Ontology highlight
ABSTRACT:
PROVIDER: PRJNA596918 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Targeted RNA sequencing enhances gene expression profiling of ultra-low input samples
| PRJNA589751 | ENA
Project description:We isolated genomic DNA from adult male mouse nucleus accumbens (NAc) D2 medium spiny neurons (D2-MSN) by fluorescence-activated cell sorting. We performed the whole genome methylation profiling using two independent library preparation methods, namely the sodium bisulfite-based Accel-NGS Methyl-Seq (AM-seq) of Swift biosciences and the enzymatic conversion-based method Enzymatic Methyl-seq (EM-seq) from New England Biolabs, on two identical samples. We mapped about 400 million paired-end reads to the mouse genome (build mm10) and assessed measures of each methylome by two methods. This study provided a side-by-side comparison of two independent whole genome profiling methods for low-input neuronal samples.
2022-03-04 | GSE195752 | GEO
Project description:To test whether the addition of a peptide nucleic acid (PNA) clamp, which binds WT KRAS at codon 12, can increase the efficacy of mutation detection for KRASG12D within a targeted NGS setting. We tested the effect of clamping the wild-type KRAS sequence in a reference standard (Tru-Q 7, 1.3% Tier from Horizon Diagnostics, Cambridge, UK) with a KRAS c.35G>A mutation (KRASG12D) at an allelic frequency (AF) of 1.3% assessed by digital droplet PCR (ddPCR). We then re-tested the PNA on circulating-free DNA from a patient harbouring a KRASG12D mutation (at an AF of 3.2%, determined by ddPCR). Multiple runs were conducted using 10, 5, 2.5 and 1ng of DNA input.
2017-07-29 | E-MTAB-5718 | biostudies-arrayexpress
Project description:Droplet microfluidic methods have massively increased the throughput of single-cell RNA sequencing campaigns. The benefit of scale-up is, however, accompanied by increased background noise when processing challenging samples as well as lower overall RNA capture efficiency. These drawbacks stem from the lack of strategies to enrich for high-quality material at the moment of cell encapsulation and the lack of implementable multi-step enzymatic processes that increase RNA capture. Here we alleviate both bottlenecks by deploying fluorescence-activated droplet sorting to enrich for droplets that contain single viable cells, intact nuclei or fixed cells and use reagent addition to droplets by picoinjection to perform multi-step lysis and reverse transcription. Our methodology increases gene detection rates fivefold, while reducing background noise by up to half, depending on sample quality. We harness these unique properties to deliver a high-quality molecular atlas of mouse brain development using highly damaged input material. Our method is broadly applicable to other droplet-based workflows to deliver sensitive and accurate single-cell profiling at a reduced cost.
2023-07-02 | GSE208156 | GEO
Project description:Fluorescence-activated cell sorting (FACS) is a specialized technique to isolate
cell subpopulations with a high level of recovery and accuracy. However, the cell sorting
procedure can impact the viability and metabolic state of cells. Here, we performed a comparative study and evaluated the impact of traditional high-pressure charged droplet-based and a microfluidic chip-based sorting approach on the metabolic and phosphoproteomic profile of different cell types. While microfluidic chip-based sorted cells more closely resembled the unsorted control group for most cell types tested, the droplet-based sorted cells showed significant metabolic and phosphoproteomic alterations. In particular, greater changes in redox and energy status were present in cells sorted with the droplet-based cell sorter along with higher transcriptional and spliceosomal regulation and mechanical stress signaling. These results
indicate microfluidic chip-based sorting is less disruptive compared to droplet-based sorting.
2023-11-09 | MSV000093348 | MassIVE
Project description:Human tumors are comprised of heterogeneous cell populations that display diverse molecular and phenotypic features. To examine the extent to which epigenetic differences contribute to intratumoral cellular heterogeneity, we have developed a high-throughput method, termed MAPit-patch. The method uses multiplexed amplification of targeted sequences from sub-microgram input quantities of genomic DNA followed by next generation bisulfite sequencing. This provides highly scalable and simultaneous mapping of chromatin accessibility and DNA methylation on single molecules at high resolution. Long sequencing reads from targeted regions maintains the structural integrity of epigenetic information and provides substantial depth of coverage, detecting for the first time minority subpopulations of epigenetic configurations formerly obscured by existing genome-wide and population-ensemble methodologies. Analyzing a cohort of 71 promoters of genes with exons commonly mutated in cancer, MAPit-patch uncovered several differentially accessible and methylated promoters that are associated with altered gene expression between neural stem cell (NSC) and glioblastoma (GBM) cell populations. Additionally, substantial epigenetic heterogeneity was observed across the sequenced molecules at individual promoters, indicating the presence of epigenetically distinct cellular subpopulations. This study includes 4 samples, NSC probed with 100U M.CviPI and 0U control; GBM probed with 100U M.CviPI and 0U control.
2013-10-03 | E-GEOD-50047 | biostudies-arrayexpress
Project description:As the most abundant and best-characterized internal mRNA modification, N6-methyladenosine (m6A) emerges to play a critical regulatory role in wide range of physiological and pathological processes, including gametogenesis, neuronal development, obesity and tumorigenesis. Methylated RNA immunoprecipitation coupled with next-generation sequencing (MeRIP-seq) facilitates transcriptome-wide m6A profiling, also is the most widely used technique to understand the biological significance of m6A. However, it typically requires over 100 μg of total RNA or 107 cells as input materials, hampering its application in limited samples. Here, we develop tMeRIP-seq, a transposase assisted MeRIP-seq method to achieve m6A profiling using ultra-low amount of input RNA. By marrying Tn5 tagmentation to m6A-specific immunoprecipitation, tMeRIP-seq largely improves the efficiency of library construction and reduces the input materials to as little as 60 ng total RNA or 103 cells. We apply this method on a small droplet of human blood and recapitulate the m6A profile previously reported using conventional protocol. We find tMeRIP-seq is a convenient and powerful method to examine m6A in ultra-low input material, potentially providing m6A as a new layer of bio-marker for liquid biopsy.
2021-09-07 | GSE167307 | GEO
Project description:<p>Recently developed methods that utilize partitioning of long genomic DNA fragments, and barcoding of shorter fragments derived from them, have succeeded in retaining long-range information in short sequencing reads. These so-called read cloud approaches represent a powerful, accurate, and cost-effective alternative to single-molecule long-read sequencing. We developed software, GROC-SVs, that takes advantage of read clouds for structural variant detection and assembly. We apply the method to two 10x Genomics data sets, one chromothriptic sarcoma with several spatially separated samples, and one breast cancer cell line, all Illumina-sequenced to high coverage. Comparison to short-fragment data from the same samples, and validation by mate-pair data from a subset of the sarcoma samples, demonstrate substantial improvement in specificity of breakpoint detection compared to short-fragment sequencing, at comparable sensitivity, and vice versa. The embedded long-range information also facilitates sequence assembly of a large fraction of the breakpoints; importantly, consecutive breakpoints that are closer than the average length of the input DNA molecules can be assembled together and their order and arrangement reconstructed, with some events exhibiting remarkable complexity. These features facilitated an analysis of the structural evolution of the sarcoma. In the chromothripsis, rearrangements occurred before copy number amplifications, and using the phylogenetic tree built from point mutation data, we show that single nucleotide variants and structural variants are not correlated. We predict significant future advances in structural variant science using 10x data analyzed with GROC-SVs and other read cloud-specific methods.</p>
| phs001255 | dbGaP