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Sequencing-based quantitative mapping of the cellular small RNA landscape

Hu, J. F.; Yim, D.; Huber, S. M.; Bacusmo, J. M.; Ma, D.; DeMott, M. S.; Levine, S. S.; Crecy-Lagard, V. d.; Dedon, P. C.; Cao, B.

2019-11-13 molecular biology
10.1101/841130 bioRxiv
Show abstract

Current next-generation RNA sequencing methods cannot provide accurate quantification of the population of small RNAs within a sample due to strong sequence-dependent biases in capture, ligation, and amplification during library preparation. We report the development of an RNA sequencing method - AQRNA-seq - that minimizes biases and enables absolute quantification of all small RNA species in a sample mixture. Validation of AQRNA-seq library preparation and data mining algorithms using a 963-member microRNA reference library, RNA oligonucleotide standards of varying lengths, and northern blots demonstrated a direct, linear correlation between sequencing read count and RNA abundance. Application of AQRNA-seq to bacterial tRNA pools, a traditionally hard-to-sequence class of RNAs, revealed 80-fold variation in tRNA isoacceptor copy numbers, patterns of site-specific tRNA fragmentation caused by stress, and quantitative maps of ribonucleoside modifications, all in a single AQRNA-seq experiment. AQRNA-seq thus provides a means to quantitatively map the small RNA landscape in cells and tissues.

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