Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA285681 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR2048232_1.fastq.gz | Fastqsanger.gz | |||
| SRR2048232_2.fastq.gz | Fastqsanger.gz | |||
| SRR2048233_1.fastq.gz | Fastqsanger.gz | |||
| SRR2048233_2.fastq.gz | Fastqsanger.gz | |||
| SRR2048234_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 6 |
Similar Datasets
Project description:Next Generation Sequencing has proven to be an exceptionally powerful tool in the field of genomics and transcriptomics. With recent development it is nowadays possible to analyze ultra-low input sample material down to single cells. Nevertheless investigating such sample material still limits the analysis to either the genome or transcriptome, hence a combined analysis of both types of nucleic acids from the same sample material is still in demand.We developed a protocol which enables the combined analysis of the genome as well as the transcriptome by Next Generation Sequencing from ultra-low input samples. The protocol was evaluated by sequencing sub-colony structures from human embryonic stem cells containing 150 to 200 cells. The method can be adapted to any available sequencing system (e.g. Illumina, SOLiD, 454, etc.).To our knowledge, this is the first report where sub-colonies of human embryonic stem cells have been analyzed both at the genomic as well as transcriptome level. The method of this proof of concept study may find useful practical applications for cases where only a limited number of cells are available, e.g. for tissues samples from biopsies, circulating tumor cells and cells from early embryonic development. The results we present demonstrate that a combined analysis of genomic DNA and messenger RNA from ultra low input samples is feasible and can readily be applied to other cellular systems with limited material available.
2015-11-17 | GSE69471 | GEO
Project description:High-throughput RNA-sequencing has now become the gold standard method for whole-transcriptome gene expression analysis. It is widely used in a number of applications studying various transcriptomes of cells and tissues. It is also being increasingly considered for a number of clinical applications, including expression profiling for diagnostics or alternative transcripts detection. However, RNA sequencing can be challenging in some situations, for instance due to low input quantities or degraded RNA samples. Several protocols have been proposed to overcome some of these challenges, and many are available as commercial kits. Here we perform a comprehensive testing of three recent commercial technologies for RNA-seq library preparation (Truseq, Smarter and Smarter Ultra-Low) on human reference tissue preparations, for standard (1ug), low (100 and 10 ng) and ultra-low (< 1 ng) input quantities, and for mRNA and total RNA, stranded or unstranded. We analyze the results using read quality and alignments metrics, gene detection and differential gene expression metrics. Overall, we show that the Truseq kit performs well at 100 ng input quantity, while the Smarter kit shows degraded performances for 100 and 10 ng input quantities, and that the Smarter Ultra-Low kit performs quite well for input quantities < 1 ng. All the results are discussed in details, and we provide guidelines for the selection of a RNA-seq library preparation kits by biologists.
2019-05-10 | GSE124198 | GEO
Project description:There are a total of four samples each for this analysis. Each sample consists of the cells grown on three 10 cm culture plates. Each plate should have 2x106 cells for a total of 6x106 cells per sample when all three plates are combined. The first sample is undifferentiated human embryonic stem cells, the second sample is human glutamatergic neurons derived from those human embryonic stem cells, the third sample is undifferentiated human induced pluripotent stem cells and the fourth sample is human glutamatergic neurons derived from those human induced pluripotent stem cells.
2017-06-19 | ST000768 | MetabolomicsWorkbench
Project description:mouse embryonic fibroblasts, embryonic stem cells, and induced pluripotent stem cells were compared via metabolomic analysis
2018-08-02 | MSV000082680 | GNPS
Project description:Haematopoetic RNA-seq from ultra low input
| PRJNA419186 | ENA
Project description:Mice deficient in the LDL receptor (LDLR KO mice) fed with high fat diet (HFD) feeding have been widely used as a model to mimic human atherosclerosis. RNA-seq using aortic macrophages to investigate the effects of aortic macrophages on the plaque size progression. LDLR KO mice, 6-8 weeks old, were used, and fed with either an alternative HFD or a regular HFD. After aorta macrophages were isolated, RNeasy Mini Kit (Qiagen) was used to isolate mRNA. Single end (50bp), unstranded, SMART-Seq v4 plus nextera (SMART-Seq v4 Ultra Low Input RNA Kit (Takara) ). The RNA-seq libraries were prepared with SMART-Seq v4 Ultra Low Input RNA Kit (Takara).
2024-07-31 | E-MTAB-12759 | 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:Single cell transcriptomics have revolutionized fundamental understanding of basic biology and disease. Since transcripts often do not correlate with protein expression, it is paramount to complement transcriptomics approaches with proteome analysis at single cell resolution. Despite continuous technological improvements in sensitivity, mass spectrometry-based single cell proteomics ultimately faces the challenge of reproducibly comparing the protein expression profiles of thousands of individual cells. Here, we combine two hitherto opposing analytical strategies, DIA and Tandem-Mass-Tag (TMT)-multiplexing, to generate highly reproducible, quantitative proteome signatures from ultra-low input samples. While conventional, data-dependent shotgun proteomics (DDA) of ultra-low input samples critically suffers from the accumulation of missing values with increasing sample-cohort size, data-independent acquisition (DIA) strategies do usually not to take full advantage of isotope-encoded sample multiplexing. We also developed a novel, identification-independent proteomics data analysis pipeline to quantitatively compare DIA-TMT proteome signatures across hundreds of samples independent of their biological origin to identify cell types and single protein knockouts. We validate our approach using integrative data analysis of different human cell lines and standard database searches for knockouts of defined proteins. These data establish a novel and reproducible approach to markedly expand the numbers of proteins one detects from ultra-low input samples, such as single cells.
2021-05-17 | PXD023574 | Pride
Project description:The aim of this project is to differentiate human embryonic stem cells to an extra-embryonic fate, specifically the hypoblast. This is of uttermost importance given the current lack of human hypoblast stem cells.
We hypothesized that the pluripotent characteristics of the starting human embryonic stem cell population may dictate the competency for extra-embryonic cell fate specification. Based on this hypothesis and using human embryonic stem cells maintained in different naïve-like culture regimes, we have now developed conditions that allow the differentiation of human embryonic stem cells to a stable GATA6+ SOX2- population. This suggests that these cells may be putative human hypoblast stem cells. To validate this finding here we propose to perform RNA sequencing experiments of the differentiated human embryonic stem cells. By comparing their RNA expression profile to the single cell sequencing data of the human embryo that we are currently generating, we will be able to determine the identity of our GATA6+ SOX2- cells, and establish whether they represent the in vivo human hypoblast.
| EGAS00001003571 | EGA