Please find Frequently Asked Questions in the drop-down menu below:
We have several kits to choose from depending on your RNA samples.
The most frequently-used kit at NGI is the Illumina TruSeq Stranded mRNA. This kit selectively enriches polyA-tailed RNA i.e. mRNA, and is therefore best suited when studying protein encoding genes.
Libraries can also be prepared without polyA-enrichment of the provided RNA sample. This allows for sequencing all RNAs in a sample (Illumina TruSeq Stranded RNA without selection or depletion), rendering it suitable for samples where ribosomal RNA molecules (rRNA) have already been depleted by the user using a preferred depletion kit (suitable for their particular organism).
For projects seeking a more comprehensive whole transcriptome analysis by capturing diverse RNA molecules (not small RNA), where long non-coding RNAs (lncRNAs) and other non-polyadenylated RNAs are especially interesting, total RNA samples can be depleted of rRNA and/or mitochondrial rRNA and/or globin transcripts using the Illumina TruSeq Stranded total RNA (RiboZero) protocol. This kit can in some cases also be suitable for investigating mRNAs in slightly degraded samples. NGI currently supports rRNA depletion for human/mice/rat samples.
Low concentration and/or amount of RNA or samples that are degraded? We recommend using the TaKaRa SMARTer pico RNA kit. This kit is also suited to explore mitochondrial transcripts.
This depends on your specific project, but as a rule of thumb, try and balance the study aim vs. the cost vs. the value you get per extra read. To achieve this, consider whether you aim to compare transcriptomes among different samples, or if you would like to gain a deeper understanding of just a few samples:
While the best case scenario would be to start with high amounts of input RNA, less material will also likely allow detection of major effects among samples. To confirm perturbation of a candidate pathway/study effects in a knockout etc, anything from 1M reads/sample and up could be useful (however we recommend at least 10M reads/sample). For analysing differences among different conditions/treatments without any prior information, 10-50M reads/sample, can detect major effects in commonly-expressed transcripts. In general, the amount of sequencing data will directly influence the power to investigate effects of well or poorly expressed genes.
For a deeper investigation of only a few samples, there is often no need for biological replicates. We recommend sequencing as deeply as is practical (between 20-60M reads/sample). However, it is worth noting that in these cases, the input RNA material needs to be of high quality and concentration to allow sequencing libraries of high complexity.
Remember that the input will mirror the quality of the output, meaning that performing deeper sequencing of a low quality sample most often only generates additional duplicates. Your data/samples cannot always be of perfect quality, but make sure the quality is similar in samples to be compared.
Please carefully go through the sample requirement section for your particular library prep. You find them all here:
Illumina TruSeq Stranded mRNA
Illumina TruSeq Stranded RNA without selection or depletion
Illumina TruSeq Stranded total RNA (RiboZero)
TaKaRa SMARTer pico RNA kit
Read more about sample submission here.
The final cost for a standard RNA-seq project depends on the number of samples and the sequencing depth. The approximate cost for the library preparation per sample can be found here (click on the Illumina sequencing tab and refer to the info below “Library preparation for RNA-seq”). You can also find a general cost example under “Cost for standard RNA-seq”. If you scroll down a bit further you find a table with data outputs and prices for different sequencing options.
Last Updated: 16th April 2021