Ontology highlight
ABSTRACT:
PROVIDER: PRJNA699395 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13626839_1.fastq.gz | Fastqsanger.gz | |||
| SRR13626839_2.fastq.gz | Fastqsanger.gz | |||
| SRR13626741_1.fastq.gz | Fastqsanger.gz | |||
| SRR13626741_2.fastq.gz | Fastqsanger.gz | |||
| SRR13626742_1.fastq.gz | Fastqsanger.gz |
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Project description:We applied high throughput sequencing technology to identify microRNA genes in bighead carp and silver carp. We identified 167 conserved miRNAs in bighead carp and 166 in silver carp. By two computational stragegies, we obtained 39 novel miRNAs in bighead carp and 54 in silver carp, for which, no homologs were found in other species. Several miRNA* sequences were found in our dataset as well, some particular ones might have gene regulation function. Gain and loss of family members were observed in several miRNA families, which partially reflected the fate of miRNA gene duplicates.
2010-09-01 | GSE22232 | GEO
Project description:We applied high throughput sequencing technology to identify microRNA genes in bighead carp and silver carp. We identified 167 conserved miRNAs in bighead carp and 166 in silver carp. By two computational stragegies, we obtained 39 novel miRNAs in bighead carp and 54 in silver carp, for which, no homologs were found in other species. Several miRNA* sequences were found in our dataset as well, some particular ones might have gene regulation function. Gain and loss of family members were observed in several miRNA families, which partially reflected the fate of miRNA gene duplicates. Total RNA of juvenile bighead carp and silver carp were sequenced on one Solexa lane, respectively.
2010-09-01 | E-GEOD-22232 | biostudies-arrayexpress
Project description:China produces more than 77.9% of the world's production of silver carp in 2020 with the production of 3812.9 kiloton.3 The high consumption of silver carp in China is mainly by using its edible muscles for manufacture of surimi-based seafoods or other muscle foods, which may contribute high quality protein resource and other valuable nutrients in human diets. This project is to understanding the muscle composition of slaughtered fish skeletal muscle use the proteomics methods. The proteomics was performed based on the improved DDA experiment with extensive fractionation and prolonged separation of peptides, and protein searching database was informed by the Iso-seq transcriptomics.
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Project description:Difference in gut microbiome is linked with health, disease and eventually host fitness, however, the molecular mechanisms by which this variation affects the host fitness are not well characterized. Here, we modified the fish gut microbiota by using antibiotic and probiotic to address the effect of host microbiome on gene expression pattern by using transcriptome.
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Project description:Erythromycin (ERY) is a commonly used antibiotic that can be found in wastewater effluents globally. Due to the mechanisms by which they kill and prevent bacterial growth, antibiotics can have significant unwanted impacts on the fish gut microbiome. The overall objective of this project was to assess the effects of erythromycin and an antibiotic mixture on fish gut microbiomes. The project was split into two experiments to assess gut microbiome in response to exposure with ERY alone or in mixture with other common antibiotics. The objectives of experiment 1 were to understand uptake and depuration of ERY in juvenile rainbow trout (RBT) over a 7 d uptake followed by a 7 d depuration period using three concentrations of ERY. Furthermore, throughout the study changes in gut microbiome response were assessed. In experiment 2, a follow-up study was conducted using an identical experimental design to assess the impacts of an antibiotic-mixture (ERY, ampicillin, metronidazole, and ciprofloxacin at 100 µg/g each). Here, three matrices were analyzed, with gut collected for 16s metabarcoding, plasma for untargeted metabolomics, and brain for mRNA-seq analysis. ERY was depurated from the fish relatively quickly and gut microbiome dysbiosis was observed at 7 d after exposure, with a slight recovery after the 7 d depuration period. A greater number of plasma metabolites was dysregulated at 14 d compared to 7 d revealing temporality compared to gut microbiome dysbiosis. Furthermore, several transformation products of antibiotics and biomarker metabolites were observed in plasma due to antibiotic exposure. Brain transcriptome revealed only slight alterations due to antibiotic exposure. The results of these studies will help inform aquaculture practitioners and risk assessors when assessing the potential impacts of antibiotics in fish feed and the environment, with implications for host health.
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Project description:Pancreatic cancer is the 3rd most prevalent cause of cancer related deaths in United states alone, with over 55000 patients being diagnosed in 2019 alone and nearly as many succumbing to it. Late detection, lack of effective therapy and poor understanding of pancreatic cancer systemically contributes to its poor survival statistics. Obesity and high caloric intake linked co-morbidities like type 2 diabetes (T2D) have been attributed as being risk factors for a number of cancers including pancreatic cancer. Studies on gut microbiome has shown that lifestyle factors as well as diet has a huge effect on the microbial flora of the gut. Further, modulation of gut microbiome has been seen to contribute to effects of intensive insulin therapy in mice on high fat diet. In another study, abnormal gut microbiota was reported to contribute to development of diabetes in Db/Db mice. Recent studies indicate that microbiome and microbial dysbiosis plays a role in not only the onset of disease but also in its outcome. In colorectal cancer, Fusobacterium has been reported to promote therapy resistance. Certain intra-tumoral bacteria have also been shown to elicit chemo-resistance by metabolizing anti-cancerous agents. In pancreatic cancer, studies on altered gut microbiome have been relatively recent. Microbial dysbiosis has been observed to be associated with pancreatic tumor progression. Modulation of microbiome has been shown to affect response to anti-PD1 therapy in this disease as well. However, most of the studies in pancreatic cancer and microbiome have remained focused om immune modulation. In the current study, we observed that in a T2D mouse model, the microbiome changed significantly as the hyperglycemia developed in these animals. Our results further showed that, tumors implanted in the T2D mice responded poorly to Gemcitabine/Paclitaxel (Gem/Pac) standard of care compared to those in the control group. A metabolomic reconstruction of the WGS of the gut microbiota further revealed that an enrichment of bacterial population involved in drug metabolism in the T2D group.
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