Pattern recognition in the landscape of seemingly random chimeric transcripts

The molecular and functional diversity generated by chimeric transcripts (CTs) that are derived from two genes is indicated to contribute to tumor cell survival. Several gaps yet exist. The present research is a systematic study of the spectrum of CTs identified in RNA sequencing datasets of 160 ovarian cancer samples in the The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov). Structural annotation revealed complexities emerging from chromosomal localization of partner genes, differential splicing and inclusion of regulatory, untranslated regions. Identification of phenotype-specific associations further resolved a dynamically modulated mesenchymal signature during transformation. On an evolutionary background, protein-coding CTs were indicated to be highly conserved, while non-coding CTs may have evolved more recently. We also realized that the current premise postulating structural alterations or neighbouring gene readthrough generating CTs is not valid in instances wherein the parental genes are genomically distanced. In addressing this lacuna, we identified the essentiality of specific spatiotemporal arrangements mediated gene proximities in 3D space for the generation of CTs. All these features together suggest non-random mechanisms towards increasing the molecular diversity in a cell through chimera formation either in parallel or with cross-talks with the indigenous regulatory network.

Automated summary

This study systematically investigates the spectrum of chimeric transcripts (CTs) in ovarian cancer samples. The results reveal the complex structures of CTs, influenced by chromosomal localization, differential splicing, and regulatory non-coding regions. The study also identifies associations between CTs and specific phenotype features during tumor transformation. Furthermore, it suggests that protein-coding CTs are highly conserved in evolution, while non-coding CTs may have evolved more recently. Additionally, the study highlights the importance of spatial arrangement in 3D space for the generation of CTs.