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RNA-seq03:21

RNA-seq

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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: Oct 28, 2025

A Method for Targeted 16S Sequencing of Human Milk Samples
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Simple mapping-based quantification of a mock microbial community using total RNA-seq data.

Shigeharu Moriya1

  • 1Environmental Metabolic Analysis Research Team, Center for Sustainable Resource Science, RIKEN Institute, Yokohama, Kanagawa, Japan.

Plos One
|July 16, 2021
PubMed
Summary
This summary is machine-generated.

Culture-independent microbial community analysis is crucial. Total RNA sequencing offers a bias-free method for quantifying microbial structures, outperforming traditional amplicon sequencing in accuracy.

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Genomics

Background:

  • Most environmental microbes are unculturable, necessitating culture-independent methods for community analysis.
  • Traditional amplicon sequencing (e.g., 16S rRNA) is prone to PCR-induced bias and requires specific primers for different microbial domains.
  • Total RNA sequencing provides a comprehensive approach to analyze entire microbial communities, including bacteria, archaea, and eukaryotes, without PCR bias.

Purpose of the Study:

  • To develop and evaluate a mapping-based total RNA sequencing (RNA-seq) analysis for quantitative microbial community structure determination.
  • To compare the quantitative accuracy of the developed total RNA-seq method against conventional amplicon sequencing.

Main Methods:

  • Developed a novel mapping-based analysis pipeline for total RNA sequences.
  • Processed sequences from a commercially available mock microbial community (ATCC MSA-2003).
  • Filtered reads to isolate small subunit ribosomal RNA (ssrRNA) and mapped them to assembled contigs using optimized strategies (low complexity removal, paired-in mode sorting, BLAST+/vsearch for taxonomy).

Main Results:

  • The developed total RNA-seq method accurately quantified microbial community members, achieving a median relative abundance of approximately 10% for ten members.
  • Optimized analysis strategies, including low complexity sequence removal and specific ssrRNA sorting, significantly improved quantitative outcomes.
  • Total RNA-seq demonstrated superior quantitative performance compared to standard amplicon sequencing, which yielded much lower abundance percentages.

Conclusions:

  • Total RNA sequencing is a powerful and accurate tool for quantitative microbial community structure analysis.
  • This method overcomes limitations of PCR-based approaches, offering a more reliable assessment of microbial diversity.
  • Total RNA-seq is not restricted to gene expression profiling and can be effectively utilized for microbiome composition studies.