12443 results for ""non-traditional+communal+storytelling+approach"+novel+segment+noted+in+critical+commentary"

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• An alternative splicing modulator decreases mutant HTT and improves the molecular fingerprint in Huntington’s disease patient neurons

  Huntington's disease (HD) is a neurodegenerative disorder caused by poly-Q expansion in the Huntingtin (HTT) protein. Here, we delineate elevated mutant HTT (mHTT) levels in patient-derived cells including fibroblasts and iPSC derived cortical neurons using a GLP approved HTT assay. HD patients’ fibroblasts and cortical neurons recapitulate aberrant alternative splicing as a molecular fingerprint of HD. Branaplam is a splicing modulator currently tested in a phase II study in HD (NCT05111249). The drug lowers total HTT (tHTT) and mHTT levels in fibroblasts, iPSC, cortical progenitors, and neurons in a dose dependent manner at an IC50 consistently below 10nm without inducing cellular toxicity. Branaplam promotes inclusion of non-annotated novel exons. Amongst, a 115bp frameshift-inducing exon in the HTT transcript in Branaplam treated cells from Ctrl and HD patients leading to a profound reduction of HTT RNA and protein levels. Importantly, Branaplam ameliorates aberrant alternative splicing in HD patients’ fibroblasts and cortical neurons. These findings highlight the applicability of splicing modulators in the treatment of CAG repeat disorders and decipher their molecular effects associated with the pharmacokinetic and -dynamic properties in patient-derived cellular models.

  Study EGAS00001006289

• CD8-targeted IL-2 unleashes tumor-specific immunity in human cancer tissue by reviving the dysfunctional T cell pool

  Tumor-specific CD8+ T cells are key effectors of antitumor immunity but are often rendered dysfunctional in the tumor microenvironment. Immune checkpoint blockade can restore antitumor T cell function in some patients, however most do not respond to this therapy, often despite T cell infiltration in their tumors. We here explored a CD8-targeted IL-2 fusion molecule (CD8-IL2) to selectively reactivate intratumoral CD8+ T cells in patient-derived tumor fragments. Treatment with CD8-IL2 broadly armed intratumoral CD8+ T cells with enhanced effector capacity, thereby specifically enabling reinvigoration of the dysfunctional T cell pool to elicit potent immune activity. Notably, the revival of dysfunctional T cells to mediate effector activity by CD8-IL2 depended on simultaneous antigen recognition and was quantitatively and qualitatively superior to that achieved by PD-1 blockade. Finally, CD8-IL2 was able to functionally reinvigorate T cells in tumors resistant to anti-PD-1, underscoring its potential as a novel treatment strategy for cancer patients.

  Study EGAS00001007712

• Passive and active DNA methylation and the interplay with genetic variation in gene regulation

  DNA methylation is an essential1 epigenetic mark whose role in gene regulation and its dependency on genomic sequence and environment are not yet fully understood2,3. In this study we provide novel insights into the mechanistic relationships between genetic variation, DNA methylation and transcriptome sequencing data in three different cell-types of the GenCord human population cohort4. We find that the association between DNA methylation and gene expression variation among individuals are likely due to different mechanisms from those establishing methylation-expression patterns during differentiation. Furthermore, cell-type differential DNA methylation may delineate a platform in which more local inter-individual changes may respond to or act in gene regulation. We show that unlike genetic regulatory variation, DNA methylation alone does not significantly drive allele specific expression.. Finally, inferred mechanistic relationships using genetic variation as well as correlations with TF abundance reveal both a passive and active role of DNA methylation to regulatory interactions influencing gene expression.

  Study EGAS00001000446

• Somatic mutations reveal lineage relationships and age-related mutagenesis in human hematopoiesis

  Mutation accumulation during human life can contribute to hematopoietic dysfunction; however, the underlying dynamics are unknown. Somatic mutations in blood progenitors can provide insight into the rate and processes underlying this accumulation, as well as the developmental lineage tree and stem cell division numbers. Here, we catalogue somatic mutations in the genomes of human bone marrow-derived and cord blood-derived hematopoietic stem and multipotent progenitor cells (HSPCs) and find that base substitutions accumulate with approximately 17 base substitutions per year in both populations, while insertions and deletions occur sporadically and at low numbers. The majority of mutations in adult HSPCs were acquired after birth and could be explained by the constant activity of various endogenous processes, which also explains the mutation load in acute myeloid leukemia (AML). We construct a developmental lineage tree revealing a polyclonal architecture of the hematopoietic progenitor compartment and providing evidence that developmental clones exhibit multipotency, though lineage biases can be detected. Our approach highlights novel features of human native hematopoiesis and its implications for leukemogenesis.

  Study EGAS00001003068

• Whole-genome sequencing of rare disease patients in a national healthcare system

  Most patients with rare diseases do not receive a molecular diagnosis and the aetiologicalvariants and mediating genes for more than half such disorders remain to be discovered. Weimplemented whole-genome sequencing (WGS) in a national healthcare system to streamlinediagnosis and to discover unknown aetiological variants, in the coding and non-coding regionsof the genome. In a pilot study for the 100,000 Genomes Project, we generated WGS data for13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to1,138 of the 7,065 patients with detailed phenotypic data. We identified 95 Mendelianassociations between genes and rare diseases, of which 11 have been discovered since 2015and at least 79 are confirmed aetiological. Using WGS of UK Biobank1, we showed that rarealleles can explain the presence of some individuals in the tails of a quantitative red blood cell(RBC) trait. Finally, we reported 4 novel non-coding variants which cause disease through thedisruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates asynergy by using WGS for diagnosis and aetiological discovery in routine healthcare.

  Study EGAS00001004364

• RNAseq data to study PRPF6 regulated splice forms in colon cancer cell lines

  Alternative splicing plays critical roles in differentiation, development, and cancer (Pettigrew et al., 2008; Chen and Manley, 2009). The recent identification of specific spliceosome inhibitors has generated interest in the therapeutic potential of targeting this cellular process (van Alphen et al., 2009). Using an integrated genomic approach, we have identified PRPF6, an RNA binding component of the pre-mRNA spliceosome, as an essential driver of oncogenesis in colon cancer. Importantly, PRPF6 is both amplified and overexpressed in colon cancer, and only colon cancer cells with high PRPF6 levels are sensitive to its loss. Our data clearly point to an important role for PRPF6 in colon cancer growth and suggest that a better understanding of its role in alternative splicing in colon cancer is warranted. To determine the specific alternative splice forms that PRPF6 regulates in colon cancer, we plan three experiments: 1. The first involves knocking down expression of PRPF6 in two different cancer cell lines with 3 different siRNAs, and then completing RNA-seq to determine the gene expression changes that occur relative to a non-targeting control siRNA. Because of the role for PRPF6 in pre-mRNA splicing, we especially want to quantify the changes in splice-specific forms of all genes genome-wide to identify genes whose splicing is altered upon PRPF6 knockdown. 2. The second involves immunoprecipitating PRPF6 from two different cancer cell lines and isolating any RNA that is bound to PRPF6, since PRPF6 is an RNA-binding protein. We then want to carry out RNA-seq to identify which RNA molecules co-immunoprecipitated with PRPF6. This will help us determine possible functions for PRPF6 in regulating colon cancer growth. 3. The third involves overexpressing PRPF6 in cell lines and then carrying out RNA-seq to identify any changes in splice-specific gene expression. This will allow us to determine whether increased PRPF6 expression is sufficient to drive alternative splicing changes.

  Dataset EGAD00001000817

• (Epi)genetic Risk Architectures of Opioid-Dependent Brain

  With nearly 20,000 overdose deaths in 2014 alone, opioid addiction (OA) has emerged as one of the most pressing public health crises in recent US history. One-fifth of individuals who try heroin develop an addiction to opioids. Genetics is a major contributor to OA with an estimated 60% heritability, only somewhat less than schizophrenia (80%) which has recently seen substantial gains in identified underlying genetics. Yet, studies to date have failed to uncover most of the genes that predispose individuals to OA, leaving the overwhelming fraction of OA heritability unexplained. The proposed study takes a novel, integrated "omics-based" strategy to investigate the molecular basis of OA and uncover both genetic and epigenetic factors associated with opioid addiction. The premise for our approach is founded on studies from our labs, and others, implicating regulatory variation in common traits and diseases, including those associated with complex brain phenotypes like addiction. We have collected the largest known cohort of postmortem brains from addicts who overdosed on opioids, along with matched control brains from non-users. From both cases and control specimens, we will isolate cells from 2 regions of the brain closely implicated in the addiction phenotype: the Prefrontal Cortex (PFC) and the Nucleus Accumbens (NAc). In Aim 1, we propose ChIP-seq studies to identify regulatory elements that distinguish cases from controls and define the opioid addiction phenotype. The regulatory differences will be connected to their gene targets through high resolution in situ Hi-C. In Aim 2, we propose QTL-based approaches to identify genetic variants that underlie the regulatory differences (hmQTLs). We also propose eQTL analyses to identify genetic variants that underlie differences in transcript levels between cases and controls. Aim 3 leverages the largest heroin addiction GWAS meta-analysis to date to test the hypothesis that SNPs in regions associated with chromatin and expression differences between cases and controls define novel loci for predisposition to OA. Each Aim has the potential for discovery independent of the others (differential HM, RNAexp, QTLs, and variant-phenotype associations) but their synergy is the most powerful component of the proposed study: identifying regulatory pathways that generate, not only phenotype associations, but hypothesized mechanisms for those associations which can be the focus of new opioid addiction prevention and treatment development.

  Study phs002724

• Whole Exome Sequencing in Alopecia Areata Identifies Rare Mutations in KRT82

  Alopecia areata (AA) is an autoimmune disorder, in which the body's own immune cells attack hair follicels resulting in hair loss. It is a complex genetic disease with 14 associated loci previously identified in our genome-wide association study (GWAS). In the study, we performed the whole-exome sequencing (WES) on 849 AA patients with the aim to identify the novel rare variants in genes contributing to AA susceptibility. We performed gene-collapsing analyses and identified keratin 82 (KRT82 Gene ID: 3888) as the highest associated AA gene in the three rare damaging collapsing models with p<6.7E-07 in one of the models. The KRT82 gene is a hair-specific type II keratin expressed in the hair shaft cuticle during the anagen phase of the hair cycle. We reported the lower expression of KRT82 in AA hair follicles, compared to controls, and the KRT82 expression is absent from the bulb region, the site of AA immune attack. This study emphasizes the significance of using WES and gene collapsing analyses to identify rare variation in a functionally relevant risk gene using a moderate sample size.  

  Study phs002632

• METABRIC

  Solid tumors are complex tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Normal cell contamination can dilute cancer cell information and tissue architecture is generally not reflected in molecular assays. To address these challenges, we developed a computational approach based on standard Haematoxylin and Eosin-stained sections and demonstrated its power in a discovery cohort of 323 breast tumors and an independent validation cohort of 241 tumors. First, to deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy-number profiles between samples. Second, we demonstrated that a predictor for survival integrating image-based and molecular features significantly outperforms classifiers based on single data types. Third, we described and validated a novel, independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative methods refine and complement molecular assays of tumor samples and could benefit all large-scale cancer studies.First, to deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy-number profiles between samples. Second, we demonstrated that a predictor for survival integrating image-based and molecular features significantly outperforms classifiers based on single data types. Third, we described and validated a novel, independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative methods refine and complement molecular assays of tumor samples and could benefit all large-scale cancer studies.

  Study EGAS00000000098

• Resolving the Full Spectrum of Human Genome Variation using Linked-Reads

  Large-scale population based analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. Standard short-read approaches, used primarily due to accuracy, throughput and costs, fail to give a complete picture of a genome. They struggle to identify large, balanced structural events, cannot access repetitive regions of the genome and fail to resolve the human genome into its two haplotypes. Here we describe an approach that retains long range information while harnessing the power of short reads. Starting from only 1ng of DNA, we produce barcoded short read libraries. The use of novel informatic approaches allows for the barcoded short reads to be associated with the long molecules of origin producing a novel datatype known as 'Linked-Reads'. This approach allows for simultaneous detection of small and large variants from a single Linked-Read library. We have previously demonstrated the utility of whole genome Linked-Reads (lrWGS) for performing diploid, de novo assembly of individual genomes. In this manuscript, we show the utility of reference based analysis using a single Linked-Read library for full spectrum genome analysis. We demonstrate the ability of Linked-Reads to reconstruct megabase scale haplotypes and to recover parts of the genome that are typically inaccessible to short reads, including phenotypically important genes such as STRC, SMN1 and SMN2. We demonstrate the ability of both lrWGS and Linked-Read Whole Exome Sequencing (lrWES) to identify complex structural variations, including balanced events, single exon deletions, and single exon duplications. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone.

  Study EGAS00001003121