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
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
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.
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
Calculator can also be used to calculate how many samples to pool
together for a given run, depending on the instrument and the type of
sequencing kit being used.
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.
For more information on other considerations in planning your
RNA-Seq experiments, and RNA-Seq kit options, go to the Training
website and see the recorded webinars. Under “Filters” select
Training Type > Training and Videos > Online Training:
RNA Sequencing Part I: Introduction
Part II: Kits
Part III: Best Practices
Part IV: Introduction to Analysis
Small RNA-Seq Part I: Introduction and Part II: Best Practices
Illumina Instrument Specifications: