Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Nauphoeta cinerea transcriptome Raw sequence reads

PROVIDER: PRJNA322693 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR3581673_1.fastq.gz	Fastqsanger.gz
	SRR3581673_2.fastq.gz	Fastqsanger.gz
	SRR3586489_1.fastq.gz	Fastqsanger.gz
	SRR3586489_2.fastq.gz	Fastqsanger.gz

Items per page:

1 - 4 of 4

Similar Datasets

Nauphoeta cinerea

Project description:Nauphoeta cinerea transcriptome Raw sequence reads

| PRJNA322855 | ENA

Nauphoeta cinerea

Project description:Nauphoeta cinerea transcriptome Raw sequence reads

| PRJNA322515 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of Cucumber and Botrytis cinerea Transcriptome Changes During Infection

Project description:Purpose: The goals of this study are using RNA-seq to obtain cucumber and Botrytis cinerea transcriptome changes during infection Methods: mRNA profiles of anti-infection samples and interaction sample were generate by deep sequencing,using Illumina Hiseq 2500. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using SYBR Green assays Results: Using an optimized data analysis workflow,In total, 248,908,688 raw reads were generated; after removing low-quality reads and those containing adapter and poly-N, 238,341,648 clean reads remained to map the reference genome. There were 3,512 cucumber (differential expression genes) DEGs and 1,735 B. cinerea DEGs. GO enrichment and KEGG enrichment analysis were performed on these DEGs to study the interaction between cucumber and B. cinerea. To verify the reliability and accuracy of our transcriptome data, 5 cucumber DEGs and 5 B. cinerea DEGs were chosen for RT-PCR verification. Conclusions:To the best of our knowledge, this is the first analysis of large-scale transcriptome changes of cucumber during the infection of Botrytis cinerea. These results will increase our understanding of the molecular mechanisms of the cucumber defense Botrytis cinerea and may be used to protect plants against disasters caused by necrotrophic fungal pathogens.

2016-08-01 | GSE72191 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Cucumber and Botrytis cinerea Transcriptome Changes During Infection

Project description:Purpose: The goals of this study are using RNA-seq to obtain cucumber and Botrytis cinerea transcriptome changes during infection Methods: mRNA profiles of anti-infection samples and interaction sample were generate by deep sequencing,using Illumina Hiseq 2500. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: BurrowsâWheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRTâPCR validation was performed using SYBR Green assays Results: Using an optimized data analysis workflow,In total, 248,908,688 raw reads were generated; after removing low-quality reads and those containing adapter and poly-N, 238,341,648 clean reads remained to map the reference genome. There were 3,512 cucumber (differential expression genes) DEGs and 1,735 B. cinerea DEGs. GO enrichment and KEGG enrichment analysis were performed on these DEGs to study the interaction between cucumber and B. cinerea. To verify the reliability and accuracy of our transcriptome data, 5 cucumber DEGs and 5 B. cinerea DEGs were chosen for RT-PCR verification. Conclusions:To the best of our knowledge, this is the first analysis of large-scale transcriptome changes of cucumber during the infection of Botrytis cinerea. These results will increase our understanding of the molecular mechanisms of the cucumber defense Botrytis cinerea and may be used to protect plants against disasters caused by necrotrophic fungal pathogens. mRNA profiles of infection and anti-infection cucumber were generated by deep sequencing, using Illumina Hiseq 2500 .

2016-08-01 | E-GEOD-72191 | biostudies-arrayexpress

Morus alba Raw protein sequence reads

Project description:Morus alba L. Raw protein sequence reads and sequence

2024-02-08 | PXD049451 |

RNA-Seq data of Vitis vinifera cv. Furmint berry samples (Tokaj wine region) exposed to noble rot

Project description:White grape (Vitis vinifera cv. Furmint) berry samples subjected to natural noble rot were collected in a vineyard in Mád, Hungary (Tokaj wine region). Raw data include grapevine and Botrytis cinerea sequence reads.

2021-11-25 | E-MTAB-11205 | biostudies-arrayexpress

Nauphoeta cinerea

Project description:Nauphoeta cinerea overview

| PRJNA390445 | ENA

Nauphoeta cinerea strain:Nauci

Project description:Nauphoeta cinerea strain:Nauci Transcriptome or Gene expression

| PRJNA322851 | ENA

Blattabacterium sp. (Nauphoeta cinerea)

Project description:Blattabacterium sp. (Nauphoeta cinerea) Genome sequencing

| PRJNA196320 | ENA

Quantitative profiling of differentially expressed miRNAs in siCTL- and siOASL-transfected HUVECs

Project description:Purpose: The goal of this study is to compare endothelial small RNA transcriptome to identify the target of OASL under basal or stimulated conditions by utilizing miRNA-seq. Methods: Endothelial miRNA profilies of siCTL or siOASL transfected HUVECs were generated by illumina sequencing method, in duplicate. After sequencing, the raw sequence reads are filtered based on quality. The adapter sequences are also trimmed off the raw sequence reads. rRNA removed reads are sequentially aligned to reference genome (GRCh38) and miRNA prediction is performed by miRDeep2. Results: We identified known miRNA in species (miRDeep2) in the HUVECs transfected with siCTL or siOASL. The expression profile of mature miRNA is used to analyze differentially expressed miRNA(DE miRNA). Conclusions: Our study represents the first analysis of endothelial miRNA profiles affected by OASL knockdown with biologic replicates.

2022-09-06 | GSE186354 | GEO

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