Eliminating contaminants in miRNA-seq libaries just got easier

Biogenesis

microRNA sequencing is not only useful for finding novel microRNAs and detecting isomiRs; it’s also an attractive method for miRNA expression profiling, particularly when combined with molecular indexing to boost quantification accuracy (see our previous post, Barcodes in NGS: sample vs molecular). But preparing a library to sequence purely microRNAs can be difficult due to contaminating molecules that eat up sequencing capacity, diminishing the amount of real data you get. There are 2 types of contaminants that can affect microRNA sequencing: adapter dimers and other small RNA species. How can you address these contaminants so they don’t derail your data collection?

Adapter dimers

Adapter ligation prior to cDNA synthesis is one of the key steps in preparing a small RNA library. Briefly, a DNA adapter with a 5’ pre-adenylation group is ligated to the hydroxyl group at the 3’ ends of all miRNAs, and then an RNA adapter is ligated to the 5’ end of mature miRNAs. cDNA synthesis follows, where a reverse transcription primer binds to the 3’ adapter and facilitates conversion of the 3’/5’ ligated miRNAs into cDNA.

Adapter dimers are the binding of the 5’ adapter and the 3’ adapter with one another, with no miRNA insert. During the PCR amplification step, these dimers can be overamplified, generating high amounts of a molecule that is very close in size to a properly ligated miRNA (miRNAs, after all, are only between 21-24 nt in length), making them impossible to eliminate by bead-based cleanups alone.

Small RNA species

The other major contaminant to contend with in preparing miRNA for sequencing are other small RNA species. Adapter ligation can target any RNA with a 5’ phosphate group, which includes tRNAs, piRNAs and snoRNAs, leading to their reverse transcription as well. In serum and plasma samples, HY4 Y RNA is also frequently observed at high levels. These RNA species vary in length from sizes very close to miRNA, like in the case of piRNA, to much larger species in the tRNA and snoRNA.

What can you do to eliminate contaminants?

The original method for getting rid of contaminants before microRNA sequencing was just to cut around them. You can run the RNA on a polyacrylamide gel, find the band that fit the size of microRNA plus the adapters, and take that slice of the gel. This method will get you the microRNA fraction, but it’s also tedious, adding a substantial amount of time to your workflow. Additionally, it may be difficult to precisely separate the miRNA-sized library from adapter dimers, which are about 20 nt smaller than a miRNA library and may bleed into your band of interest if your sample input was low.

The QIAseq miRNA Library Kit provides a better solution to the problem of small RNA library contaminants. Rather than using an imprecise physical excision, the kit’s enhanced reaction chemistry and proprietary methodology using modified oligonucleotides prevent adapter dimerization in the first place. This enables efficient bead-based cleanup at two subsequent steps, one after cDNA synthesis and the other after library amplification, which ensure that no contaminating RNA species or adapter dimers remain in the sample.

Want to learn more?

Check out our new webinar on miRNA-seq technology! In “miRNA-seq from liquid biopsy: robust detection from the lowest sample,” we’ll discuss miRNA-seq technology in liquid biopsy, for sequencing even the smallest miRNA samples from biofluids.

miRNA-seq from liquid biopsy: robust detection from the lowest sample
March 20, 1 p.m. EST, 10 a.m. PST, 7 p.m. CET
Check out the recording!

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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