Competitive Kinetics of ptRNA Substrates

ptRNAs and ptRNA^Met with randomized leader sequences were produced by in vitro transcription from PCR-generated templates. RNase P processing reactions were performed with 1 μM ptRNA and 5 nM RNase P holoenzyme (equimolar RNase P RNA and C5). Product and unreacted ptRNA were separated by PAGE. cDNA libraries for Illumina sequencing were prepared from unreacted ptRNA at each given timepoint. Primers with degenerate barcodes were used to detect biased PCR amplification of certain sequences. Sequencing was performed on an Illumina GA2. Relative rate constants ^rk for individual substrate variants were calculated from changes in the distribution of substrates over time, using a multiple turnover reaction scheme for competitive substrate kinetics, which was extended to several thousand substrates. Computational modeling for the rules of substrate discrimination was performed by ordinary least squares regression of the matrix of values for ln(^rk) for each sequence variant according to four models of increasing complexity. The quality of the different models was judged by the correlation coefficient between a dataset calculated from values obtained from the regression analysis and the set of experimentally obtained values for ln(^rk).