Efficient targeted transcript discovery via array-based normalization of RACE libraries

Abstract

RACE (Rapid Amplification of cDNA Ends) is a widely used approach for transcript identification. Random clone selection from the RACE mixture, however, is an ineffective sampling strategy if the dynamic range of transcript abundances is large. Here, we describe a strategy that uses array hybridization to improve sampling efficiency of human transcripts. The products of the RACE reaction are hybridized onto tiling arrays, and the exons detected are used to delineate a series of RT-PCR reactions, through which the original RACE mixture is segregated into simpler RT-PCR reactions. These are independently cloned, and randomly selected clones are sequenced. This approach is superior to direct cloning and sequencing of RACE products: it specifically targets novel transcripts, and often results in overall normalization of transcript abundances. We show theoretically and experimentally that this strategy leads indeed to efficient sampling of novel transcripts, and we investigate multiplexing it by pooling RACE reactions from multiple interrogated loci prior to hybridization.