Metatranscriptomics analyses RNA from microbial communities and allows you to determine which genes are expressed under the conditions studied. Choose it when you want to assess the microbiome's response to environmental change, diet or an experimental treatment. If you are primarily interested in microbiome composition and the presence of genes with specific functions, the more suitable choice is shotgun metagenomics.
Metatranscriptomics versus shotgun metagenomics
| Feature | Metatranscriptomics | Shotgun metagenomics |
|---|---|---|
| Material | RNA reverse-transcribed into cDNA | DNA |
| Main question | Which genes are expressed? | Which microorganisms and genes are present? |
| Functional information | Gene expression and assignment of genes to functions and pathways | Functional potential encoded in genes |
| Limitation | RNA abundance is not a direct measure of enzyme activity | The presence of a gene does not confirm its expression |
Which should you choose?
Choose metatranscriptomics, when you plan to compare gene expression in the microbiome between groups, conditions or time points. The analysis may include transcript assembly, taxonomic assignment, functional annotation and between-group differential analysis, using resources such as GO, KEGG, eggNOG, CAZy or CARD.
Choose shotgun metagenomics, when you want to determine community composition and detect genes associated with, for example, metabolism or antibiotic resistance.
Both methods can be used together on the same samples. DNA data help you assess whether a change in the RNA signal is associated with a change in gene expression or a change in the relative abundance of a particular microorganism in the community.
Sample requirements
The starting material is total RNA. Library preparation includes rRNA depletion and the construction of stranded libraries. Indicative requirements for extracted RNA are shown below.
| Parameter | Requirement |
|---|---|
| Total amount | ≥1 µg |
| Concentration | ≥50 ng/µl |
| Volume | ≥20 µl |
| Integrity | RIN ≥6.5 |
| Purity (A260/A280) | 1,8-2,0 |
| Purity (A260/A230) | 1,0-2,5 |
We determine the quantity of biological material required for extraction based on the sample type. It is worth agreeing on collection, preservation and transport procedures before starting the experiment. Stabilise the material promptly to prevent RNA degradation, using the same procedure across all groups.
Approximate data output
The recommended amount of sequencing data is 12 Gb of data per sample using Illumina PE150, i.e. 2 × 150 nucleotides. This corresponds to approximately 40 million read pairs, or 80 million individual full-length reads.
The target amount of data we select is based on microbiome complexity, the proportion of host RNA and the analysis objective. After rRNA, host sequences and low-quality reads have been filtered out, less usable data will remain. The quotation should specify whether the stated amount refers to raw or filtered data.
Common mistakes
Questions for project planning
Describe your project - we will recommend a method and amount of data.
Selected projects and client publications
See which institutions we perform next-generation sequencing (NGS) for and explore scientific publications that draw on the data we have supplied.