Literature DB >> 30308315

META RNA profiling: Multiplexed quantitation of targeted RNAs across large numbers of samples.

Azeet Narayan1, Rofina Johnkennedy1, Maheen Zakaria1, Victor Lee1, Abhijit A Patel2.   

Abstract

META RNA profiling is a simple and inexpensive method to measure the expression of multiple targeted RNAs across many samples. By assigning sample-specific tags up-front during reverse-transcription, cDNAs from multiple samples can be pooled prior to amplification and deep sequencing. Such early parallelization of samples simplifies the workflow, minimizes cross-sample experimental variability, and reduces reagent and sequencing costs. Herein we describe the theoretical framework of the method and provide a detailed protocol to facilitate its implementation.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Gene expression; RNA profiling; RNA-Seq; microRNA quantitation

Mesh:

Substances:

Year:  2018        PMID: 30308315      PMCID: PMC6311137          DOI: 10.1016/j.ymeth.2018.09.012

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


  18 in total

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Journal:  Methods Mol Biol       Date:  2012

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4.  Quantitative single-cell RNA-seq with unique molecular identifiers.

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5.  Mapping and quantifying mammalian transcriptomes by RNA-Seq.

Authors:  Ali Mortazavi; Brian A Williams; Kenneth McCue; Lorian Schaeffer; Barbara Wold
Journal:  Nat Methods       Date:  2008-05-30       Impact factor: 28.547

6.  Better together: multiplexing samples to improve the preparation and reliability of gene expression studies.

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Journal:  Nat Methods       Date:  2015-04       Impact factor: 28.547

7.  Quantitative monitoring of gene expression patterns with a complementary DNA microarray.

Authors:  M Schena; D Shalon; R W Davis; P O Brown
Journal:  Science       Date:  1995-10-20       Impact factor: 47.728

8.  Real-time quantification of microRNAs by stem-loop RT-PCR.

Authors:  Caifu Chen; Dana A Ridzon; Adam J Broomer; Zhaohui Zhou; Danny H Lee; Julie T Nguyen; Maura Barbisin; Nan Lan Xu; Vikram R Mahuvakar; Mark R Andersen; Kai Qin Lao; Kenneth J Livak; Karl J Guegler
Journal:  Nucleic Acids Res       Date:  2005-11-27       Impact factor: 16.971

9.  A novel and universal method for microRNA RT-qPCR data normalization.

Authors:  Pieter Mestdagh; Pieter Van Vlierberghe; An De Weer; Daniel Muth; Frank Westermann; Frank Speleman; Jo Vandesompele
Journal:  Genome Biol       Date:  2009-06-16       Impact factor: 13.583

10.  Dynamic repertoire of a eukaryotic transcriptome surveyed at single-nucleotide resolution.

Authors:  Brian T Wilhelm; Samuel Marguerat; Stephen Watt; Falk Schubert; Valerie Wood; Ian Goodhead; Christopher J Penkett; Jane Rogers; Jürg Bähler
Journal:  Nature       Date:  2008-05-18       Impact factor: 49.962

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