miRNA-seq vs qPCR in 2017: an update

Biogenesis

Time marches on and technology with it, and these new advances yield new perspectives. Of particular interest to this blog is the changing technology and perspective on microRNA profiling methods. Two years ago, I wrote about the pros and cons of 3 methods commonly used for miRNA expression analysis, NGS, qPCR and microarray, and concluded that each method has strengths and weaknesses suited for different types of experiments. To summarize:

2015 NGS vs qPCR:

•  NGS was time-consuming compared to qPCR
•  NGS was not as good as qPCR for accurate quantification
•  NGS was superior to qPCR for novel discovery and isomiR differentiation

The takeaway was that novel discovery demands NGS, but accurate quantification and convenience are the realm of qPCR. However, new advances have taken place in miRNA sequencing over the past year that cast a new light on the comparison. I’ve recently covered the QIAseq miRNA Library Kit, which uses unique chemistry to bias the library reaction toward microRNAs and molecular barcodes, called Unique Molecular Indices (UMIs), to boost accurate read-counting. But what does this mean for our NGS vs qPCR comparison?

NGS vs qPCR workflow: closing the timing gap

In 2015, microRNA sequencing was notably more time-consuming than qPCR, requiring multiple days. New advances have reduced this disparity dramatically. The reason traditional miRNA library construction is so time-consuming is that it involves a gel excision step to enrich for the miRNA fraction of a library and slice out adapter dimers and contaminating RNAs. The QIAseq miRNA Library Kit enables a single-day, 8-hour sample-to-sequencer workflow due to its optimized reaction chemistry that virtually eliminates adapter dimer formation and background contaminants, making the gel excision step unnecessary. So how does this new standard compare to qPCR? Pretty favorably. A qPCR experiment, start-to-finish, will typically take about 6 hours. When both techniques fit within a single working day, the additional advantages of NGS (the ease of profiling more miRNAs, novel discovery and isomiR differentiation) become well worth the bit of extra time.

An additional, distinct advantage of miRNA-seq is the multiplex capacity in relation to both time commitment and output data. In one 10 hour sequencing run, you have the ability to sequence the entire miRNome (both annotated and non-annotated) of 48 samples in parallel. Using qPCR, the same experiment would take either 192 hours (when you are assessing only 750 miRNAs) or 672 hours (if you want to assess the entire annotated miRNome), and the associated cost would be higher as well – see the table below for details. Hands down, the time commitment and output data of miRNA-seq cannot be beat.

Table: Scalability of NGS compared to qPCR for a 48-sample miRNome experiment

Parameter NGS (All miRNAs present, either known or unknown) qPCR (~750 miRNAs.  Only known miRNAs can be assessed) qPCR (~2400 miRNAs. Only known miRNAs can be assessed)
Material required QIAseq miRNA Library Kit 96 384-well plates 336 384-well plates
Run time 10 hours for NextSeq run 192 hours 672 hours
Cost per sample $78 (exclusive of sequencing run) $586 $2028
Sample 100 ng for cellular samples or 5 µl of RNA eluate for serum/plasma* 500 ng for cellular samples or 3 µl of RNA eluate for serum/plasma* 1.75 µg for cellular samples or 10.5 µl of RNA eluate for serum/plasma*
  • * Prepped from 200 µl serum or plasma

 

NGS makes strides toward matching qPCR quantification capacity

qPCR is the gold standard for absolute quantification, and against this advantage, NGS has been slow to catch up. The key problem has been read counting – without some way of distinguishing which reads come from which original miRNA molecule, PCR and sequencing bias could lead to skewed reads ratios that don’t reflect the original sample. In 2017, however, there’s a solution to this problem: molecular barcodes. Called Unique Molecular Indices in the QIAseq family, or UMIs, these barcodes are appended to each unique miRNA molecule before any PCR amplification takes place. So when reads are counted at the end of the sequencing experiment, reads with the same UMI are “collapsed” into 1 count, enabling a much more accurate picture of the original sample. The result is a sequencing experiment that can also be used for miRNA quantification with nearly the accuracy of qPCR – a massive step forward in making NGS the technology of choice for nearly any miRNA profiling application.

Novel discovery and isomiR differentiation – NGS remains on top

Nothing’s changed here in the past 2 years – NGS is still the only option available for novel discovery, and is still the best at isomiR differentiation.

How might the new miRNA-seq advances improve your research?

Many labs still prefer qPCR for its absolute quantification capabilities and convenience – NGS instruments are still not ubiquitous in molecular biology labs to the extent that qPCR instruments are. However, the face of miRNA expression profiling is changing rapidly with these new advances. We encourage anyone who hasn’t yet tried the new miRNA-seq to check it out and to tell your core labs about it too – you’ll be surprised by the ease of use and impressive data quality, and you just might decide to make the switch for good.

QIAseq is making NGS accessible for not only miRNA, but for mRNA profiling as well. Want to know more? Join our Summer of NGS webinar event in July to learn all about DNA-seq, RNA-seq and miRNA-seq solutions, as well as single-cell NGS! Sign up for the webinars you’re interested in below:

•  Introduction to Unique Molecular Index targeted sequencing
•  Targeted DNA-seq for mutation detection
•  Gene expression analysis using targeted RNA-seq & desktop NGS instruments
•  Linking miRNA & gene expression using NGS
•  Single-cell applications using NGS

Ali Bierly

Ali Bierly, PhD is a Global Market Manager in Translational Sciences at QIAGEN, and has written on a number of scientific topics in the biotech industry as the author of QIAGEN's Reviews Online. She received her PhD from Cornell University in 2009, studying the immune response to a protozoan parasite, Toxoplasma gondii. Ali has a keen interest in the emerging importance of microRNA and other circulating nucleic acids as biomarkers for disease.

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