Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Next Generation Sequencing Facilitates Quantitative Analysis of P. gingivalis and HUVEC Transcriptomes

ABSTRACT: Next Generation Sequencing Facilitates Quantitative Analysis of P. gingivalis and HUVEC Transcriptomes

PROVIDER: PRJNA763155 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR15886831_1.fastq.gz	Fastqsanger.gz
	SRR15886831_2.fastq.gz	Fastqsanger.gz
	SRR15886832_1.fastq.gz	Fastqsanger.gz
	SRR15886832_2.fastq.gz	Fastqsanger.gz
	SRR15886833_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 24

Similar Datasets

Next Generation Sequencing Facilitates Quantitative Analysis of P. gingivalis and HUVEC Transcriptomes

Project description:Purpose: This study provides the transcriptional landscape of intracellular P. gingivalis as well as that of endothelial cells infected by this bacteria based on dual RNA sequencing. Methods: HUVECs were seeded in 6-well plates and cultured to 80% confluence. After washing with phosphate-buffered saline (PBS), cell were infected with P. gingivalis at a multiplicity of infection (MOI) of 100 for 2 h at 37 °C in 5% CO2, unless otherwise stated. Non-adherent bacteria were removed by washing with PBS, and the cell-adherent bacteria were killed using gentamicin (300 μg/mL) and metronidazole (200 μg/mL) for 1 h at 37 °C in 5% CO2.Total RNA was isolated from the samples using TRIzol® reagent.cDNA libraries for Illumina® sequencing were generated using the KC-DigitalTM Stranded mRNA Library Prep Kit (Illumina, San Diego, CA, USA). The library products corresponding to 200–250 bps were then enriched, quantified, and sequenced using a Nova-seq 6000 sequencer (Illumina, San Diego, CA, USA). Results: Using an optimized data analysis workflow, intracellular P. gingivalis showed a total of 573 DEGs compared with the control bacteria, and of these DEGs, 304 and 269 were upregulated and downregulated, respectively. A total of 838 DEGs were detected in P. gingivalis-infected HUVECs compared with their uninfected counterparts, and of these, 297 and 541 genes were upregulated and downregulated, respectively. Conclusions: This study firstly provides the transcriptional landscape of intracellular P. gingivalis as well as that of endothelial cells infected by this bacteria based on dual RNA sequencing.

2021-09-17 | GSE184085 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of MED23-knockdown and Control HUVEC Cells Transcriptomes

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of MED23-knockdown and Control HUVEC Cells Transcriptomes

| PRJNA772680 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of Solanum lycopersicum bud and flower Transcriptomes

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of Solanum lycopersicum bud and flower Transcriptomes

2021-02-27 | GSE164382 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of MED23-knockdown and Control HUVEC Cells Transcriptomes

Project description:Purpose: RNA-seq analysis to evaluate the impact of MED23 knockdown on the transcriptome of HUVEC cells.Methods: Total RNA was isolated with TRIzol from Med23 knockdown HUVECs (n = 3) or control cells (n = 3). cDNA sequencing libraries were prepared with an NEBNext® Ultra™ RNA Library Prep Kit for Illumina. The RNA-Seq FASTQ raw data were trimmed to remove low-quality reads and adapters using Trimmomatic. The trimmed reads were aligned to the mouse reference genome UCSC GRCh37/hg19 with HISAT2. Gene and transcript quantification was performed using Cutdiff. The results of the mapping of the RNA-seq reads, transcript assembly and abundance estimation were reported as fragments per kilobase of exon per million fragments mapped (FPKM).

2021-10-21 | GSE186112 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of CHAA Transcriptomes

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of CHAA Transcriptomes

| PRJNA725272 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of Retinoblastoma Transcriptomes

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of Retinoblastoma Transcriptomes

| PRJNA436090 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of IBP Transcriptomes

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of IBP Transcriptomes

| PRJNA761350 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of ISL1 Regulated Transcriptomes

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of ISL1 Regulated Transcriptomes

| PRJNA612779 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of U87MG Cell Transcriptomes

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of U87MG Cell Transcriptomes

| PRJNA849513 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of Cystine-regulated Transcriptomes

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of Cystine-regulated Transcriptomes

| PRJNA663304 | ENA

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