Confident and unbiased transcript analysis

Study microbial transcriptomes and metatranscriptomes with next-generation RNA-Seq

Microbial Transcriptomics

Microbial transcriptome and metatranscriptome information is important for predicting resistance to specific antibiotics, understanding host-pathogen immune interactions, quantifying gene expression changes, and tracking disease progression. Next-generation RNA sequencing (RNA-Seq) of bacteria, viruses, and other microbes has become a standard method for analyzing transcriptome and metatranscriptome information.

The transcriptome is the comprehensive set of RNAs encoded by an organism's genome. Metatranscriptomes encompass all RNAs encoded by a group of organisms in a complex sample.

Bacterial, viral, and other microbial RNA-Seq experiments enable annotation and quantification of comprehensive microbial transcripts. Cellular RNA is extracted and converted to cDNA, which is used to prepare sequencing libraries. Sequence reads are then mapped back to the reference genome, providing qualitative information on features such as exon junctions and splicing sites, as well as quantitative transcript data that can be compared across many experimental sets.

Unlike hybridization-based methods such as microarrays, RNA-Seq enables unbiased strand-specific identification of common and novel transcripts. A wide dynamic range enables confident identification of both high and low expressors in a single bacterial, viral, or other microbial RNA-Seq experiment. Multiple samples can be processed at once with a streamlined workflow suitable for automation.

There are multiple ways to perform these experiments, but these are some suggested products for each step of the workflow.

Click on the below to view products for each workflow step.

QuickExtract RNA Extraction Kit

A simple method for extracting RNA for adherent and suspension cells.

Note: If using the TruSeq RNA library prep kit, you will NOT need to extract RNA and transcribe to cDNA. If you use an RNA extraction kit, you will need to generate dsDNA templates for use with Nextera XT.

MasterPure Complete DNA and RNA Purification Kit

Simultaneous purification of DNA, or RNA for many applications, including genomic library preparation.

TruSeq Stranded Total RNA Library Prep Kit

Streamlined, cost-efficient, and scalable solution for total RNA analysis.

Note: If you use a TruSeq RNA library prep kit, you will not need to extract RNA and transcribe to cDNA.

Nextera XT Library Prep Kit

Prepare sequencing ready libraries of bacteria, viruses, and other microbes to analyze transcriptome and metatranscriptome information.

Note: If you use an RNA extraction kit, you will need to generate dsDNA.

Desktop Sequencing Systems

MiSeq System

Speed, accuracy and simplicity for far reaching applications in microbiology.

MiSeq v3 Reagents Kits

Improved chemistry to increase cluster density and read length. Enables up to 15 Gb of output.

MiSeq v2 Reagents Kits

Ideal for sequencing microbial transcripts in less than 6 hours. Micro and nano formats available for low-throughput applications.

NextSeq 550 System

Flexible desktop sequencer for exome, transcriptome, and whole-genome sequencing.

NextSeq 500/550 v2 Kits

Enhanced clustering chemistry yields even higher data quality. Provides 130 or 400 million reads and up to 120 Gb output per run.

High-Throughput Sequencing Systems
Power for high-throughput microbial transcriptomics and flexibility to scale based on your project or workflow needs.

HiSeq 4000 System

High throughput and low cost for production-scale genomics.

HiSeq 3000/4000 SBS Kit and PE Cluster Kit

Leverage patterned flow cell technology to generate up to 1500 Gb (1.5 Tb) of output per dual flow cell run.

BaseSpace Apps for transcript profiling

RNA-Seq Alignment

Performs read mapping, FPKM estimation, novel transcript assembly, and variant calling.

Cufflinks Assembly & DE

Performs differential expression of novel and reference transcripts with Cuffdiff 2 algorithm.


Performs differential expression of reference genes with DESeq2 algorithm.

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