Considerations for RNA Seq read length and coverage
Different RNA-Seq experiment types require different sequencing read lengths and depth (number of reads per sample). This bulletin reviews RNA sequencing considerations and offers resources for planning RNA-Seq experiments.
What resources should I consult first?
For RNA sequencing, read depth is typically used instead of coverage. Detecting low-expression genes can require an increase in read depth. The ENCODE project (updated here) has data standards for RNA-Seq and Small RNA sequencing that are an excellent resource for many projects.
Illumina recommends consulting the primary literature for your field and organism for the most up-to-date guidance on experiment design.
How many reads should I target per sample?
Read depth varies depending on the goals of the RNA-Seq study. Most experiments require 5–200 million reads per sample, depending on organism complexity and size, along with project aims.
- Gene expression profiling experiments that are looking for a quick snapshot of highly expressed genes may only need 5–25 million reads per sample. In these cases, researchers can pool multiple RNA-Seq samples into one lane of a sequencing run, which allows for high multiplexing of samples.
- Experiments looking for a more global view of gene expression, and some information on alternative splicing, typically require 30–60 million reads per sample. This range encompasses most published RNA-Seq experiments for mRNA/whole transcriptome sequencing.
- Experiments looking to get an in-depth view of the transcriptome, or to assemble new transcripts, may require 100–200 million reads. In these cases, researchers may need to sequence multiple samples across several high output sequencing lanes.
- Targeted RNA expression requires fewer reads. For example, Illumina recommends 3 million reads per sample for TruSight RNA Pan Cancer and TruSight RNA Fusion Panel, which are compatible with high plexity pooling of samples.
- miRNA-Seq or small RNA Analysis experiments may require even fewer reads than whole transcriptome sequencing. This requirement varies significantly depending on the tissue type being sequenced. Illumina strongly recommends using the primary literature to determine how many reads are needed, with most applications ranging from 1–5 million reads per sample.
To determine how many samples can be run at one time, divide the number of reads produced by the flow cell by the number of reads needed per sample:
- number of reads per flow cell / number of reads per sample=number of samples per flow cell
How long should my reads be?
Read length depends on the application and final size of the library. The Library Prep Kit Selector provides read length guidance for each type of RNA-Seq library. Sequencing reads that are longer than the insert length do not provide additional useful data.
- Gene expression / RNA Profiling – Quantifying the coding transcriptome typically requires a short single read (often 50–75 bp) to minimize reading across splice junctions while counting all RNAs in the pool.
- Transcriptome Analysis – Novel transcriptome assembly and annotation projects tend to benefit from longer, paired-end reads (such as 2 x 75 bp or 2 x 100 bp) to enable more complete coverage of the transcripts and identification of novel variants or splice sites. Paired-end reads are required to get information from both 5’ and 3’ ends of RNA species with stranded RNA-Seq library preparation kits.
- Small RNA Analysis – Due to the short length of small RNA, a single read (usually a 50 bp read) typically covers the entire sequence. A read length of 50 bp sequences most small RNAs, plus enough of the adapter to be accurately identified and trimmed during data analysis.
Additional Resources
For more information on other considerations in planning your RNA-Seq experiments, and RNA-Seq kit options, see the recorded Support Webinars from Illumina:
- RNA Sequencing Part I: Introduction to Illumina’s RNA library preparation workflows RNA Sequencing Part II: Best Practices for Illumina’s RNA prep protocols RNA Sequencing Part III: Introduction to Analysis Small RNA-Seq Part I: Introduction and Part II: Best Practices
Illumina Instrument Specifications:
For any feedback or questions regarding this article (Illumina Knowledge Article #1243), contact Illumina Technical Support [email protected]. |