Questions and Answers: RNAseq

The experiment consists of a number of steps that require high-quality reagents and consumables. The experiment is priced just enough to cover the direct cost of those reagents and consumables. Not all genomic experiments cost several thousand dollars. You may make a sensible choice on methods for sequencing library prep and platform and draw solid conclusions within the budget. For instance, you may perform a pilot experiment under a thousand dollars before committing to the full-scale experiment.

Interestingly, we receive the exact opposite questions about the pricing. The Genomics Center charges the direct cost of reagents and consumables, and the University covers the rest of the operational cost and keep the technologies accessible. Therefore, our internal-user pricing is considerably low, compared with other similar facilities around our area (see the pricing table).

An RNAseq experiment consists of two parts: (1) preparation of sequencing libraries, and (2) sequencing instrument run. Therefore, pick a method for the library prep and choose a sequencing platform. Gene expression analysis of ten samples, for example, will need ten mRNA sequencing library preps (~$100 per sample) and a NextSeq MidOutput (150 cycles) run (~$1,300); thus, the total cost of this example experiment would be ~$2,300. Be mindful that every experiment may slightly be different from others such that it may need more, or fewer sequence reads.

More than two biological replicates are required; 3-5 replicates are common choices; and more than 6-12 replicates are recommended (Schurch et al. 2016). However, this question is more appropriate for your statistician. Take into account your experimental design, variance of expression of your genes of interest, significance level, statistical power, availability of samples and financial resources.

Total RNAseq is used to analyze whole transcriptome while mRNA seq is focused on expression analysis of protein-coding genes. The cost for total RNAseq is higher than mRNA seq. For total RNAseq, ribosomal RNAs are depleted using complementary probes. You may need to design and purchase sets of probes specific to your organism. The commercial kit for total RNAseq works for a limited number of organisms. Therefore, make sure that your organism is compatible with the commercial product of your choice: for example, consult with the Stranded Total RNA Species Compatibility Tables for an Illumina kit. The mRNA-seq protocol enriches the poly(A)-tailed RNA, and thus is compatible with eukaryotes.

TStandard protocols require 100 - 1,000 ng of total RNA. Therefore, submit at least 250 ng of total RNA in a total volume of 25 microliters. Consider submitting 2 micrograms of total RNA in 100 microliters if samples are not limited. Consult with us if low-input (<50 ng) protocols are desired.

The RNA integrity number (RIN) is measured using BioAnalyzer or TapeStation instruments. Samples with RIN of 7 or higher are acceptable for the standard library prep protocols (Romero et al., 2014). High quality RNA samples from plant tissues may register low RIN due to the organellar RNA abundant in green tissues. Consult with us if your samples are inherently difficult to obtain a high quality of RNA, such as samples from field study or forensic labs.

As of 2022, we have NextSeq500 and MiSeq instruments on campus, and have access to sequencers, such as iSeq, NovaSeq6000 and other types of sequencing systems through our collaborators. NextSeq500 is suitable for mid- to large-scale transcriptome analysis. MiSeq is used for a small-scale transcriptome analysis and quality test of sequencing libraries. A NextSeq sequencing run may be coupled with a MiSeq run for those experiments that require de novo transcriptome assembly as MiSeq produces the longest reads (600 bp) among the Illumina instruments.

A 50-bp single read is sufficient for sequencing small RNA such as miRNA (22-23 nt long). Also, a short single read (50-75 bp) is cost-effective for gene expression profiling of organisms with a well-annotated genome. Longer paired-end reads (75bp or 150bp paired-end) are used for gene expression profiling as well as whole transcriptome analyses to detect splicing variants.

For small genomes such as bacteria, 5-10 million reads per sample are recommended (Haas et al. 2012). For large genomes such as human, 20-30 million reads are needed for each sample. However, you need to increase the number of reads if you are interested in detecting low abundance genes, and vice versa. For de novo assembly, more than 100 million reads would be needed.

Haas BJ, Chin M, Nusbaum C, Birren BW, Livny J. (2012) How deep is deep enough for RNA-Seq profiling of bacterial transcriptomes? BMC Genomics 13: 734. 

Schurch NJ, Schofield P, Gierliński M, Cole C, Sherstnev A, Singh V, Wrobel N, Gharbi K, Simpson GG, Owen-Hughes T, Blaxter M, Barton GJ. (2016) How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use? RNA. 22(6):839-51. 

Romero IG, Pai AA, Tung J. Gilad Y (2014). RNA-seq: impact of RNA degradation on transcript quantification. BMC Biol. 12:42