Literature DB >> 33859402

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

Jennifer F Hu1,2, Daniel Yim3,4, Duanduan Ma5, Sabrina M Huber3,6, Nick Davis3,7, Jo Marie Bacusmo8, Sidney Vermeulen3, Jieliang Zhou9, Thomas J Begley10, Michael S DeMott3,11, Stuart S Levine3,5,11, Valérie de Crécy-Lagard8, Peter C Dedon12,13,14, Bo Cao15,16,17.   

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.

Entities:  

Year:  2021        PMID: 33859402     DOI: 10.1038/s41587-021-00874-y

Source DB:  PubMed          Journal:  Nat Biotechnol        ISSN: 1087-0156            Impact factor:   54.908


  65 in total

1.  Limitations and possibilities of small RNA digital gene expression profiling.

Authors:  Sam E V Linsen; Elzo de Wit; Georges Janssens; Sheila Heater; Laura Chapman; Rachael K Parkin; Brian Fritz; Stacia K Wyman; Ewart de Bruijn; Emile E Voest; Scott Kuersten; Muneesh Tewari; Edwin Cuppen
Journal:  Nat Methods       Date:  2009-07       Impact factor: 28.547

2.  RNA-ligase-dependent biases in miRNA representation in deep-sequenced small RNA cDNA libraries.

Authors:  Markus Hafner; Neil Renwick; Miguel Brown; Aleksandra Mihailović; Daniel Holoch; Carolina Lin; John T G Pena; Jeffrey D Nusbaum; Pavel Morozov; Janos Ludwig; Tolulope Ojo; Shujun Luo; Gary Schroth; Thomas Tuschl
Journal:  RNA       Date:  2011-07-20       Impact factor: 4.942

3.  Barcoding bias in high-throughput multiplex sequencing of miRNA.

Authors:  Shahar Alon; Francois Vigneault; Seda Eminaga; Danos C Christodoulou; Jonathan G Seidman; George M Church; Eli Eisenberg
Journal:  Genome Res       Date:  2011-07-12       Impact factor: 9.043

Review 4.  Distribution and frequencies of post-transcriptional modifications in tRNAs.

Authors:  Magdalena A Machnicka; Anna Olchowik; Henri Grosjean; Janusz M Bujnicki
Journal:  RNA Biol       Date:  2014       Impact factor: 4.652

Review 5.  The noncoding RNA revolution-trashing old rules to forge new ones.

Authors:  Thomas R Cech; Joan A Steitz
Journal:  Cell       Date:  2014-03-27       Impact factor: 41.582

Review 6.  RNA-Seq: a revolutionary tool for transcriptomics.

Authors:  Zhong Wang; Mark Gerstein; Michael Snyder
Journal:  Nat Rev Genet       Date:  2009-01       Impact factor: 53.242

7.  Structural bias in T4 RNA ligase-mediated 3'-adapter ligation.

Authors:  Fanglei Zhuang; Ryan T Fuchs; Zhiyi Sun; Yu Zheng; G Brett Robb
Journal:  Nucleic Acids Res       Date:  2012-01-12       Impact factor: 16.971

8.  Bias in ligation-based small RNA sequencing library construction is determined by adaptor and RNA structure.

Authors:  Ryan T Fuchs; Zhiyi Sun; Fanglei Zhuang; G Brett Robb
Journal:  PLoS One       Date:  2015-05-05       Impact factor: 3.240

9.  Diverse cell stresses induce unique patterns of tRNA up- and down-regulation: tRNA-seq for quantifying changes in tRNA copy number.

Authors:  Yan Ling Joy Pang; Ryan Abo; Stuart S Levine; Peter C Dedon
Journal:  Nucleic Acids Res       Date:  2014-10-27       Impact factor: 16.971

10.  High-efficiency RNA cloning enables accurate quantification of miRNA expression by deep sequencing.

Authors:  Zhaojie Zhang; Jerome E Lee; Kent Riemondy; Emily M Anderson; Rui Yi
Journal:  Genome Biol       Date:  2013       Impact factor: 13.583

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  9 in total

Review 1.  tRNA modification dynamics from individual organisms to metaepitranscriptomics of microbiomes.

Authors:  Wen Zhang; Marcus Foo; A Murat Eren; Tao Pan
Journal:  Mol Cell       Date:  2022-01-14       Impact factor: 17.970

Review 2.  Exploring the expanding universe of small RNAs.

Authors:  Junchao Shi; Tong Zhou; Qi Chen
Journal:  Nat Cell Biol       Date:  2022-04-12       Impact factor: 28.213

3.  A multiplex platform for small RNA sequencing elucidates multifaceted tRNA stress response and translational regulation.

Authors:  Christopher P Watkins; Wen Zhang; Adam C Wylder; Christopher D Katanski; Tao Pan
Journal:  Nat Commun       Date:  2022-05-05       Impact factor: 17.694

4.  Aberration-corrected ultrafine analysis of miRNA reads at single-base resolution: a k-mer lattice approach.

Authors:  Xuan Zhang; Pengyao Ping; Gyorgy Hutvagner; Michael Blumenstein; Jinyan Li
Journal:  Nucleic Acids Res       Date:  2021-10-11       Impact factor: 16.971

5.  5' Half of specific tRNAs feeds back to promote corresponding tRNA gene transcription in vertebrate embryos.

Authors:  Luxi Chen; Wei Xu; Kunpeng Liu; Zheng Jiang; Yang Han; Hongbin Jin; Lin Zhang; Weimin Shen; Shunji Jia; Qianwen Sun; Anming Meng
Journal:  Sci Adv       Date:  2021-11-19       Impact factor: 14.136

6.  RNA marker modifications reveal the necessity for rigorous preparation protocols to avoid artifacts in epitranscriptomic analysis.

Authors:  Florian Richter; Johanna E Plehn; Larissa Bessler; Jasmin Hertler; Marko Jörg; Cansu Cirzi; Francesca Tuorto; Kristina Friedland; Mark Helm
Journal:  Nucleic Acids Res       Date:  2022-05-06       Impact factor: 19.160

7.  The Aminoacyl-tRNA Synthetase and tRNA Expression Levels Are Deregulated in Cancer and Correlate Independently with Patient Survival.

Authors:  Anmolpreet Kaur Sangha; Theodoros Kantidakis
Journal:  Curr Issues Mol Biol       Date:  2022-07-02       Impact factor: 2.976

Review 8.  Small but strong: Pivotal roles and potential applications of snoRNAs in hematopoietic malignancies.

Authors:  Jian Dong; Hui Wang; Zhaoru Zhang; Lin Yang; Xinyue Qian; Wenchang Qian; Yingli Han; He Huang; Pengxu Qian
Journal:  Front Oncol       Date:  2022-08-12       Impact factor: 5.738

Review 9.  Transfer RNAs-derived small RNAs and their application potential in multiple diseases.

Authors:  Xiaohua Chu; Chenyang He; Bo Sang; Chaofei Yang; Chong Yin; Mili Ji; Airong Qian; Ye Tian
Journal:  Front Cell Dev Biol       Date:  2022-08-22
  9 in total

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