Quantitative mapping of the cellular small RNA landscape with AQRNA-seq.

Abstract

Current next-generation RNA sequencing methods do not provide accurate quantification of small RNAs within a sample due to sequence-dependent biases in capture, ligation, and amplification during library preparation. We present a method, Absolute Quantification (AQ) RNA-seq, that minimizes biases and provides a direct, linear correlation between sequencing read count and copy number for all small RNAs in a sample. Library preparation and data processing were optimized and validated using a 963-member miRNA reference library, oligonucleotide standards of varying lengths, and northern blots. Application of AQRNA-seq to a panel of human cancer cells revealed >800 detectable miRNAs that varied during cancer progression, while application to bacterial tRNA pools, with the challenges of secondary structure and abundant modifications, revealed 80-fold variation in tRNA isoacceptor levels, stress-induced site-specific tRNA fragmentation, quantitative modification maps, and evidence for stress-induced tRNA-driven codon-biased translation. AQRNA-seq thus provides a versatile means to quantitatively map the small RNA landscape in cells.