Transcriptome studies based on quantitative sequencing can estimate levels of gene expression by measuring target RNA abundance in sequencing libraries. Sequencing costs are proportional to the total number of sequenced reads, and in order to cover rare RNAs, considerable quantities of abundant and identical reads are needed. This major limitation can be addressed by depleting a proportion of the most abundant sequences from the library. However, such depletion strategies involve either extra handling of the input RNA sample or use of a large number of reverse transcription primers, termed not-so-random (NSR) primers, which are costly to synthesize. Taking advantage of the high tolerance of reverse transcriptase to mis-prime, we found that it is possible to use as few as 40 pseudo-random (PS) reverse transcription primers to decrease the rate of undesirable abundant sequences within a library without affecting the overall transcriptome diversity. PS primers are simple to design and can be used to deplete several undesirable RNAs simultaneously, thus creating a flexible tool for enriching transcriptome libraries for rare transcript sequences.
Keywords: high-throughput sequencing; nanoCAGE; rRNA; undesirable sequences.