Literature DB >> 27502218

Spliced synthetic genes as internal controls in RNA sequencing experiments.

Simon A Hardwick1,2, Wendy Y Chen1,2, Ted Wong1, Ira W Deveson1,3, James Blackburn1,2, Stacey B Andersen4, Lars K Nielsen4, John S Mattick1,2, Tim R Mercer1,2.   

Abstract

RNA sequencing (RNA-seq) can be used to assemble spliced isoforms, quantify expressed genes and provide a global profile of the transcriptome. However, the size and diversity of the transcriptome, the wide dynamic range in gene expression and inherent technical biases confound RNA-seq analysis. We have developed a set of spike-in RNA standards, termed 'sequins' (sequencing spike-ins), that represent full-length spliced mRNA isoforms. Sequins have an entirely artificial sequence with no homology to natural reference genomes, but they align to gene loci encoded on an artificial in silico chromosome. The combination of multiple sequins across a range of concentrations emulates alternative splicing and differential gene expression, and it provides scaling factors for normalization between samples. We demonstrate the use of sequins in RNA-seq experiments to measure sample-specific biases and determine the limits of reliable transcript assembly and quantification in accompanying human RNA samples. In addition, we have designed a complementary set of sequins that represent fusion genes arising from rearrangements of the in silico chromosome to aid in cancer diagnosis. RNA sequins provide a qualitative and quantitative reference with which to navigate the complexity of the human transcriptome.

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Year:  2016        PMID: 27502218     DOI: 10.1038/nmeth.3958

Source DB:  PubMed          Journal:  Nat Methods        ISSN: 1548-7091            Impact factor:   28.547


  46 in total

Review 1.  Towards a complete map of the human long non-coding RNA transcriptome.

Authors:  Barbara Uszczynska-Ratajczak; Julien Lagarde; Adam Frankish; Roderic Guigó; Rory Johnson
Journal:  Nat Rev Genet       Date:  2018-09       Impact factor: 53.242

2.  Annotation of Full-Length Long Noncoding RNAs with Capture Long-Read Sequencing (CLS).

Authors:  Sílvia Carbonell Sala; Barbara Uszczyńska-Ratajczak; Julien Lagarde; Rory Johnson; Roderic Guigó
Journal:  Methods Mol Biol       Date:  2021

3.  Normalizing single-cell RNA sequencing data: challenges and opportunities.

Authors:  Catalina A Vallejos; Davide Risso; Antonio Scialdone; Sandrine Dudoit; John C Marioni
Journal:  Nat Methods       Date:  2017-05-15       Impact factor: 28.547

Review 4.  Reference standards for next-generation sequencing.

Authors:  Simon A Hardwick; Ira W Deveson; Tim R Mercer
Journal:  Nat Rev Genet       Date:  2017-06-19       Impact factor: 53.242

5.  Sequencing: A sparkling standard.

Authors:  Darren J Burgess
Journal:  Nat Rev Genet       Date:  2016-08-22       Impact factor: 53.242

6.  RNA-seq mixology: designing realistic control experiments to compare protocols and analysis methods.

Authors:  Aliaksei Z Holik; Charity W Law; Ruijie Liu; Zeya Wang; Wenyi Wang; Jaeil Ahn; Marie-Liesse Asselin-Labat; Gordon K Smyth; Matthew E Ritchie
Journal:  Nucleic Acids Res       Date:  2017-03-17       Impact factor: 16.971

7.  A field guide for the compositional analysis of any-omics data.

Authors:  Thomas P Quinn; Ionas Erb; Greg Gloor; Cedric Notredame; Mark F Richardson; Tamsyn M Crowley
Journal:  Gigascience       Date:  2019-09-01       Impact factor: 6.524

8.  A combined RNA-seq and whole genome sequencing approach for identification of non-coding pathogenic variants in single families.

Authors:  Revital Bronstein; Elizabeth E Capowski; Sudeep Mehrotra; Alex D Jansen; Daniel Navarro-Gomez; Mathew Maher; Emily Place; Riccardo Sangermano; Kinga M Bujakowska; David M Gamm; Eric A Pierce
Journal:  Hum Mol Genet       Date:  2020-04-15       Impact factor: 6.150

9.  Integrative transcriptome sequencing reveals extensive alternative trans-splicing and cis-backsplicing in human cells.

Authors:  Trees-Juen Chuang; Yen-Ju Chen; Chia-Ying Chen; Te-Lun Mai; Yi-Da Wang; Chung-Shu Yeh; Min-Yu Yang; Yu-Ting Hsiao; Tien-Hsien Chang; Tzu-Chien Kuo; Hsin-Hua Cho; Chia-Ning Shen; Hung-Chih Kuo; Mei-Yeh Lu; Yi-Hua Chen; Shan-Chi Hsieh; Tai-Wei Chiang
Journal:  Nucleic Acids Res       Date:  2018-04-20       Impact factor: 16.971

10.  YAP1 Mediates Resistance to MEK1/2 Inhibition in Neuroblastomas with Hyperactivated RAS Signaling.

Authors:  Grace E Coggins; Alvin Farrel; Komal S Rathi; Colin M Hayes; Laura Scolaro; Jo Lynne Rokita; John M Maris
Journal:  Cancer Res       Date:  2019-10-31       Impact factor: 12.701

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