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• Full blood mRNA sequencing of myotonic dystrophy type 1 patients after cognitive behavioural therapy

  This dataset consists of 60 mRNA sequencing runs from full blood of 31 myotonic dystrophy type 1 patients, of which for 27 patients reliable data is available before and after 10 months of cognitive behavioural therapy. >30 million 150 bp paired end reads were obtained with UMI-labeled adapters to facilitate filtering of PCR duplicates. Via UMI-analysis we found samples with the aliases sample_01 and sample_02 to contain a very high number of PCR duplicates and recommend the use of these samples only with highest caution or not at all.

  Dataset EGAD00001008383

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  Study EGAS00001008448

• BCG-Flu Challenge Study Human RNA-seq

  Whole blood RNA sequencing data generated from human samples collected as part of the BCG-Flu Challenge study. The dataset includes 746 samples. Paired-end sequencing was performed on an Illumina NovaSeq 6000 platform with a 150 bp paired-end configuration. Raw FASTQ files are provided.

  Dataset EGAD50000002407

• Whole genome sequencing data from whole genome amplified single cells and unamplified bulk samples

  The dataset includes paired end fastq files of whole genome sequencing data on the Illumina platfrom. Individual samples are multiple annealing and looping based amplified single fibroblasts and multiple displacement amplified single T lympocytes, including unamplified bulk samples.

  Dataset EGAD00001004195

• 200PG : WGS Raw Sequence (fastq)

  200PG : WGS Raw Sequence (fastq) : Raw WG sequence data (fastq) in this dataset are from the 124 CPCGene Tumour/Normal Pairs used in the 200PG Study. https://www.ncbi.nlm.nih.gov/pubmed/28068672

  Dataset EGAD00001001094

• Characterization of Human Transcriptome by Computational and HTS Approaches

  We have deeply sequenced total RNA and whole exome of six different post-mortem human snap-frozen tissues (brain, liver, lung, striated muscle, kidney, heart) from three unrelated healthy Caucasian individuals (males, aged 47-54) with the aim to characterize post-transcriptional events due to alternative splicing and RNA editing. In addition, to facilitate the detection of RNA editing sites we have also resequenced the entire genome of each individual. Data are also used to investigate tissue-specific abundance of mitochondrial DNA from exomes and its correlation with mitochondrial transcription, mass and respiratory activity. Tissues were obtained from Cureline (South San Francisco, CA, USA). DNA and RNA were purified using the DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany) and the RNeasy Plus Mini Kit (Qiagen, Hilden, Germany), respectively. Exome capture was performed using the TruSeq Exome Enrichment Kit (Illumina, San Diego, CA) and the sequencing was carried out at IGA Technology Services in Udine (Italy) on Illumina HiSeq 2000 (generating for each tissue approximately 40 millions of 100bp paired-end reads). Strand-oriented RNA reads (2x100bp) were generated using the TruSeq Stranded Total RNA Sample Prep Kit (Illumina, San Diego, CA, USA) and sequenced at IGA Technology Services in Udine (Italy) on Illumina HiSeq 2000 platform. Whole genome resequencing was performed at Personal Genomics in Italy on an Illumina HiSeq 2000 platform (2x100bp) with a mean coverage of 30X. MiRNA-Seq was instead performed at IBBE Institute (Italy) using the TruSeq Small RNA Sample Prep Kit on Illumina MiSeq platform. Preliminary bioinformatics analyses have been performed to check quality using FASTQC software and inconsistent read regions have been trimmed using trim_galore. All reads were mapped onto the human reference genome (version hg19) using GSNAP.

  Study phs000870

• Stand Up To Cancer East Coast Prostate Cancer Research Group

  Most prostate cancer deaths are caused by metastatic, castration resistant disease (mCRPC). To develop a precision medicine framework for mCRPC, we established a multi-institutional, international clinical sequencing infrastructure to enroll and carry out prospective whole exome and transcriptome sequencing of tumors from a cohort of mCRPC patients. We obtained high quality DNA and RNA sequence data from 150 bone or soft tissue biopsies. Central pathology revealed high-grade adenocarcinoma with only four cases (3.6%) showing neuroendocrine differentiation. Aberrations of AR, ETS genes, TP53 and PTEN were frequent (40-60% of cases), with TP53 and AR alterations being the most enriched in mCRPC compared to primary prostate cancer. We identified novel genomic alterations in PIK3CA/B (fusions and mutations); R-spondin, BRAF and RAF1 (fusions); APC (inactivating mutations); delta-catenin (missense mutations); and ZBTB16/PLZF (homozygous deletions). Aberrations of BRCA2, BRCA1 and ATM were observed at substantially higher frequencies (19.3% overall) than seen in primary prostate cancers, with 56% of these being exclusively somatic. Putative driver gene alterations were identified in nearly all patients, and over half also harbored driver gene fusions, homozygous deletions and/or amplifications. Moreover, 89% of patients harbored a clinically actionable aberration including 62.7% with aberrations in AR, 65% in other cancer-related genes, and 8% with actionable pathogenic germline alterations. Overall, integrative clinical sequencing analysis can be safely and efficiently performed in mCRPC, yields findings that may be actionable for enrolling patients in clinical trials of targeted therapies, and may inform the basis of individual clinical responses.

  Study phs000915

• Somatic mutations predict an aggressive phenotype in meningioma but do not drive grade progression

  A subset of meningiomas progress in histopathological grade and drivers of progression are poorly understood. We aimed to identify somatic mutations and copy number alterations (CNAs) associated with grade progression in a unique matched tumour dataset. Utilising a prospective database, we identified 10 patients with meningiomas that had undergone grade progression and for whom matched pre- and post-progression tissue (n=50 samples) was available for targeted next-generation sequencing. Mutations in NF2 were identified in 4/10 patients, 94% were non-skull base tumours. In one patient, three different NF2 mutations were identified in four tumours. NF2 mutated tumours showed large scale CNAs, with highly recurrent losses in 1p, 10, 22q, and frequent CNAs on chromosomes 2, 3 and 4. There was a correlation between grade and CNAs in a subset of patients. In two patients with sphenoid wing Grade III tumours without detected NF2 mutations, a STAT6-NAB2 inversion was identified. Two patients with tumours without detected NF2 mutations showed a combination of loss and high gain on chromosome 17q. Mutations in SETD2, TP53, TERT promoter and NF2 were not uniform across recurrent tumours and did not correspond with grade progression. Meningiomas that progress in grade generally have a mutational profile already detectable in the pre-progressed tumour, suggesting an aggressive phenotype . CNA profiling shows frequent alterations in NF2 mutated tumours compared to non NF2 mutated tumours and the pattern of CNAs may be associated with grade progression in a subset of cases.

  Study EGAS00001006585

• CRISPR screening in human trophoblast stem cells reveals both shared and distinct aspects of human and mouse placental development

  The placenta serves as the interface between the mother and fetus, facilitating the exchange of gases and nutrients between their separate blood circulation systems. Trophoblasts in the placenta play a central role in this process. Our current understanding of mammalian trophoblast development relies largely on mouse models. However, given the diversification of mammalian placentas, findings from the mouse placenta cannot be readily extrapolated to other mammalian species, including humans. To fill this knowledge gap, we performed CRISPR knockout (KO) screening in human trophoblast stem cells (hTSCs). We targeted genes essential for mouse placental development and identified more than 100 genes as critical regulators in both human hTSCs and mouse placentas. Among them, we further characterized in detail two transcription factors, DLX3 and GCM1, and revealed their essential roles in hTSC differentiation. Moreover, a gene function-based comparison between human and mouse trophoblast subtypes suggests that their relationship may differ significantly from previous assumptions based on tissue localization or cellular function. Notably, our data reveal that hTSCs may not be analogous to mouse TSCs or the extraembryonic ectoderm (ExE) in which in vivo TSCs reside. Instead, hTSCs may be analogous to progenitor cells in the mouse ectoplacental cone and chorion. This finding is consistent with the absence of ExE-like structures during human placental development. Our data not only deepen our understanding of human trophoblast development but also facilitate cross-species comparison of mammalian placentas.

  Study JGAS000659

• The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia

  Acute lymphoblastic leukaemia (ALL) is the most common childhood malignancy, and implementation of risk-adapted therapy has been instrumental in the dramatic improvements in clinical outcomes. A key to risk-adapted therapies includes the identification of genomic features of individual tumors, including chromosome number (for hyper- and hypodiploidy) and gene fusions, notably ETV6-RUNX1, TCF3-PBX1 and BCR-ABL1 in B-cell ALL (B-ALL). RNA-sequencing (RNA-seq) of large ALL cohorts has expanded the number of recurrent gene fusions recognized as drivers in ALL, and identification of these new entities will contribute to refining ALL risk stratification. We used RNA-seq on 126 ALL patients from our clinical service to test the utility of including RNA-seq in standard of care diagnostic pipelines to detect gene rearrangements and IKZF1 deletions. RNA-seq identified 86% of rearrangements detected by standard of care diagnostics. KMT2A-rearrangements (MLL), whilst usually identified, were the most commonly missed by RNA-seq as a result of low expression. RNA-seq identified rearrangements that were not detected by standard of care testing in nine patients. These were found in patients who were not classifiable using standard molecular assessment. We developed an approach to detect the commonest IKZF1 deletion from RNA-seq data and validated this using a RQ-PCR assay. We applied an expression classifier to identify Ph-like B-ALL patients. T-ALL proved a rich source of novel gene fusions which have clinical implications or provide insights into disease biology. Our experience shows that RNA-seq can be implemented within an individual clinical service to enhance the current molecular diagnostic risk classification of ALL.

  Study EGAS00001004212