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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: Sep 20, 2025

A Method for Targeted 16S Sequencing of Human Milk Samples

A Method for Targeted 16S Sequencing of Human Milk Samples

Published on: March 23, 2018

Marine microbial mock communities for validating rRNA gene amplicon sequencing.

Robert H Lampe^1,2, Ariel J Rabines^1,2, Bryce A Ellman^1,2

¹Integrative Oceanography Division, Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA.

Microbiology Resource Announcements

|May 30, 2025

Summary

Defined mixtures of DNA, called mock communities, are presented for microbial research. These tools aid in validating amplicon sequencing methods for marine microorganisms by detecting errors.

Keywords:

16S 18S amplicon sequencing marine microbiology metabarcoding rRNA

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Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

Published on: August 29, 2014

Area of Science:

Microbiology
Molecular Biology
Bioinformatics

Background:

Mock communities are essential for validating molecular methods.
Established mock communities often utilize 16S and 18S rRNA gene sequences.
Diverse microbial communities are crucial for comprehensive method testing.

Purpose of the Study:

To present novel mock communities for microbial research.
To provide standardized controls for amplicon sequencing.
To facilitate the detection of biases and errors in sequencing runs.

Main Methods:

Utilizing previously published 16S and 18S rRNA gene sequences.
Creating defined mixtures of DNA from diverse marine microorganisms.
Implementing these mock communities as controls in amplicon sequencing workflows.

Main Results:

Demonstrated the utility of mock communities in identifying sequencing biases.
Validated the effectiveness of the presented mock communities for quality control.
Enabled the detection of aberrant sequencing runs.

Conclusions:

The presented mock communities serve as valuable tools for methods development and validation.
These controls enhance the reliability and accuracy of amplicon sequencing data.
Consistent use of such mock communities will improve the standardization of microbial community analysis.