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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Updated: Apr 17, 2026

Efficient Nucleic Acid Extraction and 16S rRNA Gene Sequencing for Bacterial Community Characterization

Efficient Nucleic Acid Extraction and 16S rRNA Gene Sequencing for Bacterial Community Characterization

Published on: April 14, 2016

Accurate multiplexing and filtering for high-throughput amplicon-sequencing.

Philippe Esling¹, Franck Lejzerowicz², Jan Pawlowski²

¹Department of Genetics and Evolution, University of Geneva, Sciences 3, 30, Quai Ernest Ansermet, CH-1211 Geneva 4, Switzerland IRCAM, UMR 9912, Université Pierre et Marie Curie, Paris, France philippe.esling@unige.ch.

Nucleic Acids Research

|February 19, 2015

Summary

This summary is machine-generated.

High-throughput sequencing (HTS) mistagging contaminates amplicon libraries, skewing diversity analyses. A new method using Latin Square Designs and PCR replicates accurately filters these critical errors, improving HTS data reliability.

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Area of Science:

Molecular Biology
Bioinformatics
Genomics

Background:

Multiplexing samples using tag sequences in PCR primers is standard for high-throughput sequencing (HTS).
This technique is crucial for diversity analyses in fields like microbial ecology and biomedical diagnostics.
A significant challenge is sample sequence cross-contamination due to tag switching, known as mistagging.

Purpose of the Study:

To quantify the prevalence and impact of mistagging in amplicon library preparation for HTS.
To evaluate different multiplexing designs for their effectiveness in detecting and mitigating mistagging.
To develop a robust method for filtering mistags and recovering accurate community composition in HTS data.

Main Methods:

Sequencing of seven amplicon libraries prepared with varied multiplexing strategies.
Analysis of mistag prevalence, including critical mistags, in single- and double-tagging designs.
Implementation of Latin Square Designs for optimized mistag detection and distribution analysis.
Integration of PCR replicates with Latin Square Designs to filter mistags.

Main Results:

Up to 28.2% of unique sequences in single- or saturated double-tagging libraries were identified as critical, undetectable mistags.
Latin Square Designs significantly improved the detection and understanding of mistag distribution across samples.
The proposed method, incorporating PCR replicates, successfully filtered critical mistags and accurately reconstructed mock community compositions.

Conclusions:

Mistagging poses a substantial threat to the accuracy of HTS-based diversity analyses.
Latin Square Designs offer a superior strategy for managing mistagging in multiplexed amplicon sequencing.
The developed parameter-free, data-driven approach enhances the accuracy and reproducibility of HTS data, leading to more reliable interpretations.