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• Pulldown_DNA_methylation_study_v2

  Pilot study to set up sequencing protocols for targeted pulldown methylation profiling

  Study EGAS00001000979

• Nuclear_single_seq_pilot

  The aim of this study is to analyse the genomes of tumours

  Study EGAS00001003386

• Low_input_LC__ISC_

  R&D project to develop low input library construction methods.

  Study EGAS00001001856

• Infant_Spindle_Tumour_Study

  We aim to describe the transcriptomic landscape of infant spindle cell tumours.

  Study EGAS00001002935

• Settlement of Polynesia

  Genotypes used to reconstruct the settlement timings and paths of Polynesia.

  Study EGAS00001005362

• HCA_Muscle_Adult_Wellcome_RNA_Managed_Access

  Transcriptomic analysis of skeletal muscle, to understand the mechanisms of muscle ageing.

  Study EGAS00001007495

• Whole Exome and Transcriptome Sequencing in Sporadic ALS

  Amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig's disease, is a fatal and devastating neurodegenerative disorder that causes the progressive death of upper and lower motor neurons. Although many efforts have been done to elucidate molecular factors involved in the onset and progression of the disorder, the causes of ALS are yet unknown and undefined. Transcriptome studies, based mostly on microarrays, have revealed multiple perturbations of the motor neuron function, supporting the current idea that several cellular events contribute to the pathobiology of the disease, including mitochondrial dysfunction, enhanced apoptosis, glutamate-mediated excitotoxicity, free radical injury, protein misfolding, abnormal calcium metabolism and altered axonal transport. In the present study, we have deeply sequenced the whole transcriptome of ventral horns of the human lumbar spinal cord from matched control and ALS post-mortem donors. Whole exome sequencing from the same donors has also been performed to exclude known genetic variants associated to the familiar form of ALS. In addition, to characterize the ALS transcriptome we have sequenced the RNA fraction at low molecular weight in the same tissues and individuals. Genomic and transcriptomic reads have been generated using the Illumina HiSeq2000 sequencer.

  Study phs000747

• E5103 Correlative Studies

  ECOG-ACRIN E5103 (E5103) was a phase III adjuvant breast cancer trial that randomized 4994 patients with node-positive or high-risk node-negative breast cancer to intravenous doxorubicin and cyclophosphamide every 2 or 3 weeks (at the discretion of treating physician), for four cycles of adriamycin and cyclophosphamide (AC) followed by 12 weeks of weekly paclitaxel (80 mg/m2) alone (Arm A), or to the same chemotherapy with either concurrent bevacizumab (Arm B), or concurrent plus sequential bevacizumab (Arm C). To develop predictive genetic biomarkers for chemotherapy efficacy and toxicities, we have successfully performed genome-wide genotyping and whole exome sequencing in the germline (blood) DNA of 3215 and 672 patients, respectively, from the E5103 trial to investigate the association of genetic variants with chemotherapy efficacy and toxicities. Case and control studies were performed with genome-wide analyses (GWAS) and whole exome analyses (WES) across all arms of E5103 to identify genotypes at single-nucleotide polymorphisms (SNPs) and deleterious gene mutations that were associated with paclitaxel-induced peripheral neuropathy (TIPN). Through GWAS, we have identified a SNP, rs3125923, and through WES, Cytochrome P450 oxidoreductase (POR), that was significantly associated with grade 3-4 TIPN.

  Study phs003201

• eMERGE Phase III Clinical Center at Partners HealthCare

  The Partners HealthCare Biobank is a large research data and sample repository working within the framework of Partners Personalized Medicine. It provides researchers access to high quality, consented samples to help foster research, advance understanding of the causes of common diseases, and advance the practice of medicine. The Partners Biobank provides banked samples (plasma, serum and DNA) collected from consented patients. These samples are available for distribution to Partners HealthCare investigators with appropriate approval from the Partners Institutional Review board (IRB). They are linked to clinical data that originates in the Electronic Medical Record (EMR), as well as additional health information collected in a self-reported survey. The Partners Biobank will be genotyping 25,000 subjects with the Illumina Multiethnic Beadchip 1.6 million SNPs with exome and custom content (> 60,000 LoFs). Of the participants genotyped so far, 4929 of 4962 (99.3%) individuals have genotype data that passed the default quality thresholds for the Infinium array (call rate >= 0.99). We are submitting the genotype data to dbGaP for 4929 subjects with 12 phenotypes (based on icd9 codes). We will do annual releases until we reach the full 25,000 genotyped subjects.

  Study phs000944

• Epigenetic Biomarkers of Aging

  The aim of the study was to discover new epigenetic biomarkers of aging. We used a genome-wide screen for genetic loci showing consistent changes of DNA methylation with progressive aging. Blood DNA samples from 19 apparently healthy individuals aged 22-80 years obtained from the NINDS repositories were analyzed for DNA methylation using Reduced Representation Bisulfite Sequencing. We followed the New England Biolabs (NEB) protocol for methylated adaptors as described previously. Briefly, 1 microgram of genomic DNA was spiked with 100 picograms of lambda phage DNA as the unmethylated standard and digested with MspI endonuclease at C’CGG sites. Ends of restriction fragments were filled in, 3’-dA tailed and methylated adaptors were ligated to the ends of restriction fragments. Bisulfite treatment using the Epitect kit (Qiagen) followed. Bisulfite-converted libraries were amplified using EpiMark Taq DNA polymerase (NEB) and primers with dual barcode indices. The libraries were pooled and sequenced on Illumina HiSeqX instrument using paired end reads of 150 bases. We used Bismark v0.23.1 to align the sequences to hg19 human genome assembly. We used methylKit v1.22.0 to analyze differential methylation in individuals of different ages.

  Study phs003046