Background: RUNX1 gene, a master regulator of the hematopoietic process, participates in pathological conditions as a partner for several genes in chromosomal translocations. One of the most frequent chromosomal translocations found in acute myeloid leukemia patients is the t(8;21), in which RUNX1 and ETO genes recombine. In RUNX1 gene, the DNA double-strand breaks that originate the t(8;21) are generated in the intron 5, specifically within three regions designated as BCR1, BCR2, and BCR3. To date, what determines that these regions are more susceptible to DNA double-strand breaks is not completely clear. In this report, we characterized RUNX1 intron 5, by analyzing DNase-seq and ChIP-seq data, available in the ENCODE Project server, to evaluate DNaseI hypersensitivity and the presence of the epigenetic mark H3K4me3 in 124 and 51 cell types, respectively.
Results: Our results show that intron 5 exhibits an epigenetic mark distribution similar to known promoter regions. Moreover, using the online tool YAPP and available CAGE data from the ENCODE Project server, we identified several putative transcription start sites within intron 5 in regions BCR2 and BCR3. Finally, available EST data was analyzed, identifying a novel uncharacterized long non-coding RNA, which is expressed in hematopoietic cell lines as shown by RT-PCR. Our data suggests that the core promoter of the novel long non-coding RNA locates within the region BCR3.
Conclusion: We identified a novel long non-coding RNA within RUNX1 intron 5, transcribed from a promoter located in the region BCR3, one of the chromosomal breakpoints of RUNX1 gene.
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http://dx.doi.org/10.1186/s40246-019-0219-1 | DOI Listing |
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College of Physics and Electronic Information, Gannan Normal University, Ganzhou, 341000, Jiangxi, China.
Long non-coding RNAs (lncRNAs) play crucial roles in numerous biological processes and are involved in complex human diseases through interactions with proteins. Accurate identification of lncRNA-protein interactions (LPI) can help elucidate the functional mechanisms of lncRNAs and provide scientific insights into the molecular mechanisms underlying related diseases. While many sequence-based methods have been developed to predict LPIs, efficiently extracting and effectively integrating potential feature information that reflects functional attributes from lncRNA and protein sequences remains a significant challenge.
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NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer Metabolism, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, 410078, China.
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