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

使用 AQRNA-seq 定量绘制细胞小 RNA 景观

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作者:Jennifer F Hu, Daniel Yim, Duanduan Ma, Sabrina M Huber, Nick Davis, Jo Marie Bacusmo, Sidney Vermeulen, Jieliang Zhou, Thomas J Begley, Michael S DeMott, Stuart S Levine, Valérie de Crécy-Lagard, Peter C Dedon, Bo Cao

Abstract

Current next-generation RNA-sequencing (RNA-seq) 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 RNA-sequencing (AQRNA-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 microRNA reference library, oligonucleotide standards of varying length, and RNA 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 transfer RNA 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.

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