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• Benchmark and validation of whole exome sequencing of a trio and singleton

  Whole exome paired-end sequencing data was obtained for a trio and a fourth unrelated individual sequenced to high depth (95x) using a paired-end library with the Illumina HiSeq platform and aligned by BWA 0.5.9. The bam files were analysed and experimentally vaidated for the novel insertion of mobile elements.

  Study EGAS00001000852

• Mutation tracking in single cell RNA-Seq reveals consequences of subclonal evolution in acute myeloid leukemia

  Total bone marrow from AML patients was FACS index sorted with staining for Lineage markers (Lin), CD33, CD34, CD38, CD45RA, CD90, CD99, Tim3 and GPR56, and enrichment for Lin- and Lin-CD34+ cells. Single cells were subjected to a modified smart-seq2 protocol with targeting of mutant sites of interest ("MutaSeq”).

  Study EGAS00001003414

• Capturing disease severity in LIS1-lissencephaly reveals proteostasis dysregulation in patient-derived forebrain organoids

  Lissencephaly is a developmental cortical malformation characterized by reduced to absent gyri and a disorganized cortex, often leading to severe impairments in affected individuals and a reduced life expectancy. Heterozygous mutations in the LIS1 gene, encoding a regulator of the microtubule motor dynein, cause lissencephaly with different clinical severities. While the clinical disease spectrum correlates with the degree of lissencephaly, location and type of mutation may not. We leveraged forebrain-type organoids from LIS1-lissencephaly patients, diagnosed with mild, moderate or severe lissencephaly to investigate, in a cytoarchitecture and multi-omics approach, how the severity degree in patients might relate to specific mutations in the LIS1 gene. We questioned which processes during cortical development might be differentially affected by severity grade, and whether they could be pharmacologically targeted. We found alterations in neurodevelopment often with a severity-dependent gradient. Specifically, we identified alterations of the cytoarchitecture, progenitor cell homeostasis and neurogenesis. Particularly important disease-linked molecular mechanisms were microtubule destabilization, WNT-signaling, and perturbed cadherin- and unfolded protein-binding. Some mechanisms exhibited a severity-dependent gradient, or were specific to a severe grade. We present strategies to reverse phenotypic changes in LIS1-patient organoids, and an in silico approach with therapeutic potential. Thus, we show that different LIS1-severity grades can be recapitulated in vitro, that there is a direct link between the phenotype and genotype, that organoid-based disease modeling can identify molecular underpinnings of malformations of cortical development and that organoids provide a valid platform to develop and test therapeutic strategies.

  Study EGAS00001008227

• Gene-Environment Interactions (GxE) and Complex Traits

  Functional variants associated with complex traits tend to fall in non-coding regions and affect regulatory mechanisms that are not yet well characterized. Furthermore, it is generally difficult to determine in which tissues and conditions they may have a functional impact. This is because the effect of a genetic variant on a molecular pathway, and ultimately on the individual's phenotype, may be modulated by "environmental" factors. We denominate such variants "gene-expression environment-specific quantitative trait nucleotides" GxE-QTNs. Achieving a better understanding of the mechanisms underlying GxE is a critical step in understanding the link between genotype and complex phenotype. It is also crucial to develop computationally efficient and statistically sound methods capable to integrate tissue/condition-specific functional genomics data to predict and validate when a sequence variant is functional. In this study we developed novel experimental and computational approaches to screen, analyze and functionally characterize genetic variants for complex traits modulated by environmental exposures. To identify and characterize genes with GxE, we analyzed allele specific gene expression in a panel of five relevant tissues (e.g. the vascular endothelium for cardiovascular diseases) under 50 controlled environmental conditions (e.g. glucocorticoids treatment, as a proxy for stress exposure). These data should be useful to develop computational tools that integrate different sources of evidence including data collected by ENCODE, RoadMap Epigenome and GTEx projects to functionally annotate GWAS variants. The experimental and computational tools developed by this project have widespread applicability, for example, can be used to tackle the functional basis of complex traits in other environmental contexts (e.g. other types of stress and hormonal levels) and genetic backgrounds. This resource represents the first comprehensive catalog of genetic variants that interact with environmental exposure in determining human complex traits.

  Study phs001176

• RNA004 DRS METTL5 variant

  RNA004 is a method for direct RNA sequencing (DRS) that holds promise to enhance the detection of modopathies. To this end, we provide DRS data for a patient sample harboring heterozygous inactivating SNPs for the methyltransferase METTL5, which modifies m6A on 18S rRNA. Companion datasets are 1) EGAS50000001201 for DRS of a healthy control with intact METTL5 and 2) PRJEB74238 for IVT 18S rRNA vector data as unmodified control.

  Study EGAS50000001321

• Significant and pervasive effects of RNA degradation on Nanopore direct RNA sequencing

  Abstract Oxford Nanopore direct RNA sequencing (DRS) is capable of sequencing complete RNA molecules and accurately measuring gene and isoform expression. However, as DRS is designed to profile intact RNA, expression quantification may be more heavily dependent upon RNA integrity than alternate RNA-seq methodologies. It is currently unclear how RNA degradation impacts DRS or if it can be corrected for. To assess the impact of RNA integrity on DRS we performed a degradation time-series using SH-SY5Y neuroblastoma cells. Our results demonstrate that degradation is a significant and pervasive factor that can bias DRS measurements, including a reduction in library complexity resulting in an overrepresentation of short genes and isoforms. Degradation also biases differential expression analyses; however, we find explicit correction can almost fully recover meaningful biological signal. In addition, DRS provided less biased profiling of partially degraded samples than nanopore cDNA-PCR sequencing. Overall, we find samples with RIN > 9.5 can be treated as undegraded and samples with RIN > 7 can be utilised for DRS with appropriate correction. These results establish the suitability of DRS for a wide range of samples, including partially degraded in-vivo clinical and post-mortem samples, whilst limiting the confounding effect of degradation on expression quantification.

  Study EGAS00001006542

• DNA methylation array study for 7 pairs of primary NSCLCs and distant metastases

  This study is to compare DNA methylation profiles between primary NSCLCs and paired distant metastases.

  Study EGAS00001004079

• Whole-Exome Sequencing Study of Diabetic Nephropathy

  To identify rare variants of diabetic kidney disease (DKD), we conducted a whole-exome sequencing (WES) study. This study employed an extreme case–control design, which included a selection of the 593 most rapidly progressing DKD cases from the Chronic Renal Insufficiency Cohort (CRIC) Study (phs000524). In this two-stage WES study of DKD, participants with DKD from the CRIC were compared with control groups of participants without DKD from another cohort in the first stage. Suggestive signals identified in the first stage were confirmed in the second stage analysis among a diverse population with existing whole-genome sequencing (WGS) data. Generalized linear mixed models, which accounted for genetic relatedness and adjusted for age, sex and ancestry, were used to test associations between single variants and DKD. Gene-based aggregate rare variant analyses were conducted using an optimized sequence kernel association test implemented within our mixed model framework. As a result, we identified four novel gene loci, DIS3L2, KRT6B, ERAP2 and NPEPPS, that achieved exome-wide significance and may play an important role in the DKD disease course. This large WES study provides novel insights into DKD's molecular mechanisms.

  Study phs003429

• SC_DDD-G-3

  Unfiltered genotype data for DDD Study trios (patient and parents) (N=2,166 samples), some of which were used for replication of neurodevelopmental disorder polygenic risk (Niemi et al., Nature 2018). Samples were genotyped on the Illumina HumanOmniExpress BeadChip

  Dataset EGAD00010001602

• Whole Exome Sequencing of Parathyroid Cancer Identifies Candidate Driver Mutations and Core Pathways

  Here we performed genomic characterization of twenty-nine sporadic parathyroid cancers using next generation whole exome sequencing. Thirty-three novel candidate driver genes for sporadic parathyroid cancer were proposed, in addition to previously known driver genes CDC73 and MEN1.

  Study phs001765