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• Investigating transcriptional changes in rapidly differentiated iPSC-derived neurons (i3Ns) harbouring the SNCA A53T mutation +/- RSL3

  In this study we performed bulk RNA sequencing of a iPSC-derived rapid neuronal model harbouring the Parkinson's disease associated A53T mutation in SNCA. These neurons were subsequently treated with a low dose of RSL3 (300nM) for 6 hours to establish the transcriptional impact of ferroptosis induction in the presence or absence of SNCA A53T mutation.

  Study EGAS50000001536

• The Gene Partnership (TGP) - eMERGE Data

  The Gene Partnership (TGP) is a prospective longitudinal registry at Boston Children's Hospital (BCH) to study the genetic and environmental contributions to childhood health and disease, collect genetic information on a large number of children who have been phenotyped, and implement the Informed Cohort and the Informed Cohort Oversight Board (ICOB). The term "The Gene Partnership" reflects a partnership between researchers and participants. Children seen at BCH are offered enrollment, as are their parents and siblings. DNA is collected on all enrollees. BCH has a comprehensive EMR system, and virtually all inpatient and outpatient data are captured electronically. Clinical data in the BCH EMR is loaded in the i2b2 data warehouse which is available to investigators. Cases, phenotypes, and covariates are ascertained using the i2b2 database. Participants at BCH in TGP have consented to receive any research result and/or incidental finding that arises from studies using TGP that is approved by the Informed Cohort Oversight Board (ICOB) and is in accordance with the participants' preferences; results are returned through the Personally Controlled Health Record (PCHR). BCH and Cincinnati Children's Hospital Medical Center (CCHMC) have partnered as the Pediatric Alliance for Genomic and Electronic Medical Record (EMR) Research (PAGER) site for the eMERGE Phase II network for pediatric institutions, and the cohort for eMERGE at BCH is TGP.

  Study phs000495

• Genetic Control of Expression and Splicing in Developing Human Brain

  Most genetic risk for human diseases lies within non-coding regions of the genome that are predicted to regulate gene expression in a tissue- and stage-specific manner. Given the importance of regulatory pathways during brain development, we characterized the genetic control of the transcriptome in 201 mid-gestational human brains, identifying 7962 eQTL and 4635 sQTL. By integration with GWAS, we characterized the genes and isoforms contributing to specific neuropsychiatric disorders, including SCZ and ASD, as well as other cognition or behavioral-related phenotypes. SCZ and ASD impact distinct developmental gene co-expression modules, yet in both disorders, common and rare genetic variation converge. These analyses demonstrate the highly distinctive effects of transcriptional control, as well as divergent age-related contributions to disease. More broadly, these findings demonstrate the genetic mechanisms by which early developmental events have a striking and widespread influence on adult anatomical and behavioral phenotypes.

  Study phs001900

• Combined – whole blood and skin fibroblasts - transcriptomic analysis in Psoriatic arthritis.

  Whole blood RNA sequencing was performed longitudinally in 27 subjects with PsA at the beginning, one month and six months after treatment and response to therapy was defined at 6 months. As control groups 7 healthy individuals and 9 subjects with rheumatoid arthritis were recruited combined with public RNA-sequencing datasets from patients with psoriasis and systemic lupus erythematous. Differential expression analysis and weighted gene co-expression network analysis were performed to identify gene expression signatures, while deconvolution and flow cytometry to characterize the peripheral blood immune cell profile. RNA sequencing of skin fibroblasts was performed in a subset of affected (n=3) and healthy individuals (n=3) combined with CellChat to identify the blood-skin fibroblasts interaction network.

  Study EGAS00001006288

• Targeted Linked-Read DNA-seq Analysis of Castration-Resistant Prostate Cancers

  Androgen receptor (AR) inhibition is standard of care for advanced prostate cancer (PC). However, its efficacy is limited by progression to castration-resistant PC (CRPC), usually due to AR re-activation via mechanisms that include AR amplification and structural rearrangement. These two classes of AR alterations often co-occur in CRPC tumors, but it is unclear whether this reflects intercellular or intracellular heterogeneity of AR. It is important to resolve the mechanisms of AR genomic rearrangements to develop new therapies and predictive biomarkers for PC. We developed a targeted linked-read DNA sequencing assay to interrogate alterations in AR and a panel of genes known to be amplified or mutated in CRPC. Linked-read DNA-sequencing libraries were generated using the 10X Genomics Chromium platform and subjected to hybridization enrichment using a custom-designed Agilent SureSelect bait panel. Post-capture DNA-seq libraries were pooled and sequenced on an Illumina HiSeq 2500 using 2x150 bp settings. This targeted linked-read DNA-seq assay was used to interrogate a set of 6 benchmarking samples harboring known AR gene rearrangements and other alterations in AR, as well a panel of 6 patient-derived xenograft CRPC tumors and 23 clinical CRPC tumors. In this cohort, we identified a subset of samples that developed complex, multiply-rearranged AR gene structures in conjunction with very high AR copy number. The data that will be made available through dbGaP are raw FASTQ files.

  Study phs003343

• Sample Multiplexing Oligo Comparison

  In this study, we compared various multiplexing reagents, including MULTI-Seq, Hashtag antibody, and CellPlex, in patient-derived xenografts (PDXs). We found that all multiplexing reagents worked well in cell types robust to ex vivo manipulation but suffered from signal-to-noise issues in more delicate sample types. We also compared the performance of fixed scRNA-Seq kits and CRISPR-based destruction of non-informative genes.

  Study EGAS50000000153

• Human colorectal cancer single-cell RNA sequencing

  The aim was to investigate changes in transcriptomics following irradiation. This was studied in colorectal cancer-patient derived organoids. Analysis was performed with scRNA-seq.

  Study EGAS50000001348

• MPN_mutation_order_followup

  To evaluate the presence of mutations in frequently mutated genes in MPN by performing targeted resequencing of a selected gene panel comprising of 111 genes across 40 samples with MPN.

  Study EGAS00001000663

• RNA stability controlled by m6A methylation contributes to X-to-autosome dosage compensation in mamals

  In mammals, X-chromosomal genes are expressed from a single copy since males (XY) possess a single X chromosome, while females (XX) undergo X inactivation. To compensate for this reduction in dosage compared to two active copies of autosomes, it has been proposed that genes from the active X chromosome exhibit dosage compensation. However, the existence and mechanism of X-to-autosome dosage compensation are still under debate. Here, we show that X-chromosomal transcripts are reduced in m6A modifications and more stable compared to their autosomal counterparts. Acute depletion of m6A selectively stabilises autosomal transcripts, resulting in perturbed dosage compensation in mouse embryonic stem cells. We propose that higher stability of X-chromosomal transcripts is directed by lower levels of m6A, indicating that mammalian dosage compensation is partly regulated by epitranscriptomic RNA modifications.

  Dataset EGAD00001010194

• Tumor-derived cell lines as pharmacogenomic models to predict therapeutic vulnerabilities in hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is a heterogeneous aggressive malignancy with low efficacy of current therapies at advanced stages. We integrated molecular and pharmacological profiling of a large panel of liver cancer cell lines (LCCL) to assess their clinical relevance as HCC preclinical models and identify new effective therapies and biomarkers of response. We performed multi-omic analysis including whole-exome, RNA and miRNA sequencing and quantification of 126 proteins in a series 34 LCCL coupled with a screening of 29 anti-cancer agents. Molecular profiles of LCCL and primary HCC were compared and we searched for molecular features associated with drug response. Our panel of LCCL faithfully recapitulated the most aggressive molecular "proliferation class" of HCC. Genomic alterations of the RAS-MAPK pathway correlated with trametinib sensitivity that was more potent than FGFR4 inhibitors in tumor cells depending on the FGF19/FGFR4 pathway. Moreover, we showed that FGF19 amplification was only functional in tumor cells that retained a hepatocyte differentiation program with expression of FGFR4, KLB and NR1H4 highlighting the complex interplay between the genomic and transcriptomic context in drug response. We also identified drugs/combination that could target efficiently the transcriptomic "progenitor subclass of HCC", as well as specific genetic contexts such as inactivating mutations in TSC1/TSC2 and TP53 associated with higher sensitivity to the mTOR inhibitor rapamycin and the AURKA inhibitor alisertib, respectively. LCCL represent relevant preclinical models for drug-biomarker discovery in HCC and enabled to identify molecular contexts linked with particular therapeutic vulnerabilities that may be useful to stratify patients in future clinical trials

  Study EGAS00001003536