Evidence map›Paper›PMID 40894776›Full record

ArticlebioRxiv : the preprint server for biology2025

Comparison of iSeq and Miseq in 16S rRNA sequencing-based human gut microbiome analysis.

Yanling Wang, Vin Tangpricha, Andrew Gewirtz

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Yanling WangCenter for Inflammation, Immunity, & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, Georgia.
Vin TangprichaDivision of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia.
Andrew GewirtzCenter for Inflammation, Immunity, & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, Georgia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Illumina's MiSeq platform is a common approach in 16S-based microbiome analysis. Such usage is self-perpetuating in that many studies seek to employ widely used approaches to facilitate comparison of their results to existing literature. Yet, a range of factors, including cost and equipment availability can necessitate alternate approaches. For example, use of a Nano kit, lowers reagent costs by over 60% while others may only have access to entry-level sequencers such as Illumina's iSeq. The extent to which these approaches would impact results and subsequently conclusions is unknown. Attempting to address this question from the literature is complicated in that various studies not only use distinct cohorts but also differ in the reagents/methodologies to used to isolate DNA and generate sequencing libraries. Hence, we sequenced a single 16S rRNA gene amplicon library derived from 60 fecal samples, collected during a dietary supplement intervention study via MiSeq, MiseqNano, and iSeq. We evaluated platform performance by several key measurements: alpha diversity, beta diversity, taxonomic composition, and differential taxonomic abundance analysis. We found that iSeq outperformed MiSeq-Nano in alpha diversity and differential abundance detection, while MiSeq-Nano provided better taxonomic resolution than iSeq. Most importantly, all platforms showed similar core biological patterns in alpha and beta diversity and overall taxonomic composition. Thus, MiSeq, MiseqNano, and iSeq are likely to yield the same biological conclusions although specific questions and logistical consideration may favor one of these approaches.

Identifiers

PMID40894776
PMCPMC12393557

What OpenQuestion holds

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LicenceCC BY-ND
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Registered trials

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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.