Oncorhynchus mykiss
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA298491 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR2640598_1.fastq.gz | Fastqsanger.gz | |||
| SRR2640598_2.fastq.gz | Fastqsanger.gz | |||
| SRR2651090_1.fastq.gz | Fastqsanger.gz | |||
| SRR2651090_2.fastq.gz | Fastqsanger.gz | |||
| SRR2650312_1.fastq.gz | Fastqsanger.gz |
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Project description:Purpose:Our data significantly advance understanding of heat stress regulatory mechanism of miRNA in the head kidney of rainbow trout Methods:miRNAs of rainbow trout were involved in heat stress were identified by high-throughput sequencing of six small RNA libraries of the kidney tissues under control (18℃) and heat-treated (24℃) conditions Results:high-throughput sequencing was performed to identify miRNAs responsive to heat stress. We obtained 41,991,119 and 43,882,123 raw reads and 39,756,736 and 42,538,331 clean reads from under control (18℃) and heat-treated (24℃) .A total of 392 conserved miRNAs and 989 novel miRNAs were identified, of which 78 miRNAs were expressed in different response to heat stress. In addition to, including 393 negative correlation miRNA-target gene pairs Conclusions:through high-throughput sequencing of the six libraries from head kidney tissue of rainbow trout, the expression level of miRNA has significant changes after heat stress.
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Project description:16S raw sequence reads derived from rainbow trout
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Project description:Intestinal microbiota of rainbow trout Raw sequence reads
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Project description:The aim of this sequencing experiment was to make available tissue expression panels for selected fish species for comparative expression studies between the species. Tissue samples were collected for zebrafish (Danio rerio), medaka (Oryzias latipes), and rainbow trout (Oncorhynchus mykiss). Tissue types included liver, skin, muscle, heart, gut, gill, eye, brain for all three species, with additionally pyloric caeca, kidney, head kidney, and spleen for rainbow trout. Only liver samples were taken in replicate of four or three for rainbow trout. All fish were raised under standard rearing conditions for the species. Total RNA was extracted from the tissue samples and paired‐end sequencing of sample libraries was completed on an Illumina HiSeq 2500 with 125‐bp reads. Processed count tables per species as raw counts, FPKM, or TPM, were generated from read alignment to the Ensembl genomes of the respective species using STAR and gene level counting using RSEM and Ensembl gene annotation.
2020-04-30 | E-MTAB-8959 | biostudies-arrayexpress
Project description:Transcriptional profiling of rainbow trout liver cells comparing liver cells from small fish with liver cells from large fish at two time periods.
2012-11-29 | GSE42583 | GEO
Project description:Transcriptional profiling of rainbow trout muscle cells comparing muscle cells from small fish with muscle cells from large fish at two time periods.
2012-11-29 | GSE42582 | GEO
Project description:Purpose: Next-generation sequencing (NGS) of small RNAs allows transcriptome level analysis of the miRNAome. The goals of this study are to identify differentially regulated hepatic miRNAs in response to a dominant or subordinate social status using small RNA next generation sequencing. Specific quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods were used to validate optimal high-throughput data analysis, and in silico prediction to identify bona fide target pathways regulated by differentially regulated miRNAs following these social interactions. Method: Small RNA sequencing was performed using four randomly selected samples from each treatment group were used for sequencing. The quality of total RNA was confirmed by RNA Integrity Numbers greater than 9.0 using an Agilent Technologies 2100 Bioanalyzer. Nucleotide fractions (15-50) of small RNA were isolated from the total RNA using polyacrylamide gel electrophoresis and were ligated to a 30 adapter followed by a 50 adapter (Illumina, San Diego, CA, USA). The small RNA ligated to the adaptors was reverse transcribed to cDNA, PCR amplified and gel purified. The gel-extracted cDNA was used for library preparation, which was further used for cluster generation on Illumina's Cluster Station before sequencing using Illumina GAIIx. Raw sequence data was obtained from image data using Illumina's Sequencing Control Studio software version 2.8 (SCS v2.8) following real-time sequencing image analysis and base-calling by Illumina's Real-Time Analysis version 1.8.70 (RTA v1.8.70). The ACGT101-miR v4.2 pipeline (LC Sciences) was used to analyze sequenced data. Sequences with low Q scores, reads mapped to mRNA, RFam, Repbase and piRNA database were deleted and unique families were generated from identical sequences. These filtered unique sequences were then mapped to fish pre-miRNA and miRNA using miRBase or to the rainbow trout genome (Berthelot et al., 2014) to identify conserved miRNA following ACGT-101 User's Manual. Unique or novel miRNAs were identified after the BLAST performed against fish miRNAs from miRbase database (release 21) and published miRNAs from rainbow trout (Mennigen et al., 2016). The miRNAs that do not match any sequences in the specified databases and have the propensity of forming hairpin structure with the extended sequences at the mapped positions were classified as unique miRNAs. These unique miRNAs were further classified into different groups depending on the mappable reads to selected miRNAs in miRbase. Differentially expressed miRNAs were identified using the statistical software R (Version 3.2.2) package DESeq2 for one-way ANOVA comparison of all three treatment groups. Real-time RT–PCR validation was performed using SYBR Green assays Results: 24 miRNAs are differentially regulated by social status. 9 miRNAs are higher expressed in dominant trout. 15 miRNAs are higher expressed in subordinate trout. Conclusions: Our study represents the first detailed analysis of the rainbow trout miRNAome in response to nutritional stimuli. Specifically, we here identify common hepatic miRNAs differentially regulated by refeeding following a short-term fast (2d), as well as miRNAs differentially regulated in the postprandial state depending on the dieatary stimulus (no carbohydrates compared to >20% dietary carbohydrates)
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Project description:Rainbow trout is a typical cold-water fish, with the intensification of global warming, high temperatures severely restrict the development of aquaculture in summer. Understanding the molecular regulation mechanisms of rainbow trout in response to heat stress will be salutary to alleviate heat stress-related damage. In the present study, we performed transcriptome analysis of liver tissues in rainbow trout under heat stress (24℃) and control (18℃) conditions to identify induced lncRNAs and pathways by heat stress. More than 658 million clean reads and 5,916 lncRNAs were identified from six liver libraries. A total of 927 novel lncRNAs were generated and 428 differentially expressed lncRNAs were screened through stringent thresholds. The RNA-seq results were verified by RT-qPCR. In addition, the regulatory network of important functional lncRNA-mRNA were constructed. GO and KEGG enrichment analysis of target gene of differentially expressed lncRNAs were performed. Many target genes involved in maintaining homeostasis or adapting to stress and stimuli were highly induced under heat stress. Several important regulatory pathways were involved in heat stress, including thyroid hormone signaling pathway, PI3K-Akt signaling pathway, estrogen signaling pathway, etc. This result broadens our understanding of lncRNA associated with heat stress and provides new insights into lncRNA-mediated regulation of rainbow trout heat stress.
2019-08-11 | GSE135668 | GEO
Project description:Rainbow trout (Oncorhynchus mykiss) is highly sensitive to high-temperature stress as an important economic cold-water fish. While previous research has concentrated on the transcriptomic to acute heat stress in rainbow trout, there remains a gap in knowledge regarding the overarching regulatory mechanisms at the translation level. In our research, we utilized a combination of transcriptomic and translatomic analyses to investigate the intricate molecular response mechanisms in the liver of rainbow trout when subjected to heat stress. Through comprehensive multi-omics analysis, we revealed the dynamic translational pattern of rainbow trout liver under heat stress for the first time. Comparative analysis of ribosome analysis data with RNA-seq data showed that the fold changes of gene expression at the transcriptional level were highly correlated (R2 = 0.83) with those at the translational level globally. In total, 2,203 genes exhibited significant alterations exclusively within the translational level. However, the limited overlap in response genes between transcription and translation under heat stress suggests that these two processes may independently modulate the cellular response to thermal challenges. Significant changes in the translation efficiency of 809 genes were observed under heat stress. Further analysis indicated that the translation efficiency of genes were strongly influenced by sequence characteristics such as GC content, coding sequence length and NMFE. Moreover, 3,468 putative uORFs were identified in 2,676 genes, which potentially modulating translation efficiency of mORFs. These findings provide a novel perspective for understanding the physiological adaptations of rainbow trout in response to changes in ambient temperature.
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