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How to: Choose the best RNA sequencing method for quantitative miRNA profiling

This article has been based upon this blog post, written by Dr Karolina Szczesna.

RNA sequencing (RNA-seq) uses next generation sequencing (NGS) to quantify and discover RNA in biological samples. It allows high throughput, cost effective analysis of transcriptomes, and has advantages over microarrays and expressed sequence tag (EST) sequencing.

RNA sequencing is mainly used for:

  • Quantitative analysis of RNA expression and expression profiling
  • Detection of single nucleotide polymorphisms
  • Functional annotation of genomes by identifying coding and non-coding RNAs
  • Studying RNA editing

Different RNA-seq setups can focus on different subsets of RNA, e.g. coding RNAs or ribosomal RNAs. Single-cell RNA-seq is an invaluable tool for studying heterogeneous cell populations and tissue complexity, such as tumours.

Challenges in small RNA-seq

Standard RNA-seq is used for sequencing messenger RNAs and long non-coding RNAs. The RNA is isolated, fragmented to between 30-400bp, then reversely transcribed to cDNA. Small RNAs however, such as mature microRNAs (miRNAs), are too small for standard RNA-seq protocols and require additional extension steps during library preparation to allow unbiased and efficient PCR amplification.

Proper normalisation and reproducibility assessments are needed for biological samples with low abundance of RNA, such as circulating cell-free miRNAs in blood.

Different methods of small RNA-seq

Different methods have been developed to perform small RNA-seq experiments, most of which require 3’ and 5’ adapter ligations. These ligations are crucial and have an impact on the quality and selectivity of the amplified RNAs. Current strategies for small RNA-seq can be divided into those that employ adapters with invariant ends, and those with adapters containing four degenerate nucleotides (4N) at the ligation ends.

A study by Giraldez et al. evaluated three commercial kits that use invariant ends and six protocols with 4N adapters and found that:

  1. Sequence bias is a big problem
    Small RNA-seq protocols suffer from sequencing bias. The sequence bias between different protocols were significantly higher between the datasets generated by different research groups using the same protocol, suggesting that the protocol choice has a major impact on the quality of the data.
    The blog recommends bearing this in mind when comparing small RNA-seq results that were analysed using different library preparation protocols. They also found that 4N adapter protocols raised smaller sequence bias than invariant adapter methods.

(What is sequencing bias? – During the amplification step, certain lengths or sequences of RNAs are preferentially amplified compared to others. This results in these RNAs being represented as a higher proportion of the sample than they actually are. This is especially problematic when using such small samples and miRNAs.)

  1. Small RNA-seq protocols are accurate and reproducible
    The researchers used pre-defined pools of small synthetic RNAs, which allowed them to compare the protocols in terms of accuracy and reproducibility. They found that observed miRNA abundance ratios were close to the expected ratios, meaning all the protocols were accurate for obtaining miRNA abundance. They also measured reproducibility by statistical parameters.
  1. miRNA detection is most reliable using an in-house 4N adapter protocol
    Researchers need to use an appropriate RNA-seq method that allows for precise A-to-I miRNA editing, as deamination of adenosine residues to inosine can occur in a subset of miRNA precursors. In their studies, an in-house 4N adapter protocol performed better than commercial invariant adapter protocols in accurately detecting actual editing levels.

 Despite this study helping researchers follow up on their protocols and experimental design details for small RNA-seq, it still has large sequence biases when compared with long RNA-seq. Recent investigations that have used 4N adapters seem to yield a lower sequence bias.

The blog post also concludes that researchers should consider other parameters, such as ligation times and temperatures, when performing small RNA-seq experiments.

More on these topics

How to / RNA / Sequencing