We describe a computational approach that integrates GRO-seq and RNA-seq data to annotate long noncoding RNAs (lncRNAs), with increased sensitivity for low-abundance lncRNAs. We used this approach to characterize the lncRNA transcriptome in MCF-7 human breast cancer cells, including >700 previously unannotated lncRNAs. We then used information about the (1) transcription of lncRNA genes from GRO-seq, (2) steady-state levels of lncRNA transcripts in cell lines and patient samples from RNA-seq, and (3) histone modifications and factor binding at lncRNA gene promoters from ChIP-seq to explore lncRNA gene structure and regulation, as well as lncRNA transcript stability, regulation, and function. Functional analysis of selected lncRNAs with altered expression in breast cancers revealed roles in cell proliferation, regulation of an E2F-dependent cell-cycle gene expression program, and estrogen-dependent mitogenic growth. Collectively, our studies demonstrate the use of an integrated genomic and molecular approach to identify and characterize growth-regulating lncRNAs in cancers.
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