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Complete Transcriptome RNA-Seq

  • David F. B. MillerEmail author
  • Pearlly Yan
  • Fang Fang
  • Aaron Buechlein
  • Karl Kroll
  • David Frankhouser
  • Cameron Stump
  • Paige Stump
  • James B. Ford
  • Haixu Tang
  • Scott Michaels
  • Daniela Matei
  • Tim H. Huang
  • Jeremy Chien
  • Yunlong Liu
  • Douglas B. Rusch
  • Kenneth P. NephewEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1513)

Abstract

RNA-Seq is the leading technology for analyzing gene expression on a global scale across a broad spectrum of sample types. However, due to chemical modifications by fixation or degradation due to collection methods, samples often contain an abundance of RNA that is no longer intact, and the capability of current RNA-Seq protocols to accurately quantify such samples is often limited. We have developed an RNA-Seq protocol to address these key issues as well as quantify gene expression from the whole transcriptome. Furthermore, for compatibility with improved sequencing platforms, we use restructured adapter sequences to generate libraries for Illumina HiSeq, MiSeq, and NextSeq platforms. Our protocol utilizes duplex-specific nuclease (DSN) to remove abundant ribosomal RNA sequences while retaining other types of RNA for superior transcriptome profiling from low quantity input. We employ the Illumina sequencing platform, but this method is described in sufficient detail to adapt to other platforms.

Key words

RNA-Seq Transcriptome Gene Expression Duplex-specific Nuclease Sequencing 

Notes

Acknowledgements

David F.B. Miller and Kenneth P. Nephew are corresponding authors of this work. We would like to thank Jay Pilrose for providing the solid tumor homogenization protocol.

This work was funded by Interrogating Epigenetic Changes in Cancer Genomes (The Integrative Cancer Biology Program (ICBP): Centers for Cancer Systems Biology (CCSB), NIH NCI- U54 CA113001, CA125806, the V-Foundation for Cancer Research (Cary, NC), and Walther Cancer Foundation (Indianapolis, Indiana)

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • David F. B. Miller
    • 1
    Email author
  • Pearlly Yan
    • 2
  • Fang Fang
    • 1
  • Aaron Buechlein
    • 3
  • Karl Kroll
    • 2
  • David Frankhouser
    • 2
  • Cameron Stump
    • 2
  • Paige Stump
    • 2
  • James B. Ford
    • 3
  • Haixu Tang
    • 3
  • Scott Michaels
    • 3
  • Daniela Matei
    • 4
  • Tim H. Huang
    • 5
  • Jeremy Chien
    • 6
  • Yunlong Liu
    • 7
  • Douglas B. Rusch
    • 3
  • Kenneth P. Nephew
    • 8
    • 9
    • 10
    Email author
  1. 1.Medical Sciences ProgramIndiana University School of MedicineBloomingtonUSA
  2. 2.Department of Internal MedicineOSUCCC-Illumina CoreColumbusUSA
  3. 3.Indiana University Center for Genomics and BioinformaticsBloomingtonUSA
  4. 4.Department of MedicineIndiana University School of MedicineIndianapolisUSA
  5. 5.Department of Molecular MedicineUniversity of Texas Health Science Center at San AntonioSan AntonioUSA
  6. 6.University of Kansas Medical CenterKansas CityUSA
  7. 7.Center for Computation Biology and BioinformaticsIndiana University School of MedicineIndianapolisUSA
  8. 8.Medical Sciences ProgramIndiana University School of MedicineBloomingtonUSA
  9. 9.Department of Cellular and Integrative PhysiologyIndiana University School of MedicineIndianapolisUSA
  10. 10.Department of Obstetrics and GynecologyIndiana University School of MedicineIndianapolisUSA

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