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Metatranscriptome Sequencing


Metatranscriptome refers to the total content of gene transcripts (RNA copies of the genes) in a nature community (i.e. soil, water, sea, feces, and gut), considered as a unique entity, at a specific moment of sampling. Metatranscriptome changes with time and environmental variation. Metatranscriptome sequencing using the next generation sequencing (NGS) now can be applied to obtain the whole expression profile in a community and to follow the dynamics of gene expression patterns over time or environmental parameters, improving our understanding of the structure, function, and adaptive mechanisms in complex communities.

Metatranscriptome sequencing identifies gene expression of microbes, both eukaryotes and prokaryotes, within natural environments. Specifically, this service allows you to obtain whole gene expression profiling of complex microbial communities, taxonomic analysis of species, functional enrichment analysis of differently expressed genes, and more. At Novogene, we also provide a considerate pre-sales evaluation that is tailored for your project and assists you in more easily realizing your research objectives.

Service Specifications Demo Reports


Microbial ecology research:

  • Functional active bacteria characterization
  • Community metabolic interaction

Clinical research:

  • Immune recognition
  • Immune education
  • Autoimmune processes trigger
  • Biotechnology research


  • Extensive experience with thousands of samples being successfully sequenced.
  • Unsurpassed data quality with a guaranteed Q30 score ≥ 80% that exceeds Illumina’s official benchmarks.
  • Comprehensive analysis using mainstream software and mature in-house pipeline to meet multiple bioinformatic requests.

Sample Requirements


Library Type Sample Type Amount RNA Integrity Number
(Agilent 2100)
Meta-transcriptome Library
Total RNA
≥ 2.5 μg
≥ 6.5, smooth base line
OD260/280 = 1.8-2.2;
OD260/230 ≥ 1.8;

Sequencing Parameter and Analysis

Platform Illumina Novaseq 6000
Read length Pair-end 150
Recommended Sequencing Depth ≥40 million read pair per sample for the species with reference genome
Standard Data Analysis
Data Quality Control
De novo Assembly
Gene Functional Annotation
rRNA& mRNA Taxonomic Analysis
Gene expression quantification & Differential expressed genes profiling & Enrichment analysis
Comparative Analysis between Various Samples

Note: For detailed information, please refer to the Service Specifications & Demo Reports and contact us for customized requests.

Project Workflow

Sample Quality Control

Library Quality Control

Data Quality Control

Total RNA

Library Construction


Bioinformatics Analysis

Cryptophyte farming by symbiotic ciliate host detected in situ


Protist–alga symbiosis is much more widespread in the marine ecosystem than previously thought, both spatially and taxonomically. Field and laboratory observations have documented a wide range of host integration of symbionts, from enslaving transiently kept chloroplasts to permanent intact-cell endosymbionts. However, the degree of host integration and function of endosymbionts in natural plankton assemblages in situ is poorly understood and severely understudied.


Water in long island sound

Sequencing Strategy:

Library preparation: Directional RNA library
Sequencing: Illumina HiSeq 2000 platform

Figure 1. Red-tide bloom and the causative organisms.

(A) Photograph of the red tide.
(B) Light microscopic image of the causative ciliate.
(C) 18S rDNA phylogenetic tree verifying that the causative ciliate was M. rubrum.

Figure 2. Metabolic circuit map constructed from the cryptophyte subset of the metatranscriptome. Highlighted in this circuit are pathways of nucleotide metabolism (red), carbohydrate metabolism (blue), energy metabolism (purple), lipid metabolism (cyan), and amino acid metabolism (yellow) in cryptophytes.

The Mesodinium-farming-Teleaulax model not only distinguishes itself from the current model of Mesodinium enslaving cryptophyte chloroplasts or the organelle complex, but by promoting the proliferation of the endosymbiotic cells also differs from the conventional whole-cell endosymbiont models in which only binary division synchronous with host division is expected. The ecological significance in each case should be further studied in the future.

Figure 1 Error Rate Distribution

The x-axis shows the base position along each sequencing read and the y-axis shows the base error rate.

Figure 2 GC Content Distribution

Horizontal axis for reads position, vertical axis for single base percentage. Different color for different base type.

Figure 3 Composition of raw data.

Figure 4 Length distribution of transcripts and unigenes.

Figure 5 Species abundance clustering.

Figure 6 Quantification of transcripts.

Figure 7 Volcano diagram of differential expression genes.

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