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• Emirati Genome Project subset of 43,608 WGS samples for population-scale variant discovery and allele frequency mapping.

  Here, we present a comprehensive genomic characterization of a cohort of 43,608 Emirati genomes sequenced as part of the Emirati Genome Program (EGP). This study identified more than 421 million single nucleotide variants and indels and more than 600 million copy number- and structural variants. Small variants had 756 million molecular effects annotated. Of the identified variants, 69.04% were observed with more than one allele. Of 7.7 million polymorphic variants having an allele frequency (AF) of more than 5% in EGP, 1,348 have a predicted deleterious effect on a protein. Characterization of global variation reveals that EGP represents a genetic continuum encompassing the range of African, Asian, and European populations. It is best described by two Arabian, an Eurasian, and an African component, with the predominant Arabian component linked to mitochondrial haplogroups J and T, which are commonly attributed to the Middle East. Various aneuploidies of sex chromosomes were detected in 93 individuals overall and of chromosome 21 in 41 individuals. The median inbreeding coefficient and cumulative runs of homozygosity (ROHs) lengths were increased due to extensive consanguinity, being largest in the groups with Arabian main ancestry components and higher than reported for Qatar. Families were identified based on genetic relatedness and classified into 264 families with unrelated parents and 247 families with third- and fourth-degree consanguineous parents. Representative consanguineous pedigrees of families in EGP were outlined. Cumulative ROHs were affected by the main ancestry component and significantly increased in offspring of consanguineous parents, with a pronounced difference between 3rd and 4th-degree relatedness. Investigation of cumulative AFs of variants causing Mendelian diseases highlighted genes related to alpha- and beta-thalassemia (HBB, HBA2). It showed a high burden of variants causing severe recessive diseases, metabolic and retinal disorders, and hearing loss. In summary, EGP represents a landmark effort in characterizing the genetic diversity of the Emirati population, leveraging the largest Middle Eastern cohort reported to date.

  Study EGAS50000001071

• UK10K COHORT ALSPAC

  The UK10K project proposes 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 directly analyse 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 Avon Longitudinal Study of Parents and Children (ALSPAC) is a two-generation prospective study. Pregnant women living in one of three health districts in the former county of Avon with an expected delivery date between April 1991 and December 1992 were eligible to be enrolled in the study, and this formed the initial point of contact for the development of a large, family based resource. Information has been collected on the children and the mothers through retrieval of biological materials (e.g. antenatal blood samples, placentas), biological sampling (e.g. collection of cord blood, umbilical cord, milk teeth, hair, toenails, blood and urine), self-administered questionnaires, data extraction from medical notes, linkage to routine information systems and at repeat research clinics.

  Study EGAS00001000090

• H3Africa - Genomic and Environmental Risk Factors for Cardiometabolic Disease in Africans

  The long-term vision of the AWI-Gen Collaborative Centre (CC) is to build sustainable capacity in Africa for research that leads to an understanding of the interplay between genetic, epigenetic and environmental risk factors for obesity and related cardiometabolic diseases (CMD) in sub-Saharan Africa. The CC will be consolidated under the auspices of the University of the Witwatersrand (Wits) and the International Network for the Demographic Evaluation of Populations and Their Health in Developing Countries (INDEPTH). It will capitalize on the unique strengths of existing longitudinal cohorts, including the urban Soweto and rural Agincourt studies in South Africa (Wits based), and the well established INDEPTH demographic health and surveillance centers in Kenya, Ghana, Burkina Faso and South Africa. The centers offer established infrastructure, trained fieldworkers, long-standing community engagement, and detailed longitudinal phenotypic data, focusing on obesity and cardiometabolic health. Key strengths are harmonized phenotyping across sites, building on strong existing cohorts, and representation of the geographic and social variability of African populations. We aim to: 1. Build sustainable infrastructure (biobanks and laboratories) and capabilities (well characterized population cohorts, genotyping and bioinformatics) for genomic research on the African continent; 2. Understand the genomic architecture of sub-Saharan populations from west, east and south Africa to guide genomic studies (genome sequencing and high throughput SNP and CNV arrays using unrelated individuals and family trios to improve the accuracy of haplotype analyses) and; 3. Investigate the independent and synergistic genomic contributions to body fat distribution (BMI, hip/waist circumference, subcutaneous and visceral fat) in these populations considering the relevant environmental and social contexts (rural/urban communities, quickly transitioning obesity prevalence, differential HIV, TB, and malaria infection histories). We will investigate the effect of obesity and fat distribution on the risk for CMD in the longitudinal cohorts.

  Study EGAS00001002482

• UK10K_NEURO_ASD_FI

  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.These samples are a subset of a nationwide collection of Finnish autism spectrum disorder (ASD) samples. The samples have been collected from Central Hospitals across Finland in collaboration with the University of Helsinki. The samples consist of 93 individuals with a diagnosis of autistic disorder or Asperger syndrome from 36 families with at least two affected individuals. Of these individuals, 16 can be genealogically connected to form two large pedigrees originating from Central Finland, suggesting possible genetic risk factors shared identical by descent within the pedigrees. All diagnoses are based on ICD-10 and DSM-IV diagnostic criteria for ASDs. Additional phenotypic data is available for a subset of the individuals.For further information with regard to this cohort please contact Aarno Palotie (Aarno.palotie@helsinki.fi).

  Study EGAS00001000110

• Genomic Profiling of Pediatric Tumors by Cell Free DNA Sequencing

  BACKGROUND Analysis of cell-free DNA (cfDNA) from peripheral blood has been studied extensively for detection and monitoring therapy response in adult cancers, but utility in pediatric tumors is unclear. METHODS We studied 233 children with hematologic, solid and brain tumors. cfDNA was extracted from 1 mL of plasma collected at diagnosis. Circulating tumor DNA (ctDNA) in cfDNA was quantified and diverse classes of somatic genomic variants were detected using PeCan-Seq. PeCan-Seq findings were compared with matched tumor whole-genome and whole-exome sequencing data. Minimal residual disease (MRD) status was evaluated by cfDNA PeCan-Seq in 14 patients with B-cell acute lymphoblastic leukemia. RESULTS Plasma cfDNA yields at diagnosis were higher for hematologic malignancies than for solid and brain tumors. Patients with hematologic malignancy were 100% ctDNA-positive, the median ctDNA fraction in cfDNA was 0.77. We detected 97% variants that were present in tumors and covered by the capture panel, and 50 subclonal variants that were present in cfDNA only. Our approach enabled detection of sequence and structural variants in B-ALL ctDNA at varying levels of MRD. Nineteen of 38 patients with solid tumors were ctDNA-positive, with high prevalence in Ewing Sarcoma, liver tumors and osteosarcoma. One of 19 brain tumor patients was ct-DNA positive, indicating lack of utility for plasma-derived cfDNA in this disease. Notably, cfDNA analysis of a single plasma sample identified genomic features in ctDNA derived from B-ALL, concurrent primary neuroblastoma, and a later neuroblastoma relapse, indicating that genomic variations from multiple tumors could be detected simultaneously. CONCLUSIONS Pediatric patients with hematologic malignancy had an abundance of plasma ctDNA at diagnosis. Plasma ctDNA levels varied between different solid tumor types, more studies are needed to determine utility. Panel-based cfDNA sequencing could serve as a non-invasive approach for pediatric cancer diagnosis and disease monitoring.

  Study EGAS50000000072

• Intra-tumor heterogeneity of localized lung adenocarcinomas defined by multi-region sequencing

  Background: Intra-tumor heterogeneity (ITH) may have profound impacts on biopsy strategy, characterization of actionable targets, treatment planning, and drug resistance. ITH of lung cancers has not been well studied. Methods: We performed multi-region whole exome sequencing (average sequencing depth 277x) on 48 tumor regions from 11 resected lung adenocarcinomas (8 stage I, 2 stage II and one stage III tumors) followed by deep sequencing validation (average sequencing depth 863x). Results: All tumors showed clear evidence of spatial ITH. On average, 76% of all mutations and 20/21 known cancer gene mutations were present in all regions of individual tumors (trunk mutations). Copy number analysis did not show substantial difference in large-scale chromosome aberrations. A canonical KRAS p.G12C mutation was detected in only 1 of 4 tumor regions (branch mutations) at exome depth but detected in all four tumor regions (trunk mutations) at increased sequencing depth. In addition, many heterogeneous branch mutations defined by exome sequencing were detectable in all regions of individual tumors with increasing sequencing depth. Significant differences in mutational spectrum were observed in 6 tumors indicating that specific mutational processes were likely operative at different times during development of these tumors. With a median follow up of 21 months post surgery, 3 patients have relapsed and all 3 patients presented with significantly larger fractions of subclonal mutations in their primary tumors. Conclusions: Although multi-region sampling is still required to fully assess ITH complexity, single biopsy analysis at appropriate depth might be sufficient to identify the majority of known cancer gene mutations in localized lung adenocarcinomas. Larger subclonal mutation fractions may be associated with increased likelihood of postsurgical relapse in patients with localized lung adenocarcinomas. Studies on larger cohort, ideally with comprehensive clinical annotation and repeat biopsy at relapse are needed to fully understand the clinical impact of ITH.

  Study EGAS00001000930

• Whole exome sequencing of germline DNA was performed and subsequent polymorphisms in genes known and putatively involved in the innate immune response to fungi were identified

  Disease can be conceptualized as the result of interactions between infecting microbe and holobiont, the combination of a host and its microbial communities. It is likely that genomic variation in the host, infecting microbe, and commensal microbiota are key determinants of infectious disease clinical outcomes. However, until recently, simultaneous, multiomic investigation of infecting microbe and holobiont components has rarely been explored. Herein, we characterized the infecting microbe, host, micro- and mycobiomes leading up to infection onset in a leukemia patient that developed invasive mucormycosis. We discovered that the patient was infected with a strain of the recently described Mucor velutinosus species which we determined was hypervirulent in a Drosophila challenge model and has a predisposition for skin dissemination. After completing the infecting M. velutinosus genome and genomes from four other Mucor species, comparative pathogenomics was performed and assisted in identifying 66 M. velutinosus-specific putatively secreted proteins, including multiple novel secreted aspartyl proteinases which may contribute to the unique clinical presentation of skin dissemination. Whole exome sequencing of the patient revealed multiple non-synonymous polymorphisms in genes critical to control of fungal proliferation, such as TLR6 and PTX3. Moreover, the patient had a non-synonymous polymorphism in the NOD2 gene and a missense mutation in FUT2, which have been linked to microbial dysbiosis and microbiome diversity maintenance during physiologic stress, respectively. In concert with host genetic polymorphism data, the micro- and mycobiome analyses revealed that the infection developed amid a dysbiotic microbiome with low α-diversity, dominated by staphylococci. Additionally, longitudinal mycobiome data showed that M. velutinosus DNA was detectable in oral samples preceding disease onset. Our genome-level study of the host-infecting microbe-commensal triad extends the concept of personalized genomic medicine to the holobiont-infecting microbe interface thereby offering novel opportunities for using synergistic genetic methods to increase understanding of infectious diseases pathogenesis and clinical outcomes.

  Study EGAS00001001542

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• 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

• Deep single-cell RNA sequencing data for 11138 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naive CRC patients. The DATA ACCESS AGREEMENT is provided at https://github.com/zhangyybio/single-T-cell-data-access. Applicants can request access to the data by directly downloading it or by sending an email to cancerpku@pku.edu.cn. The process that is used to approve an application includes verifying the institution, participants and research purposes of the application. In general this process will take about two weeks. In principal, any scientific research program complying with the laws and bioethic regulation policies of China will be approved.

  T cells are central players in cancer immunotherapy1, yet some of their fundamental properties such as development and migration within tumours remain elusive. The enormous T cell receptor (TCR) repertoire, required for recognising foreign and self-antigens2,3, could serve as lineage tags to track these T cells in tumours4. Here, we obtained transcriptomes of 11,138 single T cells from 12 colorectal cancer (CRC) patients and developed STARTRAC (Single T-cell Analysis by Rna-seq and Tcr TRACking) indices to quantitatively analyse dynamic relationships among 20 identified T cell subsets with distinct functions and clonalities. While both CD8+ effector and “exhausted” T cells exhibited high clonal expansion, they were independently connected with tumour-resident CD8+ effector memory cells, implicating a TCR-based fate decision. Of the CD4+ T cells, the majority of tumour-infiltrating Tregs showed clonal exclusivity, whereas certain Treg clones were developmentally linked to multiple TH clones. Notably, we identified two IFNG+ TH1-like clusters in tumours, the GZMK+ TEM and CXCL13+ TH1-like clusters, which were associated with distinct IFN-γ-regulating transcription factors, EOMES/RUNX3 and BHLHE40, respectively. Only CXCL13+BHLHE40+ TH1-like cells were preferentially enriched in tumours of microsatellite-instable (MSI) patients, which might explain their favourable response rates to immune-checkpoint blockade. Furthermore, we found IGFLR1 to be highly expressed in both CXCL13+BHLHE40+ TH1-like and CD8+ exhausted T cells and possessed co-stimulatory functions. Our integrated STARTRAC analyses provides a powerful avenue to comprehensively dissect the T cell properties in CRC, which could shed new insights into the dynamic relationships of T cells in other cancers

  Study EGAS00001002791