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High-throughput sequencing based methodologies have been widely applied to many biological samples in recent years greatly expanding our understanding of the molecular complexity of biological systems3,4. However, preparation of RNA samples for high-throughput sequencing often imparts specific biases inherent to the employed methodology, limiting the potential utility of these powerful techniques. These method specific biases have been well documented for ligation-based, small-RNA library preparations1,2,5,6. These biases result in 1,000-fold variation in reads numbers for equimolar synthetic miRNAs, making inference of miRNA abundance from sequencing data wildly variable and error prone.
Studies focusing on the properties of phage-derived T4 RNA ligases have documented that the enzymes exhibit nucleotide-based preferences7, which manifest as biased libraries in high-throughput sequencing experiments1,2,8. In order to minimize the biases imparted by RNA ligases, multiple strategies have been employed; macromolecular crowding9, randomizing the nucleotide sequence on the adapter which is proximal to the ligation site6, and employing high concentrations of ligation adapter2. Through a combination of these three approaches we have developed a work-flow for unbiased preparation of small RNA libraries compatible for high-throughput sequencing (Figure 1). For direct comparisons between current protocols and our optimized method, please refer to our recent report2. This optimized method yields ligation efficiencies of greater than 95% at both 3’ and 5’ steps and permits the unbiased ligation of small RNA molecules from synthetic and biological samples2.