RNA is the message your cells are sending right now: which genes are switched on and how strongly. With RNA sequencing (RNA-seq) we read all those messages at once, across a whole tissue or cell by cell. We design the study with you, analyze the data and interpret the results in the context of your question.
Every active gene produces copies of messenger RNA. RNA sequencing (RNA-seq) captures all those messages from a sample and reads them at once, millions of fragments in parallel, to reveal which genes are switched on and how strongly.
First we extract the RNA and convert it into complementary DNA (cDNA), which is far more stable. We cut it into fragments and add small tags (adapters) that make it readable and tell us which sample each fragment comes from. The sequencer then reads millions of fragments at once. Finally, each read is assigned to the gene it came from and counted: the more reads a gene has, the more active it is. A single run measures the activity of the whole transcriptome.
No need to pick genes in advance: tens of thousands are measured at once, the ones you expected and the ones nobody was looking at.
Every read is counted, so the result is quantitative with a huge range: from highly active genes to those barely expressed.
Beyond how much each gene is expressed, you also see variants of the same transcript (isoforms), non-coding RNAs and gene fusions.
Depending on your question, your sample and the level of detail you need, we choose the right technique with you.
We take care of the whole process: library preparation, sequencing, analysis and interpretation. If you already have your data, we start straight from it.
Captures coding messenger RNA with a poly-A tail. Answers questions on differential expression, activated pathways, mechanism of action and biomarkers.
All RNA except ribosomal: coding and non-coding. Suited to degraded or FFPE samples, non-polyadenylated transcripts and a global view.
Long non-coding RNAs and circular RNAs, to study gene regulation, ceRNA networks and new biomarkers.
miRNA, piRNA and other 18–40 nt RNAs: regulatory microRNAs and their targets, and biomarkers in biofluids.
Full-length transcripts from end to end, to study isoforms, alternative splicing and genome annotation.
Reads the transcriptome of each cell separately to uncover cell types, states and rare populations that would stay hidden in a whole tissue.
See single-cell with 10x Genomics →Indicative depths: we adjust them to the organism and the design of each study.
Reference values for a standard study. Every project is adjusted to your question and your sample.
| Aspect | Detail |
|---|---|
| Sample types | Fresh or frozen tissue, cells, blood, paraffin-embedded (FFPE) samples or extracted RNA |
| RNA quality | RIN ≥ 7 recommended · dedicated protocols for degraded RNA, FFPE or low RNA input |
| Sequencing depth | Depends on the technique (see cards) · deeper sequencing for low-expressed genes |
| Read length | Paired-end 150 bp |
| Organisms | Human, mouse, rat and any organism with a reference genome |
Expression data are huge, noisy and full of technical effects. Instead of forcing them into rigid linear models, we use AI models that learn the real structure of your data.
We review your question, your sample type and what you want to be able to decide with the results.
We propose the RNA-seq modality, sequencing depth and experimental design best suited to your question and budget.
We sequence your samples (or start from your data), process the reads and review preliminary results with you.
Interpreted report, figures and a meeting to review the results and plan next steps.
Some examples of questions RNA-seq can answer:
Which processes switch on or off in cancer, neurodegeneration, autoimmune or rare diseases.
How the transcriptome responds to a drug and which genes could become new therapeutic targets.
Genes or microRNAs that separate patient groups and deserve to become the candidate you validate later.
Which cells are in a tissue or organoid and what state they are in, at single-cell resolution.
What changes before and after an intervention, a treatment or a stimulus, and in which biological processes.
Characterization of cell lines, organoids and animal models to check whether they reproduce the biology you are after.
At the end of the project you receive:
We review the sequencing sample by sample so the results rest on solid data.
Which genes switch on or off between your conditions, with false-positive control.
Changes grouped into processes and pathways, to read the biology and not just a list of genes.
PCA, volcano, heatmaps and boxplots ready for your paper, report or committee.
A PDF explaining what the results mean, plus a meeting to review it with you.
Access to our software to explore the results without coding: search any gene, compare groups, filter by significance and build your own interactive plots.
What most affects the outcome of an RNA-seq study is the design and how the data are analyzed, especially with few samples and subtle effects. That is why we pay particular attention to:
Tell us your question and your sample type and we will send you a design proposal.