R-loops are three-stranded RNA:DNA hybrid structures essential for many normal and pathobiological processes. Previously, we generated a quantitative R-loop forming sequence (RLFS) model, quantitative model of R-loop-forming sequences (QmRLFS) and predicted ∼660 000 RLFSs; most of them located in genes and gene-flanking regions, G-rich regions and disease-associated genomic loci in the human genome. Here, we conducted a comprehensive comparative analysis of these RLFSs using experimental data and demonstrated the high performance of QmRLFS predictions on the nucleotide and genome scales.
YENAMANDRA Surya Pavan
Invasive ductal carcinoma (IDC) is a major histo-morphologic type of breast cancer. Histological grading (HG) of IDC is widely adopted by oncologists as a prognostic factor. However, HG evaluation is highly subjective with only 50%–85% inter-observer agreements. Specifically, the subjectivity in the assignment of the intermediate grade (histologic grade 2, HG2) breast cancers (comprising ~50% of IDC cases) results in uncertain disease outcome prediction and sub-optimal systemic therapy.
The ecotropic virus integration site 1(Evi1) transcription factor, encoded in the MECOM complex locus, is implicated in several cancers, including ovarian cancer(OC). High-grade serous OC(HG-SOC) represents its most common and aggressive form. The pathobiological and clinical roles of MECOM and its products in HG-SOC are poorly understood.
The possible formation of three-stranded RNA and DNA hybrid structures (R-loops) in thousands of functionally important guanine-rich genic and inter-genic regions could suggest their involvement in transcriptional regulation and even development of diseases. Here, we introduce the first freely available R-loop prediction program called Quantitative Model of R-loop Forming Sequence (RLFS) finder (QmRLFS-finder), which predicts RLFSs in nucleic acid sequences based on experimentally supported structural models of RLFSs. QmRLFS-finder operates via a web server or a stand-alone command line tool.