Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

A high-throughput RNA-seq approach to profile transcriptional responses

G. A. Moyerbrailean, G. O. Davis, C. T. Harvey, D. Watza, X. Wen, R. Pique-Regi, F. Luca
doi: https://doi.org/10.1101/018416
G. A. Moyerbrailean
*Center for Molecular Medicine and Genetics, Wayne State University
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
G. O. Davis
*Center for Molecular Medicine and Genetics, Wayne State University
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
C. T. Harvey
*Center for Molecular Medicine and Genetics, Wayne State University
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
D. Watza
*Center for Molecular Medicine and Genetics, Wayne State University
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
X. Wen
§Department of Biostatistics, University of Michigan
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
R. Pique-Regi
*Center for Molecular Medicine and Genetics, Wayne State University
†Department of Obstetrics and Gynecology, Wayne State University
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
F. Luca
*Center for Molecular Medicine and Genetics, Wayne State University
†Department of Obstetrics and Gynecology, Wayne State University
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

In recent years, different technologies have been used to measure genome-wide gene expression levels and to study the transcriptome across many types of tissues and in response to in vitro treatments. However, a full understanding of gene regulation in any given cellular and environmental context combination is still missing. This is partly because analyzing tissue/environment-specific gene expression generally implies screening a large number of cellular conditions and samples, without prior knowledge of which conditions are most informative (e.g. some cell types may not respond to certain treatments). To circumvent these challenges, we have established a new two-step high-throughput and cost-effective RNA-seq approach: the first step consists of gene expression screening of a large number of conditions, while the second step focuses on deep sequencing of the most relevant conditions (e.g. largest number of differentially expressed genes). This study design allows for a fast and economical screen in step one, with a more profitable allocation of resources for the deep sequencing of re-pooled libraries in step two. We have applied this approach to study the response to 26 treatments in three lymphoblastoid cell line samples and we show that it is applicable for other high-throughput transcriptome profiling requiring iterative refinement or screening.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted April 22, 2015.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
A high-throughput RNA-seq approach to profile transcriptional responses
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
A high-throughput RNA-seq approach to profile transcriptional responses
G. A. Moyerbrailean, G. O. Davis, C. T. Harvey, D. Watza, X. Wen, R. Pique-Regi, F. Luca
bioRxiv 018416; doi: https://doi.org/10.1101/018416
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
A high-throughput RNA-seq approach to profile transcriptional responses
G. A. Moyerbrailean, G. O. Davis, C. T. Harvey, D. Watza, X. Wen, R. Pique-Regi, F. Luca
bioRxiv 018416; doi: https://doi.org/10.1101/018416

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Genomics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4381)
  • Biochemistry (9581)
  • Bioengineering (7086)
  • Bioinformatics (24844)
  • Biophysics (12597)
  • Cancer Biology (9952)
  • Cell Biology (14345)
  • Clinical Trials (138)
  • Developmental Biology (7944)
  • Ecology (12101)
  • Epidemiology (2067)
  • Evolutionary Biology (15984)
  • Genetics (10921)
  • Genomics (14735)
  • Immunology (9869)
  • Microbiology (23645)
  • Molecular Biology (9477)
  • Neuroscience (50838)
  • Paleontology (369)
  • Pathology (1539)
  • Pharmacology and Toxicology (2681)
  • Physiology (4013)
  • Plant Biology (8655)
  • Scientific Communication and Education (1508)
  • Synthetic Biology (2391)
  • Systems Biology (6427)
  • Zoology (1346)