Browse
Submit Data
Databases
API
Help

Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Drop-Seq analysis of mixtures of human (HEK) and mouse (3T3) cells (1000/100 STAMPs) at 12.5 cells per microliter

ABSTRACT: A cell supsension containing an equal mix of HEK and 3T3 cells was used in Drop-Seq, a novel technology for high-throughput single cell mRNAseq. Cells were mixed at a final concentration of 12.5 cells per microliter in droplets. An estimated 570 STAMPs were selected for amplification.

ORGANISM(S): Homo sapiens

SUBMITTER: Evan Macosko

PROVIDER: E-GEOD-66693 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Similar Datasets

Drop-Seq analysis of ERCC spike in capture

Project description:A bead supsension and a solution of ERCC spike-ins at a concentration of ~100,000 molecules per droplet was used in Drop-Seq, a novel technology for high-throughput single cell mRNAseq An estimated 84 beads were selected for amplification.

2015-05-20 | E-GEOD-66694 | biostudies-arrayexpress

Drop-Seq analysis of mixtures of human (HEK) and mouse (3T3) cells (1000/100 STAMPs) at 12.5 cells per microliter

Project description:A cell supsension containing an equal mix of HEK and 3T3 cells was used in Drop-Seq, a novel technology for high-throughput single cell mRNAseq. Cells were mixed at a final concentration of 12.5 cells per microliter in droplets.

2015-05-20 | GSE66693 | GEO

Drop-Seq analysis of mixtures of human (HEK) and mouse (3T3) cells (1000/100 STAMPs) at 50 cells per microliter

Project description:A cell supsension containing an equal mix of HEK and 3T3 cells was used in Drop-Seq, a novel technology for high-throughput single cell mRNAseq. The cells were mixed at a final concentration of 50 cells per microliter.

2015-05-20 | GSE63269 | GEO

Drop-Seq analysis of mixtures of human (HEK) and mouse (3T3) cells (1000/100 STAMPs) at 12.5 cells per microliter

Project description:Drop-Seq analysis of mixtures of human (HEK) and mouse (3T3) cells (1000/100 STAMPs) at 12.5 cells per microliter

| PRJNA277734 | ENA

Drop-Seq analysis of P14 mouse retina single-cell suspension

Project description:A cell suspension was prepared from wild-type P14 mouse retinas, and single-cell mRNAseq libraries were generated with Drop-Seq. Drop-Seq was performed on four separate days using the same age (P14) and strain (C57BL/6). On day 1, replicate 1 was obtained. On day 2, replicates 2 and 3 were obtained. On day 3, replicates 4-6 were obtained. On day 4, replicate 7 was obtained.

2015-05-20 | E-GEOD-63472 | biostudies-arrayexpress

"More crop per drop": Exploring India's cereal water use since 2005.

Project description:India has the highest national freshwater demand globally and 91% of India's freshwater is used in the agriculture sector. Cereals account for over 50% of the dietary water footprint in India and represent a potential opportunity for reducing water use in Indian agriculture. This study combines governmental production and irrigation statistics with crop distribution maps to examine trends in annual water use for cereal production in India between 2005 and 2014. A new online water assessment tool, Cool Farm Tool Water (CFTW), was used to calculate water use and derive seasonal state-level blue and green water footprints for rice, wheat, sorghum, millet and maize. The analysis indicates that India achieved 26.4% increased total cereal production between 2005 and 2014 without additional water or land use. Cereal water footprints have declined due to higher yields for most crops and slightly lower rates of evapotranspiration. There has also been a shift in the area under production away from the Kharif (monsoon) towards the Rabi (dry) season in which total water footprints for all cereals except rice are substantially lower (-33.4% to -45.0% compared to Kharif), but show a significantly higher dependency on ground and surface water. The value of this study is two-fold. First, it provides a full assessment of production trends for the five major cereals in India for each year from 2005 to 2014 and links it to water use. Secondly, it uses updated seasonal water footprints, which demonstrate the potential for changes in cereal production practices to contribute to improved efficiency of water use in India. Future pressures on scarce water resources may encourage transition to cereals with lower irrigation dependency, in particular maize, but also sorghum and millet. In addition, increased emphasis on improving millet and sorghum yields would be of benefit to secure cereal production and reduce its overall water footprint.

| S-EPMC6510970 | biostudies-literature

The Conserved Tpk1 Regulates Non-Homologous End Joining Double-Strand Break Repair by Phosphorylation of Nej1, a Homolog of the Human XLF

Project description:The yeast cyclic-AMP dependent protein kinase A (PKA) is a ubiquitous serine-threonine kinase, encompassing three catalytic (Tpk1-3) and one regulatory (Bcy1) subunits. Evidence suggests PKA involvement in DNA damage checkpoint response, but how DNA repair pathways are regulated by PKA subunits remains inconclusive. Here, we report that deleting the catalytic subunit, tpk1, reduces non-homologous end joining (NHEJ) efficiency, whereas tpk2-3 and bcy1 deletion does not. Epistatic analyses revealed that tpk1, as well as the DNA damage checkpoint kinase (dun1) and NHEJ regulator (nej1), co-function in the same pathway. Chromatin immunoprecipitation and resection data suggest that the recruitment of repair proteins and DNA resection is influenced by tpk1 deletion. Further, we show that Tpk1 phosphorylation of Nej1 at S298 (a Dun1 phosphosite) is indispensable for NHEJ repair, in addition to nuclear targeting of Nej1 and its binding partner Lif1. In mammalian cells, loss of PRKACB (the human homolog of Tpk1) also reduced NHEJ efficiency, and similarly, PRKACB was found to phosphorylate XLF (a Nej1 human homolog) at S263, a corresponding residue of the yeast Nej1 S298. Together, our results uncover a new and conserved mechanism for Tpk1 and PRKACB in phosphorylating Nej1 (or XLF), which is critically required for NHEJ repair.

2021-09-10 | PXD024768 | Pride

The Conserved Tpk1 Regulates Non-Homologous End Joining Double-Strand Break Repair by Phosphorylation of Nej1, a Homolog of the Human XLF

2021-09-10 | PXD024695 | Pride

High-throughput sequencing for microRNAs in uninjured and regenerating newt hearts

Project description:We have developed a standardized and reproducible heart resection/regeneration model system in the red-spotted newt. In order to ascertain the involvement of microRNAs in this amazing process, we made and sequenced cDNA libraries for microRNAs in order to provide sequence data that we could use in further quantitative and qualitative studies. We constructed small RNA cDNA libraries for uninjured (Uninj), 7dpi and 21dpi heart samples, which were sequenced using Illumina-Solexa technology at SciLifeLabs (Stockholm, Sweden).

2013-09-24 | E-GEOD-46527 | biostudies-arrayexpress

Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell.

Project description:We report on the combination of nanodroplet sample preparation, ultra-low-flow nanoLC, high-field asymmetric ion mobility spectrometry (FAIMS), and the latest-generation Orbitrap Eclipse Tribrid mass spectrometer for greatly improved single-cell proteome profiling. FAIMS effectively filtered out singly charged ions for more effective MS analysis of multiply charged peptides, resulting in an average of 1056 protein groups identified from single HeLa cells without MS1-level feature matching. This is 2.3 times more identifications than without FAIMS and a far greater level of proteome coverage for single mammalian cells than has been previously reported for a label-free study. Differential analysis of single microdissected motor neurons and interneurons from human spinal tissue indicated a similar level of proteome coverage, and the two subpopulations of cells were readily differentiated based on single-cell label-free quantification.

| S-EPMC8178986 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data