The generation of induced pluripotent stem cells (iPSCs) and the direct conversion approach provide an invaluable resource of cells for disease modeling, drug screening, and patient-specific cell-based therapy. However, while iPSCs are stable and resemble ESCs in their transcriptome, methylome and function, the vast majority of the directly converted cells represent an incomplete reprogramming state as evident by their aberrant transcriptome and transgene dependency. This raises the question of whether complete and stable nuclear reprogramming can be achieved only in pluripotent cells. Here we demonstrate the generation of stable and fully functional induced trophoblast stem cells (iTSCs) by transient expression of Gata3, Tfap2c and Eomes. Similarly to iPSCs, iTSCs underwent a complete and stable reprogramming process as assessed by transcriptome and methylome analyses and functional assays such as the formation of hemorrhagic lesion and placenta contribution. Careful examination of the conversion process indicated that the cells did not go through a transient pluripotent state. These results suggest that complete nuclear reprograming can be attained in non-pluripotent cells. Overall design: Technical duplicates of 10 samples
Extensive Nuclear Reprogramming Underlies Lineage Conversion into Functional Trophoblast Stem-like Cells.
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View SamplesWe Report the genome-wide RNA expression levels in control and schizophrenia hiPSC dervied NPC treated with neuronal media for 2 days. In total about 15,000 gene expression were detected in all samples, of which 1349 were dysregualted. Overall design: Examination, identification and comparision of mRNA expression profliles in control and schizophrenia npc
Common developmental genome deprogramming in schizophrenia - Role of Integrative Nuclear FGFR1 Signaling (INFS).
Specimen part, Subject
View SamplesSarcoidosis + Follow-up 6 month after
Functional genomics and prognosis in sarcoidosis--the critical role of antigen presentation.
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View SamplesSamples collected from human subjects in clinical trials possess a level of complexity, arising from multiple cell types, that can obfuscate the analysis of data derived from them. Blood, for example, contains many different cell types that are derived from a distinct lineage and carry out a different immunological purpose. Failure to identify, quantify, and incorporate sources of heterogeneity into an analysis can have widespread and detrimental effects on subsequent statistical studies.
Optimal deconvolution of transcriptional profiling data using quadratic programming with application to complex clinical blood samples.
Sex, Specimen part
View SamplesA LysM Receptor-like Kinase Mediates Chitin Perception and Fungal Resistance in Arabidopsis
A LysM receptor-like kinase plays a critical role in chitin signaling and fungal resistance in Arabidopsis.
No sample metadata fields
View SamplesExpression of meningioma 1 (MN1) has been proposed to be a negative prognostic molecular marker in adult AML with normal cytogenetics, however its role in pediatric leukemia is unknown. We found elevated MN1 expression in 53 of 88 pediatric leukemia cases: significant amounts of MN1 were found in immature B-cell ALL and most cases of infant leukemia but no MN1 expression was detected in T-cell acute lymphoblastic leukemia (T-ALL). Interestingly 17 of 19 cases harboring MLL-X fusions showed also elevated MN1 expression. Lentiviral siRNA mediated MN1 knock-down resulted in cell cycle arrest and impaired clonogenic growth of 3 MLL-X-positive human leukemia cell lines overexpressing MN1 (THP-1, RS4;11, MOLM13). In a mouse MLL/ENL-induced leukemia MN1 overexpression resulted from retroviral provirus insertion. Strikingly co-expression of MN1 with MLL/ENL resulted in significantly reduced latency for induction of an AML phenotype in mice suggesting functional cooperation. MN1 overexpression in MLL/ENL-carrying cells resulted in expansion of the L-GMP population and facilitated disease induction in secondary recipients. Gene expression profiling allowed to define a number of potential MN1 hematopoietic targets. Up-regulation of CD34, FLT3, HLF, or DLK1 was validated in bone marrow transiently overexpressing MN1, in MN1-induced mouse leukemias, as well as in some cases of pediatric leukemias overexpressing MN1. Taken together, our work suggests that MN1 overexpression is essential for growth of leukemic cells, and that MN1 can act as a cooperating oncogene with MLL-X fusion genes most probably through modification of a distinct gene expression program that leads to expansion of a leukemia initiating cell population.
Functional characterization of high levels of meningioma 1 as collaborating oncogene in acute leukemia.
No sample metadata fields
View SamplesMessenger RNA levels in eukaryotes are balanced by two consecutive regulatory layers. Primary, transcriptional regulation at the level of chromatin and secondary, post-transcriptional regulation of the initial transcript in the cytoplasm. Each layer is individually studied in mechanistic detail, while integration of both processes is required to quantify the individual contribution to steady-state RNA levels. Here we show that chromatin features are sufficient to model transcription rate but with different sensitivities in dividing versus post mitotic cells. In both cases chromatin derived transcript levels explains over 80% of variance in measured RNA level enabling to separate transcription from different post-transcriptional processes. By further inclusion of measurements of mRNA half-life and micro RNA expression data we identify a low quantitative contribution of RNA decay by either micro RNA or general differential turnover to final mRNA levels. Together this establishes a chromatin based quantitative model for the contribution of transcriptional and posttranscriptional processes to steady-state levels of messenger RNA.
Chromatin measurements reveal contributions of synthesis and decay to steady-state mRNA levels.
Specimen part, Disease, Treatment, Time
View SamplesTissues are often made up of multiple cell-types. Blood, for example, contains many different cell-types, each with its own functional attributes and molecular signature. In humans, because of its accessibility and immune functionality, blood cells have been used as a source for RNA-based biomarkers for many diseases. Yet, the proportions of any given cell-type in the blood can vary markedly, even between normal individuals. This results in a significant loss of sensitivity in gene expression studies of blood cells and great difficulty in identifying the cellular source of any perturbations. Ideally, one would like to perform differential expression analysis between patient groups for each of the cell-types within a tissue but this is impractical and prohibitively expensive.
Cell type-specific gene expression differences in complex tissues.
Specimen part
View SamplesFull title: Expression data from whole blood gene expression analysis of stable and acute rejection pediatric kidney transplant patients
Cell type-specific gene expression differences in complex tissues.
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View SamplesWe report the genome-wide RNA expression levels in pluripotent mESC and as mESC differentiate towards a neuronal lineage in response to high levels of Retinoic Acid treatment in vitro. RNA-seq was performed to identify all RNAs expressed in both ESCs and neuronal cells. In total, In total, 14,443 expressed genes were detected, of which 1,834 were up-regulated and 1,477 down-regulated (fold change (FC) > -/+2.0 and p-value < 0.035) during RA-induced neuronal differentiation. The top down-regulated genes included members of the pluripotency core transcriptional network, including Klf4, Sox2, Oct4, Nanog, Suz12, Esrrb, Stat3 and Tcfcp2l1. The top up-regulated genes are important for neuronal differentiation (e.g. Pax3, Irx3, Rest and Foxd3) and reside in the RA-pathway (e.g. various homeobox genes), the retinoic acid receptors and the RA-degradation enzyme Cyp26a1. Overall design: Examination, identification and comparision of mRNA expression profliles in two cellular states.
Global Developmental Gene Programing Involves a Nuclear Form of Fibroblast Growth Factor Receptor-1 (FGFR1).
No sample metadata fields
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