3413 results for "*geneti*"

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• METABRIC: Data from Batra et al (2021); DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation

  DNA methylation is aberrant in cancer, but the dynamics, regulatory role and clinical implications of such epigenetic changes are still poorly understood. Here, RRBS-based profiles of 1538 breast tumors and 244 normal breast tissues from the METABRIC cohort are reported, facilitating detailed analysis of DNA methylation within a rich context of genomic, transcriptional, and clinical data. Tumor methylation from immune and stromal signatures are deconvoluted leading to the discovery of a tumor replication-linked clock with genome-wide methylation loss in non-CpG island sites. Unexpectedly, methylation in most tumor CpG islands follows two replication-independent processes of gain (MG) or loss (ML) that we term epigenomic instability. Epigenomic instability is correlated with tumor grade and stage, TP53 mutations and poorer prognosis. After controlling for these global trans-acting trends, as well as for X-linked dosage compensation effects, cis-specific methylation and expression correlations are uncovered at hundreds of promoters and over a thousand distal elements. Some of these targeted known tumor suppressors and oncogenes. In conclusion, the study demonstrates that global epigenetic instability can erode cancer methylomes and expose them to localized methylation aberrations in-cis resulting in transcriptional changes seen in tumors.

  Study EGAS00001004327

• Epigenome and transcriptome profiling of chronic lymphocytic leukemia patients

  Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay, and we also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research.

  Study EGAS00001001821

• Whole exome sequencing of Finnish hereditary breast cancer families

  A remarkable proportion of factors causing genetic predisposition to breast cancer (BC) are unknown in non-BRCA1/2 families. Exome sequencing was performed for 13 high-risk Finnish hereditary breast and/or ovarian cancer (HBOC) families to detect variants contributing to BC susceptibility

  Study EGAS00001001835

• 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

• The dataset of Southeast Borneo individuals (Banjar and Ngaju ethnic groups) was used as comparative data to determine the Asian parental population of the Malagasy. Our study found strong support for an origin of the Asian ancestry of Malagasy among the Banjar.

  Malagasy genetic diversity results from an exceptional proto-globalisation process that took place over a thousand years ago across the Indian Ocean. Previous efforts to locate the Asian origin of Malagasy have highlighted Borneo broadly as a potential source, but so far no firm source populations have been identified. Here, we have generated genome-wide data from two Southeast Borneo populations, the Banjar and the Ngaju, together with published data compiled from populations across the Indian Ocean region. We find strong support for an origin of the Asian ancestry of Malagasy among the Banjar. This group emerged from the long-standing presence of a Malay Empire trading post in Southeast Borneo, which favoured admixture between the Malay and an autochthonous Borneo group, the Ma’anyan. Reconciling genetic, historical and linguistic data, we show that the Banjar, in Malay-led voyages, were the most probable Asian source among the analysed groups in the founding of the Malagasy gene pool.

  Study EGAS00001001841

• Genetic history of the Comorian populations.

  At the dawn of the second millennium, the expansion of the Indian Ocean trading network aligned with the emergence of an outward-oriented community along the East African coast to create a cosmopolitan cultural and trading zone known as the Swahili Corridor. Based on analyses of genome-wide genotyping data in 140 individuals from coastal Kenya and the Comoros islands, along with 3,477 individuals from the Indian Ocean rim, we reconstruct historical population dynamics showing that the Swahili Corridor is largely an East Bantu genetic continuum. Within this continuity significant gene flows from the Middle East can be seen in the Swahili and Comorians at dates corresponding to the Islamization of East Africa. However the main external gene flow into insular populations of the Swahili Corridor, such as Comorian and Malagasy groups, came from Island Southeast Asia as early as the 10th century. Remarkably, our results reflect archaeological and linguistic data in suggesting that the Comoros archipelago is the oldest place of contact between Austronesian and African populations in the Swahili Corridor.

  Study EGAS00001002565

• Genetic history of the Swahili population

  At the dawn of the second millennium, the expansion of the Indian Ocean trading network aligned with the emergence of an outward-oriented community along the East African coast to create a cosmopolitan cultural and trading zone known as the Swahili Corridor. Based on analyses of genome-wide genotyping data in 140 individuals from coastal Kenya and the Comoros islands, along with 3,477 individuals from the Indian Ocean rim, we reconstruct historical population dynamics showing that the Swahili Corridor is largely an East Bantu genetic continuum. Within this continuity significant gene flows from the Middle East can be seen in the Swahili and Comorians at dates corresponding to the Islamization of East Africa. However the main external gene flow into insular populations of the Swahili Corridor, such as Comorian and Malagasy groups, came from Island Southeast Asia as early as the 10th century. Remarkably, our results reflect archaeological and linguistic data in suggesting that the Comoros archipelago is the oldest place of contact between Austronesian and African populations in the Swahili Corridor.

  Study EGAS00001002569

• Whole-genome sequencing of two probands with hereditary spastic paraplegia reveals novel splice-donor region mutation and known pathogenic mutation in SPG11

  Hereditary spastic paraplegias (SPG) are a group of heterogeneous neurodegenerative disorders, which are often presented with overlapping phenotypes such as progressive paraparesis and spasticity. To assist the diagnosis of SPG subtypes, next-generation sequencing is often used to provide supporting evidence. In this study, we report the case of two probands from the same family with SPG symptoms, including bilateral lower limbs weakness, unsteady gait, cognitive decline, dysarthria and slurring of speech since age of 14. Subsequent whole-genome sequencing revealed that the patients are compound heterozygous for mutations in SPG11 gene, including the paternally inherited c.6856C>T (p.Arg2286*) mutation and the novel maternally inherited c.2316+5G>A splice donor region mutation. Mutations in SPG11 are the common cause of autosomal recessive Spastic Paraplegia type 11. According to the ClinVar database, there are already 101 reported pathogenic mutations in SPG11 that are associated with SPG. To our knowledge, this is the first report of SPG11 mutations in our local population. Novel splice mutation identified in this study would enrich the catalog of SPG11 mutations, potentially leading to better genetic diagnosis of SPG.

  Study EGAS00001001849

• A targeted gene panel that covers coding, noncoding, and short tandem repeat regions improves the diagnosis of patients with neurodegenerative diseases

  Genetic testing for diagnosis of neurodegenerative diseases (NDs) is highly challenging because of genotype heterogeneity and overlapping clinical manifestations. Targeted-gene panels (TGPs), coupled with next-generation sequencing (NGS), can facilitate the profiling of a large repertoire of ND-related genes and help with differential diagnosis. Due to the technical limitations inherent in NGS and TGPs, short tandem repeat (STR) variations are often ignored. However, STR expansions are known to cause such NDs as Huntington’s disease and several types of spinocerebellar ataxias, such as SCA type 3 (SCA3).Here, we studied the clinical utility of a custom-made TGP that targets 199 NDs and 311 ND-associated genes on 118 undiagnosed patients. At least one known pathogenic or likely pathogenic variation was found in 54 (45.8%) patients; 27 (22.9%) of the 118 patients demonstrated clinical profiles that matched the variants. Based on the findings from the TGP, we refined the original diagnosis of 16 patients. A high concordance of single-nucleotide polymorphisms (99.9%) and small insertions and deletions (93.2%) were observed when comparing the results from TGP and whole-exome sequencing of four patients. We tested an in-house STR detection algorithm, and it reached a specificity of 0.88 and a sensitivity of 0.82 in our SCA3 cohort. This study also uncovered a trove of novel and recurrent variants that may enrich the repertoire of ND-related genetic markers. We propose that a combination of comprehensive TGPs and the bioinformatics analysis pipeline can improve the clinical diagnosis and accelerate the diagnosis of NDs.

  Study EGAS00001003737

• Recurrent somatic JAK-STAT mutations within a novel RUNX1-mutated pedigree

  The acquisition of somatic mutations is an emerging field of investigation in familial leukemia. Currently, genetic profiles in familial MDS/AML are considered analogous to sporadic disease, although the patterns of clonal evolution within families are poorly defined. We performed whole exome profiling of tumour samples from a novel RUNX1 mutated family, to determine the stepwise evolution of MDS/AML across 4 young siblings. Three siblings developed monocytic AML/RAEB2 at 5 years of age, with hepatosplenomegaly and somatic mutations upregulating JAK-STAT signalling, the latter are typically detected in <5% of sporadic MDS/AML. Two siblings acquired the canonical JAK2 V617F mutation, while another acquired a unique missense mutation of SH2B3, a negative regulator of JAK2. Notably, 2/3 siblings demonstrated dosage amplification of these mutations due to acquired uniparental disomy of chromosomes 9p and 12q (encompassing JAK2 and SH2B3, respectively). All 4 siblings were heterozygous for the 46/1 JAK2 haplotype associated with predisposition to sporadic V617F myeloproliferative disorders, which likely influenced the acquisition of JAK2 mutations. Our findings provide further evidence that relatives with shared germline mutations may acquire somatic mutations in a non-random manner leading to convergent patterns of disease evolution.

  Study EGAS00001001862

• Variation in the Glucose Transporter gene SLC2A2 is associated with glycaemic response to metformin

  Metformin is the first-line antidiabetic drug with over 100 million users worldwide, yet its mechanism of action remains unclear1. Here the Metformin Genetics (MetGen) Consortium reports a three-stage genome wide association study (GWAS), consisting of 13,123 participants of different ancestries. The C-allele of rs8192675 in the intron of SLC2A2, which encodes the facilitated glucose transporter GLUT2, was associated with a 0.17% (p=6.6x10-14) greater metformin induced HbA1c reduction in 10,577 participants of European ancestry. rs8192675 is the top cis-eQTL for SLC2A2 in 1,226 human liver samples, suggesting a key role for hepatic GLUT2 in regulation of metformin action. In obese individuals C-allele homozygotes at rs8192675 had a 0.33% (3.6mmol/mol) greater absolute HbA1c reduction than T-allele homozygotes.This is about half the effect seen with the addition of a DPP-4 inhibitor, and equates to a dose difference of 550mg of metformin, suggesting rs8192675 as a potential biomarker for stratified medicine.

  Study EGAS00001001875

• Recent genetic history of Denmark

  The "Where Are You From?" project explores the extent to which recent and more distant historical events left their mark on the genetic structure of the current Danish population. The project's ultimate goal is to gain insights into the historical complexity of Denmark from the genetic perspective. To this goal, a data set consisting of approximately 800 high school students from across Denmark was used to run an extensive genetic analysis.

  Study EGAS00001001868

• GoDARTS T2D-GENES Exome Sequencing Study is a subset of the ~52,000 Type 2 diabetes exome sequencing project.

  The GoDARTS T2D-GENES Exome sequencing study is a subset of a larger Type 2 Diabetes Exome Sequencing project. This effort is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date and includes samples from: T2D-GENES, GoT2D, ESP, SIGMA T2D, LuCAMP, and ProDIGY. This data generated from the Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for T2D through multiethnic sequencing studies. Sequencing for the GoDARTS study was performed at the Broad Institute using Illumina Rapid Capture on Illumina HiSeq machines.

  Study EGAS00001002937

• Investigating genetic susceptibility to rheumatic heart disease in Oceania

  This case-control study investigated susceptibility to rheumatic heart disease in over 3,000 individuals recruited across eight Oceanian countries. Cases were patients with rheumatic heart disease and controls were members of the general population. In addition to the Illumina HumanCore-24 BeadChip genotyping, a subset of 128 samples were analysed using the higher density Illumina HumanOmniExpressExome BeadChip of which 64 were also analysed using low coverage sequencing with the Illumina HiSeq 4000 platform.

  Study EGAS00001001881

• Genome-wide quantification of rare somatic mutations in normal human tissues using massively parallel sequencing

  We present Bottleneck Sequencing System (BotSeqS), a nextgeneration sequencing method that simultaneously quantifies rare somatic point mutations across the mitochondrial and nuclear genomes. BotSeqS combines molecular barcoding with a simple dilution step immediately prior to library amplification. We use BotSeqS to show age and tissue-dependent accumulations of rare mutations and demonstrate that somatic mutational burden in normal tissues can vary by several orders of magnitude, depending on biologic and environmental factors. We further show major differences between the mutational patterns of the mitochondrial and nuclear genomes in normal tissues. Lastly, the mutation spectra of normal tissues were different from each other, but similar to those of the cancers that arose in them. This technology can provide insights into the number and nature of genetic alterations in normal tissues and can be used to address a variety of fundamental questions about the genomes of diseased tissues.

  Study EGAS00001001838

• Whole-Exome Sequencing of Salivary Gland Mucoepidermoid Carcinoma

  Mucoepidermoid carcinoma (MEC) is the most common salivary gland malignancy. To explore the genetic origins of MEC, we performed systematic genomic analyses of these tumors.Experimental DesignWhole-exome sequencing and gene copy number analyses were performed for 18 primary cancers with matched normal tissue. Fluorescence in situ hybridization (FISH) was used to determine the presence or absence of the MECT1-MAML2 translocation in 17 tumors.ResultsTP53 was the most commonly mutated gene in MEC (28%), and mutations were found only in intermediate- and high-grade tumors. Tumors with TP53 mutations had more mutations overall than tumors without TP53 mutations (p=0.006). POU6F2 was the second most frequently mutated gene, found in three low-grade MECs with the same in-frame deletion. Somatic alterations in IRAK1, MAP3K9, ITGAL, ERBB4, OTOGL, KMT2C, and OBSCN were identified in at least two of the 18 tumors sequenced. FISH analysis confirmed the presence of the MECT1-MAML2 translocation in 15 of 17 tumors (88%).ConclusionsThrough these integrated genomic analyses, MECT1-MAML2 translocation and somatic TP53 and POU6F2 mutations appear to be the main drivers of mucoepidermoid carcinoma.

  Study EGAS00001002811

• Genomic profiling of esthesioneuroblastoma

  We performed whole exome and whole genome sequencing on a cohort of esthesioneurblastoma to understand the genetic underpinnings of this neoplasm.

  Study EGAS00001003225

• An Isogenic Cell Line Panel for Sequence-based Screening of Targeted Anti-cancer Drugs

  We describe the creation and characterization of an isogenic cell line panel representing common cancer pathways, with multiple features optimized for high-throughput screening. More than 1,800 cell lines from three normal human cells were generated using CRISPR-technologies. Surprisingly, we discovered most of these lines did not result in complete gene inactivation, despite integration of sgRNA at the desired genomic site. However, a subset of the lines harbored true, biallelic disruptions of the targeted tumor suppressor gene, yielding a final panel of 100 well-characterize lines covering 19 pathways frequently subject to loss of function in cancers. This panel included genetic markers optimized for sequence-based ratiometric assays for drug-based screening assays. To illustrate the potential utility of this panel, we developed a multiplexed high-throughput screen that identified Wee1 inhibitor MK-1775 as a selective growth inhibitor of cells with inactivation of TP53. These cell lines and screening approach should prove useful for researchers studying a variety of cellular and biochemical phenomena

  Study EGAS00001005974

• Exome-sequencing of two UFM individuals and their Fragile X family members.

  Fragile X syndrome (FXS) is a monogenic neurodevelopmental disease often caused by a CGG triplet expansion in the 5’UTR of the FMR1 gene, which results in DNA methylation of the FMR1 promoter and its transcriptional silencing. Exceptional healthy individuals named "unmethylated full mutation (UFM)" have been identified in the families of FX patients. They carry an expanded CGG repeat, but show normal FMR1 epigenetic configuration and expression. In this study we performed exome-sequencing of two UFM individuals and their family members to identify possible genetic mutations responsible for the escape of silencing in the unmethylated full mutation (UFM) phenotype.

  Study EGAS00001001737

• Same-day genomic and epigenomic diagnosis of brain tumors using realtime nanopore sequencing

  Molecular classification of cancer has entered clinical routine to inform diagnosis, prognosis and treatment decisions. At the same time, new tumor entities have been identified that cannot be defined histologically. For central nervous systems tumors, the current World Health Organization classification explicitly demands molecular testing, e.g. for 1p/19q- codeletion or IDH mutations, to make an integrated histomolecular diagnosis. However, a plethora of sophisticated technologies is currently needed to assess different genomic and epigenomic alterations and turnaround times are in the range of weeks, which makes standardized and widespread implementation difficult and hinders timely decision making. Here, we explored the potential of a pocket-size nanopore sequencing device for multimodal and rapid molecular diagnostics of cancer. Low-pass whole genome sequencing was used to simultaneously generate copy number (CN) and methylation profiles from native tumor DNA in the same sequencing run. Single nucleotide variants in IDH1, IDH2, TP53, H3F3A and the TERT promoter region were identified using deep amplicon sequencing. Nanopore sequencing yielded ~0.1X genome coverage within six hours and resulting CN and epigenetic profiles correlated well with matched microarray data. Diagnostically relevant alterations, such as 1p/19q codeletion, and focal amplifications could be recapitulated. Using ad hoc random forests, we could perform supervised pan-cancer classification to distinguish gliomas, medulloblastomas and brain metastases of different primary sites. Single nucleotide variants in IDH1, IDH2 and H3F3A were identified using deep amplicon sequencing within minutes of sequencing. Detection of TP53 and TERT promoter mutations shows that sequencing of entire genes and GC-rich regions is feasible. Nanopore sequencing allows same-day detection of structural variants, point mutations and methylation profiling using a single device with negligible capital cost. It outperforms hybridization-based and current sequencing technologies with respect to time-to diagnosis and required laboratory equipment and expertise, aiming to make precision medicine possible for every cancer patient, even in resource restricted settings.

  Study EGAS00001002213

• Genetic Basis of Hepatosplenic T Cell Lymphoma (HSTL)

  Hepatosplenic T cell lymphoma (HSTL) is a rare and lethal lymphoma; the genetic drivers of this disease are unknown.  Through whole exome sequencing of 68 HSTLs, we define recurrently mutated driver genes and copy number alterations in the disease. Chromatin modifying genes including SETD2, INO80 and ARID1B were commonly mutated in HSTL, affecting 62% of cases. HSTLs manifest frequent mutations in STAT5B (31%), STAT3 (9%), and PIK3CD (9%) for which there currently exist potential targeted therapies. In addition, we noted less frequent events in EZH2, KRAS and TP53. SETD2 was the most frequently silenced gene in HSTL. We experimentally demonstrated that SETD2 acts as a tumor suppressor gene. In addition, we found that mutations in STAT5B and PIK3CD activate critical signaling pathways important to cell survival in HSTL. Our work thus defines the genetic landscape of HSTL and implicates novel gene mutations linked to HSTL pathogenesis and potential treatment targets.

  Study EGAS00001002182

• Multisample genomic analysis of solid childhood cancers using high resolution SNP-arrays, Whole Exome Sequencing and Targeted Deep Sequencing.

  We mapped the prevalence of genetically distinct clones over 248 regions in 54 childhood cancers. This revealed that primary tumors can simultaneously follow up to four evolutionary patterns in different anatomic areas. The most common pattern consists of a fluctuating presence over anatomic space of subclones with very few mutations. The second most common is a surprisingly stable coexistence, over vast areas, of clones with different changes in chromosome numbers. This is contrasted by a third, less frequent, pattern where a novel clone harboring driver mutations or structural chromosome rearrangements completely replaces its progenitor. The fourth and rarest pattern is the local emergence of a myriad of clones with TP53 inactivation. Strikingly, death from disease was limited to tumors exhibiting the two latter, most dynamic patterns.

  Study EGAS00001002662

• Genomics of enteropathy associated T cell lymphoma (EATL)

  Enteropathy-associated T cell lymphoma (EATL) is a lethal and the most common neoplastic complication of celiac disease. In this study, we applied whole exome sequencing in 69 EATL tumors to define the genetic landscape of EATLs. The most frequently mutated gene in EATL was SETD2 (32% of cases), with loss of function mutations comprising a large proportion (41%) of those mutations. The JAK-STAT pathway was the most frequently mutated signaling pathway, with mutations in STAT5B being the most common, followed by JAK1, JAK3, STAT3, and the negative regulator of the pathway, SOCS1. We also identified mutations in NRAS and KRAS, as well as TP53 and TERT. Interestingly, the two types of EATL had highly overlapping genetic alterations indicating shared mechanisms underlying their pathogenesis. Gene expression analysis of the two types of EATL identify robust differences in transcriptional profiles. We further modeled the effects of SETD2 loss in vivo by developing a T cell specific knockout mouse model. These mice manifested an expansion of γδ T cells that identify novel roles for SETD2 in T cell development and lymphomagenesis. Together, our data render the most comprehensive genetic portrait yet of this uncommon but lethal disease, and may inform future classification schemes.

  Study EGAS00001001954

• Genome-Wide Association Study of aspirin-induced PUD in a UK cohort

  Aspirin is a widely prescribed non-steroidal anti-inflammatory drug used as an effective analgesic and at low doses as anti-platelet drug for the prevention of cardiovascular diseases. However, aspirin is associated with a significant incidence of upper gastrointestinal (GI) complications, notably peptic ulceration. This study aims to identify genetic risk factors associated with the pathogenesis of aspirin-induced upper GI ulceration.A cohort of 248 patients with aspirin-induced, endoscopiclly confirmed GI ulceration and 491 controls (ulcer, without aspirin or aspirin without ulcer) were genotyped for 1.524,956 SNPs using the Illumina Omni 2.5 SNP array. A replication cohort (206 NSAID-induced ulcer cases [of which 87 were aspirin] and 309 controls) was subsequently genotyped for identified SNP association signals using Sequenom iPLEX Massarry. Logistic regression analysis of identified two SNP signal with suggestive association with aspirin-induced GI ulceration. A SNP within the EYA1 locus (rs12678747) was found to be associated with aspirin GI ulceration in both the discovery cohort (p=3.79x10-7, OR=2.06 ([1.55-2.73]) and, to a lesser extent, in the replication cohort (p=.0005, OR=1.71[1.17-2.50]. Combined analysis of both cohorts yielded a genome wide significant association (p=1.46x10-8). The rs12678747 genotype was found to be associated with significantly higher EYA1 transcript in ulcer biopsy tissue (p<0.05).Data suggest that EYA1 may represent a risk locus for aspirin-induced GI ulceration. Though it is thought that EYA1 may play a key role in mediating cell death/ survival

  Study EGAS00001002052

• Systematic comparative analysis of single-nucleotide variants detection methods from single-cell RNA sequencing data

  Systematic interrogation of single nucleotide variations (SNVs) is one of the most promising approaches to delineate the cellular heterogeneity and phylogenetic relationships at the single cell level. While SNV detection from abundant single cell RNA sequencing (scRNA-seq) data is applicable and cost-effective in identifying expressed variants, inferring sub-clones, and deciphering genotype-phenotype linkages, there is a lack of computational methods specifically developed for SNV calling in scRNA-seq. Although variant callers for bulk RNA-seq have been sporadically used in scRNA-seq, the performances of different tools have not been assessed. Here, we performed a systematic comparison of seven tools including SAMtools, the GATK pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, using both simulation and scRNA-seq datasets, and identified multiple elements influencing their performance. Our study provided the first benchmarking to evaluate the performances of different SNV detection tools for scRNA-seq data.

  Study EGAS00001003883