Integration of RNA-seq and Ribosome Profiling to Characterize Transcriptional and Translational Estrogen Responses of Genes in Human Breast Cancer
BackgroundEstrogen is a hormone that is frequently essential in breast cancer to drive key transcriptional programs by interacting with the estrogen receptor alpha that upregulates proliferative and oncogenic genes and represses apoptotic and tumor suppressor genes. Protein-coding targets of estrogen regulation in breast cancer are well-defined. However, long non-coding RNA (lncRNA) genes account for the majority of human gene catalogs. The coding status of these genes – their accidental, or
... r accidental, or regulated, translation by ribosomes, under the influence of estrogen – remains a controversial topic. MethodsHere, we performed comprehensive transcriptome analysis using RNA-Seq, as well as ribosome profiling using Ribo-Seq, on the same samples: biological replicates of human estrogen receptor alpha (ERa) positive MCF7 breast cancer cells before and after estrogen treatment. We correlated these two datasets, globally highlighting protein-coding and lncRNA differentially expressed genes and transcripts that were positively as well as negatively responsive to estrogen, separately at the transcriptional level and the translational (as approximated by ribosome binding) level.ResultsOur data showed that some transcripts were more robustly detected in RNA-Seq than in the ribosome-profiling data, and vice versa, suggesting distinct gene-specific estrogen responses at the transcriptional and the translational level, respectively. Certain differentially expressed transcripts may point to the regulation of alternative splicing by estrogen. Several pseudogenes were co- and anti-regulated with their cancer-functional parental genes. Gene ontology analysis highlighted cancer-relevant pathways enriched after estrogen treatment in cells.ConclusionsOur study represents a significant advance in the estrogen receptor biology, because we demonstrated global effects of estrogen on splicing and translation that are distinct from, and not always correlated with, its effects on transcription, and that differ globally for protein-coding and lncRNA genes. We have also highlighted for the first time the transcriptional and translational response of expressed pseudogenes to estrogen, pointing to new perspectives for biomarker and drug-target development for breast cancer in future.