Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA233537 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR1104200.fastq.gz | Fastqsanger.gz | |||
| SRR1104210.fastq.gz | Fastqsanger.gz | |||
| SRR1104230.fastq.gz | Fastqsanger.gz | |||
| SRR1104240.fastq.gz | Fastqsanger.gz | |||
| SRR1104250.fastq.gz | Fastqsanger.gz |
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Project description:Background: Whole transcriptome sequencing (RNA-seq) represents a powerful approach for whole transcriptome gene expression analysis. However, RNA-seq carries a few limitations, e.g., the requirement of a significant amount of input RNA and complications led by non-specific mapping of short reads. The Ion AmpliSeqTM Transcriptome Human Gene Expression Kit (AmpliSeq) was recently introduced by Life Technologies as a whole-transcriptome, targeted gene quantification kit to overcome these limitations of RNA-seq.To assess the performance of this new methodology, we performed a comprehensive comparison of AmpliSeq with RNA-seq using two well-established next-generation sequencing platforms (Illumina HiSeq and Ion Torrent Proton). We analyzed standard reference RNA samples and RNA samples obtained from human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs). Results: Using published data from two standard RNA reference samples, we observed a strong concordance of log2 fold change for all genes when comparing AmpliSeq to Illumina HiSeq (Pearson’s r=0.92) and Ion Torrent Proton (Pearson’s r=0.92). We used ROC, Matthew’s correlation coefficient and RMSD to determine the overall performance characteristics. All three statistical methods demonstrate AmpliSeq as a highly accurate method for differential gene expression analysis. Additionally, for genes with high abundance, AmpliSeq outperforms the two RNA-seq methods. When analyzing four closely related hiPSC-CM lines, we show that both AmpliSeq and RNA-seq capture similar global gene expression patterns consistent with known sources of variations. Conclusions: Our study indicates that AmpliSeq excels in the limiting areas of RNA-seq for gene expression quantification analysis. Thus, AmpliSeq stands as a very sensitive and cost-effective approach for very large scale gene expression analysis and mRNA marker screening with high accuracy.
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Project description:Purpose: The goals of this study are to determine the effect of microRNA-17 overexpression on 20,803 human genes in RASFs using Ion ProtonTM System platform. Human RASFs from two RA patients were transfected with pre-miR-17 or NC-pre-miR for 48 h and total RNA was prepared using miRNeasy kit (Qiagen). Total RNA integrity was checked using an Agilent Technologies 2100 Bio analyzer (Santa Clara, CA). 10 ng of high quality RNA was used to make cDNA for amplification with the Ion AmpliSeq Transcriptome Human Gene Expression kit (ThermoFisher Scientific). The cDNA was subjected to 12 cycles of amplification with panel primers and barcoded with adapters as recommended. Resulting sequencing libraries were quantified by qPCR using SYBR FAST master mix from KapaBiosystems (Wilmington, MA). Sets of eight libraries were balanced, pooled and sequencing beads produced on an Ion Chef. Sequencing was performed on an Ion P1 semi-conductor sequencing chip using an Ion Proton⢠System (ThermoFisher Scientific, Grand Island, NY). Data was collected and primary analysis performed using Torrent Suite software version 5.0.3. Reads were mapped to the panel and expression values determined. R Software version R-3.2.3 was used to generate heatmap. Among the panel of 20,803 genes, the expression of 15,067 genes as shown in the representative heat map was observed in pre-miR-17 and NC-pre-miR transfected RASFs. A total of 664 significantly modulated genes (301 upregulated and 363 downregulated) using Student âtâ test were further utilized for the IPA analysis. The result of IPA predicted the protein ubiquitin pathway as a major canonical pathway affected by the differentially regulated genes. Interestingly, IPA analysis generated an interactome that showed connectivity among various ubiquitin ligases, NF-ÔB family, AP-1/cJun, 20S and 26S proteasome system. Conclusion: Our results clearly shows the major pathways affected by miR-17 overexpression in RASFs were Protein ubiquitination related. mRNA profiles of pre-miR-17 and NC-pre-miR transfected RASFs were generated by AmpliSeq, in duplicate, using Ion Proton⢠System.
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