Search Results - EGA European Genome-Phenome Archive

Genome and transcriptome sequence data from a lung cancer patient

Genome and transcriptome sequence data from a lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

Dataset EGAD00001004643

UK10K_OBESITY_SCOOP UK10K_EXOME_EXTRAS

Dataset EGAD00001000756

UK10K_RARE_NMWG REL-2013-03-06

Dataset EGAD00001000804

Detection of rare mutations, copy number variation, and DNA methylation in the same template DNA molecules

The analysis of cell-free DNA (cfDNA) from plasma offers great promise for the earlier detection of cancer. At present, changes in DNA sequence, methylation, or copy number are the most sensitive ways to detect the presence of cancer. To further increase the sensitivity of such assays with limited amounts of sample, it would be useful to be able to evaluate the same template molecules for all these changes. Here we report an approach, called MethylSaferSeqS, that achieves this goal, and can be applied to any standard library preparation method suitable for massively parallel sequencing. The innovative step was to copy both strands of each DNA-barcoded molecule with a primer that allows the subsequent separation of the original strands (retaining their 5-methylcytosine residues) from the copied strands (in which the 5-methylcytosine residues are replaced with unmodified cytosine residues). The epigenetic and genetic alterations present in the DNA molecules can then be obtained from the original and copied strands, respectively. We applied this approach to plasma from 265 individuals, including 198 with cancers of the pancreas, ovary, lung and colon, and found the expected patterns of mutations, copy number alterations, and methylation. Furthermore, we could determine which original template DNA molecules were methylated and/or mutated. MethylSaferSeqS should be useful for addressing a variety of questions relating genetics and epigenetics in the future.

Study EGAS00001006839

Genetics of Chemotherapy Induced Peripheral Neuropathy in N08C1 and N08CB

Chemotherapy-induced peripheral neuropathy (CIPN) is a common and potentially dose-limiting toxicity of chemotherapy treatment. CIPN severity varies widely between cancer patients, and previous studies had found evidence of genes and single nucleotide variants (SNV) being associated with CIPN. The goal of this study was to further identify genetic markers and pathways associated with CIPN severity using whole exome sequencing (WES) and whole genome sequencing (WGS) of participants in two clinical studies which collected longitudinal patient-reported outcome (PRO) measures of CIPN. NCCTG/Alliance study N08C1 was a prospective cohort study of the natural history of paclitaxel-associated acute pain syndrome (P-APS) and CIPN. NCCTG/Alliance trial N08CB was a randomized, placebo-controlled trial of calcium and magnesium for prevention of oxaliplatin-induced sensory neuropathy in which the treatment had no significant effect on either acute pain or sensory neuropathy. Both N08C1 and N08CB collected patient assessments of CIPN symptoms before each cycle of chemotherapy using the EORTC QLQ-CIPN20 instrument. For this study, CIPN cases were selected from each of N08C1 and N08CB as those patients with the most severe CIPN symptoms (assessed longitudinally). CIPN controls were selected as those with the least severe symptoms. WGS was obtained for N08C1 samples (WES had been obtained and analyzed previously), and WES was obtained for N08CB samples.

Study phs001480

High Density SNP Association Analysis of Lung Cancer

This research builds upon an extensive resource of a case-control study that has been ongoing at the UT MD Anderson Cancer Center since 1991. To identify risk variants for lung cancer, we conducted a genome-wide association study. Cases are newly diagnosed, histologically-confirmed patients presenting at MD Anderson Cancer and who had not previously received treatment other than surgery. Controls are healthy individuals seen for routine care at Kelsey-Seybold Clinics, the largest physician group-practice plan in the Houston Metropolitan area. This lung GWAS led to the identification of a susceptibility locus for lung cancer at 15q25.1. We used data from 315,450 tagging SNPs in 1,154 current and former (ever) smoking cases of European ancestry and 1,137 frequency-matched, ever-smoking controls from Houston, Texas in the discovery followed by the replication of the ten SNPs most significantly associated with lung cancer in an additional 711 cases and 632 controls from Texas and 2,013 cases and 3,062 controls from the UK. Two SNPs, rs1051730 and rs8034191, were significantly associated with risk of lung cancer with combined analysis yielded odds ratios of 1.32 (P < 1X10-17) for both SNPs. These two SNPs mapped to a region of strong linkage disequilibrium within 15q25.1 containing PSMA4 and the nicotinic acetylcholine receptor subunit genes CHRNA3 and CHRNA5. (Nat Genet. 2008 May;40(5):616-22. PMID:18385676)

Study phs000753

Ischemic Stroke Genetics Study (ISGS)

The third leading cause of death in the United States, stroke is an acute neurological event leading to death of neural tissues. Although the majority of strokes are ischemic strokes, meaning there is oxygen deprivation to the brain, almost 20% of strokes are hemorrhagic, resulting from bleeding into the brain. Stroke is a complex disorder and likely multigenic in nature, resulting from a combination of genetic and environmental factors. These well characterized risk factors that contribute to the incidence of stroke include hypertension, cardiac disease, sickle cell disease, hyperhomocysteinemia, family history of stroke and smoking. ISGS aim is to perform a prospective genetic association study of ischemic stroke focusing on the hemostatic system. ISGS is a 5-center case-control study of first-ever ischemic stroke cases and concurrent controls individually matched for age, sex and recruitment site. This data includes that from subjects both banked in the NINDS repository with biologicals publicly available, and those whose samples are not banked/not available. Important links to apply for individual-level data Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Participant Protection Policy FAQ --> This study utilized the NINDS Repository Cerebrovascular/Stroke Study, and neurologically normal controls from the sample population which are banked in the National Institute of Neurological Disorders and Stroke (NINDS Repository) collection for a first stage whole genome analysis.

Study phs000102

Natural History, Pathogenesis and Outcome of Melorheostosis

Melorheostosis is a rare osteosclerotic disease resulting in exuberant excessive bone growth with a characteristic radiographic appearance often described as "dripping candle wax". As a result of these bony formations, patients report mild to moderate pain that interferes with their routine activities. It is usually diagnosed on radiographs but bone biopsy may be performed to exclude other osteosclerotic diseases and/or osteosarcoma. Deformities, limb-length discrepancy, muscle atrophy, neurological deficit have been reported as complications. A subset of patients have somatic mutations in MAP2K1. The cause of this disease is not known in all patients, the natural history poorly described and there is no clearly-defined systemic therapy. We propose a prospective observational study to investigate the natural history and pathogenesis of the disease. Subjects will undergo standardized initial evaluation and medically indicated testing. Skin biopsies may be performed to test for known mutations related to melorheostosis, and if negative affected bone and/or skin may be sent for genetic testing for acquired somatic mutations in genes that control bone homeostasis. Enrolled subjects will be followed every two to three years for assessment of disease progression and receive clinically indicated testing and treatment. The study of this rare bone disease offers the potential to generate new insights, provide answers as well as generate new questions into the biology of the skeletal and mineral metabolism.

Study phs001976

The Gene Partnership (TGP) - eMERGE Data

The Gene Partnership (TGP) is a prospective longitudinal registry at Boston Children's Hospital (BCH) to study the genetic and environmental contributions to childhood health and disease, collect genetic information on a large number of children who have been phenotyped, and implement the Informed Cohort and the Informed Cohort Oversight Board (ICOB). The term "The Gene Partnership" reflects a partnership between researchers and participants. Children seen at BCH are offered enrollment, as are their parents and siblings. DNA is collected on all enrollees. BCH has a comprehensive EMR system, and virtually all inpatient and outpatient data are captured electronically. Clinical data in the BCH EMR is loaded in the i2b2 data warehouse which is available to investigators. Cases, phenotypes, and covariates are ascertained using the i2b2 database. Participants at BCH in TGP have consented to receive any research result and/or incidental finding that arises from studies using TGP that is approved by the Informed Cohort Oversight Board (ICOB) and is in accordance with the participants' preferences; results are returned through the Personally Controlled Health Record (PCHR). BCH and Cincinnati Children's Hospital Medical Center (CCHMC) have partnered as the Pediatric Alliance for Genomic and Electronic Medical Record (EMR) Research (PAGER) site for the eMERGE Phase II network for pediatric institutions, and the cohort for eMERGE at BCH is TGP.

Study phs000495

PGRN-RIKEN: Genetic Determinants of Clinical Cardiovascular Events in Patients Receiving Statins

Coronary heart disease (CHD) is an important public health problem in developed countries. Statins are effective in the prevention and treatment of CHD; nevertheless, many patients receiving statins still suffer cardiovascular events (CV) such as heart attack. Identifying genetic variants responsible for differential clinical responses to statins will not only allow individual patients at high residual risk to be targeted for additional therapies, but also will define new biologic pathways contributing to statin response, and thus new targets for future therapies. Accordingly, the goal of this study is to identify genetic variants associated with clinical CV in patients receiving statins. Subjects identified for study are of European descent and include 1718 subjects with CV while on statins (cases) and 4172 subjects without CV while on statins (controls). Key research resources utilized in this effort include VanderbiltD's BioVU DNA databank and associated Synthetic Derivative database of clinical information, and software tools developed to identify drugs and clinical events using Electronic Health Record-derived structured and unstructured ("free text") data. Most cases and controls identified include three data types: ICD-9 codes, medication regimens, and medical test results. Genotyping, using IlluminaD's Infinium HumanOmniExpressExome BeadChip (OmniExpressExome), was performed by the RIKEN Integrative Medical Sciences Center (IMS) and supported by the Pharmacogenomics Research Network (PGRN)-RIKEN IMS Global Alliance.

Study phs000963

Large Scale Genotyping of Psychiatric Disorders

Psychiatric disorders cause enormous human suffering and cost to society. The goal of this project is to elucidate the genetics of psychiatric disorders through a large consortium effort and genome-wide genotyping. The Psychiatric Genomics Consortium (PGC) (https://www.med.unc.edu/pgc) is an international consortium to pursue genome-wide analyses of common psychiatric disease. The PGC was founded in 2007 to unite investigators from around the world to conduct mega-analyses of individual genome-wide genotype data for schizophrenia (SCZ), bipolar disorder (BIP), autism (AUT), attention-deficit hyperactivity disorder (ADHD), and major depressive disorder (MDD). Subsequently, the PGC has expanded to include Tourette syndrome (TS), obsessive-compulsive disorder (OCD), eating disorders (ED), post-traumatic stress disorder (PTSD), and substance abuse (SUD). The PGC partnered with Illumina to develop the PsychChip, a custom GWAS array aimed at capturing common variation genome-wide for imputation, rare coding variation drawn from the exome chip and dense genotypes for loci with suggestive evidence for association across the initial PGC analyses of SCZ, MDD, BPD, ASD and ADHD. Samples (cases, controls, and families) were collected from Institutional Review Board-approved protocols that aim to study the genetics of psychiatric disorders. Genome-wide genotyping was performed at the Broad Institute (Cambridge, MA, USA) and the Mount Sinai School of Medicine Friedman Brain Institute (New York, NY, USA) using the PsychChip or Exome Chip.

Study phs001413

Identification of Cancer Predisposition Genes in Breast Cancer Families

Breast cancer has a significant genetic component. The strongest epidemiologic risk factor is family history of the disease. Familial studies have identified a number of genes contributing to increased risk. Of these, the highly penetrant BRCA1 and BRCA2 genes account for the majority of families in whom disease-causal mutations have been identified. However, mutations in other genes have been associated with predisposition to breast or breast and ovarian cancer including (CHEK2, ATM, PALB2, RAD51C, RAD51D). Together these genes account for less than 20% of excess familial breast cancer risk and do not explain ~50% of high-risk families referred for genetic testing. This significant gap in our understanding of the genetic basis of breast cancer poses a significant barrier to our ability to identify women at increased risk, who would benefit greatly from appropriate clinical management. To identify additional breast cancer predisposition genes whole exome sequencing of familial high-risk breast cancer patients was undertaken. DNA samples from 50 pairs of breast cancer patients from high-risk breast cancer families with no pathogenic mutations in the BRCA1 or BRCA2 breast cancer predisposition genes were subjected to whole exome sequencing. The goal was to select candidate predisposition genes for further validation studies based on sharing of putative protein inactivating mutations among both members of each family and/or the frequency of inactivating mutations among the 50 families.

Study phs000480

Genome-Wide Association Study of Heparin-Induced Thrombocytopenia

Heparin-induced thrombocytopenia (HIT) is an unpredictable, potentially catastrophic adverse effect resulting from an immune response to platelet factor 4 (PF4)/heparin complexes. We performed a genome-wide association study (GWAS) with positive functional assay as the outcome. Genetic associations were investigated in a cohort of functional assay-confirmed HIT cases, antibody-positive (function assay-negative) controls, and antibody negative controls. Both PF4-specific enzyme-linked immunosorbent assay (ELISA) and serotonin release assay (SRA) were positive in every HIT case. GWAS genotyping was performed at the Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences (IMS). All samples in the discovery and replication cohorts were genotyped using the lllumina® Infinium HumanOmniExpressExome BeadChip, which contains 958,497 markers, including 273,000 functional exonic markers. Quality control was accomplished using sample and marker call rate ≥98%, sex mismatch, duplicate concordance, and removal of related samples through identity by descent. Genomic imputation was performed for samples using Minimac4 and the phase3 v5 reference panel data from the 1000 genomes project. The primary GWAS analysis used multivariable logistic regression assuming an additive genetic model with functional assay-confirmed case status as the outcome. Both PF4/heparin antibody negative and antibody positive controls were considered controls in the primary analysis. Logistic regressions were used to generate odds ratios and 95% confidence intervals (95%CIs) after adjustment for age, sex, and first three principal components.

Study phs002863

Developing Allelic Imbalance Analysis from Single-Nucleus RNA-Seq Data

Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool for understanding gene function across diverse cells. Recently, this has included the use of allele-specific expression (ASE) analysis to better understand how variation in the human genome affects RNA expression at the single-cell level. We reasoned that, because intronic reads are more prevalent in single-nucleus RNA-Seq (snRNA-Seq) and introns are under lower purifying selection, and are thus enriched for genetic variants, that snRNA-seq should facilitate single-cell analysis of ASE. Here we demonstrate how experimental and computational choices can improve the results of allelic imbalance analysis. We explore how experimental choices, such as RNA source, read length, sequencing depth, genotyping, etc., impact the power of ASE-based methods. We developed a new suite of computational tools to process and analyze scRNA-seq and snRNA-seq for ASE. As hypothesized, we extracted more ASE information from reads in intronic regions than those in exonic regions and show how read length can be set to increase power. Additionally, hybrid selection improved our power to detect allelic imbalance in genes of interest. We also explored methods to recover allele-specific isoform expression levels from both long- and short-read snRNA-seq. Overall, we provide an end-to-end experimental and computational approach for future studies.

Study phs003749

Heterogeneity in Lysosomal Storage Disorders

Gaucher disease (GD) is an inherited lysosomal storage disorder caused by biallelic pathogenic variants in GBA1, which encodes glucocerebrosidase. Additionally, GBA1 variants are a well-established genetic risk factor for Parkinson's disease (PD), leading some PD research centers to incorporate GBA1 screening to identify patients who may benefit from targeted therapeutics. However, detecting GBA1 variants remains challenging due to the gene's high sequence homology with its pseudogene, which can give rise to complex recombinant alleles. This study evaluates the performance of Gauchian, a recently developed software tool for identifying GBA1 variants from whole genome sequencing (WGS) data. The assessment was conducted in a cohort of 90 individuals with GD and five GBA1 heterozygotes, all previously characterized through Sanger sequencing. While Gauchian successfully identified the most common genotypes, it demonstrated limitations in detecting rare or de novo variants due to its restricted internal database and heavy reliance on intergenic structural variants. These limitations led to misclassified homozygosity, incomplete genotyping, and undetected recombination events, ultimately reducing the tool's utility for comprehensive variant screening and precluding its application in diagnostic settings. The study dataset includes WGS from the 90 individuals used in the Gauchian pipeline. This data will be available through dbGaP to facilitate further research on GBA1 variant detection, genotype-phenotype correlations in GD and PD, and the development of improved bioinformatics tools for complex variant identification.

Study phs003459

The Federated EGA network

In the last 10 years, most human omics data has been generated in the context of research consortia while recently there has been an emergence of large cohorts of human data generated by healthcare initiatives. Many countries in Europe now have nascent personalised medicine programmes. Thus, human genomics is shifting from being predominantly research-driven to being funded through healthcare systems. Genetic data generated in a healthcare context is subject to more stringent information governance than research data and nonetheless all data must adhere to national data protections laws. In this context, EGA identified the need for the development of a federated network to enable secure sharing of data whilst enabling genetic data to remain within the jurisdiction in which it was generated. The Federated EGA is designed to support national data management requirements for genomic and clinical data collected from citizens as part of healthcare or biomedical research projects. It includes a secure authorised access mechanism to support research use of these data across Europe and worldwide. We have engaged with over 14 ELIXIR countries to develop the federation model. The EGA federated configuration is composed of Central EGA, Federated EGA nodes and Community EGA nodes: Central EGA offers international submissions and helpdesk support, currently EGA co-managed by EMBL-EBI and CRG, Federated EGA nodes offer EGA services to researchers within their national jurisdiction, Community EGA nodes are individual institutions or initiatives with human genetic data intended to be shared with the research community. Key services available in the Federated EGA structure are: Central EGA Federated EGA node Community EGA nodes Data submission Offers international submissions service Offers submission service in a particular jurisdiction Does not offer an external submissions service Helpdesk support Provides external international helpdesk Provides helpdesk support for submitters in its jurisdiction and for approved users of data managed at its facilities Provides helpdesk support only for approved users of data managed at its facilities Data distribution Manages worldwide distribution for data hosted at Central EGA Manages worldwide distribution for data hosted at Federated EGA node Distribution for data hosted at Community EGA node EMBL-EBI and CRG have prepared a series of documents describing the overall governance and coordination framework. These describe the Federated EGA structure, the rights and responsibilities of the different parties and governing committees, and node operation guidelines. The federation governance proposal is under review by the first countries invited to join as Federated nodes, with further interested countries likely to join in the coming years. The Central EGA team has been working closely with many ELIXIR partners, including ELIXIR Finland, Luxembourg, Germany, Norway, Spain and Sweden.

Blog the-federated-ega-network

MRCA and MRCE SNP genotypes

Gene expression levels can be an important link DNA between variation and phenotypic manifestations. Our previous map of global gene expression based on approximately 400K SNPs and 50K transcripts in 400 sib pairs from the MRCA family panel has been widely used to interpret the results of GWAS. Here, we more than double the size of our initial dataset with expression data on 550 additional individuals from the MRCE family panel using the Illumina whole genome expression array. We have used new statistical methods for dimension reduction to account for non-genetic effects in estimates of expression levels and we have also included SNPs imputed from the 1000 Genomes Project. Our methods reduced false discovery rates and increased the number of eQTLs mapped either locally or at a distance (i.e. in cis or trans) from 1,534 in the MRCA dataset to 4,452 (with <5% FDR). Imputation of 1000 Genomes SNPs further increased the number of eQTLs to 7,302. Using the same methods and imputed SNPs in the newly acquired MRCE dataset we identified eQTLs for 9000 genes. The combined results identify strong local and distant effects for transcripts from 14,177 genes. Our eQTL database (http://www.hsph.harvard.edu/faculty/liming-liang/software/eqtl/) based on these results is freely available to help define the function of disease-associated variants.

Study EGAS00000000137

Organoid BulkRNAseq

Here, we aim to understand early determinants of brain organoid quality and generated a set of brain organoids from 12 different hPSC lines using an adaptation of the unguided Lancaster protocol (Lancaster & Knoblich, 2014). All cell lines were obtained from healthy donors. 12 donor hPSC lines were differentiated into brain organoids and a set of 72 individual organoids (6 per line) were randomly selected morphologically diverse organoids and subjected to bulk RNA sequencing for gene expression analysis. RNA was extracted using the RNeasy kit (Qiagen, Germany) according to the manufacturer’s instructions. A total of 1000 ng per sample was sent for RNA sequencing to Azenta Life Sciences (Genewiz Leipzig, Germany) for sequencing. Library preparation was performed using the NEBNext Ultra II RNA Library Prep Kit for Illumina following manufacturer’s instructions (NEB, Ipswich, MA, USA). mRNAs were first enriched with Oligo(dT) beads. The samples were sequenced using a 2x150 Pair-End (PE) configuration v1.5 at a depth of >20 million reads in each sample. Raw sequence data (.bcl files) generated from Illumina NovaSeq6000 was converted into fastq files and de-multiplexed using Illumina bcl2fastq program version 2.20. The raw sequence reads were aligned to the human reference genome GRCh38 using the STAR aligner (Dobin et al., 2013). Gene expression levels were quantified using the FeatureCounts tool (Liao et al., 2014).

Study EGAS50000000659

GENETIC HISTORY OF ITALY

Recent scientific literature has highlighted the relevance of population genetic studies both for disease association-mapping in admixed populations and for understanding the history of human migrations. Deeper insight into the history of Italian population is critical for understanding the peopling of Europe. Because of its crucial position at the centre of the Mediterranean basin, the Italian peninsula has experienced a complex history of colonization and migration, whose genetic signatures are still present in contemporary Italians. In this study, we investigated genomic variation in the Italian population using 2.5 million single nucleotide polymorphisms (SNPs) in a sample of more than 300 unrelated Italian subjects with well-defined geographical origins. We combined several analytical approaches to interpret genome-wide data on 1,272 individuals from European, Middle Eastern, and North African populations. We detected three major ancestral components contributing different proportions across the Italian peninsula, and signatures of continuous gene flow within Italy, which has produced remarkable genetic variability among contemporary Italians. In addition, we have extracted novel details about the Italian population’s ancestry: we identified genetic signatures of major historical events in Europe and the Mediterranean basin from the Neolithic (e.g., peopling of Sardinia) to recent times (e.g., ‘barbarian invasion’ of Northern and Central Italy). These results are valuable for further genetic, epidemiological and forensic studies in Italy and in Europe.

Study EGAS00001001458

Automated system for scoring hematoxylin and eosin-stained ovarian cancer sections by identifying single cells uncovered that stromal cell ratio is a significant predictor for overall survival and progression-free survival.

Concerted efforts in genomic studies have revealed profound insights in prognostic ovarian cancer subtypes. On the other hand, abundant histology slides have been generated to date, yet their uses remain very limited and largely qualitative. Our goal is to develop automated histology analysis as an alternative subtyping technology for ovarian cancer that is cost-efficient and do not rely on DNA quality. We develop an automated system for scoring hematoxylin and eosin-stained (H&E) primary tumour sections of 91 late-stage ovarian cancer to identify single cells including cancer and stromal cells. We demonstrated high accuracy of our system based on expert pathologists’ scores (cancer=97.1%, stromal=89.1%) as well as compared to immunohistochemistry scoring (correlation=0.87). Quantitative stromal cell ratio is significantly associated with poor overall survival after controlling for clinical parameters including debulking status and age (multivariate analysis p=0.0021, HR=2.54, CI=1.40-4.60) and progression-free survival (multivariate analysis p=0.022, HR=1.75, CI=1.09–2.82). We demonstrate how automated image analysis enables objective quantification of microenvironmental composition of ovarian tumours. Our analysis reveals a strong effect of the tumour microenvironment on ovarian cancer progression and highlights the potential of therapeutic interventions that target the stromal compartment or cancer-stroma signalling in the stroma-high, late-stage ovarian cancer subset.

Study EGAS00001001694

UK10K NEURO ASD TAMPERE

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 Tampere Autism sample set consists of samples from Finnish subjects with ASD (autism spectrum disorders) with IQs over 70 recruited from a clinical centre for the diagnosis and treatment of children with ASD. For further information on this cohort please contact either Terho Lehtimaki (terho.lehtimaki@uta.fi) or Kaija Puura (kaija.puura@pshp.fi).

Study EGAS00001000115

Sensitive Monogenic Noninvasive Prenatal Diagnosis by Targeted Haplotyping

During pregnancy, cell-free DNA (cfDNA) in maternal blood encompasses a small percentage of cell-free fetal DNA (cffDNA), an easilyaccessible source for determination of fetal disease status in risk families through non-invasive procedures. In case of monogenic heritabledisease, background maternal cfDNA prohibits direct observation of the maternally inherited allele. Non-invasive prenatal diagnostics(NIPD) of monogenic diseases therefore relies on parental haplotyping and statistical assessment of inherited alleles from cffDNA,techniques currently unavailable for routine clinical practice. Here, we present monogenic NIPD (MG-NIPD), which requires a bloodsample from both parents, for targeted locus amplification (TLA)-based phasing of heterozygous variants selectively at a gene of interest.Capture probes-based targeted sequencing of cfDNA from the pregnant mother and a tailored statistical analysis enables predicting fetalgene inheritance. MG-NIPD was validated for 18 pregnancies, focusing on CFTR, CYP21A2, and HBB. In all cases we could predict theinherited alleles with >98% confidence, even at relatively early stages (8 weeks) of pregnancy. This prediction and the accuracy ofparental haplotyping was confirmed by sequencing of fetal material obtained by parallel invasive procedures. MG-NIPD is a robustmethod that requires standard instrumentation and can be implemented in any clinic to provide families carrying a severe monogenicdisease with a prenatal diagnostic test based on a simple blood draw.

Study EGAS00001002622

Homozygous loss-of-function variants in European cosmopolitan and isolate populations

Homozygous loss of function (HLOF) variants provide a valuable window on gene function in humans, as well as an inventory of the human genes that are not essential for survival and reproduction. All humans carry at least a few HLOF variants, but the exact number of inactivated genes that can be tolerated is currently unknown-as are the phenotypic effects of losing function for most human genes. Here, we make use of 1432 whole exome sequences from five European populations to expand the catalogue of known human HLOF mutations; after stringent filtering of variants in our dataset, we identify a total of 173 HLOF mutations, 76 (44%) of which have not been observed previously. We find that population isolates are particularly well suited to surveys of novel HLOF genes because individuals in such populations carry extensive runs of homozygosity, which we show are enriched for novel, rare HLOF variants. Further, we make use of extensive phenotypic data to show that most HLOFs, ascertained in population-based samples, appear to have little detectable effect on the phenotype. On the contrary, we document several genes directly implicated in disease that seem to tolerate HLOF variants. Overall HLOF genes are enriched for olfactory receptor function and are expressed in testes more often than expected, consistent with reduced purifying selection and incipient pseudogenisation.

Study EGAS00001001606

scRNA-seq data of human nuclei collected from the temporal cortex of 17 individuals.

Transcriptome analysis of single cells has tremendously increased our understanding of cellular heterogeneity in complex tissues. However, whole-cell transcriptomics cannot be applied to frozen tissue due to poor cell recovery after freezing. Human tissue is usually limited to tissue banks containing frozen material, and since single nuclei can be readily isolated from frozen tissues, human cell nuclei can substitute whole-cell analysis to extract single cell transcriptomes from human cells. Despite the importance of human tissue analysis, single-nucleus RNA-sequencing protocols are less developed than those for whole cells. SMARTSeq, either in form of custom-made SMARTSeq2 or as part of the Fluidigm C1 platform, provides a high resolution view of the transcriptome, has proven effective for whole-cell analysis and has recently been adapted to nuclei. Here, we show that the standard SMARTSeq2 protocol applied to single nuclei biases the amplification of single-nucleus transcriptomes due to unspecific capturing of transcripts, which can comprise the majority of reads in single-nucleus RNA-sequencing libraries. We demonstrate that modification of the SMARTSeq2 protocol with respect to template switching and cDNA amplification conditions generates sequencing libraries of higher complexity, allows for detection of more genes and reduces biases of the amplified transcriptome. In addition, modification of SMARTSeq2 chemistry allows for gene detection at shallower sequencing depth, thus increasing efficiency and decreasing cost.

Study EGAS00001002882

Uncovering tumor intrinsic and extrinsic factors that regulate hepatocellular carcinoma growth using patient derived xenograft assays

Several major factors limit our understanding of hepatocellular carcinoma (HCC). First, human HCCs are infrequently biopsied for diagnosis and thus are not often biologically interrogated. Second, HCC initiation and progression are strongly influenced by the cirrhotic microenvironment, and the exact contributions of intrinsic and extrinsic tumor factors are unclear. A powerful approach to examine the personalized biology of liver cancers and the influence of host tissues is with patient derived xenograft (PDX) models. In Asia, HCCs from hepatitis B virus patients have been efficiently converted into PDXs, but few parallel efforts from the west have been reported. In a large-scale analysis, we implanted 93 HCCs and 8 cholangiocarcinomas (CCAs) to systematically analyze host factors and to define an optimized platform for PDX development from both surgical and biopsy samples. NSG mice that had undergone partial hepatectomy (PHx) represented the best combination of engraftability, growth, and passageability, but overall rates were low and indicative of a unique intrinsic biology for HCCs in the US. PDX models preserved the histology and genetic features of parental tumors, and ultimately, 9 new models were usable for pre-clinical studies. Intriguingly, HCC PDXs were differentially sensitive to regorafenib and sorafenib and CCA PDXs were also highly sensitive to regorafenib. PDX models functionalize early and advanced stage HCCs and revealed unique biological features of liver cancers from the US.

Study EGAS00001004020

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