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Next Generation Sequencing identifies differential genes regulated by FTSJ1 overexpression

ABSTRACT: Next Generation Sequencing identifies differential genes regulated by FTSJ1 overexpression

PROVIDER: PRJNA611060 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR11263433_1.fastq.gz	Fastqsanger.gz
	SRR11263433_2.fastq.gz	Fastqsanger.gz
	SRR11263434_1.fastq.gz	Fastqsanger.gz
	SRR11263434_2.fastq.gz	Fastqsanger.gz
	SRR11263435_1.fastq.gz	Fastqsanger.gz

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Next Generation Sequencing identifies differential genes regulated by FTSJ1 overexpression

Project description:We report the application of RNA-sequencing for high-throughput profiling of transcriptomes in PC9 cells transfected with stably expressed FTSJ1.

2020-05-19 | GSE146604 | GEO

The ribose methylation enzyme FTSJ1 has a conserved role in neuron morphology and learning performance

Project description:FTSJ1 is a conserved human 2’-O-methyltransferase (Nm-MTase) that modifies several transfer RNAs (tRNAs) at position 32 and the wobble position 34 in the AntiCodon Loop (ACL). Its loss of function has been linked to Non-Syndromic X-Linked Intellectual Disability (NSXLID), and more recently to cancers. However, the molecular mechanisms underlying these pathologies are currently unclear. Here we report a novel FTSJ1 pathogenic variant from a NSXLID patient. Using blood cells derived from this patient and other affected individuals carrying FTSJ1 mutations, we performed an unbiased and comprehensive RiboMethSeq analysis to map the ribose methylation (Nm) on all tRNAs and identify novel targets. In addition, we performed a transcriptome analysis in these cells and found that several genes previously associated with intellectual disability and cancers were deregulated. We also found changes in the miRNA population that suggest potential cross-regulation of some miRNAs with these key mRNA targets. Finally, we show that differentiation of FTSJ1-depleted human neuronal progenitor cells (NPC) into neurons displays long and thin spine neurites compared to control cells. These defects are also observed in Drosophila and are associated with long term memory deficit in this organism. Altogether, our study adds insight into FTSJ1 pathologies in human by the identification of novel FTSJ1 targets and the defect in neuron morphology.

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Next Generation Sequencing identifies differentially expressed genes regulated by overexpression of tRF AS-tDR-007333 in A549 cells

Project description:Next Generation Sequencing identifies differentially expressed genes regulated by overexpression of tRF AS-tDR-007333 in A549 cells

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P0.5 WT or Ftsj1 KO mouse brain or liver total mRNA or ribosome-contained mRNA

Project description:P0.5 WT or Ftsj1 KO mouse brain or liver ribosome-contained mRNAs or total mRNAs, and were sequenced using MiSeq and HiSeq.

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WT or Ftsj1 KO mouse brain

Project description:WT or Ftsj1 KO mouse brain

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Next Generation Sequencing identifies differentially expressed genes regulated by overexpression of tRF AS-tDR-007333 in A549 cells

Project description:Our previous study identified that a novel tRNA-derived fragment (tRF) termed AS-tDR-007333 was up-regulated in non-small cell lung cancer (NSCLC), but the molecular mechanisms of AS-tDR-007333 in NSCLC were unclear. Here, we used RNA-seq for high-throughput profiling of transcriptomes in A549 cells transfected with AS-tDR-007333, in order to find differentially expressed genes regulated by AS-tDR-007333.

2022-05-25 | GSE184690 | GEO

FTSJ1 patients RNASeq

Project description:RNASeq: FTSJ1 tRNA Nm-MTase: new human targets and role in the regulation of brain-specific genes

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FTSJ1 patients RiboMethSeq

Project description:RiboMethSeq FTSJ1 tRNA Nm-MTase: new human targets and role in the regulation of brain-specific genes

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Next Generation Sequencing explore the relationship between apolipoprotein AV (APOAV) overexpression and insulin resistance in hepatocytes.

Project description:We sought to explore the relationship between apolipoprotein AV (APOAV) overexpression and insulin resistance in hepatocytes. The insulin-resistant HepG2 cell model was constructed and then APOAV overexpressed HepG2 cells (B-M) were induced by infecting with recombinant adenovirus vector. Microarray data were developed from B-M samples compared with negative controls (A-con) and the microarray data were analyzed by bioinformatic methods. APOAV overexpression induced 313 up-regulated genes and 563 down-regulated ones in B-M sample. The differentially expressed genes (DEGs) were significantly classified in Fat digestion and absorption pathway. Protein-protein interaction network was constructed and AGTR1 (angiotensin II receptor type 1) and P2RY2 (purinergic receptor P2Y, G-protein coupled 2) were found to be the significant nodes closely related with G-protein related signaling. Additionally, overexpression of APOAV could change the expression of Glut4 and release insulin resistance of hepatic cells. Thus, APOAV overexpression may prevent the insulin resistance in liver cells by mediating the genes such as AGTR1 and P2RY2.

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Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare transgene-derived OsAFB6 overexpression mutant transcriptome profiling (RNA-seq) to microarray Methods: young panicle(<1mm) mRNA profiles of 80 individual plants of OsAFB6 overexpression mutants and the correspondinng negative plants during the same transgenic event as control were generated by deep sequencing, in two replicate, using Illumina HiSeq 2000. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. Results: Using an optimized data analysis workflow, we found 59 genes were upregulated and 229 genes were down regulated in OsAFB6 overexpression mutant. Conclusions: Our study represents the first detailed analysis of young panicle transcriptomes of OsAFB6 overexpression mutant, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

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