Ontology highlight
ABSTRACT:
PROVIDER: PRJNA576560 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10249392_1.fastq.gz | Fastqsanger.gz | |||
| SRR10249392_2.fastq.gz | Fastqsanger.gz | |||
| SRR10249393_1.fastq.gz | Fastqsanger.gz | |||
| SRR10249393_2.fastq.gz | Fastqsanger.gz | |||
| SRR10249394_1.fastq.gz | Fastqsanger.gz |
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Project description:Comparison of seven single cell Whole Genome Amplification commercial kits using targeted sequencing
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Project description:We compared the performance of two commercial kits (NEBNext and NEXTflex) for miRNA detection sensitivity, reliability, titration response and ability to detect differentially expressed miRNAs at different amounts of synthetic miRNAs. We observed differences in detection sensitivity between the kits, but none were able to detect the full repertoire of expected miRNAs. The reliability within the replicates of all kits was good, while larger differences were observed between the kits, although none could accurately quantify the majority of miRNAs. In a previous publication (https://doi.org/10.1080/15476286.2019.1667741; GEO accession number GSE133719) we accessed the performance of six additional miRNA library preparation kits.
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Project description:Transcriptome analysis via RNA sequencing (RNA-seq) has become a standard technique employed across a variety of biological fields of study. This rapid adoption of the RNA-seq approach has been mediated, in part, by the development of various commercial RNA-seq library preparation kits compatible with common next-generation sequencing (NGS) platforms. Generally, the essential steps of library preparation such as rRNA depletion and first-strand cDNA synthesis are tailored to a certain group of organisms (e.g. eukaryotes versus prokaryotes) or genomic GC content. Therefore, selection of appropriate commercial products is of crucial importance to capture the transcriptome of interest as closely to the native state as possible without introduction of technical bias. However, researchers rarely have the resources and time to test various commercial RNA-seq kits for their samples. In this work, we report a side-by-side comparison of RNA-seq data from the same Clostridium autoethanogenum input samples obtained using three commercial rRNA removal and strand-specific library construction products by NuGEN Technologies, Qiagen, and Zymo Research, and compare their performance with published data. While all three vendors advertise their products as suitable for prokaryotes, we found significant differences in their performance in terms of rRNA removal, strand-specificity, and, most importantly, transcript abundance distribution profiles. Notably, RNA-seq data obtained with Qiagen products were most similar to published data and delivered the best results in terms of library strandedness and transcript abundance distribution range. Our results highlight the importance of finding appropriate organism-specific workflows and library preparation products for RNA-seq studies.
2022-07-20 | GSE200959 | GEO
Project description:Generating sufficient DNA for high-throughput genetic analysis has always been a challenge for clinical settings where the amount of source DNA is limited. Multiple displacement amplification (MDA) has been proposed as a promising candidate for such situations. Previous work with lower-resolution arrays confirmed the utility of single-cell MDA products for large-size (~30 Mb) genome variation screening. We tested the performance of single-cell MDA products on the SNP 6.0 arrays to examine the performance of single-cell MDA in SNP genotyping, copy number polymorphism, de novo copy number variation (CNV) and loss of heterozygosity (LOH) analysis. Our data show that for SNP genotyping, single-cell MDA did not obtain complete genome coverage or high sequence fidelity. For CNV calling, single-cell MDA introduced stochastic amplification artifacts in log2 ratio profiles, reducing the robustness of CNV calling; however, by adjusting smooth window size, it is still possible to analyze large chromosomal aberrations, and homozygous deletions as small as 500 kb can still be identified from the noisy log2 ratio profiles. Our results also suggest that even with a modified protocol (reduction of reaction volume, addition of a molecular crowding reagent, minimization of reaction time), single-cell MDA presented little improvement over the unmodified protocol, but by increasing the number of cells as template to 5M-bM-^@M-^S10 cells, SNP 6.0 array results comparable to those of 10 ng genomic DNA MDA could be obtained. Algorithms like PICNIC improved the CNV calling, suggesting that better algorithms can better utilize single-cell MDA array results. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from cell line samples, and multiple displacement samples. Genotyping, Copy number and LOH analysis of Affymetrix SNP 6.0 arrays was performed for 3 samples of unamplified cell line genomic DNA, 2 samples of DNA obtained by multiple displacement amplification from 10ng genomic DNA, 3 single-cell multiple displacement amplification (MDA) products, single cell modified MDA amplification product, 5-cell modified MDA amplification product, 10-cell modified MDA amplification product.
2011-03-25 | E-GEOD-28132 | biostudies-arrayexpress
Project description:We compared the performance of six commercial kits (QIAseq, SMARTer, CATS, CleanTag, srLp, TailorMix) capable of handling <100ng total RNA input for miRNA detection sensitivity, reliability, titration response and ability to detect differentially expressed miRNAs at different amounts of synthetic miRNAs. We observed differences in detection sensitivity between the kits, but none were able to detect the full repertoire of expected miRNAs. The reliability within the replicates of all kits was good, while larger differences were observed between the kits, although none could accurately quantify the majority of miRNAs.
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Project description:Generating sufficient DNA for high-throughput genetic analysis has always been a challenge for clinical settings where the amount of source DNA is limited. Multiple displacement amplification (MDA) has been proposed as a promising candidate for such situations. Previous work with lower-resolution arrays confirmed the utility of single-cell MDA products for large-size (~30 Mb) genome variation screening. We tested the performance of single-cell MDA products on the SNP 6.0 arrays to examine the performance of single-cell MDA in SNP genotyping, copy number polymorphism, de novo copy number variation (CNV) and loss of heterozygosity (LOH) analysis. Our data show that for SNP genotyping, single-cell MDA did not obtain complete genome coverage or high sequence fidelity. For CNV calling, single-cell MDA introduced stochastic amplification artifacts in log2 ratio profiles, reducing the robustness of CNV calling; however, by adjusting smooth window size, it is still possible to analyze large chromosomal aberrations, and homozygous deletions as small as 500 kb can still be identified from the noisy log2 ratio profiles. Our results also suggest that even with a modified protocol (reduction of reaction volume, addition of a molecular crowding reagent, minimization of reaction time), single-cell MDA presented little improvement over the unmodified protocol, but by increasing the number of cells as template to 5–10 cells, SNP 6.0 array results comparable to those of 10 ng genomic DNA MDA could be obtained. Algorithms like PICNIC improved the CNV calling, suggesting that better algorithms can better utilize single-cell MDA array results.
2011-03-25 | GSE28132 | GEO
Project description:Methods of comprehensive microarray based analyses of single cell DNA are rapidly emerging. Whole genome amplification (WGA) remains a critical component for these methods to be successful. A number of commercially available WGA kits have been independently utilized in previous single cell microarray studies. However, direct comparison of their performance on single cells has not been conducted. The present study demonstrates that among previously published methods, a single cell GenomePlex WGA protocol provides the best combination of speed and accuracy for SNP microarray based copy number analysis when compared to a REPLI-g or GenomiPhi based protocol. Alternatively, for applications that do not have constraints on turn-around time and that are directed at accurate genotyping rather than copy number assignments, a REPLI-g based protocol may provide the best solution.
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Project description:We tested the performance of three methods for amplifying single-cell amounts of RNA under ideal conditions: T7-based in vitro transcription; switching mechanism at 5' end of RNA template (SMART) PCR amplification; and global PCR amplification. All methods introduced amplification-dependent noise when mRNA was amplified 108-fold, compared with data from unamplified cDNA. PCR-amplified cDNA demonstrated the smallest number of differences between two parallel replicate samples and the best correlation between independent amplifications from the same cell type, with SMART outperforming global PCR amplification. SMART had the highest true-positive rate and the lowest false-positive rate when comparing expression between two different cell types, but had the lowest absolute discovery rate of all three methods. Direct comparison of the performance of SMART and global PCR amplification on single-cell amounts of total RNA and on single neural stem cells confirmed these findings. Under the conditions tested, PCR amplification was more reliable than linear amplification for detecting true expression differences between samples. SMART amplification had a higher true-positive rate than global amplification, but at the expense of a considerably lower absolute discovery rate and a systematic compression of observed expression ratios. Keywords: Oliginucleotide expression microarrays, T7-based linear amplification; SMART PCR-based amplification; global PCR amplification
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