Ontology highlight
ABSTRACT:
PROVIDER: PRJNA735185 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14731500.fastq.gz | Fastqsanger.gz | |||
| SRR14731501.fastq.gz | Fastqsanger.gz | |||
| SRR14731502.fastq.gz | Fastqsanger.gz | |||
| SRR14731503.fastq.gz | Fastqsanger.gz | |||
| SRR14731504.fastq.gz | Fastqsanger.gz |
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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:Solanum americanum fruit RNA-seq rawdata Raw sequence reads
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Project description:Nitrate-reducing iron(II)-oxidizing bacteria are widespread in the environment contribute to nitrate removal and influence the fate of the greenhouse gases nitrous oxide and carbon dioxide. The autotrophic growth of nitrate-reducing iron(II)-oxidizing bacteria is rarely investigated and poorly understood. The most prominent model system for this type of studies is enrichment culture KS, which originates from a freshwater sediment in Bremen, Germany. To gain insights in the metabolism of nitrate reduction coupled to iron(II) oxidation under in the absence of organic carbon and oxygen limited conditions, we performed metagenomic, metatranscriptomic and metaproteomic analyses of culture KS. Raw sequencing data of 16S rRNA amplicon sequencing, shotgun metagenomics (short reads: Illumina; long reads: Oxford Nanopore Technologies), metagenome assembly, raw sequencing data of shotgun metatranscriptomes (2 conditions, triplicates) can be found at SRA in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA682552. This dataset contains proteomics data for 2 conditions (heterotrophic and autotrophic growth conditions) in triplicates.
2021-05-17 | PXD023186 | Pride
Project description:Background: MicroRNAs (miRNAs) represent a family of small endogenous, non-coding RNAs that play critical regulatory roles in plant growth, development, and environmental stress responses. Although Hami melon is an attractive model for valuable biological traits analysis, the role of miRNA action in the fruit development and ripening remains largely unknown. Here, we performed small RNA sequencing to investigate the Hami melon miRNA profiles at four fruit developmental stages Results: Small RNA sequencing yielded raw reads in eight libraries. miRNAs expression profiles were variable at different fruit developmental stages. The expression levels of five known miRNAs were validated by quantitative real-time PCR. Among the identified miRNAs, several miRNAs showed developmentally regulated and differentially expressed pattern during fruit development. Conclusions: Our results present a first comprehensive set of identification and characterization of Hami melon fruit miRNAs and their potential targets, which provide valuable basis for further research on the critical role of miRNAs in melon fruit development.
2017-09-06 | GSE77127 | GEO
Project description:Purpose: Tomato (Solanum lycopersicum) serves as a research model for fruit development; however, while it is an important dietary source of antioxidant nutrients, the transcriptional regulation of genes that determine nutrient levels remains poorly understood. The goals of this study are to investigate dynamic changes of tomato genes during fruit development at transcription level and provides insight into the regulatory mechanism of fruit development and presents candidate transcription factors involved in secondary metabolism. Methods: The transcriptomes of fruit at seven developmental stages (7, 14, 21, 28, 35, 42 and 49 days after flowering) from two tomato cultivars (Ailsa Craig and HG6-61) were evaluated using the Illumina sequencing platform. Raw sequences were filtered and the resulting sets of clean reads were used for the following analysis by tophat and edgeR software. qRT–PCR validation was performed using SYBR Green assays Results: The average number of reads produced for each sample was 9.5 million, with the number of clean reads per sample ranging from 3.3 to 10.9 million. The number of reads that were mapped to the S. lycopersicum genome ranged from 1,786,380 to 6,780,667. A total of 26,397 genes, which were expressed in at least one developmental stage, were detected in the two cultivars, and the expression patterns of those genes could be divided into 20 groups using a K-mean cluster analysis. Gene Ontology term enrichment analysis indicated that genes involved in RNA regulation, secondary metabolism, hormone metabolism and cell wall metabolism were the most highly differentially expressed genes during fruit development and ripening. A co-expression analysis revealed several transcription factors whose expression patterns correlated with those of genes associated with ascorbic acid, carotenoid and flavonoid biosynthesis and 15 of these were validated with qRT–PCR. Correlation analysis revealed a high degree of consistency between transcript abundance determined by qRT-PCR or RNA-seq. Conclusions: Using RNA-seq analysis, the transcript abundance of a total of 26,397 genes was revealed. A total of 823 transcription factors were identified and their expression levels were compared to those of genes encoding enzymes involved in flavonoid, ascorbic acid and carotenoid biosynthesis. This revealed 20, 34 and 37 transcription factors putatively involved in the biosynthesis of flavonoids, ascorbic acid and carotenoids, respectively. This transcriptome study provides insight into the regulatory mechanism of fruit development and presents candidate transcription factors involved in secondary metabolism.
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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