Dataset Information

ScRNA-seq of day 32 p.i. GC B cells induced by experimental Plasmodium infection following the inducible deletion of IL-21 from CD4 T cells on day 16-18

ABSTRACT: scRNA-seq of day 32 p.i. GC B cells induced by experimental Plasmodium infection following the inducible deletion of IL-21 from CD4 T cells on day 16-18

PROVIDER: PRJNA1065457 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	SRR27585756_1.fastq.gz	Fastqsanger.gz
	SRR27585756_2.fastq.gz	Fastqsanger.gz
	SRR27585757_1.fastq.gz	Fastqsanger.gz
	SRR27585757_2.fastq.gz	Fastqsanger.gz
	SRR27585758_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 8

Similar Datasets

Project description:This study compared the gene expression of extraembryonic membranes (EEM) from in vitro produced (IVP) and in vivo (AI) derived embryos. Samples of EEM from AI and IVP pregnancies were collected on days 18 and 32. A piece of the conceptus (day 18) or chorioallantois (day 32) were used for DNA and RNA isolation and subsequent determination of the sex by amplification of a Y-linked region of the DNA. The male and female ratios were analyzed by Chi-square of SAS. A subset of three female and three male EEM samples from each group (AI and IVP, days 18 and 32) were used for transcriptome analysis. Differentially expressed genes (DEGs) between groups, sex, and days were determined using edgeR-robust. A false discovery rate (FDR) <0.05 was used for statistical significance, and Toppgene platform was used for biological processes analysis. Sex ratio was similar on day 18 for AI and IVP groups. On day 32, the IVP group had a greater number of females than males (75 vs 25%, P=0.004). On day 18 female embryos, out of 71 DEGs identified, 50 were upregulated in IVP, and 21 in AI. The trophectoderm marker, TKDP2, was upregulated in the AI group, whereas IGF2, which is involved in placenta development, and APOA2, APOB, and APOE, which are important for lipid metabolism, were upregulated in the IVP group. Male embryos on day 18 had 22 DEGs, being 15 upregulated in AI and 7 in IVP. Female embryos on day 32 had 74 DEGs, with 21 upregulated in AI and 53 in IVP embryos. Some of the genes with increased expression in the IVP group were PTGIS, APOB, and APOH, which are related to lipid synthesis and metabolism. Male embryos on day 32 presented 899 DEGs, 564 upregulated in AI and 335 in IVP. Embryos from IVP had increased expression of genes related to embryo development, morphogenesis, neurogenesis, and developmental growth. In addition, male IVP embryos had decreased expression of genes related to lipid and carbohydrate metabolism. Interestingly, PLAC8B, BRB, pregnancy-associated glycoproteins (PAG) 7, 9, 10, and 19, were also downregulated in IVP male EEM. When comparing IVP males and females, there were 6753 DEGs, with 3091 being upregulated in females, and 3662 in male conceptuses on day 18. Some of the genes upregulated in females were related to placental function such as TKDP4, PLAC8A and PAGs 6, 8, 10, 12, 17, 18 and 19. On males, IFNT-related genes were upregulated (IFNT, IFNT2 IFNT3 and IFN-T). On day d32, there were 6772 DEGs, with 3252 genes with increased expression in female, and 3520 in male placentas. Among the genes increased in female placentas are genes involved in placentation: PAGs 17, 19, 9 and PLAC8B. On the other hand, PAG1 was detected as highly expressed in male placentas. In conclusion, IVP-derived male embryos were more susceptible to alterations in gene expression and these effects extend to the peri-implantation period including genes associated with placental development and markers of placental function.

Project description:Glucocorticoids (GCs) are commonly used to treat patients suffering from lymphoid malignancies i.e. leukemia and multiple myeloma. Although GCs are known to be strong inducers of apoptosis in lymphoid cells, the molecular determinants of GC therapy resistance are poorly understood. Although GC treatment triggers important changes in gene expression, few studies have addressed the regulatory role of small regulatory microRNAs (miRNAs) in GC therapy response. Only recently, aberrant microRNA expression has been linked to the development of haematological malignancies and microRNAs have become master regulators of drug resistance. We identified GC inducible mRNA and microRNA transcription profiles in GC sensitive MM1S as compared to GC resistant MM1R cells. Transcriptome analysis revealed that GCs regulate multiple genes involved in cell cycle control, cell organization and cell death in MM1S, which remain unaffected in MM1R cells. Correspondingly, GCs selectively trigger cell death in MM1S but not in MM1R. Out of 32 microRNAs responsive to GC in MM1S cells but not in MM1R cells, mir-150 was identified as the most persistent GC responsive microRNA. Furthermore, Ingenuity Pathways Analysis (IPA) revealed that ectopic transfection of a synthetic mir-150 mimics GC therapy response in MM1S cells, associated with selective changes in mRNA levels of typical GR transactivated and transrepressed target genes. Although mir-150 largely mirrors GC responsive changes in gene expression of the transcription factor Myb, GR chaperone FKBP5, cell cycle modulator proteins (IL23A, SKP2, CDKN1A), chemokine signaling proteins (CXCR4, CX3CR1, CCL3) and mTOR/UPR stress related proteins (DDIT4, TXNIP), we also observed mir-150 selective effects on transcription factors (NR3C2 (MR), Myb, Fos, Jun, C/EBP-beta, IRF4, NFE2L1, ATF3, ATF4,), chaperone molecules HSPA8, HSP90AB1), the sodium channel SCNN1G and UPR stress proteins (TRIB3, DDIT3). Remarkably, mir-150 overexpression was not able to overcome GC therapy resistance, since we could not detect GC like effects of mir-150 in GR (NR3C1) deficient MM1R cells. Altogether GC-inducible mir-150 adds a novel complex layer of regulation for fine tuning GC specific therapeutic responses in multiple myeloma.

Dataset Information

ScRNA-seq of day 32 p.i. GC B cells induced by experimental Plasmodium infection following the inducible deletion of IL-21 from CD4 T cells on day 16-18

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets