As a result of the large cost reduction for sequencing, RNA-seq is now a more affordable and popular technique in multiple areas, including clinical applications where the detection of aberrant transcription can be analyzed in human disease. And while each step of the experimental setup is of critical importance to get the most reliable results possible, and there are a number of ways to increase accuracy and success of RNA-seq experiments, sample prep stands at a pivotal point in experimental success.

RNA-seq is used to understand the landscape of biologically expressed genes in different conditions and also to uncover non-coding RNAs such as microRNAs and long non-coding RNA. Studies have shown that differences in sample prep and enrichment can cause large variations in experimental outcomes.

Protocol comparison studies

Comprehensive reviews of RNA-seq library protocols and methods have already been done for various experimental applications. Two notable, large-scale projects include the Sequencing Quality Control project of the SEQC/MAQC-III Consortium, led by U.S. FDA1, and the Association of Biomolecular Resource Facilities (ABRF) next-generation sequencing (NGS) study.2

The SEQC concluded that data variability originates from differences in library prep protocols and sequencing platforms. The specific sample preparation parameters evaluated included: fragmentation time, ribosomal RNA depletion methods, cDNA synthesis procedures, library purification methods, ligation efficiency, and RNA quality.

The ABRF-NGS study reported that library preparation influenced the detection of non-polyA tail transcripts, 3′ UTRs, and introns. They concluded that the primary differences were between rRNA reduction methods such as rRNA depletion and polyA enrichment with some capturing more structural and non-coding versus full-length RNAs.

Additional studies have also shed light on and evaluated various platforms for degraded and low-quality samples such as the three Illumina RNA-Seq protocols3 or for low-input and single-cell sequencing.4-7

The interest in generating data from rare cell populations and being able to obtain high-quality libraries from small quantities of total RNA makes sense as the field moves toward the use of single-cell technologies. How to optimize sample preparation for experiments designed for low-input or degraded samples has also been evaluated.8

Considerations for RNA recovery

The first step to consider when preparing for successful RNA-seq experiments is that RNA is more labile than DNA, and RNAses are very stable enzymes. Taking general precautions when working can prevent a significant amount of potential RNase contamination. Gloves, of course, need to be worn when handing reagents or reaction tubes, and although the microcentrifuge tubes themselves (if they were handled properly) may not need to be treated, gloves that have previously touched refrigerator handles, doors, or pipettors are not considered RNase-free. And while RNase contamination can ruin an experiment and also make it hard to track the equipment responsible, there are kits that can help such as Ambion’s RNaseAlert, which allows researchers to identify the contaminated source quickly and nonisotopically.

Limit RNA degradation

Since the goal of RNA-seq is to characterize the transcriptome, care should be paid to the potential for RNA degradation. Because there is usually a time delay between harvesting and isolation, it is suggested that RNA samples should be immediately frozen in liquid nitrogen upon harvest. Several kits have also been designed for specific purposes like extraction from bacteria (Qiagen’s RNAprotect Bacteria Reagent), which immediately stabilizes gram-positive and gram-negative bacteria. In addition, isolation from fresh tissue can be achieved with RNAstable® (from Biomatrica) and RNAlater® (from Qiagen).

Isolation and purification

Isolation of RNA is centered around the need to separate and preserve the integrity of extracted RNA. Incomplete homogenization can significantly impact sample preparation, and different types of samples require different methods of homogenization. For animal cells, mechanical homogenization with rotor-stator homogenizer, bead mills, syringe and needle, vortex, or sonication are all viable options. Chemical methods include addition of lysis buffer, and physical methods include heat and osmotic shock. For animal tissue, the mechanical methods listed above are preferred. Bacterial cells can also be lysed with biological enzymes (lysozyme/zymolase, etc.) and when used in bacteria or yeast, lysis buffer should be added after enzymatic digestion.

RNA recovery and enrichment

RNA recovery can come in various forms. Thermo-Fischer states “Our RNA extraction products include organic, silica spin columns, crude lysate, and magnetic beads. Some of these familiar products include Ambion Cells-to-CT Kits, TRIzol reagents, PureLink purification kits, MagMAX extraction kits, mirVana isolation kits, and Dynabeads mRNA isolation technologies.” After assessing RNA quality and quantity, it is often necessary to enrich specific classes of RNA. Some of the most common methods used to enrich RNA are:

  • Hybridization for target RNA or removal of non-target RNA
  • Copy number normalization via nuclease digestion
  • Size selection

Hybridization that uses oligo-dT to recover mature mRNAs by duplexing with their poly-tails assumes that proportions of RNA that don’t have poly-A stretches will be reduced. A number of commercial kits are available, but consideration should be given that bacterial mRNAs are not poly-adenylated and cannot be enriched this way. It is also possible to use hybridization methods to remove non-target RNA from a sample, such as the removal of ribosomal RNA. This option preserves non-polyadenylate RNAs. Companies like Evrogen offer duplex-specific nucleases. Usually this is performed after cDNA prep. For enrichment of small RNAs like miRNA, siRNA, and piRNA, electrophoresis can be useful.

Other innovative options include Sera-Mag Oligo(dT)-Coated Magnetic Particles enable mRNA isolation and extraction for applications by Cytiva Life Sciences.

Overall, the methods for RNA transcriptome analysis are always expanding. As methods change and new methods evolve, a few principles of RNA-seq prep remain:

    • High-quality samples are essential for RNA-seq success
    • When sending samples off to a facility, you as the researchers are usually responsible for total RNA isolation
    • Before undertaking a large experiment, consider a pilot project to determine the best tissue/cell isolation technique and RNA purification technique
    • Once a technique for isolation and purification has been established, stick with it throughout the whole project
    • Always determine total RNA sample purity and estimate concentration
    • Determine the total RNA quality prior to library construction, ask your genomics facility for assistance if needed

It should also be considered that most protocols rely on DNA sequencing technology to perform RNA sequencing experiments, thus requiring the conversion to a cDNA library. Currently, direct RNA sequencing using nanopore arrays is offering new and exciting alternatives. All the while, however, the quality and isolation of the RNA sample remains an important step, and one to be well considered.

References

1. Consortium, S. M.-. I. A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the sequencing quality control consortium. Nat Biotechnol 32, (2014).

2. Li, S. et al. Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study. Nat. Biotechnol. 32, 915–925 (2014).

3. Schuierer, S. et al. A comprehensive assessment of RNA-seq protocols for degraded and low-quantity samples. BMC Genomics 18, 442 (2017).

4. Adiconis, X. et al. Comparative analysis of RNA sequencing methods for degraded or low-input samples. Nat. Methods 10, 623–629 (2013).

5. Shanker, S. et al. Evaluation of commercially available RNA amplification kits for RNA sequencing using very low input amounts of total RNA. J. Biomol. Tech. 26, 4–18 (2015).

6. Wu, A. R. et al. Quantitative assessment of single-cell RNA-sequencing methods. Nat. Methods 11, 41–46 (2014).

7. Ziegenhain, C. et al. Comparative Analysis of Single-Cell RNA Sequencing Methods. Mol. Cell 65, 631-643.e4 (2017).

8. Palomares, M. A. et al. Systematic analysis of TruSeq, SMARTer and SMARTer Ultra-Low RNA-seq kits for standard, low and ultra-low quantity samples. Sci. Rep. 9, 1–12 (2019).