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• Precision Diagnosis of Neurodevelopmental Disorders in Middle Eastern Populations

  We constructed de novo genome assemblies for six family trios from diverse Middle Eastern ancestries (Sudan, Jordan, Syria, Qatar, and Afghanistan), involving probands with various unresolved neurodevelopmental conditions. We generated high-quality, nearly complete genome assemblies for trios, revealing extended novel sequence impacting known genes, novel HLA/KIR alleles, and strong signals of inbreeding, with runs of homozygosity covering large parts of individual chromosomes. We also identified potential disease variants underlying the unresolved symptoms. Also, the assemblies uncovered unique variation relative to existing references, showing enhanced mapping and variant calling of Middle Eastern genomes. The dataset available through dbGaP includes raw short (Illumina) and long (PacBio) sequencing reads and assembled haplotypes.

  Study phs003917

• Identification of novel fusion genes in lung cancer using breakpoint assembly of transcriptome sequencing data

  Genomic translocation events frequently underlie cancer development through generation of gene fusions with oncogenic properties. Identification of such fusion transcripts by transcriptome sequencing might help to discover new potential therapeutic targets. We developed TRUP (Tumor-specimen suited RNA-seq Unified Pipeline (https://github.com/ruping/TRUP), a computational approach that combines split-read and read-pair analysis with de-novo assembly for the identification of chimeric transcripts in cancer specimens. We apply TRUP to RNA-seq data of different tumor types, and find it to be more sensitive than alternative tools in detecting chimeric transcripts, such as secondaryrearrangements in EML4-ALK-positive lung tumors, or recurrent inactivating rearrangements affecting RASSF8.

  Study EGAS00001000659

• Targeted de novo phasing and long-range assembly by template mutagenesis

  Long-range sequencing with low error rate has been challenging. Sequence assembly and phasing usually require a high-quality reference genome for mapping, so working on highly-variable genomic regions or regions with no reference genome information would be difficult. In this study, we describe novel bench protocols and algorithms to obtain ultra-low-error-rate haplotype-phased sequence assemblies of regions 10 KB in length using a short-read sequencing platform that simultaneously solves the above two problems. We accomplish this by imprinting each template strand from a target region with a dense and unique mutation pattern. The mutation process randomly and independently converts ~50% of cytosines to uracils. Short-read sequencing libraries are made from both mutated and unmutated templates. A conservative de Bruijn graph approach seeds an assembly of the mutated templates, which we then extend by mapping paired-end reads. We next partition the template assemblies into two or more haplotypes after using the unmutated sequence library to recover almost all of the mutated bases. The final haplotype is assembled and corrected for residual template mutations and PCR errors. We obtain per-base-error rates below 10 9. We apply this method to a human family, correctly assembling and phasing three genomic intervals, including the highly polymorphic HLA-B gene.

  Dataset EGAD00001008444

• WES analysis of DMD-ASD, DMD-ID and DMD-Control individuals for de novo and rare risk variants analysis

  This project generated a whole-exome sequencing (WES) dataset of 83 boys with a pathogenic variant in the DMD gene, along with WES data from the parents of 38 of them, totaling 159 samples. In addition to DMD, 12 boys also had ID (12 DMD-ID samples), 36 boys had ASD (DMD-ASD samples) and 35 did not present ID or ASD diagnosis (DMD-Control samples).

  Dataset EGAD50000001113

• Targeted sequencing data of regulatory regions in 200 Spanish ASD trios

  This dataset consists of genomic sequencing data obtained through targeted sequencing of regulatory regions ( 85,394 human cCREs from ENCODE v2, version 2, https://screenv2.wenglab.org/) in 200 ASD (Autism Spectrum Disorder) trios (father and mother unaffected and proband affected)(600 samples total). Sequencing was carried out at the Centre for Genomic Regulation (CRG), Barcelona, Spain. Uploaded files are .vcf (600 samples). The goals of our study were to detect de novo and inherited variants in ASD probands. Sequencing data were obtained in an Illumina NovaSeq6000 instrument.

  Dac EGAC50000000695

• Merged analysis-ready bam files: HiSeq sequencing of matched tumour/normal DNA samples from Pancreatic Ductal Adenocarcinoma cases

  Additional sequencing data for 173 donors in EGAS00001000154, a study of Pancreatic Ductal Adenocarcinoma. WGS libraries were used for high-cellularity cases, WXS sequencing to high depth on low-cellularity cases. HiSeq 2xxx platform was used in all cases. The analysis files associated with this dataset are merged, de-duplicated bams aligned against GRCh37, one tumour and one normal bam per donor.

  Dataset EGAD00001002192

• Chromatin accessibility analysis of hepatocyte-like cell in vitro differentiation from iPSC in comparison to primary human hepatocytes

  Fastq files of ATAC-seq data of induced pluripotent stem cells (iPSC), definitive endoderm (DE), hepatocyte-like cells (HLC) and primary human hepatocytes (PHH). The dataset comprises data from two different in vitro differentiation protocols: Cellartis (Takara Bio, "CEL", n = 4) and as described by Wang et al. (PMID: 28287600, "HAY", n = 1), as well as from 3 PHH donors.

  Dataset EGAD00001005934

• mRNA-seq of in vitro differentiation from induced pluripotent stem cells to hepatocyte-like cells

  Fastq files of mRNA-seq data of induced pluripotent stem cells (iPSC), definitive endoderm (DE) and hepatocyte-like cells (HLC). The dataset comprises data from the in vitro differentiation protocol Cellartis (Takara Bio, "CEL", n = 4) and several interventions (11x3 replicates).

  Dataset EGAD00001005935

• The Role of Germline Mutation and Parental Age in Autism Spectrum Disorders

  <p>We will apply whole genome sequencing of trio families to determine how patterns of germline mutation throughout the genome determine risk for Autism Spectrum Disorder (ASD). We will investigate the nature intrinsic hypermutability and the extrinsic forces, such as paternal age, that influence rates of germline mutation. We will accomplish these goals through the following specific aims: Specific Aim 1 will characterize germline de novo mutations (DNMs) by whole genome sequencing in families. These studies will identify and validate ~8,000 de novo point mutations and structural variants in trios and controls to determine the parent of origin of DNMs. Specific Aim 2 will identify hot spots for germline mutation based on the regional density of DNMs in the genome, and determine the effects of DNA sequence features on rates of mutation. We will determine the association of mutation hotspots with ASD in the discovery sample and in genomic datasets from an independent sample of 2700 cases and 2700 controls. Specific Aim 3 will characterize the effects of extrinsic factors, including parental age and environment, on genome-wide rates of mutation. We will quantify the effect of paternal age on pathogenic and neutral alleles in sperm and investigate whether some DNMs confer a germline selective advantage. The findings of this study will provide fundamental insights into the genetic basis of autism risk and the genetic mechanism of the observed parental age effects in ASD. We will identify genes that confer significant risk for autism, and we will determine how intrinsic properties of the genome interact with extrinsic forces to determining risk for disease in offspring.

  Study phs001164

• Epigenetic Profiling of Human Colorectal Cancer

  DNA methylation, together with chromatin modifications, constitute the epigenome that functions to regulate gene expression and genome integrity. DNA methylation alterations are ubiquitous in human cancers, as many genes acquire DNA methylation in a cancer-specific manner. DNA methylation at these sites in the genome of cancer cells not only serves as a marker for tumor identification, but together with gene mutation and gene expression data, can also be used to describe subsets of tumors of the same organ source. We have previously shown distinct human colorectal cancer subtypes based on DNA methylation differences. Correlating these DNA methylation differences with clinical co-variates will serve to further understand how these distinct subtypes are generated. We have collected 100 colorectal tumor tissues (for which clinical information is known) and have obtained (unprotected) genome-wide DNA methylation and chromatin modification information for each sample for the purposes of identifying and classifying unique tumor subtypes of colorectal cancers. In addition, we have determined mutations of key genes relevant to colorectal cancer as well as gene expression profiles. We will use the clinical data for each de-identified sample to correlate with the DNA methylation, mutation and gene expression information so as to understand the driving forces behind these distinct colorectal subtypes. We have selected the most promising tumors for whole-genome bisulfite sequencing using next-generation sequencing technology to obtain complete maps of colon cancer methylomes. Researchers will be unable to identify the subjects because the samples and associated information have been de-identified and anonymized by the tissue source site. In addition, upon receipt by the USC Epigenome Center, we have assigned new random identifiers for each sample. The data generated using these new codes are not traceable to the patient identity.

  Study phs000385