Exposing layers of transcriptome complexity and its use in dissecting complex traits

Genome-wide pervasive transcription has been reported in many eukaryotic organisms, revealing a highly interleaved transcriptome organization that involves hundreds of non-coding RNAs with the potential to condition phenotypes. These include SUTs (Stable Unannotated Transcripts) and CUTs (Cryptic Unstable Transcripts) that we identified in yeast by profiling the transcriptome in multiple conditions, mutants, and strain backgrounds. We have shown that most non-coding RNAs (SUTs and CUTs) initiate from bidirectional transcription of promoters, and that gene looping helps to maintain the directionality of transcription from these promoters. We have also characterized antisense transcripts genome-wide, demonstrating that they play a key role in shutting off gene expression and extending its variability. In addition to complexity that exists across the genome in terms of expressed regions on each strand, there is an extensive hidden layer of complexity found in alternative overlapping transcripts at each individual gene. Here I will discuss our findings in this new area and how these transcripts add functionality to cells and populations. In addition, I will show how we apply transcriptome profiling in QTL mapping to understand the genetic basis of complex traits with the aim to identify transcriptional intervention points that enable modulation of phenotypes.