Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Triticum aestivum cultivar:BTS, SYN42

ABSTRACT: Triticum aestivum cultivar:BTS, SYN42 Raw sequence reads

PROVIDER: PRJNA915011 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR22924134.fastq.gz	Fastqsanger.gz
	SRR22924135.fastq.gz	Fastqsanger.gz
	SRR22924136.fastq.gz	Fastqsanger.gz
	SRR22924137.fastq.gz	Fastqsanger.gz

Items per page:

1 - 4 of 4

Similar Datasets

Triticum aestivum cultivar:BTS

Project description:Triticum aestivum cultivar:BTS Raw sequence reads

| PRJNA915009 | ENA

Triticum aestivum cultivar:BTS

Project description:Triticum aestivum cultivar:BTS Raw sequence reads

| PRJNA914883 | ENA

Transcriptome of Triticum aestivum genotypes associated with resistance against the Wheat dwarf virus

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived Triticum aestivum transcriptome (RNA-seq) profiling methods and to evaluate genotypes associated with resistance against the Wheat dwarf virus. Methods: Triticum aestivum mRNA profiles of genotypes associated with resistance against the Wheat dwarf virus were generated by deep sequencing, in four replicates, using Illumina. 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 TaqMan and SYBR Green assays. Conclusions: Our study represents the first detailed analysis of Triticum aestivum transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA and miRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

2023-04-04 | GSE192518 | GEO

Triticum aestivum

Project description:Triticum aestivum Raw sequence reads

| PRJNA360204 | ENA

Triticum aestivum

Project description:Triticum aestivum Raw sequence reads

| PRJNA1079080 | ENA

Triticum aestivum

Project description:Triticum aestivum Raw sequence reads

| PRJNA870211 | ENA

Triticum aestivum

Project description:Triticum aestivum Raw sequence reads