RNA methylation in diabetes [RNA-Seq]
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PROVIDER: PRJNA735941 | ENA |
REPOSITORIES: ENA
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Project description:RNA methylation in diabetes [MeRIP-seq]
| PRJNA735942 | ENA
Project description:N6-methyladenosine (m6A) is one of the most prevalent and abundant epigenetic modifications in various fundamental bioprocesses. We hypothesized that m6A-mediated inflammation pathway contributes to diabetes. Total RNA was extracted from the retinas of wide type rat and their littermates with diabetes by STZ injection. A total amount of 1 μg RNA per sample was used as an input for the RNA sample preparations. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumia), the reagents used in library preparation are NEBNext® Ultra RNA Library Prep Kit for Illumina (NEB, USA) .After cluster generation, the library preparations were sequenced on an Illumina Novaseq platform and 150 bp paired-end reads were generated. The MeRIP-seq was carried out in Novogene (Beijing, China). Briefly, 2 μg total RNA was extracted from the retinas of both wide type mice and their littermates with diabetes. The integrity and concentration of extracted RNA was detected using an Agilent 2100 bioanalyzer (Agilent) and simpliNano spectrophotometer (GE Healthcare), respectively. Fragmented RNA (~100 nt) was incubated for 2 hours at 4 ℃ with anti-m6A polyclonal antibody (Synaptic Systems) in the immunoprecipitation experiment. Then, immunoprecipitated RNA or input was used for library construction with Ovation SoLo RNA-Seq System Core Kit (NuGEN). The library preparations were sequenced on Illumina Novaseq platform with a paired-end read length of 150 bp according to the standard protocols. The sequencing was carried out with three independent biological replicates.
2021-07-01 | GSE176352 | GEO
Project description:RNA-Seq analysis carried out in three different backcrosses based on Iberian breed with Landrace, Pietrain and Duroc breeds
2017-10-31 | PRJEB23068 | EVA
Project description:N6-methyladenosine (m6A) is one of the most prevalent and abundant epigenetic modifications in various fundamental bioprocesses. We hypothesized that m6A-mediated inflammation pathway contributes to diabetes. Total RNA was extracted from the retinas of wide type rat and their littermates with diabetes by STZ injection. A total amount of 1 μg RNA per sample was used as an input for the RNA sample preparations. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumia), the reagents used in library preparation are NEBNext® Ultra RNA Library Prep Kit for Illumina (NEB, USA) .After cluster generation, the library preparations were sequenced on an Illumina Novaseq platform and 150 bp paired-end reads were generated. The MeRIP-seq was carried out in Novogene (Beijing, China). Briefly, 2 μg total RNA was extracted from the retinas of both wide type mice and their littermates with diabetes. The integrity and concentration of extracted RNA was detected using an Agilent 2100 bioanalyzer (Agilent) and simpliNano spectrophotometer (GE Healthcare), respectively. Fragmented RNA (~100 nt) was incubated for 2 hours at 4 ℃ with anti-m6A polyclonal antibody (Synaptic Systems) in the immunoprecipitation experiment. Then, immunoprecipitated RNA or input was used for library construction with Ovation SoLo RNA-Seq System Core Kit (NuGEN). The library preparations were sequenced on Illumina Novaseq platform with a paired-end read length of 150 bp according to the standard protocols. The sequencing was carried out with three independent biological replicates.
2021-07-01 | GSE176353 | GEO
Project description:Profiling of CD14+ monocytes from humans with Type diabetes and without diabetes [RNA-Seq]
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Project description:RNA-seq analysis of diabetes treated with FGF1 variants
| PRJNA642731 | ENA
Project description:Macrophage dysfunction and polarization plays key role in chronic inflammation associated with diabetes and its complications. However, the effect of diabetes on macrophage transcriptome including long non-coding RNAs is not known. Here, we analyzed global changes in transcriptome of bone marrow macrophages isolated from type 2 diabetic db/db mice and control littermates db/+ mice using high throughput RNA-seq technique. Data analysis showed that expression of genes relevant to fibrosis, cell adhesion and inflammation were altered in diabetic db/db mice relative to control db/+ mice. Furthermore, expression of several known and novel long non coding RNAs and nearby genes was altered in db/db mice. Gene ontology and IPA showed activation of signaling netwroks relevant to fibrosis, cell adhesion and inflammatory pathways . This study for the first time demonstrated that diabetes profoundly affects macrophage transcriptome including expression of long non coding RNAs and altered the levels of genes relevant to diabetes complications. Bone marrow macrophages were isolated from 12 weeks old type 2 diabetic male db/db mice and control littermates db/+ mice. These were differentiated in culture for 7-8 days in the presence of 10 ng/ml of MCSF-1 (BMMC) or 20 ng/ml of GM-CSF (BMGM). Then RNA was extracted and used for RNA-seq.
2014-09-15 | E-GEOD-54154 | biostudies-arrayexpress
Project description:DNA methylation may be involved in development of type 1 diabetes (T1D), but previous epigenome-wide association studies were conducted among cases with clinically diagnosed diabetes. Using multiple pre-disease peripheral blood samples on the Illumina 450K and EPIC platforms, we investigated longitudinal methylation differences between 87 T1D cases and 87 controls from the prospective Diabetes Autoimmunity Study in the Young (DAISY) cohort. Change in methylation with age differed between cases and controls in 10 regions. Average longitudinal methylation differed between cases and controls at two genomic positions and 28 regions. Some methylation differences were detectable and consistent as early as birth, including before and after the onset of preclinical islet autoimmunity. Results map to transcription factors, other protein coding genes, and non-coding regions of the genome with regulatory potential. The identification of methylation differences that predate islet autoimmunity and clinical diagnosis may suggest a role for epigenetics in T1D pathogenesis.
2020-03-09 | GSE142512 | GEO
Project description:A Comparative Study of Human Testes and Epididymis through the Proteomics and RNA-seq Methods
2021-06-03 | PXD026440 | iProX