RBM6-RBM5 transcription-induced chimeras are differentially expressed in tumours

We identified three novel transcription-induced chimeras resulting from the intergenic splicing of a single RNA transcript incorporating the two neighbouring 3p21.3 tumour suppressor locus genes, RBM6 and RBM5, which encode the RNA Binding Motif protein 6 and RNA Binding Motif protein 5, respectively. Each of the three novel chimeric transcripts lacked exons 3, 6, 20 and 21 of RBM6 and exon 1 of RBM5. Differences between the transcripts were associated with the presence or absence of exon 4, exon 5 and a 17 nucleotide (nt) sequence from intron 10 of RBM6. All three chimeric transcripts incorporated the canonical splice sites from both genes (excluding the 17 nt intron 10 insertion). Differential expression was observed in tumour tissue compared to non-tumour tissue, and amongst tumour types. In breast tumour tissue, chimeric expression was associated with elevated levels of RBM6 and RBM5 mRNA, and increased tumour size. No protein expression was detected by in vitro transcription/translation.These results suggest that RBM6 mRNA experiences altered co-transcriptional gene regulation in certain cancers. The results also suggest that RBM6-RBM5 transcription-induced chimerism might be a process that is linked to the tumour-associated increased transcriptional activity of the RBM6 gene. It appears that none of the transcription-induced chimeras generates a protein product; however, the novel alternative splicing, which affects putative functional domains within exons 3, 6 and 11 of RBM6, does suggest that the generation of these chimeric transcripts has functional relevance. Finally, the association of chimeric expression with breast tumour size suggests that RBM6-RBM5 chimeric expression may be a potential tumour differentiation marker.Transcription-induced chimerism, resulting from the transcription and intergenic splicing of two consecutive genes, was previously thought to be a rare event in mammals. Recent studies, however, incorporating systematic in silico analyses