Literature DB >> 34674175

A High-Throughput 3'-Tag RNA Sequencing for Large-Scale Time-Series Transcriptome Studies.

Xiaoyu Weng1, Thomas E Juenger2.   

Abstract

RNA sequencing (RNA-seq) has proven invaluable for exploring gene expression variation under complex environmental cues. However, the cost of standard RNA-seq (e.g., Illumina TruSeq or NEBNext) remains a barrier for high-throughput applications. 3'-Tag RNA-seq (3'-TagSeq) is a cost-effective solution that permits large-scale experiments. Unlike standard RNA-seq, which generates sequencing libraries for full-length mRNAs, 3'-TagSeq only generates a single fragment from the 3' end of each transcript (a tag read) and quantifies gene expression by tag abundance. Consequently, 3'-TagSeq requires lower sequencing depth (~5 million reads per sample) than standard RNA-seq (~30 million reads per sample), which reduces costs and allows increased technical and biological replication in experiments. Because 3'-TagSeq is considerably cheaper than standard RNA-seq while exhibiting comparable accuracy and reproducibility, researchers focusing on gene expression levels in large or extensive time-series experiments might find 3'-TagSeq to be superior to standard RNA-seq. In this chapter, we describe 3'-TagSeq sequencing library preparation and provide example bioinformatics and statistical analyses of gene expression data.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  3′-TagSeq; Gene expression variation; Large-scale experiments

Mesh:

Substances:

Year:  2022        PMID: 34674175     DOI: 10.1007/978-1-0716-1912-4_13

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  2 in total

1.  Promises and Challenges of Eco-Physiological Genomics in the Field: Tests of Drought Responses in Switchgrass.

Authors:  John T Lovell; Eugene V Shakirov; Scott Schwartz; David B Lowry; Michael J Aspinwall; Samuel H Taylor; Jason Bonnette; Juan Diego Palacio-Mejia; Christine V Hawkes; Philip A Fay; Thomas E Juenger
Journal:  Plant Physiol       Date:  2016-05-31       Impact factor: 8.340

2.  Profiling gene expression responses of coral larvae (Acropora millepora) to elevated temperature and settlement inducers using a novel RNA-Seq procedure.

Authors:  E Meyer; G V Aglyamova; M V Matz
Journal:  Mol Ecol       Date:  2011-07-29       Impact factor: 6.185

  2 in total

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