Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR3474180_1.fastq.gz | Fastqsanger.gz | |||
| SRR3474180_2.fastq.gz | Fastqsanger.gz | |||
| SRR3474181_1.fastq.gz | Fastqsanger.gz | |||
| SRR3474181_2.fastq.gz | Fastqsanger.gz | |||
| SRR3474191_1.fastq.gz | Fastqsanger.gz |
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Project description:Morus alba L. Raw protein sequence reads and sequence
2024-02-08 | PXD049451 |
Project description:Purpose: Cucumber (Cucumis sativus L.) is an economically important vegetable crop worldwide, and cucumber fruit spine density has an important impact on the commercial value. However, little is known about the regulatory mechanism for the fruit spine formation.In this study, the transcriptome analyses of ovaries and pericarps from numerous-spine parent and few-spine parent were conducted to identify the gene regulatory networks involved in the formation and development of numerous fruit spines in cucumber. Methods: Cucumber mRNA profiles of ovaries and pericarps from numerous-spine parent and few-spine parent were generated by deep sequencing, in triplicate, using Illumina HiSeq 4000. Then, clean data (clean reads) were obtained by removing reads containing adapters, reads containing poly-N sequences and low-quality reads from the raw data. Simultaneously, the Q20, Q30 and GC contents of the clean data were calculated. All of the downstream analyses were based on the high-quality clean data. Clean paired-end reads were mapped to the reference genome using TopHat v2.0.12 (Trapnell et al. 2012). Then, the FPKM (fragments per kilobase of transcript sequence per million base pairs sequenced) value of each gene was calculated to estimate gene expression levels (Trapnell et al. 2010). Genes with an adjusted P-value < 0.05 identified by DESeq were assigned as differentially expressed genes(DEGs). Results: We generated 42.96-57.53 million raw reads from each library, and 39.85-54.02 million clean reads were obtained after the removal of low-quality reads and adapter sequences. Among the clean reads, 79.03-80.94% were mapped to the gene database . Based on the KEGG database, pathway enrichment analysis was performed to identify significantly enriched metabolic pathways or signal transduction pathways in DEGs. Plant hormone signal transduction was significantly enriched in up-regulated genes in both F_6DBF compared with M_6DBF and F_0DAA compared with M_0DAA. Conclusions: Based on the transcriptome analysis, we excavated possible biological regulatory networks involved in the formation and development of numerous fruit spines in cucumber. This work will promote the exploration of molecular mechanisms that regulate cucumber fruit spine density.
2018-01-27 | GSE109615 | GEO
Project description:Purpose: We aimed to dissect response of bermudagrass to drought, salt, submergence and heat stresses and identify stress responsive genes inbermudagrass. Methods: A total amount of 3 µg RNA was used for generation of sequencing libraries using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated. Clean reads were obtained by removing low quality reads, reads containing adapter and ploy-N from raw data. At the same time, Q20, Q30 and GC content the clean data were calculated.Paired-end clean reads were aligned to the reference genome of TAIR10 and rice protein sequence from MSU (version_7.0) using TopHat v2.0.12. HTSeq v0.6.1 was used to count the reads numbers mapped to each gene. And then RPKM of each gene was calculated . Differential expression analysis of abiotic stress versus control condition was performed using the DESeq R package (1.18.0). Results:In total, 12 samples with two biological replicates per treatment were used for RNA sequencing analysis. At least 2 G clean bases were generated for each sample. Comparative analysis identified genes modulated by different abiotic stress treatments.
2022-11-01 | GSE140362 | GEO
Project description:Purpose: We aimed to dissect response of Perennial_ryegrass to drought, heat and cold stresses and identify stress responsive genes in Perennial_ryegrass. Methods: The sequencing libraries was constructed using NEBNext® UltraTM RNA Library Prep Kit for Illumina®, sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated. Clean data (clean reads) were obtained after removing reads containing poly-N or adapter, and low quality reads from raw data. Transcriptome assembly was accomplished based on the left.fq.gz and right.fq.gz using Trinity. Gene function was annotated based on the following databases: NR (NCBI non-redundant protein sequences), Pfam (Protein family), KOG/COG/eggNOG (Clusters of Orthologous Groups of proteins), Swiss-Prot (A manually annotated and reviewed protein sequence database), KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology). Differential expression analysis of two groups was performed using the DESeq R package (1.10.1). Genes with an adjusted P-value<0.05 and fold change>2 found by DESeq were assigned as differentially expressed. Results:In total, four samples with two biological replicates per genotype/treatment combination were used for RNA sequencing analysis. At least 5 G clean bases were generated for each sample.After sequencing quality control, a total 137822219 clean reads and 41.05 G clean bases were generated. The Q30 base percentage of each sample was higher than 91.0% (Table S1). A total of 32840 unigenes were obtained after transcriptome assembly. Comparative analysis identified genes modulated by drought, heat and cold stresses
2020-11-08 | GSE141654 | GEO