Fig. 1: Adaptive sampling enriches for transcripts of interest.
From: Direct RNA sequencing coupled with adaptive sampling enriches RNAs of interest in the transcriptome
a Schematic showing the nanopore adaptive sampling sequencing workflow. b Schematic of four transcripts that were generated by in vitro transcription (IVT), and then used for adaptive sampling sequencing. The four genes are labeled with different colors as shown. c Table showing the parameters for break time (decision times) and the obtained read numbers during different decision times for adaptive sampling in bulk sequencing and in adaptive sampling at different decision times. The base counts from Adaptive sequencing are labeled orange. d IGV plots showing the distribution of read coverage along the length of GAPDH, ACTB, 18S rRNA, and ENO2 after GAPDH enrichment by adaptive sampling. We tested different decision times (1, 3.5, or 6.5 s) for adaptive sampling. Left: Schematic showing parameters for bulk and adaptive sequencing, using 50% of the pores of a flow cell for bulk sequencing and 50% of the pores for adaptive sequencing at 1 s (e), 3.5 s (f), and 6.5 s (g), decision times. Left Middle: Bar plots showing the total number of bases obtained on GAPDH, ENO2, 18S rRNA, and ACTB using adaptive sampling and bulk sequencing. Right Middle: Bar plots showing the number of reads mapped to GAPDH, ENO2, 18S rRNA, and ACTB in normal bulk sequencing (from 50% of the pores) and in adaptive sampling sequencing (from the other 50% of the pores) at different decision times. Right: Bar plots showing the percentage of accepted reads in adaptive sequencing as compared to bulk sequencing for each transcript. The color labels are as shown. h Bar plots showing the number of reads from GAPDH, ENO2, 18S rRNA, and ACTB in the rejected reads pool at different decision times. The color labels are as shown.
