7193 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

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• 1_RNAseq_sALS_Ctrl

  iPSC-derived motor neurons form sporadic ALS and Controls. 4 sALS iPSC lines and 4 Ctrl iPSC lines.

  Dataset EGAD00001008424

• Human primary and metastatic colorectal cancer (CRC) samples

  Bank of human both primary and metastastic colorectal cancer sample RNAseq

  Dataset EGAD00001009712

• Multiome

  This dataset contains the raw sequencing data (Runs) from all of the 10x Genomics single-cell Multiome Experiments

  Dataset EGAD00001009824

• scRNA-seq

  This dataset gather scRNAseq data performed for MM.1S cell line in control and dex conditions at 4h and 24h

  Dataset EGAD00001011139

• BLUEPRINT Gene expression profiles of human hematopoietic progenitors

  Gene expression was analyzed for stem/progenitor cell types and terminally differentiated cell types of the human blood lineage (HSC, MPP, CMP, GMP, CLP, MLP0, MLP1, MLP2, MLP3).

  Dataset EGAD00001002733

• scRNAseq of neuroblastoma patients

  This dataset contains 19 scRNAseq realized on neuroblastoma patients biopsies straight after surgical act.

  Dataset EGAD00001006556

• PacBio sequence data

  PacBio sequencing data of HKCI-2, HKCI-C1, HKCI-C2, HKCI-C3, HKCI-4, HKCI-9, HKCI-11, HKCI-5A and MIHA. All the data (9 samples) were saved in pacbio hdf5 format.

  Dataset EGAD00001004475

• A Clone's Genomic Stability as a Biomarker of Its DNA-Damage Resilience

  A main problem in the treatment of advanced cancers, including gastric cancers and glioblastoma, is the incertitude at which we predict how individual patients will respond to DNA-damaging agents, especially on the long run. Knowing the mechanism behind a patient's response, or the lack thereof, will help us depart from the oversimplified “more-is-better” and “one-size-fits-all” principles according to which DNA-damaging agents are administered. This will improve clinical outcome by allowing us to pinpoint those who would respond better and longer to lower doses than to higher doses of DNA-damaging agents. Under the assumption that the success of DNA-damaging therapy increases with the proliferation rate of a relatively homogeneous tumor population, there was little reason to assume anything other than monotonic dose-response relations. With the recent paradigm shift that most cancers are in fact DNA mosaic products of ongoing evolution, comes the urgency to reconsider these fundamental principles behind DNA-damaging therapy administration. As the developers of one of the first DNA deconvolution methods and with access to technologies to profile the transcriptomes of up to 10,000 cells simultaneously, we are equipped to embark on first personalized dose-finding strategies for DNA-damaging therapies. We will test the potential of the very long-term legacy that DNA-damage entails on a cell “genomic instability” as new biomarker of DNA-damage response. Our preliminary studies showed that, for most cancer types, DNA-damaging agents change a clone's genomic instability and that clones succumb to a limit in the amount of genomic instability they can tolerate. In particular, our results showed that patients with intermediate genomic instability have a very poor outcome and that this relation is only evident among treatment-naive patients, but not among patients treated with DNA-damaging agents. Further they show that we can measure genomic instability per clone and that clones with extreme genomic instability typically don't grow large. Our hypothesis that genomic instability, rather than proliferation rate, determines how sensitive a tumor is to DNA-damaging agents on the long-term, is founded on two unexpected findings. Patients with extremely high genomic instability per tumor clone have an exceptionally good outcome. Aim 1 will integrate exome- and single cell RNA-Seq (scRNA-Seq) data to characterize clones and to measure how much genomic instability they can tolerate. Low genomic instability is associated with reduced benefit from DNA-damaging agents. Aim 2 will use comet assays and treatment history to quantify DNA damage per clone, relating it to the clones' ability to tolerate DNA damage and to changes in the genomic instability of therapy-surviving clones.

  Study phs003762

• Genome and Transcriptome Assembly Reveals SVA-Mediated Aberrant Splicing in X-Linked Dystonia Parkinsonism

  X-linked Dystonia-Parkinsonism (XDP, DYT3) is a long-standing quandary in human disease genetics. XDP is predominantly observed on Panay island in the Philippines. This study is one of the first of its kind to interrogate an unsolved Mendelian disorder by integrating genome and transcriptome assembly methods using Illumina, 10X Genomics, Pacific Biosciences, and Agilent genome targeting technologies. These data provide strong evidence for a pathogenic link between a noncoding SVA retrotransposon and XDP. We demonstrate that this Mendelian disorder is associated with a sine-VNTR-Alu (SVA) retrotransposon that inserted into the TAF1 gene and is shared by all XDP probands, yet never observed in controls from worldwide populations. Transcriptome assembly in iPSC-derived neural stem cells (NSCs) and neurons revealed that this SVA caused aberrant splicing and significant intron retention, which was negatively correlated with TAF1 expression. Remarkably, CRISPR/Cas9 excision of the SVA rescued the aberrant transcriptional signature and normalized expression of TAF1 in patient-derived NSCs. We have also interrogated iPSC-derived microglia to investigate the contribution of glial components to the cellular and molecular deficit, effect of TNF treatment on XDP transcriptional signatures. To further understand what XDP may have in common with other hereditary dystonias (such as DYT6), we are further comparing these signatures to ones associated with dystonia-specific variants in proteins that, like TAF1, are also involved in regulating transcription, i.e. THAP1. 

  Study phs001525

• Single-nucleus fixed mRNA profiling of FFPE samples

  Single-nucleus fixed mRNA profiling of FFPE samples from patients after sex-mismatched blood stem cell transplantation and matched controls.

  Dataset EGAD50000000047