Overview
Small RNA sequencing targets the class of short non-coding RNA molecules, typically 18–35 nucleotides in length, that play critical regulatory roles in gene expression. These include microRNAs (miRNAs), small interfering RNAs (siRNAs), and Piwi-interacting RNAs (piRNAs). Despite their small size, these molecules exert powerful control over mRNA stability, translation, chromatin state, and transposon silencing. Small RNA-seq requires specialized library preparation to capture such short fragments and distinct bioinformatics tools for accurate annotation and quantification.
Methods
Small RNA-seq library preparation involves size selection of RNA (typically by gel excision or bead-based purification), ligation of 3’ and 5’ adapters, reverse transcription, and PCR amplification. Because small RNAs are shorter than the read length, they are sequenced entirely, and adapter sequences must be trimmed precisely during preprocessing. Dedicated alignment tools (such as miRDeep2, sRNAbench, or ShortStack) map reads to known small RNA databases (miRBase for miRNAs, Rfam for other ncRNAs). Quantification estimates expression levels of known miRNAs while detection of novel miRNAs relies on characteristic hairpin precursor structures. Differential expression analysis follows similar principles to mRNA-seq but with special considerations for normalization because small RNAs have different length distributions and GC biases.
Applications
Small RNA profiling has revealed the pervasive regulatory roles of these molecules. miRNA signatures distinguish cancer subtypes and predict treatment response. Circulating miRNAs in blood or serum serve as minimally invasive biomarkers for diseases including cancer, cardiovascular disease, and neurodegeneration. The analysis connects to broader RNA structure and types studies and gene regulation and epigenetics, as many small RNAs participate in regulatory loops with transcription factors and epigenetic modifiers. Understanding small RNA biogenesis also builds on transcription and RNA processing concepts, particularly the role of Drosha and Dicer in miRNA maturation.
Practical Protocol
Small RNA-seq library preparation begins with total RNA input (100–1000 ng). Size selection is critical: RNA fragments of 18–35 nt are isolated by gel excision from a 15% polyacrylamide gel or by bead-based purification with AMPure XP beads at specific PEG concentrations. Adaptor ligation uses truncated T4 RNA ligase 2 for the 3’ adapter (minimizing circularization) and T4 RNA ligase 1 for the 5’ adapter. After reverse transcription with SuperScript III, the cDNA is PCR amplified (12–15 cycles to avoid over-amplification) and size-selected again to remove adapter dimers. For preprocessing, Cutadapt trims adapter sequences precisely: cutadapt -a TGGAATTCTCGGGTGCCAAGG --discard-untrimmed -m 18 -M 35 -o trimmed.fastq raw.fastq. The --discard-untrimmed flag removes reads without detectable adapter. For miRNA discovery and quantification, miRDeep2 provides a comprehensive pipeline: run mapper.pl to process reads, miRDeep2.pl to identify known and novel miRNAs against miRBase, and quantifier.pl to quantify expression. The pipeline scores candidate miRNA precursors by evaluating the characteristic hairpin structure: a miRDeep2 score above 10 indicates high-confidence predictions. Alternative tools include sRNAbench for species with incomplete miRBase annotations and ShortStack for de novo small RNA discovery without a reference genome. Normalization of small RNA expression data requires special attention; options include TPM (transcripts per million), reads per million (RPM), or the use of spike-in controls such as synthetic cel-miR-39. Differential expression analysis can be performed with DESeq2 on count data, but size factor estimation should use only miRNA counts rather than total mapped reads to avoid bias from abundant non-miRNA small RNAs.
