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The tRNA derived fragments (tRFs) expression profiles in human aortic smooth muscle cells (HASMCs)

ABSTRACT: The tRNA derived fragments (tRFs) expression profiles in human aortic smooth muscle cells (HASMCs)

PROVIDER: PRJNA877112 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR21431762.fastq.gz	Fastqsanger.gz
	SRR21431763.fastq.gz	Fastqsanger.gz
	SRR21431764.fastq.gz	Fastqsanger.gz
	SRR21431765.fastq.gz	Fastqsanger.gz
	SRR21431766.fastq.gz	Fastqsanger.gz

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The tRNA derived fragments (tRFs) expression profiles in human aortic smooth muscle cells (HASMCs)

Project description:To explore the potential involvement of tRNA derived fragments (tRFs) in the human aortic vascular smooth muscle cells (HASMCs), we conducted tRFs profiling in three pairs of differentiated HASMCs (treated with PBS) and dedifferentiated HASMCs (treated with PDGF-BB 50 ng/ml) by microarray. Our results showed that tRFs were aberrantly expressed in dedifferentiated HASMCs compared with differentiated HASMCs and provided potential targets for novel insights into VSMC differentiation or vascular remodeling diseases.

2023-01-31 | GSE212737 | GEO

Transciptomic analysis of human aortic smooth muscle cells (HASMCs) with BAF60a overexpression

Project description:We used NGS-derived transcriptome profiling (RNA-seq) to compare the transcriptional difference between human aortic smooth muscle cells (HASMCs) infected with 20MOI adenovirus encoding human BAF60a (AdBAF60a) or GFP (AdGFP)

2020-11-21 | GSE153447 | GEO

Transciptomic analysis of human aortic smooth muscle cells (HASMCs) with BAF60a knockdown

Project description:We used NGS-derived transcriptome profiling (RNA-seq) to compare the transcriptional difference between human aortic smooth muscle cells (HASMCs) transfected with 30nM siRNA targeting BAF60a (siBAF60a) or non-targeting siRNA (siControl)

2020-11-21 | GSE153448 | GEO

Genome-wide maps of chromatin state changes in BAF60a deficient human aortic smooth muscle cells (HASMCs)

Project description:We compared BRG1 binding and histone modification states between siControl and siBAF60a transfected human aortic smooth muscle cells (HASMCs) through ChIP sequencing.

2020-11-21 | GSE153446 | GEO

Genome-wide maps of chromatin state changes in BAF60c deficient human aortic smooth muscle cells (HASMCs)

Project description:We compared BRG1 binding and 4 histone modification states between siControl and siBAF60c transfected human aortic smooth muscle cells (HASMCs) through ChIP sequencing (ChIP-seq).

2022-09-23 | GSE180583 | GEO

tRNA fragments (tRFs) analysis of small RNA libraries

Project description:tRNA fragments (tRFs) populations analysis in mutants affecting tRNAs processing and tRNA methylation

| PRJEB35713 | ENA

Maternal Serum tRNA-derived Fragments (tRFs) as Potential Candidates for Diagnosis of Fetal Congenital Heart Disease

Project description:Background: Congenital heart disease (CHD) is one of the most predominant birth defects that cause infant death worldwide. The timely and successful surgical treatment of CHD on newborns after delivery requires accurate detection and reliable diagnosis during pregnancy. However, there are no biomarkers that can serve as an early diagnostic factor for CHD patients. tRNA-derived fragments (tRFs) have been reported to play an important role in the occurrence and progression of numerous diseases, but their roles in CHD remains unknown. Methods: High-throughput sequencing was performed on the peripheral blood of pregnant women with abnormal fetal heart and normal fetal heart, and 728 differentially expressed tRFs/tiRNAs were identified, among which the top 18 tRFs/tiRNAs were selected as predictive biomarkers of CHD. Then, quantitative reverse transcriptase polymerase chain reaction verified the expression of tRFs/tiRNAs in more clinical samples, and the correlation between tRFs/tiRNAs abnormalities and CHD was analyzed. Results: tRF-58:74-Gly-GCC-1 and tiRNA-1:35-Leu-CAG-1-M2 may be promising biomarkers. Through further bioinformatics analysis, we predicted that TRF-58:744-GLy-GCC-1 could induce CHD by influencing biological metabolic processes. Conclusions: our results provide a theoretical basis for the abnormally expressed tRF-58:74-Gly-GCC-1 in maternal peripheral blood as a new potential biomarker for the accurate diagnosis of CHD during pregnancy.

2023-03-01 | GSE221349 | GEO

Transciptome analysis of human aortic smooth muscle cells (HASMCs) with BAF60c knockdown

Project description:HASMCs were transfected with BAF60c siRNA (siBAF60c, 20um) or control siRNA (siControl) for 48 hours, and serum-starved for 24 hours , followed by RNA-sequencing

2022-09-23 | GSE180584 | GEO

Identity transcript factor EB (TFEB) target genes in human aortic smooth muscle cells (HASMCs)

Project description:Using ChIP-Seq technology, we identitied novel target of TFEB in HASMCs.

2020-11-21 | GSE137575 | GEO

Serum tRNA-derived fragments (tRFs) as potential candidates for diagnosis of non-triple-negative breast cancer

Project description:Breast cancer is one of the most common cancers in the world and non-triple-negative breast cancer (non-TNBC) accounts for 80-90% of all invasive breast cancers. Early detection of breast cancer is considered as key to successful treatment. Conventionally，breast imaging and needle core biopsy are used for detection and monitoring of disease progression. However, small volume changes may be ignored on imaging and traditional biopsy is spatially and temporally limited, leading to a significant lag time in detecting cancer progression. This thus prompted renewed focus on early and accurate diagnosis. In this article, we committed to investigate whether there exists accurate molecule in peripheral blood which can help diagnose breast cancer. tRNA-derived fragments (tRFs) have been reported to be involved in many pathological processes, but whether it can serve as biomarkers for the diagnosis of breast cancer remains unclear. Using high-throughput sequencing technology, we identified 4021 differentially expressed tRFs in normal breast epithelial cell lines and non-triple-negative breast cancer cell lines and 8 tRFs were selected to construct a signature to predict the non-TNBC. Further, qRT-PCR was conducted to verify its expression and to analyze the correlation between dysregulated tRFs and breast cancer. The results indicated that tDR-7816, tDR-5334, tDR-4733 might be promising biomarkers. Through further bioinformatics analysis, we predicted that tDR-7816 influences xenobiotic metabolic process that support the oncogenesis of breast cancer. Taken together, our results provide a rationale for using circulating tDR-7816 expression as a novel potential biomarker to diagnose early non-TNBC patients.

2019-10-30 | GSE134992 | GEO

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