title: Modeling Enzyme Processivity Reveals that RNA-Seq Libraries Are Biased in Characteristic and Correctable Ways.
abstract: Experimental procedures for preparing RNA-seq and single-cell (sc) RNA-seq libraries are based on assumptions regarding their underlying enzymatic reactions. Here, we show that the fairness of these assumptions varies within libraries: coverage by sequencing reads along and between transcripts exhibits characteristic, protocol-dependent biases. To understand the mechanistic basis of this bias, we present an integrated modeling framework that infers the relationship between enzyme reactions during library preparation and the characteristic coverage patterns observed for different protocols. Analysis of new and existing (sc)RNA-seq data from six different library preparation protocols reveals that polymerase processivity is the mechanistic origin of coverage biases. We apply our framework to demonstrate that lowering incubation temperature increases processivity, yield, and (sc)RNA-seq sensitivity in all protocols. We also provide correction factors based on our model for increasing accuracy of transcript quantification in existing samples prepared at standard temperatures. In total, our findings improve our ability to accurately reflect in vivo transcript abundances in (sc)RNA-seq libraries.
authors.affiliation: School of Life Sciences, University of Warwick, Coventry CV4 7AL, UK.
authors.forename: Nathan
authors.initials: N
authors.lastname: Archer
authors.affiliation: School of Life Sciences, University of Warwick, Coventry CV4 7AL, UK.
authors.forename: Mark D
authors.initials: MD
authors.lastname: Walsh
authors.affiliation: Department of Mathematics, Imperial College, London SW7 2AZ, UK. Electronic address: v.shahrezaei@imperial.ac.uk.
authors.forename: Vahid
authors.initials: V
authors.lastname: Shahrezaei
authors.affiliation: School of Life Sciences, University of Warwick, Coventry CV4 7AL, UK. Electronic address: d.hebenstreit@warwick.ac.uk.
authors.forename: Daniel
authors.initials: D
authors.lastname: Hebenstreit
mesh_terms: D000818:Animals; D015723:Gene Library; D051379:Mice; D012313:RNA; D017423:Sequence Analysis, RNA
chemical_list: D012313:RNA
keywords: Bayesian framework; Markov Chain Monte Carlo; RNA-seq; bias; coverage; enzyme; mathematical modeling; polymerase; processivity; reverse transcriptase