3246 results for "*geneti*"

in 23.13 milliseconds.

• Single Duplex DNA Sequencing with CODEC Detects Mutations with High Sensitivity

  Detecting mutations from single DNA molecules is crucial in many fields but challenging. Next generation sequencing (NGS) affords tremendous throughput but cannot directly sequence double-stranded DNA molecules (single duplexes) to discern the true mutations on both strands. Here, we present Concatenating Original Duplex for Error Correction (CODEC) which confers single duplex resolution to NGS. CODEC affords 1,000-fold higher accuracy than NGS, using up to 100-fold fewer reads than Duplex Sequencing. CODEC revealed mutation frequencies of 2.72 x 10-8 in sperm of a 39-year-old individual, and somatic mutations acquired with age in blood cells. CODEC detected genome-wide clonal hematopoiesis mutations from single DNA molecules, single mutated duplexes from tumor genomes and liquid biopsies, microsatellite instability (MSI) with 10-fold greater sensitivity, and mutational signatures and specific tumor mutations with up to 100-fold fewer reads. CODEC enables more precise genetic testing and reveals biologically significant mutations which are commonly obscured by NGS errors. We applied CODEC to clinical colon and breast neoplasm samples and uncovered expected mutational signatures including homologous recombination deficiency (HRD) and MSI.

  Study phs003255

• Genetic Analysis of Skin Cells

  Cutaneous squamous cell carcinoma (cSCC) is a form of skin cancer originating from keratinocytes in the skin. They have high mutation burdens, primarily driven by UV-radiation-induced DNA damage. The order in which mutations undergo selection during the evolution of cSCC is not known. A subset of cSCCs grow out of benign neoplasms called actinic keratoses. To better understand the evolution of cSCC, we identified cases of cSCCs adjacent to actinic keratoses. From these cases, we separately microdissected the surrounding normal skin, the actinic keratosis, and the cSCC, and we performed targeted DNA-sequencing on the tissue from each area. We reconstructed tumor phylogenies and performed spatial transcriptomics on the 10X FFPE Visium platform on a subset of cases. Collectively, these studies revealed the mutational and gene expression changes that arise during the evolution of cSCC.

  Study phs003282

• Studies in the Pathogenesis of Systemic Capillary Leak Syndrome (SCLS, Clarkson Disease)

  Systemic capillary leak syndrome (Clarkson disease) is an ultra-rare disease of unknown etiology. Patients experienced transient and recurrent episodes of hypotensive shock and massive peripheral edema due to plasma extravasation, often precipitated by minor viral infections. Disease onset occurs most frequently in middle age, and there is no family history. More than 90% of patients with the disease have monoclonal gammopathy of unknown significance (MGUS). The goal of the study is to determine pathogenic mechanisms and identify genetic underpinnings of the disease. Toward this end, we performed whole genome sequencing (WGS).

  Study phs003261

• Maintenance of Brain Tumor Profile on Organotypic Brain Slice Culture (OBSC)

  We used uncultured tumor resection tissue from an NF2 mutation-driven grade II meningioma (MG-II) to investigate whether tumors engrafted onto organotypic brain slice cultures (OBSCs) maintained the genetic profile of the parent tumor. We prepared three groups of samples for whole exome sequencing (WES) from the same pool of dissociated MG-II tissue. Group HT is the original uncultured human tumor tissue (n = 3). Group CL is the parent tumor tissue expanded in standard in vitro cell culture until the minimum number of cells required for WES had grown. Because of initial cell loss and subsequent clonal expansion, this required six passages over the span of approximately one month (n = 3). Group BSHT is the uncultured tumor resection tissue engrafted onto OBSCs and subsequently dissected from the OBSCs at the conclusion of our standardized assay length (4 days; n = 4). WES analysis showed that tumor tissue engrafted onto OBSCs maintained a significant genetic resemblance to the parent tumor, while tumor tissue expanded in vitro displayed a distinctly different profile. Furthermore, the mutational profiles of all four BSHT biological replicates were markedly similar, indicating that each OBSC-engrafted tumor indeed contained a representative sample of the original patient tumor. A closer look at the hallmark NF2 mutations existing within all samples revealed that while all samples from the original tumor (HT1-3) and the OBSC-engrafted tumor (BSHT1-4) maintain the frame shift deletion at V24, this mutation was lost in all samples expanded in vitro (CL1-3) and replaced by mutations in other areas. Together, this data suggests that the rapid assay design and tumor-accommodating niche of our OBSC platform enables effective maintenance of the original patient tumor profile. The BBsplit algorithm from the BBtools suite was run on all samples to eliminate rat DNA contamination in the BSHT samples as well as to account for any biases that may result as a part of that process. Only the reads that were binned to the human reference were used for subsequent analysis. Reads were then mapped to the GRCh38 version of the human genome with BWA v0.7.17 and realigned together with ABRA2 v.23. Quality control was implemented using the GATK/Picard v4.1.7.0 toolkit. Somatic variants were called for each sample using the MuTect2 algorithm v4.1.7.0. Variants were merged into a single cohort variant call file and then converted to MAF via vcf2maf v1.6.21 tool. Variants were annotated using VEP v87. To identify mutations with potentially high biological impact, multiple filtering steps were applied to somatic mutation calling. First, we selected only the somatic variants that passed all filters from the MuTect2 FilterMutectCalls algorithm and second, only high/moderate impact (change coding) variants as defined by the VEP annotation were further analyzed. Over 1900 single nucleotide variants (SNVs) were detected across all samples. Figures that summarized the results were generated using maftools.

  Study phs003268

• DNA Methylation Studies in CREW Cohorts (URECA and COAST)

  Children's Respiratory Environment Workgroup (CREW) is an NIH-funded project consisting of 12 individual U.S. cohorts and three scientific centers working together to identify phenotypes and causes of childhood asthma. CREW includes data from a large number of children and their families, with broad diversity in terms of ethnicity, family characteristics, neighborhoods and geographic locations. In this study, we identified differentially methylated regions from whole-genome bisulfite sequencing (WGBS) in nasal epithelial cells from 39 children of European or African ancestries, and with or without allergic asthma. Study participants were from two of the CREW cohorts: the Urban Environment and Childhood Asthma (URECA) cohort and the Childhood Origins of Asthma (COAST) cohort.The URECA children are also participants of a larger genetic study, in which DNA samples are derived from blood. That data is presented in the "Whole Genome Sequencing in the Inner City Asthma Consortium (ICAC) Cohorts - phs002921" study.

  Study phs003321

• Single-Cell Multi-Omic Analysis of the Vestibular Schwannoma Ecosystem Uncovers a Nerve Injury-Like State

  Vestibular schwannomas are benign tumors that can lead to significant morbidity, including hearing loss, facial nerve paralysis and obstructive hydrocephalus. The genomic landscape of vestibular schwannomas is relatively bland and the molecular pathophysiology of vestibular schwannomas is poorly understood. Therefore, we performed single cell RNA sequencing on 15 sporadic vestibular schwannomas, with paired single cell ATAC sequencing (n = 6) and whole exome sequencing (n = 12) to perform a detailed characterization of the vestibular schwannoma tumor microenvironment at the transcriptional and epigenetic level. We validated our results by analyzing bulk RNA sequencing data from 22 newly sequenced vestibular schwannomas and 173 previously sequenced bulk RNA sequencing data from 195 vestibular schwannomas. Data available in dbGaP include whole exome sequencing of 12 tumors and matched blood samples. Matching single cell RNA sequencing and single cell ATAC sequencing data is available via NCBI GEO.

  Study phs003318

• FinaleMe: Predicting DNA Methylation by the Fragmentation Patterns of Plasma Cell-Free DNA

  Analysis of DNA methylation in cell-free DNA (cfDNA) reveals clinically relevant biomarkers but requires specialized protocols and sufficient input material that limits its applicability. Millions of cfDNA samples have been profiled by genomic sequencing. To maximize the gene regulation information from existing datasets, we developed FinaleMe, a non-homogeneous Hidden Markov Model (HMM), to predict DNA methylation of cfDNA and, therefore, tissues of origin directly from plasma whole genome sequencing (WGS). We validated the performance with 80 pairs of deep and shallow coverage WGS and whole genome bisulfite sequencing (WGBS) data from both cancer patients and healthy controls.

  Study phs003287

• Multi-Ethnic Study of Atherosclerosis (BioLINCC)

  The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Data available for request include phenotypic data previously released on BioLINCC as well as raw images (E.g. Echocardiogram) and raw tracing data files (e.g. Electrocardiogram). These new data are intended to be made available to interested researchers via BioData Catalyst, will include participants irrespective of participation in genetics (i.e. the full MESA cohort), and may be merged with currently posted (to dbGaP) phenotype and molecular datasets (WGS, GWA, RNA Seq, Methylation, Metabolomics, and Proteomics).

  Study phs003288

• Cell-Free, Methylated DNA in Blood Samples Reveals Tissue-Specific, Cellular Damage from Radiation Treatment

  Radiation therapy is an effective cancer treatment, although damage to surrounding healthy tissues can also occur. Cell-type specific DNA methylation patterns can be used to decode the cellular origins of cell-free DNA fragments, allowing for minimally-invasive monitoring of tissue damage. To evaluate whether changes in cell-free DNA methylation can indicate damages to tissues in patients treated with radiation, we collected serum samples from 15 breast cancer patients at three timepoints during their standard-of-care radiation therapy after surgery. A baseline sample was taken for each patient before onset of radiation therapy and a second End-Of-Treatment (EOT) sample was taken 30 minutes after the last treatment fraction. Finally, a recovery sample was taken one month after completion of radiation therapy. From serum samples, cell-free DNA was isolated and bisulfite capture-sequencing DNA methylation data were generated. Bisulfite capture-sequencing DNA methylation data were also generated from buffy coat and tissue-specific endothelial gDNA samples as well as from serum/plasma samples of healthy controls. The analysis of serum samples from breast cancer patients undergoing radiation treatment revealed distinct tissue-specific epithelial and endothelial responses to radiation across multiple organs. In conclusion, as a proof of concept we show that cell-type specific methylation signatures can be applied to detect cellular injury from radiation treatment using minimally invasive cell-free DNA in blood samples.

  Study phs003290

• Population Genetic Testing and SERPINA1 Sequencing Identifies Unidentified Alpha-1 Antitrypsin Deficiency Alleles and Gene-Environment Interaction with Hepatitis C Infection

  Design and aims: Data were available through an institutional effort to combine de-identified electronic health records (EHR) data with genomic information from a DNA biobank. The design of this work was a retrospective cohort study in which we investigated the rates of liver transplantation and hepatitis C infection as it relates to genotype risk for alpha-1 antitrypsin deficiency (AATD). We used regression analysis to look for relationships between these risks and outcomes. This led to further investigation of environmental exposures and phenotypes as it related to the underlying genotypic risk. Population information: The cohort consisted of 72,027 individuals of European ancestry for whom genotype and EHR data were available. Molecular technologies employed: Genome-wide genotyping was previously performed using the Illumina Infinium Expanded Multi-Ethnic Genotyping Array plus custom content (referred to as the Vanderbilt University Medical Center BioVU MEGAEX). Individuals' AATD-related alleles were inferred from the genotyping data. Principal findings of the study: Liver transplantation was associated with presence of the Z AATD allele and with hepatitis C infection. There was a significant interaction between AATD genotype groups and hepatitis C infection as it related to liver transplantation. Data available through dbGaP: Inferred AATD genotype status, sex, age, length of EHR in years, presence/absence of AATD clinical diagnosis, liver transplant status, and hepatitis C infection status.

  Study phs003297