title: Technical variations in low-input RNA-seq methodologies.
abstract: Recent advances in RNA-seq methodologies from limiting amounts of mRNA have facilitated the characterization of rare cell-types in various biological systems. So far, however, technical variations in these methods have not been adequately characterized, vis-à-vis sensitivity, starting with reduced levels of mRNA. Here, we generated sequencing libraries from limiting amounts of mRNA using three amplification-based methods, viz. Smart-seq, DP-seq and CEL-seq, and demonstrated significant technical variations in these libraries. Reduction in mRNA levels led to inefficient amplification of the majority of low to moderately expressed transcripts. Furthermore, noise in primer hybridization and/or enzyme incorporation was magnified during the amplification step resulting in significant distortions in fold changes of the transcripts. Consequently, the majority of the differentially expressed transcripts identified were either high-expressed and/or exhibited high fold changes. High technical variations ultimately masked subtle biological differences mandating the development of improved amplification-based strategies for quantitative transcriptomics from limiting amounts of mRNA.
authors.affiliation: Bioinformatics and Systems Biology Graduate Program, University of California at San Diego, La Jolla, California, USA.
authors.forename: Vipul
authors.initials: V
authors.lastname: Bhargava
authors.affiliation: Next Generation Sequencing Core Facility, The Scripps Research Institute, La Jolla, California, USA.
authors.forename: Steven R
authors.initials: SR
authors.lastname: Head
authors.affiliation: Next Generation Sequencing Core Facility, The Scripps Research Institute, La Jolla, California, USA.
authors.forename: Phillip
authors.initials: P
authors.lastname: Ordoukhanian
authors.affiliation: 1] Department of Bioengineering, University of California at San Diego, La Jolla, California, USA [2] Sanford-Burnham Medical Research Institute, La Jolla, California, USA.
authors.forename: Mark
authors.initials: M
authors.lastname: Mercola
authors.affiliation: 1] Bioinformatics and Systems Biology Graduate Program, University of California at San Diego, La Jolla, California, USA [2] Department of Bioengineering, University of California at San Diego, La Jolla, California, USA [3] Departments of Cellular and Molecular Medicine and Chemistry and Biochemistry, University of California at San Diego, La Jolla, California, USA.
authors.forename: Shankar
authors.initials: S
authors.lastname: Subramaniam
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D020869:Gene Expression Profiling / Q000379:methods; D005786:Gene Expression Regulation; D051379:Mice; D015203:Reproducibility of Results; D017423:Sequence Analysis, RNA / Q000379:methods* / Q000592:standards*; D059467:Transcriptome