A Scalable and Cost‐Effective In‐Line Barcoding Strategy for Standardized <scp>16S rRNA</scp> Gene Amplicon Sequencing: Performance Evaluation and Bias Assessment

In-line barcoding offers a streamlined and scalable alternative to two-step PCR library preparation for 16S rRNA gene amplicon sequencing, enabling cost-effective, high-throughput profiling of microbial communities. Here, we tested 136 and 156 in-line barcoded primer pairs for bacterial and archaeal communities for their performance across environmental samples and a mock standard community. The primers were designed by combining widely used universal 16S rRNA gene primers with existing barcode sets from Illumina kits. The designed primer pairs produced efficient and consistent amplification with minimal dropout and no systematic taxonomic bias. Through clustering and performance-based filtering, we selected final sets of 96 pairs for both bacterial and archaeal communities that work efficiently and well together for direct further use. This in-line tagging strategy is easy to adopt with fewer processing steps and PCR-associated artefacts, allows straightforward sample tracking, and supports reliable large-scale microbiome studies. We also present a framework for evaluating barcode- or primer-induced biases. More broadly, the proposed in-line barcoding strategy can be adapted to any amplicon-sequencing application, as well as targeted sequencing, highlighting its relevance beyond 16S rRNA gene surveys. All validation datasets, open-source processing scripts, and barcode design resources are provided to promote reproducibility and community-wide adoption.

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Publication Details

Journal
Molecular Ecology Resources
Published
2026-05-01
DOI
https://doi.org/10.1111/1755-0998.70138
Primary Topic
Microbial Community Ecology and Physiology
Type
article
Field-Weighted Citation Impact
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article

A Scalable and Cost‐Effective In‐Line Barcoding Strategy for Standardized 16S rRNA Gene Amplicon Sequencing: Performance Evaluation and Bias Assessment

Lisa Jourdain, Aline Charpagne, Emmanuelle Chevalier, Julien Marquis et al.
Molecular Ecology Resources
Microbial Community Ecology and Physiology
article

A Scalable and Cost‐Effective In‐Line Barcoding Strategy for Standardized 16S rRNA Gene Amplicon Sequencing: Performance Evaluation and Bias Assessment

Lisa Jourdain, Aline Charpagne, Emmanuelle Chevalier, Julien Marquis, Wenyu Gu, Pierre Rossi, Viviane Praz, Johann Weber
article en

Abstract

In-line barcoding offers a streamlined and scalable alternative to two-step PCR library preparation for 16S rRNA gene amplicon sequencing, enabling cost-effective, high-throughput profiling of microbial communities. Here, we tested 136 and 156 in-line barcoded primer pairs for bacterial and archaeal communities for their performance across environmental samples and a mock standard community. The primers were designed by combining widely used universal 16S rRNA gene primers with existing barcode sets from Illumina kits. The designed primer pairs produced efficient and consistent amplification with minimal dropout and no systematic taxonomic bias. Through clustering and performance-based filtering, we selected final sets of 96 pairs for both bacterial and archaeal communities that work efficiently and well together for direct further use. This in-line tagging strategy is easy to adopt with fewer processing steps and PCR-associated artefacts, allows straightforward sample tracking, and supports reliable large-scale microbiome studies. We also present a framework for evaluating barcode- or primer-induced biases. More broadly, the proposed in-line barcoding strategy can be adapted to any amplicon-sequencing application, as well as targeted sequencing, highlighting its relevance beyond 16S rRNA gene surveys. All validation datasets, open-source processing scripts, and barcode design resources are provided to promote reproducibility and community-wide adoption.

Molecular Ecology ResourcesVol. 26(4)
École Polytechnique Fédérale de Lausanne (CH), University of Lausanne (CH)
Openalex Percentile: Top 4%
Microbial Community Ecology and Physiology
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