Project description:Erythrocytes and platelets have high production rates, with 1012 cells released daily into the blood stream. This output from bone-marrow residing hematopoietic stem cells is tightly regulated by transcription factors and epigenetic modifications. Whether and how non-coding RNAs such as circular RNAs (circRNAs) contribute to the differentiation and/or identity of hematopoietic cells is to date not well understood. We recently published a circRNA expression map of hematopoietic cells, which showed that erythrocytes and platelets contain the highest levels and numbers of circRNAs. Whether and how circRNA expression alters during differentiation of erythrocytes and platelet precursors is however not known. Therefore, we here provide the first detailed and comprehensive analysis of circRNA expression during red blood cell and megakaryocyte differentiation. CircRNA expression significantly increased during erythroid precursor differentiation into red blood cells, and in differentiating megakaryocytes, in particular upon enucleation. Many functions have been attributed to circRNAs. To dissect their possible function in hematopoietic differentiation, we first focused on translation regulation. We compared circRNA and mRNA expression to ribosomal foot printing data, and found that only 20 (2.6%) circRNAs associated with translation regulation of their mRNA counterparts. We also identified thousands of putative open reading frames in circRNAs, suggesting that circRNAs may also encode proteins. However, deep ribosome-footprinting sequencing data and in-depth mass spectrometry data analysis provided little evidence for translation of endogenously expressed circRNAs in erythroblasts, megakaryocytes and platelets. In conclusion, circRNAs in platelets and red blood cells are highly abundant and alter their expression profile during differentiation, yet their contribution to regulate cellular processes remains enigmatic.
Project description:Erythrocytes and platelets have high production rates, with 1012 cells released daily into the blood stream. This output from bone-marrow residing hematopoietic stem cells is tightly regulated by transcription factors and epigenetic modifications. Whether and how non-coding RNAs such as circular RNAs (circRNAs) contribute to the differentiation and/or identity of hematopoietic cells is to date not well understood. We recently published a circRNA expression map of hematopoietic cells, which showed that erythrocytes and platelets contain the highest levels and numbers of circRNAs. Whether and how circRNA expression alters during differentiation of erythrocytes and platelet precursors is however not known. Therefore, we here provide the first detailed and comprehensive analysis of circRNA expression during red blood cell and megakaryocyte differentiation. CircRNA expression significantly increased during erythroid precursor differentiation into red blood cells, and in differentiating megakaryocytes, in particular upon enucleation. Many functions have been attributed to circRNAs. To dissect their possible function in hematopoietic differentiation, we first focused on translation regulation. We compared circRNA and mRNA expression to ribosomal foot printing data, and found that only 20 (2.6%) circRNAs associated with translation regulation of their mRNA counterparts. We also identified thousands of putative open reading frames in circRNAs, suggesting that circRNAs may also encode proteins. However, deep ribosome-footprinting sequencing data and in-depth mass spectrometry data analysis provided little evidence for translation of endogenously expressed circRNAs in erythroblasts, megakaryocytes and platelets. In conclusion, circRNAs in platelets and red blood cells are highly abundant and alter their expression profile during differentiation, yet their contribution to regulate cellular processes remains enigmatic.
Project description:To further explore the differential expression profile of circRNA in human bladder cancer, we have employed circRNA microarray expression profiling as a discovery platform to identify potential differential expression profile of circRNA between human bladder cancer cell (UM-UC-3 cell) and urothelial immortalized cell (SV-HUC-1 cell). Results showed a large number of differentially expressed circRNAs. In this study, we screened the eight circRNAs that were most significantly downregulated in the circRNA differential expression profile of bladder cancer cells, designed primers across the splice site, and detected them using qPCR. We found that hsa_circ_0047253 (circLAMA3) was most significantly decreased in the bladder cancer cells, then its biological function and action mechanism have been further explored in this study.
Project description:This study aimed to provide a characterization of morphologically-altered red blood cells (RBCs) and to compare their properties to those of long-stored morphologically normal RBCs and to short-stored RBCs. For proteomics experiments, RBC concentrates stored in blood bank conditions were submitted to a CFSE staining protocol that allows specific sorting of morphologically-altered (CFSEhigh) and normal (CFSElow) RBC subpopulations. Proteome of erythrocytes and ghosts were analyzed at day 3-10 (short-stored, CFSElow RBC subpopulation) and day 40-44 (long-stored, CFSEhigh and CFSElow RBC subpopulations) of storage by a label free quantification approach.
Project description:To compare the circRNA expression profile of diabetic retinopathy with that of diabetes mellitus and controls, peripheral blood mononuclear cell samples were obtained and extracted from healthy controls and diabetes mellitus patients (with or without diabetic retinopathy). CircRNA Capital Bio Technology Human CircRNA Array v2 was performed to detect circRNA expression profiles. To further check differentiate circRNA, qRT_PCR assay was performed to detect the level of 5 candidates.
Project description:Periventricular white matter damage (PWMD) is the principal pathological type of brain damage in premature. It causes irreversible damage to the overall function of the central nervous system resulting in cerebral palsy, convulsions, epilepsy, cognitive, motor dysfunction and other late effects. CircRNAs are participate in the biological processes underlying many nervous system diseases. However, the circRNA expression profile of peripheral venous blood of premature infants with PWMD is not completely understood. Three premature with white matter damage (PWMD group) and three infants without brain injury (Normal group) were enrolled. Peripheral venous blood was collected from both groups for extraction of RNA and circRNA sequencing was performed. The RNA-seq technique was used to screen the differentially expressed circRNA in peripheral blood of infants with PWMD. The accuracy of sequencing results was verified by quantitative reverse transcription polymerase chain reaction (q-PCR) to the differentially express partial circRNA in the sequencing results. Bioinformatics analysis of Host genes was performed with differential circRNA. TargetScan and Miranda were used to predict circRNA-binding miRNAs and mapped into a circRNA-miRNA co-expression network. There were 119 significantly different circRNAs as compared with premature without brain injury, along with 1 circRNA was up-regulated and 4 circRNAs were down-regulated expression in the PWMD group. Combined with the existing research results and bioinformatics analysis results after sequencing, it is suggested that circRNA may regulate the occurrence and development of white matter damage in premature infants by interacting with miRNA. This first study of its kind further identified the expression profile of circRNA in peripheral blood of premature with WMD, and provide a novel targets for further investigation about the molecular mechanisms underlying PWMD and potential therapeutic intervention.
Project description:In order to identify new biomarkers for the diagnosis of rheumatoid arthritis, we used circRNA microarray technology to screen the differential expression of circRNA in peripheral blood mononuclear cells of patients with rheumatoid arthritis. We identified a total of 399 differentially expressed circRNAs in RA patients and healthy controls, of which 149 circRNAs were significantly up-regulated in RA patients and 250 were down-regulated. Among them, hsa_circRNA_101328 may be a potential biomarker for the diagnosis of RA.