Randomized Adapters for Reducing Bias in Small RNA-Seq Libraries

Abstract

Distinguishing closely-related small RNAs is difficult using microarray- and qPCR-based approaches, since imperfectly matched small RNAs may still be able to hybridize to PCR primers or immobilized probes. These considerations have led to the realization that next generation sequencing (NGS) is the most practical method for large-scale small RNA studies that aim to identify and enumerate small RNAs in various species and tissues. NGS offers advantages of sensitivity, specificity, and the ability to maximize data acquisition and minimize costs by using multiplex strategies to allow many samples to be sequenced simultaneously. NGS approaches for small RNA analysis are not without their own challenges. Small RNA libraries prepared for sRNA-Seq have been found to contain biases, resulting in libraries that inaccurately represent relative levels of the different small RNAs present in the starting RNA sample. Much effort has gone into identifying the cause of bias, and it is now generally accepted that bias in sRNA-seq libraries is primarily introduced by the T4-phage RNA ligases used during the ligation step of small RNA library preparation (2, 3, 4). NGS libraries are made by ligation of adapter oligonucleotides to the 5’ and 3’ ends of the target nucleic acids. The adapters comprise sequences needed to amplify the library by PCR using generic Forward and Reverse primers, as well as sequences needed to associate the target nucleic acids with the NGS sequencing instrument (e.g. the flowcell in Illumina sequencers) and optionally, sequences comprising barcodes to allow multiplexing. For sequencing small RNAs, adapters are added directly to the population of small RNAs using RNA ligases derived from T4 bacteriophage (Rnl1 for 5’ adapter ligation and Rnl2 for 3’ adapter ligation). Ideally, the RNA ligases would show no preference for attaching adapters to small RNAs of different sequences, but the reality is that RNA ligases show sequencespecific bias, resulting in preferential inclusion of some small RNAs in the sRNA-seq libraries, at the expense of others. Bioo Scientific has developed a novel solution to this problem, which allows meaningful results to be obtained in comparing small RNA profiles between samples.