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• Conjunctival fibrosis and the innate barriers to Chlamydia trachomatis intracellular infection: a genome wide association study

  This data comes from a genome-wide association study in 1090 cases of scarring trachoma and 1531 controls from a non-selected multi-ethnic sampling of The Gambia. The data constitutes hard base calls at 1457295 features from the HumanOmni2.5-8 (Omni2.5) BeadChip. Three genotype-calling algorithms were used : Illuminus (Bioinformatics 2007, 23:2741–6), GenCall (Patent US7035740, 2006) and GenoSNP (Bioinformatics 2008, 24:2209–14). Data from each calling algorithm was filtered to retain only SNPs with a call rate ≥ 0.98. To obtain a merged set of SNPs, all genotypes that matched across call-sets were retained, whilst those that mismatched between call-sets were set to missing. Genotypes that were present in one call set and missing in others were also retained. The merged SNP set contained 1467876 SNPs, which were filtered for call rate ≥ 0.99 and Hardy-Weinberg equilibrium P value < 5 x 10-8. The case and control groups were approximately equivalent with respect to gender and ethnicity. 70% of cases and 63% of controls were female. Self-described ethnic composition of the cases was 29% Jola, 27% Mandinka, 21% Wolof, 10% Fula and 13% other/no data. In controls the composition was 25% Jola, 24% Mandinka, 21% Wolof, 8% Fula and 22% other/no data. Median age was 49 (range 32-60) in cases and 37 (range 12-52) in controls (t = -3.6019, P = 0.0003). This data set has substantial levels of population structure, which reflects extensive networks of pairwise kinship between participants. First pass tests of association in EMMAX (Nat Genet 2010, 42:348–54) led to genome-wide deflation of the test statistics (λ = 0.982 SE = 1.74e-05) that could be directly attributed to the differing age and gender distributions between cases and controls. Modelling the phenotype to adjust for age and gender successfully controlled for this and no genome-wide deviation from the null was subsequently observed (λ = 1.001, SE = 8.7 x 10-7). Neither principal components analysis (PCA) nor tests of proportional identity by state (IBS) variance in PLINK identified significant levels of within or between group genetic variance. The phenotypes submitted in the phenotypes file include both uncorrected (case/control status) and corrected (age and gender corrected case/control status) phenotypes, as well as age and self-described ethnicity.

  Study EGAS00001001516

• UK10K RARE COLOBOMA

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. Ocular coloboma is the most common significant developmental eye defect with an incidence of ~1 in 5,000 live births. It results from failure of optic fissure closure during embryogenesis. The position and extent of the fusion failure dictates the clinical appearance and functional effect. ~30% of coloboma cases are associated with other systemic malformations. These UK10K samples will mostly comprise isolated coloboma cases without systemic involvement (aka non-syndromal coloboma). There is strong evidence from family studies that coloboma has a major genetic component with autosomal dominance being the most common pattern of inheritance. However, many cases are isolated or show complex patterns of familial clustering. The genes responsible for isolated coloboma are largely unknown, but in a small number of families mutations in SHH, CHX10, and PAX6 have been identified indicating marked genetic heterogeneity. Thus in addition to the clinical benefits of achieving a molecular diagnosis there are also major scientific advantages to identifying coloboma genes, as these are likely to provide insights into the complex process of optic fissure closure, that is critical to normal eye development. In the longer term, understanding the molecular basis of the disease may provide clues to therapeutic strategies.For further information with regard to this cohort please contact David Fitzpatrick (david.fitzpatrick@ed.ac.uk).

  Study EGAS00001000127

• UK10K_OBESITY_SCOOP

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches.The SCOOP samples are part of the Obesity group and will undergo exome sequencing. Severe Childhood Onset Obesity Project (SCOOP) is a sub-cohort of the Genetics Of Obesity Study (GOOS) cohort established by Sadaf Farooqi and Steve O’Rahilly at the University of Cambridge over the last 12 years. The GOOS cohort contains >4,000 patients of diverse geographic origin, many of whom have monogenic and syndromic forms of obesity, and includes patients that are offspring of consanguineous union. SCOOP is a subset of >1500 UK Caucasian patients with severe, early onset obesity (all patients have a BMI Standard Deviation Score (SDS) > 3 and obesity onset before the age of 10 years), in whom all known monogenic causes of obesity have been excluded. GWAS data on the SCOOP cohort will be available (WTCCC2 independent study) at the time of the start of this study. Data from this cohort has demonstrated that the prevalence of the common obesity risk alleles in FTO, MC4R and NEGR1 are amongst the highest within SCOOP, demonstrating its value also in the study of genetic variants with an impact on more common obesity. For further information with regard to this cohort please contact Sadaf Farooqi (isf20@medschl.cam.ac.uk).

  Study EGAS00001000124

• WGSPD Project 1: Whole Genome Sequencing for Schizophrenia and Bipolar Disorder

  The Center for Genomic Psychiatry at the University of Southern California (USC) and an extensive network of academic medical centers have created the Genomic Psychiatry Cohort (GPC). The GPC consists of a large clinical cohort of patients with schizophrenia, bipolar disorder, and healthy controls. The pilot phase of whole genome sequencing of the GPC has been done in collaboration with the USC and the Broad Institute of MIT and Harvard. Whole genome sequencing (20X) and analysis of 9,033 well-phenotyped individuals from the Genomic Psychiatry Cohort (GPC), divided among schizophrenia cases, bipolar disorder cases, and psychiatrically normal controls, and comprised of European-Ancestry (EA), African-Ancestry (AA), and Latino individuals. The combination of clinically well-characterized GPC participants and whole genome sequencing with rich functional annotation aims to identify functional variants associated with schizophrenia and bipolar disorder risk. Over half of the sequenced samples are patients with a diagnosis of either schizophrenia or bipolar disorder. The majority of the study participants are of African American ancestry, increasing the diversity of sampling for these important diseases in traditionally understudied populations. This data set also contains 545 samples that have undergone 10x Genomics Linked-Read Sequencing (169 participants overlapping with the 9,033 participant WGS 20X dataset). In addition to the benefits due to disease phenotyping and ancestry selection that apply to all of the WGSPD Project 1 samples, the 10x Genomics Linked-Read samples, through the use of barcodes that can identify the long input DNA fragment that each sequencing read was generated from, can be used to 1) identify structural variants that are difficult to call with standard short read data, 2) map short reads to repetitive regions of the genome that cannot be assayed with standard short reads, and provide highly accurate phasing information about genetic variants, including rare variants that are more difficult to phase using statistical phasing techniques.

  Study phs002041

• Liver biopsy derived induced pluripotent stem cells provide an unlimited supply for the generation of patient-specific hepatocyte-like cells

  Background: Hepatocyte-like cells (HLCs) differentiated from induced pluripotent stem cells (iPSCs) have emerged as a promising cell culture model to study metabolism, biotransformation, viral infections and genetic liver diseases. However the derivation of iPSCs is restricted by ethical and procedural constraints. Furthermore, incomplete HLC differentiation remains a major challenge. iPSC may carry-on a tissue of origin dependent expression memory influencing iPSC differentiation into different cell types. If liver derived iPSCs (Li-iPSCs) maintain a liver specific gene expression profile is not known. It is also not known, if Li-iPSCs would allow the generation of more fully differentiated HLCs.Methods: Primary liver cells (PLCs) were expanded from liver needle biopsies and reprogrammed into Li-iPSCs using a non-integrative Sendai virus-based system. Li-iPSCs were differentiated into HLCs using established differentiation protocols. The HLC phenotype was characterized at the protein, functional and transcriptional level. RNA sequencing data were generated from the originating liver biopsies, the Li-iPSCs, fibroblast derived iPSCs, and differentiated HLCs, and used to characterize and compare their transcriptome profiles.Results: PLCs were obtained from small pieces of liver biopsies and could be reprogrammed into Li-iPSCs. Li-iPSCs indeed retain a liver specific transcriptional footprint. Li-iPSCs can be propagated to provide an unlimited supply of cells for differentiation into Li-HLCs. Similar to HLCs derived from fibroblasts, Li-HLCs could not be fully differentiated into hepatocytes. Relative to the originating liver, Li-HLCs showed lower expression of liver specific transcription factors and increased expression of genes involved in the differentiation of other tissues.Conclusions: PLCs and Li-iPSCs obtained from small pieces of human needle liver biopsies constitute a novel unlimited source for the production of HLCs. Despite the preservation of a liver specific gene expression footprint in Li-iPSCs, the generation of fully differentiated hepatocytes cannot be achieved with the current differentiation protocols.

  Study EGAS00001002676

• Molecular Tumor Board to Inform on Personalized Medicine for a Man with Advanced Prostate Cancer

  Purpose: Molecular profiling of cancer is increasingly common as part of routine care in oncology, and germline and somatic profiling may provide insights and actionable targets for men with metastatic prostate cancer. However, all reported cases are of deidentified individuals without full medical and genomic data available in the public domain. Patient and Methods: We present a case of whole genome tumor and germline sequencing in a patient with advanced prostate cancer, who has agreed to make his genomic and clinical data publicly available in an accompanying personal testimonial. Results: We describe an 84-year-old Caucasian male with a Gleason 10 oligometastastic hormone-sensitive prostate cancer. Whole-genome sequencing provided insights into his tumor’s underlying mutational processes and the development of an SPOP mutation. It also revealed an androgen-receptor dependency of his cancer which was reflected in his durable response to radiation and hormonal therapy. Potentially actionable genomic lesions in the tumor were identified through a personalized medicine approach for potential future therapy, but at the moment, he remains in remission, illustrating the hormonal sensitivity of his SPOP-driven prostate cancer. We also placed this patient in the context of a large prostate-cancer cohort from the PCAWG (Pan-cancer Analysis of Whole Genomes) group. In this comparison, the patient's cancer appears typical in terms of the number and type of somatic mutations, but it has a somewhat larger contribution from the mutational process associated with aging. Conclusion: We combined the expertise of medical oncology and genomics approaches to develop a molecular tumor board to integrate the care and study of this patient, who continues to have an outstanding response to his combined modality treatment. This identifiable case potentially helps overcome barriers to clinical and genomic data sharing.

  Study EGAS00001004648

• RNA-Seq in Patients with Primordial Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in the interpretation of likely causal genetic variation through identification of altered transcript abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating transcript structure and abundance The primary aim of this pilot project is to investigate to what degree integrating exome-Seq and RNA-Seq data on the same individual can accelerate the identification of causal alleles for rare genetic diseases. There are two main strands to this: (i) identifying which variants discovered in exome-seq appear to be having a functional impact on transcripts, and (ii) identifying transcript outliers, especially among known causal genes, that may not necessarily have a causal variant identified from exome sequencing. The latter may identify the presence of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites deep within introns, or loss of long range regulatory elements), which can be confirmed with further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g. nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs). This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with primordial dwarfism syndromes, for 10 of these samples we have previously generate exome data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining samples are positive controls where the causal mutation is known, and is known to affect transcript structure and/or abundance. Primordial dwarfism is a prime candidate for these RNA-seq studies because all known causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the products of the causal genes are typically ubiquitously expressed. Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000640

• RNAseq dataset for MALT1 in MCL

  Manuscript Title: Co-targeting of BTK and MALT1 overcomes resistance to BTK inhibitors in mantle cell lymphoma Journal: Journal of Clinical Investigation Authors Vivian Changying Jiang1, Yang Liu1, Junwei Lian1, Shengjian Huang1, Alexa Jordan1, Qingsong Cai1, Fangfang Yan3, Joseph Mitchell McIntosh1, Yijing Li1, Yuxuan Che1, Zhihong Chen1, Jovanny Vargas1, Maria Badillo1, JohnNelson Bigcal1, Heng-Huan Lee1, Wei Wang1, Yixin Yao1, Lei Nie1, Christopher Flowers1, and Michael Wang1, 2* Abstract Bruton’s tyrosine kinase (BTK) is a proven target in mantle cell lymphoma (MCL), an aggressive subtype of non-Hodgkin lymphoma. However, resistance to BTK inhibitors is a major clinical challenge. We here report that MALT1 is one of the top overexpressed genes in ibrutinib-resistant MCL cells, while expression of CARD11, which is upstream of MALT1, is decreased. MALT1 genetic knockout or inhibition produced dramatic defects in MCL cell growth regardless of ibrutinib sensitivity. Conversely, CARD11 knockout cells showed anti-tumor effects only in ibrutinib-sensitive cells, suggesting that MALT1 overexpression could drive ibrutinib resistance via bypassing BTK-CARD11 signaling. Additionally, BTK knockdown and MALT1 knockout markedly impaired MCL tumor migration and dissemination, and MALT1 pharmacological inhibition decreased MCL cell viability, adhesion, and migration by suppressing NF-κB, PI3K-ATK-mTOR, and integrin signaling. Importantly, co-targeting MALT1 with safimaltib and BTK with pirtobrutinib induced potent anti-MCL activity in ibrutinib-resistant MCL cell lines and patient-derived xenografts. Therefore, we conclude that MALT1 overexpression associates with resistance to BTK inhibitors in MCL, targeting abnormal MALT1 activity could be a promising therapeutic strategy to overcome BTK inhibitor resistance, and co-targeting of MALT1 and BTK should improve MCL treatment efficacy and durability as well as patient outcomes. Dataset description: The bulk RNA-seq dataset was generated for the cell lines below and used for two major purposes: 1. DEG analysis and GSEA analysis comparing IBN-R and IBN-S cells 2. DEG analysis and GSEA analysis comparing MCL cells with/without MI-2 treatment. sample Cell MI-2 Ibrutinib (IBN) Venetoclax (VEN) Used for IBN-R vs IBN-S comparison Used for MI-2 vs untreated (DMSO) H9 Granta519 - R S yes H21 Granta519 - R S yes H33 Granta519 - R S yes H10 Granta519-VEN-R - R R yes H22 Granta519-VEN-R - R R yes H34 Granta519-VEN-R - R R yes H3 JeKo BTK KD_1 - R R yes yes H15 JeKo BTK KD_1 - R R yes yes H27 JeKo BTK KD_1 - R R yes yes H5 JeKo BTK KD_2 - R R yes yes H17 JeKo BTK KD_2 - R R yes yes H29 JeKo BTK KD_2 - R R yes yes H1 JeKo-1 - S R yes yes H13 JeKo-1 - S R yes yes H25 JeKo-1 - S R yes yes H7 Mino - S S yes H19 Mino - S S yes H31 Mino - S S yes H8 Mino-VEN-R - S R yes H20 Mino-VEN-R - S R yes H32 Mino-VEN-R - S R yes H11 Rec-1 - S S yes H23 Rec-1 - S S yes H12 Rec-VEN-R - S S yes H24 Rec-VEN-R - S R yes H36 Rec-VEN-R - S R yes H35 Rec-1 -- S R yes H4 JeKo BTK KD_1 + MI-2 + yes H16 JeKo BTK KD_1 + MI-2 + yes H28 JeKo BTK KD_1 + MI-2 + yes H6 JeKo BTK KD_2 + MI-2 + yes H18 JeKo BTK KD_2 + MI-2 + yes H30 JeKo BTK KD_2 + MI-2 + yes H2 JeKo-1 + MI-2 + yes H14 JeKo-1 + MI-2 + yes H26 JeKo-1 + MI-2 + yes

  Dataset EGAD00001009771

• DNA methylation changes associated with hyperglycemia in type 1 diabetes

  This dataset includes DNA methylation profiles from 112 young with Type 1 Diabetes (T1D) at T1D diagnosis, who were longitudinally monitored for hyperglycemia over an average duration of 3 years. These datasets were generated using whole-genome bisulfite sequencing. It includes 1872 fastq files (i.e. 936 paired-end fastq files) generated through 150 bp paired-end sequencing on Illumina HiSeqX.

  Dac EGAC50000000237

• DAC for Human exome sequencing data from three family members reported in the publication

  Germline variants in UHRF1 are associated with multi-locus imprinting disturbance in humans and mice. Eguzkine Ochoa, Ilona Zvetkova, Sunwoo Lee, Nozomi Takahashi, Benoit Lan-Leung, Emma Hobson, Mahmoud Issa, Bryndis Yngvadottir, France Docquier, Fay Rodger, Dounia Foster-Hall, Graeme Clark, Ana Toribio, Ezequiel Martin, Leonardo Bottolo, Anne C Ferguson-Smith, Wolfgang Fischle, Miguel Constancia, Eamonn R Maher

  Dac EGAC50000000710