Ontology highlight
ABSTRACT:
PROVIDER: PRJNA779084 | ENA |
REPOSITORIES: ENA
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Project description:Nigeria Sabin-like poliovirus (complete genome)
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Project description:Poliovirus Type 1, 2 and 3 strain:Sabin
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Project description:Methylation analysis of 12 corresponding pairs of tumor endothelial cells (TECs) and normal endothelial cells (NECs) isolated from human colorectal carcinoma (CRC) patients with different prognostic tumor microenvironments (TMEs: Th1-TME vs Control-TME): High and low GBP-1 expression in the tumors detected by IHC was used to categorize the patient-derived cells into Th1-TME and Control-TME (compare Naschberger et al, J Clin Invest 2016 and Naschberger et al, Int J Cancer 2008). Isolation of the samples was done according to Naschberger et al, JoVE 2018. The analysis is paralleled by omics-analysis of the same cell cultures at the transcriptome (E-MTAB-10465) and genome level (E-MEXP-3993).
2023-05-01 | E-MTAB-10467 | biostudies-arrayexpress
Project description:Complete genome of an ST515 Klebsiella pneumoniae involved in Brisbane CR-Ab outbreak 2016-2018
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Project description:Complete genome of an ST1050 Acinetobacter baumannii involved in Brisbane CR-Ab outbreak 2016-2018
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Project description:We report testis H3K4me3 enrichment in an F1 male from a C57BL/6J (B6) x CAST/Eij (CAST) cross (B6 mother, CAST father). This mouse is heterozygous at PRDM9 for a humanized allele (Davies et al. Nature 2016) and the CAST allele. After filtering of promoter H3K4me3 regions, these data serve as a measure of PRDM9 binding enrichment on each homologue. We found that both crossovers and non-crossovers (observed by sequencing F2/F4/F5 genomic DNA) are depleted at "asymmetric" Double-Strand Break hotspots where PRDM9 primarily binds only one of the two homologues. This proves that PRDM9 plays an important role in promoting inter-homologue interactions and can explain why increasing PRDM9 binding asymmetry predicts hybrid infertility. See Li, Bitoun, Altemose et al. 2018 (pending) for a complete summary.
2018-09-28 | GSE119727 | GEO
Project description:A human embryonic fibroblast cell line was synchronously infected with poliovirus in the absence or presence of interferon-α, or with vacciniavirus, a virus that is not inhibited by interferon. The titers were sufficient to yield productive infection in a majority of the cells. The cells were harvested in triplicate at various time-points, and the transcriptosome compared with mock infected cells using oligo-based 35 k microarrays. The project had two purposes: to characterize the cellular response and to look for candidate genes involved in viral defense. The changes in gene expression due to vaccinia virus did not correspond to those caused by poliovirus. More surprisingly, neither did the changes when comparing 8 h and 16 h of poliovirus infection. However, a large proportion of the genes up-regulated by interferon-α were also up-regulated by poliovirus, both at 8 h and 16 h. Interferon-α inhibited poliovirus replication, thus the observations suggest that the cells do launch an antiviral response to poliovirus. Moreover, as interferon genes were not induced, the data indicate that several of the relevant genes can be activated in an interferon independent manner. Further analyses of the data led to a list of candidate antiviral genes. Functional information was limited, or absent, for most of these genes. Keywords: Poliovirus; Vacciniavirus; Interferon; Microarray; Gene expression; Defense genes
2006-10-16 | GSE5549 | GEO
Project description:DNA damage can promote altered RNA splicing and decreased gene expression (Gregersen and Svejstrup, 2018; Milek et al., 2017; Munoz et al., 2009; Shkreta and Chabot, 2015), and aberrant splicing is implicated in neurodegenerative diseases including amyotrophic lateral sclerosis (ALS), Fragile X syndrome and spinal muscular atrophy (SMA) (Conlon et al., 2016; Jia et al., 2012; Loomis et al., 2014; Qiu et al., 2014; Scotti and Swanson, 2016). Therefore, we used RNA-seq data to assess RNA-splicing in double-mutant brain tissue using multivariate analysis of transcriptional splicing (rMATS) (Shen et al., 2014) and a splicing deficiency score algorithm (Bai et al., 2013) to assess intron retention.
2021-12-14 | GSE174841 | GEO