, and correspondence between morphology‐ and DNA‐based identification. COI amplicons sequenced on separate runs showed that operational taxonomic units representing >0.1% of reads per sample were highly reproducible, although slightly more taxa were detected using a lower annealing temperature. Mitochondrial COI and nuclear 18S showed similar taxonomic coverage across zooplankton phyla. However, mitochondrial COI resolved up to threefold more taxa to species compared to 18S. All markers revealed similar patterns of beta‐diversity, although different taxa were identified as the greatest contributors to these patterns for 18S. For calanoid copepod families, all markers displayed a positive relationship between biomass and sequence reads, although the relationship was typically strongest for 18S. The use of COI for metabarcoding has been questioned due to lack of conserved primer‐binding sites. However, our results show the taxonomic coverage and resolution provided by degenerate COI primers, combined with a comparatively well‐developed reference sequence database, make them valuable metabarcoding markers for biodiversity assessment.

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Section: Methodsmentioning

confidence: 99%

Effect of marker choice and thermal cycling protocol on zooplankton DNA metabarcoding studies

Clarke

Beard

Swadling

et al. 2017

Ecology and Evolution

169

193

View full text Add to dashboard Cite

show abstract

“…Raw sequence data were screened, trimmed, denoised, chimera‐depleted and filtered using QIIME pipeline version 1.8.0 31. Sequence data were uploaded into the Sequence Read Archive of the National Centre for Biotechnology Information (NCBI), GenBank database, under submission number SRP 101454.…”

Section: Methodsmentioning

confidence: 99%

Effect of an extruded animal protein‐free diet on fecal microbiota of dogs with food‐responsive enteropathy

Bresciani

Minamoto

Suchodolski

et al. 2018

Veterinary Internal Medicne

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BackgroundDietary interventions are thought to modify gut microbial communities in healthy individuals. In dogs with chronic enteropathies, resolution of dysbiosis, along with remission of clinical signs, is expected with treatment.Hypothesis/ObjectiveTo evaluate changes in the fecal microbiota in dogs with food‐responsive chronic enteropathy (FRE) and in healthy control (HC) dogs before and after an elimination dietary trial with an animal protein‐free diet (APFD).AnimalsDogs with FRE (n = 10) and HC (n = 14).MethodsDogs were fed the APFD for 60 days. Fecal microbiota was analyzed by Illumina 16S rRNA sequencing and quantitative polymerase chain reaction (PCR).ResultsA significantly lower bacterial alpha‐diversity was observed in dogs with FRE compared with HC dogs at baseline, and compared with FRE dogs after the trial. Distinct microbial communities were observed in dogs with FRE at baseline compared with HC dogs at baseline and compared with dogs with FRE after the trial. Microbial communities still were different in FRE dogs after the trial compared with HC dogs at baseline. In HC dogs, the fecal microbiota did not show a significant modification after administration of the APFD.Conclusion and Clinical ImportanceOur results suggest that, in FRE dogs, treatment with the APFD led to a partial recovery of the fecal microbiota by significantly increasing microbiota richness, which was significantly closer to a healthy microbiota after the treatment. In contrast, no changes were detected in the fecal microbiota of HC dogs fed the same APFD.

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“…For all the procedures described in this section, we used the Quantitative Insights Into Microbial Ecology (QIIME, Caporaso, Kuczynski et al., 2010) pipeline v1.9.1. We clustered operational taxonomic units (OTUs) using the uclust algorithm (Edgar, 2010) at a 97% similarity threshold and other parameters set to default.…”

Section: Methodsmentioning

confidence: 99%

Gut microflora may facilitate adaptation to anthropic habitat: A comparative study in Rattus

Varudkar

Ramakrishnan

2018

Ecology and Evolution

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Anthropophilic species (“commensal” species) that are completely dependent upon anthropic habitats experience different selective pressures particularly in terms of food than their noncommensal counterparts. Using a next‐generation sequencing approach, we characterized and compared the gut microflora community of 53 commensal Rattus rattus and 59 noncommensal Rattus satarae captured in 10 locations in the Western Ghats, India. We observed that, while species identity was important in characterizing the microflora communities of the two Rattus hosts, environmental factors also had a significant effect. While there was significant geographic variation in the microflora of the noncommensal R. satarae, there was no effect of geographic distance on gut microflora of the commensal R. rattus. Interestingly, host genetic distance did not significantly influence the community in either Rattus hosts. Collectively, these results indicate that a shift in habitat is likely to result in a change in the gut microflora community and imply that the gut microflora is a complex trait, influenced by various parameters in different habitats.

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QIIME allows analysis of high-throughput community sequencing data

Cited by 30,732 publications

References 6 publications

Effect of marker choice and thermal cycling protocol on zooplankton DNA metabarcoding studies

Effect of marker choice and thermal cycling protocol on zooplankton DNA metabarcoding studies

Effect of an extruded animal protein‐free diet on fecal microbiota of dogs with food‐responsive enteropathy

Gut microflora may facilitate adaptation to anthropic habitat: A comparative study in Rattus

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