Abstract
RNA sequencing (RNA-seq) has become an important tool for examining the role of the transcriptome to biological processes. While RNA-seq has been widely adopted as a popular approach in many experimental designs, from gene discovery to mechanistic validation of targets, technical issues have largely limited the use of this technique to abundantly available sample sources. However, RNA-seq is becoming increasingly utilized for more specialized applications, such as flow cytometry-sorted cells and clinical specimens, due to protocol advances enabling the use of very low input material ranging from 10 pg to 10 ng of total RNA or 1–1000 intact cells. In this chapter, we present an optimized and detailed approach to RNA-seq for use with low abundance samples.
This is a preview of subscription content, log in via an institution to check access.
References
Byron SA, Van Keuren-Jensen KR, Engelthaler DM, Carpten JD, Craig DW (2016) Translating RNA sequencing into clinical diagnostics: opportunities and challenges. Nat Rev Genet 17:257–271
Hrdlickova R, Toloue M, Tian B (2017) RNA-Seq methods for transcriptome analysis. Wiley Interdiscip Rev RNA 8
Wang Z, Gerstein M, Snyder M (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10:57–63
Shalek AK, Satija R, Adiconis X, Gertner RS, Gaublomme JT, Raychowdhury R, Schwartz S, Yosef N, Malboeuf C, Lu D, Trombetta JJ, Gennert D, Gnirke A, Goren A, Hacohen N, Levin JZ, Park H, Regev A (2013) Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells. Nature 498:236–240
Tirosh I, Izar B, Prakadan SM, Wadsworth MH 2nd, Treacy D, Trombetta JJ, Rotem A, Rodman C, Lian C, Murphy G, Fallahi-Sichani M, Dutton-Regester K, Lin JR, Cohen O, Shah P, Lu D, Genshaft AS, Hughes TK, Ziegler CG, Kazer SW, Gaillard A, Kolb KE, Villani AC, Johannessen CM, Andreev AY, Van Allen EM, Bertagnolli M, Sorger PK, Sullivan RJ, Flaherty KT, Frederick DT, Jane-Valbuena J, Yoon CH, Rozenblatt-Rosen O, Shalek AK, Regev A, Garraway LA (2016) Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352:189–196
Shalek AK, Satija R, Shuga J, Trombetta JJ, Gennert D, Lu D, Chen P, Gertner RS, Gaublomme JT, Yosef N, Schwartz S, Fowler B, Weaver S, Wang J, Wang X, Ding R, Raychowdhury R, Friedman N, Hacohen N, Park H, May AP, Regev A (2014) Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature 510:363–369
Trombetta JJ, Gennert D, Lu D, Satija R, Shalek AK, Regev A (2014) Preparation of single-cell RNA-seq libraries for next generation sequencing. Curr Protoc Mol Biol 107:4.22.21–4.22.17
Clontech Laboratories, Inc. (2017) Clontech SMART-seq ultra low input RNA kit for sequencing. http://www.clontech.com. Accessed 7 Jan 2017
Illumina, (2017) Nextera XT DNA library preparation kit. https://www.illumina.com/products/by-type/sequencing-kits/library-prep-kits/nextera-xt-dna.html. Accessed 7 Jan 2017
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC
About this protocol
Cite this protocol
Walton, K., O’Connor, B.P. (2018). Optimized Methodology for the Generation of RNA-Sequencing Libraries from Low-Input Starting Material: Enabling Analysis of Specialized Cell Types and Clinical Samples. In: DiStefano, J. (eds) Disease Gene Identification. Methods in Molecular Biology, vol 1706. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7471-9_10
Download citation
DOI: https://doi.org/10.1007/978-1-4939-7471-9_10
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-7470-2
Online ISBN: 978-1-4939-7471-9
eBook Packages: Springer Protocols