A comparison of RNA extraction and sequencing protocols for detection of small RNAs in plasma
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE118125 | GEO | 2019/05/21
REPOSITORIES: GEO
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2024-01-01 | GSE246437 | GEO
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2020-05-31 | GSE141658 | GEO
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2019-09-27 | GSE133719 | GEO
Project description:Purpose: To determine the optimal RNA extraction and library generation protocols for mouse hippocampal tissue acquired by laser capture microdissection (LCM). Methods: Hippocampal subregion CA2 was captured from eight micron fresh frozen brain sections from AMIGO2 EGFP mice. Total RNA was extracted using the PicoPure (LCM standard) and QIAGEN micro RNeasy RNA extraction kits. RNA quantity and quality was assessed using a Bioanalzyer. Resulting RNA was used to generate cDNA libraries using NuGEN or SMARTer low input RNA-Seq library kits. We compared the effects of RNA quality and library generation approach to determine the methods that detected the greatest number of genes/exons with even coverage using minimal rounds of PCR. Results: We determined that the QIAGEN RNA extraction kit resulted in far superior RNA compared to the Picopure RNA extraction kit. We also found the NuGEN library generation kit that depletes ribosomal RNA towards the end of the protocol, led to higher cDNA library yields that required fewer rounds of PCR while providing even gene coverage and detection.
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2022-02-21 | MODEL2202170007 | BioModels
Project description:Total RNA was isolated from serum samples by the Qiagen miRNeasy Serum/Plasma extraction kit and QIAcube automation. All samples were quantified using the Nanodrop spectrophotometer prior to plating. Small RNA-seq libraries were prepared using the Norgen Biotek Small RNA Library Prep Kit and then sequenced on the Illumina NextSeq 500 platform at 51bp single end reads. ExceRpt was employed to assess the read quality and annotate miRNAs. The read count was log transformed and normalized by quantile normalization.
2020-07-08 | GSE134897 | GEO
Project description:Comparison of DNA extraction kits for MiSeq sequencing
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Project description:RNA-seq workflows have become progressively more efficient over time however, RNA extraction still remains a significant bottleneck. For small numbers of sample, highly efficient RNA extraction is simple to perform but becomes costly and laborious at the scale of hundreds of samples. Our prior work has demonstrated that qPCR can be accurately performed using bulk cells samples lysate instead of RNA extraction. We combined this method with the recently developed simple method for rapid RNA-seq library prep; Smart-3SEQ (Foley et al., 2019) and hypothesized that bulk RNA-seq can be performed in a multi-well plate format, and at low cost by performing RNA-seq library prep cDNA synthesis using in-lysate RNA followed by Smart-3SEQ. The result shows success of our approach in various levels: 1) all quality control measures were achieved, 2) Gene expression profiles, gene differential expression and the response patterns reported by in-lysate and purified RNA library highly correlate with each other, and 3) in-lysate RNA-seq library prep performed similar to the gold standard used here (Illumina Truseq) for DEG calling.
2021-01-22 | GSE164650 | GEO
Project description:Entamoeba histolytica membrane proteins are important players in the parasite’s pathogenicity. However, most of the proteins have not been identified. This study reports the membrane proteins extracted using three extractions methods: two commercial kits (ProteoExtract® from Calbiochem and ProteoPrep® from Sigma), and a conventional laboratory method. The resulting membrane fractions (MF) and cytosolic fractions (CF)were analysed using LC-ESI-MS/MS. The proteins identified in at least two out of three biological replicates revealed a total of 490, 492, and 587 MF proteins extracted using the ProteoExtract® kit, ProteoPrep® kit and conventional method, respectively. Meanwhile, 487, 611 and 343 proteins were identified in the CF extracted using the ProteoExtract® kit, ProteoPrep® kit and conventional method, respectively. Analysis of the identified MF and CF proteins extracted by the respective extraction kits suggests that the ProteoPrep® extraction kit was the most selective in separating MF and CF among the three extraction methods.
2018-10-16 | PXD010171 | Pride
Project description:Background & aims: MicroRNAs (miRNAs) encapsulated in EVs are potential diagnostic and prognostic biomarkers. However, discrepancies on miRNA patterns and their validation are still frequent due to differences in sample origin, EVs isolation, miRNA extraction and sequencing methods. Selecting appropriate EVs isolation methods is therefore a critical step for miRNA-based biomarker discovery. The aim of the present study is to find the most suitable EVs isolation method for miRNAs sequencing adequate for clinical application. Material & Methods EVs were isolated by Size Exclusion Chromatography (SEC), iodixanol gradients (GRAD) and the combination of both (SEC+GRAD), using the same plasma sample, in triplicate isolation assays. Isolated EVs were characterized and RNA was extracted. Three different protocols for miRNA library preparation were compared (NEBNext, NEXTFlex and SMARTer smRNA-seq) and miRNAs encapsulated on EVs were sequenced using NextSeq 500 system (Illumina). Finally, the yield, abundance and diversity of miRNAs using the three different EVs isolation protocols were analyzed and compared between them. Results The majority of lipoproteins, total cholesterol and plasma proteins were removed from the EVs-containing fractions by using SEC, GRAD, and SEC+GRAD. SEC method recovered a larger amount of EVs followed by GRAD and SEC+GRAD, while GRAD and SEC+GRAD yielded the purest vesicles. NEBNext was the library preparation kit that showed the highest reproducibility among replicas, higher number of reads corresponding to miRNAs and more different miRNAs, followed by NEXTFlex and SMARTer smRNA-seq. GRAD method showed the highest reproducibility among replicas, a higher number of reads corresponding to miRNAs and more different miRNAs, followed by SEC and SEC+GRAD methods. Conclusions These results render the GRAD method to isolate EVs as one of the most appropriate to detect miRNAs from Evs.
2023-04-26 | GSE223838 | GEO