Transfection-based genomic readout for identifying rare transcriptional splice variants

Understanding the transcriptome, defined as the complete transcriptional component of the genome, is far more complex than originally considered. Even with the near fully resolved human and mouse genomes, for which extensive databases of transcribed sequence data (e.g., expressed sequence tags) are available, it is presently not possible to experimentally recover or computationally predict the full range of transcription products that derive from multiexon genes. Many genes are tightly regulated, which could include alternative processing of RNA, and lead to significant underrepresentation of many transcripts. A multitude of factors in addition to cell lineage- and developmental stage-specific expression as well as shortcomings in computational methods result in a less than complete understanding of transcriptional complexity. Here, we describe an approach to predict and evaluate a more complete repertoire of transcriptional products that derive from specific genetic loci with attention toward analysis of immune receptor genes. This approach is particularly useful in identifying gene products, including alternative splice forms, that originate from complex multigene families.