We have determined the high-resolution strand-specific transcriptome of the fission yeast S. pombe under multiple growth conditions using a novel RNA-DNA hybridization mapping (HybMap) technique. HybMap uses an antibody against an RNA-DNA hybrid to detect RNA molecules hybridized to a high-density DNA oligonucleotide tiling microarray. HybMap showed exceptional dynamic range and reproducibility, and allowed us to identify strand-specific coding, noncoding and structural RNAs, as well as previously unknown RNAs conserved in distant yeast species. Notably, we found that virtually the entire euchromatic genome (including intergenics) is transcribed, with heterochromatin dampening intergenic transcription. We identified features including large numbers of condition-specific noncoding RNAs, extensive antisense transcription, new properties of antisense transcripts and induced divergent transcription. Furthermore, our HybMap data informed the efficiency and locations of RNA splicing genome-wide. Finally, we observed strand-specific transcription islands around tRNAs at heterochromatin boundaries inside centromeres. Here, we discuss these new features in terms of organism fitness and transcriptome evolution.

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The detection of chromosomal translocations has important implications in the diagnosis, prognosis and treatment of patients with cancer. Current approaches to translocation detection have significant shortcomings, including limited sensitivity and/or specificity, and difficulty in application to formalin-fixed paraffin-embedded (FFPE) clinical samples. We developed a new approach called antibody detection of translocations (ADOT) that avoids the shortcomings of current techniques. ADOT combines a transcriptional microarray-based approach with a novel antibody-based detection method. ADOT allows for the accurate and sensitive identification of translocations and provides exon-level information about the fusion transcript. ADOT can detect translocations in poor-quality unprocessed total ribonucleic acid (RNA). Furthermore, the technique is readily generalizable to detect any potential fusion transcript, including previously undescribed fusions. We demonstrate the feasibility of ADOT by examples in which both known and unknown Ewing sarcoma translocations are identified from cell lines, tumour xenografts and FFPE primary tumours. These results demonstrate that ADOT may be an effective approach for translocation analysis in clinical specimens with significant RNA degradation and may offer a novel diagnostic tool for translocation-based cancers.