How Individual Steps Bias RNA-Seq Data

A Team led by researchers at Centre de Regulació Genòmica (CRG), Spain analysed multiple RNA-Seq experiments, involving different sample preparation protocols and sequencing platforms: they broke them down into their common—and currently indispensable—technical components:

(reverse transcription, fragmentation, adapter ligation, PCR amplification, gel segregation and sequencing),

and investigated how such different steps influence abundance and distribution of the sequenced reads. For each of those steps, they developed universally applicable models, which can be parameterised by empirical attributes of any experimental protocol.

flux simulatorThe researchers models are implemented in a computer simulation pipeline called the Flux Simulator, and they show that read distributions generated by different combinations of these models reproduce well corresponding evidence obtained from the corresponding experimental setups. They further demonstrate that our in silico RNA-Seq provides insights about hidden precursors that determine the final configuration of reads along gene bodies; enhancing or compensatory effects that explain apparently controversial observations can be observed. Moreover, their simulations identify hitherto unreported sources of systematic bias from RNA hydrolysis, a fragmentation technique currently employed by most RNA-Seq protocols.

  • Griebel T, Zacher B, Ribeca P, Raineri E, Lacroix V, Guigó R, Sammeth M. (2012) Modelling and simulating generic RNA-Seq experiments with the flux simulator. Nucleic Acids Res [Epub ahead of print]. [article]