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Transcriptome Profiling Strategies

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Abstract

With the rapid development of high-speed DNA sequencing technologies, it became feasible to sequence deeply into cDNA libraries prepared from RNA samples. Such cDNA libraries can benefit from the development of full-length cDNA cloning technologies providing means to obtain sequence information on the entire RNA transcripts or their selected 5′ end. Comprehensive overviews on transcriptomes can be obtained today by combination of those new sequencing technologies with large-scale cDNA library preparation forming the basis to different approaches for transcriptome profiling.

In this chapter, we describe the use of full-length cDNA preparations in combination with shotgun sequencing in mRNA profiling (so-called RNA-Seq methods for “RNA sequencing”) and RNA-Seq profiling starting directly from RNA. Moreover, we describe the use of cap analysis gene expression (CAGE) for high-throughput mRNA detection and determination of transcription start sites (TSS) on the genome level. Here we applied “nanoCAGE", which uses template switching in the 5′ end selection step, to obtain CAGE data from very small amounts of RNA. We compare the sequencing data obtained by the three different library preparation methods and give directions for a bioinformatics pipeline used for their analysis. Examples are taken from our studies on the transcriptional regulation of gene expression during behavioral maturation of worker honey bees (Apis mellifera) to advise on transcriptome profiling strategies.

Keywords

Transcriptome profiling cDNA RNA sequencing CAGE CAGEscan Bioinformatics RNA-Seq nanoCAGE Full-length cDNA 

List of Abbreviations

CAGE

Cap analysis gene expression

CPCC

Cophenetic correlation coefficient

DEGs

Differentially expressed genes

EST

Expressed sequence tag

FPKM

Fragments per kilobase per million reads

GO

Gene ontology

MAPQ

Mapping quality

RNA-Seq

RNA sequencing

RPKM

Reads per kilobase per million

TMM

Trimmed mean of M-values

TPM

Tags per million

TSSs

Transcription start sites

Notes

Acknowledgment

We want to express our great thanks to Adam R. Hamilton, Yulia A. Medvedeva, Tanvir Alam, Intikhab Alam, Magbubah Essack, Boris Umylny, Boris R. Jankovic, Nicholas L. Naeger, Makoto Suzuki, and Gene E. Robinson for their great support for our honey bee project, which would have not been possible without working together with them. We further want to thank Charles Plessy and Piero Carninci for their support and encouragement for using CAGE.

Supplementary material

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Computer, Electrical and Mathematical Sciences and Engineering Division, Computational Bioscience Research CenterKing Abdullah University of Science and Technology (KAUST)ThuwalSaudi Arabia
  2. 2.Division of Genomic TechnologiesRIKEN Center for Life Science TechnologiesYokohamaJapan

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