Ontology highlight
ABSTRACT:
PROVIDER: PRJNA816064 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18326300.fastq.gz | Fastqsanger.gz | |||
| SRR18326301.fastq.gz | Fastqsanger.gz | |||
| SRR18326296_1.fastq.gz | Fastqsanger.gz | |||
| SRR18326296_2.fastq.gz | Fastqsanger.gz | |||
| SRR18326297_1.fastq.gz | Fastqsanger.gz |
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Project description:To investigate the contribution of parental genomes to early embryogenesis, we systematically profiled the single-cell transcriptomes of human biparental and uniparental embryos from one-cell to morula stages. We observed that uniparental embryos exhibit variable and overall less activation patterns of embryonic genome activation (EGA). Comparative transcriptome analysis identified 807 maternally biased expressed genes (MBGs) and 581 paternally biased expressed genes (PBGs) in preimplantation stages. MBGs became obviously appeared at the four-cell stage and contribute to EGA initiation, whereas PBGs preferentially appeared at the eight-cell stage, and possibly affect embryo compaction and trophectoderm specification. Regulatory network analysis revealed DUX4, EGR2 and DUXA as key transcription factors for MBGs expression as well as ZNF263 and KLF3 for PBGs expression. Furthermore, we revealed that the expression of MBGs and PBGs especially PBGs, probably due to DNA methylation differences between the parental genomes. Together, our results provide a valuable resource to understand parental genome activation and may help to dissect parent-of-origin effect on early human development.
2019-10-08 | GSE133854 | GEO
Project description:To investigate the contribution of parental genomes to early embryogenesis, we systematically profiled the single-cell transcriptomes of human biparental and uniparental embryos from one-cell to morula stages. We observed that uniparental embryos exhibit variable and overall less activation patterns of embryonic genome activation (EGA). Comparative transcriptome analysis identified 807 maternally biased expressed genes (MBGs) and 581 paternally biased expressed genes (PBGs) in preimplantation stages. MBGs became obviously appeared at the four-cell stage and contribute to EGA initiation, whereas PBGs preferentially appeared at the eight-cell stage, and possibly affect embryo compaction and trophectoderm specification. Regulatory network analysis revealed DUX4, EGR2 and DUXA as key transcription factors for MBGs expression as well as ZNF263 and KLF3 for PBGs expression. Furthermore, we revealed that the expression of MBGs and PBGs，especially PBGs, probably due to DNA methylation differences between the parental genomes. Together, our results provide a valuable resource to understand parental genome activation and may help to dissect parent-of-origin effect on early human development.
2019-10-08 | GSE133855 | GEO
Project description:Background & Aims: Patients with beta-catenin (encoded by CTNNB1)-mutated hepatocellular carcinoma (HCC) have demonstrated limited clinical benefit to first-line immunotherapy (IO). Animal models of HCC expressing mutant-beta-catenin and additional aberrations via hydrodynamic tail vein injection with sleeping beauty transposon/transposase (SB-HDTVI) represent clinically relevant human HCC subsets. Here, we perform transcriptomic analysis on multiple beta-catenin-mutated and non-mutated HCC animal models to identify Mutated beta-catenin Gene Signature (MBGS) for HCC patient stratification for CTNNB1-mutations and IO response. Methods: We co-expressed in mice mutant-NFE2L2 and hMET +- mutant-CTNNB1 via SB-HDTVI and monitored for HCC development. Bulk RNA-sequencing was assessed for transcriptional differences between various beta-catenin-mutated and non-mutated models. MBGS was generated for predictive ability of CTNNB1 mutations and IO resistance in multiple HCC patient cohorts. Results: Co-expression of S45Y-beta-catenin + G31A-NFE2L2 + hMet (beta-N-M) resulted in HCC development by 4.5 weeks while co-expression of G31A-NFE2L2 + hMet (N-M) led to HCC by 14 weeks with tumors being positive for expected targets by immunohistochemistry (IHC). Bulk RNA-sequencing comparing beta-catenin-driven versus non-beta-catenin driven models yielded 95 common upregulated genes. Differential gene expression analysis of the common genes comparing CTNNB1-mutated vs non-mutated TCGA patients narrowed the gene panel to 13-(or 10-) genes. This MBGS predicted CTNNB1-mutation status in TCGA (n=374) and French (n=398) patient cohorts (with ROC AUC of 0.90 and 0.94). High MBGS expression was also associated with no overall and progression-free survival benefit when comparing atezolizumab + bevacizumab versus sorafenib arms in IMbrave150 cohort implying fewer treatment effects. Conclusions: In an era of patient molecular stratification for HCC, MBGS may aid in optimally selecting patients for IO through diagnosis of a molecular subset which lacks optimal response.
2024-10-09 | GSE261316 | GEO