Customer-friendly solutions

- to complex problems

DNA sequencing and bioinformatics made easy
- we provide tailored sample-to-answer solutions


RNA sequencing (RNA-seq) using NGS enables the identification and quantification of gene expression in biological samples. DNASense offers RNA-seq of individual prokaryotic and eukaryotic organisms (transcriptomics) as well as mixed microbial communities (metatranscriptomics). We provide full sample-to-answer RNA-seq solutions with cutting-edge bioinformatic pipelines for identification of differentially expressed genes (DEGs). Our workflows support mapping and identification of RNA transcripts by either de-novo assembly, reference genomes or purpose built reference-hybrids (please refer to our (meta)genomics workflow for more information).

A crucial prerequisite for useful RNA-seq results is a suitably scaled experiment design. The number of biological replicates and required sequencing depths are highly dependent on the experiment’s scientific purpose, sample complexity and total transcript content. For large-scale projects setting up a pilot study is always the recommendation. The table below provides general recommendations, but if you are considering to do (meta)transcriptomics, we encourage you to contact DNASense already during the experimental planning and design, setting the foundation for the most optimal result outcome for your project.

Strategy Example sample environment mil reads/sample List price/sample
(EUR ex vat)
12 samples 24 samples
Transcriptome Prokaryote 5 900 650
Eukaryote 25 1120 837
Metatranscriptome Complex microbial community 50 1320 1039
Strategy Example sample environment mil reads/sample List price/sample
(DKK ex vat)
12 samples 24 samples
Transcriptome Prokaryote 5 6700 4850
Eukaryote 25 8325 6225
Metatranscriptome Complex microbial community 50 9800 7725

Our standard package includes: Optional pre- and post-project meeting with a DNASense specialist, RNA extraction, rRNA depletion, library preparation and cDNA sequencing, DEGs analysis (mapping/de novo assembly, gene annotation, quantification and statistical analysis), online-access to raw data and result files, a detailed project report with ready to use for publication materials and methods and publication grade illustrations.

Add-on services (non-exhaustive list): functional annotation (KO, GO), functional enrichment analysis, LEfSe analysis, manual curation of metabolic pathways, Data submission (e.g. ENA).


  • Ribosomal RNA constitutes up > 80% of cellular RNA.  Our recommendation is to perform rRNA depletion for RNA high yield samples, to maximize focus RNA in the subsequent sequencing. For RNA low-yield, for which RNA-depletion due to recovery loss is not a recommended option, increasing sequencing depth may be used as an alternative solution.

  • Statistical power increases with increasing number of replicates, especially for low-abundant genes. Our recommendation is a minimum 4 biological replicates per condition.

  • Depends on the scientific question at hand and sample matrix. For DEGs 2-5 million mapped reads for pure cultures is sufficient for most prokaryotes, for whole transcriptome sequencing 100-200 mio reads is typical.

  • The transcriptome/metatranscriptome is prone to mRNA degradation and changes in expression profile. Hence, to minimize biases associated with sampling, special care must be taken. We recommend adding a mRNA preservative (preferably RNAlater) and snap freezing samples as soon as possible.

Mie Bech Lukassen, Ph.D.
Chief Operating Officer

    Company / Institution