Normalization of high-throughput small RNA sequencing (sRNA-Seq) data is required to compare sRNA levels across different samples. Commonly used relative normalization approaches can cause erroneous conclusions due to fluctuating small RNA populations between tissues. Researchers from the Austrian Academy of Sciences developed a set of sRNA spike-in oligonucleotides (sRNA spike-ins) that enable absolute normalization of sRNA-Seq data across independent experiments, as well as the genome-wide estimation of sRNA:mRNA stoichiometries when used together with mRNA spike-in oligonucleotides.
Small RNA spike-in design and use as a tool to estimate absolute small RNA levels
(a) Design of small RNA spike-in oligonucleotides. Key features of small RNA spike-ins are shown in different colors corresponding to the key. Molar amounts of oligonucleotides added per µg of total RNA are indicated in parentheses. (b) Scatter plot of relative small RNA spike-in levels (reads per million genome-matching reads) compared to absolute small RNA levels (molecules detected per µg of total RNA) in Col-0 flowers (biological replicate 1). Pearson’s r value is indicated, as well as a dashed line that represents a linear model derived from the plotted values. (c) Density plot of individual miRNA family levels in Col-0 flowers (biological replicate 1) in molecules detected per µg of total RNA. Vertical dashed line indicates the median number of molecules per miRNA family.