Similar Datasets
Project description:Despite the precipitous decline in the cost of genome sequencing over the last few years, library preparation for RNA-seq is still laborious and expensive for high throughput screening for drug discovery. Limited availability of RNA generated by some experimental workflows poses an additional challenge and typically adds to the cost of RNA library preparation. In a search for low cost, automation-compatible RNA library preparation kits that also maintain strand specificity and are amenable to low input RNA quantities, we systematically tested two recent commercial technologies – Swift and Swift Rapid – using the Illumina TruSeq stranded mRNA, the de facto standard workflow for bulk transcriptomics, as our reference. We used the Universal Human Reference RNA (UHRR) (composed of equal quantities of total RNA from 10 human cancer cell lines) to benchmark differential gene expression in these kits, at input quantities ranging between 10 ng to 500 ng. Read quality and alignment metrics revealed high mapping efficiency and uniform read coverage through genes for all samples across all three kits. Normalized read counts between all treatment groups were in high agreement, with pairwise Pearson correlation coefficients >0.97. Compared to the Illumina TruSeq stranded mRNA kit, both Swift RNA library kits are cost effective and offer shorter workflow times enabled by their patented Adaptase technology. Furthermore, the Swift RNA kit allows for a relatively broader (and lower) input range, producing consistent results across diverse samples. The Swift Rapid RNA method is the fastest and most cost effective NGS workflow that is best suited for higher RNA yields, with the exact same RNA input range as the Illumina TruSeq kit. We also found the Swift RNA kit to produce the fewest number of differentially expressed genes and pathways attributable to input mRNA concentration.
2021-02-23 | GSE167300 | GEO
Project description:Advances in Next Generation Sequencing (NGS) have made available a wealth of information that had previously been inaccessible to researchers and clinicians. NGS has been applied to understand genomic, transcriptomic, and epigenomic changes and gained traction as a significant tool capable of accelerating diagnosis, prognosis, and biomarker discovery. However, these NGS assays have yet to be practical methods for patient stratification or diagnosis because of the gap between the tiny quantities of biomaterials provided by a clinical sample and the large DNA input required by most of these assays. Current library preparation methodologies typically require large input amounts of DNA and a long and complicated manual process. Here we present a microfluidic reactor system for NGS library preparation, capable of reducing the number of pipetting steps significantly, automating much of the process, while supporting extremely low DNA input requirement (10 pg per library). This largely automated technology will allow for low-input preparations of 8 libraries simultaneously while reducing batch to batch variation and operator hands-on time.
2020-01-02 | GSE132786 | GEO
Project description:Two biological replicates Hi-C and HPV16-specific Region Capture Hi-C libraries were prepared for each of the W12 cell lines. Capture Hi-C was performed using HPV16-specific RNA baits. Hi-C libraries alone were prepared from normal cervix tissue (Ncx).
2021-06-18 | E-MTAB-10152 | biostudies-arrayexpress
Project description:Library preparation is a key step in gene expression quantification. There are considerable advantages to both strand specific sequencing and the ability to sequence samples with very small amounts of starting material. Until recently there was no kit available that allowed both simultaneously. The standard Illumina-TruSeq stranded mRNA Sample Preparation kit requires abundant starting quantity while the Takara Bio-SMART-Seq® v4 Ultra® Low Input RNA kit allows for ultra low starting quantities but sacrifices strand specificity. Recently a kit that can do both, SMARTer® Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian by Takara Bio, has become available. Evaluating the performance and effects of these sample preparation kits is a critical determinant for selecting the appropriate sequencing protocol, but a comprehensive comparison is currently missing. To address this we performed a detailed comparative analysis of sequencing libraries prepared with the three kits. We prepared a set of samples representing two experimental conditions with each kit, allowing for comparison of the kits in a standard realistic differential expression analysis. We find substantial differences in the levels of alignment and differential gene expression. Using differential expression analysis we show that using Pico results in identifying 55% less differentially expressed genes than TruSeq. Nevertheless, using gene pathway enrichment analysis we find similar results for all three kits, indicating that ultimately comparable functional results can be reached.
2019-09-17 | GSE124167 | GEO
Project description:In this experiment, we've examined chromatin conformation of OG2 (B6; CBA-Tg(Pou5f1-EGFP)2Mnn/J; stock number 004654) mouse stem cells cultured as described in (Shi et al., 2008), using different amounts of starting cells. We performed a modified in situ Hi-C protocol for 6 samples digested with MboI restriction enzyme having as starting material 1 million (M), 100 thousand (k), 50k, 25k, 10k or 1k cells. As well as, to 2 samples digested with HindIII restriction enzyme that had as starting material 5M or 100k cells. Traditional in situ Hi-C protocols recommend 5-10 million starting cells. The aim of the experiment was to assess the impact of decreasing the cell number on reproducibility, library complexity, chromatin structure visualization in order to adapt the method to the study of rare cell populations. Furthermore, we have characterised the 3D structure of peripheral blood mononuclear cells (PBMCs) obtained from a blood extraction from a healthy donor and from a lymph node biopsy from a DLBCL patient as a proof of concept for the suitability of Low-C for rare cell population analysis.
2018-11-30 | E-MTAB-5875 | biostudies-arrayexpress
Project description:Capture Hi-C (CHi-C) is a new technique for assessing genome organization based on chromosome conformation capture coupled to oligonucleotide capture of regions of interest, such as gene promoters. Chromatin loop detection is challenging because existing Hi-C/4C-like tools, which make different assumptions about the technical biases presented, are often unsuitable. We describe a new approach, ChiCMaxima, which uses local maxima combined with limited filtering to detect DNA looping interactions, integrating information from biological replicates. ChiCMaxima shows more stringency and robustness compared to previously developed tools. The tool includes a GUI browser for flexible visualization of CHi-C profiles alongside epigenomic tracks. The results of the analysis on existing mouse ES Capture Hi-C data (ArrayExpress E-MTAB-2414) were validated by two 4C-seq experiments, submitted here.
2019-04-17 | GSE129884 | GEO
Project description:HiCUP is a pipeline for processing sequence data generated by Hi-C, a technique used to investigate the three-dimensional organisation of a genome. The pipeline maps data to a specified reference genome and removes artefacts that would otherwise hinder subsequent analysis. HiCUP also provides an easy-to-interpret yet detailed quality control report that may be used by researchers to refine their experimental protocol for future studies. The software is freely available and has already been used for processing Hi-C data in several recently published peer-reviewed research articles. This experiment investigates the impact of using HiCUP to remove putative PCR amplification products in heavily duplicated Capture Hi-C libraries. Examination of three Capture Hi-C libraries
2015-10-29 | E-GEOD-73204 | biostudies-arrayexpress
Project description:Hi-C was performed on SK-N-SH cells to study 3-dimensional chromatin architecture. Two biological replicates were performed, each with roughly 25x10^7 cells.
2015-09-01 | E-GEOD-71072 | biostudies-arrayexpress
Project description:Genome-wide mapping of chromatin interactions at high resolution remains experimentally and computationally challenging. Here we used a low-input “easy Hi-C” protocol to map the 3D genome architecture in human neurogenesis and brain tissues and also demonstrated that a rigorous Hi-C bias-correction pipeline (HiCorr) can significantly improve the sensitivity and robustness of Hi-C loop identification at sub-TAD level, especially the enhancer-promoter (E-P) interactions. We used HiCorr to compare the high-resolution maps of chromatin interactions from 10 tissue or cell types with a focus on neurogenesis and brain tissues. We found that dynamic chromatin loops are better hallmarks for cellular differentiation than compartment switching. HiCorr allowed direct observation of cell-type- and differentiation-specific E-P aggregates spanning large neighborhoods, suggesting a mechanism that stabilizes enhancer contacts during development. Interestingly, we concluded that Hi-C loop outperforms eQTL in explaining neurological GWAS results, revealing a unique value of high-resolution 3D genome maps in elucidating the disease etiology.
2020-07-31 | GSE116825 | GEO